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Asymmetric Information and DividendPolicy
Kai Li and Xinlei Zhao
We examine how informational asymmetries affect firms dividend
policies. We find that firms thatare more subject to information
asymmetry are less likely to pay, initiate, or increase
dividends,and disburse smaller amounts. We show that our main
results are not driven by our sample andthat our results persist
after accounting for the changing composition of payout over the
sampleperiod, the increasing importance of institutional
shareholdings, and catering incentives. Weconclude that there is a
negative relation between asymmetric information and dividend
policy.Our results do not support the signaling theory of
dividends.
In this paper, we study how informational asymmetries affect
firms dividend policies by exam-ining the relation between a firms
dividend policy and the quality of its information
environment.Dividends have long puzzled financial economists.
Miller and Modigliani (1961) prove that
dividend policy is irrelevant to share value in a perfect and
efficient capital market. However, theobservation that share prices
typically rise when firms increase dividend payments suggests
that,on the contrary, dividends do matter after all.Various studies
have proposed various explanations for firms dividend behavior (see
Allen
and Michaely, 2003, for a comprehensive review of the
literature). Among them, the div-idend signaling theory is one of
the dominant explanations. Under the signaling models
ofBhattacharya (1979), John and Williams (1985), and Miller and
Rock (1985), managers knowmore about the firms true worth than do
its investors and use dividends to convey information tothe market.
Thus, these models suggest a positive relation between information
asymmetry anddividend policy. Other studies have developed tests to
examine the dividend signaling models.However, our study may be the
first to specifically examine the testable implications of the
sig-naling models in the context of the relation between
information asymmetry and firms dividendpolicies.To conduct our
research, we ask the following questions: Are corporate dividend
policies
affected by the degree of information asymmetry that firms face?
Is the relation consistentwith the signaling view of asymmetric
information? Given that information asymmetry is a
We thank Xia Chen for her help in obtaining the analyst coverage
data, Bill Christie (the editor), an anonymous referee,Nalinaksha
Bhattacharyya, Laurence Booth, Jason Chen, Qiang Cheng, Ming Dong,
Charles Gaa, Ron Giammarino,Rob Heinkel, Harrison Hong, Alan Kraus,
Rafael La Porta, Ranjan DMello, Hernan Ortiz-Molina, Gordon
Phillips,Antoinette Schoar, Carina Sponholtz, John Thornton,
seminar participants at Kent State University, University of
BritishColumbia, and participants of the Northern Finance
Association Meetings in Vancouver, the FMA European Conferencein
Stockholm, and the FMA Annual Meetings in Salt Lake City for
valuable comments. We gratefully acknowledgethe contribution of
Thomson Financial for providing analyst data, available through the
Institutional Brokers, EstimateSystem. These data have been
provided as part of a broad academic program to encourage earnings
expectations research.Li acknowledges the financial support from
the Social Sciences and Humanities Research Council of Canada. Li
alsowishes to thank the MIT Sloan School of Management for its
hospitality and support when this paper was initially written.All
errors are our own.
Kai Li is the W.M. Young Professor of Finance at the University
of British Columbia in Vancouver, BC, Canada. XinleiZhao is an
Associate Professor of Finance at Kent State University in Kent,
OH.
Financial Management Winter 2008 pages 673 - 694
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674 Financial Management Winter 2008
major market imperfection and that dividend policies are among
the most important corporatedecisions, these are important
questions.We use analyst earnings forecast errors and the
dispersion in analyst forecasts to gauge the
degree of information asymmetry between managers and investors.
We find that both analystearnings forecast errors and the
dispersion in forecasts are negatively, and very often
significantly,associated with a firms likelihood of paying
dividends, initiating or increasing dividends, andwith the level of
dividends paid. Overall, our findings suggest that firms with more
transparentinformation environments pay out more dividends. This
evidence does not support the signalingtheory of dividends.We also
examine the relation between the quality of a firms information
environment and
measures of total payout that include both dividends and
repurchases. We do not find a positiveassociation between
information asymmetry and repurchase activities. Signaling theory
predicts astronger positive relation between asymmetric information
and dividends than between asymmet-ric information and repurchases.
Our finding of a stronger negative relation between
asymmetricinformation and dividends confirms our evidence on the
lack of support for the signaling theory.Our results are not
broadly consistent with the dividend signaling models.The paper is
organized as follows. In Section I, we discuss the signaling
theory, describe
the sample and variables, and provide summary statistics.
Section II presents our empiricalresults on firms dividend
policies. Section III provides robustness checks on our main
findings.Section IV presents our investigation of repurchase
activities and total payout policies, andSection V concludes.
I. Variable Construction and Sample Characteristics
Since dividends provide a costly way of resolving asymmetric
information, we examine therelation between information asymmetry
and firms dividend policies under the signalingmodels.Because the
resolution of asymmetric information is valuable, firms with
greater asymmetricinformation should be more active dividend
payers. Therefore, after controling for other dividenddeterminants,
if the signaling theory of dividends is valid, we would observe a
positive relationbetween information asymmetry and firm dividend
policy. Further, because dividends imply afirm commitment and are
also historically tax disadvantaged relative to repurchases,
dividendsconstitute a more costly signal and investors should
perceive them as having stronger informationcontent. Thus, the
signaling theory predicts a stronger positive relation between
asymmetricinformation and dividends than between asymmetric
information and repurchases.1
Following earlier studies, we use Compustat and CRSP to examine
dividend policy in industrialfirms. We exclude utilities (SIC
4900-4949) and financial firms (SIC 6000-6999). We note thatdoing
so does not change our main conclusions (results available on
request). To constructmeasures of asymmetric information, we merge
our initial sample with Institutional BrokersEstimate System
(IBES). Due to the availability of Detailed History Files from
IBES, our sampleperiod is from 1983 to 2003. Our final sample is an
unbalanced panel comprising 22,413 firm-yearobservations.
A. Measures of Dividend Policies
To explore the role of asymmetric information in dividend
policy, we focus on quarterly regulardividends to common
shareholders, the dividends with the greatest possible information
content.
1We thank an anonymous referee for pointing this out to us.
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Li & Zhao Asymmetric Information and Dividend Policy 675
The dividend items in Compustat (e.g., data items 21 and 26)
include nonregular dividendpayments, such as special dividends and
liquidation dividends, and thus they may not carry thesame
information content as predicted in the models of Bhattacharya
(1979), Miller and Rock(1985), and John and Williams (1985). We
note that using the dividend variables in Compustatto define our
dependent variables has no material effect on our main conclusions.
We followGrullon, Michaely, Benartzi, and Thaler (2005) and Amihud
and Li (2006) by using the CRSPdatabase to identify dividend and
nondividend payers.We collect all regular quarterly dividends on
ordinary common stocks in the CRSP daily file
(CRSP distribution code first digit = 1 (ordinary dividend);
second digit = 2 (cash, US dollars);third digit = 3 (quarterly
dividend); fourth digit = 2 (normal taxable at same rate as
dividend)).After adjusting for changes in number of shares
outstanding, we aggregate the quarterly dividendsinto an annual
dividend amount. We set our first dividend variable, the payer
dummy, equal toone for firm i in year t if the annual amount of
dividends paid is positive, and zero otherwise.Our second dividend
variable captures the initiation decisions of nondividend payers.
For firm i
in year t, we set the initiation dummy equal to one if this is
the first time firm i pays dividends, andzero for all the years
prior to year t. The dividend initiation sample includes only the
firm-yearsuntil the non-dividend-paying firm makes its first
dividend payment, or when the sample periodends, whichever comes
earlier. Over the sample period, if a firm omits and then resumes
dividendpayments, our initiation dummy variable captures only the
very first time that the firm initiateddividend payment.The
decision that dividend payers have to make on a regular basis is
whether or not to increase
dividends. Lintner (1956) shows that dividends are sticky and
firms usually are reluctant to cutor omit dividends. Thus, our next
measure of dividend policy examines dividend increases bydividend
payers. We set the increase of dummy equal to one for firm i in
year t if the percentageincrease in dividends is greater than 15%,
and zero otherwise. To exclude any minor changes inthe sample, we
use a cutoff point of 15% when we define dividend increases. Our
rationale isthat if the signaling models hold, then we are more
likely to find a negative relation between thequality of a firms
information environment and a large increase in dividends. Our main
resultsare not sensitive to the level of cutoff used in defining
the dividend increase dummy.We obtain our fourth dividend variable,
dividend payout, by scaling the annual dividend amount
by total assets. To ensure that our results are not driven by
price variation or affected by the factthat a significant
proportion of firms with negative earnings are paying dividends, we
normalizethe amount of dividends by book assets, instead of market
capitalization or earnings followingAllen and Michaely (2003).Table
I provides summary statistics of our dividend policy variables.
Column (1) shows that the
proportion of dividend payers declines steadily over the sample
period, starting at 80.0% in 1983and reaching 30.7% in 2002, with a
slight rebound in 2003.We note that the proportion of
dividendpayers is higher in our sample than in the one used by Fama
and French (2001), suggesting that oursample firms are on average
larger and more mature than the general population of firms
coveredin Compustat/CRSP. (We note that as a robustness check, we
examine the effect of our sampleselection criterion on our main
results.) This difference is due to our sample requirement for
theavailability of analyst forecast data. Nonetheless, the same
declining trend in the propensity topay dividends is evident
throughout most of our sample period.Column (2) in Table I reports
the fraction of first-time payers in year t among surviving
nondividend payers from year t 1. In our sample, the fraction of
firms that initiate dividendsstarts at 7.3% in 1983. This measure
drops steadily throughout most of the sample period andthen rises
again beginning in 2002. Column (3) shows that there is no apparent
time trend in thefraction of dividend payers increasing dividends.
Column (4) shows that the average dividend
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676 Financial Management Winter 2008
Table I. Time Series Characteristics of Dividend Policy
The sample period is from 1983 to 2003. We obtain accounting
information from Compustat, dividendinformation from CRSP, and
analyst forecasts from IBES. We define dividend payers as firms
that payquarterly dividends to common shareholders (CRSP four-digit
distribution code = 1232) in year t. Wedefine nondividend payers as
firms that do not pay dividends in year t. Dividend initiation
takes the valueof one if the firm makes its first dividend payment
in year t, and zero for all the years prior to t. Dividendincrease
takes the value of one if the percentage increase in dividends is
greater than 15%. We presentfrequency counts for dividend payers,
nondividend payers, and payers that increase dividends.
Dividendpayout is the ratio of annual aggregation of quarterly
dividends paid to common shareholders to total assetsat the end of
year t measured in percentages. We present annual averages for this
measure.
Year (1) (2) (3) (4)Proportion Proportion Proportion Dividendof
Dividend of Nondividend of Payers Payout
Payers Payers Initiating IncreasingDividends Dividends
1983 0.800 0.073 0.194 2.1201984 0.755 0.060 0.320 1.8481985
0.716 0.056 0.286 1.6881986 0.668 0.016 0.240 1.5221987 0.623 0.040
0.344 1.4651988 0.620 0.039 0.401 1.4611989 0.586 0.049 0.416
1.3351990 0.564 0.027 0.323 1.3361991 0.550 0.009 0.211 1.2991992
0.557 0.043 0.235 1.3221993 0.505 0.031 0.247 1.1711994 0.447 0.009
0.255 1.0411995 0.429 0.015 0.264 0.9451996 0.380 0.009 0.292
0.8681997 0.360 0.009 0.202 0.8091998 0.317 0.004 0.169 0.5871999
0.316 0.008 0.450 0.5492000 0.325 0.006 0.213 0.6152001 0.308 0.005
0.364 0.5582002 0.307 0.010 0.318 0.5352003 0.330 0.037 0.276
0.569
payout appears to decline steadily over the sample period, from
2.12% in 1983 to 0.54% in 2002,before rising in 2003. The
increasing use of dividends as cash payout toward the end of our
sampleperiod is probably partly due to the tax reform in 2003,
after which most dividends were taxed ata lower 15% rate.
B. Measures of Firms Information Environments
We use analyst earnings forecast errors and the dispersion in
analyst earnings forecasts tocapture the quality of a firms
information environment. Elton, Gruber, and Gultekin (1984)
showthat a large fraction of analyst forecast error is attributable
to misestimation of firm-specificfactors rather than to
misestimation of economy or industry factors. Their finding
suggests thatanalyst forecast errors are a reasonable proxy for the
degree of information asymmetry about thefirm.
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Li & Zhao Asymmetric Information and Dividend Policy 677
The dispersion in analyst earnings forecasts represents the
dispersion among analysts abouta consensus estimate of the
forecast. Since disagreement among analysts is an indication of
alack of available information, we use this standard deviation as
another metric of the degree ofinformation asymmetry for a firm.We
define analyst earnings forecast error as the absolute value of the
difference between the
mean earnings forecast and actual earnings, divided by the
absolute value of actual earnings.Dispersion of analyst earnings
forecast is the standard deviation of the earnings forecast
scaledby the absolute value of the mean earnings forecast. We
require our sample firms to have both ofthese measures available.We
have one reservation regarding our use of analyst forecast errors
and forecast dispersion
as measures of asymmetric information, which is that forecast
errors and dispersion might notso much capture asymmetries in
information as levels of uncertainty that are common to
bothmanagers and outside investors. For example, our measures might
pick up a more risky environ-ment for the firm, implying a greater
deviation than what we expected (and a larger variance ofsuch
deviations). We argue that this concern does not pose any serious
problems for our analysis.First, this is because other studies show
that our measures for information asymmetry do capturedimensions
beyond firm risk. Ajinkya, Atiase, and Gift (1991) and Lang and
Lundholm (1993,1996) show that as firms enhance information
disclosure, analyst earnings forecast accuracyincreases while
forecast dispersion decreases. Bowen, Davis, and Matsumoto (2002)
show thatconference calls improve analyst forecast precision and
reduce forecast dispersion, and Chen andMatsumoto (2006) find that
better access to management is associated with more accurate
analystforecasts. Second, the concern about risky environments does
not pose serious problems for ouranalysis because the positive
correlation between firm risk and our two measures for
asymmetricinformation is quite low (to be shown later). And to
further lessen this concern, we control forfirm risk in all of our
regression specifications. Thus, our results are not contaminated
by thecommonality between information asymmetry and uncertainty,
which is captured by firm risk.Panel A of Table II reports summary
statistics for our two measures of asymmetric information.
The mean (median) analyst earnings forecast error is 21.7%
(3.8%) of actual earnings, but themean (median) analyst forecast
dispersion is 14% (3.2%) of the mean earnings forecast. The
largedifference between mean and median values suggests that the
distributions of these two measuresare highly skewed.Panel B
presents summary statistics grouped by firm dividend policies. We
find that both
measures of asymmetric information are significantly lower for
dividend payers than are thoseobserved for nondividend payers. In
addition, nondividend payers who initiate dividends anddividend
payers with above-median payouts have lower forecast errors and
forecast dispersionthan do nondividend payers who do not initiate
dividends and dividend payers with below-medianpayout,
respectively. The univariate results suggest a negative association
between the degree ofinformation asymmetry and dividend
policies.
C. Other Firm Characteristics
We also control for other firm characteristics that may affect a
firms dividend policy: size,growth potential (the market-to-book
ratio (M/B ratio), and asset growth), profitability, andfirm risk.
Fama and French (2001) show that firms paying dividends are usually
larger, withlower growth potential and higher cash flows. We add
firm risk because Grullon, Michaely, andSwaminathan (2002), Hoberg
and Prabhala (2008), and Bulan, Subramanian, and Tanlu
(2007)suggest that firms pay dividends as a signal of firm maturity
and declining risk.
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678 Financial Management Winter 2008
We follow Fama and French (2001) in the construction of our
first four variables that describefirm characteristics. We define
profitability as earnings before extraordinary items (data 18)
+interest expense (data 15) + income statement deferred taxes (data
50, if available)/total assets(data 6). We use both the M/B ratio
and asset growth as growth opportunity measures. We definethe M/B
ratio as the ratio of the market value of total assets to the book
value of total assets. Wedefine the market value of total assets as
the market value of equity plus the book value of totalassets minus
the book value of equity, and the book value of equity is defined
as stockholdersequity (data 216) or common equity (data 60) +
preferred stock par value (data 130) or totalassets (data 6) total
liabilities (data 181), plus balance sheet deferred taxes and
investment taxcredit (data 35, if available) and postretirement
benefit liabilities (data 330, if available), minusthe book value
of preferred stocks (estimated in the order of the redemption (data
56), liquidation(data 10), or par value (data 130), depending on
availability). We define firm size as the annualpercentile of
market capitalization and use NYSE firms to calculate cutoff
points. We do so toneutralize any effects of the growth in typical
firm size through time, with the largest (smallest)firm taking the
value of one (0.01). For firm risk, we follow Hoberg and Prabhala
(2008) by usingthe standard deviation of residuals from a
regression of firm daily stock returns on returns ofthe market
portfolio. Our main results remain the same if we use the standard
deviation of dailyreturns or the standard derivation of residuals
from a regression of daily excess returns on thethree Fama and
French (1992) factors.Panel A of Table II presents the summary
statistics for firm characteristics. We show that the
mean (median) profitability of our sample firms is about 7.1%
(9.6%), and the mean (median)M/B ratio is 1.99 (1.49). The mean
(median) growth rate of assets is 23.6% (10.1%), suggestinga highly
skewed distribution for asset growth among sample firms. The mean
(median) firm riskis 2.79% (1.37%). Summary statistics of firm size
suggest that on average, our sample firms areslightly smaller than
the median NYSE firm but larger than the average publicly traded
firm. Interms of the risk measure, our sample firms are less risky
than an average public firm as examinedin Hoberg and Prabhala
(2008). The standard deviations indicate that there are large
variationsacross firms.In Panel C, Table II, we report the pairwise
correlations between firm characteristics and the
asymmetric information measures. The two asymmetric information
measures have a correlationof 0.37, suggesting that when analysts
cannot agree on a firms earnings forecast, they are lesslikely to
provide accurate forecasts. Neither of the asymmetric information
measures is highlycorrelated with the firm characteristics that we
find are important determinants of dividend policy.In particular,
the correlations between firm risk and the two measures of
information asymmetryare below 0.09. This result confirms that
there is some overlap between firm risk and ourmeasuresof
information asymmetry. However, it also indicates that the extent
of overlap is limited, whichsuggests that our two measures do pick
up aspects of a firms information environment that arenot captured
by firm risk. Thus, our two measures are more likely to be
exogenous proxies forasymmetric information, implying that our
model specification should be a relatively clean testof the
relation between information asymmetry and dividend policy.
II. Main Results
Given that most of our analyses involve panel data, our
estimates are based on robust standarderrors. We estimate these
errors by assuming independence across firms, but we account
forpossible autocorrelation within the same firm. The robust
standard errors are frequently muchlarger than conventional
estimates, which assume independence among firm-year
observations,
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Li & Zhao Asymmetric Information and Dividend Policy 679
Table II. Summary Statistics
The sample period is from 1983 to 2003. We obtain accounting
information from Compustat, dividendinformation from CRSP, and
analyst forecasts from IBES. We define profitability as earnings
beforeextraordinary items (data 18) + interest expense (data 15) +
income statement deferred taxes (data 50,if available)/total assets
(data 6). The market-to-book (M/B) ratio is the ratio of the market
value of totalassets to the book value of total assets. Asset
growth is the rate of growth of total assets. Firm size is theNYSE
market capitalization percentile. Firm risk is the standard
deviation of residuals from the marketmodel measured in
percentages. We define forecast error as the absolute value of the
difference betweenmean analyst earnings forecasts and actual
earnings, divided by the absolute value of actual earnings.
Wedefine forecast dispersion as the standard deviation of analyst
earnings forecast scaled by the absolute valueof the mean earnings
forecast. Panel A presents summary statistics of firm
characteristics and measuresof firms information environment. Panel
B presents summary statistics of measures of firms
informationenvironment for firms with different dividend
characteristics. Panel C presents a correlation matrix of
firmcharacteristics and measures of firms information environment.
p-values appear in parentheses.
Panel A. Firm Characteristics and Information Environment
Mean Median Standard 25th 75thDeviation Percentile
Percentile
Profitability 0.071 0.096 0.203 0.046 0.146M/B ratio 1.992 1.494
1.742 1.137 2.199Asset growth 0.236 0.101 1.103 0.012 0.252Firm
size 0.473 0.450 0.289 0.220 0.720Firm risk 2.786 1.371 1.771 2.480
3.479Forecast error 0.217 0.038 0.622 0.013 0.125Forecast
dispersion 0.140 0.032 0.357 0.013 0.095
Panel B. Measures of Firms Information Environment Grouped by
Dividend Policy
Mean Standard 25th Median 75thDeviation Percentile
Percentile
Forecast errorDividend payers 0.162 0.517 0.010 0.030
0.090Nondividend payers 0.267 0.700 0.016 0.049 0.167Difference
0.104p-value
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680 Financial Management Winter 2008
Table II. Summary Statistics (Continued)
Panel B. Measures of Firms Information Environment Grouped by
Dividend Policy (Continued)
Mean Standard 25th Median 75thDeviation Percentile
Percentile
Dividend payers with above-median payouts 0.072 0.209 0.010
0.023 0.051Dividend payers with below-median payouts 0.161 0.389
0.014 0.037 0.117Difference 0.089p-value
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Li & Zhao Asymmetric Information and Dividend Policy 681
growth potential are more likely to pay dividends. Moreover, we
show that risky firms are lesslikely to pay dividends. This finding
confirms the result in Grullon et al. (2002) and Hoberg andPrabhala
(2008).More importantly, after controlling for the usual
determinants of a firms propensity to pay
dividends, our results show negative coefficients on both
measures of information asymmetry,which suggests that firms in a
poorer information environment are less likely to pay
dividends.This evidence does not support the signaling models of
dividends.In Panel B, we report the results from the logistic
regressions that we use to examine the
nondividend payers decisions to initiate dividends. Similar to
our results on the decision to pay,we find that larger, more
profitable firms are more likely to initiate dividend payments.
Thepropensity to initiate dividends is negatively associated with
the M/B ratio. After we control forthe M/B ratio, we find that the
asset growth rate is positively associated with the propensity
toinitiate dividends. Also, risky firms are less likely to initiate
dividends, a result that is consistentwith the maturity and risk
argument. Both measures of asymmetric information are
negativelyassociated with the likelihood of dividend
initiation.Panel C presents regression results from our examination
of the decision to increase dividends
among payers. We find that more profitable firms are more likely
to increase dividends. Thepositive effect of M/B ratios on the
likelihood of increasing dividends appears to contradictthe growth
opportunity argument. However, this result can be explained by the
dual role played bytheM/B ratio. Fama and French (2002) suggest
that theM/B ratio is ameasure of both profitabilityand growth
potential. It is likely that theM/B ratio ismore ameasure of
profitability than ameasureof growth opportunities among
dividend-paying firms. Both measures of asymmetric informationare
negatively associated with the likelihood of increasing
dividends.In Panel D, we examine the determinants of the level of
dividend payout. We show that larger,
more profitable firms with lower risk pay more cash dividends.
Consistent with the findings fromthe other panels, both asymmetric
information measures are negatively related to the amount
ofdividends paid.Our findings lead us to conclude that there is a
negative relation between asymmetric informa-
tion and measures of dividend policy. Our results do not support
the signaling theory of dividends.We note that using insider
returns as a proxy for information asymmetry, Khang and King
(2006)show that the amount of dividends is negatively related to
returns to insider trades across firms.They thus conclude that
their results do not support the signaling theory of dividends
either.
III. Additional Investigation
Here, we address other possibilities that may lead to our
results. First, we ask if our sampleconstruction, which requires
firms to have data available on analyst earnings forecasts,
couldsystematically bias our findings. Second, we ask if a
significant part of our results could beexplained by the increasing
use of share repurchases as a form of payout. Third, we ask
howsensitive are our results to other factors that have been
suggested in the literature to explaindividend policy, such as
institutional monitoring and catering.
A. Sample Selection
As mentioned before, our sample firms are different from the
general population covered inCompustat/CRSP as examined in Fama and
French (2001). So the important question is, doesthis sample
difference drive the results?2
2We thank an anonymous referee for suggesting this analysis to
us.
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682 Financial Management Winter 2008
Table III. Explaining Dividend Policy
The sample period is from 1983 to 2003. We obtain accounting
information from Compustat, dividendinformation from CRSP, and
analyst forecasts from IBES. We define profitability as earnings
beforeextraordinary items (data 18) + interest expense (data 15) +
income statement deferred taxes (data 50, ifavailable)/total assets
(data 6). The market-to-book (M/B) ratio is the ratio of the market
value of total assetsto the book value of total assets. Asset
growth is the rate of growth of total assets. Firm size is the
NYSEmarket capitalization percentile. Firm risk is the standard
deviation of residuals from the market modelmeasured in
percentages. We define forecast error as the absolute value of the
difference between meananalyst earnings forecasts and actual
earnings, divided by the absolute value of actual earnings. We
defineforecast dispersion as the standard deviation of analyst
earnings forecast scaled by the absolute value of themean earnings
forecast. The dependent variable in Panel A is the payer dummy set
equal to one for firm iin year t if the annual amount of dividends
paid is positive, and zero otherwise. The dependent variable
inPanel B is the initiation dummy set equal to one if this is the
first time firm i pays dividends, and zero for allthe years prior
to year t. The dependent variable in Panel C is the increase dummy
set equal to one for firmi in year t if the percentage increase in
dividends is greater than 15%, and zero otherwise. The
dependentvariable in Panel D is dividend payout, which we define as
the ratio of annual aggregation of quarterlycommon dividends
obtained from CRSP to total assets measured in percentages. The
estimation includesindustry and year dummies. We base the reported
p-values on White (1980) heteroskedasticity-consistentstandard
errors, adjusted to account for possible correlation within a
(firm) cluster.
Panel A. The Decision to Pay Dividends
(1) (2) (3)
Profitability 2.446 2.413 2.370[
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Li & Zhao Asymmetric Information and Dividend Policy 683
Table III. Explaining Dividend Policy (Continued)
Panel B. The Decision to Initiate Dividends (Continued)
(1) (2) (3)
Firm risk 0.592 0.586 0.581[
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684 Financial Management Winter 2008
Table III. Explaining Dividend Policy (Continued)
Panel D. The Decision on the Amount of Dividends (Continued)
(1) (2) (3)
Forecast error 0.052 0.021[0.001] [0.146]
Forecast dispersion 0.173 0.161[
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Li & Zhao Asymmetric Information and Dividend Policy 685
Table IV. Sample Selection
The sample period is from 1983 to 2003. To assess the impact of
sample selection criterion on our mainresults, we expand the sample
to include all firms from the Compustat/CRSP merged file. For firms
withoutinformation on analyst forecasts, we assign zero to their
forecast errors and forecast dispersion. We also addto the
regression model the no analyst coverage dummy, which we set equal
to one for firms without anyanalyst coverage, and zero otherwise in
year t. We define profitability as earnings before extraordinary
items(data 18) + interest expense (data 15) + income statement
deferred taxes (data 50, if available)/total assets(data 6). The
market-to-book (M/B) ratio is the ratio of the market value of
total assets to the book value oftotal assets. Asset growth is the
rate of growth of total assets. Firm size is the NYSE market
capitalizationpercentile. Firm risk is the standard deviation of
residuals from the market model measured in percentages.We define
forecast error as the absolute value of the difference between mean
analyst earnings forecastsand actual earnings, divided by the
absolute value of actual earnings. We define forecast dispersion as
thestandard deviation of analyst earnings forecast scaled by the
absolute value of the mean earnings forecast.The dependent variable
in Column (1) is the payer dummy, set equal to one for firm i in
year t if the annualamount of dividends paid is positive, and zero
otherwise. The dependent variable in Column (2) is theinitiation
dummy, set equal to one if this is the first time firm i is paying
dividends, and zero for all theyears prior to year t. The dependent
variable in Column (3) is the increase dummy, set equal to one for
firmi in year t if the percentage increase in dividends is greater
than 15%, and zero otherwise. The dependentvariable in Column (4)
is dividend payout, which we define as the ratio of annual
aggregation of quarterlycommon dividends obtained from CRSP to
total assets measured in percentages. The estimation
includesindustry and year dummies. We base the reported p-values on
White (1980) heteroskedasticity-consistentstandard errors adjusted
to account for possible correlation within a (firm) cluster.
(1) (2) (3) (4)Decision Decision Decision Decision onto Pay to
Initiate to Increase the Amount
Dividends Dividends Dividends of Dividends
Profitability 3.170 4.007 5.426 0.077[
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686 Financial Management Winter 2008
Table V. Repurchase, Institutional Ownership, and Catering
The sample period is from 1983 to 2003. We obtain accounting
information from Compustat, dividendinformation from CRSP, and
analyst forecasts from IBES. We define profitability as earnings
beforeextraordinary items (data 18) + interest expense (data 15) +
income statement deferred taxes (data 50,if available)/total assets
(data 6). The market-to-book (M/B) ratio is the ratio of the market
value of totalassets to the book value of total assets. Asset
growth is the rate of growth of total assets. Firm size is theNYSE
market capitalization percentile. Firm risk is the standard
deviation of residuals from the marketmodel measured in
percentages. We define forecast error as the absolute value of the
difference betweenmean analyst earnings forecasts and actual
earnings, divided by the absolute value of actual earnings.
Wedefine forecast dispersion as the standard deviation of analyst
earnings forecast scaled by the absolutevalue of the mean earnings
forecast. The repurchase amount is the product of the
split-adjusted changein shares outstanding and the average of the
split-adjusted stock price at the beginning and the end of theyear,
normalized by total assets and measured in percentages.
Institutional ownership is the fractional shareownership by
institutions. Dividend premium is the difference between log(M/B
ratio) for dividend payersand the same measure for nondividend
payers. The dependent variable in Panel A is the payer dummy,
setequal to one for firm i in year t if the annual amount of
dividends paid is positive, and zero otherwise.The dependent
variable in Panel B is the initiation dummy, set equal to one if
this is the first time firm i ispaying dividends, and zero for all
the years prior to year t. The dependent variable in Panel C is the
increasedummy, set equal to one for firm i in year t if the
percentage increase in dividends is greater than 15%,and zero
otherwise. We define the dependent variable in Panel D, dividend
payout, as the ratio of annualaggregation of quarterly common
dividends obtained from CRSP to total assets measured in
percentages.The estimation has industry and year dummies included.
We base the reported p-values on White
(1980)heteroskedasticity-consistent standard errors adjusted to
account for possible correlation within a (firm)cluster.
Panel A. The Decision to Pay Dividends
(1) (2) (3) (4)
Profitability 2.190 2.948 3.209 2.873[
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Li & Zhao Asymmetric Information and Dividend Policy 687
Table V. Repurchase, Institutional Ownership, and Catering
(Continued)
Panel B. The Decision to Initiate Dividends
(1) (2) (3) (4)
Profitability 7.148 7.089 8.255 8.059[
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688 Financial Management Winter 2008
Table V. Repurchase, Institutional Ownership, and Catering
(Continued)
Panel D. The Decision on the Amount of Dividends
(1) (2) (3) (4)
Profitability 0.460 0.691 1.283 1.131[0.018] [0.001] [
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Li & Zhao Asymmetric Information and Dividend Policy 689
C. Institutional Shareholdings
Allen, Bernardo, andWelch (2000) present amodel in which they
use dividends to attract better-informed, monitoring, institutional
shareholders. Their theory predicts a positive correlationbetween
dividends and institutional shareholdings.To explore whether our
results are driven by institutional monitoring, we control for
institutional
holdings in our regression specifications, and report the
results in Table V, Column (2). We findthat measures of asymmetric
information remain negatively related to firms dividend
policies.Further, contrary to the monitoring argument in Allen et
al. (2000), but mostly consistent with theempirical findings in
Grinstein and Michaely (2005), we show that, after we control for
firm risk,firms with higher institutional shareholdings are less
likely to pay dividends and are associatedwith lower dividend
payouts. It is clear that the negative relation between asymmetric
informationand dividend policy is not explained by the presence of
(monitoring) institutional shareholders.Again, our results fail to
lend support to the signaling theory of dividends.
D. The Catering Theory of Dividends
Using aggregate data, Baker and Wurgler (2004) develop their
catering theory of dividends.They find that investor demand for
dividend-paying stocks is time-varying. Managers cater toinvestor
demand for dividends by paying dividends when investors place a
premium on dividend-paying stocks, and vice versa.We use the
dividend premium measure provided in Baker and Wurgler (2004),
which they
define as the difference in the value-weighted averageM/B ratio
of payers and the value-weightedaverage M/B ratio of nondividend
payers. We add this measure to Equation (1). Column (3) ofTable V
presents the results. (We note that because the sample in Baker and
Wurglers, 2004,study ends in 2000, the sample size with the
catering measure is smaller.) We find that adding thedividend
premium into our model specification has no material effect on the
role of asymmetricinformation in dividend policy.Moreover, the
coefficient estimate of dividend premium contradicts the argument
in Baker and
Wurgler (2004). We show that this finding is mainly due to our
inclusion of the year dummiesand firm risk. Once we remove these
dummies and the risk variable, the coefficient on dividendpremium
is significant and positive. This result is consistent with Baker
and Wurglers argumentthat the dividend premium primarily captures
the temporal variation in market sentiment.Column (4) of Table V
presents our results when we use all additional dividend factors.
It is
clear that our main results on asymmetric information do not
change with this expanded modelspecification. Thus, we conclude
that the negative relation between information asymmetry
anddividend policy is not driven by other factors that may affect a
firms dividend policy. And again,our evidence does not support the
signaling theory of dividends.
IV. Repurchase and Total Payout
Although our main focus is on the relation between information
asymmetry and firms divi-dend policies, we also examine whether
information asymmetry is an important consideration forrepurchases.
Vermaelen (1984), Ofer and Thakor (1987), and McNally (1999) extend
the modelsin Bhattacharya (1979) and Miller and Rock (1985) to
repurchases, suggesting that the signalingmotive may also determine
firms repurchase decisions. However, the inherent inflexibility
individends implies that dividends have stronger informational
content than do repurchases. Thus,if the signaling models are
valid, we expect to find a weaker (less positive or more
negative)
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690 Financial Management Winter 2008
relation between asymmetric information and repurchases (or
total payouts) than between asym-metric information and dividends.
Therefore, we examine the relation between repurchases
andinformation asymmetry separately, and we opt not to combine
repurchase and dividend policiesin our main analysis.We use the two
repurchase measures defined in Section III, the repurchase dummy
and the
repurchase amount. We define the total payout policy variables
in a comparable way. We set thepayout dummy equal to one for firm i
in year t if the firm either pays dividends or repurchasesshares,
and zero otherwise. The total payout aggregates all dividends paid
and the amountrepurchased during the year, scaled by total
assets.We report the time-series characteristics of repurchase and
payout measures in Table VI,
Panel A. We see that the proportion of repurchasing firms
increases from 1983 to 1990, declinesafterward, and then peaks
again toward the end of the technology bubble. The proportion of
firms
Table VI. Summary Statistics of Repurchase and Payout
Policies
The sample period is from 1983 to 2003. We obtain accounting
information from Compustat, divi-dend/repurchase information from
CRSP, and analyst forecasts from IBES. We define repurchasing firms
asthose firms that make nontrivial repurchases in year t and
nonrepurchasing firms as those firms that makeno repurchases in
year t. The repurchase amount is the ratio of the product of the
split-adjusted change inshares outstanding and the average of the
split-adjusted stock price at the beginning and the end of the
year,normalized by total assets. Payout firms are firms that either
pay dividends or make repurchases or both inyear t and nonpayout
firms are those that make no payout in year t. We define total
payout as the ratio ofthe sum of the dividend payout and repurchase
amount in year t to total assets.
Panel A. Time-Series Characteristics of Repurchase and Payout
Policies
Year (1) (2) (3) (4)Proportion of Repurchase Proportion of
TotalRepurchasing Amount Payout Payout
Firms Firms
1983 0.121 0.262 0.817 2.3811984 0.283 1.053 0.808 2.9011985
0.210 0.779 0.743 2.4661986 0.252 1.179 0.712 2.7011987 0.259 1.418
0.701 2.8831988 0.377 2.096 0.712 3.5571989 0.271 1.111 0.652
2.4461990 0.333 1.441 0.651 2.7771991 0.193 0.696 0.599 1.9961992
0.172 1.709 0.602 3.0311993 0.166 0.724 0.552 1.8941994 0.186 0.775
0.503 1.8161995 0.214 0.969 0.495 1.9141996 0.211 0.938 0.453
1.8061997 0.240 1.458 0.452 2.2671998 0.297 1.569 0.457 2.1561999
0.259 1.339 0.440 1.8892000 0.307 2.322 0.464 2.9372001 0.208 0.957
0.400 1.5152002 0.209 0.972 0.432 1.5072003 0.202 0.833 0.425
1.402
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Li & Zhao Asymmetric Information and Dividend Policy 691
Table VI. Summary Statistics of Repurchase and Payout Policies
(Continued)
Panel B. Measures of Firms Information Environment Grouped by
Repurchasing or Not,and Paying Out or Not
Mean Median Standard 25th 75thDeviation Percentile
Percentile
Forecast errorRepurchasing firms 0.174 0.553 0.010 0.029
0.090Nonrepurchasing Firms 0.231 0.641 0.014 0.042 0.139Difference
0.057p-value
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692 Financial Management Winter 2008
Table VII. Explaining Repurchase and Payout Policies
The sample period is from 1983 to 2003. We obtain accounting
information from Compustat, divi-dend/repurchase information from
CRSP, and analyst forecasts from IBES. We define profitability
asearnings before extraordinary items (data 18) + interest expense
(data 15) + income statement deferredtaxes (data 50, if
available)/total assets (data 6). The market-to-book (M/B) ratio is
the ratio of the marketvalue of total assets to the book value of
total assets. Asset growth is the rate of growth of total
assets.Firm size is the NYSE market capitalization percentile. Firm
risk is the standard deviation of residualsfrom the market model
measured in percentages. We define forecast error as the absolute
value of thedifference between mean analyst earnings forecasts and
actual earnings, divided by the absolute value ofactual earnings.
We define forecast dispersion as the standard deviation of analyst
earnings forecast scaledby the absolute value of the mean earnings
forecast. The dependent variable in Column (1) is the
repurchasedummy, set equal to one for firm i in year t if the
annual amount of repurchases is positive, and zerootherwise. The
dependent variable in Column (2), repurchase amount, is the product
of the split-adjustedchange in shares outstanding and the average
of the split-adjusted stock price at the beginning and the endof
the year, normalized by total assets. The dependent variable in
Column (3) is the payout dummy, set equalto one for firm i in year
t if the annual amount of payout is positive, and zero otherwise.
We define thedependent variable in Column (4), total payout, as the
ratio of the sum of the dividend payout and repurchaseamount to
total assets. The estimation includes industry and year dummies. We
base the reported p-valueson White (1980)
heteroskedasticity-consistent standard errors adjusted to account
for possible correlationwithin a (firm) cluster.
(1) (2) (3) (4)Decision to Repurchase Decision to
TotalRepurchase Amount Pay Out Payout
Profitability 2.574 1.780 2.259 2.335[
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Li & Zhao Asymmetric Information and Dividend Policy 693
Prior research shows that forecast errors and dispersion are
positively correlated with the extentof information asymmetry that
firms face. We conjecture that if the signaling theory of
dividendsis an accurate description of reality, then firms dividend
policies should be positively associatedwith analyst earnings
forecast errors and forecast dispersion.Using a CRSP/Compustat/IBES
combined sample over 1983-2003 and controlling for firm
characteristics, we find that, ceteris paribus, firms more
subject to the problem of informationasymmetry are less likely to
make dividend payments, to initiate dividends, and to
increasedividends, and that these firms also distribute smaller
amounts. Our conclusions are not drivenby sample selection
criteria, and they hold after we control for contemporaneous
repurchasingactivities, the presence of monitoring institutional
investors, and catering incentives. Therefore,our evidence casts
doubt on the validity of the dividend signaling models.We find a
weak negative relation between repurchases andmeasures of
information asymmetry.
This finding further strengthens our evidence on the lack of
support for the signaling theory ofdividends.
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