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Electronic copy available at: http://ssrn.com/abstract=1009309 1 Do concentrated institutional investors really reduce executive compensation whilst raising incentives? * Gavin S. Smith and Peter L. Swan Current Draft: February 2, 2012 Abstract Hartzell and Starks (2003) (HS) report that more concentrated institutional investing associates with higher pay-for-performance sensitivity and lower CEO pay. We find that institutional concentration has no effect on pay-for-performance sensitivity and increases compensation when we replicate their analysis using the logarithm of firm size instead of HSraw firm size as control. Moreover, HS results are sensitive to measuring concentration among institutions rather than concentration among shareholders. Finally, the HS concentration definition also appears to exacerbate firm-size effects. Overall, HS results may be primarily due to what appear to be weak firm-size controls and not due to institutional monitoring. JEL classification: G23, G32, J33 Keywords: Executive compensation, Monitoring, Institutional ownership, Principal- agent, Incentives, Concentrated ownership. * The authors are grateful to the Australian Research Council (DP0346064) for research funding. We also thank the organizers of the First Singapore International Conference on Finance, namely the Saw Centre for Financial Studies and Department of Finance and Accounting, NUS Business School, National University, for their financial support. We wish to thank Reneé Adams, Rajesh Aggaral, Philip Brown, Sudipo Dasgupta, Alex Edmans, Joseph Fan, David Feldman, David Gallagher, Gerald Garvey, Jay Hartzell, Petko Kalev, Ron Masulis, Sir James Mirrlees, Peter Pham, Jay Ritter, Laura Starks, Jaeyoung Sung, David Yermack, and seminar participants at the Chinese University of Hong Kong and University of Illinois, Chicago, First Singapore International Conference on Finance, the European Finance Association (EFA) Conference, 2007, and the 20 th Australasian Finance and Banking Conference participants for useful comments. We are also particularly grateful to Jay Hartzell and Laura Starks for supplying us with their original dataset. Barclays Capital, 745 Seventh Avenue, New York, NY 10019; [email protected]; Tel: (+1) 212 526 4217. Corresponding author. School of Banking and Finance, University of New South Wales, Sydney 2052, Australia; [email protected]; Phone: (+61) (0)2 9385 5871.
35

Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

Mar 30, 2023

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Page 1: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

Electronic copy available at httpssrncomabstract=1009309

1

Do concentrated institutional investors really reduce executive

compensation whilst raising incentives

Gavin S Smith

dagger and Peter L Swan

Dagger

Current Draft February 2 2012

Abstract

Hartzell and Starks (2003) (HS) report that more concentrated institutional investing

associates with higher pay-for-performance sensitivity and lower CEO pay We find

that institutional concentration has no effect on pay-for-performance sensitivity and

increases compensation when we replicate their analysis using the logarithm of firm

size instead of HSrsquo raw firm size as control Moreover HS results are sensitive to

measuring concentration among institutions rather than concentration among

shareholders Finally the HS concentration definition also appears to exacerbate

firm-size effects Overall HS results may be primarily due to what appear to be weak

firm-size controls and not due to institutional monitoring

JEL classification G23 G32 J33

Keywords Executive compensation Monitoring Institutional ownership Principal-

agent Incentives Concentrated ownership

The authors are grateful to the Australian Research Council (DP0346064) for research funding We

also thank the organizers of the First Singapore International Conference on Finance namely the Saw

Centre for Financial Studies and Department of Finance and Accounting NUS Business School

National University for their financial support We wish to thank Reneeacute Adams Rajesh Aggaral

Philip Brown Sudipo Dasgupta Alex Edmans Joseph Fan David Feldman David Gallagher Gerald

Garvey Jay Hartzell Petko Kalev Ron Masulis Sir James Mirrlees Peter Pham Jay Ritter Laura

Starks Jaeyoung Sung David Yermack and seminar participants at the Chinese University of Hong

Kong and University of Illinois Chicago First Singapore International Conference on Finance the

European Finance Association (EFA) Conference 2007 and the 20th

Australasian Finance and

Banking Conference participants for useful comments We are also particularly grateful to Jay Hartzell

and Laura Starks for supplying us with their original dataset daggerBarclays Capital 745 Seventh Avenue New York NY 10019 gavinsmithbarclayscapitalcom

Tel (+1) 212 526 4217 DaggerCorresponding author School of Banking and Finance University of New South Wales Sydney 2052

Australia peterswanunsweduau Phone (+61) (0)2 9385 5871

Electronic copy available at httpssrncomabstract=1009309

2

With 128 cites in Web of Science and 757 cites in Google Scholar Hartzell and Starks

(2003) [hereafter HS] ranks among the most influential corporate finance papers of the

last decade HS find that concentrated institutional monitors provide greater incentives for

executives to perform by granting more options while simultaneously lowering their cash-

based pay with an even greater fall in total direct compensation HS (p2355) define

concentrated institutional holdings [hereafter Top 5 Concentration] by the proportion of

institutional ownership accounted for by the top five institutional investors12

By

contrast our paper argues that several methodological issues in HS alter their finding by

showing that concentration has either no effect on incentives or perhaps reduces them

and in the case of salary and total pay levels reverse their findings Our paper discusses

these issues and then empirically demonstrates the effect that they have on the findings of

HS

HSrsquos findings are supportive of the idea that firms overpay executives as the

skimming or rent-seeking view of executive compensation maintains See for example

Bertrand and Mullainathan (2001) Bebchuk Fried and Walker (2002) Bebchuk and

Fried (2003 2004) Chhaochharia and Grinstein (2009) and Morse Nanda and Seru

(2011) Chhaochharia and Grinstein (2009) find that increased board requirements

reduced CEO pay but note the fragility qualification provided by Guthrie Sokolowsky

and Wan (2012) and Morse Nanda and Seru (2011) find that powerful CEOs rig

performance measures to increase their pay and that these firms then underperform

1 More specifically HS (p2352) find that an increase of one standard deviation in Top 5 institutional

investor concentration is associated with a 20 percent increase in option grant pay-for-performance

sensitivity and a 19 percent drop in total compensation for the average executive

2 HS also obtain similar findings using a Herfindahl index of institutional fractional holdings that they

construct in a very similar fashion to their main concentration measure Our findings for their concentration

measure will also tend to be true of their Herfindahl measure

Electronic copy available at httpssrncomabstract=1009309

3

We find that Institutional Top 5 Concentration according to the HS definition does

not raise option grant pay-for-performance sensitivity as it has no statistically significant

impact either way once one introduces a standard logarithmically transformed size

control Similarly lagged Institutional Concentration has a negative but statistically

insignificant effect on the pay-for-performance sensitivity of cash (salary plus bonus)

compensation when interacted with the lagged change in shareholder wealth HS obtain a

significant positive coefficient using the contemporaneous change in shareholder wealth

but one need replace this by the lagged change in shareholder wealth in keeping with

what influential institutional investors knew at the time Additionally HS find that lagged

concentrated institutional ownership sizably lowers both salary and total direct

compensation and this is statistically significant but we find the reverse ‒ it appears to

raise both and the findings are highly statistically significant also following a standard

logarithmically transformed size control

Upon closer examination several aspects of the HS research design are of interest

First the primary argument in our paper is that the use by HS of the lagged value of the

level of market capitalization as the size control in regressions (HS p2359) rather than

the conventional lagged logarithm of capitalization distorts the coefficient on the

measure of institutional influence3 A number of authors have drawn attention to falling

pay-for-performance sensitivities as firm size increases (eg Jensen and Murphy (1990)

Garen (1994) Hadlock and Lumer (1997) Schaefer (1998) Murphy (1999) Jin (2002)

and Chichello (2005)) and hence the need to have effective size controls In the HS

dataset the raw mean market capitalization ranges from $1181m in decile 1 to $36654m

in decile 10 (see Table III below) a difference of 3104 fold reducing to only 22 with the

3 HS (p2357) also use net assets and total assets as controls but in keeping with the use of raw

capitalization retain them in their raw form

4

logarithmic transformation While this skewed nature of the level of market capitalization

does not per se rule out its use specification tests such as Box-Cox and the replacement

of market capitalization by its cumulative distribution (see Section VI below) indicates a

possible specification error Moreover using the lagged natural logarithm of market

capitalization as a firm size control in the actual HS data with the same dependent

variable and no other changes raises the explanatory power (R-Squared) of the HS model

by between 135 and 1516 percent4

Given that firm size is an important determinant of executive compensation selecting

the correct functional form for firm size is a vexing and important issue Many estimates

including those of Murphy (1985) Rosen (1992) Gibbons and Murphy (1992) Huson

Parrino and Starks (2001) Baker and Hall (2004) Gabaix and Landier (2008) Edmans

Gabaix and Landier (2009) Babenko (2009) and Aggarwal Erel and Ferreira (2011)

use a logarithmic specification with the elasticity between firm size and executive total

pay in the range of 03 and 04 HS seems to employ inadvertently a firm size measure in

levels (also alternative firm size measures also in levels) and consequently imply an

elasticity value (exponent on market capitalization) of unity

Second we question the use of the HS Top 5 Concentration measure of institutional

influence based on the influence of concentrated institutional investors relative to their

peers that appears to lead inadvertently to an exacerbation of the size-control problem In

their companion theoretical model AHS arrive at a different and what might seem a more

natural specification namely Top 5 Ownership which measures concentration relative to

all shareholders not just institutional peers The following example illustrates the

4 The lower result is based on OLS regressions of model 1 of Table II of HS with the R-Squared rising from

00853 to 00968 once Market Capitalization is logged and the higher result model 1 of Table V of HS is

based on an improvement in R-Squared from 04604 to 05302 (see Table VI below)

5

differences between these two methods If there are one hundred shares outstanding in a

small company and the only institution owns one share that company is concentrated

according even though that institution may lack effective monitoring power Instead if

one deflates by shares on issue this results in a concentration ratio of 1100 If on the

other hand ten institutions collectively own 500 shares in a much larger company of

1000 shares and the Top Five collectively own 250 then the HS concentration ratio falls

to only 250500 or 05 and utilizing shares on issue 025 in this case As is confirmed by

the data one expects Top 5 Concentration to correlate negatively with firm size and Top

5 Ownership the reverse given a positive association between institutional ownership and

company size We then re-examine the monitoring hypothesis using this AHS proposed

measure of institutional investor influence that intuitively relates better to institutional

proxy voting power

Third we address issues of reliance on potentially biased self-reported values of option

grants that result in the exclusion of 16 percent of the HS sample size for tests on total

(direct) compensation Forth we argue that tests that HS perform using an alternative

measure of pay-for-performance sensitivity to provide support for the main hypothesis of

the study require one to get the timing right in terms of the lag structure of performance

and concentration Finally we address issues associated with their tests of endogeneity

and reverse causality These issues collectively might suggest overlooking of a

monitoring effect with the main driving forces size related

The next section reviews the HS study in an effort to tease out what might really be

going on Section II examines the literature for studies that in replicating HS provide

independent support for their findings It also reports findings on the actual proxy voting

record of mutual funds and actions of institutional investors in reducing pay Section III

describes the data and methodology Section IV analyzes the relation between

6

institutional influence and measures of pay-for-performance sensitivity Section V

documents the relationship between institutional influence and total and fixed

compensation Section VI examines the robustness of our findings and the final Section

concludes

I Review of Hartzell and Starks Methodology

We comment on five areas of the HS methodology 1) Size control 2) Measurement of

institutional influence 3) Testing the Jensen-Murphy measure of incentives 4) Reliance

on incomplete self-reported valued for option grants and 5) Endogeneity

A Size Control

In our paper we argue that HS unintentionally identify incentive-size and pay-size

effects5 not a monitoring effect It can be seen in Figure II that executive total pay for

HSrsquos Top 5 institutional concentration measure rises from as little as $072m for the

smallest market capitalization decile to $85m for the highest This twelve-fold pay-size

effect in the deciles can cause problems if one utilizes an untransformed size measure

Due to skewness in the size measure using this in its untransformed state appears to

weaken its effectiveness leaving open the possibility that correlations they identify

between incentives and pay levels on the one hand and Top 5 Concentration on the other

are due largely to size-related effects

Table III displays this strong pay-size effect based on our full 1992‒2002 dataset and

graphically in Figure 1 It shows that the incentive measure adopted by HS declines from

$272 per $1000 change in shareholder wealth for the smallest market capitalization

decile of firms to approximately $030 for the largest Table III and Figure 1 show the

5 The multiplicative model of Edmans Gabaix and Landier (2009) finds that incentive pay increases with

firm size (elasticity value of 13) and the empirical elasticity is 037

7

strong relation between institutional concentration as measured by HS and market

capitalization For the smallest decile of market capitalization firms institutional

concentration averages 61 percent declining to about 275 percent for the highest decile

This negative relationship between firm size and institutional concentration seems to arise

because institutional investors do generally favor small firms This causes problems

because in the limit a small company may have only one institutional investor owning

only a small percentage of the company Hence it would appear to be fully concentrated

even though the ability of the institutional investor to influence pay decisions might be

small Thus it is not at all surprising that the correlation between the logarithm of market

capitalization and their institutional concentration measure is both negative and high in

absolute value at 63 percent Their methodology appears to favor small companies that

Table III shows to have low pay levels and high pay for performance sensitivity

Moreover if one does not transform the raw size measure it implicitly assumes that a

given dollar change in firm size has the same absolute impact on pay for a very large

company as it does for a small company Indeed the conventional logarithmic

specification for firm size provides proportionate effects that imply a pay-size elasticity of

approximately one-third instead of unity6

B Measurement of Institutional Influence

We argue that there are additional issues related to the HS measure of institutional

influence ndash institutional concentration In their companion article to HS AHS develop a

model where they capture institutional influence by a single large long-term institutional

6 Note that unlike an earlier version of our paper we leave the HS dependent variables in levels and hence

untransformed While we do this to minimize the alterations that we make to the HS specification ideally

the elasticity specification is preferable especially for the compensation variables Transforming the

dependent variables does not significantly affect the results

8

investor They measure influence relative to total shareholding including private or

atomistic shareholders Presumably they do this to capture relative activism and proxy

voting strength However when it comes to the empirical implementation of the model

AHS adopt the same relative institutional concentration measure as in HS (AHS (p12))

potentially downplaying the relative strength of institutions compared with other

shareholders They justify this because there is generally more than one institutional

investor and there will be free-riding problems with multiple investors that only the

largest institutional investors can overcome While we accept their premise of free-rider

problems it is not obvious why the deflator is lsquoinstitutional shareholdingrsquo rather than

lsquototal shareholdingrsquo from this perspective7 If the strength of the size control can be

queried scaling by total shareholding (ie Top 5 Ownership) produces a measure that

remains relatively unaffected across the size deciles It is 20 percent for the smaller

decile declining to 14 percent for the largest decile whereas for the HS concentration

measure it declines by over 50 percent from 61 percent to 28 percent (see Table III and

Figure 1)

C Testing the Jensen-Murphy Measure of Incentives

The testing of their secondary measure of executive pay-for-performance sensitivity

(see HS Table IV) based on Jensen and Murphy (1990) raises issues other than the size

control HS regress changes in compensation (cash and total) on lagged institutional

influence that has been interacted with the contemporaneous change in shareholder

wealth to capture a pay-for-performance relationship Such a test is appealing ndash

7 AHS do point out one benefit of the institutional concentration measure Institutional investors may prefer

companies with lsquobetterrsquo incentive compensation structures Could using institutional shareholding rather

than total shareholding as the deflator alleviate this problem Presumably both the numerator and

denominator will have the same bias and hence error cancellation is a possibility

9

institutions should increase compensation when the firm has performed well Following

Greene (2000 p326) to execute such a test one needs to include in level form variables

that are then interacted Hence the HS model specification ought to be

1 2 3 1 4 1it it it it it itCompn SW IC SW IC (1)

where itCompn is the change in executive compensation itSW is the contemporaneous

change in shareholder wealth which also appears in the interaction term and 1itIC is

lagged institutional ownership concentration However HS (p2363) omit the

contemporaneous term itSW and the lagged term 1itIC which should appear in levels

as well as in the interaction term Most importantly HS interact their lagged institutional

concentration measure 1itIC with the contemporaneous change in shareholder wealth

itSW As it is after all pay-for-performance concentrated institutions need to condition

their influence on some observed measure of firm performance Contemporaneous firm

performance is unknown at the time institutional influence is measured Reflecting this

timing insight leads to a new Greene (2000) specification

1 2 1 3 1 4 1 1it it it it it itCompn SW IC SW IC (2)

such that all the lagged RHS independent variables that now appear in the interaction

term are included on a stand-alone basis

Reliance on incomplete self-reported values for option grants

Prior to receiving the HS dataset we tried to replicate the findings of HS to validate

our datasets for the HS period and the longer period 1992‒2002 While we initially

focused on the same period as HS (ie 1992‒1997) we found that our sample size was

larger at 47765 observations than HSrsquos at 33928 observations This discrepancy could

have arisen if HS did not replace missing and self-reported option valuations using their

10

Black-Scholes option methodology This may introduce a downward pay bias since self-

reported option-grant pay is subject to possible understatement and there are 13839

observations with likely high option pay dropped altogether

Endogeneity

HSrsquos endogeneity testing raises concerns about reverse causality Institutions may

prefer to hold firms with certain compensation structures such as incentivized executives

HS rightly highlight this concern and use instrumental variables to address this issue HS

assume that institutional ownership reflects any reverse causality Using an instrumental

variables approach to resolve this problem involves finding a variable that influences or

explains institutional ownership but not directly executive compensation They use share

turnover in a firm as an instrument for institutional ownership However theoretical work

by Holmstrom and Tirole (1993) indicates that measures of stock liquidity and trading

activity are indeed important determinants of executive market-based incentives as Kang

and Lui (2008) and Dikolli Kulp and Sedatole (2009) find empirically As such one can

make a case for adopting another instrument rather than share turnover for institutional

ownership

II Previous Research

Prior research fails to address issues concerning possible fragility of the HS results

AHS replicate the HS findings on both incentives and pay levels using the same dataset as

HS and they apply the same definition of institutional concentration and use market

capitalization expressed as a level Cadman Klasa and Matsunaga (2010 Table 6) set out

to replicate HSrsquos (Table II) model of option grant pay-for-performance sensitivity when

they compare a dataset of ExecuComp and Non-ExecuComp firms for the period 2000-

2007 Their ExecuComp results for this sample period are quite similar to our results for

11

the 1992‒2002 period for the same specification controlling for the logarithm of market

capitalization but they do not regard these results as a test of HS as their focus is entirely

on comparing the two groups of stocks Nor do they investigate the impact of

concentration on either cash compensation or total pay Kang and Liu (2008) examine

pay-performance sensitivity use a version of the HS institutional concentration measure

as a control variable in a different framework deriving from Holmstrom and Tirole

(1993) Dikolli Kulp and Sedatole (2009) argue that firms with transient ownership will

issue relatively more equity incentives to counter short-termism with their results robust

to the inclusion of the HS concentration variable

We hoped to find supportive evidence from proxy voting behavior in support of HSs

findings However evidence from actual mutual fund proxy voting records suggests that

most oppose reductions in CEO pay but overall the evidence is mixed8 Davis and Kim

(2005) examine proxy votes of mutual funds for 2004 and find that for a sample of

Fortune 1000 proxy contests in 45 cases that attempted to limit executive pay mutual

funds were unanimously opposed to such attempts Rothberg and Lilien (2006) also

examine proxy-voting data and find that mutual funds voted 66 percent of the time in

managementrsquos favor on issues of executive compensation Ertimur Ferri and Muslu

(2011) find that institutional investors lack sophistication in that they do not target

excessively paid CEOs relative to CEOs with high predicted-pay based on economic

determinants but exert a moderating influence ndash a $23 million reduction ndash for those they

deem ldquoexcessively paidrdquo CEOs

III Data and Methodology

8 We do acknowledge that the HS results are for all institutional investors while the transparency with

respect to proxy voting applies only to mutual funds

12

This Section discusses the data used in the study the construction of variables

descriptive statistics and the methodology Two datasets are used ndash one is the original

dataset generously supplied by Jay Hartzell and Laura Starks which covers 1992‒1997

second a more comprehensive dataset covering 1992‒2002 is computed from the same

data sources used in the HS dataset This is Standard and Poorrsquos (SampP) ExecuComp for

compensation data Thomson Financial CDASpectrum database for institutional holdings

to compute measure of institutional influence SampPrsquos Compustat and the Center for

Research in Stock Prices (CRSP) for firm level accounting and stock price data Our more

comprehensive dataset contains 2559 firms compared with 1914 for the HS dataset Our

full matched sample yields 97679 executive years

A Institutional Influence Measures

To measure institutional influence we employ two ownership-based metrics The first

measure of institutional influence is HSrsquos Institutional Concentration We use this for

direct comparison to the HS analysis The second measure of institutional influence

changes the denominator of the HS measure from institutional shares held to total shares

outstanding in the firm with nomenclature Top 5 Ownership9 We compute both

measures at the fiscal year end of the firm We adjust all compensation measures and

asset prices for inflation to 30 June 2002 prices for our comprehensive sample compared

to the HS dataset that is in the dollars of the day

B Compensation Measures

The ExecuComp database reports several raw measures of executive compensation for

the top five executives (where available) including total salary bonus long-term

9 Top 5 Ownership is included in the HS database but not utilized by them in reported tests as well as

constructed by us for the more comprehensive sample

13

incentives and number of option grants For our more comprehensive dataset we replicate

all the compensation measures used by HS In common with HS we compute the pay-for-

performance sensitivity of option grants using the Yermack (1995) approach This

measure shows the dollar change in value of the executive options for every dollar change

in the value of the firm This involves calculating the option delta using the Black-

Scholes formula adjusted for dividends10

The ratio of the number of shares represented

by the award of options divided by the diluted number of shares outstanding at the

beginning of the year multiplies the option delta with units given by a $1000 change in

firm value Summing salary bonus long-term incentive plan payouts and stock and

option grants provides total direct compensation Options are valued using the Black and

Scholes (1973) formula for European call options adjusted by Merton (1973) to

incorporate dividends

C Descriptive Statistics

Table I presents descriptive statistics of key variables employed in the study according

to our comprehensive dataset11

Institutions own on average 546 percent of the firms in

which they invest This is almost identical to the 531 percent found by HS The

institutions with the five largest holdings account 45 percent of institutional ownership

Once again the figure for HS is almost identical at 44 percent The institutions with the

five largest holdings own on average 229 percent of shares outstanding in a firm (HS

have 223 percent) Average total compensation for executives is $2583 million

considerably larger than that documented by HS ($1250 million) but the HS figure is an

10 When there is more than one grant during the year a weighted average delta is used

11 With the data supplied to us by Hartzell and Starks we are able to replicate exactly their summary data

(HS Table I) for all but cash compensation Salary is included but bonus payments are missing The

replicated table is available on request

14

amalgam of price levels over their sample period 1992‒1997 and ours are in consistent

dollars of June 30 2002 However there has also been significant growth in

compensation levels from 1998 to 2002

ltltINSERT TABLE Igtgt

Based on our comprehensive data in Table II we examine correlations between the

key variables employed in the study Of concern is the large negative correlation of 63

percent which has been discussed previously (Section IIA) between the HS measure of

institutional concentration and the natural logarithm of firm market capitalization

ltltINSERT TABLE IIgtgt

In view of this high correlation Table III provides a breakdown of the three key pay

variables and three institutional ownership variables by size deciles We find that the high

institutional concentration but low institutional ownership share of total shareholdings

mentioned above is evident in the smallest decile of firms by size This decile has low

salary and even lower total compensation in a relative sense but by far the highest pay-

for-performance sensitivity of option grants Small firms award executives a far higher

proportion of market capitalization Since small firm market-capitalization is negligible in

comparison with the highest decile (300 times larger in magnitude) total compensation is

very small in absolute value Moreover due to the domination of the pay-size effect base

salaries are also exceedingly small

ltltINSERT TABLE IIIgtgt

Figure 1 based on Table III shows how as institutional concentration falls with

increases in stock size (but also as the total share of institutional ownership increases)

and the pay-for-performance sensitivity of option grants falls Thus because of what

appears to be a weak size control and size-influenced concentration measure HS

15

potentially pick up a size effect as their main result but not necessarily a monitoring

effect Figure 2 shows that as firm size increases up to decile 8 at least the share of

institutional total ownership increases as does total compensation

ltltINSERT FIGURES 1 AND 2 gtgt

D Methodology

Following HS we use two estimation techniques to examine the effect of institutional

investor influence on executive compensation Due to the censored nature of option grant

pay-for-performance sensitivity this compensation measure most appropriately uses

Tobit model specification whereas an Ordinary Least Squares (OLS) model specification

is used for all other compensation measures We model compensation measures as a

function of contemporaneous and lagged change in shareholder wealth institutional

influence Tobinrsquos Q and market capitalization Controls for CEO industry and year

effects are also used Augmentation occurs to test the effect of institutional influence on

the change in executive cash and total compensation with an interaction term that is the

product of institutional influence and the change in shareholder wealth

The variables used to model executive compensation have the following definitions

The lagged and contemporary measure of change in shareholder wealth is simply the

difference in market capitalization of the firm The measures of institutional influence

used are Institutional Concentration and Top 5 Ownership Use of the two types of

institutional influence occurs in separate models In order to replicate the HS

methodology models using Institutional Concentration have an additional control

consisting of lagged total institutional holdings and Tobinrsquos Q controls for performance

and growth opportunities Market capitalization of the firm is the number of shares

outstanding multiplied by the share price with inclusion both in levels and natural

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 2: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

Electronic copy available at httpssrncomabstract=1009309

2

With 128 cites in Web of Science and 757 cites in Google Scholar Hartzell and Starks

(2003) [hereafter HS] ranks among the most influential corporate finance papers of the

last decade HS find that concentrated institutional monitors provide greater incentives for

executives to perform by granting more options while simultaneously lowering their cash-

based pay with an even greater fall in total direct compensation HS (p2355) define

concentrated institutional holdings [hereafter Top 5 Concentration] by the proportion of

institutional ownership accounted for by the top five institutional investors12

By

contrast our paper argues that several methodological issues in HS alter their finding by

showing that concentration has either no effect on incentives or perhaps reduces them

and in the case of salary and total pay levels reverse their findings Our paper discusses

these issues and then empirically demonstrates the effect that they have on the findings of

HS

HSrsquos findings are supportive of the idea that firms overpay executives as the

skimming or rent-seeking view of executive compensation maintains See for example

Bertrand and Mullainathan (2001) Bebchuk Fried and Walker (2002) Bebchuk and

Fried (2003 2004) Chhaochharia and Grinstein (2009) and Morse Nanda and Seru

(2011) Chhaochharia and Grinstein (2009) find that increased board requirements

reduced CEO pay but note the fragility qualification provided by Guthrie Sokolowsky

and Wan (2012) and Morse Nanda and Seru (2011) find that powerful CEOs rig

performance measures to increase their pay and that these firms then underperform

1 More specifically HS (p2352) find that an increase of one standard deviation in Top 5 institutional

investor concentration is associated with a 20 percent increase in option grant pay-for-performance

sensitivity and a 19 percent drop in total compensation for the average executive

2 HS also obtain similar findings using a Herfindahl index of institutional fractional holdings that they

construct in a very similar fashion to their main concentration measure Our findings for their concentration

measure will also tend to be true of their Herfindahl measure

Electronic copy available at httpssrncomabstract=1009309

3

We find that Institutional Top 5 Concentration according to the HS definition does

not raise option grant pay-for-performance sensitivity as it has no statistically significant

impact either way once one introduces a standard logarithmically transformed size

control Similarly lagged Institutional Concentration has a negative but statistically

insignificant effect on the pay-for-performance sensitivity of cash (salary plus bonus)

compensation when interacted with the lagged change in shareholder wealth HS obtain a

significant positive coefficient using the contemporaneous change in shareholder wealth

but one need replace this by the lagged change in shareholder wealth in keeping with

what influential institutional investors knew at the time Additionally HS find that lagged

concentrated institutional ownership sizably lowers both salary and total direct

compensation and this is statistically significant but we find the reverse ‒ it appears to

raise both and the findings are highly statistically significant also following a standard

logarithmically transformed size control

Upon closer examination several aspects of the HS research design are of interest

First the primary argument in our paper is that the use by HS of the lagged value of the

level of market capitalization as the size control in regressions (HS p2359) rather than

the conventional lagged logarithm of capitalization distorts the coefficient on the

measure of institutional influence3 A number of authors have drawn attention to falling

pay-for-performance sensitivities as firm size increases (eg Jensen and Murphy (1990)

Garen (1994) Hadlock and Lumer (1997) Schaefer (1998) Murphy (1999) Jin (2002)

and Chichello (2005)) and hence the need to have effective size controls In the HS

dataset the raw mean market capitalization ranges from $1181m in decile 1 to $36654m

in decile 10 (see Table III below) a difference of 3104 fold reducing to only 22 with the

3 HS (p2357) also use net assets and total assets as controls but in keeping with the use of raw

capitalization retain them in their raw form

4

logarithmic transformation While this skewed nature of the level of market capitalization

does not per se rule out its use specification tests such as Box-Cox and the replacement

of market capitalization by its cumulative distribution (see Section VI below) indicates a

possible specification error Moreover using the lagged natural logarithm of market

capitalization as a firm size control in the actual HS data with the same dependent

variable and no other changes raises the explanatory power (R-Squared) of the HS model

by between 135 and 1516 percent4

Given that firm size is an important determinant of executive compensation selecting

the correct functional form for firm size is a vexing and important issue Many estimates

including those of Murphy (1985) Rosen (1992) Gibbons and Murphy (1992) Huson

Parrino and Starks (2001) Baker and Hall (2004) Gabaix and Landier (2008) Edmans

Gabaix and Landier (2009) Babenko (2009) and Aggarwal Erel and Ferreira (2011)

use a logarithmic specification with the elasticity between firm size and executive total

pay in the range of 03 and 04 HS seems to employ inadvertently a firm size measure in

levels (also alternative firm size measures also in levels) and consequently imply an

elasticity value (exponent on market capitalization) of unity

Second we question the use of the HS Top 5 Concentration measure of institutional

influence based on the influence of concentrated institutional investors relative to their

peers that appears to lead inadvertently to an exacerbation of the size-control problem In

their companion theoretical model AHS arrive at a different and what might seem a more

natural specification namely Top 5 Ownership which measures concentration relative to

all shareholders not just institutional peers The following example illustrates the

4 The lower result is based on OLS regressions of model 1 of Table II of HS with the R-Squared rising from

00853 to 00968 once Market Capitalization is logged and the higher result model 1 of Table V of HS is

based on an improvement in R-Squared from 04604 to 05302 (see Table VI below)

5

differences between these two methods If there are one hundred shares outstanding in a

small company and the only institution owns one share that company is concentrated

according even though that institution may lack effective monitoring power Instead if

one deflates by shares on issue this results in a concentration ratio of 1100 If on the

other hand ten institutions collectively own 500 shares in a much larger company of

1000 shares and the Top Five collectively own 250 then the HS concentration ratio falls

to only 250500 or 05 and utilizing shares on issue 025 in this case As is confirmed by

the data one expects Top 5 Concentration to correlate negatively with firm size and Top

5 Ownership the reverse given a positive association between institutional ownership and

company size We then re-examine the monitoring hypothesis using this AHS proposed

measure of institutional investor influence that intuitively relates better to institutional

proxy voting power

Third we address issues of reliance on potentially biased self-reported values of option

grants that result in the exclusion of 16 percent of the HS sample size for tests on total

(direct) compensation Forth we argue that tests that HS perform using an alternative

measure of pay-for-performance sensitivity to provide support for the main hypothesis of

the study require one to get the timing right in terms of the lag structure of performance

and concentration Finally we address issues associated with their tests of endogeneity

and reverse causality These issues collectively might suggest overlooking of a

monitoring effect with the main driving forces size related

The next section reviews the HS study in an effort to tease out what might really be

going on Section II examines the literature for studies that in replicating HS provide

independent support for their findings It also reports findings on the actual proxy voting

record of mutual funds and actions of institutional investors in reducing pay Section III

describes the data and methodology Section IV analyzes the relation between

6

institutional influence and measures of pay-for-performance sensitivity Section V

documents the relationship between institutional influence and total and fixed

compensation Section VI examines the robustness of our findings and the final Section

concludes

I Review of Hartzell and Starks Methodology

We comment on five areas of the HS methodology 1) Size control 2) Measurement of

institutional influence 3) Testing the Jensen-Murphy measure of incentives 4) Reliance

on incomplete self-reported valued for option grants and 5) Endogeneity

A Size Control

In our paper we argue that HS unintentionally identify incentive-size and pay-size

effects5 not a monitoring effect It can be seen in Figure II that executive total pay for

HSrsquos Top 5 institutional concentration measure rises from as little as $072m for the

smallest market capitalization decile to $85m for the highest This twelve-fold pay-size

effect in the deciles can cause problems if one utilizes an untransformed size measure

Due to skewness in the size measure using this in its untransformed state appears to

weaken its effectiveness leaving open the possibility that correlations they identify

between incentives and pay levels on the one hand and Top 5 Concentration on the other

are due largely to size-related effects

Table III displays this strong pay-size effect based on our full 1992‒2002 dataset and

graphically in Figure 1 It shows that the incentive measure adopted by HS declines from

$272 per $1000 change in shareholder wealth for the smallest market capitalization

decile of firms to approximately $030 for the largest Table III and Figure 1 show the

5 The multiplicative model of Edmans Gabaix and Landier (2009) finds that incentive pay increases with

firm size (elasticity value of 13) and the empirical elasticity is 037

7

strong relation between institutional concentration as measured by HS and market

capitalization For the smallest decile of market capitalization firms institutional

concentration averages 61 percent declining to about 275 percent for the highest decile

This negative relationship between firm size and institutional concentration seems to arise

because institutional investors do generally favor small firms This causes problems

because in the limit a small company may have only one institutional investor owning

only a small percentage of the company Hence it would appear to be fully concentrated

even though the ability of the institutional investor to influence pay decisions might be

small Thus it is not at all surprising that the correlation between the logarithm of market

capitalization and their institutional concentration measure is both negative and high in

absolute value at 63 percent Their methodology appears to favor small companies that

Table III shows to have low pay levels and high pay for performance sensitivity

Moreover if one does not transform the raw size measure it implicitly assumes that a

given dollar change in firm size has the same absolute impact on pay for a very large

company as it does for a small company Indeed the conventional logarithmic

specification for firm size provides proportionate effects that imply a pay-size elasticity of

approximately one-third instead of unity6

B Measurement of Institutional Influence

We argue that there are additional issues related to the HS measure of institutional

influence ndash institutional concentration In their companion article to HS AHS develop a

model where they capture institutional influence by a single large long-term institutional

6 Note that unlike an earlier version of our paper we leave the HS dependent variables in levels and hence

untransformed While we do this to minimize the alterations that we make to the HS specification ideally

the elasticity specification is preferable especially for the compensation variables Transforming the

dependent variables does not significantly affect the results

8

investor They measure influence relative to total shareholding including private or

atomistic shareholders Presumably they do this to capture relative activism and proxy

voting strength However when it comes to the empirical implementation of the model

AHS adopt the same relative institutional concentration measure as in HS (AHS (p12))

potentially downplaying the relative strength of institutions compared with other

shareholders They justify this because there is generally more than one institutional

investor and there will be free-riding problems with multiple investors that only the

largest institutional investors can overcome While we accept their premise of free-rider

problems it is not obvious why the deflator is lsquoinstitutional shareholdingrsquo rather than

lsquototal shareholdingrsquo from this perspective7 If the strength of the size control can be

queried scaling by total shareholding (ie Top 5 Ownership) produces a measure that

remains relatively unaffected across the size deciles It is 20 percent for the smaller

decile declining to 14 percent for the largest decile whereas for the HS concentration

measure it declines by over 50 percent from 61 percent to 28 percent (see Table III and

Figure 1)

C Testing the Jensen-Murphy Measure of Incentives

The testing of their secondary measure of executive pay-for-performance sensitivity

(see HS Table IV) based on Jensen and Murphy (1990) raises issues other than the size

control HS regress changes in compensation (cash and total) on lagged institutional

influence that has been interacted with the contemporaneous change in shareholder

wealth to capture a pay-for-performance relationship Such a test is appealing ndash

7 AHS do point out one benefit of the institutional concentration measure Institutional investors may prefer

companies with lsquobetterrsquo incentive compensation structures Could using institutional shareholding rather

than total shareholding as the deflator alleviate this problem Presumably both the numerator and

denominator will have the same bias and hence error cancellation is a possibility

9

institutions should increase compensation when the firm has performed well Following

Greene (2000 p326) to execute such a test one needs to include in level form variables

that are then interacted Hence the HS model specification ought to be

1 2 3 1 4 1it it it it it itCompn SW IC SW IC (1)

where itCompn is the change in executive compensation itSW is the contemporaneous

change in shareholder wealth which also appears in the interaction term and 1itIC is

lagged institutional ownership concentration However HS (p2363) omit the

contemporaneous term itSW and the lagged term 1itIC which should appear in levels

as well as in the interaction term Most importantly HS interact their lagged institutional

concentration measure 1itIC with the contemporaneous change in shareholder wealth

itSW As it is after all pay-for-performance concentrated institutions need to condition

their influence on some observed measure of firm performance Contemporaneous firm

performance is unknown at the time institutional influence is measured Reflecting this

timing insight leads to a new Greene (2000) specification

1 2 1 3 1 4 1 1it it it it it itCompn SW IC SW IC (2)

such that all the lagged RHS independent variables that now appear in the interaction

term are included on a stand-alone basis

Reliance on incomplete self-reported values for option grants

Prior to receiving the HS dataset we tried to replicate the findings of HS to validate

our datasets for the HS period and the longer period 1992‒2002 While we initially

focused on the same period as HS (ie 1992‒1997) we found that our sample size was

larger at 47765 observations than HSrsquos at 33928 observations This discrepancy could

have arisen if HS did not replace missing and self-reported option valuations using their

10

Black-Scholes option methodology This may introduce a downward pay bias since self-

reported option-grant pay is subject to possible understatement and there are 13839

observations with likely high option pay dropped altogether

Endogeneity

HSrsquos endogeneity testing raises concerns about reverse causality Institutions may

prefer to hold firms with certain compensation structures such as incentivized executives

HS rightly highlight this concern and use instrumental variables to address this issue HS

assume that institutional ownership reflects any reverse causality Using an instrumental

variables approach to resolve this problem involves finding a variable that influences or

explains institutional ownership but not directly executive compensation They use share

turnover in a firm as an instrument for institutional ownership However theoretical work

by Holmstrom and Tirole (1993) indicates that measures of stock liquidity and trading

activity are indeed important determinants of executive market-based incentives as Kang

and Lui (2008) and Dikolli Kulp and Sedatole (2009) find empirically As such one can

make a case for adopting another instrument rather than share turnover for institutional

ownership

II Previous Research

Prior research fails to address issues concerning possible fragility of the HS results

AHS replicate the HS findings on both incentives and pay levels using the same dataset as

HS and they apply the same definition of institutional concentration and use market

capitalization expressed as a level Cadman Klasa and Matsunaga (2010 Table 6) set out

to replicate HSrsquos (Table II) model of option grant pay-for-performance sensitivity when

they compare a dataset of ExecuComp and Non-ExecuComp firms for the period 2000-

2007 Their ExecuComp results for this sample period are quite similar to our results for

11

the 1992‒2002 period for the same specification controlling for the logarithm of market

capitalization but they do not regard these results as a test of HS as their focus is entirely

on comparing the two groups of stocks Nor do they investigate the impact of

concentration on either cash compensation or total pay Kang and Liu (2008) examine

pay-performance sensitivity use a version of the HS institutional concentration measure

as a control variable in a different framework deriving from Holmstrom and Tirole

(1993) Dikolli Kulp and Sedatole (2009) argue that firms with transient ownership will

issue relatively more equity incentives to counter short-termism with their results robust

to the inclusion of the HS concentration variable

We hoped to find supportive evidence from proxy voting behavior in support of HSs

findings However evidence from actual mutual fund proxy voting records suggests that

most oppose reductions in CEO pay but overall the evidence is mixed8 Davis and Kim

(2005) examine proxy votes of mutual funds for 2004 and find that for a sample of

Fortune 1000 proxy contests in 45 cases that attempted to limit executive pay mutual

funds were unanimously opposed to such attempts Rothberg and Lilien (2006) also

examine proxy-voting data and find that mutual funds voted 66 percent of the time in

managementrsquos favor on issues of executive compensation Ertimur Ferri and Muslu

(2011) find that institutional investors lack sophistication in that they do not target

excessively paid CEOs relative to CEOs with high predicted-pay based on economic

determinants but exert a moderating influence ndash a $23 million reduction ndash for those they

deem ldquoexcessively paidrdquo CEOs

III Data and Methodology

8 We do acknowledge that the HS results are for all institutional investors while the transparency with

respect to proxy voting applies only to mutual funds

12

This Section discusses the data used in the study the construction of variables

descriptive statistics and the methodology Two datasets are used ndash one is the original

dataset generously supplied by Jay Hartzell and Laura Starks which covers 1992‒1997

second a more comprehensive dataset covering 1992‒2002 is computed from the same

data sources used in the HS dataset This is Standard and Poorrsquos (SampP) ExecuComp for

compensation data Thomson Financial CDASpectrum database for institutional holdings

to compute measure of institutional influence SampPrsquos Compustat and the Center for

Research in Stock Prices (CRSP) for firm level accounting and stock price data Our more

comprehensive dataset contains 2559 firms compared with 1914 for the HS dataset Our

full matched sample yields 97679 executive years

A Institutional Influence Measures

To measure institutional influence we employ two ownership-based metrics The first

measure of institutional influence is HSrsquos Institutional Concentration We use this for

direct comparison to the HS analysis The second measure of institutional influence

changes the denominator of the HS measure from institutional shares held to total shares

outstanding in the firm with nomenclature Top 5 Ownership9 We compute both

measures at the fiscal year end of the firm We adjust all compensation measures and

asset prices for inflation to 30 June 2002 prices for our comprehensive sample compared

to the HS dataset that is in the dollars of the day

B Compensation Measures

The ExecuComp database reports several raw measures of executive compensation for

the top five executives (where available) including total salary bonus long-term

9 Top 5 Ownership is included in the HS database but not utilized by them in reported tests as well as

constructed by us for the more comprehensive sample

13

incentives and number of option grants For our more comprehensive dataset we replicate

all the compensation measures used by HS In common with HS we compute the pay-for-

performance sensitivity of option grants using the Yermack (1995) approach This

measure shows the dollar change in value of the executive options for every dollar change

in the value of the firm This involves calculating the option delta using the Black-

Scholes formula adjusted for dividends10

The ratio of the number of shares represented

by the award of options divided by the diluted number of shares outstanding at the

beginning of the year multiplies the option delta with units given by a $1000 change in

firm value Summing salary bonus long-term incentive plan payouts and stock and

option grants provides total direct compensation Options are valued using the Black and

Scholes (1973) formula for European call options adjusted by Merton (1973) to

incorporate dividends

C Descriptive Statistics

Table I presents descriptive statistics of key variables employed in the study according

to our comprehensive dataset11

Institutions own on average 546 percent of the firms in

which they invest This is almost identical to the 531 percent found by HS The

institutions with the five largest holdings account 45 percent of institutional ownership

Once again the figure for HS is almost identical at 44 percent The institutions with the

five largest holdings own on average 229 percent of shares outstanding in a firm (HS

have 223 percent) Average total compensation for executives is $2583 million

considerably larger than that documented by HS ($1250 million) but the HS figure is an

10 When there is more than one grant during the year a weighted average delta is used

11 With the data supplied to us by Hartzell and Starks we are able to replicate exactly their summary data

(HS Table I) for all but cash compensation Salary is included but bonus payments are missing The

replicated table is available on request

14

amalgam of price levels over their sample period 1992‒1997 and ours are in consistent

dollars of June 30 2002 However there has also been significant growth in

compensation levels from 1998 to 2002

ltltINSERT TABLE Igtgt

Based on our comprehensive data in Table II we examine correlations between the

key variables employed in the study Of concern is the large negative correlation of 63

percent which has been discussed previously (Section IIA) between the HS measure of

institutional concentration and the natural logarithm of firm market capitalization

ltltINSERT TABLE IIgtgt

In view of this high correlation Table III provides a breakdown of the three key pay

variables and three institutional ownership variables by size deciles We find that the high

institutional concentration but low institutional ownership share of total shareholdings

mentioned above is evident in the smallest decile of firms by size This decile has low

salary and even lower total compensation in a relative sense but by far the highest pay-

for-performance sensitivity of option grants Small firms award executives a far higher

proportion of market capitalization Since small firm market-capitalization is negligible in

comparison with the highest decile (300 times larger in magnitude) total compensation is

very small in absolute value Moreover due to the domination of the pay-size effect base

salaries are also exceedingly small

ltltINSERT TABLE IIIgtgt

Figure 1 based on Table III shows how as institutional concentration falls with

increases in stock size (but also as the total share of institutional ownership increases)

and the pay-for-performance sensitivity of option grants falls Thus because of what

appears to be a weak size control and size-influenced concentration measure HS

15

potentially pick up a size effect as their main result but not necessarily a monitoring

effect Figure 2 shows that as firm size increases up to decile 8 at least the share of

institutional total ownership increases as does total compensation

ltltINSERT FIGURES 1 AND 2 gtgt

D Methodology

Following HS we use two estimation techniques to examine the effect of institutional

investor influence on executive compensation Due to the censored nature of option grant

pay-for-performance sensitivity this compensation measure most appropriately uses

Tobit model specification whereas an Ordinary Least Squares (OLS) model specification

is used for all other compensation measures We model compensation measures as a

function of contemporaneous and lagged change in shareholder wealth institutional

influence Tobinrsquos Q and market capitalization Controls for CEO industry and year

effects are also used Augmentation occurs to test the effect of institutional influence on

the change in executive cash and total compensation with an interaction term that is the

product of institutional influence and the change in shareholder wealth

The variables used to model executive compensation have the following definitions

The lagged and contemporary measure of change in shareholder wealth is simply the

difference in market capitalization of the firm The measures of institutional influence

used are Institutional Concentration and Top 5 Ownership Use of the two types of

institutional influence occurs in separate models In order to replicate the HS

methodology models using Institutional Concentration have an additional control

consisting of lagged total institutional holdings and Tobinrsquos Q controls for performance

and growth opportunities Market capitalization of the firm is the number of shares

outstanding multiplied by the share price with inclusion both in levels and natural

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 3: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

Electronic copy available at httpssrncomabstract=1009309

3

We find that Institutional Top 5 Concentration according to the HS definition does

not raise option grant pay-for-performance sensitivity as it has no statistically significant

impact either way once one introduces a standard logarithmically transformed size

control Similarly lagged Institutional Concentration has a negative but statistically

insignificant effect on the pay-for-performance sensitivity of cash (salary plus bonus)

compensation when interacted with the lagged change in shareholder wealth HS obtain a

significant positive coefficient using the contemporaneous change in shareholder wealth

but one need replace this by the lagged change in shareholder wealth in keeping with

what influential institutional investors knew at the time Additionally HS find that lagged

concentrated institutional ownership sizably lowers both salary and total direct

compensation and this is statistically significant but we find the reverse ‒ it appears to

raise both and the findings are highly statistically significant also following a standard

logarithmically transformed size control

Upon closer examination several aspects of the HS research design are of interest

First the primary argument in our paper is that the use by HS of the lagged value of the

level of market capitalization as the size control in regressions (HS p2359) rather than

the conventional lagged logarithm of capitalization distorts the coefficient on the

measure of institutional influence3 A number of authors have drawn attention to falling

pay-for-performance sensitivities as firm size increases (eg Jensen and Murphy (1990)

Garen (1994) Hadlock and Lumer (1997) Schaefer (1998) Murphy (1999) Jin (2002)

and Chichello (2005)) and hence the need to have effective size controls In the HS

dataset the raw mean market capitalization ranges from $1181m in decile 1 to $36654m

in decile 10 (see Table III below) a difference of 3104 fold reducing to only 22 with the

3 HS (p2357) also use net assets and total assets as controls but in keeping with the use of raw

capitalization retain them in their raw form

4

logarithmic transformation While this skewed nature of the level of market capitalization

does not per se rule out its use specification tests such as Box-Cox and the replacement

of market capitalization by its cumulative distribution (see Section VI below) indicates a

possible specification error Moreover using the lagged natural logarithm of market

capitalization as a firm size control in the actual HS data with the same dependent

variable and no other changes raises the explanatory power (R-Squared) of the HS model

by between 135 and 1516 percent4

Given that firm size is an important determinant of executive compensation selecting

the correct functional form for firm size is a vexing and important issue Many estimates

including those of Murphy (1985) Rosen (1992) Gibbons and Murphy (1992) Huson

Parrino and Starks (2001) Baker and Hall (2004) Gabaix and Landier (2008) Edmans

Gabaix and Landier (2009) Babenko (2009) and Aggarwal Erel and Ferreira (2011)

use a logarithmic specification with the elasticity between firm size and executive total

pay in the range of 03 and 04 HS seems to employ inadvertently a firm size measure in

levels (also alternative firm size measures also in levels) and consequently imply an

elasticity value (exponent on market capitalization) of unity

Second we question the use of the HS Top 5 Concentration measure of institutional

influence based on the influence of concentrated institutional investors relative to their

peers that appears to lead inadvertently to an exacerbation of the size-control problem In

their companion theoretical model AHS arrive at a different and what might seem a more

natural specification namely Top 5 Ownership which measures concentration relative to

all shareholders not just institutional peers The following example illustrates the

4 The lower result is based on OLS regressions of model 1 of Table II of HS with the R-Squared rising from

00853 to 00968 once Market Capitalization is logged and the higher result model 1 of Table V of HS is

based on an improvement in R-Squared from 04604 to 05302 (see Table VI below)

5

differences between these two methods If there are one hundred shares outstanding in a

small company and the only institution owns one share that company is concentrated

according even though that institution may lack effective monitoring power Instead if

one deflates by shares on issue this results in a concentration ratio of 1100 If on the

other hand ten institutions collectively own 500 shares in a much larger company of

1000 shares and the Top Five collectively own 250 then the HS concentration ratio falls

to only 250500 or 05 and utilizing shares on issue 025 in this case As is confirmed by

the data one expects Top 5 Concentration to correlate negatively with firm size and Top

5 Ownership the reverse given a positive association between institutional ownership and

company size We then re-examine the monitoring hypothesis using this AHS proposed

measure of institutional investor influence that intuitively relates better to institutional

proxy voting power

Third we address issues of reliance on potentially biased self-reported values of option

grants that result in the exclusion of 16 percent of the HS sample size for tests on total

(direct) compensation Forth we argue that tests that HS perform using an alternative

measure of pay-for-performance sensitivity to provide support for the main hypothesis of

the study require one to get the timing right in terms of the lag structure of performance

and concentration Finally we address issues associated with their tests of endogeneity

and reverse causality These issues collectively might suggest overlooking of a

monitoring effect with the main driving forces size related

The next section reviews the HS study in an effort to tease out what might really be

going on Section II examines the literature for studies that in replicating HS provide

independent support for their findings It also reports findings on the actual proxy voting

record of mutual funds and actions of institutional investors in reducing pay Section III

describes the data and methodology Section IV analyzes the relation between

6

institutional influence and measures of pay-for-performance sensitivity Section V

documents the relationship between institutional influence and total and fixed

compensation Section VI examines the robustness of our findings and the final Section

concludes

I Review of Hartzell and Starks Methodology

We comment on five areas of the HS methodology 1) Size control 2) Measurement of

institutional influence 3) Testing the Jensen-Murphy measure of incentives 4) Reliance

on incomplete self-reported valued for option grants and 5) Endogeneity

A Size Control

In our paper we argue that HS unintentionally identify incentive-size and pay-size

effects5 not a monitoring effect It can be seen in Figure II that executive total pay for

HSrsquos Top 5 institutional concentration measure rises from as little as $072m for the

smallest market capitalization decile to $85m for the highest This twelve-fold pay-size

effect in the deciles can cause problems if one utilizes an untransformed size measure

Due to skewness in the size measure using this in its untransformed state appears to

weaken its effectiveness leaving open the possibility that correlations they identify

between incentives and pay levels on the one hand and Top 5 Concentration on the other

are due largely to size-related effects

Table III displays this strong pay-size effect based on our full 1992‒2002 dataset and

graphically in Figure 1 It shows that the incentive measure adopted by HS declines from

$272 per $1000 change in shareholder wealth for the smallest market capitalization

decile of firms to approximately $030 for the largest Table III and Figure 1 show the

5 The multiplicative model of Edmans Gabaix and Landier (2009) finds that incentive pay increases with

firm size (elasticity value of 13) and the empirical elasticity is 037

7

strong relation between institutional concentration as measured by HS and market

capitalization For the smallest decile of market capitalization firms institutional

concentration averages 61 percent declining to about 275 percent for the highest decile

This negative relationship between firm size and institutional concentration seems to arise

because institutional investors do generally favor small firms This causes problems

because in the limit a small company may have only one institutional investor owning

only a small percentage of the company Hence it would appear to be fully concentrated

even though the ability of the institutional investor to influence pay decisions might be

small Thus it is not at all surprising that the correlation between the logarithm of market

capitalization and their institutional concentration measure is both negative and high in

absolute value at 63 percent Their methodology appears to favor small companies that

Table III shows to have low pay levels and high pay for performance sensitivity

Moreover if one does not transform the raw size measure it implicitly assumes that a

given dollar change in firm size has the same absolute impact on pay for a very large

company as it does for a small company Indeed the conventional logarithmic

specification for firm size provides proportionate effects that imply a pay-size elasticity of

approximately one-third instead of unity6

B Measurement of Institutional Influence

We argue that there are additional issues related to the HS measure of institutional

influence ndash institutional concentration In their companion article to HS AHS develop a

model where they capture institutional influence by a single large long-term institutional

6 Note that unlike an earlier version of our paper we leave the HS dependent variables in levels and hence

untransformed While we do this to minimize the alterations that we make to the HS specification ideally

the elasticity specification is preferable especially for the compensation variables Transforming the

dependent variables does not significantly affect the results

8

investor They measure influence relative to total shareholding including private or

atomistic shareholders Presumably they do this to capture relative activism and proxy

voting strength However when it comes to the empirical implementation of the model

AHS adopt the same relative institutional concentration measure as in HS (AHS (p12))

potentially downplaying the relative strength of institutions compared with other

shareholders They justify this because there is generally more than one institutional

investor and there will be free-riding problems with multiple investors that only the

largest institutional investors can overcome While we accept their premise of free-rider

problems it is not obvious why the deflator is lsquoinstitutional shareholdingrsquo rather than

lsquototal shareholdingrsquo from this perspective7 If the strength of the size control can be

queried scaling by total shareholding (ie Top 5 Ownership) produces a measure that

remains relatively unaffected across the size deciles It is 20 percent for the smaller

decile declining to 14 percent for the largest decile whereas for the HS concentration

measure it declines by over 50 percent from 61 percent to 28 percent (see Table III and

Figure 1)

C Testing the Jensen-Murphy Measure of Incentives

The testing of their secondary measure of executive pay-for-performance sensitivity

(see HS Table IV) based on Jensen and Murphy (1990) raises issues other than the size

control HS regress changes in compensation (cash and total) on lagged institutional

influence that has been interacted with the contemporaneous change in shareholder

wealth to capture a pay-for-performance relationship Such a test is appealing ndash

7 AHS do point out one benefit of the institutional concentration measure Institutional investors may prefer

companies with lsquobetterrsquo incentive compensation structures Could using institutional shareholding rather

than total shareholding as the deflator alleviate this problem Presumably both the numerator and

denominator will have the same bias and hence error cancellation is a possibility

9

institutions should increase compensation when the firm has performed well Following

Greene (2000 p326) to execute such a test one needs to include in level form variables

that are then interacted Hence the HS model specification ought to be

1 2 3 1 4 1it it it it it itCompn SW IC SW IC (1)

where itCompn is the change in executive compensation itSW is the contemporaneous

change in shareholder wealth which also appears in the interaction term and 1itIC is

lagged institutional ownership concentration However HS (p2363) omit the

contemporaneous term itSW and the lagged term 1itIC which should appear in levels

as well as in the interaction term Most importantly HS interact their lagged institutional

concentration measure 1itIC with the contemporaneous change in shareholder wealth

itSW As it is after all pay-for-performance concentrated institutions need to condition

their influence on some observed measure of firm performance Contemporaneous firm

performance is unknown at the time institutional influence is measured Reflecting this

timing insight leads to a new Greene (2000) specification

1 2 1 3 1 4 1 1it it it it it itCompn SW IC SW IC (2)

such that all the lagged RHS independent variables that now appear in the interaction

term are included on a stand-alone basis

Reliance on incomplete self-reported values for option grants

Prior to receiving the HS dataset we tried to replicate the findings of HS to validate

our datasets for the HS period and the longer period 1992‒2002 While we initially

focused on the same period as HS (ie 1992‒1997) we found that our sample size was

larger at 47765 observations than HSrsquos at 33928 observations This discrepancy could

have arisen if HS did not replace missing and self-reported option valuations using their

10

Black-Scholes option methodology This may introduce a downward pay bias since self-

reported option-grant pay is subject to possible understatement and there are 13839

observations with likely high option pay dropped altogether

Endogeneity

HSrsquos endogeneity testing raises concerns about reverse causality Institutions may

prefer to hold firms with certain compensation structures such as incentivized executives

HS rightly highlight this concern and use instrumental variables to address this issue HS

assume that institutional ownership reflects any reverse causality Using an instrumental

variables approach to resolve this problem involves finding a variable that influences or

explains institutional ownership but not directly executive compensation They use share

turnover in a firm as an instrument for institutional ownership However theoretical work

by Holmstrom and Tirole (1993) indicates that measures of stock liquidity and trading

activity are indeed important determinants of executive market-based incentives as Kang

and Lui (2008) and Dikolli Kulp and Sedatole (2009) find empirically As such one can

make a case for adopting another instrument rather than share turnover for institutional

ownership

II Previous Research

Prior research fails to address issues concerning possible fragility of the HS results

AHS replicate the HS findings on both incentives and pay levels using the same dataset as

HS and they apply the same definition of institutional concentration and use market

capitalization expressed as a level Cadman Klasa and Matsunaga (2010 Table 6) set out

to replicate HSrsquos (Table II) model of option grant pay-for-performance sensitivity when

they compare a dataset of ExecuComp and Non-ExecuComp firms for the period 2000-

2007 Their ExecuComp results for this sample period are quite similar to our results for

11

the 1992‒2002 period for the same specification controlling for the logarithm of market

capitalization but they do not regard these results as a test of HS as their focus is entirely

on comparing the two groups of stocks Nor do they investigate the impact of

concentration on either cash compensation or total pay Kang and Liu (2008) examine

pay-performance sensitivity use a version of the HS institutional concentration measure

as a control variable in a different framework deriving from Holmstrom and Tirole

(1993) Dikolli Kulp and Sedatole (2009) argue that firms with transient ownership will

issue relatively more equity incentives to counter short-termism with their results robust

to the inclusion of the HS concentration variable

We hoped to find supportive evidence from proxy voting behavior in support of HSs

findings However evidence from actual mutual fund proxy voting records suggests that

most oppose reductions in CEO pay but overall the evidence is mixed8 Davis and Kim

(2005) examine proxy votes of mutual funds for 2004 and find that for a sample of

Fortune 1000 proxy contests in 45 cases that attempted to limit executive pay mutual

funds were unanimously opposed to such attempts Rothberg and Lilien (2006) also

examine proxy-voting data and find that mutual funds voted 66 percent of the time in

managementrsquos favor on issues of executive compensation Ertimur Ferri and Muslu

(2011) find that institutional investors lack sophistication in that they do not target

excessively paid CEOs relative to CEOs with high predicted-pay based on economic

determinants but exert a moderating influence ndash a $23 million reduction ndash for those they

deem ldquoexcessively paidrdquo CEOs

III Data and Methodology

8 We do acknowledge that the HS results are for all institutional investors while the transparency with

respect to proxy voting applies only to mutual funds

12

This Section discusses the data used in the study the construction of variables

descriptive statistics and the methodology Two datasets are used ndash one is the original

dataset generously supplied by Jay Hartzell and Laura Starks which covers 1992‒1997

second a more comprehensive dataset covering 1992‒2002 is computed from the same

data sources used in the HS dataset This is Standard and Poorrsquos (SampP) ExecuComp for

compensation data Thomson Financial CDASpectrum database for institutional holdings

to compute measure of institutional influence SampPrsquos Compustat and the Center for

Research in Stock Prices (CRSP) for firm level accounting and stock price data Our more

comprehensive dataset contains 2559 firms compared with 1914 for the HS dataset Our

full matched sample yields 97679 executive years

A Institutional Influence Measures

To measure institutional influence we employ two ownership-based metrics The first

measure of institutional influence is HSrsquos Institutional Concentration We use this for

direct comparison to the HS analysis The second measure of institutional influence

changes the denominator of the HS measure from institutional shares held to total shares

outstanding in the firm with nomenclature Top 5 Ownership9 We compute both

measures at the fiscal year end of the firm We adjust all compensation measures and

asset prices for inflation to 30 June 2002 prices for our comprehensive sample compared

to the HS dataset that is in the dollars of the day

B Compensation Measures

The ExecuComp database reports several raw measures of executive compensation for

the top five executives (where available) including total salary bonus long-term

9 Top 5 Ownership is included in the HS database but not utilized by them in reported tests as well as

constructed by us for the more comprehensive sample

13

incentives and number of option grants For our more comprehensive dataset we replicate

all the compensation measures used by HS In common with HS we compute the pay-for-

performance sensitivity of option grants using the Yermack (1995) approach This

measure shows the dollar change in value of the executive options for every dollar change

in the value of the firm This involves calculating the option delta using the Black-

Scholes formula adjusted for dividends10

The ratio of the number of shares represented

by the award of options divided by the diluted number of shares outstanding at the

beginning of the year multiplies the option delta with units given by a $1000 change in

firm value Summing salary bonus long-term incentive plan payouts and stock and

option grants provides total direct compensation Options are valued using the Black and

Scholes (1973) formula for European call options adjusted by Merton (1973) to

incorporate dividends

C Descriptive Statistics

Table I presents descriptive statistics of key variables employed in the study according

to our comprehensive dataset11

Institutions own on average 546 percent of the firms in

which they invest This is almost identical to the 531 percent found by HS The

institutions with the five largest holdings account 45 percent of institutional ownership

Once again the figure for HS is almost identical at 44 percent The institutions with the

five largest holdings own on average 229 percent of shares outstanding in a firm (HS

have 223 percent) Average total compensation for executives is $2583 million

considerably larger than that documented by HS ($1250 million) but the HS figure is an

10 When there is more than one grant during the year a weighted average delta is used

11 With the data supplied to us by Hartzell and Starks we are able to replicate exactly their summary data

(HS Table I) for all but cash compensation Salary is included but bonus payments are missing The

replicated table is available on request

14

amalgam of price levels over their sample period 1992‒1997 and ours are in consistent

dollars of June 30 2002 However there has also been significant growth in

compensation levels from 1998 to 2002

ltltINSERT TABLE Igtgt

Based on our comprehensive data in Table II we examine correlations between the

key variables employed in the study Of concern is the large negative correlation of 63

percent which has been discussed previously (Section IIA) between the HS measure of

institutional concentration and the natural logarithm of firm market capitalization

ltltINSERT TABLE IIgtgt

In view of this high correlation Table III provides a breakdown of the three key pay

variables and three institutional ownership variables by size deciles We find that the high

institutional concentration but low institutional ownership share of total shareholdings

mentioned above is evident in the smallest decile of firms by size This decile has low

salary and even lower total compensation in a relative sense but by far the highest pay-

for-performance sensitivity of option grants Small firms award executives a far higher

proportion of market capitalization Since small firm market-capitalization is negligible in

comparison with the highest decile (300 times larger in magnitude) total compensation is

very small in absolute value Moreover due to the domination of the pay-size effect base

salaries are also exceedingly small

ltltINSERT TABLE IIIgtgt

Figure 1 based on Table III shows how as institutional concentration falls with

increases in stock size (but also as the total share of institutional ownership increases)

and the pay-for-performance sensitivity of option grants falls Thus because of what

appears to be a weak size control and size-influenced concentration measure HS

15

potentially pick up a size effect as their main result but not necessarily a monitoring

effect Figure 2 shows that as firm size increases up to decile 8 at least the share of

institutional total ownership increases as does total compensation

ltltINSERT FIGURES 1 AND 2 gtgt

D Methodology

Following HS we use two estimation techniques to examine the effect of institutional

investor influence on executive compensation Due to the censored nature of option grant

pay-for-performance sensitivity this compensation measure most appropriately uses

Tobit model specification whereas an Ordinary Least Squares (OLS) model specification

is used for all other compensation measures We model compensation measures as a

function of contemporaneous and lagged change in shareholder wealth institutional

influence Tobinrsquos Q and market capitalization Controls for CEO industry and year

effects are also used Augmentation occurs to test the effect of institutional influence on

the change in executive cash and total compensation with an interaction term that is the

product of institutional influence and the change in shareholder wealth

The variables used to model executive compensation have the following definitions

The lagged and contemporary measure of change in shareholder wealth is simply the

difference in market capitalization of the firm The measures of institutional influence

used are Institutional Concentration and Top 5 Ownership Use of the two types of

institutional influence occurs in separate models In order to replicate the HS

methodology models using Institutional Concentration have an additional control

consisting of lagged total institutional holdings and Tobinrsquos Q controls for performance

and growth opportunities Market capitalization of the firm is the number of shares

outstanding multiplied by the share price with inclusion both in levels and natural

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 4: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

4

logarithmic transformation While this skewed nature of the level of market capitalization

does not per se rule out its use specification tests such as Box-Cox and the replacement

of market capitalization by its cumulative distribution (see Section VI below) indicates a

possible specification error Moreover using the lagged natural logarithm of market

capitalization as a firm size control in the actual HS data with the same dependent

variable and no other changes raises the explanatory power (R-Squared) of the HS model

by between 135 and 1516 percent4

Given that firm size is an important determinant of executive compensation selecting

the correct functional form for firm size is a vexing and important issue Many estimates

including those of Murphy (1985) Rosen (1992) Gibbons and Murphy (1992) Huson

Parrino and Starks (2001) Baker and Hall (2004) Gabaix and Landier (2008) Edmans

Gabaix and Landier (2009) Babenko (2009) and Aggarwal Erel and Ferreira (2011)

use a logarithmic specification with the elasticity between firm size and executive total

pay in the range of 03 and 04 HS seems to employ inadvertently a firm size measure in

levels (also alternative firm size measures also in levels) and consequently imply an

elasticity value (exponent on market capitalization) of unity

Second we question the use of the HS Top 5 Concentration measure of institutional

influence based on the influence of concentrated institutional investors relative to their

peers that appears to lead inadvertently to an exacerbation of the size-control problem In

their companion theoretical model AHS arrive at a different and what might seem a more

natural specification namely Top 5 Ownership which measures concentration relative to

all shareholders not just institutional peers The following example illustrates the

4 The lower result is based on OLS regressions of model 1 of Table II of HS with the R-Squared rising from

00853 to 00968 once Market Capitalization is logged and the higher result model 1 of Table V of HS is

based on an improvement in R-Squared from 04604 to 05302 (see Table VI below)

5

differences between these two methods If there are one hundred shares outstanding in a

small company and the only institution owns one share that company is concentrated

according even though that institution may lack effective monitoring power Instead if

one deflates by shares on issue this results in a concentration ratio of 1100 If on the

other hand ten institutions collectively own 500 shares in a much larger company of

1000 shares and the Top Five collectively own 250 then the HS concentration ratio falls

to only 250500 or 05 and utilizing shares on issue 025 in this case As is confirmed by

the data one expects Top 5 Concentration to correlate negatively with firm size and Top

5 Ownership the reverse given a positive association between institutional ownership and

company size We then re-examine the monitoring hypothesis using this AHS proposed

measure of institutional investor influence that intuitively relates better to institutional

proxy voting power

Third we address issues of reliance on potentially biased self-reported values of option

grants that result in the exclusion of 16 percent of the HS sample size for tests on total

(direct) compensation Forth we argue that tests that HS perform using an alternative

measure of pay-for-performance sensitivity to provide support for the main hypothesis of

the study require one to get the timing right in terms of the lag structure of performance

and concentration Finally we address issues associated with their tests of endogeneity

and reverse causality These issues collectively might suggest overlooking of a

monitoring effect with the main driving forces size related

The next section reviews the HS study in an effort to tease out what might really be

going on Section II examines the literature for studies that in replicating HS provide

independent support for their findings It also reports findings on the actual proxy voting

record of mutual funds and actions of institutional investors in reducing pay Section III

describes the data and methodology Section IV analyzes the relation between

6

institutional influence and measures of pay-for-performance sensitivity Section V

documents the relationship between institutional influence and total and fixed

compensation Section VI examines the robustness of our findings and the final Section

concludes

I Review of Hartzell and Starks Methodology

We comment on five areas of the HS methodology 1) Size control 2) Measurement of

institutional influence 3) Testing the Jensen-Murphy measure of incentives 4) Reliance

on incomplete self-reported valued for option grants and 5) Endogeneity

A Size Control

In our paper we argue that HS unintentionally identify incentive-size and pay-size

effects5 not a monitoring effect It can be seen in Figure II that executive total pay for

HSrsquos Top 5 institutional concentration measure rises from as little as $072m for the

smallest market capitalization decile to $85m for the highest This twelve-fold pay-size

effect in the deciles can cause problems if one utilizes an untransformed size measure

Due to skewness in the size measure using this in its untransformed state appears to

weaken its effectiveness leaving open the possibility that correlations they identify

between incentives and pay levels on the one hand and Top 5 Concentration on the other

are due largely to size-related effects

Table III displays this strong pay-size effect based on our full 1992‒2002 dataset and

graphically in Figure 1 It shows that the incentive measure adopted by HS declines from

$272 per $1000 change in shareholder wealth for the smallest market capitalization

decile of firms to approximately $030 for the largest Table III and Figure 1 show the

5 The multiplicative model of Edmans Gabaix and Landier (2009) finds that incentive pay increases with

firm size (elasticity value of 13) and the empirical elasticity is 037

7

strong relation between institutional concentration as measured by HS and market

capitalization For the smallest decile of market capitalization firms institutional

concentration averages 61 percent declining to about 275 percent for the highest decile

This negative relationship between firm size and institutional concentration seems to arise

because institutional investors do generally favor small firms This causes problems

because in the limit a small company may have only one institutional investor owning

only a small percentage of the company Hence it would appear to be fully concentrated

even though the ability of the institutional investor to influence pay decisions might be

small Thus it is not at all surprising that the correlation between the logarithm of market

capitalization and their institutional concentration measure is both negative and high in

absolute value at 63 percent Their methodology appears to favor small companies that

Table III shows to have low pay levels and high pay for performance sensitivity

Moreover if one does not transform the raw size measure it implicitly assumes that a

given dollar change in firm size has the same absolute impact on pay for a very large

company as it does for a small company Indeed the conventional logarithmic

specification for firm size provides proportionate effects that imply a pay-size elasticity of

approximately one-third instead of unity6

B Measurement of Institutional Influence

We argue that there are additional issues related to the HS measure of institutional

influence ndash institutional concentration In their companion article to HS AHS develop a

model where they capture institutional influence by a single large long-term institutional

6 Note that unlike an earlier version of our paper we leave the HS dependent variables in levels and hence

untransformed While we do this to minimize the alterations that we make to the HS specification ideally

the elasticity specification is preferable especially for the compensation variables Transforming the

dependent variables does not significantly affect the results

8

investor They measure influence relative to total shareholding including private or

atomistic shareholders Presumably they do this to capture relative activism and proxy

voting strength However when it comes to the empirical implementation of the model

AHS adopt the same relative institutional concentration measure as in HS (AHS (p12))

potentially downplaying the relative strength of institutions compared with other

shareholders They justify this because there is generally more than one institutional

investor and there will be free-riding problems with multiple investors that only the

largest institutional investors can overcome While we accept their premise of free-rider

problems it is not obvious why the deflator is lsquoinstitutional shareholdingrsquo rather than

lsquototal shareholdingrsquo from this perspective7 If the strength of the size control can be

queried scaling by total shareholding (ie Top 5 Ownership) produces a measure that

remains relatively unaffected across the size deciles It is 20 percent for the smaller

decile declining to 14 percent for the largest decile whereas for the HS concentration

measure it declines by over 50 percent from 61 percent to 28 percent (see Table III and

Figure 1)

C Testing the Jensen-Murphy Measure of Incentives

The testing of their secondary measure of executive pay-for-performance sensitivity

(see HS Table IV) based on Jensen and Murphy (1990) raises issues other than the size

control HS regress changes in compensation (cash and total) on lagged institutional

influence that has been interacted with the contemporaneous change in shareholder

wealth to capture a pay-for-performance relationship Such a test is appealing ndash

7 AHS do point out one benefit of the institutional concentration measure Institutional investors may prefer

companies with lsquobetterrsquo incentive compensation structures Could using institutional shareholding rather

than total shareholding as the deflator alleviate this problem Presumably both the numerator and

denominator will have the same bias and hence error cancellation is a possibility

9

institutions should increase compensation when the firm has performed well Following

Greene (2000 p326) to execute such a test one needs to include in level form variables

that are then interacted Hence the HS model specification ought to be

1 2 3 1 4 1it it it it it itCompn SW IC SW IC (1)

where itCompn is the change in executive compensation itSW is the contemporaneous

change in shareholder wealth which also appears in the interaction term and 1itIC is

lagged institutional ownership concentration However HS (p2363) omit the

contemporaneous term itSW and the lagged term 1itIC which should appear in levels

as well as in the interaction term Most importantly HS interact their lagged institutional

concentration measure 1itIC with the contemporaneous change in shareholder wealth

itSW As it is after all pay-for-performance concentrated institutions need to condition

their influence on some observed measure of firm performance Contemporaneous firm

performance is unknown at the time institutional influence is measured Reflecting this

timing insight leads to a new Greene (2000) specification

1 2 1 3 1 4 1 1it it it it it itCompn SW IC SW IC (2)

such that all the lagged RHS independent variables that now appear in the interaction

term are included on a stand-alone basis

Reliance on incomplete self-reported values for option grants

Prior to receiving the HS dataset we tried to replicate the findings of HS to validate

our datasets for the HS period and the longer period 1992‒2002 While we initially

focused on the same period as HS (ie 1992‒1997) we found that our sample size was

larger at 47765 observations than HSrsquos at 33928 observations This discrepancy could

have arisen if HS did not replace missing and self-reported option valuations using their

10

Black-Scholes option methodology This may introduce a downward pay bias since self-

reported option-grant pay is subject to possible understatement and there are 13839

observations with likely high option pay dropped altogether

Endogeneity

HSrsquos endogeneity testing raises concerns about reverse causality Institutions may

prefer to hold firms with certain compensation structures such as incentivized executives

HS rightly highlight this concern and use instrumental variables to address this issue HS

assume that institutional ownership reflects any reverse causality Using an instrumental

variables approach to resolve this problem involves finding a variable that influences or

explains institutional ownership but not directly executive compensation They use share

turnover in a firm as an instrument for institutional ownership However theoretical work

by Holmstrom and Tirole (1993) indicates that measures of stock liquidity and trading

activity are indeed important determinants of executive market-based incentives as Kang

and Lui (2008) and Dikolli Kulp and Sedatole (2009) find empirically As such one can

make a case for adopting another instrument rather than share turnover for institutional

ownership

II Previous Research

Prior research fails to address issues concerning possible fragility of the HS results

AHS replicate the HS findings on both incentives and pay levels using the same dataset as

HS and they apply the same definition of institutional concentration and use market

capitalization expressed as a level Cadman Klasa and Matsunaga (2010 Table 6) set out

to replicate HSrsquos (Table II) model of option grant pay-for-performance sensitivity when

they compare a dataset of ExecuComp and Non-ExecuComp firms for the period 2000-

2007 Their ExecuComp results for this sample period are quite similar to our results for

11

the 1992‒2002 period for the same specification controlling for the logarithm of market

capitalization but they do not regard these results as a test of HS as their focus is entirely

on comparing the two groups of stocks Nor do they investigate the impact of

concentration on either cash compensation or total pay Kang and Liu (2008) examine

pay-performance sensitivity use a version of the HS institutional concentration measure

as a control variable in a different framework deriving from Holmstrom and Tirole

(1993) Dikolli Kulp and Sedatole (2009) argue that firms with transient ownership will

issue relatively more equity incentives to counter short-termism with their results robust

to the inclusion of the HS concentration variable

We hoped to find supportive evidence from proxy voting behavior in support of HSs

findings However evidence from actual mutual fund proxy voting records suggests that

most oppose reductions in CEO pay but overall the evidence is mixed8 Davis and Kim

(2005) examine proxy votes of mutual funds for 2004 and find that for a sample of

Fortune 1000 proxy contests in 45 cases that attempted to limit executive pay mutual

funds were unanimously opposed to such attempts Rothberg and Lilien (2006) also

examine proxy-voting data and find that mutual funds voted 66 percent of the time in

managementrsquos favor on issues of executive compensation Ertimur Ferri and Muslu

(2011) find that institutional investors lack sophistication in that they do not target

excessively paid CEOs relative to CEOs with high predicted-pay based on economic

determinants but exert a moderating influence ndash a $23 million reduction ndash for those they

deem ldquoexcessively paidrdquo CEOs

III Data and Methodology

8 We do acknowledge that the HS results are for all institutional investors while the transparency with

respect to proxy voting applies only to mutual funds

12

This Section discusses the data used in the study the construction of variables

descriptive statistics and the methodology Two datasets are used ndash one is the original

dataset generously supplied by Jay Hartzell and Laura Starks which covers 1992‒1997

second a more comprehensive dataset covering 1992‒2002 is computed from the same

data sources used in the HS dataset This is Standard and Poorrsquos (SampP) ExecuComp for

compensation data Thomson Financial CDASpectrum database for institutional holdings

to compute measure of institutional influence SampPrsquos Compustat and the Center for

Research in Stock Prices (CRSP) for firm level accounting and stock price data Our more

comprehensive dataset contains 2559 firms compared with 1914 for the HS dataset Our

full matched sample yields 97679 executive years

A Institutional Influence Measures

To measure institutional influence we employ two ownership-based metrics The first

measure of institutional influence is HSrsquos Institutional Concentration We use this for

direct comparison to the HS analysis The second measure of institutional influence

changes the denominator of the HS measure from institutional shares held to total shares

outstanding in the firm with nomenclature Top 5 Ownership9 We compute both

measures at the fiscal year end of the firm We adjust all compensation measures and

asset prices for inflation to 30 June 2002 prices for our comprehensive sample compared

to the HS dataset that is in the dollars of the day

B Compensation Measures

The ExecuComp database reports several raw measures of executive compensation for

the top five executives (where available) including total salary bonus long-term

9 Top 5 Ownership is included in the HS database but not utilized by them in reported tests as well as

constructed by us for the more comprehensive sample

13

incentives and number of option grants For our more comprehensive dataset we replicate

all the compensation measures used by HS In common with HS we compute the pay-for-

performance sensitivity of option grants using the Yermack (1995) approach This

measure shows the dollar change in value of the executive options for every dollar change

in the value of the firm This involves calculating the option delta using the Black-

Scholes formula adjusted for dividends10

The ratio of the number of shares represented

by the award of options divided by the diluted number of shares outstanding at the

beginning of the year multiplies the option delta with units given by a $1000 change in

firm value Summing salary bonus long-term incentive plan payouts and stock and

option grants provides total direct compensation Options are valued using the Black and

Scholes (1973) formula for European call options adjusted by Merton (1973) to

incorporate dividends

C Descriptive Statistics

Table I presents descriptive statistics of key variables employed in the study according

to our comprehensive dataset11

Institutions own on average 546 percent of the firms in

which they invest This is almost identical to the 531 percent found by HS The

institutions with the five largest holdings account 45 percent of institutional ownership

Once again the figure for HS is almost identical at 44 percent The institutions with the

five largest holdings own on average 229 percent of shares outstanding in a firm (HS

have 223 percent) Average total compensation for executives is $2583 million

considerably larger than that documented by HS ($1250 million) but the HS figure is an

10 When there is more than one grant during the year a weighted average delta is used

11 With the data supplied to us by Hartzell and Starks we are able to replicate exactly their summary data

(HS Table I) for all but cash compensation Salary is included but bonus payments are missing The

replicated table is available on request

14

amalgam of price levels over their sample period 1992‒1997 and ours are in consistent

dollars of June 30 2002 However there has also been significant growth in

compensation levels from 1998 to 2002

ltltINSERT TABLE Igtgt

Based on our comprehensive data in Table II we examine correlations between the

key variables employed in the study Of concern is the large negative correlation of 63

percent which has been discussed previously (Section IIA) between the HS measure of

institutional concentration and the natural logarithm of firm market capitalization

ltltINSERT TABLE IIgtgt

In view of this high correlation Table III provides a breakdown of the three key pay

variables and three institutional ownership variables by size deciles We find that the high

institutional concentration but low institutional ownership share of total shareholdings

mentioned above is evident in the smallest decile of firms by size This decile has low

salary and even lower total compensation in a relative sense but by far the highest pay-

for-performance sensitivity of option grants Small firms award executives a far higher

proportion of market capitalization Since small firm market-capitalization is negligible in

comparison with the highest decile (300 times larger in magnitude) total compensation is

very small in absolute value Moreover due to the domination of the pay-size effect base

salaries are also exceedingly small

ltltINSERT TABLE IIIgtgt

Figure 1 based on Table III shows how as institutional concentration falls with

increases in stock size (but also as the total share of institutional ownership increases)

and the pay-for-performance sensitivity of option grants falls Thus because of what

appears to be a weak size control and size-influenced concentration measure HS

15

potentially pick up a size effect as their main result but not necessarily a monitoring

effect Figure 2 shows that as firm size increases up to decile 8 at least the share of

institutional total ownership increases as does total compensation

ltltINSERT FIGURES 1 AND 2 gtgt

D Methodology

Following HS we use two estimation techniques to examine the effect of institutional

investor influence on executive compensation Due to the censored nature of option grant

pay-for-performance sensitivity this compensation measure most appropriately uses

Tobit model specification whereas an Ordinary Least Squares (OLS) model specification

is used for all other compensation measures We model compensation measures as a

function of contemporaneous and lagged change in shareholder wealth institutional

influence Tobinrsquos Q and market capitalization Controls for CEO industry and year

effects are also used Augmentation occurs to test the effect of institutional influence on

the change in executive cash and total compensation with an interaction term that is the

product of institutional influence and the change in shareholder wealth

The variables used to model executive compensation have the following definitions

The lagged and contemporary measure of change in shareholder wealth is simply the

difference in market capitalization of the firm The measures of institutional influence

used are Institutional Concentration and Top 5 Ownership Use of the two types of

institutional influence occurs in separate models In order to replicate the HS

methodology models using Institutional Concentration have an additional control

consisting of lagged total institutional holdings and Tobinrsquos Q controls for performance

and growth opportunities Market capitalization of the firm is the number of shares

outstanding multiplied by the share price with inclusion both in levels and natural

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 5: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

5

differences between these two methods If there are one hundred shares outstanding in a

small company and the only institution owns one share that company is concentrated

according even though that institution may lack effective monitoring power Instead if

one deflates by shares on issue this results in a concentration ratio of 1100 If on the

other hand ten institutions collectively own 500 shares in a much larger company of

1000 shares and the Top Five collectively own 250 then the HS concentration ratio falls

to only 250500 or 05 and utilizing shares on issue 025 in this case As is confirmed by

the data one expects Top 5 Concentration to correlate negatively with firm size and Top

5 Ownership the reverse given a positive association between institutional ownership and

company size We then re-examine the monitoring hypothesis using this AHS proposed

measure of institutional investor influence that intuitively relates better to institutional

proxy voting power

Third we address issues of reliance on potentially biased self-reported values of option

grants that result in the exclusion of 16 percent of the HS sample size for tests on total

(direct) compensation Forth we argue that tests that HS perform using an alternative

measure of pay-for-performance sensitivity to provide support for the main hypothesis of

the study require one to get the timing right in terms of the lag structure of performance

and concentration Finally we address issues associated with their tests of endogeneity

and reverse causality These issues collectively might suggest overlooking of a

monitoring effect with the main driving forces size related

The next section reviews the HS study in an effort to tease out what might really be

going on Section II examines the literature for studies that in replicating HS provide

independent support for their findings It also reports findings on the actual proxy voting

record of mutual funds and actions of institutional investors in reducing pay Section III

describes the data and methodology Section IV analyzes the relation between

6

institutional influence and measures of pay-for-performance sensitivity Section V

documents the relationship between institutional influence and total and fixed

compensation Section VI examines the robustness of our findings and the final Section

concludes

I Review of Hartzell and Starks Methodology

We comment on five areas of the HS methodology 1) Size control 2) Measurement of

institutional influence 3) Testing the Jensen-Murphy measure of incentives 4) Reliance

on incomplete self-reported valued for option grants and 5) Endogeneity

A Size Control

In our paper we argue that HS unintentionally identify incentive-size and pay-size

effects5 not a monitoring effect It can be seen in Figure II that executive total pay for

HSrsquos Top 5 institutional concentration measure rises from as little as $072m for the

smallest market capitalization decile to $85m for the highest This twelve-fold pay-size

effect in the deciles can cause problems if one utilizes an untransformed size measure

Due to skewness in the size measure using this in its untransformed state appears to

weaken its effectiveness leaving open the possibility that correlations they identify

between incentives and pay levels on the one hand and Top 5 Concentration on the other

are due largely to size-related effects

Table III displays this strong pay-size effect based on our full 1992‒2002 dataset and

graphically in Figure 1 It shows that the incentive measure adopted by HS declines from

$272 per $1000 change in shareholder wealth for the smallest market capitalization

decile of firms to approximately $030 for the largest Table III and Figure 1 show the

5 The multiplicative model of Edmans Gabaix and Landier (2009) finds that incentive pay increases with

firm size (elasticity value of 13) and the empirical elasticity is 037

7

strong relation between institutional concentration as measured by HS and market

capitalization For the smallest decile of market capitalization firms institutional

concentration averages 61 percent declining to about 275 percent for the highest decile

This negative relationship between firm size and institutional concentration seems to arise

because institutional investors do generally favor small firms This causes problems

because in the limit a small company may have only one institutional investor owning

only a small percentage of the company Hence it would appear to be fully concentrated

even though the ability of the institutional investor to influence pay decisions might be

small Thus it is not at all surprising that the correlation between the logarithm of market

capitalization and their institutional concentration measure is both negative and high in

absolute value at 63 percent Their methodology appears to favor small companies that

Table III shows to have low pay levels and high pay for performance sensitivity

Moreover if one does not transform the raw size measure it implicitly assumes that a

given dollar change in firm size has the same absolute impact on pay for a very large

company as it does for a small company Indeed the conventional logarithmic

specification for firm size provides proportionate effects that imply a pay-size elasticity of

approximately one-third instead of unity6

B Measurement of Institutional Influence

We argue that there are additional issues related to the HS measure of institutional

influence ndash institutional concentration In their companion article to HS AHS develop a

model where they capture institutional influence by a single large long-term institutional

6 Note that unlike an earlier version of our paper we leave the HS dependent variables in levels and hence

untransformed While we do this to minimize the alterations that we make to the HS specification ideally

the elasticity specification is preferable especially for the compensation variables Transforming the

dependent variables does not significantly affect the results

8

investor They measure influence relative to total shareholding including private or

atomistic shareholders Presumably they do this to capture relative activism and proxy

voting strength However when it comes to the empirical implementation of the model

AHS adopt the same relative institutional concentration measure as in HS (AHS (p12))

potentially downplaying the relative strength of institutions compared with other

shareholders They justify this because there is generally more than one institutional

investor and there will be free-riding problems with multiple investors that only the

largest institutional investors can overcome While we accept their premise of free-rider

problems it is not obvious why the deflator is lsquoinstitutional shareholdingrsquo rather than

lsquototal shareholdingrsquo from this perspective7 If the strength of the size control can be

queried scaling by total shareholding (ie Top 5 Ownership) produces a measure that

remains relatively unaffected across the size deciles It is 20 percent for the smaller

decile declining to 14 percent for the largest decile whereas for the HS concentration

measure it declines by over 50 percent from 61 percent to 28 percent (see Table III and

Figure 1)

C Testing the Jensen-Murphy Measure of Incentives

The testing of their secondary measure of executive pay-for-performance sensitivity

(see HS Table IV) based on Jensen and Murphy (1990) raises issues other than the size

control HS regress changes in compensation (cash and total) on lagged institutional

influence that has been interacted with the contemporaneous change in shareholder

wealth to capture a pay-for-performance relationship Such a test is appealing ndash

7 AHS do point out one benefit of the institutional concentration measure Institutional investors may prefer

companies with lsquobetterrsquo incentive compensation structures Could using institutional shareholding rather

than total shareholding as the deflator alleviate this problem Presumably both the numerator and

denominator will have the same bias and hence error cancellation is a possibility

9

institutions should increase compensation when the firm has performed well Following

Greene (2000 p326) to execute such a test one needs to include in level form variables

that are then interacted Hence the HS model specification ought to be

1 2 3 1 4 1it it it it it itCompn SW IC SW IC (1)

where itCompn is the change in executive compensation itSW is the contemporaneous

change in shareholder wealth which also appears in the interaction term and 1itIC is

lagged institutional ownership concentration However HS (p2363) omit the

contemporaneous term itSW and the lagged term 1itIC which should appear in levels

as well as in the interaction term Most importantly HS interact their lagged institutional

concentration measure 1itIC with the contemporaneous change in shareholder wealth

itSW As it is after all pay-for-performance concentrated institutions need to condition

their influence on some observed measure of firm performance Contemporaneous firm

performance is unknown at the time institutional influence is measured Reflecting this

timing insight leads to a new Greene (2000) specification

1 2 1 3 1 4 1 1it it it it it itCompn SW IC SW IC (2)

such that all the lagged RHS independent variables that now appear in the interaction

term are included on a stand-alone basis

Reliance on incomplete self-reported values for option grants

Prior to receiving the HS dataset we tried to replicate the findings of HS to validate

our datasets for the HS period and the longer period 1992‒2002 While we initially

focused on the same period as HS (ie 1992‒1997) we found that our sample size was

larger at 47765 observations than HSrsquos at 33928 observations This discrepancy could

have arisen if HS did not replace missing and self-reported option valuations using their

10

Black-Scholes option methodology This may introduce a downward pay bias since self-

reported option-grant pay is subject to possible understatement and there are 13839

observations with likely high option pay dropped altogether

Endogeneity

HSrsquos endogeneity testing raises concerns about reverse causality Institutions may

prefer to hold firms with certain compensation structures such as incentivized executives

HS rightly highlight this concern and use instrumental variables to address this issue HS

assume that institutional ownership reflects any reverse causality Using an instrumental

variables approach to resolve this problem involves finding a variable that influences or

explains institutional ownership but not directly executive compensation They use share

turnover in a firm as an instrument for institutional ownership However theoretical work

by Holmstrom and Tirole (1993) indicates that measures of stock liquidity and trading

activity are indeed important determinants of executive market-based incentives as Kang

and Lui (2008) and Dikolli Kulp and Sedatole (2009) find empirically As such one can

make a case for adopting another instrument rather than share turnover for institutional

ownership

II Previous Research

Prior research fails to address issues concerning possible fragility of the HS results

AHS replicate the HS findings on both incentives and pay levels using the same dataset as

HS and they apply the same definition of institutional concentration and use market

capitalization expressed as a level Cadman Klasa and Matsunaga (2010 Table 6) set out

to replicate HSrsquos (Table II) model of option grant pay-for-performance sensitivity when

they compare a dataset of ExecuComp and Non-ExecuComp firms for the period 2000-

2007 Their ExecuComp results for this sample period are quite similar to our results for

11

the 1992‒2002 period for the same specification controlling for the logarithm of market

capitalization but they do not regard these results as a test of HS as their focus is entirely

on comparing the two groups of stocks Nor do they investigate the impact of

concentration on either cash compensation or total pay Kang and Liu (2008) examine

pay-performance sensitivity use a version of the HS institutional concentration measure

as a control variable in a different framework deriving from Holmstrom and Tirole

(1993) Dikolli Kulp and Sedatole (2009) argue that firms with transient ownership will

issue relatively more equity incentives to counter short-termism with their results robust

to the inclusion of the HS concentration variable

We hoped to find supportive evidence from proxy voting behavior in support of HSs

findings However evidence from actual mutual fund proxy voting records suggests that

most oppose reductions in CEO pay but overall the evidence is mixed8 Davis and Kim

(2005) examine proxy votes of mutual funds for 2004 and find that for a sample of

Fortune 1000 proxy contests in 45 cases that attempted to limit executive pay mutual

funds were unanimously opposed to such attempts Rothberg and Lilien (2006) also

examine proxy-voting data and find that mutual funds voted 66 percent of the time in

managementrsquos favor on issues of executive compensation Ertimur Ferri and Muslu

(2011) find that institutional investors lack sophistication in that they do not target

excessively paid CEOs relative to CEOs with high predicted-pay based on economic

determinants but exert a moderating influence ndash a $23 million reduction ndash for those they

deem ldquoexcessively paidrdquo CEOs

III Data and Methodology

8 We do acknowledge that the HS results are for all institutional investors while the transparency with

respect to proxy voting applies only to mutual funds

12

This Section discusses the data used in the study the construction of variables

descriptive statistics and the methodology Two datasets are used ndash one is the original

dataset generously supplied by Jay Hartzell and Laura Starks which covers 1992‒1997

second a more comprehensive dataset covering 1992‒2002 is computed from the same

data sources used in the HS dataset This is Standard and Poorrsquos (SampP) ExecuComp for

compensation data Thomson Financial CDASpectrum database for institutional holdings

to compute measure of institutional influence SampPrsquos Compustat and the Center for

Research in Stock Prices (CRSP) for firm level accounting and stock price data Our more

comprehensive dataset contains 2559 firms compared with 1914 for the HS dataset Our

full matched sample yields 97679 executive years

A Institutional Influence Measures

To measure institutional influence we employ two ownership-based metrics The first

measure of institutional influence is HSrsquos Institutional Concentration We use this for

direct comparison to the HS analysis The second measure of institutional influence

changes the denominator of the HS measure from institutional shares held to total shares

outstanding in the firm with nomenclature Top 5 Ownership9 We compute both

measures at the fiscal year end of the firm We adjust all compensation measures and

asset prices for inflation to 30 June 2002 prices for our comprehensive sample compared

to the HS dataset that is in the dollars of the day

B Compensation Measures

The ExecuComp database reports several raw measures of executive compensation for

the top five executives (where available) including total salary bonus long-term

9 Top 5 Ownership is included in the HS database but not utilized by them in reported tests as well as

constructed by us for the more comprehensive sample

13

incentives and number of option grants For our more comprehensive dataset we replicate

all the compensation measures used by HS In common with HS we compute the pay-for-

performance sensitivity of option grants using the Yermack (1995) approach This

measure shows the dollar change in value of the executive options for every dollar change

in the value of the firm This involves calculating the option delta using the Black-

Scholes formula adjusted for dividends10

The ratio of the number of shares represented

by the award of options divided by the diluted number of shares outstanding at the

beginning of the year multiplies the option delta with units given by a $1000 change in

firm value Summing salary bonus long-term incentive plan payouts and stock and

option grants provides total direct compensation Options are valued using the Black and

Scholes (1973) formula for European call options adjusted by Merton (1973) to

incorporate dividends

C Descriptive Statistics

Table I presents descriptive statistics of key variables employed in the study according

to our comprehensive dataset11

Institutions own on average 546 percent of the firms in

which they invest This is almost identical to the 531 percent found by HS The

institutions with the five largest holdings account 45 percent of institutional ownership

Once again the figure for HS is almost identical at 44 percent The institutions with the

five largest holdings own on average 229 percent of shares outstanding in a firm (HS

have 223 percent) Average total compensation for executives is $2583 million

considerably larger than that documented by HS ($1250 million) but the HS figure is an

10 When there is more than one grant during the year a weighted average delta is used

11 With the data supplied to us by Hartzell and Starks we are able to replicate exactly their summary data

(HS Table I) for all but cash compensation Salary is included but bonus payments are missing The

replicated table is available on request

14

amalgam of price levels over their sample period 1992‒1997 and ours are in consistent

dollars of June 30 2002 However there has also been significant growth in

compensation levels from 1998 to 2002

ltltINSERT TABLE Igtgt

Based on our comprehensive data in Table II we examine correlations between the

key variables employed in the study Of concern is the large negative correlation of 63

percent which has been discussed previously (Section IIA) between the HS measure of

institutional concentration and the natural logarithm of firm market capitalization

ltltINSERT TABLE IIgtgt

In view of this high correlation Table III provides a breakdown of the three key pay

variables and three institutional ownership variables by size deciles We find that the high

institutional concentration but low institutional ownership share of total shareholdings

mentioned above is evident in the smallest decile of firms by size This decile has low

salary and even lower total compensation in a relative sense but by far the highest pay-

for-performance sensitivity of option grants Small firms award executives a far higher

proportion of market capitalization Since small firm market-capitalization is negligible in

comparison with the highest decile (300 times larger in magnitude) total compensation is

very small in absolute value Moreover due to the domination of the pay-size effect base

salaries are also exceedingly small

ltltINSERT TABLE IIIgtgt

Figure 1 based on Table III shows how as institutional concentration falls with

increases in stock size (but also as the total share of institutional ownership increases)

and the pay-for-performance sensitivity of option grants falls Thus because of what

appears to be a weak size control and size-influenced concentration measure HS

15

potentially pick up a size effect as their main result but not necessarily a monitoring

effect Figure 2 shows that as firm size increases up to decile 8 at least the share of

institutional total ownership increases as does total compensation

ltltINSERT FIGURES 1 AND 2 gtgt

D Methodology

Following HS we use two estimation techniques to examine the effect of institutional

investor influence on executive compensation Due to the censored nature of option grant

pay-for-performance sensitivity this compensation measure most appropriately uses

Tobit model specification whereas an Ordinary Least Squares (OLS) model specification

is used for all other compensation measures We model compensation measures as a

function of contemporaneous and lagged change in shareholder wealth institutional

influence Tobinrsquos Q and market capitalization Controls for CEO industry and year

effects are also used Augmentation occurs to test the effect of institutional influence on

the change in executive cash and total compensation with an interaction term that is the

product of institutional influence and the change in shareholder wealth

The variables used to model executive compensation have the following definitions

The lagged and contemporary measure of change in shareholder wealth is simply the

difference in market capitalization of the firm The measures of institutional influence

used are Institutional Concentration and Top 5 Ownership Use of the two types of

institutional influence occurs in separate models In order to replicate the HS

methodology models using Institutional Concentration have an additional control

consisting of lagged total institutional holdings and Tobinrsquos Q controls for performance

and growth opportunities Market capitalization of the firm is the number of shares

outstanding multiplied by the share price with inclusion both in levels and natural

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 6: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

6

institutional influence and measures of pay-for-performance sensitivity Section V

documents the relationship between institutional influence and total and fixed

compensation Section VI examines the robustness of our findings and the final Section

concludes

I Review of Hartzell and Starks Methodology

We comment on five areas of the HS methodology 1) Size control 2) Measurement of

institutional influence 3) Testing the Jensen-Murphy measure of incentives 4) Reliance

on incomplete self-reported valued for option grants and 5) Endogeneity

A Size Control

In our paper we argue that HS unintentionally identify incentive-size and pay-size

effects5 not a monitoring effect It can be seen in Figure II that executive total pay for

HSrsquos Top 5 institutional concentration measure rises from as little as $072m for the

smallest market capitalization decile to $85m for the highest This twelve-fold pay-size

effect in the deciles can cause problems if one utilizes an untransformed size measure

Due to skewness in the size measure using this in its untransformed state appears to

weaken its effectiveness leaving open the possibility that correlations they identify

between incentives and pay levels on the one hand and Top 5 Concentration on the other

are due largely to size-related effects

Table III displays this strong pay-size effect based on our full 1992‒2002 dataset and

graphically in Figure 1 It shows that the incentive measure adopted by HS declines from

$272 per $1000 change in shareholder wealth for the smallest market capitalization

decile of firms to approximately $030 for the largest Table III and Figure 1 show the

5 The multiplicative model of Edmans Gabaix and Landier (2009) finds that incentive pay increases with

firm size (elasticity value of 13) and the empirical elasticity is 037

7

strong relation between institutional concentration as measured by HS and market

capitalization For the smallest decile of market capitalization firms institutional

concentration averages 61 percent declining to about 275 percent for the highest decile

This negative relationship between firm size and institutional concentration seems to arise

because institutional investors do generally favor small firms This causes problems

because in the limit a small company may have only one institutional investor owning

only a small percentage of the company Hence it would appear to be fully concentrated

even though the ability of the institutional investor to influence pay decisions might be

small Thus it is not at all surprising that the correlation between the logarithm of market

capitalization and their institutional concentration measure is both negative and high in

absolute value at 63 percent Their methodology appears to favor small companies that

Table III shows to have low pay levels and high pay for performance sensitivity

Moreover if one does not transform the raw size measure it implicitly assumes that a

given dollar change in firm size has the same absolute impact on pay for a very large

company as it does for a small company Indeed the conventional logarithmic

specification for firm size provides proportionate effects that imply a pay-size elasticity of

approximately one-third instead of unity6

B Measurement of Institutional Influence

We argue that there are additional issues related to the HS measure of institutional

influence ndash institutional concentration In their companion article to HS AHS develop a

model where they capture institutional influence by a single large long-term institutional

6 Note that unlike an earlier version of our paper we leave the HS dependent variables in levels and hence

untransformed While we do this to minimize the alterations that we make to the HS specification ideally

the elasticity specification is preferable especially for the compensation variables Transforming the

dependent variables does not significantly affect the results

8

investor They measure influence relative to total shareholding including private or

atomistic shareholders Presumably they do this to capture relative activism and proxy

voting strength However when it comes to the empirical implementation of the model

AHS adopt the same relative institutional concentration measure as in HS (AHS (p12))

potentially downplaying the relative strength of institutions compared with other

shareholders They justify this because there is generally more than one institutional

investor and there will be free-riding problems with multiple investors that only the

largest institutional investors can overcome While we accept their premise of free-rider

problems it is not obvious why the deflator is lsquoinstitutional shareholdingrsquo rather than

lsquototal shareholdingrsquo from this perspective7 If the strength of the size control can be

queried scaling by total shareholding (ie Top 5 Ownership) produces a measure that

remains relatively unaffected across the size deciles It is 20 percent for the smaller

decile declining to 14 percent for the largest decile whereas for the HS concentration

measure it declines by over 50 percent from 61 percent to 28 percent (see Table III and

Figure 1)

C Testing the Jensen-Murphy Measure of Incentives

The testing of their secondary measure of executive pay-for-performance sensitivity

(see HS Table IV) based on Jensen and Murphy (1990) raises issues other than the size

control HS regress changes in compensation (cash and total) on lagged institutional

influence that has been interacted with the contemporaneous change in shareholder

wealth to capture a pay-for-performance relationship Such a test is appealing ndash

7 AHS do point out one benefit of the institutional concentration measure Institutional investors may prefer

companies with lsquobetterrsquo incentive compensation structures Could using institutional shareholding rather

than total shareholding as the deflator alleviate this problem Presumably both the numerator and

denominator will have the same bias and hence error cancellation is a possibility

9

institutions should increase compensation when the firm has performed well Following

Greene (2000 p326) to execute such a test one needs to include in level form variables

that are then interacted Hence the HS model specification ought to be

1 2 3 1 4 1it it it it it itCompn SW IC SW IC (1)

where itCompn is the change in executive compensation itSW is the contemporaneous

change in shareholder wealth which also appears in the interaction term and 1itIC is

lagged institutional ownership concentration However HS (p2363) omit the

contemporaneous term itSW and the lagged term 1itIC which should appear in levels

as well as in the interaction term Most importantly HS interact their lagged institutional

concentration measure 1itIC with the contemporaneous change in shareholder wealth

itSW As it is after all pay-for-performance concentrated institutions need to condition

their influence on some observed measure of firm performance Contemporaneous firm

performance is unknown at the time institutional influence is measured Reflecting this

timing insight leads to a new Greene (2000) specification

1 2 1 3 1 4 1 1it it it it it itCompn SW IC SW IC (2)

such that all the lagged RHS independent variables that now appear in the interaction

term are included on a stand-alone basis

Reliance on incomplete self-reported values for option grants

Prior to receiving the HS dataset we tried to replicate the findings of HS to validate

our datasets for the HS period and the longer period 1992‒2002 While we initially

focused on the same period as HS (ie 1992‒1997) we found that our sample size was

larger at 47765 observations than HSrsquos at 33928 observations This discrepancy could

have arisen if HS did not replace missing and self-reported option valuations using their

10

Black-Scholes option methodology This may introduce a downward pay bias since self-

reported option-grant pay is subject to possible understatement and there are 13839

observations with likely high option pay dropped altogether

Endogeneity

HSrsquos endogeneity testing raises concerns about reverse causality Institutions may

prefer to hold firms with certain compensation structures such as incentivized executives

HS rightly highlight this concern and use instrumental variables to address this issue HS

assume that institutional ownership reflects any reverse causality Using an instrumental

variables approach to resolve this problem involves finding a variable that influences or

explains institutional ownership but not directly executive compensation They use share

turnover in a firm as an instrument for institutional ownership However theoretical work

by Holmstrom and Tirole (1993) indicates that measures of stock liquidity and trading

activity are indeed important determinants of executive market-based incentives as Kang

and Lui (2008) and Dikolli Kulp and Sedatole (2009) find empirically As such one can

make a case for adopting another instrument rather than share turnover for institutional

ownership

II Previous Research

Prior research fails to address issues concerning possible fragility of the HS results

AHS replicate the HS findings on both incentives and pay levels using the same dataset as

HS and they apply the same definition of institutional concentration and use market

capitalization expressed as a level Cadman Klasa and Matsunaga (2010 Table 6) set out

to replicate HSrsquos (Table II) model of option grant pay-for-performance sensitivity when

they compare a dataset of ExecuComp and Non-ExecuComp firms for the period 2000-

2007 Their ExecuComp results for this sample period are quite similar to our results for

11

the 1992‒2002 period for the same specification controlling for the logarithm of market

capitalization but they do not regard these results as a test of HS as their focus is entirely

on comparing the two groups of stocks Nor do they investigate the impact of

concentration on either cash compensation or total pay Kang and Liu (2008) examine

pay-performance sensitivity use a version of the HS institutional concentration measure

as a control variable in a different framework deriving from Holmstrom and Tirole

(1993) Dikolli Kulp and Sedatole (2009) argue that firms with transient ownership will

issue relatively more equity incentives to counter short-termism with their results robust

to the inclusion of the HS concentration variable

We hoped to find supportive evidence from proxy voting behavior in support of HSs

findings However evidence from actual mutual fund proxy voting records suggests that

most oppose reductions in CEO pay but overall the evidence is mixed8 Davis and Kim

(2005) examine proxy votes of mutual funds for 2004 and find that for a sample of

Fortune 1000 proxy contests in 45 cases that attempted to limit executive pay mutual

funds were unanimously opposed to such attempts Rothberg and Lilien (2006) also

examine proxy-voting data and find that mutual funds voted 66 percent of the time in

managementrsquos favor on issues of executive compensation Ertimur Ferri and Muslu

(2011) find that institutional investors lack sophistication in that they do not target

excessively paid CEOs relative to CEOs with high predicted-pay based on economic

determinants but exert a moderating influence ndash a $23 million reduction ndash for those they

deem ldquoexcessively paidrdquo CEOs

III Data and Methodology

8 We do acknowledge that the HS results are for all institutional investors while the transparency with

respect to proxy voting applies only to mutual funds

12

This Section discusses the data used in the study the construction of variables

descriptive statistics and the methodology Two datasets are used ndash one is the original

dataset generously supplied by Jay Hartzell and Laura Starks which covers 1992‒1997

second a more comprehensive dataset covering 1992‒2002 is computed from the same

data sources used in the HS dataset This is Standard and Poorrsquos (SampP) ExecuComp for

compensation data Thomson Financial CDASpectrum database for institutional holdings

to compute measure of institutional influence SampPrsquos Compustat and the Center for

Research in Stock Prices (CRSP) for firm level accounting and stock price data Our more

comprehensive dataset contains 2559 firms compared with 1914 for the HS dataset Our

full matched sample yields 97679 executive years

A Institutional Influence Measures

To measure institutional influence we employ two ownership-based metrics The first

measure of institutional influence is HSrsquos Institutional Concentration We use this for

direct comparison to the HS analysis The second measure of institutional influence

changes the denominator of the HS measure from institutional shares held to total shares

outstanding in the firm with nomenclature Top 5 Ownership9 We compute both

measures at the fiscal year end of the firm We adjust all compensation measures and

asset prices for inflation to 30 June 2002 prices for our comprehensive sample compared

to the HS dataset that is in the dollars of the day

B Compensation Measures

The ExecuComp database reports several raw measures of executive compensation for

the top five executives (where available) including total salary bonus long-term

9 Top 5 Ownership is included in the HS database but not utilized by them in reported tests as well as

constructed by us for the more comprehensive sample

13

incentives and number of option grants For our more comprehensive dataset we replicate

all the compensation measures used by HS In common with HS we compute the pay-for-

performance sensitivity of option grants using the Yermack (1995) approach This

measure shows the dollar change in value of the executive options for every dollar change

in the value of the firm This involves calculating the option delta using the Black-

Scholes formula adjusted for dividends10

The ratio of the number of shares represented

by the award of options divided by the diluted number of shares outstanding at the

beginning of the year multiplies the option delta with units given by a $1000 change in

firm value Summing salary bonus long-term incentive plan payouts and stock and

option grants provides total direct compensation Options are valued using the Black and

Scholes (1973) formula for European call options adjusted by Merton (1973) to

incorporate dividends

C Descriptive Statistics

Table I presents descriptive statistics of key variables employed in the study according

to our comprehensive dataset11

Institutions own on average 546 percent of the firms in

which they invest This is almost identical to the 531 percent found by HS The

institutions with the five largest holdings account 45 percent of institutional ownership

Once again the figure for HS is almost identical at 44 percent The institutions with the

five largest holdings own on average 229 percent of shares outstanding in a firm (HS

have 223 percent) Average total compensation for executives is $2583 million

considerably larger than that documented by HS ($1250 million) but the HS figure is an

10 When there is more than one grant during the year a weighted average delta is used

11 With the data supplied to us by Hartzell and Starks we are able to replicate exactly their summary data

(HS Table I) for all but cash compensation Salary is included but bonus payments are missing The

replicated table is available on request

14

amalgam of price levels over their sample period 1992‒1997 and ours are in consistent

dollars of June 30 2002 However there has also been significant growth in

compensation levels from 1998 to 2002

ltltINSERT TABLE Igtgt

Based on our comprehensive data in Table II we examine correlations between the

key variables employed in the study Of concern is the large negative correlation of 63

percent which has been discussed previously (Section IIA) between the HS measure of

institutional concentration and the natural logarithm of firm market capitalization

ltltINSERT TABLE IIgtgt

In view of this high correlation Table III provides a breakdown of the three key pay

variables and three institutional ownership variables by size deciles We find that the high

institutional concentration but low institutional ownership share of total shareholdings

mentioned above is evident in the smallest decile of firms by size This decile has low

salary and even lower total compensation in a relative sense but by far the highest pay-

for-performance sensitivity of option grants Small firms award executives a far higher

proportion of market capitalization Since small firm market-capitalization is negligible in

comparison with the highest decile (300 times larger in magnitude) total compensation is

very small in absolute value Moreover due to the domination of the pay-size effect base

salaries are also exceedingly small

ltltINSERT TABLE IIIgtgt

Figure 1 based on Table III shows how as institutional concentration falls with

increases in stock size (but also as the total share of institutional ownership increases)

and the pay-for-performance sensitivity of option grants falls Thus because of what

appears to be a weak size control and size-influenced concentration measure HS

15

potentially pick up a size effect as their main result but not necessarily a monitoring

effect Figure 2 shows that as firm size increases up to decile 8 at least the share of

institutional total ownership increases as does total compensation

ltltINSERT FIGURES 1 AND 2 gtgt

D Methodology

Following HS we use two estimation techniques to examine the effect of institutional

investor influence on executive compensation Due to the censored nature of option grant

pay-for-performance sensitivity this compensation measure most appropriately uses

Tobit model specification whereas an Ordinary Least Squares (OLS) model specification

is used for all other compensation measures We model compensation measures as a

function of contemporaneous and lagged change in shareholder wealth institutional

influence Tobinrsquos Q and market capitalization Controls for CEO industry and year

effects are also used Augmentation occurs to test the effect of institutional influence on

the change in executive cash and total compensation with an interaction term that is the

product of institutional influence and the change in shareholder wealth

The variables used to model executive compensation have the following definitions

The lagged and contemporary measure of change in shareholder wealth is simply the

difference in market capitalization of the firm The measures of institutional influence

used are Institutional Concentration and Top 5 Ownership Use of the two types of

institutional influence occurs in separate models In order to replicate the HS

methodology models using Institutional Concentration have an additional control

consisting of lagged total institutional holdings and Tobinrsquos Q controls for performance

and growth opportunities Market capitalization of the firm is the number of shares

outstanding multiplied by the share price with inclusion both in levels and natural

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 7: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

7

strong relation between institutional concentration as measured by HS and market

capitalization For the smallest decile of market capitalization firms institutional

concentration averages 61 percent declining to about 275 percent for the highest decile

This negative relationship between firm size and institutional concentration seems to arise

because institutional investors do generally favor small firms This causes problems

because in the limit a small company may have only one institutional investor owning

only a small percentage of the company Hence it would appear to be fully concentrated

even though the ability of the institutional investor to influence pay decisions might be

small Thus it is not at all surprising that the correlation between the logarithm of market

capitalization and their institutional concentration measure is both negative and high in

absolute value at 63 percent Their methodology appears to favor small companies that

Table III shows to have low pay levels and high pay for performance sensitivity

Moreover if one does not transform the raw size measure it implicitly assumes that a

given dollar change in firm size has the same absolute impact on pay for a very large

company as it does for a small company Indeed the conventional logarithmic

specification for firm size provides proportionate effects that imply a pay-size elasticity of

approximately one-third instead of unity6

B Measurement of Institutional Influence

We argue that there are additional issues related to the HS measure of institutional

influence ndash institutional concentration In their companion article to HS AHS develop a

model where they capture institutional influence by a single large long-term institutional

6 Note that unlike an earlier version of our paper we leave the HS dependent variables in levels and hence

untransformed While we do this to minimize the alterations that we make to the HS specification ideally

the elasticity specification is preferable especially for the compensation variables Transforming the

dependent variables does not significantly affect the results

8

investor They measure influence relative to total shareholding including private or

atomistic shareholders Presumably they do this to capture relative activism and proxy

voting strength However when it comes to the empirical implementation of the model

AHS adopt the same relative institutional concentration measure as in HS (AHS (p12))

potentially downplaying the relative strength of institutions compared with other

shareholders They justify this because there is generally more than one institutional

investor and there will be free-riding problems with multiple investors that only the

largest institutional investors can overcome While we accept their premise of free-rider

problems it is not obvious why the deflator is lsquoinstitutional shareholdingrsquo rather than

lsquototal shareholdingrsquo from this perspective7 If the strength of the size control can be

queried scaling by total shareholding (ie Top 5 Ownership) produces a measure that

remains relatively unaffected across the size deciles It is 20 percent for the smaller

decile declining to 14 percent for the largest decile whereas for the HS concentration

measure it declines by over 50 percent from 61 percent to 28 percent (see Table III and

Figure 1)

C Testing the Jensen-Murphy Measure of Incentives

The testing of their secondary measure of executive pay-for-performance sensitivity

(see HS Table IV) based on Jensen and Murphy (1990) raises issues other than the size

control HS regress changes in compensation (cash and total) on lagged institutional

influence that has been interacted with the contemporaneous change in shareholder

wealth to capture a pay-for-performance relationship Such a test is appealing ndash

7 AHS do point out one benefit of the institutional concentration measure Institutional investors may prefer

companies with lsquobetterrsquo incentive compensation structures Could using institutional shareholding rather

than total shareholding as the deflator alleviate this problem Presumably both the numerator and

denominator will have the same bias and hence error cancellation is a possibility

9

institutions should increase compensation when the firm has performed well Following

Greene (2000 p326) to execute such a test one needs to include in level form variables

that are then interacted Hence the HS model specification ought to be

1 2 3 1 4 1it it it it it itCompn SW IC SW IC (1)

where itCompn is the change in executive compensation itSW is the contemporaneous

change in shareholder wealth which also appears in the interaction term and 1itIC is

lagged institutional ownership concentration However HS (p2363) omit the

contemporaneous term itSW and the lagged term 1itIC which should appear in levels

as well as in the interaction term Most importantly HS interact their lagged institutional

concentration measure 1itIC with the contemporaneous change in shareholder wealth

itSW As it is after all pay-for-performance concentrated institutions need to condition

their influence on some observed measure of firm performance Contemporaneous firm

performance is unknown at the time institutional influence is measured Reflecting this

timing insight leads to a new Greene (2000) specification

1 2 1 3 1 4 1 1it it it it it itCompn SW IC SW IC (2)

such that all the lagged RHS independent variables that now appear in the interaction

term are included on a stand-alone basis

Reliance on incomplete self-reported values for option grants

Prior to receiving the HS dataset we tried to replicate the findings of HS to validate

our datasets for the HS period and the longer period 1992‒2002 While we initially

focused on the same period as HS (ie 1992‒1997) we found that our sample size was

larger at 47765 observations than HSrsquos at 33928 observations This discrepancy could

have arisen if HS did not replace missing and self-reported option valuations using their

10

Black-Scholes option methodology This may introduce a downward pay bias since self-

reported option-grant pay is subject to possible understatement and there are 13839

observations with likely high option pay dropped altogether

Endogeneity

HSrsquos endogeneity testing raises concerns about reverse causality Institutions may

prefer to hold firms with certain compensation structures such as incentivized executives

HS rightly highlight this concern and use instrumental variables to address this issue HS

assume that institutional ownership reflects any reverse causality Using an instrumental

variables approach to resolve this problem involves finding a variable that influences or

explains institutional ownership but not directly executive compensation They use share

turnover in a firm as an instrument for institutional ownership However theoretical work

by Holmstrom and Tirole (1993) indicates that measures of stock liquidity and trading

activity are indeed important determinants of executive market-based incentives as Kang

and Lui (2008) and Dikolli Kulp and Sedatole (2009) find empirically As such one can

make a case for adopting another instrument rather than share turnover for institutional

ownership

II Previous Research

Prior research fails to address issues concerning possible fragility of the HS results

AHS replicate the HS findings on both incentives and pay levels using the same dataset as

HS and they apply the same definition of institutional concentration and use market

capitalization expressed as a level Cadman Klasa and Matsunaga (2010 Table 6) set out

to replicate HSrsquos (Table II) model of option grant pay-for-performance sensitivity when

they compare a dataset of ExecuComp and Non-ExecuComp firms for the period 2000-

2007 Their ExecuComp results for this sample period are quite similar to our results for

11

the 1992‒2002 period for the same specification controlling for the logarithm of market

capitalization but they do not regard these results as a test of HS as their focus is entirely

on comparing the two groups of stocks Nor do they investigate the impact of

concentration on either cash compensation or total pay Kang and Liu (2008) examine

pay-performance sensitivity use a version of the HS institutional concentration measure

as a control variable in a different framework deriving from Holmstrom and Tirole

(1993) Dikolli Kulp and Sedatole (2009) argue that firms with transient ownership will

issue relatively more equity incentives to counter short-termism with their results robust

to the inclusion of the HS concentration variable

We hoped to find supportive evidence from proxy voting behavior in support of HSs

findings However evidence from actual mutual fund proxy voting records suggests that

most oppose reductions in CEO pay but overall the evidence is mixed8 Davis and Kim

(2005) examine proxy votes of mutual funds for 2004 and find that for a sample of

Fortune 1000 proxy contests in 45 cases that attempted to limit executive pay mutual

funds were unanimously opposed to such attempts Rothberg and Lilien (2006) also

examine proxy-voting data and find that mutual funds voted 66 percent of the time in

managementrsquos favor on issues of executive compensation Ertimur Ferri and Muslu

(2011) find that institutional investors lack sophistication in that they do not target

excessively paid CEOs relative to CEOs with high predicted-pay based on economic

determinants but exert a moderating influence ndash a $23 million reduction ndash for those they

deem ldquoexcessively paidrdquo CEOs

III Data and Methodology

8 We do acknowledge that the HS results are for all institutional investors while the transparency with

respect to proxy voting applies only to mutual funds

12

This Section discusses the data used in the study the construction of variables

descriptive statistics and the methodology Two datasets are used ndash one is the original

dataset generously supplied by Jay Hartzell and Laura Starks which covers 1992‒1997

second a more comprehensive dataset covering 1992‒2002 is computed from the same

data sources used in the HS dataset This is Standard and Poorrsquos (SampP) ExecuComp for

compensation data Thomson Financial CDASpectrum database for institutional holdings

to compute measure of institutional influence SampPrsquos Compustat and the Center for

Research in Stock Prices (CRSP) for firm level accounting and stock price data Our more

comprehensive dataset contains 2559 firms compared with 1914 for the HS dataset Our

full matched sample yields 97679 executive years

A Institutional Influence Measures

To measure institutional influence we employ two ownership-based metrics The first

measure of institutional influence is HSrsquos Institutional Concentration We use this for

direct comparison to the HS analysis The second measure of institutional influence

changes the denominator of the HS measure from institutional shares held to total shares

outstanding in the firm with nomenclature Top 5 Ownership9 We compute both

measures at the fiscal year end of the firm We adjust all compensation measures and

asset prices for inflation to 30 June 2002 prices for our comprehensive sample compared

to the HS dataset that is in the dollars of the day

B Compensation Measures

The ExecuComp database reports several raw measures of executive compensation for

the top five executives (where available) including total salary bonus long-term

9 Top 5 Ownership is included in the HS database but not utilized by them in reported tests as well as

constructed by us for the more comprehensive sample

13

incentives and number of option grants For our more comprehensive dataset we replicate

all the compensation measures used by HS In common with HS we compute the pay-for-

performance sensitivity of option grants using the Yermack (1995) approach This

measure shows the dollar change in value of the executive options for every dollar change

in the value of the firm This involves calculating the option delta using the Black-

Scholes formula adjusted for dividends10

The ratio of the number of shares represented

by the award of options divided by the diluted number of shares outstanding at the

beginning of the year multiplies the option delta with units given by a $1000 change in

firm value Summing salary bonus long-term incentive plan payouts and stock and

option grants provides total direct compensation Options are valued using the Black and

Scholes (1973) formula for European call options adjusted by Merton (1973) to

incorporate dividends

C Descriptive Statistics

Table I presents descriptive statistics of key variables employed in the study according

to our comprehensive dataset11

Institutions own on average 546 percent of the firms in

which they invest This is almost identical to the 531 percent found by HS The

institutions with the five largest holdings account 45 percent of institutional ownership

Once again the figure for HS is almost identical at 44 percent The institutions with the

five largest holdings own on average 229 percent of shares outstanding in a firm (HS

have 223 percent) Average total compensation for executives is $2583 million

considerably larger than that documented by HS ($1250 million) but the HS figure is an

10 When there is more than one grant during the year a weighted average delta is used

11 With the data supplied to us by Hartzell and Starks we are able to replicate exactly their summary data

(HS Table I) for all but cash compensation Salary is included but bonus payments are missing The

replicated table is available on request

14

amalgam of price levels over their sample period 1992‒1997 and ours are in consistent

dollars of June 30 2002 However there has also been significant growth in

compensation levels from 1998 to 2002

ltltINSERT TABLE Igtgt

Based on our comprehensive data in Table II we examine correlations between the

key variables employed in the study Of concern is the large negative correlation of 63

percent which has been discussed previously (Section IIA) between the HS measure of

institutional concentration and the natural logarithm of firm market capitalization

ltltINSERT TABLE IIgtgt

In view of this high correlation Table III provides a breakdown of the three key pay

variables and three institutional ownership variables by size deciles We find that the high

institutional concentration but low institutional ownership share of total shareholdings

mentioned above is evident in the smallest decile of firms by size This decile has low

salary and even lower total compensation in a relative sense but by far the highest pay-

for-performance sensitivity of option grants Small firms award executives a far higher

proportion of market capitalization Since small firm market-capitalization is negligible in

comparison with the highest decile (300 times larger in magnitude) total compensation is

very small in absolute value Moreover due to the domination of the pay-size effect base

salaries are also exceedingly small

ltltINSERT TABLE IIIgtgt

Figure 1 based on Table III shows how as institutional concentration falls with

increases in stock size (but also as the total share of institutional ownership increases)

and the pay-for-performance sensitivity of option grants falls Thus because of what

appears to be a weak size control and size-influenced concentration measure HS

15

potentially pick up a size effect as their main result but not necessarily a monitoring

effect Figure 2 shows that as firm size increases up to decile 8 at least the share of

institutional total ownership increases as does total compensation

ltltINSERT FIGURES 1 AND 2 gtgt

D Methodology

Following HS we use two estimation techniques to examine the effect of institutional

investor influence on executive compensation Due to the censored nature of option grant

pay-for-performance sensitivity this compensation measure most appropriately uses

Tobit model specification whereas an Ordinary Least Squares (OLS) model specification

is used for all other compensation measures We model compensation measures as a

function of contemporaneous and lagged change in shareholder wealth institutional

influence Tobinrsquos Q and market capitalization Controls for CEO industry and year

effects are also used Augmentation occurs to test the effect of institutional influence on

the change in executive cash and total compensation with an interaction term that is the

product of institutional influence and the change in shareholder wealth

The variables used to model executive compensation have the following definitions

The lagged and contemporary measure of change in shareholder wealth is simply the

difference in market capitalization of the firm The measures of institutional influence

used are Institutional Concentration and Top 5 Ownership Use of the two types of

institutional influence occurs in separate models In order to replicate the HS

methodology models using Institutional Concentration have an additional control

consisting of lagged total institutional holdings and Tobinrsquos Q controls for performance

and growth opportunities Market capitalization of the firm is the number of shares

outstanding multiplied by the share price with inclusion both in levels and natural

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 8: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

8

investor They measure influence relative to total shareholding including private or

atomistic shareholders Presumably they do this to capture relative activism and proxy

voting strength However when it comes to the empirical implementation of the model

AHS adopt the same relative institutional concentration measure as in HS (AHS (p12))

potentially downplaying the relative strength of institutions compared with other

shareholders They justify this because there is generally more than one institutional

investor and there will be free-riding problems with multiple investors that only the

largest institutional investors can overcome While we accept their premise of free-rider

problems it is not obvious why the deflator is lsquoinstitutional shareholdingrsquo rather than

lsquototal shareholdingrsquo from this perspective7 If the strength of the size control can be

queried scaling by total shareholding (ie Top 5 Ownership) produces a measure that

remains relatively unaffected across the size deciles It is 20 percent for the smaller

decile declining to 14 percent for the largest decile whereas for the HS concentration

measure it declines by over 50 percent from 61 percent to 28 percent (see Table III and

Figure 1)

C Testing the Jensen-Murphy Measure of Incentives

The testing of their secondary measure of executive pay-for-performance sensitivity

(see HS Table IV) based on Jensen and Murphy (1990) raises issues other than the size

control HS regress changes in compensation (cash and total) on lagged institutional

influence that has been interacted with the contemporaneous change in shareholder

wealth to capture a pay-for-performance relationship Such a test is appealing ndash

7 AHS do point out one benefit of the institutional concentration measure Institutional investors may prefer

companies with lsquobetterrsquo incentive compensation structures Could using institutional shareholding rather

than total shareholding as the deflator alleviate this problem Presumably both the numerator and

denominator will have the same bias and hence error cancellation is a possibility

9

institutions should increase compensation when the firm has performed well Following

Greene (2000 p326) to execute such a test one needs to include in level form variables

that are then interacted Hence the HS model specification ought to be

1 2 3 1 4 1it it it it it itCompn SW IC SW IC (1)

where itCompn is the change in executive compensation itSW is the contemporaneous

change in shareholder wealth which also appears in the interaction term and 1itIC is

lagged institutional ownership concentration However HS (p2363) omit the

contemporaneous term itSW and the lagged term 1itIC which should appear in levels

as well as in the interaction term Most importantly HS interact their lagged institutional

concentration measure 1itIC with the contemporaneous change in shareholder wealth

itSW As it is after all pay-for-performance concentrated institutions need to condition

their influence on some observed measure of firm performance Contemporaneous firm

performance is unknown at the time institutional influence is measured Reflecting this

timing insight leads to a new Greene (2000) specification

1 2 1 3 1 4 1 1it it it it it itCompn SW IC SW IC (2)

such that all the lagged RHS independent variables that now appear in the interaction

term are included on a stand-alone basis

Reliance on incomplete self-reported values for option grants

Prior to receiving the HS dataset we tried to replicate the findings of HS to validate

our datasets for the HS period and the longer period 1992‒2002 While we initially

focused on the same period as HS (ie 1992‒1997) we found that our sample size was

larger at 47765 observations than HSrsquos at 33928 observations This discrepancy could

have arisen if HS did not replace missing and self-reported option valuations using their

10

Black-Scholes option methodology This may introduce a downward pay bias since self-

reported option-grant pay is subject to possible understatement and there are 13839

observations with likely high option pay dropped altogether

Endogeneity

HSrsquos endogeneity testing raises concerns about reverse causality Institutions may

prefer to hold firms with certain compensation structures such as incentivized executives

HS rightly highlight this concern and use instrumental variables to address this issue HS

assume that institutional ownership reflects any reverse causality Using an instrumental

variables approach to resolve this problem involves finding a variable that influences or

explains institutional ownership but not directly executive compensation They use share

turnover in a firm as an instrument for institutional ownership However theoretical work

by Holmstrom and Tirole (1993) indicates that measures of stock liquidity and trading

activity are indeed important determinants of executive market-based incentives as Kang

and Lui (2008) and Dikolli Kulp and Sedatole (2009) find empirically As such one can

make a case for adopting another instrument rather than share turnover for institutional

ownership

II Previous Research

Prior research fails to address issues concerning possible fragility of the HS results

AHS replicate the HS findings on both incentives and pay levels using the same dataset as

HS and they apply the same definition of institutional concentration and use market

capitalization expressed as a level Cadman Klasa and Matsunaga (2010 Table 6) set out

to replicate HSrsquos (Table II) model of option grant pay-for-performance sensitivity when

they compare a dataset of ExecuComp and Non-ExecuComp firms for the period 2000-

2007 Their ExecuComp results for this sample period are quite similar to our results for

11

the 1992‒2002 period for the same specification controlling for the logarithm of market

capitalization but they do not regard these results as a test of HS as their focus is entirely

on comparing the two groups of stocks Nor do they investigate the impact of

concentration on either cash compensation or total pay Kang and Liu (2008) examine

pay-performance sensitivity use a version of the HS institutional concentration measure

as a control variable in a different framework deriving from Holmstrom and Tirole

(1993) Dikolli Kulp and Sedatole (2009) argue that firms with transient ownership will

issue relatively more equity incentives to counter short-termism with their results robust

to the inclusion of the HS concentration variable

We hoped to find supportive evidence from proxy voting behavior in support of HSs

findings However evidence from actual mutual fund proxy voting records suggests that

most oppose reductions in CEO pay but overall the evidence is mixed8 Davis and Kim

(2005) examine proxy votes of mutual funds for 2004 and find that for a sample of

Fortune 1000 proxy contests in 45 cases that attempted to limit executive pay mutual

funds were unanimously opposed to such attempts Rothberg and Lilien (2006) also

examine proxy-voting data and find that mutual funds voted 66 percent of the time in

managementrsquos favor on issues of executive compensation Ertimur Ferri and Muslu

(2011) find that institutional investors lack sophistication in that they do not target

excessively paid CEOs relative to CEOs with high predicted-pay based on economic

determinants but exert a moderating influence ndash a $23 million reduction ndash for those they

deem ldquoexcessively paidrdquo CEOs

III Data and Methodology

8 We do acknowledge that the HS results are for all institutional investors while the transparency with

respect to proxy voting applies only to mutual funds

12

This Section discusses the data used in the study the construction of variables

descriptive statistics and the methodology Two datasets are used ndash one is the original

dataset generously supplied by Jay Hartzell and Laura Starks which covers 1992‒1997

second a more comprehensive dataset covering 1992‒2002 is computed from the same

data sources used in the HS dataset This is Standard and Poorrsquos (SampP) ExecuComp for

compensation data Thomson Financial CDASpectrum database for institutional holdings

to compute measure of institutional influence SampPrsquos Compustat and the Center for

Research in Stock Prices (CRSP) for firm level accounting and stock price data Our more

comprehensive dataset contains 2559 firms compared with 1914 for the HS dataset Our

full matched sample yields 97679 executive years

A Institutional Influence Measures

To measure institutional influence we employ two ownership-based metrics The first

measure of institutional influence is HSrsquos Institutional Concentration We use this for

direct comparison to the HS analysis The second measure of institutional influence

changes the denominator of the HS measure from institutional shares held to total shares

outstanding in the firm with nomenclature Top 5 Ownership9 We compute both

measures at the fiscal year end of the firm We adjust all compensation measures and

asset prices for inflation to 30 June 2002 prices for our comprehensive sample compared

to the HS dataset that is in the dollars of the day

B Compensation Measures

The ExecuComp database reports several raw measures of executive compensation for

the top five executives (where available) including total salary bonus long-term

9 Top 5 Ownership is included in the HS database but not utilized by them in reported tests as well as

constructed by us for the more comprehensive sample

13

incentives and number of option grants For our more comprehensive dataset we replicate

all the compensation measures used by HS In common with HS we compute the pay-for-

performance sensitivity of option grants using the Yermack (1995) approach This

measure shows the dollar change in value of the executive options for every dollar change

in the value of the firm This involves calculating the option delta using the Black-

Scholes formula adjusted for dividends10

The ratio of the number of shares represented

by the award of options divided by the diluted number of shares outstanding at the

beginning of the year multiplies the option delta with units given by a $1000 change in

firm value Summing salary bonus long-term incentive plan payouts and stock and

option grants provides total direct compensation Options are valued using the Black and

Scholes (1973) formula for European call options adjusted by Merton (1973) to

incorporate dividends

C Descriptive Statistics

Table I presents descriptive statistics of key variables employed in the study according

to our comprehensive dataset11

Institutions own on average 546 percent of the firms in

which they invest This is almost identical to the 531 percent found by HS The

institutions with the five largest holdings account 45 percent of institutional ownership

Once again the figure for HS is almost identical at 44 percent The institutions with the

five largest holdings own on average 229 percent of shares outstanding in a firm (HS

have 223 percent) Average total compensation for executives is $2583 million

considerably larger than that documented by HS ($1250 million) but the HS figure is an

10 When there is more than one grant during the year a weighted average delta is used

11 With the data supplied to us by Hartzell and Starks we are able to replicate exactly their summary data

(HS Table I) for all but cash compensation Salary is included but bonus payments are missing The

replicated table is available on request

14

amalgam of price levels over their sample period 1992‒1997 and ours are in consistent

dollars of June 30 2002 However there has also been significant growth in

compensation levels from 1998 to 2002

ltltINSERT TABLE Igtgt

Based on our comprehensive data in Table II we examine correlations between the

key variables employed in the study Of concern is the large negative correlation of 63

percent which has been discussed previously (Section IIA) between the HS measure of

institutional concentration and the natural logarithm of firm market capitalization

ltltINSERT TABLE IIgtgt

In view of this high correlation Table III provides a breakdown of the three key pay

variables and three institutional ownership variables by size deciles We find that the high

institutional concentration but low institutional ownership share of total shareholdings

mentioned above is evident in the smallest decile of firms by size This decile has low

salary and even lower total compensation in a relative sense but by far the highest pay-

for-performance sensitivity of option grants Small firms award executives a far higher

proportion of market capitalization Since small firm market-capitalization is negligible in

comparison with the highest decile (300 times larger in magnitude) total compensation is

very small in absolute value Moreover due to the domination of the pay-size effect base

salaries are also exceedingly small

ltltINSERT TABLE IIIgtgt

Figure 1 based on Table III shows how as institutional concentration falls with

increases in stock size (but also as the total share of institutional ownership increases)

and the pay-for-performance sensitivity of option grants falls Thus because of what

appears to be a weak size control and size-influenced concentration measure HS

15

potentially pick up a size effect as their main result but not necessarily a monitoring

effect Figure 2 shows that as firm size increases up to decile 8 at least the share of

institutional total ownership increases as does total compensation

ltltINSERT FIGURES 1 AND 2 gtgt

D Methodology

Following HS we use two estimation techniques to examine the effect of institutional

investor influence on executive compensation Due to the censored nature of option grant

pay-for-performance sensitivity this compensation measure most appropriately uses

Tobit model specification whereas an Ordinary Least Squares (OLS) model specification

is used for all other compensation measures We model compensation measures as a

function of contemporaneous and lagged change in shareholder wealth institutional

influence Tobinrsquos Q and market capitalization Controls for CEO industry and year

effects are also used Augmentation occurs to test the effect of institutional influence on

the change in executive cash and total compensation with an interaction term that is the

product of institutional influence and the change in shareholder wealth

The variables used to model executive compensation have the following definitions

The lagged and contemporary measure of change in shareholder wealth is simply the

difference in market capitalization of the firm The measures of institutional influence

used are Institutional Concentration and Top 5 Ownership Use of the two types of

institutional influence occurs in separate models In order to replicate the HS

methodology models using Institutional Concentration have an additional control

consisting of lagged total institutional holdings and Tobinrsquos Q controls for performance

and growth opportunities Market capitalization of the firm is the number of shares

outstanding multiplied by the share price with inclusion both in levels and natural

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 9: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

9

institutions should increase compensation when the firm has performed well Following

Greene (2000 p326) to execute such a test one needs to include in level form variables

that are then interacted Hence the HS model specification ought to be

1 2 3 1 4 1it it it it it itCompn SW IC SW IC (1)

where itCompn is the change in executive compensation itSW is the contemporaneous

change in shareholder wealth which also appears in the interaction term and 1itIC is

lagged institutional ownership concentration However HS (p2363) omit the

contemporaneous term itSW and the lagged term 1itIC which should appear in levels

as well as in the interaction term Most importantly HS interact their lagged institutional

concentration measure 1itIC with the contemporaneous change in shareholder wealth

itSW As it is after all pay-for-performance concentrated institutions need to condition

their influence on some observed measure of firm performance Contemporaneous firm

performance is unknown at the time institutional influence is measured Reflecting this

timing insight leads to a new Greene (2000) specification

1 2 1 3 1 4 1 1it it it it it itCompn SW IC SW IC (2)

such that all the lagged RHS independent variables that now appear in the interaction

term are included on a stand-alone basis

Reliance on incomplete self-reported values for option grants

Prior to receiving the HS dataset we tried to replicate the findings of HS to validate

our datasets for the HS period and the longer period 1992‒2002 While we initially

focused on the same period as HS (ie 1992‒1997) we found that our sample size was

larger at 47765 observations than HSrsquos at 33928 observations This discrepancy could

have arisen if HS did not replace missing and self-reported option valuations using their

10

Black-Scholes option methodology This may introduce a downward pay bias since self-

reported option-grant pay is subject to possible understatement and there are 13839

observations with likely high option pay dropped altogether

Endogeneity

HSrsquos endogeneity testing raises concerns about reverse causality Institutions may

prefer to hold firms with certain compensation structures such as incentivized executives

HS rightly highlight this concern and use instrumental variables to address this issue HS

assume that institutional ownership reflects any reverse causality Using an instrumental

variables approach to resolve this problem involves finding a variable that influences or

explains institutional ownership but not directly executive compensation They use share

turnover in a firm as an instrument for institutional ownership However theoretical work

by Holmstrom and Tirole (1993) indicates that measures of stock liquidity and trading

activity are indeed important determinants of executive market-based incentives as Kang

and Lui (2008) and Dikolli Kulp and Sedatole (2009) find empirically As such one can

make a case for adopting another instrument rather than share turnover for institutional

ownership

II Previous Research

Prior research fails to address issues concerning possible fragility of the HS results

AHS replicate the HS findings on both incentives and pay levels using the same dataset as

HS and they apply the same definition of institutional concentration and use market

capitalization expressed as a level Cadman Klasa and Matsunaga (2010 Table 6) set out

to replicate HSrsquos (Table II) model of option grant pay-for-performance sensitivity when

they compare a dataset of ExecuComp and Non-ExecuComp firms for the period 2000-

2007 Their ExecuComp results for this sample period are quite similar to our results for

11

the 1992‒2002 period for the same specification controlling for the logarithm of market

capitalization but they do not regard these results as a test of HS as their focus is entirely

on comparing the two groups of stocks Nor do they investigate the impact of

concentration on either cash compensation or total pay Kang and Liu (2008) examine

pay-performance sensitivity use a version of the HS institutional concentration measure

as a control variable in a different framework deriving from Holmstrom and Tirole

(1993) Dikolli Kulp and Sedatole (2009) argue that firms with transient ownership will

issue relatively more equity incentives to counter short-termism with their results robust

to the inclusion of the HS concentration variable

We hoped to find supportive evidence from proxy voting behavior in support of HSs

findings However evidence from actual mutual fund proxy voting records suggests that

most oppose reductions in CEO pay but overall the evidence is mixed8 Davis and Kim

(2005) examine proxy votes of mutual funds for 2004 and find that for a sample of

Fortune 1000 proxy contests in 45 cases that attempted to limit executive pay mutual

funds were unanimously opposed to such attempts Rothberg and Lilien (2006) also

examine proxy-voting data and find that mutual funds voted 66 percent of the time in

managementrsquos favor on issues of executive compensation Ertimur Ferri and Muslu

(2011) find that institutional investors lack sophistication in that they do not target

excessively paid CEOs relative to CEOs with high predicted-pay based on economic

determinants but exert a moderating influence ndash a $23 million reduction ndash for those they

deem ldquoexcessively paidrdquo CEOs

III Data and Methodology

8 We do acknowledge that the HS results are for all institutional investors while the transparency with

respect to proxy voting applies only to mutual funds

12

This Section discusses the data used in the study the construction of variables

descriptive statistics and the methodology Two datasets are used ndash one is the original

dataset generously supplied by Jay Hartzell and Laura Starks which covers 1992‒1997

second a more comprehensive dataset covering 1992‒2002 is computed from the same

data sources used in the HS dataset This is Standard and Poorrsquos (SampP) ExecuComp for

compensation data Thomson Financial CDASpectrum database for institutional holdings

to compute measure of institutional influence SampPrsquos Compustat and the Center for

Research in Stock Prices (CRSP) for firm level accounting and stock price data Our more

comprehensive dataset contains 2559 firms compared with 1914 for the HS dataset Our

full matched sample yields 97679 executive years

A Institutional Influence Measures

To measure institutional influence we employ two ownership-based metrics The first

measure of institutional influence is HSrsquos Institutional Concentration We use this for

direct comparison to the HS analysis The second measure of institutional influence

changes the denominator of the HS measure from institutional shares held to total shares

outstanding in the firm with nomenclature Top 5 Ownership9 We compute both

measures at the fiscal year end of the firm We adjust all compensation measures and

asset prices for inflation to 30 June 2002 prices for our comprehensive sample compared

to the HS dataset that is in the dollars of the day

B Compensation Measures

The ExecuComp database reports several raw measures of executive compensation for

the top five executives (where available) including total salary bonus long-term

9 Top 5 Ownership is included in the HS database but not utilized by them in reported tests as well as

constructed by us for the more comprehensive sample

13

incentives and number of option grants For our more comprehensive dataset we replicate

all the compensation measures used by HS In common with HS we compute the pay-for-

performance sensitivity of option grants using the Yermack (1995) approach This

measure shows the dollar change in value of the executive options for every dollar change

in the value of the firm This involves calculating the option delta using the Black-

Scholes formula adjusted for dividends10

The ratio of the number of shares represented

by the award of options divided by the diluted number of shares outstanding at the

beginning of the year multiplies the option delta with units given by a $1000 change in

firm value Summing salary bonus long-term incentive plan payouts and stock and

option grants provides total direct compensation Options are valued using the Black and

Scholes (1973) formula for European call options adjusted by Merton (1973) to

incorporate dividends

C Descriptive Statistics

Table I presents descriptive statistics of key variables employed in the study according

to our comprehensive dataset11

Institutions own on average 546 percent of the firms in

which they invest This is almost identical to the 531 percent found by HS The

institutions with the five largest holdings account 45 percent of institutional ownership

Once again the figure for HS is almost identical at 44 percent The institutions with the

five largest holdings own on average 229 percent of shares outstanding in a firm (HS

have 223 percent) Average total compensation for executives is $2583 million

considerably larger than that documented by HS ($1250 million) but the HS figure is an

10 When there is more than one grant during the year a weighted average delta is used

11 With the data supplied to us by Hartzell and Starks we are able to replicate exactly their summary data

(HS Table I) for all but cash compensation Salary is included but bonus payments are missing The

replicated table is available on request

14

amalgam of price levels over their sample period 1992‒1997 and ours are in consistent

dollars of June 30 2002 However there has also been significant growth in

compensation levels from 1998 to 2002

ltltINSERT TABLE Igtgt

Based on our comprehensive data in Table II we examine correlations between the

key variables employed in the study Of concern is the large negative correlation of 63

percent which has been discussed previously (Section IIA) between the HS measure of

institutional concentration and the natural logarithm of firm market capitalization

ltltINSERT TABLE IIgtgt

In view of this high correlation Table III provides a breakdown of the three key pay

variables and three institutional ownership variables by size deciles We find that the high

institutional concentration but low institutional ownership share of total shareholdings

mentioned above is evident in the smallest decile of firms by size This decile has low

salary and even lower total compensation in a relative sense but by far the highest pay-

for-performance sensitivity of option grants Small firms award executives a far higher

proportion of market capitalization Since small firm market-capitalization is negligible in

comparison with the highest decile (300 times larger in magnitude) total compensation is

very small in absolute value Moreover due to the domination of the pay-size effect base

salaries are also exceedingly small

ltltINSERT TABLE IIIgtgt

Figure 1 based on Table III shows how as institutional concentration falls with

increases in stock size (but also as the total share of institutional ownership increases)

and the pay-for-performance sensitivity of option grants falls Thus because of what

appears to be a weak size control and size-influenced concentration measure HS

15

potentially pick up a size effect as their main result but not necessarily a monitoring

effect Figure 2 shows that as firm size increases up to decile 8 at least the share of

institutional total ownership increases as does total compensation

ltltINSERT FIGURES 1 AND 2 gtgt

D Methodology

Following HS we use two estimation techniques to examine the effect of institutional

investor influence on executive compensation Due to the censored nature of option grant

pay-for-performance sensitivity this compensation measure most appropriately uses

Tobit model specification whereas an Ordinary Least Squares (OLS) model specification

is used for all other compensation measures We model compensation measures as a

function of contemporaneous and lagged change in shareholder wealth institutional

influence Tobinrsquos Q and market capitalization Controls for CEO industry and year

effects are also used Augmentation occurs to test the effect of institutional influence on

the change in executive cash and total compensation with an interaction term that is the

product of institutional influence and the change in shareholder wealth

The variables used to model executive compensation have the following definitions

The lagged and contemporary measure of change in shareholder wealth is simply the

difference in market capitalization of the firm The measures of institutional influence

used are Institutional Concentration and Top 5 Ownership Use of the two types of

institutional influence occurs in separate models In order to replicate the HS

methodology models using Institutional Concentration have an additional control

consisting of lagged total institutional holdings and Tobinrsquos Q controls for performance

and growth opportunities Market capitalization of the firm is the number of shares

outstanding multiplied by the share price with inclusion both in levels and natural

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 10: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

10

Black-Scholes option methodology This may introduce a downward pay bias since self-

reported option-grant pay is subject to possible understatement and there are 13839

observations with likely high option pay dropped altogether

Endogeneity

HSrsquos endogeneity testing raises concerns about reverse causality Institutions may

prefer to hold firms with certain compensation structures such as incentivized executives

HS rightly highlight this concern and use instrumental variables to address this issue HS

assume that institutional ownership reflects any reverse causality Using an instrumental

variables approach to resolve this problem involves finding a variable that influences or

explains institutional ownership but not directly executive compensation They use share

turnover in a firm as an instrument for institutional ownership However theoretical work

by Holmstrom and Tirole (1993) indicates that measures of stock liquidity and trading

activity are indeed important determinants of executive market-based incentives as Kang

and Lui (2008) and Dikolli Kulp and Sedatole (2009) find empirically As such one can

make a case for adopting another instrument rather than share turnover for institutional

ownership

II Previous Research

Prior research fails to address issues concerning possible fragility of the HS results

AHS replicate the HS findings on both incentives and pay levels using the same dataset as

HS and they apply the same definition of institutional concentration and use market

capitalization expressed as a level Cadman Klasa and Matsunaga (2010 Table 6) set out

to replicate HSrsquos (Table II) model of option grant pay-for-performance sensitivity when

they compare a dataset of ExecuComp and Non-ExecuComp firms for the period 2000-

2007 Their ExecuComp results for this sample period are quite similar to our results for

11

the 1992‒2002 period for the same specification controlling for the logarithm of market

capitalization but they do not regard these results as a test of HS as their focus is entirely

on comparing the two groups of stocks Nor do they investigate the impact of

concentration on either cash compensation or total pay Kang and Liu (2008) examine

pay-performance sensitivity use a version of the HS institutional concentration measure

as a control variable in a different framework deriving from Holmstrom and Tirole

(1993) Dikolli Kulp and Sedatole (2009) argue that firms with transient ownership will

issue relatively more equity incentives to counter short-termism with their results robust

to the inclusion of the HS concentration variable

We hoped to find supportive evidence from proxy voting behavior in support of HSs

findings However evidence from actual mutual fund proxy voting records suggests that

most oppose reductions in CEO pay but overall the evidence is mixed8 Davis and Kim

(2005) examine proxy votes of mutual funds for 2004 and find that for a sample of

Fortune 1000 proxy contests in 45 cases that attempted to limit executive pay mutual

funds were unanimously opposed to such attempts Rothberg and Lilien (2006) also

examine proxy-voting data and find that mutual funds voted 66 percent of the time in

managementrsquos favor on issues of executive compensation Ertimur Ferri and Muslu

(2011) find that institutional investors lack sophistication in that they do not target

excessively paid CEOs relative to CEOs with high predicted-pay based on economic

determinants but exert a moderating influence ndash a $23 million reduction ndash for those they

deem ldquoexcessively paidrdquo CEOs

III Data and Methodology

8 We do acknowledge that the HS results are for all institutional investors while the transparency with

respect to proxy voting applies only to mutual funds

12

This Section discusses the data used in the study the construction of variables

descriptive statistics and the methodology Two datasets are used ndash one is the original

dataset generously supplied by Jay Hartzell and Laura Starks which covers 1992‒1997

second a more comprehensive dataset covering 1992‒2002 is computed from the same

data sources used in the HS dataset This is Standard and Poorrsquos (SampP) ExecuComp for

compensation data Thomson Financial CDASpectrum database for institutional holdings

to compute measure of institutional influence SampPrsquos Compustat and the Center for

Research in Stock Prices (CRSP) for firm level accounting and stock price data Our more

comprehensive dataset contains 2559 firms compared with 1914 for the HS dataset Our

full matched sample yields 97679 executive years

A Institutional Influence Measures

To measure institutional influence we employ two ownership-based metrics The first

measure of institutional influence is HSrsquos Institutional Concentration We use this for

direct comparison to the HS analysis The second measure of institutional influence

changes the denominator of the HS measure from institutional shares held to total shares

outstanding in the firm with nomenclature Top 5 Ownership9 We compute both

measures at the fiscal year end of the firm We adjust all compensation measures and

asset prices for inflation to 30 June 2002 prices for our comprehensive sample compared

to the HS dataset that is in the dollars of the day

B Compensation Measures

The ExecuComp database reports several raw measures of executive compensation for

the top five executives (where available) including total salary bonus long-term

9 Top 5 Ownership is included in the HS database but not utilized by them in reported tests as well as

constructed by us for the more comprehensive sample

13

incentives and number of option grants For our more comprehensive dataset we replicate

all the compensation measures used by HS In common with HS we compute the pay-for-

performance sensitivity of option grants using the Yermack (1995) approach This

measure shows the dollar change in value of the executive options for every dollar change

in the value of the firm This involves calculating the option delta using the Black-

Scholes formula adjusted for dividends10

The ratio of the number of shares represented

by the award of options divided by the diluted number of shares outstanding at the

beginning of the year multiplies the option delta with units given by a $1000 change in

firm value Summing salary bonus long-term incentive plan payouts and stock and

option grants provides total direct compensation Options are valued using the Black and

Scholes (1973) formula for European call options adjusted by Merton (1973) to

incorporate dividends

C Descriptive Statistics

Table I presents descriptive statistics of key variables employed in the study according

to our comprehensive dataset11

Institutions own on average 546 percent of the firms in

which they invest This is almost identical to the 531 percent found by HS The

institutions with the five largest holdings account 45 percent of institutional ownership

Once again the figure for HS is almost identical at 44 percent The institutions with the

five largest holdings own on average 229 percent of shares outstanding in a firm (HS

have 223 percent) Average total compensation for executives is $2583 million

considerably larger than that documented by HS ($1250 million) but the HS figure is an

10 When there is more than one grant during the year a weighted average delta is used

11 With the data supplied to us by Hartzell and Starks we are able to replicate exactly their summary data

(HS Table I) for all but cash compensation Salary is included but bonus payments are missing The

replicated table is available on request

14

amalgam of price levels over their sample period 1992‒1997 and ours are in consistent

dollars of June 30 2002 However there has also been significant growth in

compensation levels from 1998 to 2002

ltltINSERT TABLE Igtgt

Based on our comprehensive data in Table II we examine correlations between the

key variables employed in the study Of concern is the large negative correlation of 63

percent which has been discussed previously (Section IIA) between the HS measure of

institutional concentration and the natural logarithm of firm market capitalization

ltltINSERT TABLE IIgtgt

In view of this high correlation Table III provides a breakdown of the three key pay

variables and three institutional ownership variables by size deciles We find that the high

institutional concentration but low institutional ownership share of total shareholdings

mentioned above is evident in the smallest decile of firms by size This decile has low

salary and even lower total compensation in a relative sense but by far the highest pay-

for-performance sensitivity of option grants Small firms award executives a far higher

proportion of market capitalization Since small firm market-capitalization is negligible in

comparison with the highest decile (300 times larger in magnitude) total compensation is

very small in absolute value Moreover due to the domination of the pay-size effect base

salaries are also exceedingly small

ltltINSERT TABLE IIIgtgt

Figure 1 based on Table III shows how as institutional concentration falls with

increases in stock size (but also as the total share of institutional ownership increases)

and the pay-for-performance sensitivity of option grants falls Thus because of what

appears to be a weak size control and size-influenced concentration measure HS

15

potentially pick up a size effect as their main result but not necessarily a monitoring

effect Figure 2 shows that as firm size increases up to decile 8 at least the share of

institutional total ownership increases as does total compensation

ltltINSERT FIGURES 1 AND 2 gtgt

D Methodology

Following HS we use two estimation techniques to examine the effect of institutional

investor influence on executive compensation Due to the censored nature of option grant

pay-for-performance sensitivity this compensation measure most appropriately uses

Tobit model specification whereas an Ordinary Least Squares (OLS) model specification

is used for all other compensation measures We model compensation measures as a

function of contemporaneous and lagged change in shareholder wealth institutional

influence Tobinrsquos Q and market capitalization Controls for CEO industry and year

effects are also used Augmentation occurs to test the effect of institutional influence on

the change in executive cash and total compensation with an interaction term that is the

product of institutional influence and the change in shareholder wealth

The variables used to model executive compensation have the following definitions

The lagged and contemporary measure of change in shareholder wealth is simply the

difference in market capitalization of the firm The measures of institutional influence

used are Institutional Concentration and Top 5 Ownership Use of the two types of

institutional influence occurs in separate models In order to replicate the HS

methodology models using Institutional Concentration have an additional control

consisting of lagged total institutional holdings and Tobinrsquos Q controls for performance

and growth opportunities Market capitalization of the firm is the number of shares

outstanding multiplied by the share price with inclusion both in levels and natural

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 11: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

11

the 1992‒2002 period for the same specification controlling for the logarithm of market

capitalization but they do not regard these results as a test of HS as their focus is entirely

on comparing the two groups of stocks Nor do they investigate the impact of

concentration on either cash compensation or total pay Kang and Liu (2008) examine

pay-performance sensitivity use a version of the HS institutional concentration measure

as a control variable in a different framework deriving from Holmstrom and Tirole

(1993) Dikolli Kulp and Sedatole (2009) argue that firms with transient ownership will

issue relatively more equity incentives to counter short-termism with their results robust

to the inclusion of the HS concentration variable

We hoped to find supportive evidence from proxy voting behavior in support of HSs

findings However evidence from actual mutual fund proxy voting records suggests that

most oppose reductions in CEO pay but overall the evidence is mixed8 Davis and Kim

(2005) examine proxy votes of mutual funds for 2004 and find that for a sample of

Fortune 1000 proxy contests in 45 cases that attempted to limit executive pay mutual

funds were unanimously opposed to such attempts Rothberg and Lilien (2006) also

examine proxy-voting data and find that mutual funds voted 66 percent of the time in

managementrsquos favor on issues of executive compensation Ertimur Ferri and Muslu

(2011) find that institutional investors lack sophistication in that they do not target

excessively paid CEOs relative to CEOs with high predicted-pay based on economic

determinants but exert a moderating influence ndash a $23 million reduction ndash for those they

deem ldquoexcessively paidrdquo CEOs

III Data and Methodology

8 We do acknowledge that the HS results are for all institutional investors while the transparency with

respect to proxy voting applies only to mutual funds

12

This Section discusses the data used in the study the construction of variables

descriptive statistics and the methodology Two datasets are used ndash one is the original

dataset generously supplied by Jay Hartzell and Laura Starks which covers 1992‒1997

second a more comprehensive dataset covering 1992‒2002 is computed from the same

data sources used in the HS dataset This is Standard and Poorrsquos (SampP) ExecuComp for

compensation data Thomson Financial CDASpectrum database for institutional holdings

to compute measure of institutional influence SampPrsquos Compustat and the Center for

Research in Stock Prices (CRSP) for firm level accounting and stock price data Our more

comprehensive dataset contains 2559 firms compared with 1914 for the HS dataset Our

full matched sample yields 97679 executive years

A Institutional Influence Measures

To measure institutional influence we employ two ownership-based metrics The first

measure of institutional influence is HSrsquos Institutional Concentration We use this for

direct comparison to the HS analysis The second measure of institutional influence

changes the denominator of the HS measure from institutional shares held to total shares

outstanding in the firm with nomenclature Top 5 Ownership9 We compute both

measures at the fiscal year end of the firm We adjust all compensation measures and

asset prices for inflation to 30 June 2002 prices for our comprehensive sample compared

to the HS dataset that is in the dollars of the day

B Compensation Measures

The ExecuComp database reports several raw measures of executive compensation for

the top five executives (where available) including total salary bonus long-term

9 Top 5 Ownership is included in the HS database but not utilized by them in reported tests as well as

constructed by us for the more comprehensive sample

13

incentives and number of option grants For our more comprehensive dataset we replicate

all the compensation measures used by HS In common with HS we compute the pay-for-

performance sensitivity of option grants using the Yermack (1995) approach This

measure shows the dollar change in value of the executive options for every dollar change

in the value of the firm This involves calculating the option delta using the Black-

Scholes formula adjusted for dividends10

The ratio of the number of shares represented

by the award of options divided by the diluted number of shares outstanding at the

beginning of the year multiplies the option delta with units given by a $1000 change in

firm value Summing salary bonus long-term incentive plan payouts and stock and

option grants provides total direct compensation Options are valued using the Black and

Scholes (1973) formula for European call options adjusted by Merton (1973) to

incorporate dividends

C Descriptive Statistics

Table I presents descriptive statistics of key variables employed in the study according

to our comprehensive dataset11

Institutions own on average 546 percent of the firms in

which they invest This is almost identical to the 531 percent found by HS The

institutions with the five largest holdings account 45 percent of institutional ownership

Once again the figure for HS is almost identical at 44 percent The institutions with the

five largest holdings own on average 229 percent of shares outstanding in a firm (HS

have 223 percent) Average total compensation for executives is $2583 million

considerably larger than that documented by HS ($1250 million) but the HS figure is an

10 When there is more than one grant during the year a weighted average delta is used

11 With the data supplied to us by Hartzell and Starks we are able to replicate exactly their summary data

(HS Table I) for all but cash compensation Salary is included but bonus payments are missing The

replicated table is available on request

14

amalgam of price levels over their sample period 1992‒1997 and ours are in consistent

dollars of June 30 2002 However there has also been significant growth in

compensation levels from 1998 to 2002

ltltINSERT TABLE Igtgt

Based on our comprehensive data in Table II we examine correlations between the

key variables employed in the study Of concern is the large negative correlation of 63

percent which has been discussed previously (Section IIA) between the HS measure of

institutional concentration and the natural logarithm of firm market capitalization

ltltINSERT TABLE IIgtgt

In view of this high correlation Table III provides a breakdown of the three key pay

variables and three institutional ownership variables by size deciles We find that the high

institutional concentration but low institutional ownership share of total shareholdings

mentioned above is evident in the smallest decile of firms by size This decile has low

salary and even lower total compensation in a relative sense but by far the highest pay-

for-performance sensitivity of option grants Small firms award executives a far higher

proportion of market capitalization Since small firm market-capitalization is negligible in

comparison with the highest decile (300 times larger in magnitude) total compensation is

very small in absolute value Moreover due to the domination of the pay-size effect base

salaries are also exceedingly small

ltltINSERT TABLE IIIgtgt

Figure 1 based on Table III shows how as institutional concentration falls with

increases in stock size (but also as the total share of institutional ownership increases)

and the pay-for-performance sensitivity of option grants falls Thus because of what

appears to be a weak size control and size-influenced concentration measure HS

15

potentially pick up a size effect as their main result but not necessarily a monitoring

effect Figure 2 shows that as firm size increases up to decile 8 at least the share of

institutional total ownership increases as does total compensation

ltltINSERT FIGURES 1 AND 2 gtgt

D Methodology

Following HS we use two estimation techniques to examine the effect of institutional

investor influence on executive compensation Due to the censored nature of option grant

pay-for-performance sensitivity this compensation measure most appropriately uses

Tobit model specification whereas an Ordinary Least Squares (OLS) model specification

is used for all other compensation measures We model compensation measures as a

function of contemporaneous and lagged change in shareholder wealth institutional

influence Tobinrsquos Q and market capitalization Controls for CEO industry and year

effects are also used Augmentation occurs to test the effect of institutional influence on

the change in executive cash and total compensation with an interaction term that is the

product of institutional influence and the change in shareholder wealth

The variables used to model executive compensation have the following definitions

The lagged and contemporary measure of change in shareholder wealth is simply the

difference in market capitalization of the firm The measures of institutional influence

used are Institutional Concentration and Top 5 Ownership Use of the two types of

institutional influence occurs in separate models In order to replicate the HS

methodology models using Institutional Concentration have an additional control

consisting of lagged total institutional holdings and Tobinrsquos Q controls for performance

and growth opportunities Market capitalization of the firm is the number of shares

outstanding multiplied by the share price with inclusion both in levels and natural

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 12: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

12

This Section discusses the data used in the study the construction of variables

descriptive statistics and the methodology Two datasets are used ndash one is the original

dataset generously supplied by Jay Hartzell and Laura Starks which covers 1992‒1997

second a more comprehensive dataset covering 1992‒2002 is computed from the same

data sources used in the HS dataset This is Standard and Poorrsquos (SampP) ExecuComp for

compensation data Thomson Financial CDASpectrum database for institutional holdings

to compute measure of institutional influence SampPrsquos Compustat and the Center for

Research in Stock Prices (CRSP) for firm level accounting and stock price data Our more

comprehensive dataset contains 2559 firms compared with 1914 for the HS dataset Our

full matched sample yields 97679 executive years

A Institutional Influence Measures

To measure institutional influence we employ two ownership-based metrics The first

measure of institutional influence is HSrsquos Institutional Concentration We use this for

direct comparison to the HS analysis The second measure of institutional influence

changes the denominator of the HS measure from institutional shares held to total shares

outstanding in the firm with nomenclature Top 5 Ownership9 We compute both

measures at the fiscal year end of the firm We adjust all compensation measures and

asset prices for inflation to 30 June 2002 prices for our comprehensive sample compared

to the HS dataset that is in the dollars of the day

B Compensation Measures

The ExecuComp database reports several raw measures of executive compensation for

the top five executives (where available) including total salary bonus long-term

9 Top 5 Ownership is included in the HS database but not utilized by them in reported tests as well as

constructed by us for the more comprehensive sample

13

incentives and number of option grants For our more comprehensive dataset we replicate

all the compensation measures used by HS In common with HS we compute the pay-for-

performance sensitivity of option grants using the Yermack (1995) approach This

measure shows the dollar change in value of the executive options for every dollar change

in the value of the firm This involves calculating the option delta using the Black-

Scholes formula adjusted for dividends10

The ratio of the number of shares represented

by the award of options divided by the diluted number of shares outstanding at the

beginning of the year multiplies the option delta with units given by a $1000 change in

firm value Summing salary bonus long-term incentive plan payouts and stock and

option grants provides total direct compensation Options are valued using the Black and

Scholes (1973) formula for European call options adjusted by Merton (1973) to

incorporate dividends

C Descriptive Statistics

Table I presents descriptive statistics of key variables employed in the study according

to our comprehensive dataset11

Institutions own on average 546 percent of the firms in

which they invest This is almost identical to the 531 percent found by HS The

institutions with the five largest holdings account 45 percent of institutional ownership

Once again the figure for HS is almost identical at 44 percent The institutions with the

five largest holdings own on average 229 percent of shares outstanding in a firm (HS

have 223 percent) Average total compensation for executives is $2583 million

considerably larger than that documented by HS ($1250 million) but the HS figure is an

10 When there is more than one grant during the year a weighted average delta is used

11 With the data supplied to us by Hartzell and Starks we are able to replicate exactly their summary data

(HS Table I) for all but cash compensation Salary is included but bonus payments are missing The

replicated table is available on request

14

amalgam of price levels over their sample period 1992‒1997 and ours are in consistent

dollars of June 30 2002 However there has also been significant growth in

compensation levels from 1998 to 2002

ltltINSERT TABLE Igtgt

Based on our comprehensive data in Table II we examine correlations between the

key variables employed in the study Of concern is the large negative correlation of 63

percent which has been discussed previously (Section IIA) between the HS measure of

institutional concentration and the natural logarithm of firm market capitalization

ltltINSERT TABLE IIgtgt

In view of this high correlation Table III provides a breakdown of the three key pay

variables and three institutional ownership variables by size deciles We find that the high

institutional concentration but low institutional ownership share of total shareholdings

mentioned above is evident in the smallest decile of firms by size This decile has low

salary and even lower total compensation in a relative sense but by far the highest pay-

for-performance sensitivity of option grants Small firms award executives a far higher

proportion of market capitalization Since small firm market-capitalization is negligible in

comparison with the highest decile (300 times larger in magnitude) total compensation is

very small in absolute value Moreover due to the domination of the pay-size effect base

salaries are also exceedingly small

ltltINSERT TABLE IIIgtgt

Figure 1 based on Table III shows how as institutional concentration falls with

increases in stock size (but also as the total share of institutional ownership increases)

and the pay-for-performance sensitivity of option grants falls Thus because of what

appears to be a weak size control and size-influenced concentration measure HS

15

potentially pick up a size effect as their main result but not necessarily a monitoring

effect Figure 2 shows that as firm size increases up to decile 8 at least the share of

institutional total ownership increases as does total compensation

ltltINSERT FIGURES 1 AND 2 gtgt

D Methodology

Following HS we use two estimation techniques to examine the effect of institutional

investor influence on executive compensation Due to the censored nature of option grant

pay-for-performance sensitivity this compensation measure most appropriately uses

Tobit model specification whereas an Ordinary Least Squares (OLS) model specification

is used for all other compensation measures We model compensation measures as a

function of contemporaneous and lagged change in shareholder wealth institutional

influence Tobinrsquos Q and market capitalization Controls for CEO industry and year

effects are also used Augmentation occurs to test the effect of institutional influence on

the change in executive cash and total compensation with an interaction term that is the

product of institutional influence and the change in shareholder wealth

The variables used to model executive compensation have the following definitions

The lagged and contemporary measure of change in shareholder wealth is simply the

difference in market capitalization of the firm The measures of institutional influence

used are Institutional Concentration and Top 5 Ownership Use of the two types of

institutional influence occurs in separate models In order to replicate the HS

methodology models using Institutional Concentration have an additional control

consisting of lagged total institutional holdings and Tobinrsquos Q controls for performance

and growth opportunities Market capitalization of the firm is the number of shares

outstanding multiplied by the share price with inclusion both in levels and natural

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 13: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

13

incentives and number of option grants For our more comprehensive dataset we replicate

all the compensation measures used by HS In common with HS we compute the pay-for-

performance sensitivity of option grants using the Yermack (1995) approach This

measure shows the dollar change in value of the executive options for every dollar change

in the value of the firm This involves calculating the option delta using the Black-

Scholes formula adjusted for dividends10

The ratio of the number of shares represented

by the award of options divided by the diluted number of shares outstanding at the

beginning of the year multiplies the option delta with units given by a $1000 change in

firm value Summing salary bonus long-term incentive plan payouts and stock and

option grants provides total direct compensation Options are valued using the Black and

Scholes (1973) formula for European call options adjusted by Merton (1973) to

incorporate dividends

C Descriptive Statistics

Table I presents descriptive statistics of key variables employed in the study according

to our comprehensive dataset11

Institutions own on average 546 percent of the firms in

which they invest This is almost identical to the 531 percent found by HS The

institutions with the five largest holdings account 45 percent of institutional ownership

Once again the figure for HS is almost identical at 44 percent The institutions with the

five largest holdings own on average 229 percent of shares outstanding in a firm (HS

have 223 percent) Average total compensation for executives is $2583 million

considerably larger than that documented by HS ($1250 million) but the HS figure is an

10 When there is more than one grant during the year a weighted average delta is used

11 With the data supplied to us by Hartzell and Starks we are able to replicate exactly their summary data

(HS Table I) for all but cash compensation Salary is included but bonus payments are missing The

replicated table is available on request

14

amalgam of price levels over their sample period 1992‒1997 and ours are in consistent

dollars of June 30 2002 However there has also been significant growth in

compensation levels from 1998 to 2002

ltltINSERT TABLE Igtgt

Based on our comprehensive data in Table II we examine correlations between the

key variables employed in the study Of concern is the large negative correlation of 63

percent which has been discussed previously (Section IIA) between the HS measure of

institutional concentration and the natural logarithm of firm market capitalization

ltltINSERT TABLE IIgtgt

In view of this high correlation Table III provides a breakdown of the three key pay

variables and three institutional ownership variables by size deciles We find that the high

institutional concentration but low institutional ownership share of total shareholdings

mentioned above is evident in the smallest decile of firms by size This decile has low

salary and even lower total compensation in a relative sense but by far the highest pay-

for-performance sensitivity of option grants Small firms award executives a far higher

proportion of market capitalization Since small firm market-capitalization is negligible in

comparison with the highest decile (300 times larger in magnitude) total compensation is

very small in absolute value Moreover due to the domination of the pay-size effect base

salaries are also exceedingly small

ltltINSERT TABLE IIIgtgt

Figure 1 based on Table III shows how as institutional concentration falls with

increases in stock size (but also as the total share of institutional ownership increases)

and the pay-for-performance sensitivity of option grants falls Thus because of what

appears to be a weak size control and size-influenced concentration measure HS

15

potentially pick up a size effect as their main result but not necessarily a monitoring

effect Figure 2 shows that as firm size increases up to decile 8 at least the share of

institutional total ownership increases as does total compensation

ltltINSERT FIGURES 1 AND 2 gtgt

D Methodology

Following HS we use two estimation techniques to examine the effect of institutional

investor influence on executive compensation Due to the censored nature of option grant

pay-for-performance sensitivity this compensation measure most appropriately uses

Tobit model specification whereas an Ordinary Least Squares (OLS) model specification

is used for all other compensation measures We model compensation measures as a

function of contemporaneous and lagged change in shareholder wealth institutional

influence Tobinrsquos Q and market capitalization Controls for CEO industry and year

effects are also used Augmentation occurs to test the effect of institutional influence on

the change in executive cash and total compensation with an interaction term that is the

product of institutional influence and the change in shareholder wealth

The variables used to model executive compensation have the following definitions

The lagged and contemporary measure of change in shareholder wealth is simply the

difference in market capitalization of the firm The measures of institutional influence

used are Institutional Concentration and Top 5 Ownership Use of the two types of

institutional influence occurs in separate models In order to replicate the HS

methodology models using Institutional Concentration have an additional control

consisting of lagged total institutional holdings and Tobinrsquos Q controls for performance

and growth opportunities Market capitalization of the firm is the number of shares

outstanding multiplied by the share price with inclusion both in levels and natural

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 14: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

14

amalgam of price levels over their sample period 1992‒1997 and ours are in consistent

dollars of June 30 2002 However there has also been significant growth in

compensation levels from 1998 to 2002

ltltINSERT TABLE Igtgt

Based on our comprehensive data in Table II we examine correlations between the

key variables employed in the study Of concern is the large negative correlation of 63

percent which has been discussed previously (Section IIA) between the HS measure of

institutional concentration and the natural logarithm of firm market capitalization

ltltINSERT TABLE IIgtgt

In view of this high correlation Table III provides a breakdown of the three key pay

variables and three institutional ownership variables by size deciles We find that the high

institutional concentration but low institutional ownership share of total shareholdings

mentioned above is evident in the smallest decile of firms by size This decile has low

salary and even lower total compensation in a relative sense but by far the highest pay-

for-performance sensitivity of option grants Small firms award executives a far higher

proportion of market capitalization Since small firm market-capitalization is negligible in

comparison with the highest decile (300 times larger in magnitude) total compensation is

very small in absolute value Moreover due to the domination of the pay-size effect base

salaries are also exceedingly small

ltltINSERT TABLE IIIgtgt

Figure 1 based on Table III shows how as institutional concentration falls with

increases in stock size (but also as the total share of institutional ownership increases)

and the pay-for-performance sensitivity of option grants falls Thus because of what

appears to be a weak size control and size-influenced concentration measure HS

15

potentially pick up a size effect as their main result but not necessarily a monitoring

effect Figure 2 shows that as firm size increases up to decile 8 at least the share of

institutional total ownership increases as does total compensation

ltltINSERT FIGURES 1 AND 2 gtgt

D Methodology

Following HS we use two estimation techniques to examine the effect of institutional

investor influence on executive compensation Due to the censored nature of option grant

pay-for-performance sensitivity this compensation measure most appropriately uses

Tobit model specification whereas an Ordinary Least Squares (OLS) model specification

is used for all other compensation measures We model compensation measures as a

function of contemporaneous and lagged change in shareholder wealth institutional

influence Tobinrsquos Q and market capitalization Controls for CEO industry and year

effects are also used Augmentation occurs to test the effect of institutional influence on

the change in executive cash and total compensation with an interaction term that is the

product of institutional influence and the change in shareholder wealth

The variables used to model executive compensation have the following definitions

The lagged and contemporary measure of change in shareholder wealth is simply the

difference in market capitalization of the firm The measures of institutional influence

used are Institutional Concentration and Top 5 Ownership Use of the two types of

institutional influence occurs in separate models In order to replicate the HS

methodology models using Institutional Concentration have an additional control

consisting of lagged total institutional holdings and Tobinrsquos Q controls for performance

and growth opportunities Market capitalization of the firm is the number of shares

outstanding multiplied by the share price with inclusion both in levels and natural

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 15: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

15

potentially pick up a size effect as their main result but not necessarily a monitoring

effect Figure 2 shows that as firm size increases up to decile 8 at least the share of

institutional total ownership increases as does total compensation

ltltINSERT FIGURES 1 AND 2 gtgt

D Methodology

Following HS we use two estimation techniques to examine the effect of institutional

investor influence on executive compensation Due to the censored nature of option grant

pay-for-performance sensitivity this compensation measure most appropriately uses

Tobit model specification whereas an Ordinary Least Squares (OLS) model specification

is used for all other compensation measures We model compensation measures as a

function of contemporaneous and lagged change in shareholder wealth institutional

influence Tobinrsquos Q and market capitalization Controls for CEO industry and year

effects are also used Augmentation occurs to test the effect of institutional influence on

the change in executive cash and total compensation with an interaction term that is the

product of institutional influence and the change in shareholder wealth

The variables used to model executive compensation have the following definitions

The lagged and contemporary measure of change in shareholder wealth is simply the

difference in market capitalization of the firm The measures of institutional influence

used are Institutional Concentration and Top 5 Ownership Use of the two types of

institutional influence occurs in separate models In order to replicate the HS

methodology models using Institutional Concentration have an additional control

consisting of lagged total institutional holdings and Tobinrsquos Q controls for performance

and growth opportunities Market capitalization of the firm is the number of shares

outstanding multiplied by the share price with inclusion both in levels and natural

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 16: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

16

logarithmic form A dummy variable is included to identify whether the executive is the

CEO Dummy variables are also included to control for industry effects This variable

takes a value of 1 for the two-digit Standard Industrial Classification (SIC) in which the

firm operates A year fixed effects (dummy) variable is included taking a value of 1 if the

observation was from the given year

IV Executive Incentives as a Function of Institutional Investor Influence

This section presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity and changes in compensation

A Option Grant Pay-for-Performance Sensitivity

Table IV presents the results for the effect of institutional influence on option grant

pay-for-performance sensitivity

ltltINSERT TABLE IVgtgt

Model (1) is a direct replication of HS using the HS database as supplied to us by HS

with all the variables computed in the same way and in the same functional form as with

HS The coefficient and t-statistic on lagged institutional concentration interacted with the

change in shareholder wealth is 13994 and 767 that compares to 1358 and 842 in HS

We are unable to account for these minor discrepancies for values that should be

identical In model (2) the only change to the model is that we use the natural logarithm

of market capitalization instead of the level of market capitalization This single change

has a sizeable effect on the coefficient on institutional concentration The coefficient on

institutional concentration is now -00692 and is insignificant The fact that an order

preserving transformation to a control variable can change the results is of interest The

log-transformation to market capitalization also changes the coefficient on Top 5

Ownership in models (3) and (4) The coefficient on Top 5 Ownership is significant in

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 17: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

17

both model (3) and in model (4) but the better size control reduces the coefficient by over

25 percent The better size control does not affect Top 5 Ownership by as much as its

design ensures less sensitivity to what could be inadequate size controls

We also test the effect of institutional influence on option grant pay-for-performance

sensitivity over the period 1992‒2002 This sample is then approximately three times as

large as the sample used by HS Institutional concentration is highly positively significant

in model (5) similar to the results for the period 1992‒1997 When we use the log of

market capitalization in model (6) the coefficient on institutional concentration remains

positive and significant at the 10 percent level with a t-statistic of 166 Of importance

though is that the coefficient on institutional concentration is one-eighth of the coefficient

in model (5) Even for a measure of institutional influence which we believe is less

sensitive to firm size the use of log market capitalization reduces the coefficient on Top 5

Ownership by approximately 50 percent from model (7) to model (8)

B Pay-for-Performance Sensitivity due to Changes in Cash and Total

Compensation

For robustness HS examine the effect that institutional influence conditioned on firm

performance has on a changes in cash and total executive compensation using the general

method of Jensen and Murphy (1990) to compute pay-for-performance sensitivity

ltltINSERT TABLE V gtgt

Table V presents the effect of institutional influence on the change in cash

compensation using the HS size control measure throughout12

Model (1) replicates the

specification in HS for the period of 1992‒1997 and we produce a similar result ndash the

interaction of lagged institutional concentration and contemporaneous change in

12 This test uses our data for the two periods 1992‒1997 and 1992‒2002 We do not use the HS data for

cash compensation as data for bonus is missing in the data supplied to us

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 18: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

18

shareholder wealth positively and significantly relates to a change in executive cash

compensation In model (2) we include the contemporaneous change in shareholder

wealth and the lagged institutional concentration as stand-alone controls as indicated by

Greenersquos (2000) specification of equation (1) above and the interaction term remains

significant In model (3) we interact lagged institutional concentration with the lagged

change in shareholder wealth as in equation (2) above that tries to take account of what

participants could have observed at the time The interaction term is then negative but

insignificant altering the HS result Model (4) provides a similar result where our

preferred proxy Top 5 Ownership captures concentrated institutional influence In

models (5) to (8) we use our full sample In model (5) we find that the lagged

institutional concentration interaction with the contemporaneous change in shareholder

wealth is positive and significant in HSrsquos specification However including change in

contemporaneous shareholder wealth and lagged institutional concentration as separate

control variables as suggested by equation (1)rsquos specification removes the significance

from the interaction term in model (6) Moreover in model (7) when lagged institutional

concentration is interaction with the lagged change in shareholder wealth in accord with

equation (2) this interaction term is now negative and significant reversing the HS

finding We obtain a similar result in model (8) when we measure institutional

concentration influence using Top 5 Ownership13

V The Levels of Executive Fixed and Total Compensation as Functions of

Institutional Investor Influence

13 In unreported results we use the log of market capitalization as a size control These changes to the size

control do not dramatically change the findings from Table V The reason why this size issue is not as

important as in the findings for option grants pay-for-performance is that the change in cash compensation

is not so strongly influenced by firm size In unreported results available on request we also examine the

effect of institutional influence on changes in total compensation with similar results to the change in cash

compensation

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 19: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

19

Two measures of compensation are examined ndash salary and total compensation

ltltINSERT TABLE VI gtgt

Table VI examines the effect of institutional influence on the level of salary In model

(1) we use the HS sample and specification to obtain almost identical results The

coefficient on institutional concentration is (negative) $247509 that is almost identical to

(negative) $247967 in HS Both are highly significant In model (2) we make a single

change to the model ndash we use the natural logarithm of market capitalization This single

change reverses the sign of institutional concentration with the coefficient still being

significant at the 1 percent level In models (3) and (4) we measure institutional influence

using Top 5 Ownership In model (3) where we measure firm size using the level of

market capitalization Top 5 Ownership is insignificant When we use the natural

logarithm of market capitalization in model (4) Top 5 Ownership is significant and

positively relates to the salary level In models (5) to (8) we estimate the same models

using our full sample We find similar results for the full sample as for the period 1992ndash

1997

ltltINSERT TABLE VII gtgt

Table VII examines the effect of institutional influence on total compensation In

model (1) we replicate the HS methodology using the HS data to obtain a similar

significant negative relation between institutional concentration and total compensation of

(negative) $1608633 However after changing to a logarithmic specification of market

capitalization in model (2) institutional concentration increases total compensation by a

significant $32400014

Importantly when institutional influence is measured using Top 5

14 = (5688751 times 0101)

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 20: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

20

Ownership an insignificant relation exists with total compensation in model (3) using the

HS size control but it becomes both positive and significant in (4) with the logged size

control In models (5) and (6) where models are estimated using the full sample we

observe a similar reversal in sign as occurs in models (1) and (2) However now the

magnitude of the reversal is almost equal with a difference of about $67m that is very

large indeed In model (5) the coefficient on institutional concentration is (negative)

$342m and then in model (6) the coefficient is $33m Top 5 Ownership is insignificant

in both models (7) and (8) unlike the results for Salary

VI Robustness

Two issues are examined in is this Section ndash reverse causality and the appropriate

transformation of market capitalization A methodological issue inherent in examining the

effect of ownership-based measures of institutional influence on executive compensation

is endogeneity driven by reverse causality We utilize an instrumental variables approach

where orthogonalized institutional influence measures are regressed on each of the

compensation measures lagged option grant pay-for-performance sensitivity salary and

total compensation In addition market capitalization and a CEO dummy are included in

each regression We use the residual from each regression as an instrument for

institutional influence Such a process removes any preferences for compensation from

the institutional influence measures

ltltINSERT TABLES VIII AND IXgtgt

Table VIII presents the results where we instrument the HS measure lagged

institutional concentration with a compensation-orthogonalized equivalent The analysis

indicates that the instrumented institutional concentration measure is positively and

significantly related to the level of salary and total compensation and insignificantly

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 21: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

21

related to option grant pay-for-performance sensitivity (PPSOG) Table IX presents

results where we instrument Top 5 Ownership with a compensation-orthogonalized

equivalent The instrumented Top 5 Ownership measure insignificantly relates to option

grant pay-for-performance sensitivity and barely negatively relates to salary although it

negatively relates to total compensation suggesting reverse causality is driving a

significant portion of our previous results

ltltINSERT TABLE Xgtgt

Another issue examined in this section is the appropriate transformation of market

capitalization Aneuryn-Evans and Deaton (1980) provide an evaluation of methods

comparing linear and log-linear specifications We use the Box-Cox test to compare

logarithm versus linear specifications In applying the Box-Cox test we specify

transformation of only market capitalization ndash the dependent variable and all other

independent variables remain unchanged Table X presents the lambda coefficient for

each model and the log likelihood score In all models in Panel A and B a lambda of zero

receives a higher (closer to zero) log likelihood score suggesting the log specification is

appropriate

VII Conclusion

Hartzell and Starks (2003) appears to document an effective role for institutional

investors in increasing executive incentives and lowering compensation levels Our paper

re-addresses the issue of concentrated institutional monitoring from a perspective

informed by an additional decade of research since their paper appeared We cannot find

evidence that concentrated institutional investors really have any positive (or negative for

that matter) effect on executive incentive levels While superficially we find evidence

that they may raise executive pay levels this is most likely driven by an institutional

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 22: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

22

preference for highly remunerated executives in large companies and thus by reverse

causality Moreover our findings are not consistent with the rent-extraction hypothesis

suggesting that firms systematically overpay executives in the absence of effective

monitoring by outside parties such as institutional investors

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 23: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

23

References

Almazan Andres Jay C Hartzell and Laura T Starks 2005 ldquoActive Institutional

Shareholders and Costs of Monitoring Evidence from Executive Compensationrdquo

Financial Management Winter 5ndash34

Aneuryn-Evans Gwyn and Angus Deaton 1980 ldquoTesting Linear versus Logarithmic

Regression Modelsrdquo Review of Economic Studies 47 (1) Econometrics Issue 275ndash

291

Babenko Ilona 2009 ldquoShare Repurchases and Pay-Performance Sensitivity of Employee

Compensation Contractsrdquo Journal of Finance 64117-150

Baker George P and Brian J Hall 2004 ldquoCEO Incentives and Firm Sizerdquo Journal of

Labor Market Economics 22 767ndash798

Bebchuk Lucian A Jesse M Fried and David Walker 2002 ldquoManagerial power and

rent extraction in the design of executive compensationrdquo University of Chicago Law

Review 69 751ndash846

Bebchuk Lucian A and Jesse M Fried 2003 ldquoExecutive Compensation as an Agency

Problemrdquo Journal of Economic Perspectives 17 71ndash92

Bebchuk Lucian A and Jesse M Fried 2004 Pay without Performance The Unfulfilled

Promise of Executive Compensation Cambridge MA Harvard University Press

Bertrand Marianne and Sendhil Mullainathan 2001 ldquoAre CEOs Rewarded for Luck

The Ones Without Principals Arerdquo Quarterly Journal of Economics 116 901ndash32

Black Fischer and Myron Scholes 1973 ldquoThe Pricing of Options and Corporate

Liabilitiesrdquo Journal of Political Economy 81 637ndash54

Cadman Brian Sandy Klasa and Steve Matsunaga 2010 ldquoDeterminants of CEO Pay A

Comparison of ExecuComp and Non-ExecuComp Firmsrdquo The Accounting Review 85

1511ndash1543

Chhaochharia Vidhi and Yaniv Grinstein 2009 ldquoCEO Compensation and Board

Structurerdquo Journal of Finance 64 231ndash261

Cichello Michael S 2005 ldquoThe impact of firm size on pay-performance sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Davis Gerald F and E Han Kim 2007 ldquoBusiness ties and proxy voting by mutual

fundsrdquo Journal of Financial Economics 85 552ndash570

Dikolli Shane S Susan L Kulp and Karen L Sedatole 2009 ldquoTransient Institutional

Ownership and CEO Contractingrdquo Accounting Review 84 737ndash770

Edmans Alex Xavier Gabaix and Augustin Landier 2009 ldquoA Multiplicative Model of

Optimal CEO Incentives in Market Equilibriumrdquo Review of Financial Studies 22

4881ndash4917

Edmans Alex 2009 ldquoBlockholder Trading Market Efficiency and Managerial Myopiardquo

Journal of Finance 64 2481ndash2513

Ertimur Yonca Fabrizio Ferri and Volkan Muslu 2011 ldquoShareholder Activism and

CEO Payrdquo Review of Financial Studies 24 535ndash592

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 24: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

24

Gabaix Xavier and Augustin Landier 2008 ldquoWhy Has CEO Pay Increased So Muchrdquo

Quarterly Journal of Economics 123 49ndash100

Garen John 1994 ldquoExecutive compensation and principal-agent theoryrdquo Journal of

Political Economy 102 1175ndash1199

Gibbons Robert and Kevin J Murphy 1992 ldquoOptimal Incentive Contracts in the

Presence of Career Concerns Theory and Evidencerdquo Journal of Political Economy

100 468ndash505

Greene William H 2000 (4th

Edition) Econometric Analysis Prentice-Hall NJ

Guthrie Katherine Jan Sokolowsky and Kam-Ming Wan 2012 ldquoCEO Compensation

and Board Structure Revisitedrdquo Journal of Finance Forthcoming

Hadlock Charles R and Gerald B Lumer 1997 ldquoCompensation turnover and top

management incentives historical evidencerdquo Journal of Business 70 153ndash187

Hartzell Jay C and Laura T Starks 2003 ldquoInstitutional Investors and Executive

Compensationrdquo Journal of Finance 58 2351ndash2374

Huson Mark R Robert Parrino and Laura T Starks 2001 ldquoInternal Monitoring

Mechanisms and CEO Turnover A Long-Term Perspectiverdquo Journal of Finance 56

2265ndash2297

Jensen Michael C and Kevin J Murphy 1990 ldquoPerformance Pay and Top Management

Incentivesrdquo Journal of Political Economy 98 225ndash264

Jin Li 2002 ldquoCEO compensation diversification and incentivesrdquo Journal of Financial

Economics 66 29ndash63

Kang Qiang and Qiao Liu 2008 ldquoStock Market Information Production and Executive

Incentivesrdquo Journal of Corporate Finance 14 484ndash498

Merton Robert 1973 ldquoTheory of Rational Option Pricingrdquo Bell Journal of Economics

and Management Science 4 141-183

Morse Adair Vikram Nanda and Amit Seru 2011 ldquoAre Incentive Contracts Rigged by

Powerful CEOsrdquo Journal of Finance 66 1779ndash1821

Murphy Kevin J 1985 ldquoCorporate performance and managerial remuneration An

empirical analysisrdquo Journal of Accounting and Economics 7 11ndash42

Murphy Kevin J 1999 ldquoExecutive compensationrdquo in Orley Ashenfelter and David

Card Handbook of Labor Economics vol 3 Elsevier

Rosen Sherwin 1992 ldquoContracts and the market for executivesrdquo In Contract

Economics ed Lars Werin and Hans Wijkander 181ndash211 Cambridge MA

Blackwell

Rothberg Burton and Steven Lilien 2006 ldquoMutual Funds and Proxy Voting New

Evidence on Corporate Governancerdquo Journal of Business and Technology Law 1

157ndash184

Schaefer Scott 1998 ldquoThe dependence of payndashperformance sensitivity on the size of the

firmrdquo Review of Economics and Statistics 80 436ndash443

Yermack David 1995 ldquoDo Corporations Award CEO Stock Options Effectivelyrdquo

Journal of Financial Economics 39 237ndash69

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 25: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

25

Table I Univariate Descriptive Statistics

This table reports sample statistics for the key variables used in this study based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five largest

holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of shares

outstanding held by the institutions with the five largest holdings Total Institutional Ownership is the

proportion of shares held by all institutions Panel B shows the measures executive compensation The pay-

for-performance sensitivity (PPS) of option grants shows the change in executive wealth due to a $1000

change in firm in shareholder wealth Expressions for Salary and Total Compensation are in thousands of

dollars while Market Capitalization is in millions of dollars Panel C shows firm characteristics

Variable Mean Median Std Dev P10 P90

Panel A Institutional Investor Holdings

Institutional Concentration 0450 0424 0151 0282 0656

Top 5 Institutional Ownership 0229 0220 0101 0110 0355

Total Institutional Ownership 0546 0561 0206 0258 0801

Panel B Executive Compensation

PPS of Option Grants 1161 0156 3829 0 2822

Salary 36311 29462 25231 15179 67000

Total Compensation 258313 85878 980701 23875 511022

Panel C Firm Characteristics

Tobins Q 1744 1139 2738 0495 3322

Market Capitalization 560699 112094 1988108 19754 1048754

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 26: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

26

Table II Pairwise Correlation Coefficients

This table presents the correlations between the key variables based on our comprehensive

ExecuComp dataset Institutional Concentration is the shares owned by the institutions with the five

largest holdings divided by the shares held by all institutions Top 5 Ownership is the proportion of

shares outstanding held by the institutions with the five largest holdings Total Institutional

Ownership is the proportion of shares held by all institutions The pay-for-performance sensitivity

(PPS) of option grants is the change in executive wealth due to a $1000 change in shareholder

wealth

(1) (2) (3) (4) (5) (6) (7) (8)

(1) Institutional Concentration 1

(2) Top 5 Ownership 0268 1

(3) Total Ownership -0415 0706 1

(4) PPS of Option Grants 0122 0042 -0024 1

(5) Log Salary -0270 -0012 0171 0038 1

(6) Log Market Capitalization -0630 -0157 0261 -0156 0420 1

(7) Level Market Capitalization -0241 -0157 0007 -0058 0219 0534 1

(8) Tobins Q -0008 -0034 0002 0015 -0083 0066 0121 1

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 27: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

27

Table III

Descriptive Statistics by Market Capitalization Deciles

Market

Capitalization

Deciles

Market

Capitalization

($m)

Total

Compensation

($000)

Salary

($)

PPS Option

Grants

($)

Institutional

Concentration

()

Top 5 Ownership

()

Institutional

Total Ownership

()

1 (Small) 1181 76008 234700 2720 611 200 327

2 2668 90206 257955 1796 495 217 438

3 4193 105946 275120 1517 454 220 485

4 6045 129892 296067 1376 420 206 491

5 8742 155391 315864 1216 394 198 502

6 13086 191888 345942 1072 380 202 531

7 20790 239501 377021 0874 368 196 532

8 34920 314955 427808 0687 354 190 538

9 67747 450970 480319 0569 328 173 528

10 (Big) 366540 846066 614354 0297 275 138 502

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 28: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

28

Table IV Pay-for-Performance Sensitivity of Option Grants as a Function of Institutional Influence

Similar in construction to parts of HS (Table II) this table shows the coefficients from Tobit regressions of option grant pay-for-performance sensitivity per $1000 change in

shareholder wealth against the lagged change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and

dummy controls for CEO and year effects We estimate models (1) to (4) over the period 1992‒1997 using data supplied by HS and models (5) to (8) are estimated over the

whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions

with the five largest holdings divided by the shares held by all institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5

Ownership as a measure of institutional influence which we define as the proportion of shares outstanding held by the institutions with the five largest holdings Coefficients

for industry and year controls are not presented One two and three asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 77721 191781 89874 137368 -446 -218 -664 -203

(171) (429) (194) (317) (319) (168) (453) (158)

Lag1 Change in Shareholder Wealth 14446 99963 88719 8544 -144 0273 -0342 00852

(027) (212) (166) (184) (071) (015) (016) (005)

Lag1 Institutional Concentration 13994 -00692 26405 03304

(767) (032) (1402) (166)

Lag1 Total Institutional Ownership 08055 10434 07106 0937

(593) (781) (666) (898)

Lag1 Top 5 Institutional Ownership 10567 07457 12116 06293

(399) ( 283) (533) (278)

Lag1 Tobinrsquos Q 0068 00877 00647 00813 00498 00727 00508 00695

(337) (434) (319) (401) (504) (734) (51) (703)

Lag1 Market Capitalization -106202 -173515 -776 -117

(474) (742) (1011) (153)

Lag1 Log Market Capitalization -0297 -02319 -04111 -03908

(1576) (1439) (2997) (2841)

CEO Dummy 13745 13682 13765 13674 28197 28128 28155 28143

(1913) (1918) (1914) (1916) (3388) (3396) (3377) (34)

Number of Observations 33878 33878 33878 33878 97679 97679 97679 97679

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 29: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

29

Table V Pay-for-Performance Sensitivity of Cash Compensation (Salary plus Bonus) as a Function of Institutional Influence - Level Market Capitalization

Similar in parts to models (1) and (2) of HS (Table IV) this table displays the coefficients from OLS regressions of the change in cash compensation against the lagged

change and contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO and year

effects We estimate models (1) to (4) over the period 1992‒1997 based on our ExecuComp sample and models (5) to (8) over the whole sample Models (1) (2) (5) and (6)

use Institutional Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the

shares held by all institutions These models control for total institutional ownership Models (4) and (8) use Top 5 Ownership as a measure of institutional influence which

we define as the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two

and three asterisks denote significance at 10 5 and 1 levels

Our Database based on ExecuComp 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Lag1 Change in Shareholder Wealth 00014 00017 00088 00089 -00006 -00007 00072 00086

(051) (062) (129) (103) (027) (029) (131) (16)

Change in Shareholder Wealth -00102 00102 00105 00032 00102 00101

(097) (292) (293) (055) (611) (608)

Change Shareholder Wealth Lag1 Institutional

Concentration

00435 00764 00363 00253

(463) (258) (689) (144)

Lag1 Change Shareholder Wealth Lag1

Institutional Concentration

-00197 -00283

(122) (197)

Lag1 Institutional Concentration -492182 -288861 400149 453623

(09) (056) (098) (114)

Lag1 Total Institutional Ownership 720688 538372 655091 559587 682069 726226

(276) (232) (281) (314) (308) (322)

Lag1 Change Shareholder Wealth Lag1 Top 5

Institutional Ownership

-0046 -00689

(091) (256)

Lag1 Top 5 Institutional Ownership 583044 1191634

(092) (25)

Lag1 Tobinrsquos Q -32761 -36806 -19422 -18023 -54283 -48681 -29534 -24243

(138) (172) (077) (078) (227) (245) (136) (111)

Lag1 Market Capitalization 00004 00004 00002 00006 00007 00008 00007 00007

(042) (044) (022) (07) (086) (092) (082) (09)

CEO Dummy 768035 765474 768334 773634 616315 61729 619028 618535

(354) (355) (356) (355) (417) (418) (419) (418)

Adjusted R-Sq 00057 0006 00052 0005 00097 00097 00098 00102

Number of Observations 41305 41305 41305 41305 85518 85518 85518 85518

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 30: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

30

Table VI Level of Salary as a Function of Institutional Influence

Similar in parts to models (1) and (2) of HS (Table V) this table displays the coefficients from OLS regressions of salary against the lagged change and contemporary change in

shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects We estimate models (1) to

(4) over the period 1992‒1997 using the actual data supplied by HS and models (5) to (8) over the whole sample 1992‒2002 Models (1) (2) (5) and (6) use Institutional

Concentration as a measure of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all

institutions These models control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as

the proportion of shares outstanding held by the institutions with the 5 largest holdings Coefficients for industry and year controls are not presented One two and three

asterisks denote significance at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample based on ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 04125E-4 0003 -2439E-4 0003 00021 00012 00024 00012

(057) (464) (031) (468) (1004) (72) (1041) (706)

Lag1 Change in Shareholder Wealth -00062 7856E-4 -0007 9003E-4 -00014 00002 -00014 00003

(594) (098) (592) (112) (522) (123) (5) (145)

Lag1 Institutional Concentration -2475087 555134 -2734983 943317

(3245) (710) (4965) (1671)

Lag1 Total Institutional Ownership 1020109 217488 936337 252464

(1904) (432) (2471) (704)

Lag1 Top 5 Institutional Ownership -148355 31354 -87926 423166

(139) (332) (118) (643)

Lag1 Tobinrsquos Q -195348 -252191 -192344 -25158 -119837 -146373 -122132 -143821

(2812) (3762) (2721) (3752) (248) (274) (2583) (2727)

Lag1 Market Capitalization 844E-06 103E-5 00034 00039

(2781) (3051) (2874) (3104)

Lag1 Log Market Capitalization 750021 723625 776657 732279

(7511) (9285) (11224) (14039)

CEO Dummy 2683978 2702238 2668244 2702417 3281133 3285103 3292175 3283145

(8625) (9277) (8246) (9271) (12739) (13616) (12336) (13605)

Adjusted R-Sq 04604 05302 04187 05295 03856 04588 03476 04574

Number of Observations 36280 36280 36280 36280 97679 97679 97679 97679

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 31: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

31

Table VII Level of Total Direct Compensation as a Function of Institutional Influence

Similar in parts to models (3) and (5) of HS (Table V) this table displays the coefficients from OLS regressions of total direct compensation against the lagged change and

contemporary change in shareholder wealth measures of institutional influence Tobinrsquos Q firm market capitalization and dummy controls for CEO industry and year effects

We estimate models (1) to (4) over the period 1992‒1997 and models (5) to (8) over the whole sample Models (1) (2) (5) and (6) use Institutional Concentration as a measure

of institutional influence which HS define as the shares owned by the institutions with the five largest holdings divided by the shares held by all institutions These models

control for total institutional ownership Models (3) (4) (7) and (8) use Top 5 Ownership as a measure of institutional influence which we define as the proportion of shares

outstanding held by the institutions with the five largest holdings Coefficients for industry and year controls are not presented One two and three asterisks denote significance

at 10 5 and 1 levels

Hartzell and Starks Database 1992‒1997 Full Sample from ExecuComp 1992‒2002

(1) (2) (3) (4) (5) (6) (7) (8)

Change in Shareholder Wealth 005779 007006 005282 006791 00423 00148 0046 00138

(415) (581) (369) (565) (203) (07) (22) (066)

Lag1 Change in Shareholder Wealth 003182 00714 00272 00715 00613 0126 00614 01278

(126) (298) (107) (299) (275) (488) (276) (494)

Lag1 Institutional Concentration -1608633 3248998 -3424892 3334186

(151) (283) (1172) (118)

Lag1 Total Institutional Ownership 104013 5473128 1531013 -2926764

(1645) (831) (876) (158)

Lag1 Top 5 Institutional Ownership 188585 3927986 -2159177 -2640879

(016) (343) (067) (092)

Lag1 Tobinrsquos Q -445692 -803612 -454859 -833566 3257027 2971201 3213936 3086205

(427) (791) (432) (831) (83) (77) (815) (793)

Lag1 Market Capitalization 49E-5 615E-5 01031 01088

(113) (1365) (1555) (168)

Lag1 Log Market Capitalization 4683497 4759377 1645156 1427856

(2775) (3469) (3679) (4239)

CEO Dummy 1501307 1508886 1493688 1508736 4713079 4713629 47278 4703908

(2648) (2684) (2618) (2683) (282) (2828) (2819) (2824)

Adjusted R-Sq 01861 02060 01695 02051 01071 01113 01033 011

Number of Observations 33229 33229 33229 33229 97679 97679 97679 97679

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 32: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

32

Table VIII Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Institutional Concentration

This table shows the coefficients from the Two-Stage Least Squares (2SLS) regressions of executive compensation measures against the lagged change

and contemporary change in shareholder wealth instrumented institutional concentration and total institutional ownership Tobinrsquos Q the natural

logarithm of firm market capitalization and dummy variable controls for CEO and year effects We instrument measures of institutional concentration

and total institutional ownership by orthogonalizing with respect to option grant pay-for-performance sensitivity salary and total compensation

Coefficients for industry and year controls are not presented First stage results are not presented One two and three asterisks denote significance at

10 5 and 1 levels

ExecuComp Sample 1992‒1997 Full Sample from ExecuComp 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 144E-05 0004 02133 -409E-06 00011 00157

(308) (775) (596) (691) (638) (068)

Lag1 Change in Shareholder Wealth -240E-05 -00004 00866 118E-06 00002 01422

(131) (087) (346) (097) (116) (51)

Lag1 Institutional Concentration -00898 668681 3263143 02024 916656 2856417

(052) (801) (176) (163) (1545) (1004)

Lag1 Total Institutional Ownership 01021 -43997 2512587 02983 -104171 -1028347

(09) (084) (153) (4) (269) (487)

Lag1 Tobinrsquos Q 00754 -225606 119297 00655 -158657 2997205

(596) (1649) (053) (834) (2535) (727)

Lag1 Log Market Capitalization -04234 828713 7864046 -04002 825106 1685638

(2195) (8132) (2977) (4106) (11133) (373)

CEO Dummy 15848 3214117 2950274 19149 3205862 4529101

(2223) (9389) (2255) (3802) (1331) (2758)

Overall R-Sq -- 04981 01206 -- 04738 01178

Number of Observations 41305 41305 41305 85518 85518 85518

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 33: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

33

Table IX Two Stage Least Squares (Reverse Causality) Tests - Executive Compensation Measures as a Function of Top 5 Ownership

This table shows the coefficients from 2SLS regressions of executive compensation measures against the lagged change and contemporary change

in shareholder wealth instrumented Top 5 institutional ownership Tobinrsquos Q natural logarithm of firm market capitalization and dummy variable

controls for CEO and year effects We instrument Top 5 institutional ownership by orthogonalizing with respect to option grant pay-for-

performance sensitivity salary and total compensation Coefficients for industry and year controls are not presented First stage results are not

presented One two and three asterisks denote significance at 10 5 and 1 levels

ExecuComp sample 1992‒1997 Full Sample 1992‒2002

PPSOG Salary TC PPSOG Salary TC

Change in Shareholder Wealth 136E-05 00041 02128 -407E-06 00011 00146

(293) (79) (596) (692) (619) (063)

Lag1 Change in Shareholder Wealth -241E-05 -00003 00868 116E-06 00003 01439

(133) (07) (347) (096) (142) (514)

Lag1 Top 5 Institutional Ownership -03774 -187512 -3848531 00179 -104261 -126659

(163) (186) (166) (011) (149) (436)

Lag1 Tobinrsquos Q 00731 -223886 10074 00642 -155467 3115073

(573) (1631) (045) (819) (2509) (75)

Lag1 Log Market Capitalization -0416 775637 7696302 -04015 764632 1462536

(2345) (10084) (3766) (3688) (13708) (4072)

CEO Dummy 15854 3211991 2950158 19152 3203152 4519385

(2223) (9381) (2254) (3804) (133) (2752)

Overall R-Sq -- 04967 01202 -- 04722 01168

Number of Observations 41305 41305 41305 85518 85518 85518

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 34: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

34

Table X Specification Tests utilizing Box-Cox Transformation of Market Capitalization

This table presents results from a Box-Cox transformation of market capitalization In

each model we specify transformation of market capitalization only Panel A shows

results for the period 1992‒1997 and Panel B shows results for the entire period

1992‒2002 The first part of each panel shows the Lambda coefficient that applies to

the transformed market capitalization The second part of each panel shows log

likelihood scores with LR Chi2 Statistics in parentheses ‒ these test for the

appropriateness of a linear or log model specification

Panel A Our ExecuComp sample 1992‒1997

(1) (2) (3)

PPSOG Salary TC

Lambda -05143 01881 02876

(-1914) (2413) (1329)

Test H0 (Log Likelihood Score)

Lambda = -1 -1279748 -3178575 -4795326

(23866) (85952) (99688)

Lambda = 0 -1280152 -3138456 -4791159

(31934) (57147) (16339)

Lambda = 1 -1283157 -3163807 -4793506

(92039) (564156) (63292)

Panel B Full ExecuComp sample 1992‒2002

(1) (2) (4)

PPSOG Salary TC

Lambda -044 01853 04036

(-3015) (40) (3666)

Test H0 (Log Likelihood Score)

Lambda = 0 -2688334 -6476494 -10384490

(66599) (160356) (126236)

Lambda = 1 -2694886 -6538506 -10386795

(197644) (1400605) (172345)

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)

Page 35: Do concentrated institutional investors really reduce executive compensation whilst raising incentives?

35

Figure 2 Institutional Ownership Measures (LHA) vs Total

Compensation (RHA) by Market Capitalization

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10

$00

$10

$20

$30

$40

$50

$60

$70

$80

$90

Millio

ns

InstitutionalConcentration (LHS)Top5 Ownership (LHS)

Institutional TotalOwnership (LHS)Total Compensation(RHS)