What decide the Endowment and Annual Giving Size

WHAT DECIDE THE ENDOWMENTAND ANNUAL GIVING SIZE?

—BASED ON THE EMPIRICAL ANALYSIS OF UNIVERSITIES IN

AMERICA

XINWEI LIU

Abstract

This Paper, picking the university data as research samples,

takes advantages of the Multiple Linear Regression Model and

uses the empirical method to testify whether performances of

universities in the current year have impact on the size of

Endowment Assets and Annual Giving next year. The regression

results signify: Better performances of universities in

current year significantly increase the total number of

Endowment Assets and Annual Giving next year by sending to

donors and public signals that universities with better

performances have good research potential and high-quality

education potential and are deserved to be donated.

【Key Words 】 University Performances Endowment Annual

Giving

Introduction

Everyone wants to stand first in line, first in the hearts

of the country and first in the standings. The pursuit of

Number One is surely an important thing in sports or games.

Universities, however, standing in the first line is not so

important as standing among top ones. As the development of

society, 21st century shows no lessening of interest among

researchers, donors, government supports in using various

criteria to assess the performance of research institutes.

As always, University Endowment and Annual Giving in

America play an important role in the development of

universities, not only for public universities but also for

private universities. First, endowment is one of the main

sources of financial income of almost all the universities in

America since university is a kind of special non-profit

organization whose main goal is not making money. The fact is

that Endowments, Federal Support and Tuition Income consist of

more than 90% of every university’s income. Second, endowments

lay the foundation of research achievements of universities.

Given the fact that abundant financial power is the footstone

of the beginning research studies, even starting a research

will not come true without the guarantee of financial power.

Consequently, maintaining the Endowment size is the key factor

to the long-term success of universities.

Recently, Endowments issues attract more attention not

only because of the importance itself but also because of the

increased gap between top universities such as Ivy League and

other universities. Since 1992, the gap has been increased:

top universities (top 25) are richer while others fall behind.

(Josh Lerner and Jialan Wang, 2008) Why do top universities

such as Ivy League become richer? It’s not only because of

outstanding breakthroughs or research achievements they made

every year but also because of other factors such as National

Academy Membership, Faculty Awards, Doctorates Awarded,

Postdoctoral Appointees and the high average SAT Scores,

mirroring their high research and education qualities. These

measurements reflect the quality of a university from

different area. National Academy Membership represents the

excellent scholars and their researches. Faculty Awards is an

element that can reflect the faculty reputation and

achievements of a university. Doctorate Awarded and

Postdoctoral Appointees evaluates the ability to cultivate

potential researchers in the future. Average SAT Score imply

the quality of students entering the university. All these

factors reflect the quality of a university from different

aspect. Since these measurements are used to measure the

performance of University and the performances are criteria

for endowment. There does exist a necessity to find relations

between endowment size and measurements of performance, thus

providing evidence and methods for universities to keep long-

term successes.

Literature Review

When talked about the Endowments and measurements of

universities, many scholars have showed interests in some

aspects. Hoover and Farrell in 2007 found that top research

institutions such as Harvard and Princeton have used their

deep pocket to increase admissions and reduce effective

tuition rates, thus broadening the excess for elite education.

Gifts to Annual Giving allow universities to provide

extraordinary opportunities for learning and discovery; to

extend the financial aid program to more students who needs

it; and to help meet the emerging needs and challenges. The

funds of Annual Giving provide universities the flexibility to

undertake critical new initiatives such as developing the new

science research program and attracting world-renewed faculty

and so on so forth.

On the contrary, poor financial endowment will endanger the

development of a university. As Carlson said in 2007,

Antioch’s only 36 million endowments made financial

insecurity, leading to decaying facilities and declining

students enrollment. Some scholars focused on superior

investment returns of endowments compared with other

institutional investors (Lerner, Schoar and Wongsungwai,

2007). Josh Lerner and Jialan Wang, 2008 found that much of

growth in endowment size has been driven by investment

performance. What’s more, while investment in some assets have

been successful, there have also been some loss, like the $350

million investment loss that Harvard experienced in Sowood

Capital Management (Karmin and Zucker, 2007).

Most universities measure themselves on a wide range of

dimensions that they believe important for them to make

decisions. Moreover, no single indicator or study shows what

research institutes have done, can do and will do. To improve

the quality of education and research of a research institute,

its students, faculty, staff and supporters have to put the

power together to achieve the improvement among the best

universities. Since it is a fact that both private and public

universities live on the resources generated from tuition,

government support and endowment, the critical resource for

universities is the income generated from Endowment or Annual

Giving. Although Endowment attracts many scholars’ interests,

the real relation between endowment and performance

measurements of university still remains uncovered.

According to the review above, I made my hypothesis of this

paper:

H1: Performances of Universities are signals for

University donors.

H2: Performances of Universities have positive impacts on

the Size of Endowment Assets.

H3: Performances of Universities have positive impacts on

the Size of Annual Giving.

My research, in some extent, provides answers to unanswered

questions as to Endowment and Annual Giving. By finding

relationships between long-term strength “Endowment” and

measurements of university performance and between short-term

indicator “Annual Giving” and measurements of university

performance, my research have contributions to enrich the

university study. From university’s perspective, my research

gives basic considerations of the ways to improve the quality

of universities and to attract more endowment. From donors’

perspective, my research lays a foundation for making

endowment decision in terms of the performances of

universities. Not only for keeping the long-term success of

universities but also for making endowment decisions of

investors, my research provides some guidance.

Research Design

1. Sample Selection

All the Sample data of this paper come from The Center for

Measuring University Performance, samples including 771

universities and colleges in United States. In order to be

more accurate, I selected 771 universities’ data from 2005 to

2011. I choose the data of Endowment Assets, Annual Giving,

Total Research Expenses, Average SAT Scores, Faculty Rewards,

National Academy Membership, Postdoctoral Appointees and

Doctorates Awarded from 2004 to 2011 as samples. Each item has

the number of 5391 data from 2004 to 2011. Given the fact that

I focus on the relationship between the performances of

university in t year and the Endowment and Annual Giving Size

in t+1 year, data of the dependent variables such as Endowment

Assets and Annual Giving are selected from 2005 to 2011. Other

independent variables are chosen from 2004 to 2010.

According to the experience of regression and the basic

background of these university data, I made the following

standards as criteria to adjust data.

(1)Since a certain number of universities didn’t have

Endowment Assets or Annual Giving and some didn’t have

Research Expenses, I delete all the vacant data that may

affect the regression results.

(2)Moreover, I eliminated useless data and extreme-value data

to minimize the regression error.

After the adjusted work, the total number of each item changed

from 5390 to 4823 for each item.

2. Data Description Statistics

Table 1 shows the Description Statistics of the sample

data before elimination. The total Observed Sample is 4823. I

pick the following items as performance measurements of

universities and specific data description is in Table 1.

Table 1. Date Description

Mean Median Min Max Observed

Value

EndAti,t+170374 133971 182 36556284 4823

AnulGi,t+131257 10202 147 709423 4823

TRexpi,t71761 4057 0 1997252 4823

SATavgi,t1119 1105 735 1525 4823

FRewdi,t3.589 1 0 116 4823

NAMembi,t5.7536 0 0 348 4823

PostDAi,t77.5796 0 0 5827 4823

DoctAi,t73.4047 6 0 911 4823

3. Empirical Modeling Design

(1). Empirical Modeling

lnEndAti,t+1=α0+α1lnTRexpi,t+α2lnSATavgi,t+α3lnFRewdi,t+α4lnNAMembi,t+α5lnPostDAi,t+α6lnDoctAi,t(1)

In the Model (1):

The EndAti,t+1 represents the Endowment Assets in dollar of

i university in t+1 year; TRexpi,tis Total Research Expense in

dollar of i university in t year; SATavgi,t is Average SAT Score

of i university in t year; FRewdi,t is Faculty Rewards of i

university in t year; NAMembi,t is the number of National

Academic Membership of i university in t year;PostDAi,t is the

number of Post Doctor Awarded of i university in t year;

DoctAi,t is the number of Doctor Awarded i university in t year.

In this Model, I focus on figuring out the relationship

between the performances measurements of universities in t year

and the Total number of Endowment Assets in t+1 year. Is the

size of Endowment Assets in t+1 year affected by how universities

performed in t year. If the Coefficients of each variable are

positive, it means that the good performance of universities

in t year will obviously increase the Total Size of Endowment

Assets in t+1 year, or vise versa. Moreover, the Coefficients, α1,

α2, α3, α4, α5, α6, mean how the dependent variable changes

with the change of six independent variables.

lnAnulGi,t+1=β0+β1lnTRexpi,t+β2lnSATavgi,t+β3lnFRewdi,t+β4lnNAMembi,t+β5lnPostDAi,t+β6lnDoctAi,t(2)

In the Model (2):

The AnulGi,t+1is Annual Giving in dollar of i university in

t+1 year. TRexpi,tis Total Research Expense in dollar of i

university in t year; SATavgi,t is Average SAT Score of i

university in t year; FRewdi,t is Faculty Rewards of i

university in t year; NAMembi,t is the number of National

Academic Membership of i university in t year;PostDAi,t is the

number of Post Doctor Awarded of i university in t year;

DoctAi,t is the number of Doctor Awarded i university in t year.

In this Model, I focus on the relations between the Annual

Giving in dollars of universities in t+1 year and the

performance measurements of universities in t year. If the

Coefficients of each Independent variables are obviously

positive, it means that good performances for universities in t

year will lead to better impressions to donors, thus

increasing the total number of Annual Giving in t+1 year, or

vise versa. Like the meaning of coefficients in Model (1),

coefficients of six independent variables, β1, β2, β3, β4, β5,

β6, explain how the Annual Giving changes with the changes of

these six independent variables.

(2). Analysis of Regression Results

Based on the Model (1), I use R-software to do the

regression work. The results of regression are listed in Table

2.

Table 2: Effects of Performance Measurements on Endowment

Assets

Estimate

(αn)

Std.

Error

T Value P Value Sig.

α0-44.02586 1.44655 -30.435 <2e-16 ***

lnTRexpi,t0.02263 0.01445 1.566 0.117548

lnSATavgi,t7.81373 0.20542 38.037 <2e-16 ***

lnFRewdi,t0.14956 0.04528 3.303 0.000982 ***

lnNAMembi,t0.13143 0.03780 3.477 0.000522 ***

lnPostDAi,t0.04093 0.02803 1.460 0.144413

lnDoctAi,t0.15224 0.01925 7.908 5.35e-15 ***

R- Square 0.7539

Adjusted

R-Square

0.7528

P – Value <2.2e-16 ***

Notes: “*”, “**”, “***” means significance in 10%, 5%, and 1%

levels respectively.

From the results above, four coefficients of four

independent variables are obviously positive, which means: the

increase of Average SAT Scores, the increase of Faculty

Rewarded, the increase of National Academic Membership and the

increase of Doctor Awarded of a university in one year will

lead to an increase of Endowment Assets next year. That is,

good performance significantly increase the Size of Endowment

Assets by sending good signals to donors that the potential

good research ability of a university and the potential high

education quality of a university. Moreover, the P Value of

variables lnSATavgi,t, lnFRewdi,t, lnNAMembi,t and lnDoctAi,t

are quite small with three stars “***”, meaning that their

effects are extremely significant under the 1% significant

level.

On the contrary, the P-Value of the lnTRexpi,t and

lnPostDAi,tare not significant, meaning the changes of Total

Research Expenses and Number of Post Doctor Awarded in one

year have no obvious impacts on the Endowment Assets next

year. The R-Square Value and Adjusted R-Square Value are

0.7539 and 0.7528, respectively, meaning that changes of all

the six independent variables are completely enough to explain

the changes of dependent variable: Endowment Assets. The

explained power is 75%. The P-Value of the whole Model (1) is

“< 2.2e-16” which is quite small, pointing out the Model I

designed is quite appropriate and the degree of fitting is

quite powerful.

Using same method to do the regression, the results of

Model (2) regression are listed in Table 3.

Table 3: Effects of Performance Measurements on Annual Giving

Estimate

(βn)

Std.

Error

T Value P Value Sig.

β0-21.19810 1.27240 -16.660 <2e-16 ***

lnTRexpi,t0.06432 0.01271 5.062 4.72e-07 ***

lnSATavgi,t4.15510 0.18070 22.995 <2e-16 ***

lnFRewdi,t0.22635 0.03983 5.683 1.62e-08 ***

lnNAMembi,t0.09407 0.03324 2.830 0.00472 **

lnPostDAi,t0.12573 0.02465 5.101 3.8e-07 ***

lnDoctAi,t0.07862 0.01693 4.643 3.76e-06 ***

R- Square 0.7362

Adjusted

R-Square

0.7418

P – Value <2.2e-16 ***

Notes: “*”, “**”, “***” means significance in 10%, 5%, and 1%

levels respectively.

According to Table 3, unlike the regression results in

Model (1), six coefficients of all the independent variables

are positive, signifying that the increase of each item in t

year will lead to the increase of Annual Giving in t+1 year.

Given the fact that the smaller the P Value, the more

significance of the regression results. According to the P

Value in Table 3, Total Research Expenses, SAT Average Scores,

Faculty Rewards, Post Doctor Awarded and Doctor Awarded are

all significant under the 1% significance level, while the

National Academic Membership is less significant under 5%

significance level than others. The results point out that the

improvement or better performances of a university in one year

will obviously have positive impact on the increase of the

Annual Giving next year since good performances send donors

signals that one university is deserved to be given money for

research and education.

Once a university expends its research by increasing its

Total Research Expenses, enhances its students’ quality with

higher Average SAT Scores, improves its’ research by adding

the National Academic Membership and makes advance in future

research by cultivating more Post Doctors and Doctors, it

sends signals to donors, attracts their attentions and finally

increases the Endowment and Annual Giving, thus verifying the

hypothesis H1, H2 and H3 I proposed in the beginning.

Robustness Test

In order to testify the robustness of the regression

results I listed above, I certified my results in other two

areas.

1. Add two performance measurements into Independent Variables

In both Model (1) and Model (2), I added another two

independent variables in the original six measurements:

Federal Research Expenditures and National Merit and

Achievement Scholars. After the same regression process, the

conclusions remain unchanged.

2. Group by Ranking

Given the fact that the original samples include different

level of universities, I classified those data into three

groups: top 100, 100-200 and universities ranking after 200.

Clarifying different levels, I did the same regression

process, the conclusion remain unchanged.

Conclusion

My paper, picking the university data as research samples,

taking advantages of the Multiple Linear Regression Model and

using the empirical method testified whether performances of

universities in the current year have impact on the size of

Endowment Assets and Annual Giving next year. The regression

results signify: Better performances of universities in

current year significantly increase the total number of

Endowment Assets and Annual Giving next year by sending to

donors and public signals that universities with better

performances have good research potential and high-quality

education potential.

The findings of my paper not only ensure the relations

between performances and Endowment /Annual Giving with

statistic evidence, but also enrich the university researches,

hence enlightening universities to find bright way for their

further development and for maintaining their long-term

successes, especially for top universities.

References:

1. Larry L. Lesloe, Sheila Slaughter, Liang Zhang, “How do

Revenue Variations Affect Expenditures Within U.S. Research

Universities? ”, Research in Higher Education, (Sep. 2012),

pp.614-639

2. Josh Lerner and Jialan Wang, “Secrets of The Academy: The

Drivers of University Endowment Success”, National Bureau of

Economic Research, (2008);

3. Stephen G. Dimmock, “ Background Risk and University

Endowment Funds”, The Review of Economics and Statistics,

(Aug. 2012), pp.789-799;

4. Donald L. Basch, “Changes in the Endowment Spending of

Private Colleges in the Early 1990s,” The Journal of Higher

Education, (May. 1999), pp.278-308;

5. Harold A. Davidson, “Investing College Endowment Funds: A

Comparison of Internal and External Management,” (Feb.1971),

pp. 69-74