NATIONAL CENTER FOR EDUCATION STATISTICS 

Statistical Analysis Report December 2001

Postsecondary Education Descriptive Analysis Reports 

Study of College Costs and Prices, 

1988–89 to 1997–98 

Volume 1

Alisa F. Cunningham 

Jane V. Wellman 

Melissa E. Clinedinst 

Jamie P. Merisotis 

The Institute for Higher Education Policy 

C. Dennis Carroll 

National Center for Education Statistics 

U.S. Department of Education 

Office of Educational Research and Improvement NCES 2002–157 
U.S. Department of Education 

Rod Paige 

Secretary

Office of Educational Research and Improvement 

Grover J. Whitehurst 

Assistant Secretary 

National Center for Education Statistics 

Gary W. Phillips 

Acting Commissioner 

The National Center for Education Statistics (NCES) is the primary federal entity for collecting, analyzing, and 

reporting data related to education in the United States and other nations. It fulfills a congressional mandate to 

collect, collate, analyze, and report full and complete statistics on the condition of education in the United States; 

conduct and publish reports and specialized analyses of the meaning and significance of such statistics; assist state 

and local education agencies in improving their statistical systems; and review and report on education activities in 

foreign countries. 

NCES activities are designed to address high priority education data needs; provide consistent, reliable, complete, 

and accurate indicators of education status and trends; and report timely, useful, and high quality data to the U.S. 

Department of Education, the Congress, the states, other education policymakers, practitioners, data users, and the 

general public. 

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Please direct your comments to: 

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December 2001 

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Suggested Citation 

U.S. Department of Education. National Center for Education Statistics. Study of College Costs and 

Prices, 1988–89 to 1997–98, Volume 1, NCES 2002–157, by Alisa F. Cunningham, Jane V. Wellman, 

Melissa E. Clinedinst, and Jamie P. Merisotis. Project Officer: C. Dennis Carroll. Washington, DC: 2001. 

For ordering information on this report, write: 

U.S. Department of Education 

ED Pubs 

P.O. Box 1398 

Jessup, MD 20794-1398 

or call toll free 1-877-4ED-PUBS or go to the Internet: http://www.ed.gov/pubs/edpubs.html

Contact: 

Aurora D’Amico 

(202) 502-7334 
iii

Executive Summary

In the 1998 Amendments to the Higher Education Act (HEA), Congress directed the National

Center for Education Statistics (NCES) to conduct

a new study of higher education costs (expenditures)1 paid by institutions and prices paid by students and their families. This report is the final

product of Phase I of the study, which relied primarily on existing national data and statistical

models.

The framework for the study was influenced by

the findings of the National Commission on the

Cost of Higher Education, published in Straight

Talk About College Costs and Prices (1998). This

study is one follow-up to the Commission’s recommendations.

Congress directed that the study address a

number of specific questions:

• How have tuition and fees changed over

time compared with inflation?

• How have the major expenditure categories

(including capital and technology costs)

changed over time?

• How are expenditures related to prices?

• To what extent does institutional aid (i.e.,

financial aid provided by institutions) affect

tuition increases?

• To what extent has federal financial aid been

used to offset increases in institutional aid?

 

1In this report, the terms “costs” and “expenditures” are used

interchangeably to mean the amount institutions spend to

provide education and related educational services to students.

Goals and Limitations of the Study

Phase I had two major goals: (1) to address the

questions raised by Congress (listed above) insofar as possible given currently available information; and 2) to examine the usefulness of existing

statistical models for testing the relationships

among revenues, costs, and prices in higher education.

The study is limited in its ability to provide

specific answers to many of Congress’ questions

for several different reasons, not all of which

could be changed in future research. The use of

existing data, models, and institutional classification schemes restricted the ability to focus on

certain aspects of costs and prices. For instance,

institutional differences in types of students

served and in program and discipline mix make it

difficult for classification schemes to allow generalization across institutions. As a result, the comparison groups are formed of institutions that may

not be truly comparable.

In addition, currently available national data

are not sufficient to address many questions, reflecting the fact that institutions often do not collect the data required to answer questions about

the relationships among prices, revenues, and expenditures. These data concerns are further complicated by several factors, including the absence

of consistent definitions for terms such as technology, tuition discounting, and merit aid; the lack

of uniformity in defining capital costs; and the

lack of consistent institutional accounting conventions. There are differences between the ac-
Executive Summary

iv

counting standards used for public and private

not-for-profit institutions, which are particularly

relevant to the measurement of capital costs. Public and private not-for-profit institutions are subject, respectively, to standards from the

Government Accounting Standards Board (GASB)

and the Financial Accounting Standards Board

(FASB). Recent changes to both sets of standards

may improve the data collected by NCES, but it

will take several years until all changes are implemented at the institutional level.

Despite these limitations, currently available

national data can be used to describe and analyze

aggregate trends in costs, prices, and revenues for

groups of institutions, as well as to examine the

strength of various relationships among these

factors. Such analyses can improve and expand

upon previous national studies and address some

of the issues raised by Congress in the 1998 HEA

Amendments.

Study Design and Methodology

Using primarily data from the Integrated Postsecondary Education Data System (IPEDS), this

study analyzes trends in costs, prices, and revenues at postsecondary institutions from 1988–89

to 1995–96 (to 1997–98 for public institutions)

and explores relationships among the variables.

The analyses of relationships use existing statistical models, updated and extended over a longer

period of time than in previous studies. All financial data were adjusted for inflation to constant

1999 dollars using the Consumer Price Index.2 A

different model was used for the public sector

than for the private not-for-profit sector because

research has consistently documented that there

 

2The Consumer Price Index for All Urban Consumers (CPIU, 1982-84 = 100) measures change in relation to a base period, in this case the average index level for a 36-month period covering 1982, 1983, and 1984, which is set equal to

100.

are fundamental differences in the financing

structures, enrollment markets, and tuition decisionmaking processes between the sectors.

The study also examines relationships between

tuition and financial aid variables. Because neither

of the two existing models includes financial aid

(except institutional aid) among the independent

variables, new models were developed to analyze

these relationships. In addition to using data from

IPEDS, the analyses use data from the Institutional Prices and Student Financial Aid Survey

(IPSFA), a new survey that captures information

on both tuition and financial aid. At the time of

this report, financial aid data from this survey

were only available for one year, so an examination of changes over time to allow trends to be

identified was not possible.

The universe of institutions examined in this

study was drawn from the IPEDS universe, although some IPEDS institutions were excluded to

increase comparability and to deal with missing

data.3 For example, an attempt was made to include only institutions with primarily undergraduate enrollment, as undergraduate tuition charges

were the focus of the study. The institutions in the

final universe were grouped by sector; 4-year institutions were then divided into research/doctoral,

comprehensive, and bachelor’s institutions. All

analyses were performed separately on each group

of institutions because the groups face different

financial pressures and constraints.

The number of institutions and proportions of

undergraduate enrollment included in the final

groups of institutions are provided in figures 1 and

2. Although the groups of institutions comprise

 

3See the institutional universe section in Chapter I and the

data and methods sections of Chapters III, IV, and V for discussion of the exclusion of institutions.
Executive Summary

v

Figure 1.—Number of institutions included in and

Figure 1.—excluded from the final universe, by type of

Figure 1.—institution: 1997–98

NOTE: Refers to final universe for panels of institutions used in

chapters III and IV, based on IPEDS data.

SOURCE: U.S. Department of Education, National Center for

Education Statistics, Integrated Postsecondary Education Data

System (IPEDS), Full 1998 Collection Year.

Excluded Included

institutions institutions

47

135

66

192

2173

1134

451

813

221

Public research/doctoral

Public comprehensive

Public bachelor’s

Public 2-year

Private not-for-profit research/doctoral

Private not-for-profit comprehensive

Private not-for-profit bachelor’s

Excluded: public institutions

Excluded: private not-for-profit institutions

less than half of all public and private not-forprofit institutions in the IPEDS universe, they enroll more than three-quarters of undergraduates

attending IPEDS institutions in the public and private not-for-profit sectors.

Figure 2.—Percent of undergraduate fall enrollment at 

Figure 2.—institutions included in and excluded from the

Figure 2.—final universe, by type of institution: 1997–98

NOTE: Refers to final universe for panels of institutions used in

chapters III and IV, based on IPEDS data.

SOURCE: U.S. Department of Education, National Center for

Education Statistics, Integrated Postsecondary Education Data

System (IPEDS), Full 1998 Collection Year.

Excluded Included

institutions institutions

2%

4%

7%

15%

5%

35%

13%

17%

3%

Public research/doctoral

Public comprehensive

Public bachelor’s

Public 2-year

Private not-for-profit research/doctoral

Private not-for-profit comprehensive

Private not-for-profit bachelor’s

Excluded: public institutions

Excluded: private not-for-profit institutions

To provide a framework for this study’s analyses, NCES commissioned papers from seven national experts in higher education finance and

student aid. A summary of an invitational meeting

convened by NCES to discuss the commissioned

papers, as well as the papers themselves, are included in the report.
Executive Summary

vi

Findings and Conclusions

The conclusions reached from the trend analyses and models in this report are consistent with

earlier research and the views of the expert

authors who contributed commissioned papers for

this report. The detailed analyses found variations

in the nature and the strength of relationships between costs and prices across types of institutions,

and within types of institutions over time.

Changes in tuition and other revenue

sources over time

In both the public and private not-for-profit

sectors, average tuition charges increased at a

faster rate than inflation over the period of the

analyses, and tuition charges also increased faster

than most expenditure categories within the institutions. The share of overall revenue coming from

tuition has increased on average for all institutional types in both sectors, compared with relative decreases in other revenue sources.

Across all types of public institutions, in-state

undergraduate tuition and fees increased annually—by an average of 4.1 percent at research/doctoral institutions, 4.2 percent at

comprehensive institutions, 4.3 percent at bachelor’s institutions, and 3.4 percent at 2-year institutions—between 1988–89 and 1997–98 (figure 3).

On average, gross tuition revenue accounted for

increasing proportions of total educational and

general (E&G)4 revenue over this period, while

revenue from state appropriations declined as a

proportion of the total.

 

4E&G revenues include tuition and fees, government appropriations, government grants and contracts, private gifts, endowment income, sales and services, and other revenue; they

exclude revenue for auxiliary enterprises, hospitals, and independent operations.

Across all types of private not-for-profit institutions, undergraduate tuition and fees increased

annually—by an average of 3.6 percent at research/doctoral institutions, 4.1 percent at comprehensive institutions, and 3.7 percent at

bachelor’s institutions—between 1988–89 and

1995–96 (figure 4). On average, gross tuition

revenue accounted for increasing proportions of

total E&G revenue over this period. At the same

time, the proportion of E&G revenue from

endowment income and private gifts, grants, and

contracts decreased.

Changes in expenditures over time

On the expenditure side for both public and

private not-for-profit institutions, instruction expenditures continued to constitute the largest proportion of total E&G expenditures,5 but remained

flat or decreased as a proportion of E&G expenditures. Meanwhile, institutional scholarships and

fellowships constituted one of the fastest growing

expenditure categories and made up an increasing

proportion of total E&G expenditures (figures 3

and 4).

Relationship of tuition changes with

changes in revenues, expenditures, and

other factors

For public 4-year institutions, revenue from

state appropriations remains the largest source of

revenue and is the single most important factor

associated with changes in tuition.

 

5E&G expenditures include instruction, research, public

service, academic support, student services, institutional support, plant operations and maintenance, scholarships and

fellowships, and transfers; they exclude expenditures for auxiliary enterprises, hospitals, and independent operations.
Executive Summary

vii

Figure 3.—Percent change in various financial indicators at public institutions, by type of institution: 1988–89 to 1997–98

NOTE: FY, FT means full-year, full-time students. E&G signifies educational and general revenue or expenditures. All changes were calculated

using constant 1999 dollars.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS),

Full Collection Years 1989 to 1998.

3.9

4.3

-4.1

-0.9

-1.2

5.6

2.9

3.4

1.0

2.5

-1.6

-6.9

0.0

8.0

4.9

4.3

2.2

3.6

-2.5

0.6

-11.3

-1.2

8.4

4.8

4.2

1.7

4.5

-1.9

1.0

-9.8

-1.0

5.4

4.4

4.1

-3.2

1.1

-14.0 -12.0 -10.0 -8.0 -6.0 -4.0 -2.0 0.0 2.0 4.0 6.0 8.0 10.0

Percent

Research/doctoral

Comprehensive

Bachelor’s

2-year

Average annual percent change in

state appropriations revenue

Average annual percent change in

in-state undergraduate tuition for

FY, FT students

Percentage point change in

tuition as a proportion of total

E&G revenue

Average annual percent change in

instruction expenditures

Average annual percent change in

tuition revenue

Percentage point change in state 

appropriations as a proportion of 

total E&G revenue 

Percentage point change in

scholarships and fellowships as a

proportion of total E&G

expenditures

Average annual percent change in

scholarships and fellowships

Percentage point change in 

instruction as a proportion of 

total E&G expenditures 
Executive Summary

viii

Figure 4.—Percent change in various financial indicators at private not-for-profit 4-year institutions, by type of

Figure 4.—institution: 1988–89 to 1995–96

NOTE: FY, FT means full-year, full-time students. E&G signifies educational and general revenue or expenditures. All changes were calculated

using constant 1999 dollars.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS),

Full Collection Years 1989 to 1996.

3.6 3.5

1.3 1.4

1.8

-2.0

3.3

0.3

6.7

3.0

4.1

3.8

5.1

-1.0

-0.2

-3.1

1.9

-1.9

6.6

5.0

3.7

3.4

4.2

1.1

-2.2

2.0

-0.8

5.4

4.5

1.5

-4.0

-2.0

0.0

2.0

4.0

6.0

8.0

Percent

Research/doctoral Comprehensive Bachelor’s

Average 

annual 

percent 

change, 

endowment 

income

Average 

annual 

percent 

change in 

in-state 

undergraduate 

tuition for 

FY, FT 

students

Percentage 

point change 

in tuition as 

a proportion 

of total E&G 

revenue 

Percentage 

point

change in 

endowment 

income and 

private gifts 

as a proportion of total 

E&G 

revenue

Average 

annual 

percent 

change in 

tuition 

revenue

Average 

annual 

percent 

change, 

private gifts

Percentage 

point change 

in scholarships and 

fellowships 

as a proportion of total 

E&G 

expenditures 

Average 

annual 

percent 

change in 

scholarships and 

fellowships

Percentage 

point

change in 

instruction 

as a proportion of total 

E&G 

expenditures 

Average 

annual 

percent 

change in 

instruction 

expenditures

State appropriations revenue decreased relative

to other sources of revenue for all types of public

4-year institutions, and in fact experienced real

annual decreases for research/doctoral and comprehensive institutions over the time period examined (figure 3).

Decreasing revenue from government appropriations (in which state appropriations make up

the majority) was the most important factor associated with tuition increases at public 4-year institutions over the period of analysis. At public

research/doctoral institutions, the correlation between change in appropriations and change in tuition was –0.315, a medium sized relationship (the

relationships were small at the other two groups of

public 4-year institutions).

Although increases in instruction expenditures

were associated with increases in tuition at public

4-year institutions, they did not explain as much of

the variation in tuition changes as decreases in

state appropriations revenue did. At public research/doctoral institutions, the correlation between change in instruction expenditures and

change in tuition was 0.087, a small sized relationship (the relationships also were small at the

other two groups of public 4-year institutions). In

addition, the proportion of total E&G expenditures
Executive Summary

ix

for instruction for these groups of institutions declined slightly over the time period examined.

For public 2-year institutions, the model found

that changes in revenue and expenditure categories accounted for a very low percentage of the

variation in tuition changes over the entire period

of analysis—7.3 percent—in comparison with the

public 4-year sector, which had values ranging

from 39.1 percent for research/doctoral institutions to 61.3 percent for comprehensive institutions. This suggests there are some important

differences between public 2-year and 4-year institutions that are not captured in this model.

The findings suggest that prices at private notfor-profit 4-year institutions were related to both

“internal” institutional budget constraints and

“external” market conditions. In the private notfor-profit sector, there is no single overriding factor as strongly related to tuition as state appropriations revenue is in the public 4-year sector.

For all types of private not-for-profit 4-year institutions, certain “internal” factors—higher costs

in two areas (institutional aid and average faculty

compensation levels) and lower levels of revenue

from two nontuition sources (endowment income

and private gifts, grants, and contracts, together

considered philanthropic revenue)—were associated with higher levels of undergraduate tuition.

At private not-for-profit research/doctoral institutions, the correlation between the tuition and institutional aid variables was 0.801 and the

correlation between the tuition and faculty compensation variables was 0.547, both of these large

sized relationships (the relationships also were

large at comprehensive and bachelor’s institutions,

with the exception of the relationship with institutional aid at bachelor’s institutions, which was a

medium sized relationship). The correlation between tuition and philanthropic revenue was

0.511, also a large relationship (the relationships

also were large for the other two groups of institutions).

In addition, certain “external” factors—such as

the availability of institutional aid for students, the

price of attending public institutions in the same

state, and per capita income in the state—were

associated with tuition levels for all types of private not-for-profit 4-year institutions. At private

not-for-profit research/doctoral institutions, the

correlation between tuition and average tuition at

public 4-year institutions in the state was 0.357

and the correlation between tuition and per capita

state income was 0.294, both of these medium

sized relationships (the relationships also were

medium sized at comprehensive and bachelor’s

institutions).

Some differences were found regarding

whether and the extent to which other factors—for

example, instruction expenditures—were related

to tuition, suggesting that the three types of private not-for-profit 4-year institutions face different competitive environments.

Patterns in financial aid

Patterns in financial aid differ considerably

among the types of institutions (figure 5), yet

some tendencies emerge within each broad institutional sector.

At public 4-year institutions, more than twothirds of first-time, full-time, degree/certificateseeking undergraduates received aid from any

source, on average. The average percentages receiving aid and the average amounts received

varied depending on the type of aid and the type

of institution, but the highest figures were for student loan aid at all types of public 4-year institutions.
Executive Summary

x

Public 2-year institutions presented a distinctly

different situation. At these institutions, on average, 56.8 percent of first-time, full-time, degree/certificate-seeking undergraduates received

aid from any source; the highest percentage and

the highest average amount were for federal grant

aid; and relatively low percentages of students

received student loans or institutional aid.

At private not-for-profit 4-year institutions,

about three-quarters of first-time, full-time, degree/certificate-seeking undergraduates received

aid from any source, on average. The highest average percentages of students received institutional aid. Student loan aid was the second highest

in terms of the average percentage of students receiving aid.

Relationship of tuition changes with

financial aid patterns

Regarding the relationship between financial

aid and tuition, the models found no associations

between most of the aid variables (federal grants,

state grants, and student loans) and changes in

tuition in either the public or private not-for-profit

sectors. The single exception is institutional aid,

which was found to have a positive association

with tuition increases for public comprehensive

and private not-for-profit comprehensive institutions. The correlation between the change in tuition and the institutional aid variable was 0.103 at

public comprehensive institutions and 0.188 at

private not-for-profit comprehensive institutions,

both of these small sized relationships.

Figure 5.—Average proportions of first-time, full-time, degree/certificate-seeking undergraduates receiving aid, by type

Figure 5.—of institution and aid source

NOTE: Financial aid data are for either 1997–98 or 1998–99, depending on which year was reported by the institution.

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student Financial Aid Survey

(IPSFA).

68.5 71.3 71.5

56.8

72.0

86.5 85.7

28.3

38.0

44.1 40.9

24.7

32.9 35.5

26.9

31.6 29.2 25.9 23.8

36.8 38.8

30.9

25.8 28.3

14.0

64.7

79.4 76.9

45.4 47.1 49.5

16.6

55.4

66.8 65.9

0

10

20

30

40

50

60

70

80

90

100

Public

research/

doctoral

Public

comprehensive

Public

bachelor’s

Public 2-year Private

not-for-profit

research/

doctoral

Private

not-for-profit

comprehensive

Private

not-for-profit

bachelor’s

Percent

Aid from any source Federal grants State grants Institutional grants Loan aid
Executive Summary

xi

Usefulness of statistical models for testing

relationships among revenues, costs,

expenditures, and prices

In general, the study shows that available national

data can be used to explore aggregate trends in

revenues, costs, and prices for broad groups of

institutions. Models using these data also can

point out associations between revenue and expenditure variables and tuition—for example, as

state appropriations for public 4-year institutions

decrease, the average undergraduate tuition at this

type of institution tends to increase. However,

these statistical models are correlational in nature

and cannot lead to definitive conclusions regarding the underlying relationships among changes in

variables over time. Ideally, new models would

need to be constructed to explore the simultaneous

direct and indirect effects of costs, revenues, financial aid, market conditions and other external

influences, family resources, and college prices.

Finally, even with future improvements in

definitions and prospective data collection, the

technique of cost analysis will always provide

only partial answers to questions about the reasons

for price increases at colleges and universities.

Given the distinctive characteristics of higher

education—such as the availability of nontuition

sources of revenue—there is little reason to expect

a consistent relationship between costs and prices

across all institutions or groups of institutions,

even though a specific relationship may be present

at one particular institution. Nevertheless, the

analyses presented in this report highlight trends

and point to associations between variables that

can lead to a better understanding of the nature of

higher education finance.
xii

Acknowledgments

The authors wish to thank all of those who contributed to this report. We would particularly

like to thank our colleagues at MPR Associates for their feedback and assistance, including Laura

Horn, Helen Jang, Barbara Kridl, and Francesca Tussing. We also are very grateful for the support and feedback provided by Dennis Carroll at NCES throughout the project.

We appreciate the time and effort of the expert authors who contributed papers for this report, as well as all those who participated in the national invitational meeting at which the commissioned papers were discussed.

We also would like to acknowledge the careful review and thoughtful comments provided

by the following individuals at various stages: Marilyn McMillen, Bill Fowler, Paula Knepper,

and Samuel Peng of NCES; Daniel Goldenberg of the Office of the Under Secretary, Planning

and Evaluation Service; Jonathan Oberg, Tom Snyder, Audrey Warcola, and Gregory Henschel

of the Office of Educational Research and Improvement (OERI); David Bergeron of the Office of

Postsecondary Education (OPE); Michael Lance and Sally Dillow of the Education Statistics

Services Institute (ESSI); Rita Kirshstein and Daniel Sherman of the Pelavin Research Center,

American Institutes for Research; William Goggin of the Advisory Committee on Student Financial Assistance; Kenneth Redd of the National Association of Student Financial Aid Administrators; Carol Fuller, Frank Balz, and Jon Fuller of the National Association of Independent

Colleges and Universities; Patricia Smith, Brian Trzebiatowski, and Travis Reindl of the American Association of State Colleges and Universities; Kent Phillippe of the American Association

of Community Colleges; Jacqueline King of the American Council on Education; Michael

McGuire of Georgetown University; Jacob O. Stampen of the University of Wisconsin-Madison;

Mark L. Putnam of Northeastern University; and Ellie Greenberg.

Finally, we thank our colleagues at the Institute for Higher Education Policy, Jessica Shedd,

Colleen O’Brien, and Deanna High, for their suggestions and careful review of this report.
xiii

Table of Contents

Page

Executive Summary .................................................................................................................. iii

Acknowledgments...................................................................................................................... xii

List of Tables ............................................................................................................................. xv

List of Figures............................................................................................................................ xxi

Chapter I: Introduction............................................................................................................ 1

Background for the Study...................................................................................................... 2

Purpose and Design of This Study ........................................................................................ 3

Chapter II: Summary of Commissioned Papers and National Invitational Meeting ......... 17

Introduction and Overview.................................................................................................... 17

Major Discussion Points ....................................................................................................... 18

Chapter III: Revenues, Expenditures, and Prices at Public Institutions............................. 23

Data and Methods.................................................................................................................. 23

Trends in Enrollment, Tuition, Revenues, and Expenditures ............................................... 29

Model Results........................................................................................................................ 40

Discussion ............................................................................................................................. 55

Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year

Institutions................................................................................................................................. 59

Data and Methods.................................................................................................................. 59

Trends in Enrollment, Tuition, Revenues, and Expenditures ............................................... 71

Model Results........................................................................................................................ 80

Discussion ............................................................................................................................. 93

Chapter V: Financial Aid and Prices at Higher Education Institutions.............................. 99

Review of Previous Work ..................................................................................................... 99

Data and Methods.................................................................................................................. 105

Trends in Tuition and Financial Aid ..................................................................................... 111

Model Results........................................................................................................................ 119

Discussion ............................................................................................................................. 128
Table of Contents

xiv

Page

Chapter VI: Summary of Findings and Conclusions............................................................. 131

Major Conclusions from the Data Analyses.......................................................................... 132

Conclusions about Research Models..................................................................................... 136

References.................................................................................................................................. 139

Appendix A—Technical Notes and Methodology .................................................................. 143

Appendix B—Glossary ............................................................................................................. 177
xv

List of Tables

Table Page

1 Number and undergraduate enrollment of public and private not-for-profit

institutions included and excluded from the final universe in Chapters III and

IV: 1997–98..................................................................................................................... 9

2 Number and undergraduate enrollment of public and private not-for-profit

institutions included and excluded from the final universe in Chapter V: 1999............. 10

3 Characteristics of regression model for public institutions............................................. 24

4 Average annual percentage change in in-state undergraduate tuition and fees for

full-time, full-year students: 1988–89 to 1997–98.......................................................... 27

5 Average change in price, enrollment, revenue, and expenditures at public

research/doctoral institutions: 1988–89 to 1997–98 ....................................................... 30

6 Percentage composition of E&G revenue and expenditure at public research/doctoral

institutions, on average: 1988–89 to 1997–98 ................................................................ 31

7 Average change in price, enrollment, revenue, and expenditures at public

comprehensive institutions: 1988–89 to 1997–98........................................................... 33

8 Percentage composition of E&G revenue and expenditure at public comprehensive

institutions, on average: 1988–89 to 1997–98 ................................................................ 35

9 Average change in price, enrollment, revenue, and expenditures at public bachelor’s

institutions: 1988–89 to 1997–98.................................................................................... 36

10 Percentage composition of E&G revenue and expenditure at public bachelor’s

institutions, on average: 1988–89 to 1997–98 ................................................................ 38

11 Average change in price, enrollment, revenue, and expenditures at public 2-year

institutions: 1988–89 to 1997–98.................................................................................... 39

12 Percentage composition of E&G revenue and expenditure at public 2-year institutions,

on average: 1988–89 to 1997–98 .................................................................................... 41
List of Tables

xvi

Table Page

13 Coefficients for the regression of the change in in-state, full-time, full-year,

undergraduate tuition on selected revenue and expenditure variables for public

research/doctoral institutions........................................................................................... 43

14 Coefficients for the regression of the change in in-state, full-time, full-year,

undergraduate tuition on selected revenue and expenditure variables for public

comprehensive institutions.............................................................................................. 46

15 Coefficients for the regression of the change in in-state, full-time, full-year,

undergraduate tuition on selected revenue and expenditure variables for public

bachelor’s institutions ..................................................................................................... 49

16 Coefficients for the regression of the change in in-district, full-time, full-year,

undergraduate tuition on selected revenue and expenditure variables for public 2-year

institutions....................................................................................................................... 52

17 Summary of inflation-adjusted trends in tuition and selected revenue and

expenditures categories at public institutions: 1988–89 to 1997–98 .............................. 56

18 Significant relationships with the change in in-state undergraduate tuition at public

institutions: 1988–89 to 1997–98.................................................................................... 57

19 Characteristics of simultaneous equation model for private not-for-profit institutions .. 63

20 Variables included in the simultaneous equation model for private not-for-profit

institutions....................................................................................................................... 66

21 Average change in price, enrollment, revenue, and expenditures at private not-forprofit research/doctoral institutions: 1988–89 to 1995–96 ............................................. 72

22 Percentage composition of E&G revenue and expenditure at private not-for-profit

research/doctoral institutions, on average: 1988–89 to 1995–96.................................... 74

23 Average change in price, enrollment, revenue, and expenditures at private not-forprofit comprehensive institutions: 1988–89 to 1995–96................................................. 75

24 Percentage composition of E&G revenue and expenditure at private not-for-profit

comprehensive institutions, on average: 1988–89 to 1995–96 ....................................... 76

25 Average change in price, enrollment, revenue, and expenditures at private not-forprofit bachelor’s institutions: 1988–89 to 1995–96 ........................................................ 78

26 Percentage composition of E&G revenue and expenditure at private not-for-profit

bachelor’s institutions, on average: 1988–89 to 1995–96............................................... 79
List of Tables

xvii

Table Page

27 Coefficients for the simultaneous equation estimation of undergraduate tuition on

selected institutional and external characteristics for private not-for-profit

research/doctoral institutions: 1989–90 to 1995–96 ....................................................... 81

28 Coefficients for the reduced form regression of undergraduate tuition on selected

institutional and external characteristics for private not-for-profit research/doctoral

institutions: 1989–90 to 1995–96.................................................................................... 85

29 Coefficients for the simultaneous equation estimation of undergraduate tuition on

selected institutional and external characteristics for private not-for-profit

comprehensive institutions: 1989–90 to 1995–96........................................................... 86

30 Coefficients for the reduced form regression of undergraduate tuition on selected

institutional and external characteristics for private not-for-profit comprehensive

institutions: 1989–90 to 1995–96.................................................................................... 89

31 Coefficients for the simultaneous equation estimation of undergraduate tuition on

selected institutional and external characteristics for private not-for-profit bachelor’s

institutions: 1989–90 to 1995–96.................................................................................... 91

32 Coefficients for the reduced form regression of undergraduate tuition on selected

institutional and external characteristics for private not-for-profit bachelor’s

institutions: 1989–90 to 1995–96.................................................................................... 94

33 Summary of inflation-adjusted trends in tuition and selected revenue and expenditures

categories at private not-for-profit institutions: 1988–89 to 1995–96 ............................ 95

34 Significant relationships with undergraduate tuition at private not-for-profit

institutions: 1989–90 to 1995–96.................................................................................... 96

35 Variables included in the financial aid regression models .............................................. 107

36 Average changes in tuition, numbers of first-time, full-time, degree/certificate-seeking

undergraduates, percentages receiving aid, and aid amounts received at public

research/doctoral institutions........................................................................................... 112

37 Average changes in tuition, numbers of first-time, full-time, degree/certificateseeking undergraduates, percentages receiving aid, and aid amounts received at public

comprehensive institutions.............................................................................................. 113

38 Average changes in tuition, numbers of first-time, full-time, degree/certificateseeking undergraduates, percentages receiving aid, and aid amounts received at

public bachelor’s institutions .......................................................................................... 114
List of Tables

xviii

Table Page

39 Average changes in tuition, numbers of first-time, full-time, degree/certificateseeking undergraduates, percentages receiving aid, and aid amounts received at

public 2-year institutions................................................................................................. 115

40 Average changes in tuition, numbers of first-time, full-time, degree/certificate-seeking

undergraduates, percentages receiving aid, and aid amounts received at

private not-for-profit research/doctoral institutions ........................................................ 116

41 Average changes in tuition, numbers of first-time, full-time, degree/certificateseeking undergraduates, percentages receiving aid, and aid amounts received at

private not-for-profit comprehensive institutions ........................................................... 117

42 Average changes in tuition, numbers of first-time, full-time, degree/certificateseeking undergraduates, percentages receiving aid, and aid amounts received at

private not-for-profit bachelor’s institutions ................................................................... 118

43 Coefficients for reduced regression of the change in in-state tuition for first-time,

full-time, degree/certificate-seeking undergraduates on selected financial aid, revenue,

expenditure, and institutional characteristics for public research/doctoral institutions .. 120

44 Coefficients for reduced regression of the change in in-state tuition for first-time,

full-time, degree/certificate-seeking undergraduates on selected financial aid, revenue,

expenditure, and institutional characteristics for public comprehensive institutions...... 121

45 Coefficients for reduced regression of the change in in-state tuition for first-time,

full-time, degree/certificate-seeking undergraduates on selected financial aid, revenue,

expenditure, and institutional characteristics for public bachelor’s institutions ............. 122

46 Coefficients for reduced regression of the change in in-state tuition for first-time,

full-time, degree/certificate-seeking undergraduates on selected financial aid, revenue,

expenditure, and institutional characteristics for public 2-year institutions.................... 123

47 Coefficients for reduced regression of the change in in-state tuition for first-time,

full-time, degree/certificate-seeking undergraduates on selected financial aid, revenue,

expenditure, and institutional characteristics for private not-for-profit

research/doctoral institutions........................................................................................... 124

48 Coefficients for reduced regression of the change in tuition for first-time, full-time,

degree/certificate-seeking undergraduates on selected financial aid, revenue,

expenditure, and institutional characteristics for private not-for-profit comprehensive

institutions....................................................................................................................... 125
List of Tables

xix

Table Page

49 Coefficients for reduced regression of the change in tuition for first-time, full-time,

degree/certificate-seeking undergraduates on selected financial aid, revenue,

expenditure, and institutional characteristics for private not-for-profit bachelor’s

institutions in the highest tuition quartile........................................................................ 126

50 Coefficients for reduced regression of the change in in-state tuition for first-time,

full-time, degree/certificate-seeking undergraduates on selected financial aid, revenue,

expenditure, and institutional characteristics for private not-for-profit bachelor’s

institutions in the middle tuition quartiles....................................................................... 127

51 Coefficients for reduced regression of the change in tuition for first-time, full-time,

degree/certificate-seeking undergraduates on selected financial aid, revenue,

expenditure, and institutional characteristics for private not-for-profit bachelor’s

institutions in the lowest tuition quartile......................................................................... 127

52 Summary of financial aid patterns at public and private not-for-profit institutions........ 129

53 Significant relationships with the change in undergraduate tuition at public and

private not-for-profit institutions: 1997–98 to 1999–2000 ............................................. 130

Appendix Tables

A1 Final universe of public 4-year and 2-year institutions for Chapter III ........................... 151

A2 Final universe of private not-for-profit 4-year institutions for Chapter IV ..................... 152

A3 Final universe of public research/doctoral institutions in Chapter III compared to

excluded institutions: 1997–98 ....................................................................................... 152

A4 Final universe of public comprehensive institutions in Chapter III compared to

excluded institutions: 1997–98 ....................................................................................... 153

A5 Final universe of public bachelor’s institutions in Chapter III compared to excluded

institutions: 1997–98....................................................................................................... 154

A6 Final universe of public 2-year institutions in Chapter III compared to excluded

institutions: 1997–98....................................................................................................... 155

A7 Final universe of private not-for-profit research/doctoral institutions in Chapter IV

compared to excluded institutions: 1995–96................................................................... 156

A8 Final universe of private not-for-profit comprehensive institutions in Chapter IV

compared to excluded institutions: 1995–96................................................................... 157
List of Tables

xx

Appendix Table Page

A9 Final universe of private not-for-profit bachelor’s institutions in Chapter IV

compared to excluded institutions: 1995–96................................................................... 158

A10 Final universe of institutions for Chapter V.................................................................... 160

A11 Final universe of public research/doctoral institutions in Chapter V compared to

excluded institutions........................................................................................................ 161

A12 Final universe of public comprehensive institutions in Chapter V compared to

excluded institutions........................................................................................................ 162

A13 Final universe of public bachelor’s institutions in Chapter V compared to excluded

institutions....................................................................................................................... 162

A14 Final universe of public 2-year institutions in Chapter V compared to excluded

institutions....................................................................................................................... 163

A15 Final universe of private not-for-profit research/doctoral institutions in Chapter V

compared to excluded institutions................................................................................... 163

A16 Final universe of private not-for-profit comprehensive institutions in Chapter V

compared to excluded institutions................................................................................... 164

A17 Final universe of private not-for-profit bachelor’s institutions in Chapter V compared

to excluded institutions ................................................................................................... 164

A18 Descriptive statistics of model variables for private not-for-profit research/doctoral

institutions: 1989–90 to 1995–96.................................................................................... 166

A19 Descriptive statistics of model variables for private not-for-profit comprehensive

institutions: 1989–90 to 1995–96.................................................................................... 167

A20 Descriptive statistics of model variables for private not-for-profit bachelor’s

institutions: 1989–90 to 1995–96.................................................................................... 168
xxi

List of Figures

Executive Summary Figures Page

1 Number of institutions included in and excluded from the final universe, by type of

institution: 1997–98 ........................................................................................................ v

2 Percent of undergraduate fall enrollment at institutions included in and excluded from

the final universe, by type of institution: 1997–98.......................................................... v

3 Percent change in various financial indicators at public institutions, by type of

institution: 1988–89 to 1997–98 ..................................................................................... vii

4 Percent change in various financial indicators at private not-for-profit 4-year

institutions, by type of institution: 1988–89 to 1995–96................................................. viii

5 Average proportions of first-time, full-time, degree/certificate-seeking undergraduates

receiving aid, by type of institution and aid source......................................................... x
THIS PAGE INTENTIONALLY LEFT BLANK
1

Chapter I: Introduction

This report presents the findings of the first phase of a study mandated by Congress as part

of the 1998 Amendments to the Higher Education Act (HEA). Part C, section 131(c) of the HEA,

entitled “Improvements in Market Information and Public Accountability,” directs the Commissioner of Education Statistics to conduct a national study of trends in higher education prices and

costs.1 Specifically:

(1) IN GENERAL.—The Commissioner of Education Statistics shall conduct a national study of expenditures at institutions of higher education. Such

study shall include information with respect to—

a) the change in tuition and fees compared with the consumer price

index and other appropriate measures of inflation;

b) faculty salaries and benefits;

c) administrative salaries, benefits and expenses;

d) academic support services;

e) research;

f) operations and maintenance; and

g) institutional expenditures for construction and technology and the

potential cost of replacing instructional buildings and equipment.

(2) EVALUATION. —The study shall include an evaluation of—

a) changes over time in the expenditures identified in paragraph (1);

b) the relationship of the expenditures identified in paragraph (1) to

college costs; and

c) the extent to which increases in institutional financial aid affect

tuition increases, including the demographics of students receiving

 

1In this report, the terms “costs” and “expenditures” are used interchangeably to mean the amount institutions spend to provide education and related educational services to students, as the costs incurred by an institution are frequently measured

through expenditures. More strictly, however, the costs of education can be defined as the minimum of what must be given up to

accomplish some result, while expenditures are not tied to results and can exceed the minimum amount; see Fowler and Monk

(2001).
Chapter I: Introduction

2

such aid, the extent to which financial aid is provided to students

with limited need in order to attract a student to a particular institution, and the extent to which Federal financial aid, including

loan aid, has been used to offset the costs of such practices.

The study of expenditures is just one element mandated by the law. Section 131 directs the

Commissioner of Education Statistics to improve information and standardize definitions to

measure postsecondary costs, and to cooperate with the Bureau of Labor Statistics to develop a

“market basket” of items comprising the cost of postsecondary education. This report contains

the results of the study of expenditures only; however, the context within which the study was

commissioned also is relevant.

This report is organized as follows. In this volume, Chapter I provides background for the

study, defines the terms of the analysis, describes the research models used in the study, and discusses the limitations of the research. Chapter II summarizes the discussion from a national invitational meeting regarding a series of commissioned papers. Chapter III presents the findings of

the research on prices, expenditures, and revenues at public institutions, while Chapter IV presents the findings of the research on private not-for-profit institutions. Chapter V provides a brief

review of previous work in the area of financial aid and prices at higher education institutions

and presents the results of a series of regression models. Chapter VI presents a summary of findings and conclusions. Appendix A compiles technical notes and the full methodology, and Appendix B provides a glossary of terms and variables. Volume 2 includes the complete set of

commissioned papers, as well as the agenda and list of participants for the national invitational

meeting.

Background for the Study

The study mandate from Congress was influenced by the report of the National Commission on the Cost of Higher Education, Straight Talk About College Costs and Prices (1998). The

Commission’s report was delivered to Congress in the spring of 1998 following an intensive sixmonth study that included a review of national research in addition to the Commission’s own investigation of trends and causes of tuition increases. The Commission reported that sticker prices

(published tuition and fees) had been increasing faster than inflation in both the public and private not-for-profit sectors, and that expenditures (costs) were also increasing, but generally at a

lower rate than prices. They were unable to reach definitive conclusions about the root causes for

the price increases due to the limited time frame for the study and the lack of available data to

allow these questions to be addressed. The Commission found that the language of higher education finance did not consistently distinguish between costs, prices, and subsidies, and that the ab-
Chapter I: Introduction

3

sence of clear definitions and common standards precluded the collection of comparative data for

more in-depth research. They stated concern that college finances had become opaque not just to

the general public but also to the institutions themselves. They believed that more complete

analyses of trends in costs over a longer time period would help to reveal the root causes of price

increases. Their final report to Congress included recommendations for future research needed to

understand more completely the reasons for price and cost increases. They also recommended

that institutions take affirmative steps to improve their understanding of the relation between

costs and prices, both to better communicate these issues to the public and to improve management within the institutions.

By charging the National Center for Education Statistics (NCES) with the study of costs,

Congress mandated that quantitative, statistically determinable techniques be the primary means

of researching change in prices and costs. NCES determined that a proper response to Congress

required the collection of new institutional-level data, because available national data do not adequately capture distinctions between institutions and other important aspects of the issues. Limitations of current data include the inadequacy of available institutional classification schemes; a

lack of common definitions for variables being examined; and different accounting standards

between public and private not-for-profit institutions. (These issues are elaborated below in the

discussion of limitations of the research.) NCES developed a request for a proposal for a study

using new data, and proposals were received from across the country. However, no funds were

appropriated by Congress to accomplish this task. NCES therefore asked The Institute for Higher

Education Policy to attempt to respond to Congress’ questions using existing national data as

Phase I of the mandated study. This is an admittedly more limited goal than seeking complete

answers to Congress’ questions, because of the reliance on retrospective analysis of previously

collected data. Nevertheless, this study reports the story portrayed by existing research models

and currently available data.

Purpose and Design of This Study

The goal of Phase I of the NCES Study of College Costs and Prices is to examine the relation between costs and prices to more precisely answer the question left unanswered by the Cost

Commission about the extent to which spending (expenditure) patterns are contributing to tuition

increases in higher education. To do this, papers were commissioned from a number of experts in

the field of higher education finance and were discussed at an invitational meeting involving the

broader research community. The summary of this discussion, presented in Chapter II, sets the

stage for the subsequent statistical analyses, which update existing models of the relationship

between costs and prices and extend them for a longer period of time. The statistical analyses in
Chapter I: Introduction

4

the study have several components: 1) an analysis of trends in average costs, revenues, and prices

at public institutions and a description of the statistical relationships among these factors; 2) an

analysis of trends at private not-for-profit institutions, as well as an examination of the factors

associated with tuition increases at these institutions; and 3) an analysis of the relationship, if

any, of financial aid to prices at public and private not-for-profit institutions.

To fully understand these analyses and the complex relationship between cost and price, it

is important to keep in mind the structure of higher education finance, which differs substantially

from the economics of a private, for-profit firm. Most important, most public and private not-forprofit institutions receive revenue from many sources, allowing them to supplement revenue

from tuition. As a result, for most students the price they pay does not cover the average costs of

their education. The difference between average costs and the portion that is paid from tuition is

a general institutional subsidy. Other important definitions and terms relevant to higher education

are presented in the box below.

Definition of Terms

Institutional type: There are three major sectors of institutions that provide postsecondary education: public institutions, which range from constitutionally autonomous research

universities to locally-funded community colleges; private not-for-profit institutions, which range from major research universities to liberal arts institutions;

and private for-profit institutions. Education also is provided outside of institutions of higher and postsecondary education—for example, in corporate settings

and over the Internet. This study is confined to education provided within formal

institutions of higher education as defined by the U.S. Department of Education

(ED), focusing on institutions in the public and private not-for-profit sectors.

Carnegie classification: This system classifies all degree-granting and accredited institutions based on

degree conferrals, federal support, and admissions selectivity, divided into Research, Doctoral, Comprehensive, Bachelor’s (Liberal Arts), Associate of Arts,

and Specialized institutions.2 This study uses the 1994 Carnegie classifications

of research/doctoral, comprehensive, and liberal arts/bachelor’s to separate 4-

year public and private not-for-profit institutions into broadly similar groups for

the purposes of analysis.

 

2This system is undergoing changes that will not be finalized until 2005.
Chapter I: Introduction

5

Definition of Terms—Continued

Full-time equivalent (FTE)

enrollment:

FTE measures attempt to adjust enrollment for attendance patterns. In many

calculation methods, all full-time students are counted, plus a portion of parttime students (typically one-third). Because institutions define “part-time” attendance differently, however, using total instructional credit/contact hour activity

to calculate FTE, as is done in this report (see Appendix A for details), may be a

more consistent measure.

Cost: The amount institutions spend to provide education and related educational

services to students (measured through expenditures, see below).

Cost per FTE student: The average amount spent annually to provide education and related services to

each full-time equivalent student. Unless otherwise specified, costs per FTE

student cited in this report are average costs for all levels of students in all programs.

Price: In general, price is the amount students and their families are charged and what

they pay for educational services. There are different types of prices depending

on what is included; see sticker price, price of attendance, and net price below.

Sticker price: The tuition and fees that institutions charge (the published price).

Total price of attendance: The tuition and fees (sticker price) that institutions charge students plus other

expenses related to their education. These expenses may include housing (room

and board if the student lives on campus, or rent or related housing costs if the

student does not live on campus), books, and transportation. This term is often

referred to as the “cost of attendance.”

Net price: The amount students and their families pay after financial aid is subtracted from

the total price of attendance.

Revenues: The current fund revenue institutions receive can be categorized according to

source—for example, tuition and fees; earnings from endowment; government

(state, federal and local) appropriations; government grants and contracts; private gifts, grants and contracts; sales of educational services, such as bookstores,

dormitories, or auxiliary enterprises; and other revenue such as hospital revenue

and independent operations. Educational and general (E&G) revenue represents

a part of total current fund revenue. Definitions of these categories are provided

in Appendix B.

Expenditures: Institutions expend current funds in discrete functional areas, which are categorized in operating budget categories such as direct instruction; research; public

service; academic support; student services; institutional support; operation and

maintenance of plant; and scholarships and fellowships.3 Educational and general (E&G) expenditures are a portion of total current fund expenditures. Definitions of these categories are provided in Appendix B.

 

3In cost analyses, scholarships and fellowships are sometimes treated as a reduction in price rather than as an expenditure item.
Chapter I: Introduction

6

Definition of Terms—Continued

General subsidy: The general subsidy is the difference between the average price charged to students and the average cost to the institution of providing an education, per student. Because institutions receive revenue from both tuition and nontuition

sources, students—regardless of whether they attend public or private colleges

or universities, or whether they receive financial aid—typically receive a general

subsidy. This general subsidy does not include the additional subsidies that

some students receive from institutional scholarships and other types of financial

aid. Institutional decisions about tuition levels also are decisions about setting

the level of the general subsidy.

“Average” tuitions: All institutions charge different categories of students slightly different levels of

tuition and fees. Students pay different fees in addition to tuition charges. Fees

are direct charges assessed for services such as laboratory expenses, health

services, exercise facilities, and art studios. The distinction between “tuition”

and “fees” is particularly difficult to track in public institutions. At the same

time, many students receive tuition “discounts” in the form of institutional aid,4

which means that the net tuition is frequently lower than the “sticker” price or

full tuition charge.5 The analysis in this report follows the common pattern of

using the typical tuition and mandatory fees charged to full-time, full-year undergraduates as the measure of average tuition.

Financial Accounting Standards Board and Government

Accounting Standards Board:

Financial data in higher education are based on audited financial statements that

are consistent with relevant accounting standards. The Government Accounting

Standards Board (GASB) sets the standards for public institutions, and the Financial Accounting Standards Board (FASB) sets them for private institutions.

There are some differences in the accounting standards between FASB and

GASB, particularly in the treatment of capital assets.

Expert Analysis

To provide a broader context for the research, NCES commissioned papers from seven national experts in higher education finance and student aid, and sponsored an invitational meeting

involving these researchers and other members of the higher education community in conjunction

with the National Postsecondary Education Cooperative (NPEC). The authors were not asked to

conduct new research, but rather to summarize the conclusions they had reached in their own

work about college prices and costs, including recommendations for future research efforts. The

national experts are:

 

4In this report, the terms “tuition discounting,” “differential pricing,” “institutional aid,” and “expenditures for scholarships and

fellowships” are used synonymously. The term “tuition discounting” has not been consistently defined in part due to differences

in the treatment of institutional aid as a reduction in price (tuition waiver) or as an institutional expenditure. Some authors have

used “tuition discounting” to refer to all institutional aid, while others have used it to refer only to that portion of total institutional aid that is funded from unrestricted institutional funds. For the former case, see Lapovsky’s commissioned paper in Volume 2; for the latter, see Allan (1999). In either case, “tuition discounting” can include need-based aid, non-need-based aid, or

both.

5National datasets such as IPEDS do not allow analysis of the differences between “sticker” and “net” prices except at the average, aggregate level. See Yanikoski and Wilson (1984) for a discussion of differential pricing policies.
Chapter I: Introduction

7

• David W. Breneman, Dean, Curry School of Education, University of Virginia

• D. Bruce Johnstone, Professor of Higher and Comparative Education, SUNY Buffalo

• Dennis Jones, President, National Center for Higher Education Management Systems

(NCHEMS)

• Lucie Lapovsky, President, Mercy College

• Michael McPherson, President, Macalester College, and Morton Owen Schapiro,

President, Williams College

• Michael Middaugh, Vice President for Institutional Research, University of Delaware;

and

• Gordon Winston, Professor of Economics and Director of the Williams Project on the

Economics of Higher Education, Williams College.

The meeting was held on August 2-3, 2000 in Washington, DC. A summary of the discussion at the meeting is included in this report in Chapter II. In addition, the complete set of commissioned papers, a list of attendees, and an agenda for the meeting are enclosed in Volume 2.

Institutional Universe and Data Sources

The statistical analyses in this study target tuition levels for “traditional” undergraduate

students and focuses on institutions in the public and private not-for-profit “higher education”

sector, defined by NCES as institutions that are both degree granting and Title IV participating.6

To an extent, this focus is necessitated by limited information on non-degree-granting postsecondary institutions, particularly in the private for-profit and corporate sectors. In addition, it is standard practice in cost studies to endeavor to construct comparable groups of institutions for

analysis; the criteria used in this report are consistent with those used in prior studies.7

The primary source of available national data for the analyses is the Integrated Postsecondary Education Data System (IPEDS), an annual series of national surveys of postsecondary education institutions that collect information on finances, enrollment, degree completions, faculty

salaries and benefits, and other institutional characteristics. The analyses in Chapters III and IV

are based on IPEDS data for panels of higher education institutions over the period 1988–89 to

1995–96 (to 1997–98 for public institutions), which allow a description of trends in prices, revenue, and expenditures in constant dollar terms, including how they relate to enrollment.8 In addi-

 

6Title IV participating institutions are institutions that have participation agreements with the U.S. Department of Education for

Title IV student aid programs, based on the Postsecondary Education Participation System (PEPS) file.

7Bias analyses of the differences in the characteristics of institutions included in and excluded from the final universes are described in Appendix A.

8Panel data are repeated over-time observations for the same group of individual cases (institutions); each institution has data for

the same variables for each year of the period analyzed.
Chapter I: Introduction

8

tion, data from a new survey, the Institutional Prices and Student Financial Aid Survey (IPSFA),

were used in Chapter V to capture recent information on both tuition and financial aid packaging,

including the percentage of students receiving federal grants, state grants, institutional grants, and

student loans, and the average amounts of aid received. All financial variables in the report were

adjusted for inflation using the Consumer Price Index (CPI-U, 1982-84 = 100), adjusted to 1999

dollars.9

All analyses in this report were performed separately for seven groups of higher education

institutions, based on public/private control of institution and, for 4-year institutions, Carnegie

classification. The final groups include three categories of private not-for-profit 4-year institutions (research/doctoral, comprehensive, and bachelor’s institutions), and four categories of public institutions (research/doctoral, comprehensive, bachelor’s, and 2-year institutions).10 The

number of institutions and proportions of undergraduate enrollment comprised by the final universes are provided in tables 1 and 2. Although the panels of institutions used in Chapters III and

IV comprise 37 percent of all public and private not-for-profit institutions in the IPEDS universe

in 1997–98,11 together they enrolled 78 percent of undergraduates attending public and private

not-for-profit institutions in the fall of that year.12

Analytical Models Used in the Analysis

Rather than breaking new ground, most of the analyses in this report rely on current knowledge of appropriate models in order to best address Congressional concerns. Previously developed models for the public and private not-for-profit sectors were identified by NCES and

updated with more recent data. Different models were used for the public and private not-forprofit sectors, because the research has consistently documented that there are fundamental differences in the financing structures, enrollment markets, and tuition decisionmaking processes

 

9The Consumer Price Index for All Urban Consumers (CPI-U) measures changes in relation to a base period, in this case the

average index level for a 36-month period covering 1982, 1983, and 1984, which is set equal to 100.

10In addition to private for-profit institutions, 2-year private not-for-profit institutions were excluded from the analysis due to the

small size of this sector as well as problems with data availability.

11Although financial data for private not-for-profit institutions are available only until 1995-96, enrollment data are available for

subsequent years, including 1997-98.

12Similarly, the universe of institutions in Chapter V comprised 55 percent of all public and private not-for-profit institutions in

the IPSFA universe in 1999, but enrolled 85 percent of first-time, full-time undergraduates attending public and private not-forprofit institutions in that year. Bias analyses of the differences in the characteristics of institutions included in and excluded from

the final universes are described in Appendix A.
Chapter I: Introduction

9

Table 1.—Number and undergraduate enrollment of public and private not-for-profit institutions included 

Table 1.—and excluded from the final universe in Chapters III and IV: 1997–98

Percentage Percentage

Number of total Number of total

Final universe:

 Public research/doctoral 135 2.6 2,118,284 16.9 

 Public comprehensive 221 4.2 1,624,631 13.0 

 Public bachelor's 66 1.3 198,349 1.6 

 Public 2-year 813 15.5 4,424,311 35.3 

 Private not-for-profit research/doctoral 47 0.9 315,221 2.5 

 Private not-for-profit comprehensive 192 3.7 459,621 3.7 

 Private not-for-profit bachelors 451 8.6 621,849 5.0 

Excluded from universe:

 Public institutions 1,134 21.7 1,893,167 15.1 

 Private not-for-profit institutions 2,173 41.5 860,940 6.9 

All public and private not-for-profit institutions 5,232 100.0 12,516,373 100.0 

NOTE: Institutions included in the final universe were selected according to various criteria, including Title IV participation, 

degree-granting status, location in the 50 states and the District of Columbia, sector, Carnegie classification (for 4-year 

institutions), enrollment, and percentage of undergraduate and full-time enrollment. The enrollment data presented in this table 

are from the original IPEDS files, prior to the imputation process or other analysis procedures described in Chapters III and IV 

and in Appendix A.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data 

System (IPEDS), Full 1998 Collection Year.

fall headcount enrollment

Undergraduate 

Institutions

between the sectors.13 Given the differences in the pre-existing models and the theories behind

them, the variables included in the models for the two sectors also differ slightly.

Public institutions are heavily subsidized with state (and sometimes local) tax dollars.

Pricing decisions in public institutions are policy decisions shared between state governments

and institutional governing boards, defined by the broad parameters of state postsecondary education policies. Decisions about changes in tuition from year to year are dependent on the state

appropriations and budget processes. Tuition levels are often specified in the annual budget legislation, and as a technical matter, tuition revenues are often treated as offsets to state appropriation levels. At the same time, for many public institutions, decisions about student access and

enrollment are made at the state level, with the individual institutions responsible for developing

 

13See, for instance, Winston (1998b); McPherson and Shapiro (1991, 1998); Davis (1997).
Chapter I: Introduction

10

Table 2.—Number and undergraduate enrollment of public and private not-for-profit institutions included 

Table 2.—and excluded from the final universe in Chapter V: 1999

Percentage Percentage 

Number of total Number of total

Final universe:

 Public research/doctoral 145 3.6 383,705 21.0 

 Public comprehensive 254 6.4 281,057 15.4 

 Public bachelor's 74 1.9 35,545 1.9 

 Public 2-year 934 23.4 493,477 27.1 

 Private not-for-profit research/doctoral 77 1.9 105,897 5.8 

 Private not-for-profit comprehensive 222 5.6 102,308 5.6 

 Private not-for-profit bachelors 471 11.8 150,786 8.3 

Excluded from universe:

 Public institutions 615 15.4 149,853 8.2 

 Private not-for-profit institutions 1,194 30.0 120,744 6.6 

All public and private not-for-profit institutions 3,986 100.0 1,823,372 100.0 

NOTE: Institutions included in the final universe were selected according to various criteria, including Title IV participation, 

degree-granting status, location in the 50 states and the District of Columbia, sector, Carnegie classification (for 4-year 

institutions), and enrollment. The enrollment data presented in this table are from the original IPSFA files; some institutions did 

not report enrollment data. In addition, the total number of institutions differs from that in Table 1 due to differing data sources; 

IPSFA data were available for a sub-set of the institutions in IPEDS.

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).

Institutions

First-time, full-time, 

degree/certificate-seeking 

undergraduate enrollment

admissions policies that are consistent with these access goals. Within their missions, some institutions are expected to accommodate all enrollment demand from qualified applicants; others

are allowed to limit enrollments, or expand them to serve new populations. As a result, enrollment demand at public institutions is determined less by market conditions, including price, than

are enrollments at private not-for-profit institutions.

At private not-for-profit institutions, price-setting decisions are influenced by internal

budget considerations as well, such as desired expenditures and the availability of nontuition

revenue. However, prices at private not-for-profit institutions are more likely than public institutions to be influenced by external market factors of the environments in which they operate, including the existence of competition from other institutions, the income levels of potential

consumers, perceptions of quality and institutional reputation, and other factors. In addition, private not-for-profit institutions tend to have substantial control over their admissions policies, and
Chapter I: Introduction

11

enrollment management policies have become an increasingly important tool.14 Although private

not-for-profit institutions typically have a target for enrollment, the targets vary widely. Some

institutions may choose to limit new enrollments, while others may have excess capacity and

need to fill seats. Nonetheless, market conditions play an important role for both prices and enrollment at most private not-for-profit institutions.

The model that was replicated for analysis of trends in public institutions is a singleequation correlational model developed by the U.S. General Accounting Office (GAO) in 1998.

This model describes the statistical associations between institutional revenue and expenditure

categories and changes in prices over time. The model is based on the theory, which is implicit in

the 1998 HEA mandate, that various categories of expenditures—such as instruction, administrative expenses, research expenditures, and operations and maintenance—are associated with

changes in prices over time. The model also takes into account research suggesting that sources

of revenue, especially from state and local governments, are relevant to tuition levels charged at

public institutions. The model therefore focuses on factors internal to the institutions (expenditures and revenues) and captures external influences only indirectly—for example, state policy

decisions on support for higher education are indirectly measured through the level of government appropriations revenue. The research on the public model is presented in Chapter III.

The model that was updated for private not-for-profit institutions is a simultaneous equation model of college enrollments and prices, jointly developed by Westat, Inc., and Pelavin Associates (1994). This model attempts to describe the relationships between prices and both

“internal” and “external” factors at private not-for-profit 4-year institutions. The model assumes

that prices and new enrollments simultaneously determine each other, and uses separate equations to capture the associations of internal and external factors with tuition. The structure of the

model allows observed levels of tuition to be viewed as equilibrium prices at a specific point in

time, while controlling for various factors that may influence institutions’ and students’ decisions

regarding enrollment. This model was not extended to the public sector, because the Westat/Pelavin research found the model to be a poor fit for public institutions. The research on private not-for-profit 4-year institutions is presented in Chapter IV.

Neither of the two pre-existing models included financial aid among the independent variables, with the important exception of institutional aid. Therefore, a new model was developed to

analyze these relationships, using data on revenues and expenditures from IPEDS and data on

various forms of student aid from the IPSFA dataset. IPSFA resulted from a mandate in the 1998

 

14Anecdotal evidence suggests that public institutions are beginning to use enrollment management policies more frequently; to

date, however, most studies of these policies have focused on private not-for-profit institutions. See Lapovsky’s commissioned

paper in Volume 2.
Chapter I: Introduction

12

HEA Amendments that called for improved data collection. At the time of this report, financial

aid data from IPSFA were only available for one year, so an examination of changes over time to

allow trends to be identified was not possible. Chapter V reviews previous research regarding the

relationship between financial aid and prices, and presents the results of the models using the

newly available IPSFA data on financial aid.

Limitations of the Research

Despite the effort to improve on previous national studies, the analyses in this report remain unfinished insofar as providing complete answers to some aspects of Congress’ questions.

The limitations are caused by: 1) the need to rely on existing typologies for classifying institutions; 2) the absence of standard definitions for several of the factors of interest to Congress; 3)

the differences in accounting standards between institutional sectors; and 4) the inherent limitations of statistical analysis of costs to reveal causal relationships between costs and prices. These

issues are discussed in more detail below.

Institutional classification systems/comparability of types

National data systems organize institutional information into broad categories based on the

Carnegie classification system.15 However, the standard Carnegie classifications fail to capture

aspects of institutions beyond differences in primary mission and funding, such as the nature of

students served, programs offered, the role of faculty in the institution, and governance. These

areas are essential to accurate analysis of costs because they shape institutional expenditure patterns as well as the availability of revenues including tuition revenues. Some examples of institutional characteristics most relevant to the analysis of costs are:

• Student attendance status. The changing demography of American higher education

means there is no longer a “typical” college student. In addition to full-time undergraduate students—who comprise a minority of total student enrollments across all

sectors—there are part-time undergraduates, full- and part-time technical students,

post-baccalaureate certificate and credential students, academic graduate students, and

first professional (e.g., law and medicine) students. Students may live at home or on

campus, and the majority work while in college. All of these differences affect the way

that students interact with the college, which in turn shapes their price of attendance.

To conduct proper comparative analyses, samples that compare institutions serving

similar student profiles need to be developed.

 

15See Carnegie Foundation for the Advancement of Teaching, 1994 Classification System, available from their website:

http://www.carnegiefoundation.org/Classification.
Chapter I: Introduction

13

• Student academic preparation. There also are important differences among institutions

in the academic portfolios of students entering the institutions. Some institutions

maintain very selective admissions policies and only serve students who are well prepared for college-level work. However, the majority of institutions are not as selective.

The variability of student preparation is relevant to cost analysis because students in

less selective institutions generally take longer to graduate. Furthermore, academic selectivity is an important factor in shaping the competitive environment for faculty and

resources within the institutions. The most selective institutions operate in statewide or

even national markets, whereas less selective institutions draw students primarily from

local or regional areas. Academic selectivity also influences tuition and fee structures.

The most selective institutions typically charge higher tuition and fees than less selective institutions do. This is true even at public institutions where the majority of revenue is still provided by the state or local government.

• Program and mission. The Carnegie classification system attempts to categorize institutions based on their mission (instruction, research, and public service) and program

offerings. Even within these categories, however, there are variations among institutions because of different mixes of disciplines and programs, as well as the different

roles of sponsored research, institutional community service, and non-credit instruction. These differences, along with student admission selectivity, affect the revenue

sources and markets for an institution, including whether it serves local, regional, national, or even international markets. Revenue availability and market share, in turn,

shape cost structures.

• Production function of higher education. While all higher educational institutions

share an instructional mission, the way in which instruction is provided differs between

institutions in terms of class size, use of full-time faculty, reliance on educational technology, and the relation of research to instruction. Some institutions maintain small

classes taught by full-time faculty with few administrative or research roles; others use

part-time faculty, distance learning, and large classes. These differences determine the

unit costs of the instruction function, as well as the percentage of total costs that can be

directly attributed to instruction.

• Funding profile. Changes in funding patterns mean that the traditional classifications

of “public” and “private not-for-profit” are not precise descriptions of the funding profile of many institutions. Public institutions have many sources of funds in addition to

public tax revenues; private not-for-profit institutions receive public funds; and both

public and private not-for-profit institutions increasingly have for-profit subsidiaries.

The private for-profit sector also has grown considerably, and a substantial amount of

teaching and learning is now being provided in the corporate sector by entities that are

not even classified as “postsecondary” institutions. To classify institutions accurately

for research purposes, new descriptors would need to be developed that accurately

capture the new funding patterns.
Chapter I: Introduction

14

Standard definitions

The challenge of collecting comparable data is not confined to the issue of institutional

classifications. There are no standard definitions currently being used to guide data collection for

several of the variables that Congress is interested in, in particular “merit aid” and technology

finance. Many state and institutional aid programs make awards based on both need and merit,

e.g., students must establish economic need for aid, and then awards are distributed based on

merit. This inability to differentiate and clearly define merit aid makes it impossible to probe past

trends in merit-based versus need-based institutional aid. In addition, technology is not a standard

expenditure item, as the costs of technology are embedded as costs within other categories. For

instance, the costs of technology related to distance learning are reported as instructional expenditures, and the proportion of instructional costs that are attributable to technology alone are not

separately identified. The problem is similar in other categories, such as administrative costs, or

building costs, where technology costs are embedded within the larger categories.

Some of these data limitations could potentially be overcome, but would require new definitions to be developed and applied prospectively to the future collection of data. Even if there

were agreement about these definitions, it is not possible to apply these measures retroactively to

data that have already been collected.

Accounting standards

The issues of definition and classification are further complicated by institutional accounting standards, which influence the data institutions maintain. For example, there are differences

in the accounting standards used by public and private not-for-profit institutions that affect the

comparability of data for capital expenditures and the valuation of physical plant because of differences between the sectors in reporting of costs for depreciation, land value, and replacement

costs. These differences mean that existing national data cannot be used as a basis for analysis of

capital outlay costs. In addition, many public institutions do not technically own the land or the

buildings for their campuses, which are properties of either state or local government. The assets

and costs of affiliated foundations are reported differently between the sectors as well. The challenge of comparable accounting standards cannot be overcome simply through changes in IPEDS

data reporting, as the accounting standards are the province of the Federal and Government Accounting Standards Boards, independent agencies.

At the same time, current financial reporting procedures do not provide for the collection of

certain breakdowns that would be necessary for detailed analysis. For example, revenue and expenditure data cannot be differentiated by level of student. Detailed information about differential pricing policies, commonly referred to as “tuition discounting,” are not available to allow
Chapter I: Introduction

15

analysis of the difference between “sticker” and net tuition prices except at an aggregate level. In

addition, institutions often do not track internal pathways between and among revenue sources

and expenditures, which means that certain relationships—such as any direct linkage between

federal loan capital and institutional aid—cannot be specifically defined using national data.

Recently, changes were made to FASB standards and were incorporated into IPEDS beginning in Fiscal Year 1997.16 Similarly, GASB recently issued new accounting rules that will be

phased in after June 15, 2001. These changes may improve the data collected through NCES, but

it will take several years until all changes are implemented at the institutional level.

The limits of cost analysis

The production function of higher education complicates the measurement of costs, and

limits the usefulness of cost analysis as a tool for understanding the causes of trends in higher

education finance. Unlike the more technical data limitations that are described above, these constraints cannot be overcome through the refinement of data collection or prospective analysis, but

are inherent in the basic measures. The literature on cost analysis in higher education addresses

these issues in considerably more detail than will be repeated here.17 The following bullets briefly

summarize the many issues that determine the shape of the analysis:

• Inputs are outputs: The distinction between inputs and outputs is particularly difficult

to measure in higher education, because there is no good way to measure the value

added by the effect of education on students. As a result, it is not possible to isolate the

value of the product (an educated student with a degree or credential) from the cost of

production (the resources required to educate one student) from the quality of the input

(the academic and social credentials of entering college students). It is similarly hard to

measure the other institutional outputs of community service and research. As a result,

most cost analyses use expenditures as proxies for costs, without trying to separate inputs from outputs or measuring value added.

• The problem of joint products: The joint products of teaching, research, and service

do not allow most instructional resources to be separated from funds spent for other

purposes. Funds for contracted activities, including some sponsored research, can be

segregated from analyses of other expenditures, but the costs of research related to the

institution’s core mission remain.

• Student FTE enrollment as the basis for unit costs: It is necessary to develop some

way to assess “unit” costs for higher education, because looking at gross expenditures

 

16For example, expenses will be measured according to accrual rather than cost accounting methods, and tuition and fee revenue

will be reported net of price discounts, with an offsetting adjustment to the expense side. The GASB changes will be similar but

too different to compare public institutions with private not-for-profit institutions.

17See, for example, an introductory essay by Jenny (1996); and Bowen (1980).
Chapter I: Introduction

16

and revenues at the institutional level gives no context to the analysis. The default unit

measure for analysis of costs is student enrollment, typically measured in terms of FTE

enrollment. However, problems remain with the use of FTE enrollment as the basis for

measuring costs. For example, the distribution of students by level of study and discipline affects patterns of expenditures but is not captured in FTE measures. In addition,

the unit costs of administration and student services are driven by headcount enrollment rather than course-taking patterns reflected in measures of FTE. As a result, the

FTE measure does not capture all unit costs, particularly in institutions with high numbers of part-time students.

• Identification of “educational” costs and revenues: In focusing on the educational

product, analyses should attempt to isolate costs and revenues that are devoted to the

core activities of the institution. Therefore, costs and revenues associated with such

activities as auxiliary operations, contracted research, and sales or services to vendors

should be deleted from the measures. To avoid the “double-counting” of aid, and to be

able to identify how financial aid influences tuition and prices, most analysts deduct

grant aid from government or private aid sources where possible.

• Focus on operating costs: A full understanding of costs should ideally include capital

costs that are not part of the operating budget, including long-term debt financing for

construction of new facilities, renovation and repair costs, and the value of lands and

buildings. However, differences in accounting methods between the public and private

not-for-profit sectors as well as different habits in funding make it difficult to develop

comparable measures of capital costs across sectors. As a result, most analysis is isolated to evaluation of trends in operating costs and revenues. Winston estimates that

excluding capital expenditures from cost analysis understates the true cost of education

by about 25 percent.18

Given these and other characteristics of higher education—such as the availability of nontuition sources of revenue—there is little reason to expect a consistent relationship between costs

and prices across all institutions or groups of institutions, even though a specific relationship may

be present at one particular institution and may even be discovered with enough information

about the institution.19 Nevertheless, the analyses presented in this report highlight trends and

point to associations between variables that can lead to a better understanding of the nature of

higher education finance.

 

18See Winston’s commissioned paper in Volume 2.

19See Stringer and Cunningham (1999) for a more detailed discussion of these issues.
17

Chapter II: Summary of Commissioned Papers and National

Invitational Meeting

Introduction and Overview

In order to provide a framework for the analysis presented in subsequent chapters and provide different perspectives on some of the relevant issues, the views of the national higher education research community were solicited through seven commissioned papers on college costs

and prices and a discussion of these papers at a subsequent national invitational meeting. The

meeting, held in Washington, DC on August 2-3, 2000, was convened by the National Center for

Education Statistics (NCES) in conjunction with the National Postsecondary Education Cooperative (NPEC).

In their papers, the experts were asked not to present new research, but rather to summarize

the conclusions they had reached from their work about the major factors influencing changes in

college costs and prices, and to suggest the foci of future research efforts. The paper authors and

titles are:

• David W. Breneman, Dean, Curry School of Education, University of Virginia, “An

Essay on College Costs”;

• D. Bruce Johnstone, Professor of Higher and Comparative Education, SUNY Buffalo,

“Higher Education and those ‘Out of Control Costs’”;

• Dennis Jones, President, National Center for Higher Education Management Systems

(NCHEMS), “Cost Analysis and the Formulation of Public Policy”;

• Lucie Lapovsky, President, Mercy College, New York, “Institutional Financial Health:

Tuition Discounting and Enrollment Management”;

• Michael McPherson, President, Macalester College, and Morton Owen Schapiro,

President, Williams College, “Issues of Cost and Price in Higher Education: Observations on Needed Data and Research”;

• Michael Middaugh, Vice President for Institutional Research, University of Delaware,

“Measuring Higher Education Costs: Considerations and Cautions”; and

• Gordon Winston, Professor of Economics and Director of the Williams Project on the

Economics of Higher Education, Williams College, “Higher Education’s Costs, Prices,

and Subsidies: Some Economic Facts and Fundamentals.”
Chapter II: Summary of Commissioned Papers and National Invitational Meeting

18

The complete set of commissioned papers, a list of attendees, and the agenda for the meeting are included in Volume 2 of this report.

Major Discussion Points

This summary of the meeting’s discussion about the commissioned papers is not intended

to capture all of the complexity of a rich two-day discussion. Rather, this summary reiterates the

major elements of the conversation.

The Trend Data

The facts about basic trends in prices and financial aid for public 2- and 4-year and private

not-for-profit 4-year institutions are not in serious dispute. The details of the measures differ

slightly between researchers, depending on the time periods being reviewed and sources of data

used, but the direction and shape of the changes are the same regardless. Overall, between 1985–

86 and 1995–96, gross tuition (“sticker price”) in both the public and private sectors grew faster

than consumer price index (CPI) measures of inflation. Net prices (tuition and fees after receipt

of grant aid) also rose faster than inflation, despite increases in financial aid. The type of financial aid that has grown the fastest over this period has been institutional aid. Although net prices

have increased, trend data do not indicate skyrocketing college costs—for example, in the public

sector, over the past decade, costs have increased overall by around a percent a year—nor do they

reveal prices that have increased so much that overall enrollments have suffered. The highestpriced private not-for-profit institutions continue to experience more enrollment demand than can

be accommodated despite rising tuitions. (See the commissioned paper by McPherson and Schapiro for a more detailed discussion of these issues.)

Public and Policymaker Perceptions of College Costs and Prices

As measured by opinion polling and focus group studies, public concern about rising college prices remains high. However, public opinion seems to be largely based on perception of

prices at selective, private not-for-profit institutions, which tend to have the highest sticker prices

overall but represent only a fraction of the universe of American postsecondary education. These

public perceptions in turn influence policymaker views about college affordability. In general, the

public is not well informed about either college prices or financial aid, overestimating the cost of

college in all sectors and underestimating the availability of financial aid. (Johnstone’s commissioned paper discusses these issues in more detail.)
Chapter II: Summary of Commissioned Papers and National Invitational Meeting

19

Differences Between Public and Private Not-for-Profit Institutions

Research by many authors shows persistent differences between the public and private notfor-profit sectors, both in the trends in prices and costs and the probable causes for the trends. In

public institutions, prices (tuition levels) are determined by public policymakers and are a function of overall state budget practices. Tuition increases in the past decade have been partial replacements for lost state tax subsidies. (Commissioned papers by Breneman and Jones explore

these issues.) In private not-for-profit institutions, the picture is more complex, as there are distinct types of institutions within this sector that operate in different markets. For example, highly

selective, private not-for-profit research universities serve different markets than comprehensive

urban colleges. Competition plays an important and complicated role in price and cost decisions

in the private not-for-profit market. There is some evidence that institutions operate in “microclimates,” influenced by enrollment demand, pricing, and reputation for institutions in the same

stratum. (Winston’s commissioned paper goes into more detail about these issues.) The differences between sectors and types of institutions mean that research will be most informative if it

separates public and private not-for-profit institutions as well as recognizing differences within

institutional sectors.

The Relationship Between Cost and Price

For both public and private not-for-profit institutions, costs generally are only indirectly

related to prices across groups of institutions, due to multiple sources of revenue and other characteristics of higher education institutions. Therefore, an analysis of changes in internal cost

structures will not shed much light on changes in prices at the aggregate level. As a result, detailed analysis of costs, using either national or institutional data, will not yield insights that will

help to answer questions about college prices, access, affordability, or quality.

• Public institutions: The cost/price relation is particularly weak in public institutions,

where prices are set by policy, institutions are publicly subsidized regardless of student

financial need, and costs or expenditures are determined by mission, program structure,

and revenue availability. Tuition is typically the revenue of last resort, used to backfill

state funding. While many states require public institutions to set non-resident tuition

to equal “full” costs, in most states a very low percentage of undergraduate student enrollments at these institutions are out-of-state students. For the vast majority of students who pay in-state tuitions, the prices are determined by policy, not by costs.

• Private not-for-profit institutions: In private not-for-profit institutions, there is a

stronger relationship between price and cost than in the public sector because of the

absence of significant forms of institutional subsidy. Yet even in private not-for-profit

institutions, costs are only one element of pricing decisions. Prices are influenced by

student demand, institutional perceptions of quality in relation to competing institu-
Chapter II: Summary of Commissioned Papers and National Invitational Meeting

20

tions, the availability of other revenues, the cost of the programs, and other factors.

(Winston’s commissioned paper addresses these issues in greater detail.)

Tuition Discounting

Tuition discounting allows institutions to adjust sticker prices downward by using institutional financial aid. The information about tuition discounting helps to show that price-setting is

a management and marketing decision, not based predominantly on institutional costs. Institutional aid is most commonly viewed as an expenditure item, or a cost from foregone income from

reduced tuitions. Tuition discounting also contributes to gross tuition revenue, if the awards attract students to institutions that they might otherwise have not attended. Depending on the institution, tuition discounting can even increase net tuition revenue if the increases in gross tuition

are greater than the increases in the cost of institutional aid. Tuition discounting is a growing

trend, particularly among private not-for-profit institutions with relatively weak enrollment demand. The practice of tuition discounting also may be growing in public institutions, but there is

limited information on the topic. (Lapovsky’s commissioned paper provides a more complete

discussion of this issue.)

The Uses of Cost Analysis

Analysis of internal institutional expenditure patterns or costs is an important management

tool within individual institutions and, to some extent, as a comparative tool between institutions.

The development of unit cost measures has always been difficult in higher education because of

multiple sources of revenues, weak outcome measures, and joint products between research and

instruction. These methodological issues have been resolved somewhat with respect to measuring

the direct costs of instruction at the aggregate level, without differentiating between undergraduate and graduate education. Analyses of trends in costs of instruction conducted within an individual institution help reveal patterns by discipline and program, making cost assessment a useful

element of planning and program review. Comparative analysis of broad cost patterns between

institutions also can be helpful to institutions in setting a context for their own work and for

benchmarking costs. The tools developed by Michael Middaugh at the Delaware Project on Instructional Productivity and by the National Association of College and University Business Officers (NACUBO) are both good tools for these kinds of comparisons. (A complete description of

the Delaware Project is provided in Middaugh’s commissioned paper.)

Cost analysis is not, in itself, a useful mechanism for understanding the root causes of price

increases at the national level because of the relatively weak relation between prices and costs

and the differences in types of institutions. Cost analysis also requires a level of detail that can

take attention and resources away from the types of analyses that are best addressed at the state
Chapter II: Summary of Commissioned Papers and National Invitational Meeting

21

and national level, such as assessments of changes in subsidy patterns and student access. (The

commissioned papers by Jones and Breneman provide more detail on these issues.)

Cost Drivers

At the aggregate level, research and theory consistently suggest that the major cost “drivers”—the factors and forces that determine how much institutions can spend and how they spend

it—are:

• Revenue availability: institutions attempt to raise all the money they can from multiple

sources;

• Institutional aid: for some institutions, increases in the use of institutional aid may require increases in revenue, from either tuition or other sources such as endowment income (for other institutions, the use of tuition discounting may contribute to increases

in revenue);

• Mission and discipline: institutions that have research, graduate education, and public

service missions tend to have higher costs, particularly if they offer programs in engineering and other laboratory sciences;

• Faculty compensation and workload policies: institutions that use full-time faculty in

the classroom spend more on instruction than those that use teaching assistants, adjuncts, and part-time faculty to augment the core faculty;20 and

• Class size: large classes are less expensive than small ones.

 

20Related to the issue of faculty compensation is the labor-intensive nature of higher education; some economists have argued

that higher education is not capable of experiencing increases in productivity, but nevertheless institutions must pay competitive

salaries that rise over time, leading to continuous increases in unit costs. For discussion of this issue, see the commissioned papers by Johnstone and Breneman.
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23

Chapter III: Revenues, Expenditures, and Prices at Public

Institutions

This chapter focuses on the results of the first analytical component, the trend analysis and

modeling of expenditures, revenues, and prices for public institutions. The chapter seeks to address Congress’ questions by describing changes over the period 1988–89 to 1997–98 in various

expenditure and revenue categories, as well as changes in tuition levels, for public 4-year and 2-

year institutions. The analysis also updates a correlational regression model in order to explore

the associations among these factors.

Data and Methods

In order to examine the comparative changes of various categories over time, trend data on

expenditures, revenues, enrollment, and prices were calculated for the period 1988–89 to 1997–

98, using a panel of public 4-year and 2-year institutions. These data include average, inflationadjusted dollar changes over the whole period and average annual percentage changes. In addition, shifts in the composition of revenues and expenditures are described. These trend data are

presented according to type of institution.

To supplement these descriptive statistics and to better understand the statistical relationships between various revenue and expenditure categories and changes in tuition, a linear regression model from a report by GAO, Higher Education: Tuition Increases and Colleges’ Efforts to

Contain Costs (1998), was refined and updated. GAO examined changes in in-state, full-time,

full-year undergraduate tuition and fees over the five-year period 1989–90 to 1994–95 for public

4-year institutions. Linear regression analysis was used to identify relationships between the dollar change in tuition over this period (the dependent variable) and the dollar changes in various

revenue and expenditure categories per student (the independent variables, 15 in total). The

model thus identified variables associated with larger or smaller tuition increases, i.e., the characteristics of institutions with larger or smaller tuition increases.

The regression model presented in this analysis reproduces the GAO model with a few minor modifications and for a longer time period (table 3). For 4-year institutions, the dependent
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

24

GAO model Updated model

Universe Four-year public institutions in the 50 states 

and the District of Columbia where more 

than 50 percent of students enrolled in the 

fall term were undergraduates and more 

than 50 percent of students enrolled in the 

fall term were attending full time. 

Institutions had to report tuition revenue, 

instruction expenses, fall enrollment, and 

typical tuition and fees for in-state 

undergraduate students. Institutions at 

which the stated tuition charge was less than 

50 percent or more than 150 percent of 

reported tuition revenue per FTE student 

were excluded. N = 383 

Four-year and 2-year public institutions in 

the 50 states and the District of Columbia 

where at least 50 percent of students 

enrolled in the fall term were 

undergraduates, at least 25 percent of 

students enrolled in the fall term were 

attending full time, and at least 200 FTE 

students were enrolled. N = 1,235 

(research/doctoral = 135; comprehensive = 

221; bachelor’s = 66; two-year = 813)

Time period 1989–90 to 1994–95 1988–89 to 1997–98, with sub-periods of 

1988–89 to 1990–91; 1990–91 to 1994–95; 

and 1994–95 to 1997–98

Notes All financial variables were converted to 

constant 1994–95 dollars; revenue and 

expenditure variables were expressed per 

FTE student (calculated as the number of 

full-time fall-term students plus one-third 

the number of part-time fall-term students).

All financial variables were converted to 

constant 1999 dollars; revenue and 

expenditure variables were expressed per 

FTE student (calculated from reported 

instructional activity for the fall term).

Dependent variable Dollar change in in-state, full-time, full-year 

undergraduate tuition and required fees

Same for 4-year institutions; dollars change 

in in-district, full-time, full-year 

undergraduate tuition and required fees for 

2-year institutions

Independent variables Dollar change in revenue from federal, 

state, and local government appropriations 

Same

Dollar change in revenue from grants, 

contracts, and other sources (excluding noninstitutional scholarships and fellowships 

and revenue for hospitals, auxiliary and 

independent operations)

Separated into two variables: 1) government 

grants and contracts less federal, state, and 

local scholarships and fellowships; and 2) 

philanthropic revenue (endowment income 

plus revenue from private gifts, grants, and 

contracts)

Dollar change in instruction expenditures Same

Dollar change in student services 

expenditures

Same

Table 3.—Characteristics of regression model for public institutions
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

25

GAO model Updated model

Independent variables Dollar change in institutional scholarships 

and fellowships

Same

Dollar change in other student-related 

expenditures (prorated portion of academic 

and institutional support, physical plant 

maintenance, and transfers)

Same

Dollar change in research expenditures Same

Dollar change in non-student-related 

expenditures (public service plus a prorated 

portion of academic and institutional 

support, physical plant maintenance, and 

transfers)

Same

Percentage point change in the ratio of instate undergraduate tuition to average 

tuition revenue received per FTE student

Eliminated because of definitional overlap 

with dependent variable

Change in dollar amount of tuition used for 

noncurrent fund purposes

Eliminated due to lack of significance

Ratio of in-state undergraduate tuition to 

average tuition revenue received per FTE 

student in base year

Eliminated because of definitional overlap 

with dependent variable

Dollar change in market value of 

endowment fund

Eliminated due to missing data

Level of in-state undergraduate tuition in 

base year

Same

Dollar change in the amount by which E&G 

revenues exceeded/fell short of E&G 

expenditures

Same

Dollar change in surplus/deficit from 

independent operations, auxiliary 

enterprises, and hospitals

Eliminated due to lack of significance

Added: Percentage point change in ratio of 

graduate FTE enrollment to total FTE 

enrollment

SOURCE: U.S. General Accounting Office (GAO), 1998, Higher Education: Tuition Increases and Colleges’ Efforts to Contain

Costs, GAO/HEHS-98-227, Washington, DC: Government Printing Office, September.

Table 3.—Characteristics of regression model for public institutions—Continued
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

26

variable is the same: the dollar change in the tuition and required fees charged to the typical fulltime, full-year, in-state, undergraduate student.21 (For 2-year institutions, in-district undergraduate tuition is used as the dependent variable.) The model includes 12 independent variables, some

of which differ slightly from the GAO study due to clarifications or data issues. (Except where

otherwise noted, changes are in terms of constant dollars per FTE student.)

• The level of in-state undergraduate tuition in the base year

• Change in instruction expenditures

• Change in research expenditures

• Change in student services expenditures

• Change in other student-related expenditures, including pro-rated portions of academic

and institutional support, physical plant maintenance, and transfers

• Change in non-student-related expenditures, including public service and pro-rated

portions of academic and institutional support, physical plant maintenance, and transfers

• Change in philanthropic revenue, including revenue from endowment income as well

as revenue from private gifts, grants, and contracts

• Change in revenue from government appropriations, from federal, state, and local

sources

• Change in revenue from government grants and contracts from federal, state, and local

sources, less federal, state, and local scholarships and fellowships

• Change in the amount by which educational and general (E&G) revenues exceed or fall

short of E&G expenditures, where E&G revenues and expenditures are those categories that are most directly related to the missions of the institutions22

• Change in institutional scholarships and fellowships

• Percentage point change in the ratio of graduate FTE enrollment to total FTE enrollment (only for 4-year institutions)

The universe for the model includes slightly more public 4-year institutions than in the

GAO report (422 compared with 383) and includes more than 800 public 2-year institutions,

 

21In using in-state tuition as the dependent variable, this model may not reflect public institutions’ pricing policies regarding outof-state students; it is plausible that public institutions’ behavior with regard to out-of-state students is more similar to the behavior of private not-for-profit institutions. Also note that the amount of tuition and fees charged to in-state, undergraduate students differs from tuition and fee revenue per FTE student; the former represents the rate of tuition charged to a certain type of

student, while the latter reflects tuition and fee revenue collected from all students. Both of these measures do not take into account tuition discounts, which are accounted for as expenditures on institutional scholarships and fellowships.

22E&G revenues include tuition and fees, government appropriations, government grants and contracts, private gifts, endowment

income, sales and services, and other revenue. E&G expenditures include instruction, research, public service, academic support,

student services, institutional support, plant operations and maintenance, scholarships and fellowships, and transfers. Both exclude revenue and expenditures for auxiliary enterprises, hospitals, and independent operations.
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

27

whereas GAO confined its study to 4-year institutions. Regression analyses are run for each type

of public institution, i.e., research/doctoral institutions, comprehensive institutions, bachelor’s

institutions, and 2-year institutions. In addition, the model covers a longer time period (1988–89

to 1997–98) than in the GAO report. Separate analyses are performed for three sub-periods:

1988–89 to 1990–91, 1990–91 to 1994–95, and 1994–95 to 1997–98. In these sub-periods, the

average annual rate of increase in undergraduate tuition differs markedly, with the highest rate

occurring in the middle sub-period for all four groups of public institutions (see table 4).

Table 4.—full-year students: 1988–89 to 1997–98

1988–89 1988–89 1990–91 1994–95

to 1997–98 to 1990–91 to 1994–95 to 1997–98

Public research/doctoral 4.1 2.7 6.3 2.2

Public comprehensive 4.2 2.4 6.3 2.7

Public bachelor's 4.3 3.7 5.3 3.5

Public 2-year 3.4 1.3 5.3 2.4

NOTE: Percentages were calculated as averages of the average annual change increments within each institutional type. Tuition

amounts were converted to constant 1999 dollars using the CPI-U (1982–84 = 100) before annual changes were calculated.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data 

System (IPEDS), Full Collection Years 1989 to 1998.

Table 4.—Average annual percentage change in in-state undergraduate tuition and fees for full-time, 

Time period

As in the GAO report, the model identifies revenue and expenditure variables that are associated (or fail to be associated) with the size of tuition increases. The results can be interpreted as

pointing to the independent variables that have a relationship with the change in tuition, after

adjusting statistically for the covariation of all other variables in the model.

Data Sources, Panel Selection, and Statistical Procedures

The source of data for both the trend analysis and the regression modeling is the Integrated

Postsecondary Education Data System (IPEDS) for 1988–89 to 1997–98. The universe of public

institutions was drawn from Title IV-participating, degree-granting institutions located in the 50

states and the District of Columbia. Both 4-year and 2-year institutions were included; 4-year institutions were further divided by Carnegie classification into research/doctoral, comprehensive,

and bachelor’s institutions. The following were excluded from the universe: institutions that enrolled less than 200 FTE students; 4-year institutions with less than 50 percent undergraduate fall

headcount enrollment; and 4-year institutions with less than 25 percent full-time fall headcount
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

28

enrollment.23 The final dataset comprises four panels of public institutions with data for all ten

years; the total number is 1,235 (research/doctoral = 135; comprehensive = 221; bachelor’s = 66;

2-year = 813).24 Financial variables were adjusted to constant 1999 dollars using the Consumer

Price Index (CPI-U, 1982–84 = 100). Revenue and expenditure variables were calculated on a

per FTE student basis, where FTE was generated from reported or estimated fall instructional

activity (credit hours).25

Prior to conducting the regression analyses, bivariate relationships between variables were

examined through scatterplots and correlation matrices. (Relationships between the independent

variables and dependent variables were assumed to be linear, and no visual evidence was found

to contradict this assumption.) Following the GAO framework, the results of the updated models

are presented for each institutional type and each time period, including the following statistics:

multiple and adjusted R-squared; model probability; the number of valid cases; Pearson’s correlation coefficients of each independent variable with the dependent variable; regression coefficients for each independent variable; the incremental change in multiple R-squared for each

independent variable; and the probability of the t statistic for each independent variable.26 Independent variables are identified as “important” if the decline in the portion of variation accounted

for (R-squared) by omitting the variable from the model was 10 percentage points or greater.27

(See Appendix A for details on missing data procedures, FTE calculations, explanation of statistical terms, and other technical notes.)

 

23Data for 1997–98 were used to define and measure all of these selection criteria.

24The original number of public 4- and 2-year institutions in the IPEDS dataset in 1997–98 was 1,921. The various criteria and

data cleaning procedures eliminated 686 institutions, or 36 percent of the total. However, the institutions remaining in the panels

comprised 84 percent of undergraduate enrollment at all public 4-year institutions and 81 percent at all 2-year institutions in

1997–98. Selection criteria are comparable to those used in most contemporary studies of higher education costs and prices. See

Appendix A for details on how many institutions were eliminated at each step, as well as bias analyses of the differences in the

characteristics of institutions included in and excluded from the final universes.

25Because IPEDS revenue and expenditure data cannot be broken down by level of student, per FTE variables were calculated

using total FTE rather than undergraduate FTE. It is important to note that matching these variables with undergraduate tuition

levels is not ideal. Nevertheless, this study was limited to the use of available data. Attempts were made to address this issue, by

limiting the universe of institutions to those with primarily undergraduate enrollment and by adding a variable to the model to

reflect the proportion of graduate students at public 4-year institutions. In addition, the measure of FTE students captures only

enrollment for credit, while revenue and expenditure categories may capture both credit and non-credit activity. This issue is

most likely to be relevant for public 2-year institutions.

26Note that because the population is a census, some of these statistics are displayed not to measure significance, but rather to

gauge the explanatory power of the model as a whole (model probability) or the strength of the relationships between the independent variables and the dependent variable (probability of the t statistic).

27When independent variables are highly correlated with each other, the usefulness of assessing the importance of a variable by

deleting it from the model is limited because it is difficult to distinguish their independent contribution to the portion of variation

accounted for; therefore, in cases in which bivariate correlations are 0.7 or greater, the correlation is noted and the R-squared

change when both variables are deleted from the model is provided.
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

29

Trends in Enrollment, Tuition, Revenues, and Expenditures

The results of the trend analysis for public institutions reveal patterns for each institutional

type. Average amounts and percentage changes are reported on an inflation-adjusted basis wherever applicable.

Public Research/Doctoral Institutions

The sub-group of 135 public research/doctoral institutions comprised 16.9 percent of undergraduate enrollment at all public and private not-for-profit institutions in fall 1997. Over the

period between 1988–89 and 1997–98, in-state undergraduate tuition at public research/doctoral

institutions increased on average by about $1,068 in constant 1999 dollars, or by 4.1 percent annually. The average annual rate of increase in in-state undergraduate tuition was highest over the

period 1990–91 to 1994–95 at 6.3 percent, and lowest (2.2 percent) over the most recent subperiod, 1994–95 to 1997–98 (table 4). Neither total headcount fall enrollment nor FTE first-time

enrollment at this group of institutions changed over the period, while FTE fall enrollment did

increase slightly, by 0.4 percent annually (table 5).

Tuition revenue made up a substantial proportion of total E&G revenue at research/doctoral

institutions, 21.9 percent on average, and it grew at one of the highest rates of average annual increase among the various sources of revenue, at 4.4 percent. In comparison, total E&G revenue

increased annually by 1.5 percent. Over the period 1988–89 to 1997–98, tuition revenue per FTE

student increased on average by $1,682 in constant 1999 dollars, while E&G revenue per FTE

increased by $2,686. Another important source of revenue for research/doctoral institutions was

federal grants and contracts revenue, which made up 16.9 percent of total E&G revenue on average and increased annually by 2.3 percent. Nevertheless, research/doctoral institutions continued

to rely more on revenue from state appropriations than on tuition revenue or federal grants and

contracts; state appropriations revenue made up 42.6 percent of total E&G revenues on average.

Despite this fact, state appropriations revenue at research/doctoral institutions decreased annually

by about 1 percent in real dollars during this period.

As a result of the differing rates of change of various revenue categories, the composition

of E&G revenue at research/doctoral institutions changed over the period. For example, on average tuition revenue accounted for 18.4 percent of E&G revenue in 1988–89, but tuition revenue

grew to 23.8 percent of the total in 1997–98, an increase of 5.4 percentage points. Conversely,

the proportion of revenue from state appropriations decreased by 9.8 points, from 48.7 percent to

38.9 percent of the total, over the same time period (table 6).
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

30

Table 5.—Average change in price, enrollment, revenue, and expenditures at public research/doctoral 

Table 5.—institutions: 1988–89 to1997–98 

Proportion of

Average Proportion of total E&G

change, in Average annual total revenues/ revenues/

constant 1999 percentage expenditures, expenditures,

dollars change on average on average

In-state undergraduate tuition for FY, FT students $1,068 4.1 — —

In-state graduate tuition 1,285 4.3 — —

Out-of-state undergraduate tuition 3,238 4.6 — —

Total fall enrollment — 0.0* — —

FTE fall enrollment — 0.4 — —

FTE first time enrollment — 0.0* — —

Revenue (per FTE) by source:

 Tuition 1,682 4.4 17.2 21.9 

 Federal appropriations -50 -2.9 0.7 0.9 

 State appropriations -825 -1.0 33.4 42.6 

 Local appropriations 1 2.4 0.1 0.1 

 Federal grants and contracts 677 2.3 13.2 16.9 

 State grants and contracts 184 3.9 2.1 2.7 

 Local grants and contracts 20 5.6 0.3 0.4 

 Private gifts, grants, and contracts 508 4.2 5.2 6.7 

 Endowment income 31 2.4 0.6 0.8 

 Sales and services of educational activities 199 2.9 3.1 3.9 

 Other 262 4.4 2.5 3.2 

 Auxiliary enterprises 478 2.0 10.5 —

 Hospital 389 1.8 10.9 —

 Independent operations -22 -2.9 0.2 —

 Total revenue 3,568 1.6 100.0 —

 E&G revenue 2,686 1.5 — 100.0 

Expenditures (per FTE) by function:

 Instruction 615 1.0 28.0 35.6 

 Research 643 1.9 14.9 19.0 

 Public service 283 2.4 5.2 6.6 

 Academic support 283 1.7 7.3 9.3 

 Student services 132 1.7 3.3 4.2 

 Institutional support 150 1.1 6.0 7.7 

 Plant operations/maintenance -41 -0.3 5.7 7.3 

 Scholarships and fellowships 544 4.5 5.4 6.9 

 Mandatory transfers 118 4.3 1.3 1.6 

 Nonmandatory transfers 102 4.9 1.4 1.8 

 Auxiliary enterprises 457 1.9 10.7 —

 Hospital 331 1.5 10.6 —

 Independent operations -17 -2.6 0.2 —

 Total expenditures 3,602 1.6 100.0 —

 Total E&G 2,818 1.2 — 100.0 

 Institutional scholarships and fellowships 290 8.1 — —

N = 135

— Not applicable.

*Value rounds to less than .1 percent.

NOTE: Percentages may not sum to 100 due to rounding. Dollar amounts were converted to constant 1999 dollars using the CPI-U 

(1982–84 = 100) before annual changes were calculated. Average percentage changes were calculated as averages of the annual

changes. All revenue and expenditure categories are per full-time equivalent (FTE) student. Shares of total revenues and expenditures

were calculated as averages over the ten-year period.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System

(IPEDS), Full Collection Years 1989 to 1998.
Table 6.—Percentage composition of E&G revenue and expenditure at public research/doctoral institutions, on average: 1988–

1988–89 1989–90 1990–91 1991–92 1992–93 1993–94 1994–95 1995–9

Tuition 18.4 19.0 19.9 21.3 22.6 23.1 23.2 23.7 Federal appropriations 1.1 1.0 1.0 1.0 0.9 0.9 0.9 0.8 State appropriations 48.7 47.4 45.9 43.4 41.4 40.8 40.5 39.5 Local appropriations 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Federal grants and contracts 15.6 16.0 16.1 17.1 17.7 17.6 17.5 17.3 State grants and contracts 2.4 2.4 2.6 2.5 2.6 2.7 2.9 3.0 Local grants and contracts 0.3 0.4 0.4 0.4 0.4 0.4 0.4 0.4 Private gifts, grants, and contracts 5.9 6.3 6.5 6.6 6.7 6.6 6.5 6.7 Endowment income 0.9 0.9 0.8 0.7 0.8 0.7 0.7 0.8 Sales and services of educational activities 3.6 3.7 3.8 4.1 4.0 3.9 4.0 4.0 Other 3.0 2.7 2.9 2.8 2.8 3.1 3.3 3.6  E&G revenue 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Instruction 36.6 36.4 36.5 35.7 35.7 35.5 35.5 34.9 Research 18.4 18.6 19.0 19.0 19.2 19.5 19.4 19.1 Public service 6.4 6.4 6.6 6.7 6.6 6.6 6.6 6.8 Academic support 9.3 9.4 9.2 9.1 9.1 9.2 9.2 9.4 Student services 4.2 4.2 4.2 4.1 4.2 4.2 4.2 4.2 Institutional support 8.0 7.9 7.7 7.5 7.4 7.5 7.4 7.8 Plant operations/maintenance 8.0 7.8 7.6 7.3 7.1 7.2 7.0 6.9 Scholarships and fellowships 5.9 6.0 6.2 6.8 7.3 7.1 7.2 7.4 Mandatory transfers 1.4 1.4 1.5 1.6 1.8 1.6 1.7 1.7 Nonmandatory transfers 1.8 1.8 1.5 2.2 1.6 1.8 1.7 1.9  E&G expenditure 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 

N = 135NOTE: Percentages may not sum to 100 due to rounding. Dollar amounts were converted to constant 1999 dollars using the CPI-U (1982–84 = 100) 

shares were calculated. All revenue and expenditure categories are per full-time equivalent (FTE) student. SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Full Cto 1998.
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

32

Instruction expenditures, which primarily consist of spending on faculty salaries and benefits, represented the largest proportion of total E&G expenditures at research/doctoral institutions, 35.6 percent on average, followed by externally funded research expenditures at 19.0

percent. Instruction expenditures increased at a slightly slower annual rate than did E&G expenditures as a whole, 1.0 percent in real dollars, compared to 1.2 percent on average. The expenditure category of scholarships and fellowships—specifically, institutional scholarships and

fellowships—was one of the fastest growing categories. Institutional scholarships and fellowships increased annually by 8.1 percent, with an increase of $290 per FTE student in constant

1999 dollars over the whole period (table 5). Within this pattern of change, the composition of

E&G expenditure at research/doctoral institutions also shifted between 1988–89 and 1997–98.

On average, instruction expenditures as a percentage of total E&G expenditures decreased by 1.9

percentage points, from 36.6 percent to 34.7 percent. Meanwhile, scholarships and fellowships as

a proportion of total E&G expenditures increased by 1.8 percentage points, from 5.9 percent to

7.7 percent of the total (table 6).

Public Comprehensive Institutions

The sub-group of 221 public comprehensive institutions comprised 13 percent of undergraduate enrollment at all public and private not-for-profit institutions in fall 1997. Over the period 1988–89 to 1997–98, in-state undergraduate tuition at comprehensive institutions increased

by 4.2 percent annually, with the highest rate of increase over the period 1990–91 to 1994–95 at

6.3 percent, and lowest (2.4 percent) over the first sub-period, 1988–89 to 1990–91 (table 4). At

the same time, both total headcount and FTE fall enrollment at these schools increased by

slightly less than 1 percent annually, whereas FTE first-time enrollment decreased on average by

0.6 percent annually (table 7).

On average, tuition revenue made up 28.3 percent of total E&G revenue at comprehensive

institutions, with an average inflation-adjusted annual increase of 4.8 percent. In comparison, total E&G revenue increased annually by 1.2 percent in real dollars. These schools continued to

rely more on revenue from state appropriations than on tuition revenue, with state appropriations

revenue making up over half of total E&G revenues. Nonetheless, state appropriations revenue

decreased annually by about 1.2 percent in real dollars during this period. Revenue from federal

grants and contracts constituted the third largest proportion of E&G revenue at comprehensive

institutions, on average 10.8 percent (table 7).

The composition of E&G revenue at comprehensive institutions changed over the period

1988–89 to 1997–98, particularly as a result of the rates of change in tuition and state appropriations revenue. On average, tuition revenue accounted for 22.7 percent of E&G revenue in
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

33

Table 7.—Average change in price, enrollment, revenue, and expenditures at public comprehensive

Table 7.—institutions: 1988–89 to 1997–98

Proportion of

Average Proportion of total E&G

change, in Average annual total revenues/ revenues/

constant 1999 percentage expenditures, expenditures,

dollars change on average on average

In-state undergraduate tuition for FY, FT students $906 4.2 — —

In-state graduate tuition 1,053 4.5 — —

Out-of-state undergraduate tuition 2,554 4.6 — —

Total fall enrollment — 0.6 — —

FTE fall enrollment — 0.7 — —

FTE first time enrollment — -0.6 — —

Revenue (per FTE) by source:

 Tuition 1,245 4.8 24.5 28.3 

 Federal appropriations 20 17.5 0.2 0.2 

 State appropriations -653 -1.2 44.1 50.9 

 Local appropriations -10 -5.8 0.1 0.2 

 Federal grants and contracts 197 1.9 9.4 10.8 

 State grants and contracts 167 6.3 2.6 3.0 

 Local grants and contracts -3 -1.0 0.2 0.2 

 Private gifts, grants, and contracts 94 4.9 1.8 2.1 

 Endowment income 11 5.0 0.2 0.3 

 Sales and services of educational activities 49 3.4 1.5 1.7 

 Other 42 2.1 2.0 2.3 

 Auxiliary enterprises 169 1.1 13.4 —

 Hospital 0 0.0 0.0 —

 Independent operations 0* 0.9 0.1 —

 Total revenue 1,300 1.2 100.0 —

 E&G revenue 1,159 1.2 — 100.0 

Expenditures (per FTE) by function:

 Instruction 240 0.6 36.3 42.1 

 Research 79 3.2 2.3 2.6 

 Public service 112 4.0 2.6 3.1 

 Academic support 152 1.8 7.8 9.1 

 Student services 178 2.5 6.5 7.5 

 Institutional support 107 1.0 10.3 12.0 

 Plant operations/maintenance -57 -0.6 8.1 9.4 

 Scholarships and fellowships 377 3.6 9.5 11.0 

 Mandatory transfers 15 1.3 1.5 1.7 

 Nonmandatory transfers 23 8.3 1.2 1.4 

 Auxiliary enterprises 153 1.0 13.8 —

 Hospital 0 0.0 0.0 —

 Independent operations -4 0.6 0.1 —

 Total expenditures 1,374 1.3 100.0 —

 Total E&G 1,239 0.9 — 100.0 

 Institutional scholarships and fellowships 154 7.7 — —

N = 221

— Not applicable.

* Value rounds to less than $1.

NOTE: Percentages may not sum to 100 due to rounding. Dollar amounts were converted to constant 1999 dollars using the CPI-U 

(1982–84 = 100) before annual changes were calculated. Average percentage changes were calculated as averages of the annual 

changes. All revenue and expenditure categories are per full-time equivalent (FTE) student. Shares of total revenues and expenditures

were calculated as averages over the ten-year period.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System 

(IPEDS), Full Collection Years 1989 to 1998.
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

34

1988–89 but grew to 31.1 percent of the total in 1997–98, an increase of 8.4 percentage points.

The proportion of revenue from sources such as federal and state grants and contracts and private

gifts, grants, and contracts also increased slightly. At the same time, revenue from state appropriations decreased from 58.4 percent to 47.0 percent of the total, a decrease of 11.4 percentage

points (table 8).

On the expenditure side, instruction expenditures constituted the largest proportion of total

E&G spending at comprehensive institutions, 42.1 percent on average, followed by expenditures

for institutional support (12.0 percent) and expenditures for scholarships and fellowships (11.0

percent). Scholarships and fellowships—specifically, institutional scholarships and fellowships—was one of the fastest growing expenditure categories; institutional scholarships and fellowships increased annually by 7.7 percent, with an increase of $154 per FTE student in constant

1999 dollars over the period (table 7). Given these differences, the composition of E&G expenditures also changed: in particular, instruction expenditures decreased by 2.5 percentage points,

and plant operations and maintenance expenditures fell by 1.6 points. Expenditures for scholarships and fellowships as a proportion of the total increased by 2.2 percentage points (table 8).

Public Bachelor’s Institutions

The sub-group of 66 public bachelor’s institutions comprised 1.6 percent of undergraduate

enrollment at all public and private not-for-profit institutions in fall 1997. At public bachelor’s

institutions, in-state undergraduate tuition increased by about $953 in constant 1999 dollars over

the period 1988–89 to 1997–98 and increased annually by 4.3 percent on average. As at the other

groups of institutions, the average annual rate of increase in tuition was highest over the period

1990–91 to 1994–95, at 5.3 percent; the rate was lowest (3.5 percent) over the most recent subperiod, 1994–95 to 1997–98 (table 4). Enrollment at these schools increased over the period

1988–89 to 1997–98, with total headcount and FTE fall enrollment increasing annually by

slightly more than 1 percent and FTE first-time enrollment increasing at a slightly lower average

rate, 0.6 percent (table 9).

Bachelor’s institutions continued to rely more on revenue from state appropriations than on

tuition revenue, with state appropriations revenue making up 47.1 percent of total E&G revenues

on average. However, state appropriations revenue was flat over the period 1988–89 to 1997–98.

Tuition revenue, on the other hand, made up a smaller percentage of total E&G revenue on average (28.9 percent) but had the second highest rate of average annual increase among the various

sources of revenue, at 4.9 percent in real dollars (private gifts, grants, and contracts had the highest rate of annual increase, 8.8 percent, but made up only 2.5 percent of E&G revenue on
Table 8.—Percentage composition of E&G revenue and expenditure at public comprehensive institutions, on average: 1988–89 

1988–89 1989–90 1990–91 1991–92 1992–93 1993–94 1994–95 1995–9

Tuition 22.7 24.0 25.5 27.5 29.7 30.4 30.2 31.0 Federal appropriations 0.2 0.2 0.2 0.1 0.2 0.3 0.3 0.2 State appropriations 58.4 56.8 54.7 52.0 48.9 48.7 48.5 47.1 Local appropriations 0.2 0.2 0.2 0.2 0.2 0.1 0.1 0.1 Federal grants and contracts 10.3 10.3 10.5 11.2 11.5 10.9 10.8 10.8 State grants and contracts 2.3 2.6 2.6 2.5 2.9 3.0 3.3 3.6 Local grants and contracts 0.2 0.3 0.2 0.2 0.2 0.2 0.2 0.2 Private gifts, grants, and contracts 1.7 1.7 1.9 2.1 2.1 2.1 2.3 2.3 Endowment income 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.2 Sales and services of educational activities 1.5 1.5 1.6 1.7 1.8 1.9 2.0 1.7 Other 2.3 2.2 2.3 2.1 2.3 2.1 2.2 2.5  E&G revenue 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Instruction 43.0 43.1 43.2 42.8 42.1 41.7 42.1 41.7 Research 2.4 2.5 2.5 2.7 2.5 2.5 2.7 2.7 Public service 2.7 2.8 3.0 3.1 3.1 3.1 3.3 3.1 Academic support 9.0 9.1 9.0 8.9 8.9 9.0 9.1 9.1 Student services 7.1 7.2 7.3 7.3 7.9 7.6 7.6 7.3 Institutional support 12.2 12.1 12.1 11.9 11.7 11.7 12.1 12.3 Plant operation/maintenance 10.4 10.0 9.8 9.4 9.3 9.3 9.1 9.2 Scholarships and fellowships 9.9 9.9 10.1 11.1 11.5 11.1 11.2 11.6 Mandatory transfers 1.9 1.9 1.6 1.6 1.7 1.5 1.8 1.7 Nonmandatory transfers 1.4 1.5 1.4 1.2 1.2 2.4 1.2 1.2  E&G expenditure 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 

N = 221NOTE: Percentages may not sum to 100 due to rounding. Dollar amounts were converted to constant 1999 dollars using the CPI-U (1982–84 = 100shares were calculated. All revenue and expenditure categories are per full-time equivalent (FTE) student. SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Full to 1998.
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

36

Table 9.—Average change in price, enrollment, revenue, and expenditures at public bachelor's institutions: 

Table 9.—1988–89 to 1997–98 

Proportion of

Average Average Proportion of total E&G

change, in annual total revenues/ revenues/

constant 1999 percentage expenditures, expenditures,

dollars change on average on average

In-state undergraduate tuition for FY, FT students $953 4.3 — —

In-state graduate tuition 887 3.6 — —

Out-of-state undergraduate tuition 2,631 5.0 — —

Total fall enrollment — 1.2 — —

FTE fall enrollment — 1.3 — —

FTE first time enrollment — 0.6 — —

Revenue (per FTE) by source:

 Tuition 1,193 4.9 24.9 28.9 

 Federal appropriations -3 0.1 0.2 0.2 

 State appropriations -62 0.0* 40.5 47.1 

 Local appropriations -170 -19.5 0.6 0.7 

 Federal grants and contracts 50 0.5 11.2 13.0 

 State grants and contracts 96 3.5 2.8 3.3 

 Local grants and contracts -4 -1.7 0.1 0.2 

 Private gifts, grants, and contracts 173 8.8 2.1 2.5 

 Endowment income -4 -0.6 0.4 0.4 

 Sales and services of educational activities 36 3.1 1.3 1.5 

 Other 34 2.1 1.9 2.2 

 Auxiliary enterprises 119 0.8 14.2 —

 Hospital 0 0.0 0.0 —

 Independent operations 0 0.0 0.0 —

 Total revenue 1,485 1.4 100.0 —

 E&G revenue 1,338 1.5 — 100.0 

Expenditures (per FTE) by function:

 Instruction 378 1.1 32.8 38.5 

 Research 12 1.4 1.1 1.2 

 Public service 141 4.7 2.9 3.4 

 Academic support 148 2.0 7.3 8.6 

 Student services 215 2.8 7.4 8.7 

 Institutional support 77 0.7 10.8 12.7 

 Plant operations/maintenance 6 0.1 8.6 10.0 

 Scholarships and fellowships 298 2.5 12.1 14.2 

 Mandatory transfers 112 8.6 1.3 1.6 

 Nonmandatory transfers 20 13.0 0.9 1.1 

 Auxiliary enterprises 189 1.2 14.7 —

 Hospital 0 0.0 0.0 —

 Independent operations 0 0.0 0.0 —

 Total expenditures 1,597 1.6 100.0 —

 Total E&G 1,435 1.3 — 100.0 

 Institutional scholarships and fellowships 149 8.0 — —

N = 66

—Not applicable.

*Value rounds to less than .1 percent.

NOTE: Percentages may not sum to 100 due to rounding. Dollar amounts were converted to constant 1999 dollars using the CPI-U 

(1982–84 = 100) before annual changes were calculated. Average percentage changes were calculated as averages of the annual 

changes. All revenue and expenditure categories are per full-time equivalent (FTE) student. Shares of total revenues and expenditures 

were calculated as averages over the ten-year period.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System 

(IPEDS), Full Collection Years 1989 to 1998.
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

37

average). Revenue from federal grants and contracts constituted the third largest proportion of

E&G revenue at bachelor’s institutions, 13.0 percent on average (table 9).

These varying trends resulted in changes in the composition of E&G revenue at bachelor’s

institutions. As a proportion of E&G revenue, tuition revenue accounted for 23.4 percent in

1988–89 but increased to 31.5 percent of the total in 1997–98, a rise of 8.1 percentage points.

The proportion of revenue from private gifts, grants, and contracts increased slightly, by 1.3 percentage points. Conversely, revenue from state appropriations decreased by 6.9 percentage

points, and the proportion of revenue from federal grants and contracts also decreased slightly

(table 10).

Instruction expenditures constituted the largest proportion of total E&G expenditures at

bachelor’s institutions, 38.5 percent on average, but instruction expenditures increased at a

slightly slower inflation-adjusted annual rate than did E&G expenditures as a whole, 1.1 percent

compared to 1.3 percent. The next largest proportions of total expenditures were scholarships and

fellowships (14.2 percent), institutional support (12.7 percent), and expenditures for plant operations and maintenance (10.0 percent). Although institutional scholarships and fellowships increased annually by 8.0 percent, expenditures for institutional support and plant operations and

maintenance had average annual increases of less than 1 percent (table 9). These trends led to

shifts in the composition of E&G expenditures: on average, the proportion of instruction expenditures decreased by 1.6 percentage points, and the proportions of institutional support and plant

operations and maintenance expenditures also fell slightly. The proportion of expenditures for

scholarships and fellowships rose slightly, as did the proportions of student services expenditures

(table 10).

Public 2-year Institutions

The sub-group of 813 public 2-year institutions comprised 35.3 percent of undergraduate

enrollment at all public and private not-for-profit institutions in fall 1997. Over the period 1988–

89 to 1997–98, in-district undergraduate tuition at 2-year institutions increased by about 3.6 percent annually, while in-state undergraduate tuition increased by 3.4 percent annually. On average,

total headcount fall enrollment at 2-year institutions increased, by 1.4 percent annually, while

FTE fall enrollment increased by 1.1 percent annually. On the other hand, FTE first-time enrollment decreased on average by 1.9 percent annually (table 11).

Two-year institutions relied less on tuition revenue in comparison to 4-year institutions,

with tuition making up 19.9 percent of total E&G revenue on average. However, tuition revenue

had an annual rate of increase of 2.9 percent in real dollars, compared to total E&G revenue,
Table 10.—Percentage composition of E&G revenue and expenditure at public bachelor's institutions, on average: 1988–89 to 

1988–89 1989–90 1990–91 1991–92 1992–93 1993–94 1994–95 1995–9

Tuition 23.4 24.5 26.5 28.8 30.3 31.0 30.1 31.6 Federal appropriations 0.3 0.3 0.3 0.2 0.2 0.2 0.2 0.2 State appropriations 51.5 51.4 49.8 47.2 45.3 45.2 47.2 44.5 Local appropriations 2.0 1.7 1.1 0.7 0.6 0.5 0.2 0.2 Federal grants and contracts 13.4 13.4 13.2 13.8 13.8 13.0 12.5 12.3 State grants and contracts 3.2 2.7 2.8 2.8 3.1 3.5 3.4 3.8 Local grants and contracts 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.1 Private gifts, grants, and contracts 1.7 1.9 2.3 2.5 2.4 2.5 2.5 3.0 Endowment income 0.5 0.5 0.4 0.4 0.5 0.4 0.4 0.4 Sales and services of educational activities 1.4 1.3 1.2 1.4 1.5 1.6 1.4 1.5 Other 2.5 2.1 2.3 2.1 2.0 1.9 2.2 2.3  E&G revenue 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Instruction 39.2 39.0 38.7 38.6 38.3 38.1 39.1 38.7 Research 1.3 1.2 1.2 1.1 1.2 1.3 1.3 1.4 Public service 3.0 3.0 3.1 3.0 3.4 3.6 3.6 3.6 Academic support 8.3 8.7 8.7 8.6 8.5 8.5 8.6 8.6 Student services 8.3 8.3 8.4 9.0 8.4 8.6 9.0 9.2 Institutional support 13.3 13.3 13.4 13.0 12.2 12.6 12.3 12.3 Plant operation/maintenance 11.2 10.8 10.2 10.1 9.8 9.8 9.4 9.8 Scholarships and fellowships 13.4 13.8 13.9 14.6 15.3 14.3 14.1 13.5 Mandatory transfers 1.2 1.1 1.2 1.2 1.6 1.8 1.7 2.0 Nonmandatory transfers 0.8 0.8 1.2 0.6 1.3 1.4 0.9 1.0  E&G expenditure 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 

N = 66NOTE: Percentages may not sum to 100 due to rounding. Dollar amounts were converted to constant 1999 dollars using the CPI-U (1982–84 = 100) 

shares were calculated. All revenue and expenditure categories are per full-time equivalent (FTE) student. SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Full Cto 1998.
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

39

Table 11.—Average change in price, enrollment, revenue, and expenditures at public 2-year institutions: 

Table 11.—1988–89 to 1997–98 

Proportion of

Average Average Proportion of total E&G

change, in annual total revenues/ revenues/

constant 1999 percentage expenditures, expenditures,

dollars change on average on average

In-district undergraduate tuition for FY, FT students $396 3.6 — —

In-state undergraduate tuition for FY, FT students 479 3.4 — —

Out-of-state undergraduate tuition 1,154 3.4 — —

Total fall enrollment — 1.4 — —

FTE fall enrollment — 1.1 — —

FTE first time enrollment — -1.9 — —

Revenue (per FTE) by source:

 Tuition 436 2.9 18.7 19.9 

 Federal appropriations 4 4.5 0.6 0.6 

 State appropriations -570 -1.2 39.4 41.7 

 Local appropriations -517 -3.2 14.1 14.9 

 Federal grants and contracts 261 2.8 12.3 13.0 

 State grants and contracts 47 2.1 4.2 4.4 

 Local grants and contracts -13 -1.4 0.6 0.6 

 Private gifts, grants, and contracts -98 -2.4 1.1 1.1 

 Endowment income -7 -2.8 0.2 0.2 

 Sales and services of educational activities 16 3.8 0.6 0.6 

 Other -165 -3.6 2.8 3.0 

 Auxiliary enterprises -418 -4.5 6.6 —

 Hospital 0 0.0 0.0 —

 Independent operations -13 -7.5 0.2 —

 Total revenue -51 0.1 100.0 —

 E&G revenue -604 -0.4 — 100.0 

Expenditures (per FTE) by function:

 Instruction -444 -0.9 41.2 44.1 

 Research -7 -6.1 0.1 0.1 

 Public service -40 -1.4 2.2 2.3 

 Academic support 77 1.4 7.1 7.6 

 Student services 31 0.7 8.6 9.2 

 Institutional support -73 -0.3 13.4 14.3 

 Plant operations/maintenance -72 -0.8 8.8 9.5 

 Scholarships and fellowships 346 4.3 10.5 11.2 

 Mandatory transfers 10 2.9 0.5 0.6 

 Nonmandatory transfers 22 4.4 1.0 1.0 

 Auxiliary enterprises 12 0.3 6.3 —

 Hospital 0 0.0 0.0 —

 Independent operations -13 -6.9 0.2 —

 Total expenditures -151 0.4 100.0 —

 Total E&G 191 -1.2 — 100.0 

 Institutional scholarships and fellowships 107 6.8 — —

N = 813

— Not applicable.

NOTE: Percentages may not sum to 100 due to rounding. Dollar amounts were converted to constant 1999 dollars using the CPI-U 

(1982–84 = 100) before annual changes were calculated. Average percentage changes were calculated as averages of the annual 

changes. All revenue and expenditure categories are per full-time equivalent (FTE) student. Shares of total revenues and expenditures 

were calculated as averages over the ten-year period.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System 

(IPEDS), Full Collection Years 1989 to 1998.
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

40

which decreased annually by 0.4 percent. Two-year institutions continued to draw primarily on

revenue from state and local appropriations, which constituted 41.7 percent and 14.9 percent, respectively, of total E&G revenue. However, state and local appropriations revenue experienced

average annual decreases over the period of 1.2 percent and 3.2 percent, respectively. Federal and

state grants and contracts together made up 17.4 percent of total E&G revenue on average, and

experienced annual increases over the period (table 11).

As a result of these shifts, the composition of E&G revenue at 2-year institutions changed,

with tuition and federal grants and contracts revenue increasing in proportion to state and local

appropriations revenue. On average, tuition revenue accounted for 15.1 percent of E&G revenue

in 1988–89 but increased to 20.7 percent of the total in 1997–98, an increase of 5.6 percentage

points. Revenue from federal grants and contracts also increased as a proportion of E&G revenue, by 3.5 percentage points. Meanwhile, revenue from state and local appropriations decreased

by 3.2 and 4.4 percentage points, respectively (table 12).

Instruction expenditures constituted the largest proportion of total E&G expenditures at 2-

year institutions, 44.1 percent on average, followed by expenditures for institutional support

(14.3 percent), scholarships and fellowships (11.2 percent), expenditures for plant operations and

maintenance (9.5 percent), and student services expenditures (9.2 percent). Many of these expenditure categories experienced real annual decreases over the period 1988–89 to 1997–98, and

E&G expenditures as a whole decreased by about 1.2 percent annually. Instruction expenditures,

institutional support, and plant operations and maintenance had average annual decreases of

slightly less than 1 percent. Conversely, institutional scholarships and fellowships increased annually by 6.8 percent, with an increase of $107 per FTE student in constant 1999 dollars over the

period 1988–89 to 1997–98 (table 11). The composition of E&G expenditures also changed: on

average, instruction expenditures decreased by 4.0 percentage points, while the proportion of expenditures for scholarships and fellowships grew by 3.9 percentage points (table 12).

Model Results

The results of the regression modeling for public institutions highlight several major findings for each institutional type. In each set of findings, “important” independent variables are reported in decreasing order of the portion of variation they account for after controlling for other

factors.
Table 12.—Percentage composition of E&G revenue and expenditure at public 2-year institutions, on average: 1988–89 to 1997

1988–89 1989–90 1990–91 1991–92 1992–93 1993–94 1994–95 1995–9

Tuition 15.1 17.5 18.5 20.5 21.4 21.4 21.0 21.2 

Federal appropriations 0.7 0.8 0.7 0.6 0.6 0.6 0.4 0.4 State appropriations 44.3 44.0 44.0 41.6 40.4 40.1 40.0 40.0 Local appropriations 18.0 16.2 15.5 14.6 14.3 14.5 14.7 14.0 Federal grants and contracts 9.9 11.5 11.7 13.5 14.4 14.4 14.1 13.6 State grants and contracts 4.1 4.4 4.2 4.0 3.9 4.1 4.3 5.4 Local grants and contracts 0.7 0.7 0.6 0.6 0.6 0.6 0.5 0.6 Private gifts, grants, and contracts 2.1 0.9 0.9 0.9 1.0 0.9 1.1 1.1 Endowment income 0.2 0.3 0.3 0.3 0.2 0.2 0.2 0.2 Sales and services of educational activities 0.5 0.5 0.5 0.5 0.7 0.6 0.6 0.7 Other 4.3 3.2 3.0 2.8 2.5 2.6 3.0 2.8  E&G revenue 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Instruction 46.8 45.3 44.8 44.1 43.7 43.5 43.5 43.3 Research 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.1 Public service 2.7 2.3 2.4 2.3 2.4 2.2 2.2 2.2 Academic support 7.0 7.7 7.7 7.5 7.5 7.6 7.5 7.7 Student services 9.2 8.7 8.8 9.0 9.1 9.4 9.5 9.6 Institutional support 15.0 14.4 14.3 14.2 13.9 14.0 14.3 14.3 Plant operation/maintenance 9.6 10.1 9.9 9.6 9.3 9.3 9.3 9.5 Scholarships and fellowships 8.2 9.7 10.0 11.7 12.4 12.4 12.1 11.8 Mandatory transfers 0.5 0.6 0.5 0.4 0.5 0.5 0.5 0.6 Nonmandatory transfers 0.8 1.1 1.5 1.0 1.0 0.9 0.9 0.9  E&G expenditure 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 

N = 813NOTE: Percentages may not sum to 100 due to rounding. Dollar amounts were converted to constant 1999 dollars using the CPI-U (1982–84 = 100) 

calculated. All revenue and expenditure categories are per full-time equivalent (FTE) student. SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Full Cto 1998.
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

42

Public Research/Doctoral Institutions

Together, the 12 variables in the regression model accounted for almost 40 percent of the

variation in in-state undergraduate tuition at public research/doctoral institutions over the period

1988–89 to 1997–98 (table 13). The model had the strongest “explanatory” power in the 1990–91

to 1994–95 sub-period, during which time in-state undergraduate tuition was increasing the fastest. Over the whole period, the most “important” variable associated with the change in tuition

was:

• Change in revenue from government appropriations. Institutions that experienced the

greatest declines in appropriations (from all government sources) per FTE student typically had larger increases in tuition. This variable accounted for 19 percent of the

variation in the change in tuition, after accounting for the other independent variables.

The change in government appropriations also was an “important” variable in the subperiods 1988–89 to 1990–91 and 1990–91 to 1994–95.

Other independent variables accounted for lower proportions of the variation in in-state undergraduate tuition over the period 1988–89 to 1997–98:

• Change in non-student-related expenditures. In general, schools with greater increases

in public services, academic and institutional support, and plant operations and maintenance tended to have larger increases in in-state undergraduate tuition.28 This variable accounted for 4.5 percent of the variation in the change in tuition, after accounting

for the other independent variables.

• Change in instruction expenditures. Schools that had the largest increases in instruction expenditures tended to have greater increases in in-state undergraduate tuition.

This variable accounted for 4.5 percent of the variation in the change in tuition.

• Change in other student-related expenditures. Similar to non-student-related expenditures, schools with greater increases in expenditures for academic support, institutional

support, and plant operations and maintenance tended to have larger increases in instate undergraduate tuition. This variable accounted for 3.6 percent of the variation in

the change in tuition.

• Change in institutional scholarships and fellowships. In general, institutions with

larger increases in institutional aid had greater increases in in-state undergraduate tuition. This variable accounted for 3.4 percent of the variation in the change in tuition. In

the sub-period 1990–91 to 1994–95, the change in institutional scholarships and fellowships appeared particularly important, accounting for 10.6 percent of the variation

in the dependent variable.

 

28One should note that expenditures for such items as academic support and institutional support can be both student-related

and/or non-student-related; these expenditures were prorated based upon a simple formula in order to calculate the independent

variables. See Appendix A for details.
Table 13.—Coefficients for the regression of the change in in-state, full-time, full-year, undergraduate tuition on selected reven

Table 13.—variables for public research/doctoral institutions

Time periodMultiple R-squaredAdjusted R-squaredModel significanceN

Portion of 

variation 

Correlation accounted Correlation 

coefficient for after coefficient 

with controlling with 

change Regression for other change Regression 

in tuition coefficient factors Probability in tuition coefficient 

Constant — 415.584 — 0.007* — 42.499 

Level of in-state undergraduate tuition in base year 0.161 0.045 0.3 0.425 0.131 0.023 Change in instruction expenditures 0.087 0.161 4.5 0.004* 0.069 0.170 Change in research expenditures 0.184 0.104 1.2 0.124 0.116 0.195 Change in student services expenditures 0.089 0.484 2.4 0.032* -0.066 -0.141 Change in other student-related expenditures 0.041 0.209 3.6 0.009* -0.057 0.139 Change in non-student-related expenditures 0.123 0.164 4.5 0.004* -0.024 0.106 Change in philanthropic revenue 0.046 -0.155 2.7 0.024* 0.125 -0.107 Change in revenue from government appropriations -0.315 -0.241 19.0 0.000* -0.045 -0.148 Change in revenue from government grants and 0.238 -0.046 3.0 0.505 -0.043 -0.205  contractsChange in the amount by which E&G revenues exceed/fall short of E&G expenditures -0.300 0.068 0.8 0.209 0.198 0.177 Change in institutional scholarships and fellowships 0.238 0.349 3.4 0.011* 0.228 0.213 Change in ratio of graduate to total enrollment -0.064 -203.935 0.0 0.892 0.145 1267.869 

 0.000*

131

 0.0

13

0.329

1988–89 to 1997–98 

0.391

1988–89 to 

0.20.2
Table 13.—Coefficients for the regression of the change in in-state, full-time, full-year, undergraduate tuition on selected reven

Table 13.—variables for public research/doctoral institutions—Continued

Time periodMultiple R-squaredAdjusted R-squaredModel significanceN

Portion of 

variation 

Correlation accounted Correlation 

coefficient for after coefficient 

with controlling with 

change Regression for other change Regression 

in tuition coefficient factors Probability in tuition coefficient 

Constant — 318.860 — 0.014* — 308.055 

Level of in-state undergraduate tuition in base year 0.135 -0.013 0.0 0.783 -0.205 -0.056 Change in instruction expenditures -0.138 0.127 1.1 0.104 -0.134 0.053 Change in research expenditures 0.196 0.212 2.1 0.028* -0.120 0.014 Change in student services expenditures -0.035 -0.066 0.0 0.843 0.185 0.852 Change in other student-related expenditures 0.110 0.438 6.7 0.000* -0.069 0.099 Change in non-student-related expenditures 0.184 0.173 1.8 0.041* -0.024 0.060 Change in philanthropic revenue -0.002 -0.130 0.7 0.186 -0.096 -0.048 Change in revenue from government appropriations -0.370 -0.290 12.8 0.000* -0.216 -0.176 Change in revenue from government grants and 0.189 -0.127 1.7 0.149 0.076 0.023  contractsChange in the amount by which E&G revenues -0.036 0.196 3.4 0.005* 0.152 0.073  exceed/fall short of E&G expendituresChange in institutional scholarships and fellowships 0.539 0.872 10.6 0.000* 0.057 0.277 Change in ratio of graduate to total enrollment -0.070 -687.185 0.0 0.686 -0.128 -1008.624 

—Not applicable.*Relatively strong relationship.NOTE: In order to deal with outliers, one percentile was trimmed from the top and bottom of the variables for the change in government appropriatiochange in government grants and contracts. The model, in following the GAO framework, was not reduced, and therefore may be misspecified. Interpcoefficients should be more cautious than if the model had been reduced.SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Full Cto 1998.

131

1990–91 to 1994–95 

0.4970.446

 0.000*

13

0.2

1994–95 to 

0.1

 0.0
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

45

Public Comprehensive Institutions

Over the period 1988–89 to 1997–98, the 12 independent variables in the regression model

accounted for 42.4 percent of the variation in in-state undergraduate tuition at these schools. The

model had the strongest “explanatory” power in the 1990–91 to 1994–95 sub-period, which is

also the sub-period in which annual tuition increases were highest (table 14). The most important

independent variables over the period 1988–89 to 1997–98, in terms of their association with

changes in tuition, were the following:

• Change in revenue from government appropriations. After taking into account the

other independent variables, institutions that had the greatest declines in appropriations

per FTE student typically had larger increases in tuition. This variable accounted for

27.9 percent of the variation in the change in tuition, after accounting for the other independent variables. The change in revenue from government appropriations remained

an important variable in all three sub-periods.

• Change in revenue from government grants and contracts. Schools with larger increases in these types of revenue tended to have smaller increases in in-state undergraduate tuition. This variable accounted for 13.5 percent of the variation in the change

in tuition.

• Change in instruction expenditures. Schools that had larger increases in instruction expenditures tended to have greater increases in in-state undergraduate tuition. This variable accounted for 12.5 percent of the variation in the change in tuition. Nevertheless,

the change in instruction expenditures was not an important variable in any of the subperiods.

• Change in the amount by which E&G revenues exceeded/fell short of E&G expenditures. Institutions with larger decreases in the amount by which E&G revenues exceeded expenditures tended to have larger increases in in-state undergraduate tuition.

This variable accounted for 10.5 percent of the variation in the change in tuition. This

variable was important primarily for the first two sub-periods.

Other independent variables accounted for lower proportions of the variation in in-state undergraduate tuition, including:

• Change in non-student-related expenditures. In general, schools with greater increases

in these expenditures tended to have larger increases in undergraduate tuition. This

variable accounted for 8.3 percent of the variation in the change in tuition, after accounting for the other independent variables.

• Change in student services expenditures. Institutions that had greater increases in these

expenditures tended to have larger increases in in-state undergraduate tuition. This

variable accounted for 7.7 percent of the variation in the change in tuition.
Table 14.—Coefficients for the regression of the change in in-state, full-time, full-year, undergraduate tuition on selected reven

Table 14.—variables for public comprehensive institutions

Time periodMultiple R-squaredAdjusted R-squaredModel significanceNConstant — 256.345 — 0.009 * — 114.157 Level of in-state undergraduate tuition in base year 0.196 0.081 2.6 0.070 0.020 -0.021 Change in instruction expenditures 0.049 0.370 12.5 0.000 * -0.015 0.213 Change in research expenditures 0.068 0.160 0.6 0.147 0.038 0.236 Change in student services expenditures 0.252 0.639 7.7 0.000 * -0.109 0.088 Change in other student-related expenditures 0.067 0.204 3.4 0.001 * -0.208 0.093 Change in non-student-related expenditures 0.094 0.459 8.3 0.000 * -0.022 0.289 Change in philanthropic revenue 0.014 -0.477 3.6 0.001 * -0.092 -0.378 Change in revenue from government appropriations -0.215 -0.403 27.9 0.000 * -0.127 -0.209 Change in revenue from government grants and 0.064 -0.244 13.5 0.000 * -0.078 -0.252  contractsChange in the amount by which E&G revenues -0.040 0.321 10.5 0.000 * 0.200 0.234  exceed/fall short of E&G expendituresChange in institutional scholarships and fellowships 0.149 0.308 1.5 0.023 * 0.068 0.324 Change in ratio of graduate to total enrollment 0.004 1572.873 1.4 0.028 * 0.001 428.171 

2

Probability

213

Portion of 

variation 

accounted 

factors

1988–89 t

0.0.

 0.

1988–89 to 1997–98 

0.4240.390

 0.000*

change for other 

in tuition

Regression

coefficient

change

in tuition

Regression

coefficient

Correlation Correlation

coefficient

with

coefficient

with

for after 

controlling 
Table 14.—Coefficients for the regression of the change in in-state, full-time, full-year, undergraduate tuition on selected reven

Table 14.—variables for public comprehensive institutions—Continued

Time periodMultiple R-squaredAdjusted R-squaredModel significanceNConstant — 109.480 — 0.105 — 142.250 Level of in-state undergraduate tuition in base year 0.124 0.085 2.1 0.005 * 0.148 0.022 

Change in instruction expenditures 0.070 0.331 8.4 0.000 *a -0.160 0.166 

Change in research expenditures 0.031 0.611 7.9 0.000 * 0.052 0.088 Change in student services expenditures 0.300 0.440 4.1 0.000 * -0.083 0.210 Change in other student-related expenditures 0.296 0.481 24.3 0.000 * -0.152 0.055 Change in non-student-related expenditures 0.056 0.412 6.3 0.000 * 0.184 0.298 Change in philanthropic revenue -0.056 -0.657 11.7 0.000 * 0.048 -0.049 Change in revenue from government appropriations -0.057 -0.466 28.2 0.000 *a -0.355 -0.296 Change in revenue from government grants and -0.073 -0.423 8.4 0.000 * 0.073 -0.015  contractsChange in the amount by which E&G revenues -0.028 0.436 17.4 0.000 * 0.054 0.175  exceed/fall short of E&G expendituresChange in institutional scholarships and fellowships 0.073 0.118 0.1 0.440 0.053 0.175 Change in ratio of graduate to total enrollment -0.017 -163.038 0.0 0.763 -0.034 -973.378 

—Not applicable.*Relatively strong relationship.

aChange in government appropriations was correlated with change in instruction expenditures (r=.715). Removing both variables from the model decreased R 

points.

bFor this sub-period, deleting level of tuition in the base year as an independent variable actually increases the R squared rather than lessening it.

NOTE: In order to deal with outliers, one percentile was trimmed from the top and bottom of several variables: change in government appropriations, change icontracts, and level of undergraduate tuition in base year. The model, in following the GAO framework, was not reduced, and therefore may be misspecified. Icoefficients should be more cautious than if the model had been reduced.SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Full Collection 

1990–91 to 1994–95 

0.4980.468

in tuition

Regression

coefficient

 0.000*

Portion of 

variation 

accounted 

for after 

controlling 

for other 

factors in tuition Probability 

Regression

coefficient

210

1994–95 t

0.0.

 0.

2

Correlation

coefficient

with

change

Correlation

coefficient

with

change
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

48

• Change in philanthropic revenue. Schools with larger increases in revenue from endowment income and private gifts, grants, and contracts tended to have smaller increases in in-state undergraduate tuition, especially during the sub-period 1990–91 to

1994–95. This variable accounted for 3.6 percent of the variation in the change in tuition.

• Change in other student-related expenditures. Similarly to non-student-related expenditures, schools with greater increases in expenditures for academic support, institutional support, and plant operations and maintenance tended to have larger increases in

in-state undergraduate tuition. This variable accounted for 3.4 percent of the variation

in the change in tuition.

Public Bachelor’s Institutions

Despite the relatively small number of institutions in this group, the 12 variables in the regression model accounted for over 60 percent of the variation in in-state undergraduate tuition

over the period 1988–89 to 1997–98. The model had the strongest “explanatory” power in the

1990–91 to 1994–95 sub-period, but did not fit well in the 1988–89 to 1990–91 sub-period29 (table 15). The most important independent variables over the whole period, in terms of their association with changes in tuition, were the following:

• Change in revenue from government appropriations. After taking into account the

other variables, institutions that had the greatest declines in appropriations per FTE

student typically had larger increases in tuition. This variable accounted for 23.1 percent of the variation in the change in tuition, after accounting for the other independent

variables. The change in revenue from government appropriations was particularly important in the last two sub-periods.

• Change in instruction expenditures. Schools that had greater increases in instruction

expenditures tended to have larger increases in in-state undergraduate tuition. This

variable accounted for 18.7 percent of the variation in the change in tuition.

• Change in the amount by which E&G revenues exceeded/fell short of E&G expenditures. Bachelor’s institutions with larger decreases in the amount by which E&G revenues exceeded expenditures tended to have larger increases in in-state undergraduate

tuition. This variable accounted for 18 percent of the variation in the change in tuition.

• Change in non-student-related expenditures. Schools with larger increases in these expenditures tended to have greater increases in in-state undergraduate tuition. This variable accounted for 10.2 percent of the variation in the change in tuition.

 

29This group of institutions had the lowest number of cases (66), which may have caused some problems for the modeling procedures. Some influential outliers remained but could not be removed without reducing the number of cases further.
Table 15.—Coefficients for the regression of the change in in-state, full-time, full-year, undergraduate tuition on selected reven

Table 15.—variables for public bachelor's institutions

Time periodMultiple R-squaredAdjusted R-squaredModel significanceNConstant — 329.513 — 0.007 * — 200.075 Level of in-state undergraduate tuition in base year 0.365 0.100 3.6 0.040 * -0.043 -0.022 Change in instruction expenditures 0.134 0.380 18.7 0.000 * 0.160 0.104 Change in research expenditures 0.107 -0.081 0.1 0.654 -0.013 0.115 Change in student services expenditures 0.011 0.160 0.4 0.446 0.148 0.227 Change in other student-related expenditures 0.053 0.187 4.1 0.029 * 0.207 0.139 Change in non-student-related expenditures 0.085 0.464 10.2 0.001 * 0.091 0.128 Change in philanthropic revenue 0.444 0.408 6.8 0.006 * a 0.214 0.054 

Change in revenue from government appropriations -0.167 -0.380 23.1 0.000 * 0.225 -0.080 Change in revenue from government grants and -0.260 -0.259 7.6 0.004 * 0.080 -0.075  contractsChange in the amount by which E&G revenues exceed/ 0.055 0.337 18.0 0.004 * 0.149 0.150  fall short of E&G expendituresChange in institutional scholarships and fellowships 0.331 -0.406 4.4 0.024 * a 0.059 0.068 Change in ratio of graduate to total enrollment -0.182 -1670.457 0.5 0.413 0.045 67.392 

1988–89 to 1997–98 

0.613

Regression 

coefficient

controlling 

for other 

Correlation

coefficient

with change

in tuition

Portion of 

variation 

accounted 

for after 

factors 

1988–89 t

0.

-0.

0.

6

Correlation

coefficient

with change

Probability 

Regression 

in tuition coefficient

0.515

0.000*

60
Table 15.—Coefficients for the regression of the change in in-state, full-time, full-year, undergraduate tuition on selected reven

Table 15.—variables for public bachelor's institutions—Continued

Time periodMultiple R-squaredAdjusted R-squaredModel significanceNConstant — 65.646 — 0.536 — 357.757 Level of in-state undergraduate tuition in base year 0.333 0.146 9.4 0.002 * 0.139 -0.065 Change in instruction expenditures 0.258 0.130 1.8 0.163 -0.165 0.062 Change in research expenditures -0.153 0.317 1.0 0.306 -0.157 0.077 Change in student services expenditures 0.172 -0.134 0.3 0.577 0.021 0.133 Change in other student-related expenditures 0.489 0.515 34.2 0.000 * 0.199 0.209 Change in non-student-related expenditures 0.023 -0.007 0.0 0.953 0.334 0.239 Change in philanthropic revenue -0.007 -0.177 2.0 0.147 0.130 0.194 Change in revenue from government appropriations 0.227 -0.229 10.7 0.002 * -0.147 -0.205 Change in revenue from government grants and -0.047 -0.077 0.4 0.504 -0.250 -0.239 contractsChange in the amount by which E&G revenues exceed/ 0.106 0.201 6.3 0.011 * -0.111 0.155 fall short of E&G expendituresChange in institutional scholarships and fellowships 0.008 -0.150 0.3 0.578 0.165 0.290 Change in ratio of graduate to total enrollment -0.236 -3130.482 4.4 0.032 * 0.095 3154.084 

—Not applicable.*Relatively strong relationship.

aChange in institutional aid was correlated with change in philanthropic revenue (r = .752). Removing both variables from the model decreased R squared by 6

points.

bChange in government appropriations was correlated with change in amount by which E&G revenue exceeded/fell short of E&G expenditures (r = .744). Rem

model decreased R squared by 17.8 percentage points.NOTE: In order to deal with outliers, two percentiles were trimmed from the top and bottom of several variables: change in government appropriations, changrevenues exceed/fall short of E&G expenditures, and change in undergraduate tuition. The model, in following the GAO framework, was not reduced, and therInterpretation of the regression coefficients should be more cautious than if the model had been reduced.SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Full Collection 

0.000*

Correlation

coefficient

with change

Portion of 

variation 

accounted 

61

0.5690.461

in tuition Probability

Regression 

coefficient

for other 

factors 

coefficient

Regression 

Correlation

coefficient

with change

controlling 

for after 

in tuition

1990–91 to 1994–95 1994–95 t

0.0.

0.0

6
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

51

Other variables accounted for lower proportions of the variation in in-state undergraduate

tuition:

• Change in revenue from government grants and contracts. Schools with larger increases in these revenues tended to have smaller increases in in-state undergraduate

tuition. This variable accounted for 7.6 percent of the variation in the change in tuition,

after accounting for the other independent variables.

• Change in philanthropic revenue. Schools that had larger increases in endowment income and private gifts, grants, and contracts tended to have smaller increases in instate undergraduate tuition. This variable accounted for 6.8 percent of the variation in

the change in tuition.

• Change in institutional scholarships and fellowships. Contrary to the expected direction, institutions with smaller increases in institutional aid appeared to have greater increases in in-state undergraduate tuition.30 This variable accounted for 4.4 percent of

the variation in the change in tuition, after accounting for the other independent variables.

• Change in other student-related expenditures. Like non-student-related expenditures,

bachelor’s institutions with greater increases in expenditures for academic support, institutional support, and plant operations and maintenance tended to have larger increases in in-state undergraduate tuition. This variable accounted for 4.1 percent of the

variation in the change in tuition. The change in other student-related expenditures became an important variable during the 1990–91 to 1994–95 sub-period, accounting for

34.2 percent of the variance.

Public 2-year Institutions

When the regression model was applied to 2-year institutions, the 11 independent variables

(the graduate enrollment measure was not included) accounted for only 7.3 percent of the variation in in-district undergraduate tuition over the period 1988–89 to 1997–98. As with the other

groups of institutions, the model had the strongest “explanatory” power in the 1990–91 to 1994–

95 sub-period, during which time tuition was increasing the fastest (table 16). In general, however, the variables in the model left most of the variation in tuition changes unexplained. Although some of the independent variables had relationships with the change in tuition, the

associations were relatively small. Similar findings characterized the analyses of the three subperiods, where generally the proportions of the variation explained were low. This group of institutions had the largest number of cases, allowing factors to have a relationship with the dependent variable yet at the same time account for small proportions of the variance. Variables

 

30It appears that institutional aid is acting as a suppressor variable, i.e., a variable that changes the prediction value of another

variable (or set of variables) by its inclusion in the regression equation. This could have resulted from a disordinal interaction

effect (in which the direction of a relationship between two variables is different depending on the value of some other variable),

it could be a statistical artifact of the sample, or the model could be misspecified.
Table 16.—Coefficients for the regression of the change in in-district, full-time, full-year, undergraduate tuition on selected revenu

Table 16.—variables for public 2-year institutions

Time periodMultiple R-squaredAdjusted R-squaredModel significanceN Constant — 274.308 — 0.000 * — 87.667 

 Level of in-district undergraduate tuition in base 0.152 0.058 1.2 0.003 * -0.157 -0.050  year Change in instruction expenditures -0.036 0.036 1.5 0.009 * b -0.053 0.048 

 Change in research expenditures -0.104 -0.438 0.4 0.087 0.012 0.077  Change in student services expenditures 0.051 0.140 2.0 0.000 * 0.010 0.081  Change in other student-related expenditures -0.028 0.037 a 0.032 * -0.044 0.052 

 Change in non-student-related expenditures 0.028 0.060 a 0.066 -0.035 0.056 

 Change in philanthropic revenue 0.065 0.160 0.4 0.056 -0.005 -0.028  Change in revenue from government appropriations -0.111 -0.063 2.8 0.000 * b -0.073 -0.084 

 Change in revenue from government grants and -0.015 -0.048 1.9 0.019 * -0.030 -0.055  contracts Change in the amount by which E&G revenues -0.011 0.033 0.8 0.090 0.120 0.095  exceed/fall short of E&G expenditures Change in institutional scholarships and fellowships 0.029 0.081 0.2 0.237 0.065 0.336 

Regression Regression 

coefficient

for other 

factors Probability

Portion of 

variation 

accounted 

for after 

ontrolling 

Correlation

coefficient

with change

in tuition

1988–89 to 1997–98 

736

 0.000 *

0.0730.058

740

coefficient 

with change

in tuition

P

1988–89 to 1

0.0770.063

 0.000 

Correlation

coefficient 

a
Table 16.—Coefficients for the regression of the change in in-district, full-time, full-year, undergraduate tuition on selected revenu

Table 16.—variables for public 2-year institutions—Continued

Time periodMultiple R-squaredAdjusted R-squaredModel significanceN Constant — 148.61 — 0.000 * — 61.899  Level of in-district undergraduate tuition in base 0.198 0.052 1.7 0.000 * 0.094 0.020  year Change in instruction expenditures 0.074 0.123 4.4 0.000 * e -0.090 0.026 

 Change in research expenditures 0.044 0.284 0.3 0.108 -0.065 -0.230  Change in student services expenditures 0.084 0.142 1.2 0.001 * -0.069 0.012  Change in other student-related expenditures 0.124 0.148 5.4 0.000 * e -0.043 0.042 

 Change in non-student-related expenditures 0.107 0.239 3.7 0.000 * -0.027 0.032  Change in philanthropic revenue 0.065 -0.025 d 0.767 -0.033 -0.099 

 Change in revenue from government appropriations 0.024 -0.165 6.8 0.000 * e -0.132 -0.048 

 Change in revenue from government grants and 0.067 -0.114 3.1 0.000 * -0.084 -0.058  contracts

Regression 

Probability coefficient

for other 

factors

Pa

variation 

accounted 

for after 

Portion of 

1990–91 to 1994–95 

Regression 

0.143

743

 0.000 

729

0.032

coefficient

ontrolling 

 0.000 *

0.130

Correlation

1994–95 to 1

0.047

Correlation

in tuition

coefficient

with change

in tuition 

coefficient

with change
Table 16.—Coefficients for the regression of the change in in-district, full-time, full-year, undergraduate tuition on selected revenu

Table 16.—variables for public 2-year institutions—Continued

Time periodMultiple R-squaredAdjusted R-squaredModel significanceN Change in the amount by which E&G revenues 0.011 0.149 5.3 0.000 * -0.050 0.019  exceed/fall short of E&G expenditures Change in institutional scholarships and fellowships 0.132 0.344 1.8 0.000 * 0.019 0.071 

— Not applicable.*Relatively strong relationship.

aDeleting these independent variables actually increases the R squared rather than lessening it.bChange in government appropriations was correlated with change in instruction expenditures (r = .733). Removing both variables from the model decrease

4.4 percentage points.

cFor this sub-period, deleting these independent variables actually increases the R squared slightly rather than lessening it.dFor this sub-period, deleting philanthropic revenue as an independent variable actually increases the R squared slightly rather than lessening it.eChange in government appropriations was correlated with change in instructional expenditures (r = .764) and with other student-related expenditures (r = .

three variables from the model decreased R squared by 7.9 percentage points.

fFor this sub-period, deleting philanthropic revenue as an independent variable actually increases the R squared slightly rather than lessening it.gChange in government appropriations was correlated with change in instructional expenditures (r = .704). Removing both variables from the model decrea

2.1 percentage points.NOTE: In order to deal with outliers, one percentile was trimmed from the top and bottom of several variables: change in government appropriations, changin instruction expenditures, change in student services, change in other student-related expenditures, change in other non-student-related expenditures, chanwhich E&G revenues exceed/fall short of E&G expenditures, change in philanthropic revenue, change in government grants and contracts. The model, in fframework, was not reduced, and therefore may be misspecified. Interpretation of the regression coefficients should be more cautious than if the model had SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Full Collecto 1998.

a

in tuition coefficient

variation 

Probability

with change

Correlation

coefficient

in tuition

Regression 

coefficient

accounted 

for after 

ontrolling 

for other 

factors

Correlation

coefficient

with change Regression 

0.0470.032

743

0.130

 0.000 *

Portion of P

 0.000 

729

0.143

1990–91 to 1994–95 1994–95 to 1
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

55

that accounted for some of the variation in in-district undergraduate tuition over the period 1988–

89 to 1997–98 include the following:

• Change in revenue from government appropriations. After taking into account the

other variables, institutions with greater declines in appropriations per FTE student had

slightly larger increases in tuition. This variable accounted for 2.8 percent of the variation in the change in tuition, after accounting for the other independent variables.

• Change in student services expenditures. Schools with larger increases in these expenditures tended to have slightly smaller increases in in-district undergraduate tuition.

This variable accounted for 2 percent of the variation in the change in tuition.

• Change in revenue from government grants and contracts. Schools with larger increases in these revenues tended to have smaller increases in in-district undergraduate

tuition. This variable accounted for 1.9 percent of the variation in the change in tuition.

• Change in instruction expenditures. Schools that had greater decreases in instruction

expenditures tended to have smaller increases in in-district undergraduate tuition. This

variable accounted for 1.5 percent of the variation in the change in tuition.

• Level of in-district undergraduate tuition in the base year. Institutions with higher levels of tuition in 1988–89 tended to have greater increases in tuition. This variable accounted for 1.2 percent of the variation in the change in tuition.

A number of possible reasons may prevent this regression model from “explaining” the

variation in changes in tuition at 2-year institutions. It is possible that the model is inappropriately specified for this group of institutions. Two-year institutions differ from 4-year institutions

in many ways, but less research is available regarding their financing structures. Furthermore,

this large group of institutions is a very diverse group, with substantial variations in governance,

sources of funding, student characteristics, and other factors.31 It is also important to note that the

selection criteria were slightly different for 2-year institutions, as the percentage of students who

attended on a full-time basis was not used to exclude 2-year institutions from the panel, as it was

for public 4-year institutions.

Discussion

Across all types of public institutions, the trend analysis found that, on average, in-state undergraduate tuition rose in inflation-adjusted terms and that gross tuition revenue accounted for

increasing proportions of total E&G revenue over the period 1988–89 to 1997–98. On the other

hand, state appropriations revenue made up decreasing proportions of total E&G revenue over

 

31Note that California institutions make up 7 percent of the universe of public 2-year institutions used for this analysis, and have

a proportionate influence on the results of the model (California institutions also accounted for 14 percent of the total fall enrollment at public 2-year institutions in the universe in 1997–98).
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

56

the period and, in some cases, even experienced average annual declines. Nevertheless, in general, public institutions continued to rely more on revenue from state appropriations than on tuition revenue. On the expenditure side, instruction expenditures continued to constitute the largest

proportion of total E&G expenditures, while institutional scholarships and fellowships was one

of the fastest growing expenditure categories (see table 17).

Table 17.—Summary of inflation-adjusted trends in tuition and selected revenue and expenditures categories

Table 17.—at public institutions: 1988–89 to 1997–98

Research/ Compredoctoral hensive Bachelor's 2-year

Average annual percent change in in-state undergraduate tuition 4.1 4.2 4.3 3.4 

 for FY, FT students

Tuition revenue:

 Average annual percent change 4.4 4.8 4.9 2.9 

 Average proportion of total E&G revenue 21.9 28.3 28.9 19.9 

 Percentage point change as a proportion of total E&G revenue 5.4 8.4 8.0 5.6 

State appropriations revenue:

 Average annual percent change -1.0 -1.2 0.0 -1.2 

 Average proportion of total E&G revenue 42.6 50.9 47.1 41.7 

 Percentage point change as a proportion of total E&G revenue -9.8 -11.3 -6.9 -3.2 

Instruction expenditures:

 Average annual percent change 1.0 0.6 1.1 -0.9 

 Average proportion of total E&G expenditures 35.6 42.1 38.5 44.1 

 Percentage point change as a proportion of total E&G -1.9 -2.5 -1.6 -4.1 

 expenditures 

Scholarships and fellowships expenditures:

 Average annual percent change 4.5 3.6 2.5 4.3 

 Average proportion of total E&G expenditures 6.9 11.0 14.2 11.2 

 Percentage point change as a proportion of total E&G 1.7 2.2 1.0 3.9 

 expenditures 

 Average annual percent change in institutional scholarships 8.1 7.7 8.0 6.8 

 and fellowships

NOTE: Dollar amounts were converted to constant 1999 dollars using the CPI-U (1982–84 = 100) before annual changes were 

calculated. Average percentage changes were calculated as averages of the annual changes. All revenue and expenditure

categories are per full-time equivalent (FTE) student. Shares of total revenues and expenditures were calculated as averages 

over the ten-year period.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data 

System (IPEDS), Full Collection Years 1989 to 1998.
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

57

These trends appear to be consistent with the findings of the correlational regression models (see table 18). The change in tuition at public institutions over the period 1988–89 to 1997–98

was clearly associated with changes in revenue from government appropriations, and state appropriations comprised the majority of this revenue. The association between tuition and government appropriations at public institutions was not surprising given the results of prior research.

The results suggest that changes in revenue from government appropriations are a greater predictor of changes in tuition, particularly at public 4-year institutions, than other factors included

in the models.

Table 18.—Significant relationships with the change in in-state undergraduate tuition at public institutions: 

Table 18.—1988–89 to 1997–98

Research/ Compredoctoral hensive Bachelor's 2-year

Change in revenue from government appropriations ** ** ** *

Change in instruction expenditures * ** ** *

Change in other student-related expenditures * * * *

Change in revenue from government grants and contracts ** * *

Change in non-student-related expenditures * * **

Change in institutional scholarships and fellowships * * *

Change in philanthropic revenue * * *

Change in student services expenditures * * *

Change in the amount by which E&G revenues exceed/fall ** **

 short of E&G expenditures

Level of in-state undergraduate tuition in base year * *

Change in ratio of graduate to total enrollment *

Change in research expenditures

*Relatively strong relationship.

**Identified as “important.”

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data 

System (IPEDS), Full Collection Years 1989 to 1998.

According to the model results, the change in instruction expenditures also had a positive

association with the change in tuition for each type of public institution, although this variable

did not “explain” as much of the variation as did the change in state appropriations revenue.32

Other revenue and expenditure variables also had associations with the change in tuition at public

institutions over the period 1988–89 to 1997–98, varying by type of institution. In addition, the

variables associated with changes in tuition tended to differ among the sub-periods, and the

amount of variation in the change in tuition accounted for by the independent variables was highest for the 1990–91 to 1994–95 sub-period (the longest sub-period and the one in which in-state

 

32Although the proportions of variation in tuition changes accounted for by changes in appropriations and changes in instruction

expenditures were closer for public bachelor’s institutions than for the other groups of public institutions.
Chapter III: Revenues, Expenditures, and Prices at Public Institutions

58

undergraduate tuition levels were rising the fastest) in each of the models. These differences

among sub-periods suggest that any analysis of changes in tuition and financial variables needs to

consider relationships between those variables over a long period of time in order to accurately

portray change.

The model results were consistent with the findings of the original GAO study, which examined public 4-year institutions over the period 1989–90 to 1994–95 and found that the size of

tuition increases was most strongly associated with the amount of change in revenue from nontuition sources and certain expenditure categories. The most important variables in the GAO

study, which together accounted for about half of the variation in changes in tuition, were: the

change in government appropriations; the change in instruction expenditures; the change in revenue from grants, contracts, and other sources; the change in the amount by which revenues exceeded or fell short of expenditures; the change in other student-related expenditures; the change

in non-student-related expenditures; and the change in research expenditures.

Finally, it is important to keep in mind that in several of these models—particularly for

public 2-year institutions—the R-squared values are relatively low, with more of the variance in

tuition changes remaining unexplained than “explained” by the variables included in the models.

Tuition policies at public institutions are likely to be influenced by state and local policy decisions that were outside the parameters of this model, such as limits on enrollment and student aid

practices. Nonetheless, the results of these models point to associations between variables that

are consistent with the findings of previous research and contribute to an understanding of financial patterns at public institutions.
59

Chapter IV: Revenues, Expenditures, and Prices at Private Notfor-Profit Four-Year Institutions

This chapter focuses on the results of the second analytical component of the study, the

trend analysis and modeling of expenditures, revenues, and prices for private not-for-profit 4-

year institutions. The chapter describes changes over time in various expenditure and revenue

categories as well as in tuition levels for private not-for-profit 4-year institutions. This chapter

also presents the results of a structural model examining relationships at private not-for-profit

institutions.

Data and Methods

In order to examine comparative changes over time, trend data on expenditures, revenues,

enrollment, and prices were calculated for the period 1988–89 to 1995–96, using a panel of private not-for-profit 4-year institutions. These data capture both average, inflation-adjusted dollar

changes over the whole period and average annual percentage changes. In addition, shifts in the

composition of E&G revenues and expenditures are described.

To better understand the statistical relationships between various factors and tuition, a

structural model presented in a report by Westat Inc. and Pelavin Associates (1994) under contract with the U.S. Department of Education, An Analysis of Institutional Decision Making—Final Report on Estimation Results (hereafter referred to as the Westat/Pelavin model), was

updated. The study developed a simultaneous equation model, which attempted to capture the

factors influencing the supply of and demand for college placements and describe the competitive environments of private not-for-profit 4-year institutions over the period 1984 to 1989. The

structure of the model allowed observed levels of tuition to be viewed as “equilibrium” prices at

a specific point in time, while the equations also included various factors that were expected to

influence schools’ and students’ decisions regarding enrollment.33 The model assumed that prices

and new enrollments simultaneously determine each other and are “endogenous” (jointly depend-

 

33“Equilibrium” prices occur at the point at which the demand and supply curves intersect, and where the quantity demanded is

equal to the quantity supplied. The standard formulation of demand/supply curve equations places the quantity demanded/supplied (new enrollments in this case) on the left side of the equations and price (tuition) on the right, where the quantity demanded/supplied is a function of price plus other factors. In order to focus on prices, the Westat/Pelavin model reexpressed the equations’ functional forms so that price is a function of enrollment plus other factors, leading to inverse demand/supply curves.
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

60

ent), while other factors included in the model were assumed to be “exogenous” (predetermined

or derived externally).34

One equation in the model tried to capture students’ perspectives of prices given certain

characteristics of the institutions and the market in which they operate (in other words, measures

of the external environment). In this equation, prices (tuition levels) were assumed to be a function of new enrollments, plus other factors:35

• Instructional quality, represented by the proxies of per student expenditures on instruction, research, and physical plant maintenance, as well as the faculty/student ratio, for

the previous year;

• Prestige, represented by endowment income, admissions test scores, and percentage of

applicants admitted the previous year;

• The provision of ancillary services and resources, represented by student services for

the previous year;

• The cost of attending alternative institutions, as measured by the average tuition at

public institutions in the same state and the proportion of students attending private institutions in the state; and

• The availability of financial aid, represented by expenditures on institutional scholarships and fellowships.

Much of the information available to prospective students is from the previous year, and the

measures reflected that reality. In order to model the equation, the general factors had to be represented by specific, measurable variables. Many of these variables were proxies and may not accurately capture the influences they attempt to represent; this is likely to be particularly true for

instructional quality and institutional prestige, which are extremely difficult to measure (Bradburd and Mann 1990).

The second equation tried to capture institutions’ internal perspectives on prices charged,

given their costs of production and other internal factors. From this perspective, institutions must

raise tuition to the level at which it will cover their current budgets (alternatively, they can only

 

34Another way of describing these terms is that “endogenous” variables are determined within the economic model, while “exogenous” variables are taken as a given by the model.

35More accurately, prices and new enrollments are a function of each other; however, this characterization describes the functional form of the equations, which set price on the left side of the equations. Thus, in the presentation of model results in this

chapter, price is described as the dependent variable and other factors—including new enrollments—are described as independent variables, as reflected in the output of standard statistical software.
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

61

spend what they raise). In this equation, prices also were assumed to be a function of new enrollments, plus other factors:36

• The cost of inputs needed to educate students, represented by average faculty salaries,

as well as expenditures on instruction, administration, student services, and student

aid;37 and

• Other revenue that may offset the costs incurred in educating students, such as endowment income.

It is important to note that in this model, some variables were used in both equations, but as

proxies for different aspects of the relationships characterized by the two equations. For example,

institutional aid expenditures represent the availability of financial aid from the student perspective (which reduces the price they must pay) in one equation, but represents part of an institution’s cost of educating students from the internal perspective in the other equation.

In the model, natural logarithms were taken of the variables on both sides of the equations,

so that the results would express “elasticities,” or the percentage change in the independent variables associated with a one percent change in the dependent variable (price). The model also tried

to identify the extent of tuition increases that were not accounted for by other factors in the equation, by including dummy variables for each year (other than the base year, 1984 in the Westat/Pelavin study). Each dummy variable was defined so that it was equal to 1 if an observation

was for a specific year (e.g., 1987), and 0 if the observation was for another year (e.g., any year

but 1987).38 Because observations for the base year were coded 0 in all of the dummy variables,

each dummy variable year is measured relative to the base year (1984). The estimates for these

dummy variables can be interpreted as representing factors that had not been included in the

model that were associated with prices over time. Three-stage least squares regression was used

to simultaneously estimate the coefficients of both equations for each group of private not-forprofit institutions.39 In addition, reduced form regressions were performed for each sector.40

 

36It should be noted that private not-for-profit institutions typically have a target for enrollment that does not allow for unlimited

growth.

37When direct measures of the prices of inputs were not available, per-student expenditures were used in several categories.

38Note that each institution has multiple observations, one for each year of data included in the model.

39The three-stage least squares procedure allows estimation of systems of structural equations where some equations contain

endogenous variables among the explanatory variables. See Appendix A for details.

40Reduced form regressions incorporate all exogenous variables from both equations into one model, with tuition as the dependent variable (enrollment is excluded because it is endogenous, in other words, jointly determined with the dependent variable).

Whereas structural equations explore the direct relationships among variables (and are based on a stronger set of assumptions),

reduced form equations capture the aggregate effect of the exogenous factors on the endogenous variables (tuition and enrollment), including the indirect effects of the exogenous variables as well as direct effects. Nevertheless, they are useful to support

the findings of the economic model. The coefficient estimates can be interpreted descriptively as the proportional change in tuition associated with a proportional change in the exogenous variables.
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

62

The models presented in the following section update the Westat/Pelavin model, with a few

minor modifications, using data for a later time period, 1989–90 to 1995–96 (table 19).41 Therefore, 1989–90 represents the base year of the updated model. Two of the three proxy measures of

institutional reputation/prestige were eliminated from the first equation due to unavailability of

data. Conversely, a few independent variables were added to the model to capture additional

“external” and “internal” factors that were expected to be associated with prices. The models include the following variables (see table 20):

Equation 1 (“external” factors):

• Dependent variable: Undergraduate tuition and required fees42

• First-time freshmen FTE students43

• Indicators of the competitive environment:

• Average in-state undergraduate tuition at public institutions in the state44

• Proportion of undergraduates in the state enrolled at private not-for-profit 4-year

institutions

• Proxies for quality of instruction:

• Previous year’s instruction expenditures

• Previous year’s expenditures on plant maintenance, plus transfers

• Previous year’s research expenditures

• Previous year’s student/faculty ratio

• Proxy for institutional prestige/recognition:

 

41Note that because of the need for lagged variables, the time period for the model extends from 1989–90 to 1995–96, while the

data (for some variables) begin in 1988–89.

42In general, in-state tuition does not differ much, if at all, from out-of-state tuition at private not-for-profit institutions. In fact,

in 1995–96, in-state differed from out-of-state undergraduate tuition at only five of the 690 private not-for-profit institutions in

the panel, and the average tuition levels differed by less than one-half of one percent. Therefore, although the variable for in-state

tuition was used in the analysis, it is referred to here simply as undergraduate tuition.

43For simplification, first-time freshmen were chosen as the enrollment measure. It is possible that total undergraduate enrollment is also associated with price.

44This indicator represents competition for students within the state; however, competition with public institutions for out-ofstate students may also be relevant, especially for private not-for-profit institutions that draw from a national base. According to

NCES data from the National Postsecondary Student Aid Study (NPSAS), in 1995–96, almost 65 percent of undergraduates

attending all private not-for-profit 4-year institutions were attending an institution in the state of their legal residence; for private

not-for-profit research/doctoral institutions, the percentage was about 48 percent, while for comprehensive and bachelor’s institutions, the percentage was over 70 percent. U.S. Department of Education, National Center for Education Statistics, 1995–96

National Postsecondary Student Aid Study (NPSAS:96), Undergraduate Data Analysis System.
Table 19.—Characteristics of simultaneous equation model for private not-for-profit institutions

Equation 1 (“external” factors):

1994 Westat/Pelavin Model Updated Mode

Dependent variable: Log of published tuition Log of full-time, full-year undergraduatIndependent variables: Log of new enrollments Log of first-time freshmen FTE studentsIndicators of competitive Log of the average tuition of public institutions in the state Log of average in-state undergraduate tu

environment institutions in the state

Log of the proportion of students in the state attending private Log of the proportion of undergraduates institutions granting, Title IV participating higher e

the state in the fall semester who were aprofit 4-year institutions

Quality of instruction Log of previous year’s instruction expenditures per student Same

Log of previous year’s expenditures per student on maintenance and operation of physical plant, plus transfer payments SameLog of previous year’s research expenditures per student SameLog of previous year’s faculty/student ratio Log of previous year's ratio of total FTE 

time instructional faculty

Indicators of prestige and recognition Log of previous year’s top SAT quartile Eliminated due to lack of data

Log of previous years’ percent accepted Eliminated due to lack of data

Log of total endowment income Add revenue from private gifts, grants, 

to get log of philanthropic revenue per s

Financial aid Log of expenditures per student on institutional aid SameAncillary services Log of previous year’s student service expenditures per student Same
Table 19.—Characteristics of simultaneous equation model for private not-for-profit institutions—Continued

Equation 1 (“external” factors):

1994 Westat/Pelavin Model Updated Mode

Consumer purchasing power Add: log of per capita income in the staCumulative rate of increase from other sources 1985 1991

1986 19921987 19931988 19941989 1995

1996

Equation 2 (“internal” institutional factors):

1994 Westat/Pelavin Model Updated Mode

Dependent variable: Log of published tuition Log of in-state, full-time, full-year unde

required fees 

Independent variables: Log of new enrollments Log of first-time freshmen FTE studentsPrice of inputs Log of instruction expenditures per student Same

Log of institutional aid per student SameLog of average faculty salary Log of average salary and fringe benefit

instructional faculty on 9/10-month or 1

Log of administrative expenditures per student Separate into two variables: log of instit

expenditures per student, and log of acaexpenditures per student

Log of student services expenditures per student Same

Add: ratio of graduate FTE enrollment t
Table 19.—Characteristics of simultaneous equation model for private not-for-profit institutions—Continued

Equation 2 (“internal” institutional factors):

1994 Westat/Pelavin Model Updated Mode

Available revenue Log of total endowment income Add revenue from private gifts, grants, 

to get log of philanthropic revenue per sAdd: log of federal grants and contracts Add: log of appropriations and grants anand local sources, less state/local aid fun

Cumulative rate of 1985 1991increase from other sources 1986 1992

1987 19931988 19941989 1995

1996

SOURCE: Westat Inc. and Pelavin Associates. 1994. An Analysis of Institutional Decision-Making—Final Report on Estimation Results. Prepared fo

Department of Education, Office of the Under Secretary. 
Table 20.—Variables included in the simultaneous equation model for private not-for-profit institutions

Equation 1 (“external” factors):

tfuglg Log of undergraduate tuition ftefflg Log of first-time freshmen FTE studentsavtflg Log of average in-state undergraduate tuition at public 4-year institutions in the stateperprlg Log of the proportion of undergraduates enrolled in the state who were attending private not-for-pr

instln Log of previous year’s instruction expenditures per student

pltrln Log of previous year’s expenditures per student on plant maintenance, plus transfer payments

resln Log of previous year’s research expenditures per studentstufcln Log of previous year’s student/faculty ratio phillg Log of philanthropic revenue per studentiaidlg Log of expenditures per student on institutional aidstudln Log of previous year’s student service expenditures per studentstinclg Log of per capita income in the statedummy91 Dummy variable for 1991dummy92 Dummy variable for 1992dummy93 Dummy variable for 1993dummy94 Dummy variable for 1994dummy95 Dummy variable for 1995dummy96 Dummy variable for 1996reslnd Dummy variable for zero values in resln (research/doctoral, comprehensive, bachelor's)pltrlnd Dummy variable for zero values in pltrln (research/doctoral, comprehensive, bachelor's)phillgd Dummy variable for zero values in phillg (comprehensive)ftelgd Dummy variable for zero values in ftefflg (bachelor's)iaidlgd Dummy variable for zero values in iaidlg (bachelor's)tfuglgd Dummy variable for zero values in tfuglg (bachelor's)studlnd Dummy variable for zero values in studln (bachelor's)
Table 20.—Variables included in the simultaneous equation model for private not-for-profit institutions—Continued

Equation 2 (“internal” institutional factors):

tfuglg Log of undergraduate tuition ftefflg Log of first-time freshmen FTE studentsinstlg Log of instruction expenditures per studentiaidlg Log of institutional aid per studentavcmplg Log of average faculty compensationinsplg Log of institutional support expenditures per studentacadlg Log of academic support expenditures per studentstudlg Log of student services expenditures per studentpergd Ratio of graduate FTE enrollment to total FTE enrollmentphillg Log of philanthropic revenue per studentfdgrlg Log of federal grants and contracts less federal aid fundsstlolg Log of appropriations and grants and contracts from state and local sources, less state/local aiddummy91 Dummy variable for 1991dummy92 Dummy variable for 1992dummy93 Dummy variable for 1993dummy94 Dummy variable for 1994dummy95 Dummy variable for 1995dummy96 Dummy variable for 1996stlolgd Dummy variable for zero values in stlolg (research/doctoral, comprehensive, bachelor's)fdgrlgd Dummy variable for zero values in fdgrlg (comprehensive, bachelor's)phillgd Dummy variable for zero values in phillg (comprehensive)ftelgd Dummy variable for zero values in ftefflg (bachelor's)tfuglgd Dummy variable for zero values in iaidlg (bachelor's)iaidlgd Dummy variable for zero values in tfuglg (bachelor's)studlgd Dummy variable for zero values in studlg (bachelor's)NOTE: Dummy variables were required for certain logged variables in order to identify zero values, which were inserted in cases with 

values (for which logarithms return no value). 
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

68

• Philanthropic revenue (endowment income plus private gifts, grants, and contracts)45

• Availability of financial aid:

• Expenditures on institutional aid46

• Indicator of ancillary services:

• Previous year’s expenditures on student services

• Measure of in-state consumer purchasing power:47

• Average per capita income in the state

• Measures of change over time in the relationship between price and enrollment, not accounted for by other independent variables in the equation:

• Dummy variables for 1991, 1992, 1993, 1994, 1995, 1996 (base year = 1990)

Equation 2 (“internal” factors):

• Dependent variable: Undergraduate tuition and required fees

• First-time freshmen FTE students

• Proxies for price of inputs:

• Instruction expenditures

• Institutional aid expenditures

• Average faculty compensation

• Academic support expenditures

• Institutional support expenditures

• Student services expenditures

• Ratio of graduate to total FTE enrollment

 

45Note that the other two indicators of prestige from the Westat/Pelavin model, SAT scores and the percentage of applicants

admitted, had to be dropped due to the lack of data. Endowment income was combined with private gifts revenue, on the premise

that both were associated with institutional prestige. Note that some revenue from private grants and contracts also is included.

46Other forms of student aid, such as aid from federal, state, or local governments, were not captured in the original Westat/Pelavin model and are not included in the updated model. This is partly due to the limitations of IPEDS prior to the changes

in FASB standards, as it does not fully account for aid—for example, revenue from federal student loans generally shows up in

revenue from tuition and fees. Chapter V attempts to explore the relationship, if any, of various forms of aid with college prices.

47This measure reflects in-state consumer purchasing power, whereas many private not-for-profit institutions draw a substantial

proportion of their students from out-of-state. For those institutions that have relatively small proportions of out-of-state students,

however, state per capita income may be a proxy for consumer purchasing power in general. According to data from the National

Postsecondary Student Aid Study (NPSAS), in 1995–96 almost half of undergraduates attending private not-for-profit research/doctoral institutions were in-state residents, compared to 74 percent attending private not-for-profit comprehensive institutions and 72 percent attending bachelor’s institutions. U.S. Department of Education, National Center for Education Statistics,

1995–96 National Postsecondary Student Aid Study (NPSAS:96), Undergraduate Data Analysis System.
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

69

• Measures of available nontuition revenue:

• Philanthropic revenue (endowment income plus private gifts, grants, and contracts)

• Federal grants and contracts, less federal aid funds

• Revenue from state and local sources, less state/local aid

• Measures of change over time in the relationship between price and enrollment, not accounted for by other independent variables in the equation:

• Dummy variables for 1991, 1992, 1993, 1994, 1995, 1996 (base year = 1990)

As in the 1994 model, many of these variables are proxies, assumed to measure certain

“external” and “internal” factors that were expected to be associated with tuition levels. In addition several of the variables are included in both equations but represent different aspects of the

relationships.

Data Sources, Panel Selection, and Statistical Procedures

The primary source of data for both the trend analysis and the simultaneous equation modeling is the IPEDS surveys for 1988–89 to 1995–96. In addition, estimates of state per capita income were compiled from the Bureau of Economic Analysis. The use of available data for the

analysis is based on some important assumptions and limitations on the time periods examined.

Because the revenue and expenditure data are not broken down by level of student (while the dependent variable is undergraduate tuition), the analysis attempted to limit the universe of institutions to those with primarily undergraduate enrollment and added a variable to the model to

reflect the proportion of graduate students at private not-for-profit institutions. In addition, a consistent time series of finance data for private not-for-profit institutions was available only up to

1995–96, due to changes in Financial Accounting Standards Board (FASB) accounting standards

that were incorporated into IPEDS in Fiscal Year 1997. Therefore, the time period of the analysis

is two years shorter than the analysis of public institutions presented in Chapter III.

The universe of private not-for-profit institutions was drawn from Title IV-participating,

degree-granting, 4-year institutions located in the 50 states and the District of Columbia. The institutions were further divided by Carnegie classification into research/doctoral, comprehensive,

and bachelor’s institutions. The following institutions were eliminated from the universe: institutions that enrolled less than 200 FTE students; institutions with less than 50 percent undergraduate enrollment as a percentage of total fall headcount enrollment; and institutions with less than

25 percent full-time enrollment as a percentage of total fall headcount enrollment.48 The final

dataset comprises three panels of institutions with data for all eight years. The total number of

 

48Data for 1995–96 were used to define and measure all of these selection criteria.
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

70

institutions remaining in the panels was 690 (research/doctoral = 47; comprehensive = 192;

bachelor’s = 451).49 All financial data were adjusted for inflation using the Consumer Price Index (CPI-U, 1982–84 = 100), to constant 1999 dollars. Revenue and expenditure variables were

calculated on a per FTE student basis, where FTE was generated from reported or estimated fall

instructional activity (credit hours).

In updating the simultaneous equation model, natural logarithms were taken of variables in

both equations.50 In cases in which variables contained zero or negative values, zero values were

inserted into the logged variables.51 The final structure of the data for the modeling includes

seven observations for each institution, one for each year of the analysis.

Three-stage least squares was used to estimate the model coefficients simultaneously. Following the framework of the 1994 study, the results of the models are presented for each institutional type, including the following statistics for each equation: R-squared; root mean square

error (RMSE); the model probability; the number of valid observations; the estimated coefficients for each independent variable; the standard error of the estimate; and the probability of the

Z statistic for each independent variable.52 The estimated coefficients of the logged independent

variables can be interpreted as “elasticities”—in other words, each estimate represents the percentage change in tuition (the dependent variable) associated with a one percent change in an independent variable, adjusting statistically for the covariation of all other independent variables.53

Conversely, the reciprocal of the estimate can be interpreted as the percentage change in an independent variable associated with a one percent change in tuition, again adjusting statistically for

the covariation of all other independent variables. Through a simple calculation, the coefficients

of the dummy variables for years can be interpreted as the change in tuition since the base year

 

49The original number of private not-for-profit 4-year institutions in the IPEDS dataset in 1995–96 was 2,004. The various selection criteria and missing data procedures eliminated 1,314 institutions, 66 percent of the total. However, institutions remaining

in the panel comprised 66 percent of the total undergraduate enrollment at all private not-for-profit 4-year institutions in 1995–

96. Selection criteria are comparable to those used in most contemporary studies of higher education costs and prices. See Appendix A for details on how many institutions were eliminated at each step, as well as bias analyses of the differences in the characteristics of institutions included in and excluded from the final universes.

50The only exception is the ratio of graduate to total enrollment. Logs were not taken of this ratio due to the large number of zero

values, especially for comprehensive and bachelor’s institutions.

51Negative values occurred in some computed variables due to the imputation process. Logarithms cannot be taken of missing,

zero, or negative values; therefore, zero values were inserted for these cases. Separate dummy variables were then created to

identify these cases. See Appendix A for details.

52Note that because the population is a census, some of these statistics were displayed not to measure significance, but rather to

gauge the explanatory power of the model as a whole (model probability) or the strength of the relationships between the independent variables and the dependent variable (probability of the Z statistic).

53As noted above, according to the model, tuition and enrollment actually determine each other; therefore a change in either one

requires an external cause. However, given the functional form of the equations, the presentation of the results treats enrollment

as an independent variable. In this case, the elasticity represents the proportional change in tuition associated with a change in

enrollment, but the change in enrollment must have some exogenous cause. See Westat Inc. and Pelavin Associates (1994).
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

71

(1989–90), adjusting statistically for the covariation of the independent variables included in the

equations.54

Reduced form regressions also were performed within each institutional type, and the results are presented.55 The statistics provided are similar to those from the simultaneous equation

models, with the addition of adjusted R-squared, which attempts to compensate for the fact that

simply adding more independent variables tends to increase the value of multiple R-squared.

Pearson’s correlation coefficients of each independent variable with the dependent variable (tuition) also are presented. (See Appendix A for details regarding data and statistical procedures.)

Trends in Enrollment, Tuition, Revenues, and Expenditures

The results of the trend analysis for private not-for-profit institutions highlight several major findings for each institutional type. In each set of findings, average amounts and percentage

changes are reported on an inflation-adjusted basis wherever applicable.

Research/Doctoral Institutions

The sub-group of 47 private not-for-profit research/doctoral institutions comprised 2.5 percent of undergraduate enrollment at all public and private not-for-profit institutions in fall 1997.

Over the period between 1988–89 and 1995–96, undergraduate tuition at private not-for-profit

research/doctoral institutions increased by about $3,783 in constant 1999 dollars, or by 3.6 percent annually. On average, total headcount and FTE fall enrollment at research/doctoral institutions did not change over this period, while FTE first-time freshmen enrollment decreased

slightly (table 21.)

Private not-for-profit institutions, which include research/doctoral institutions, rely heavily

on tuition as a source of revenue. Thus, tuition revenue at research/doctoral institutions made up

the largest proportion of total E&G revenue, 49.0 percent on average. In addition, tuition rose at

one of the highest rates of average annual increase among the various sources of revenue, at 3.5

percent in real dollar terms; in comparison, total E&G revenue increased annually by 3.1 percent

on average. The second largest proportion of E&G revenue was federal grants and contracts,

which on average accounted for 16.4 percent of the total and increased annually by 2.5 percent

(table 21).

 

54The calculation is as follows: take the inverse log (to base e) of the estimated dummy coefficient, and subtract 1 from it.

55In the reduced form regressions, the coefficients are not elasticities, but can be interpreted descriptively as the proportional

change in tuition associated with a proportional change in the exogenous variables.
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

72

Table 21.—Average change in price, enrollment, revenue, and expenditures at private not-for-profit 

Table 21.—research/doctoral institutions: 1988–89 to 1995–96 

Undergraduate tuition for FY, FT students $3,783 3.6 — —

Graduate tuition 3,382 3.7 — —

Total fall enrollment — 0.1 — —

FTE fall enrollment — -0.1 — —

FTE first time enrollment — -1.0 — —

Revenue (per FTE) by source:

 Tuition 3,702 3.5 35.9 49.0 

 Federal appropriations 0 0.0 0.0 0.0 

 State appropriations -102 -5.2 0.5 0.6 

 Local appropriations 0 * 1.8 0.0 * 0.0 *

 Federal grants and contracts 893 2.5 12.0 16.4 

 State grants and contracts 173 4.4 1.3 1.8 

 Local grants and contracts 81 13.8 0.2 0.3 

 Private gifts, grants, and contracts 373 1.8 7.1 9.7 

 Endowment income 249 1.4 6.1 8.4 

 Sales and services of educational activities 748 5.4 4.9 6.7 

 Other 612 4.2 5.2 7.1 

 Auxiliary enterprises 268 0.9 9.5 —

 Hospital 1,408 3.5 14.8 —

 Independent operations 134 1.8 2.6 —

 Total revenue 8,666 2.9 100.0 —

 E&G revenue 6,730 3.1 — 100.0 

Expenditures (per FTE) by function:

 Instruction 2,525 3.3 26.5 36.0 

 Research 853 2.7 10.3 14.0 

 Public service 205 5.2 1.3 1.8 

 Academic support 299 1.7 6.2 8.4 

 Student services 309 2.9 3.5 4.8 

 Institutional support 460 2.0 7.6 10.3 

 Plant operations/maintenance 145 1.0 4.7 6.4 

 Scholarships and fellowships 1,824 6.7 9.4 12.8 

 Mandatory transfers 42 1.2 1.4 2.0 

 Nonmandatory transfers 1,133 17.6 2.9 4.0 

 Auxiliary enterprises 193 0.7 9.2 —

 Hospital 1,318 3.3 14.3 —

 Independent operations 162 2.3 2.5 —

 Total expenditures 9,469 3.2 100.0 —

 Total E&G 6,872 3.2 — 100.0 

 Institutional scholarships and fellowships 1,771 8.7 — —

Average faculty compensation 3,562 0.7 — —

N = 47

— Not applicable.

* Value rounds to less than $1 or less than .1 percent.

NOTE: Percentages may not sum to 100 due to rounding. Dollar amounts were converted to constant 1999 dollars using the CPI-U 

(1982–84 = 100) before annual changes were calculated. Average percentage changes were calculated as averages of the annual 

changes. All revenue and expenditure categories are per full-time equivalent (FTE) student. Shares of total revenues and expenditures

were calculated as averages over the ten-year period.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System 

(IPEDS), Full Collection Years 1989 to 1996.

Average 

change, in 

constant 

1999 dollars

Average 

annual 

percentage 

change on average

Proportion 

of total E&G 

revenues/ 

expenditures, 

on average

Proportion 

of total 

revenues/ 

expenditures, 
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

73

Gross tuition revenue also accounted for slightly increasing proportions of total E&G revenue at research/doctoral institutions over this period. From 1988–89 to 1995–96, the proportion

of E&G revenue made up of tuition revenue increased by 1.3 percentage points. The proportion

of revenue from other, nontuition sources decreased slightly over this periodfor example, revenue from endowment income and private gifts, grants, and contracts combined decreased as a

proportion of E&G revenue by about 2 percentage points (table 22).

On the expenditure side, instruction made up the largest proportion of total E&G expenditures, 36.0 percent on average. Research expenditures constituted the second largest proportion,

at 14.0 percent, with scholarships and fellowships following at 12.8 percent of total E&G expenditures and institutional support at 10.3 percent. The inflation-adjusted, average annual rates of

growth of these expenditures varied, from 3.3 percent for instruction and 2.7 percent for research,

compared to 3.2 percent for E&G expenditures as a whole. Institutional scholarships and fellowships were one of the fastest growing expenditure categories, increasing annually by 8.7 percent

on average (table 21). As a result, the composition of E&G expenditures shifted over this period.

Scholarships and fellowships made up an increasing proportion of total E&G expenditures, increasing by 3.0 percentage points. The proportion of instruction expenditures remained relatively

stable, while the proportions for academic support, institutional support, and plant operations and

maintenance fell slightly (table 22).

Comprehensive Institutions

The sub-group of 192 private not-for-profit comprehensive institutions comprised 3.7 percent of undergraduate enrollment at all public and private not-for-profit institutions in fall 1997.

Undergraduate tuition at comprehensive institutions increased by about $2,992 in constant 1999

dollars, or by 4.1 percent annually, over the period 1988–89 to 1995–96. On average, total

headcount and FTE fall enrollment at these schools increased annually, by 1.5 percent and 1.3

percent respectively, while FTE first-time freshmen enrollment decreased slightly (table 23).

Tuition revenue made up the largest proportion of total E&G revenue, 72.0 percent on average, and rose at one of the highest rates of average annual increase among the various sources

of revenue, 3.8 percent in real dollar terms. In comparison, total E&G revenue increased annually

by 2.8 percent on average. The source of revenue providing the second largest proportion of

E&G revenue was private gifts, grants, and contracts, 8.3 percent on average (table 23). Tuition

revenue accounted for slightly increasing proportions of total E&G revenue at comprehensive

institutions over this period, increasing by 5.1 percentage points. As with research/doctoral institutions, the proportion of revenue from endowment income and private gifts, grants, and contracts decreased slightly over this period, by 3.1 percentage points for both sources (table 24).
Table 22.—Percentage composition of E&G revenue and expenditure at private not-for-profit research/doctoral institutions, o

Table 22.—1995–96 

Tuition 48.0 48.1 48.7 48.8 49.2 49.9 Federal appropriations 0.0 0.0 0.0 0.0 0.0 0.0 State appropriations 0.9 0.9 0.8 0.5 0.5 0.4 Local appropriations 0.0 * 0.0 * 0.0 * 0.0 * 0.0 * 0.0 * Federal grants and contracts 16.8 16.4 16.4 16.6 16.7 16.4 State grants and contracts 1.8 1.7 1.7 1.7 1.7 1.8 Local grants and contracts 0.2 0.3 0.2 0.3 0.3 0.3 Private gifts, grants, and contracts 10.3 10.1 10.0 9.8 9.5 9.4 Endowment income 9.4 9.1 8.8 8.3 7.8 7.7 Sales and services of educational 5.9 6.2 6.5 6.6 6.9 7.2  activitiesOther 6.6 7.2 7.0 7.4 7.3 6.9  E&G revenue 100.0 100.0 100.0 100.0 100.0 100.0 Instruction 35.1 35.7 35.9 35.8 35.9 36.7 Research 14.7 14.2 13.9 13.8 13.9 13.7 Public service 1.8 1.6 1.7 1.7 1.8 1.8 Academic support 9.0 8.3 8.7 8.6 8.6 8.2 Student services 4.8 4.8 4.9 4.9 4.7 4.7 Institutional support 11.1 10.5 10.4 10.3 10.0 10.2 Plant operation/maintenance 7.0 6.7 6.5 6.5 6.3 6.3 Scholarships and fellowships 11.3 11.5 12.0 12.8 13.3 13.6 Mandatory transfers 2.1 2.2 2.0 1.9 1.9 1.9 Nonmandatory transfers 3.8 4.3 4.2 3.8 3.7 2.9  E&G expenditures 100.0 100.0 100.0 100.0 100.0 100.0 

N = 47* Values round to less than .1 percent.NOTE: Percentages may not sum to 100 due to rounding. Dollar amounts were converted to constant 1999 dollars using the CPI-U (1982–84 = 100) 

shares were calculated. All revenue and expenditure categories are per full-time equivalent (FTE) student. SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Full Cto 1996.

1988–89 1989–90 1990–91 1991–92 1992–93 1993–94 1
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

75

Table 23.—Average change in price, enrollment, revenue, and expenditures at private not-for-profit 

Table 23.—comprehensive institutions: 1988–89 to 1995–96 

Undergraduate tuition for FY, FT students $2,992 4.1 — —

Graduate tuition 1,721 3.6 — —

Total fall enrollment — 1.5 — —

FTE fall enrollment — 1.3 — —

FTE first time enrollment — -0.6 — —

Revenue (per FTE) by source:

 Tuition 2,739 3.8 61.4 72.0

 Federal appropriations 31 3.1 0.9 1.1

 State appropriations -64 -9.3 0.5 0.5

 Local appropriations 0 * 24.6 0.0 * 0.0 *

 Federal grants and contracts 75 1.5 6.2 7.3

 State grants and contracts 64 2.7 2.6 3.1

 Local grants and contracts -14 -5.8 0.1 0.1

 Private gifts, grants, and contracts -68 -0.2 7.0 8.3

 Endowment income -42 -1.0 2.8 3.3

 Sales and services of educational activities -6 -0.4 0.9 1.1

 Other 81 2.6 2.7 3.1

 Auxiliary enterprises 40 0.2 14.6 —

 Hospital 13 55.4 0.1 —

 Independent operations -3 -0.2 0.4 —

 Total revenue 2,891 2.4 100.0 —

 E&G revenue 2,795 2.8 — 100.0

Expenditures (per FTE) by function:

 Instruction 627 1.9 28.4 32.7

 Research 112 10.9 1.0 1.2

 Public service 7 0.8 1.0 1.1

 Academic support 161 2.3 5.9 6.8

 Student services 333 3.4 8.3 9.6

 Institutional support 84 0.5 13.7 15.7

 Plant operations/maintenance 28 0.4 7.0 8.0

 Scholarships and fellowships 1,324 6.6 17.7 20.4

 Mandatory transfers 65 3.4 1.9 2.1

 Nonmandatory transfers 32 1.8 2.3 2.6

 Auxiliary enterprises -127 -0.8 12.5 —

 Hospital 11 36.9 0.1 —

 Independent operations -17 -2.9 0.4 —

 Total expenditures 2,641 2.2 100.0 —

 Total E&G 2,824 2.8 — 100.0

 Institutional scholarships and fellowships 1,284 10.2 — —

Average faculty compensation 3,791 1.0 — —

N = 192

— Not applicable.

* Value rounds to less than $1 or less than .1 percent.

NOTE: Percentages may not sum to 100 due to rounding. Dollar amounts were converted to constant 1999 dollars using the CPI-U 

(1982–84 = 100) before annual changes were calculated. Average percentage changes were calculated as averages of the annual 

changes. All revenue and expenditure categories are per full-time equivalent (FTE) student. Shares of total revenues and expenditures 

were calculated as averages over the ten-year period.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System 

(IPEDS), Full Collection Years 1989 to 1996.

on average

Proportion of 

total E&G 

revenues/ 

expenditures, 

Proportion of

 total revenues/ 

expenditures,

 on average

Average 

annual 

percentage 

change

Average 

change, in 

constant 1999 

dollars
Table 24.—Percentage composition of E&G revenue and expenditure at private not-for-profit comprehensive institutions, on a

Table 24.—1995–96 Tuition 68.4 69.9 71.7 72.0 73.6 73.5 Federal appropriations 1.1 1.1 1.2 1.1 1.0 1.0 State appropriations 0.9 0.7 0.7 0.5 0.5 0.4 Local appropriations 0.0 * 0.0 * 0.0 * 0.0 * 0.0 * 0.0 * Federal grants and contracts 7.5 7.7 7.0 7.4 7.5 7.1 State grants and contracts 3.0 3.1 2.9 3.4 3.1 3.0 Local grants and contracts 0.2 0.1 0.1 0.1 0.1 0.1 Private gifts, grants, and contracts 10.1 9.0 8.5 8.2 7.3 8.3 Endowment income 4.0 3.9 3.7 3.2 3.1 2.9 Sales and services of educational 1.2 1.3 1.2 1.1 1.0 1.0  activitiesOther 3.6 3.3 3.1 3.0 2.9 2.8  E&G revenue 100.0 100.0 100.0 100.0 100.0 100.0 Instruction 33.6 33.0 33.4 32.9 32.7 32.3 Research 0.9 0.9 0.9 1.0 1.1 1.3 Public service 1.2 1.2 1.1 1.1 1.1 1.2 Academic support 6.9 6.9 6.9 6.8 6.8 6.6 Student services 9.3 9.4 9.7 9.6 9.6 9.7 Institutional support 17.1 16.9 16.6 15.7 15.1 15.0 Plant operation/maintenance 8.8 8.6 8.3 8.0 7.7 7.7 Scholarships and fellowships 17.6 18.3 18.8 20.5 21.3 21.7 Mandatory transfers 2.0 2.2 2.0 2.2 2.2 2.1 Nonmandatory transfers 3.0 3.0 2.6 2.2 2.4 2.3  E&G expenditures 100.0 100.0 100.0 100.0 100.0 100.0 

N = 192* Values round to less than .1 percent.NOTE: Percentages may not sum to 100 due to rounding. Dollar amounts were converted to constant 1999 dollars using the CPI-U (1982–84 = 100) 

shares were calculated. All revenue and expenditure categories are per full-time equivalent (FTE) student. SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Full Cto 1996.

1988–89 1989–90 1990–91 1991–92 1992–93 1993–94 
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

77

Instruction expenditures made up the largest proportion of total E&G expenditures at comprehensive institutions, 32.7 percent on average. Scholarships and fellowships made up the second largest proportion, at 20.4 percent, with institutional support following at 15.7 percent of

total E&G expenditures. Instruction expenditures experienced real average annual increases of

1.9 percent over this period and institutional support expenditures remained relatively flat, compared to 2.8 percent for E&G expenditures as a whole. Institutional scholarships and fellowships

was one of the fastest growing expenditure categories, increasing annually by 10.2 percent on

average (table 23). As a result of these differences in rates of growth, the composition of E&G

expenditures shifted over time at comprehensive institutions. Scholarships and fellowships made

up an increasing proportion of total E&G expenditures, increasing by 5.0 percentage points. The

proportion of instruction-related expenditures decreased by 1.9 percentage points while the proportion for institutional support fell by 2.4 percentage points (table 24).

Bachelor’s Institutions

The sub-group of 451 private not-for-profit bachelor’s institutions comprised 5 percent of

undergraduate enrollment at all public and private not-for-profit institutions in fall 1997. Undergraduate tuition at bachelor’s institutions increased by about $2,841 in constant 1999 dollars over

the whole period, or by 3.7 percent annually. Although total headcount and FTE fall enrollment

increased slightly, by 1.6 percent and 1.4 percent annually, FTE first-time freshmen enrollment

remained almost flat (table 25).

Bachelor’s institutions relied heavily on tuition revenue, which made up the largest proportion of total E&G revenue (64.1 percent on average). Tuition also had one of the highest rates of

average annual increase among the various sources of revenue, at 3.4 percent in inflationadjusted terms. Private gifts, grants, and contracts revenue made up the second largest proportion

of E&G revenue, 12.9 percent on average, with endowment income third at 8.8 percent. These

sources of revenue experienced small annual increases over this period of 1.1 percent and 1.5

percent, respectively (table 25). Given its relatively high rate of increase, tuition revenue accounted for an increasing proportion of total E&G revenue, increasing by 4.2 percentage points

over this period. The proportion of revenue from endowment income and private gifts, grants,

and contracts decreased slightly, by 2.2 percentage points for both sources (table 26).

As for the other groups of institutions, instruction expenditures made up the largest proportion of total E&G expenditures at these schools (28.7 percent). Scholarships and fellowships

made up the second largest proportion (23.4 percent), with institutional support (16.6 percent)

and student services (10.2 percent) following. Instruction expenditures increased annually by 2.0

percent in real terms over this period, institutional support expenditures by 1.3 percent, and
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

78

Table 25.—Average change in price, enrollment, revenue, and expenditures at private not-for-profit 

Table 25.—bachelor's institutions: 1988–89 to 1995–96 

Undergraduate tuition for FY, FT students $2,841 3.7 — —

Graduate tuition 1,890 3.4 — —

Total fall enrollment — 1.6 — —

FTE fall enrollment — 1.4 — —

FTE first time enrollment — 0.1 — —

Revenue (per FTE) by source:

 Tuition 2,635 3.4 53.1 64.1

 Federal appropriations -48 -0.3 0.1 0.1

 State appropriations -50 -13.6 0.2 0.3

 Local appropriations -6 -0.3 0.0 * 0.0 *

 Federal grants and contracts -81 -0.8 5.9 7.1

 State grants and contracts 38 1.2 2.5 3.0

 Local grants and contracts 3 18.4 0.0 * 0.0 *

 Private gifts, grants, and contracts 158 1.1 10.7 12.9

 Endowment income 144 1.5 7.3 8.8

 Sales and services of educational activities -3 0.1 0.3 0.4

 Other 207 5.4 2.7 3.3

 Auxiliary enterprises 48 0.2 17.1 —

 Hospital 0 0.0 0.0 —

 Independent operations -24 -3.0 0.3 —

 Total revenue 3,095 2.0 100.0 —

 E&G revenue 2,998 2.4 — 100.0

Expenditures (per FTE) by function:

 Instruction 717 2.0 24.5 28.7

 Research 49 5.3 0.6 0.7

 Public service 23 2.3 0.8 0.9

 Academic support 188 2.2 5.6 6.6

 Student services 314 2.4 8.7 10.2

 Institutional support 286 1.3 14.2 16.6

 Plant operations/maintenance 5 0.0 * 7.6 8.9

 Scholarships and fellowships 1,526 5.4 20.0 23.4

 Mandatory transfers 8 0.4 1.5 1.8

 Nonmandatory transfers -204 -4.1 2.0 2.4

 Auxiliary enterprises -144 -0.7 14.1 —

 Hospital -6 0.0 * 0.0 * —

 Independent operations -23 -3.1 0.3 —

 Total expenditures 2,739 1.8 100.0 —

 Total E&G 3,049 2.4 — 100.0

 Institutional scholarships and fellowships 1,593 8.5 — —

Average faculty compensation 2,982 0.8 — —

N = 451

— Not applicable.

* Value rounds to less than .1 percent.

NOTE: Percentages may not sum to 100 due to rounding. Dollar amounts were converted to constant 1999 dollars using the CPI-U 

(1982–84 = 100) before annual changes were calculated. Average percentage changes were calculated as averages of the annual

changes. All revenue and expenditure categories are per full-time equivalent (FTE) student. Shares of total revenues and expenditures

were calculated as averages over the ten-year period.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System

(IPEDS), Full Collection Years 1989 to 1996.

on average

Proportion 

of total E&G 

revenues/ 

expenditures, 

on average

Proportion

 of total 

revenues/ 

expenditures, 

Average 

annual 

percentage 

change

Average 

change, in 

constant 1999 

dollars
Table 26.—Percentage composition of E&G revenue and expenditure at private not-for-profit bachelor's institutions, on avera

Tuition 60.6 61.9 63.3 64.1 65.0 66.4 Federal appropriations 0.3 0.3 0.2 0.2 0.2 0.0 * State appropriations 0.4 0.4 0.4 0.3 0.3 0.2 Local appropriations 0.1 0.0 * 0.0 * 0.0 0.0 0.0 Federal grants and contracts 7.7 7.4 6.9 7.2 7.5 7.0 State grants and contracts 3.0 3.0 2.9 3.2 3.2 3.0 Local grants and contracts 0.0 * 0.0 * 0.0 * 0.0 * 0.0 * 0.0 * Private gifts, grants, and contracts 14.4 13.6 13.2 12.4 12.6 12.1 Endowment income 9.6 9.5 9.3 9.2 8.1 8.1 Sales and services of educational 0.4 0.4 0.4 0.3 0.4 0.3  activitiesOther 3.5 3.5 3.3 3.2 2.8 2.8  E&G revenue 100.0 100.0 100.0 100.0 100.0 100.0 Instruction 29.1 28.9 29.3 28.9 28.7 28.4 Research 0.7 0.7 0.6 0.7 0.7 0.7 Public service 0.9 1.0 1.0 0.8 0.9 0.9 Academic support 6.7 6.8 6.7 6.6 6.5 6.5 Student services 10.3 10.2 10.3 10.2 10.2 10.2 Institutional support 17.5 17.2 17.1 16.6 16.2 16.1 Plant operation/maintenance 9.8 9.5 9.3 8.9 8.7 8.6 Scholarships and fellowships 20.6 21.0 21.7 23.5 24.6 24.9 Mandatory transfers 2.0 1.9 1.8 1.7 1.7 1.7 Nonmandatory transfers 3.5 3.6 2.7 2.1 2.0 1.9  E&G expenditures 100.0 100.0 100.0 100.0 100.0 100.0 

N = 451*Values round to less than .1 percent.NOTE: Percentages may not sum to 100 due to rounding. Dollar amounts were converted to constant 1999 dollars using the CPI-U (1982–84 = 100) 

shares were calculated. All revenue and expenditure categories are per full-time equivalent (FTE) student. SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Full Cto 1996.

1988–89 1989–90 1990–91 1991–92 1992–93 1993–94 1
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

80

student services expenditures by 2.4 percent, compared to 2.4 percent for E&G expenditures as a

whole. Institutional scholarships and fellowships were one of the fastest growing expenditure

categories, increasing annually by 8.5 percent on average (table 25). As a result of these different

rates of change, the composition of E&G expenditures at bachelor’s institutions shifted over

time. Scholarships and fellowships made up an increasing proportion of total E&G expenditures—increasing by 4.5 percentage points, from 20.6 percent to 25.1 percent. The proportions of

instruction expenditures and student services remained relatively stable, while the proportion for

institutional support fell by 1.2 percentage points (table 26).

Model Results

The results of the simultaneous equation modeling for private not-for-profit institutions

highlight several findings for each institutional type. In each set of findings, variables associated

with tuition are reported in increasing order of the percentage increase in the independent variable that is associated with a one percent increase in tuition.

Research/Doctoral Institutions

The simultaneous equations model appeared to be a relatively good fit for research/doctoral

institutions over the period 1989–90 to 1995–96. In Equation 1 (which represents “external”

factors), the independent variables explained about 81.5 percent of the variation in tuition. In

Equation 2 (which represents “internal,” institutional factors), the independent variables explained about 62.0 percent of the variation (table 27).

In Equation 1, higher tuition levels were associated with slightly higher enrollment levels.56

In addition, several of the variables representing “external” factors were associated with tuition at

research/doctoral institutions, including the following:

• Availability of financial aid. Higher tuitions at research/doctoral institutions were associated with higher levels of institutional aid. A 3.5 percent increase in institutional

aid was associated with a one percent increase in tuition.

 

56In this model, the measure of price is published tuition and fees, which indicates “sticker price” rather than net price (institutional aid is represented as an expenditure rather than as a discount in the price). Issues of institutional reputation and the socalled “Chivas Regal” effect may be incorporated into the relationship between enrollment and sticker price; in the absence of

good information about quality or prestige, price may act as a signal of an institution’s elite status. Some researchers also note

that students’ sensitivity to sticker price is low; see Bradburd and Mann (1990). Also see Lapovsky’s commissioned paper in

Volume 2 for a discussion of tuition discounting.
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

81

Table 27.—Coefficients for the simultaneous equation estimation of undergraduate tuition on selected

Table 27.—institutional and external characteristics for private not-for-profit research/doctoral institutions:

Table 27.—1989–90 to 1995–96 

Equation 1 (“external” factors) 329 0.115 0.815 0.000 *

Equation 2 (“internal” institutional factors) 329 0.165 0.620 0.000 *

Equation 1

Log of first-time freshmen FTE students 0.095 10.5 0.021 0.000 *

Log of previous year’s instruction expenditures 0.048 20.7 0.025 0.052

Log of average tuition at public 4-year institutions 0.106 9.5 0.020 0.000 *

 in the state

Log of previous year’s expenditures on plant -0.020 -49.0 0.011 0.068

 maintenance and transfers

Log of the proportion of undergraduates enrolled 0.004 272.1 0.016 0.816

 in the state attending private not-for-profit 4-year 

 institutions 

Log of previous year’s research expenditures 0.048 20.8 0.011 0.000 *

Log of previous year’s student service expenditures 0.103 9.7 0.019 0.000 *

Log of expenditures on institutional aid 0.286 3.5 0.018 0.000 *

Log of previous year’s student/faculty ratioa 0.220 4.5 0.032 0.000 *

Log of philanthropic revenuea -0.034 -29.2 0.015 0.024 *

Log of per capita income in the state 0.182 5.5 0.065 0.005 *

1991 0.000 — 0.023 0.987

1992 -0.022 — 0.024 0.347

1993 -0.014 — 0.024 0.564

1994 -0.010 — 0.025 0.684

1995 -0.013 — 0.026 0.626

1996 -0.008 — 0.027 0.774

Dummy variable for zero values in log of previous year’s 0.399 — 0.063 0.000 *

 research expenditures

Dummy variable for zero values in log of previous year’s -0.187 — 0.114 0.100

 expenditures on plant maintenance and operation

Constant 2.281 — 0.828 0.006 *

variable) in tuition estimate Probability

Standard

independent percent change error of the

a 1 percent associated

change in the with a 1

tuition independent

associated with variable

Coefficient

(percentage Percentage

change in change in the

N error (RMSE) “R-squared” significance

Root mean

square Model
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

82

Table 27.—Coefficients for the simultaneous equation estimation of undergraduate tuition on selected

Table 27.—institutional and external characteristics for private not-for-profit research/doctoral institutions:

Table 27.—1989–90 to 1995–96—Continued 

Equation 2

Log of first-time freshmen FTE students -0.210 -4.8 0.067 0.002 *

Log of instruction expenditures 0.005 205.1 0.036 0.892

Log of expenditures on institutional aid 0.284 3.5 0.028 0.000 *

Log of average faculty compensation 0.684 1.5 0.165 0.000 *

Log of institutional support expenditures 0.079 12.6 0.030 0.007 *

Log of academic support expenditures -0.003 -344.9 0.021 0.890

Log of student services expenditures -0.051 -19.7 0.040 0.210

Log of philanthropic revenue -0.120 -8.3 0.021 0.000 *

Log of federal grants and contracts 0.083 12.0 0.017 0.000 *

Log of revenue from state and local sources -0.018 -56.8 0.007 0.015 *

Ratio of graduate FTE enrollment to total FTE -0.369 — 0.149 0.013 *

 enrollment

1991 -0.004 — 0.034 0.912

1992 -0.025 — 0.035 0.478

1993 -0.024 — 0.036 0.498

1994 -0.003 — 0.036 0.941

1995 0.014 — 0.036 0.694

1996 0.052 — 0.037 0.159

Dummy variable for zero values in log of revenue from -0.193 — 0.053 0.000 *

 state and local sources

Constant 1.410 — 1.258 0.262

Endogenous variables: Log of undergraduate tuition; log of first-time freshmen FTE students

Exogenous variables: all other variables

—Not applicable.

*Relatively strong relationship.

a

These variables may be acting as suppressor variables in Equation 1. This could have resulted from a disordinal interaction effect, it

could be a statistical artifact of the sample, or the model could be misspecified.

NOTE: “N” refers to the number of observations, not the number of institutions; each institution has one observation for each year.

For logged independent variables, the second column is the reciprocal of the first. The coefficients of the dummy variables

for the years can be interpreted as the change in tuition since the base year (1990), adjusting statistically for the covariation of the

independent variables, by taking the inverse log (to base e) of the estimated coefficient and subtracting 1 from it. In the case of 

research/doctoral institutions, for example, the change from 1990 to 1996 is 0.8 percent in Equation 1 and 5.4 percent in Equation 2.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System

(IPEDS), Full Collection Years 1989 to 1996; Bureau of Economic Analysis, Regional Accounts Data, Personal Income for States:

1958–98, released July 1999.

variable) in tuition estimate Probability

Standard

independent percent change error of the

a 1 percent associated

change in the with a 1

tuition independent

associated with variable

Coefficient

(percentage Percentage

change in change in the
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

83

• In-state consumer purchasing power. Higher tuitions at private not-for-profit research/doctoral institutions were associated with a higher level of per capita income in

the state.57 In fact, a 5.5 percent increase in state income levels was associated with a

one percent increase in tuition at this group of institutions.

• Price competition with the public sector. Higher tuitions at research/doctoral institutions were associated with higher average tuition levels at public 4-year institutions in

the state.

• Ancillary services. Higher tuitions were associated with higher expenditures per student on student services.

• Proxies for quality of instruction. Higher tuitions at research/doctoral institutions were

associated with higher research expenditures, as well as with higher expenditures on

student services.

Contrary to the expected relationships—which assumed that philanthropic revenue and student/faculty ratios could function as proxies for institutional reputation and instructional quality,

respectively, from the perspective of students—higher tuitions at research/doctoral institutions

were associated with lower revenue from philanthropic sources and higher student/faculty ratios.

It is possible that these variables are weak proxies for institutional reputation and quality.58 The

issue of students’ perceptions of institutional quality, as well as the difficulty of measuring reputation and quality, may be relevant in this regard.

In Equation 2, higher tuitions at research/doctoral institutions were associated with lower

enrollments.59 In addition, “internal” factors were associated with tuition at research/doctoral institutions, including the following:

• Price of inputs. Higher tuitions at research/doctoral institutions were associated with

higher expenditures—for institutional aid, institutional support expenditures, and average faculty compensation levels. A 1.5 percent increase in average faculty compensation levels or a 3.5 percent increase in institutional aid was associated with a tuition

increase of one percent, accounting for the covariance of all other variables in the

equation. Higher undergraduate tuition levels also were associated with lower proportions of graduate enrollment, which may affect cost structures as well as the internal

distribution of subsidies.

 

57Although private not-for-profit research/doctoral institutions may draw students nationally, on average almost half the undergraduates attending these schools in 1995–96 were in-state residents, according to data from U.S. Department of Education, National Center for Education Statistics, 1995–96 National Postsecondary Student Aid Study (NPSAS:96), Undergraduate Data

Analysis System.

58In addition, these variables may be acting as suppressor variables i.e., a variable that changes the prediction value of another

variable (or set of variables) by its inclusion in the regression equation. This could have resulted from a disordinal interaction

effect (in which the direction of a relationship between two variables is different depending on the value of some other variable),

it could be a statistical artifact of the sample, or the model could be misspecified.

59It is possible that research/doctoral institutions placed a limit on the quantity of places they were willing to supply in order to

maintain the quality of their student bodies, or that the model was misspecified.
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

84

• Availability of nontuition revenue. Higher tuition levels at research/doctoral institutions were associated with lower levels of philanthropic revenue. An 8.3 percent decrease in philanthropic revenue was associated with a one percent increase in tuition.

Higher tuition also was associated with lower levels of state and local revenue, but

with slightly higher levels of revenue from federal grants and contracts.

• Change over time. After adjusting statistically for the covariation of enrollment, expenditure, and revenue levels (the independent variables in the equation), prices increased slightly over time, about 5.4 percent over six years.

The estimates from the reduced form equation generally support these findings (table 28).

However, two other variables were related to tuition: the proportion of students in the state attending private institutions in Equation 1, and academic support expenditures in Equation 2.

Conversely, research expenditures and state income levels were no longer related to tuition in

Equation 1, as was true with institutional support expenditures in Equation 2.

Comprehensive Institutions

The simultaneous equation model captured some of the “external” and “internal” factors

associated with prices at comprehensive institutions over the period 1989–90 to 1995–96. In

Equation 1, the independent variables (which represented “external” factors) explained about

59.5 percent of the variation in tuition; in Equation 2, the independent variables (representing

“internal” factors) explained 58.9 percent of the variation (table 29).

In Equation 1, higher levels of tuition were associated with higher amounts of first-time

freshmen enrollment. In addition, several of the variables representing “external” factors were

associated with tuition at comprehensive institutions, including the following:

• Availability of financial aid. Higher tuitions were related to higher expenditures on institutional aid. A 4.1 percent increase in institutional aid was associated with a one

percent increase in tuition.

• Proxies for quality of instruction. Higher tuitions were related to higher instruction,

which was assumed in this model to represent the quality of the product offered. A 6.8

percent increase in instruction expenditures was associated with a one percent increase

in tuition. Higher tuitions also were associated with lower research expenditures, however.

• In-state consumer purchasing power. Higher tuitions at comprehensive institutions

were associated with higher per capita incomes in the state.

• Ancillary services. Higher tuitions were associated with higher expenditures per student on student services.
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

85

Table 28.—Coefficients for the reduced form regression of undergraduate tuition on selected institutional 

Table 28.—and external characteristics for private not-for-profit research/doctoral institutions: 1989–90 

Table 28.—to 1995–96 

Adjusted 

N R-squared R-squared

Model 329 0.849 0.836 0.000 *

Correlation 

coefficient 

with Reduced Standard 

dependent form error of the 

variable coefficient estimate

Log of previous year’s instruction expenditures 0.551 -0.038 0.068 0.577

Log of average tuition at public 4-year institutions in 0.357 0.096 0.020 0.000 *

 the state

Log of previous year’s expenditures on plant 0.342 -0.017 0.012 0.158

 maintenance and transfers

Log of the proportion of undergraduates enrolled in 0.481 0.064 0.018 0.001 *

 the state attending private not-for-profit 4-year 

 institutions 

Log of previous year’s research expenditures 0.573 0.011 0.016 0.484

Log of previous year’s student service expenditures 0.469 0.201 0.061 0.001 *

Log of expenditures on institutional aid 0.801 0.244 0.018 0.000 *

Log of previous year’s student/faculty ratio -0.283 0.244 0.035 0.000 *

Log of philanthropic revenue 0.511 -0.032 0.017 0.065

Log of per capita income in the state 0.294 0.071 0.074 0.343

Log of instruction expenditures 0.541 0.030 0.068 0.656

Log of average faculty compensation 0.547 0.253 0.057 0.000 *

Log of institutional support expenditures 0.443 0.002 0.022 0.913

Log of academic support expenditures 0.507 0.052 0.016 0.001 *

Log of student services expenditures 0.458 -0.139 0.060 0.021 *

Log of federal grants and contracts 0.683 0.050 0.014 0.000 *

Log of revenue from state and local sources 0.319 -0.004 0.006 0.488

Ratio of graduate FTE enrollment to total FTE 0.219 0.044 0.091 0.628

 enrollment

1991 -0.117 0.005 0.023 0.812

1992 -0.066 -0.020 0.023 0.387

1993 0.010 -0.011 0.024 0.649

1994 0.067 0.004 0.025 0.868

1995 0.108 0.010 0.025 0.696

1996 0.159 0.028 0.026 0.286

Dummy variable for zero values in log of previous -0.126 0.298 0.080 0.000 *

 year’s research expenditures

Dummy variable for zero values in log of previous -0.047 -0.271 0.125 0.031 *

 year’s expenditures on plant maintenance and 

 operation

Dummy variable for zero values in log of revenue -0.139 0.037 0.039 0.352

 from state and local sources

Constant — 1.893 0.948 0.047 *

— Not applicable.

*Relatively strong relationship.

NOTE: “N” refers to the number of observations, not the number of institutions; each institution has one observation for each year.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data 

(IPEDS), Full Collection Years 1989 to 1996; Bureau of Economic Analysis, Regional Accounts Data, Personal Income for States:

1958–98, released July 1999.

Probability

Model 

significance
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

86

Table 29.—Coefficients for the simultaneous equation estimation of undergraduate tuition on selected

Table 29.—institutional and external characteristics for private not-for-profit comprehensive institutions:

Table 29.—1989–90 to 1995–96 

Equation 1 (“external” factors) 1344 0.178 0.595 0.000 *

Equation 2 (“internal” institutional factors) 1344 0.180 0.589 0.000 *

Equation 1

Log of first-time freshmen FTE students 0.076 13.2 0.011 0.000 *

Log of previous year’s instruction expenditures 0.148 6.8 0.016 0.000 *

Log of average tuition at public 4-year institutions 0.032 31.7 0.008 0.000 *

 in the state

Log of previous year’s expenditures on plant 0.005 212.5 0.005 0.380

 maintenance and transfers

Log of the proportion of undergraduates enrolled -0.002 -616.9 0.005 0.750

 in the state attending private not-for-profit 4-year 

 institutions 

Log of previous year’s research expenditures -0.012 -84.3 0.004 0.002 *

Log of previous year’s student service expenditures 0.032 30.9 0.012 0.005 *

Log of expenditures on institutional aid 0.245 4.1 0.009 0.000 *

Log of previous year’s student/faculty ratioa 0.037 26.9 0.012 0.001 *

Log of philanthropic revenuea -0.068 -14.6 0.006 0.000 *

Log of per capita income in the state 0.124 8.0 0.022 0.000 *

1991 0.001 — 0.017 0.945

1992 0.012 — 0.017 0.499

1993 0.006 — 0.017 0.718

1994 0.017 — 0.018 0.323

1995 0.022 — 0.018 0.217

1996 0.037 — 0.018 0.040 *

Dummy variable for zero values in log of previous year’s -0.040 — 0.013 0.002 *

 research expenditures

Dummy variable for zero values in log of previous year’s 0.048 — 0.048 0.313

 expenditures on plant maintenance and operation

Dummy variable for zero values in log of philanthropic -0.467 — 0.126 0.000 *

 revenue

Constant 4.402 — 0.274 0.000 *

variable) in tuition estimate Probability

Standard

independent percent change error of the

a 1 percent associated

change in the with a 1

tuition independent

associated with variable

Coefficient

(percentage Percentage

change in change in the

N error (RMSE) “R-squared” significance

Root mean

square Model
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

87

Table 29.—Coefficients for the simultaneous equation estimation of undergraduate tuition on selected

Table 29.—institutional and external characteristics for private not-for-profit comprehensive institutions:

Table 29.—1989–90 to 1995–96—Continued

Equation 2

Log of first-time freshmen FTE students 0.022 46.3 0.020 0.271

Log of instruction expenditures 0.083 12.0 0.016 0.000 *

Log of expenditures on institutional aid 0.252 4.0 0.009 0.000 *

Log of average faculty compensation 0.226 4.4 0.066 0.001 *

Log of institutional support expenditures -0.005 -215.2 0.014 0.736

Log of academic support expenditures -0.004 -226.8 0.006 0.492

Log of student services expenditures 0.025 39.8 0.013 0.049 *

Log of philanthropic revenue -0.079 -12.6 0.007 0.000 *

Log of federal grants and contracts 0.000 -4088.3 0.000 0.615

Log of revenue from state and local sources 0.001 682.4 0.002 0.420

Ratio of graduate FTE enrollment to total FTE -0.017 — 0.044 0.702

 enrollment

1991 -0.003 — 0.018 0.850

1992 0.005 — 0.018 0.797

1993 0.001 — 0.018 0.937

1994 0.021 — 0.018 0.251

1995 0.026 — 0.018 0.157

1996 0.049 — 0.018 0.008 *

Dummy variable for zero values in log of revenue from -0.008 — 0.010 0.414

 state and local sources

Dummy variable for zero values in log of federal grants 0.002 — 0.009 0.811

 and contracts

Dummy variable for zero values in log of philanthropic -0.527 — 0.130 0.000 *

 revenue

Constant 4.540 — 0.487 0.000 *

Endogenous variables: Log of undergraduate tuition; log of first-time freshmen FTE students

Exogenous variables: all other variables

—Not applicable.

*Relatively strong relationship.

a

These variables may be acting as suppressor variables in Equation 1. This could have resulted from a disordinal interaction effect, it

could be a statistical artifact of the sample, or the model could be misspecified.

NOTE: “N” refers to the number of observations, not the number of institutions; each institution has one observation for each year.

For logged independent variables, the second column is the reciprocal of the first. The coefficients of the dummy variables

for the years can be interpreted as the change in tuition since the base year (1990), adjusting statistically for the covariation of the

independent variables, by taking the inverse log (to base e) of the estimated coefficient and subtracting 1 from it. In the case of 

comprehensive institutions, for example, the change from 1990 to 1996 is 3.7 percent in Equation 1 and 5.0 percent in Equation 2.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System

(IPEDS), Full Collection Years 1989 to 1996; Bureau of Economic Analysis, Regional Accounts Data, Personal Income for States:

1958–98, released July 1999.

variable) in tuition estimate Probability

Standard

independent percent change error of the

a 1 percent associated

change in the with a 1

tuition independent

associated with variable

Coefficient

(percentage Percentage

change in change in the
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

88

• Price competition with the public sector. Higher tuitions were associated with higher

average tuition levels at public 4-year institutions in the state.

• Change over time. After adjusting statistically for the covariation of enrollment levels

and other independent variables in the equation, prices increased by 3.7 percent over

six years.

As in the case of research/doctoral institutions, the relationships between tuition and philanthropic revenue and tuition and the student/faculty ratio at comprehensive institutions were

contrary to the expected directions, which assumed that these variables could function as proxies

for institutional reputation and instructional quality, respectively.60

In Equation 2, tuition was unrelated to enrollment levels at comprehensive institutions.61 In

addition, several “internal” factors were associated with tuition at comprehensive institutions:

• Price of inputs. Higher tuitions at comprehensive institutions were associated with

higher expenditures, including instruction expenditures, institutional aid expenditures,

student services expenditures, and average faculty compensation levels. A 4.0 percent

increase in institutional aid, or a 4.4 percent increase in average faculty compensation

levels, was associated with a one percent increase in tuition.

• Availability of nontuition revenue. Higher tuition was associated with lower levels of

philanthropic revenue. After adjusting statistically for the covariation of other independent variables, a 12.6 percent decrease in philanthropic revenue was associated

with a one percent increase in tuition.

• Change over time. After accounting for enrollment and other independent variables in

the equation, prices increased by 5.0 percent over the six-year period.

The reduced form regression generally supports these findings, but did not show a relationship between tuition and student services expenditures. Some other independent variables were

related to tuition, however, including plant maintenance and transfers, academic support expenditures, and the ratio of graduate to total enrollment (table 30).

Bachelor’s Institutions

Over the period 1989–90 to 1995–96, the simultaneous equation model captured some of

the “external” and “internal” factors associated with prices at bachelor’s institutions, although

not as well as for the other two groups of institutions. In Equation 1 (representing “external”

 

60These variables may be acting as suppressor variables. This could have resulted from a disordinal interaction effect, it could be

a statistical artifact of the sample, or the model could be misspecified.

61This type of relationship might exist if the cost of educating additional students is relatively low and essentially constant, as for

schools with excess capacity; see Baum (1996).
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

89

Table 30.—Coefficients for the reduced form regression of undergraduate tuition on selected institutional

Table 30.—and external characteristics for private not-for-profit comprehensive institutions: 1989–90 to

Table 30.—1995–96

Model 1344 0.679 0.672 0.000 *

Log of previous year’s instruction expenditures 0.413 0.082 0.041 0.046 *

Log of average tuition at public 4-year institutions 0.416 0.174 0.016 0.000 *

 in the state

Log of previous year’s expenditures on plant 0.122 0.023 0.009 0.014 *

 maintenance and transfers

Log of the proportion of undergraduates enrolled 0.184 0.007 0.009 0.454

 in the state attending private not-for-profit 4-year

 institutions 

Log of previous year’s research expenditures 0.206 -0.011 0.004 0.011 *

Log of previous year’s student service expenditures 0.323 0.017 0.032 0.592

Log of expenditures on institutional aid 0.644 0.228 0.008 0.000 *

Log of previous year’s student/faculty ratio -0.163 0.038 0.022 0.083

Log of philanthropic revenue -0.061 -0.039 0.007 0.000 *

Log of per capita income in the state 0.386 0.250 0.042 0.000 *

Log of instruction expenditures 0.421 0.018 0.041 0.658

Log of average faculty compensation 0.536 0.279 0.037 0.000 *

Log of institutional support expenditures 0.284 0.011 0.016 0.491

Log of academic support expenditures 0.349 0.044 0.010 0.000 *

Log of student services expenditures 0.345 0.010 0.033 0.755

Log of federal grants and contracts 0.022 0.000 0.001 0.876

Log of revenue from state and local sources 0.183 -0.020 0.003 0.000 *

Ratio of graduate FTE enrollment to total FTE 0.187 0.143 0.050 0.004 *

 enrollment

1991 -0.125 -0.003 0.016 0.850

1992 -0.054 -0.013 0.017 0.439

1993 0.006 -0.028 0.017 0.100

1994 0.068 -0.028 0.017 0.101

1995 0.115 -0.032 0.018 0.069

1996 0.166 -0.027 0.018 0.131

Dummy variable for zero values in log of previous -0.234 -0.056 0.023 0.016 *

 year’s research expenditures

Dummy variable for zero values in log of previous 0.019 0.165 0.087 0.056

 year’s expenditures on plant maintenance and

 operation

Dummy variable for zero values in log of revenue -0.182 -0.057 0.017 0.001 *

 from state and local sources

Dummy variable for zero values in log of federal -0.048 0.002 0.015 0.879

 grants and contracts

Dummy variable for zero values in log of -0.012 -0.258 0.123 0.036 *

 philanthropic revenue

Constant — -0.668 0.467 0.153

—Not applicable.

*Relatively strong relationship.

NOTE: “N” refers to the number of observations, not the number of institutions; each institution has one observation for each year.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System

(IPEDS), Full Collection Years 1989 to 1996; Bureau of Economic Analysis, Regional Accounts Data, Personal Income for States:

1958–98, released July 1999.

Correlation

coefficient

with

dependent

variable

Reduced

form

coefficient

Standard

error of the

estimate Probability

significance

Model

N R-squared R-squared

Adjusted
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

90

factors), the independent variables explained about 47.5 percent of the variation in tuition; in

Equation 2 (representing “internal” factors), the independent variables explained 49.9 percent of

the variation (table 31).

In Equation 1, higher tuitions were associated with slightly higher first-time freshmen enrollments at bachelor’s institutions. In addition, variables representing “external” factors were

associated with tuition, including the following:

• Availability of financial aid. Higher tuitions were associated with higher institutional

aid at bachelor’s institutions. A 3.9 percent increase in institutional aid was associated

with a one percent increase in tuition.

• Proxies for quality of instruction. Higher tuitions were related to higher instruction expenditures. A 5.0 percent increase in instruction expenditures was associated with a

one percent increase in tuition.

• In-state consumer purchasing power. Higher tuitions were associated with higher per

capita incomes in the state.

• Competitive environment. Higher tuitions at bachelor’s institutions were associated

with both higher average tuition levels at public 4-year institutions in the state and

lower proportions of students enrolled at private institutions.

• Ancillary services. Higher tuitions were associated with higher expenditures per student on student services.

• Change over time. After adjusting statistically for the covariation of enrollment levels

and other independent variables in the equation, prices increased by 2.2 percent over

six years.

As in the case of the other two groups of institutions, the relationships between tuition and

philanthropic revenue and tuition and the student/faculty ratio at bachelor’s institutions were

contrary to the expected directions, which assumed that philanthropic revenue and student/faculty

ratios could function as proxies for institutional reputation and instructional quality, respectively.62

In Equation 2, higher tuitions at bachelor’s institutions were associated with higher enrollment levels. In addition, several “internal” factors were associated with tuition at bachelor’s institutions:

 

62These variables may be acting as suppressor variables. This could have resulted from a disordinal interaction effect, it could be

a statistical artifact of the sample, or the model could be misspecified.
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

91

Table 31.—Coefficients for the simultaneous equation estimation of undergraduate tuition on selected

Table 31.—institutional and external characteristics for private not-for-profit bachelor's institutions:

Table 31.—1989–90 to 1995–96

Equation 1 (“external” factors) 3157 0.384 0.475 0.000 *

Equation 2 (“internal” institutional factors) 3157 0.376 0.499 0.000 *

Equation 1

Log of first-time freshmen FTE students 0.154 6.5 0.018 0.000 *

Log of previous year’s instruction expenditures 0.198 5.0 0.017 0.000 *

Log of average tuition at public 4-year institutions 0.058 17.3 0.014 0.000 *

 in the state

Log of previous year’s expenditures on plant -0.015 -68.8 0.008 0.060

 maintenance and transfers

Log of the proportion of undergraduates enrolled -0.022 -45.6 0.010 0.036 *

 in the state attending private not-for-profit 4-year 

 institutions 

Log of previous year’s research expenditures 0.001 677.1 0.003 0.658

Log of previous year’s student service expenditures 0.050 19.8 0.012 0.000 *

Log of expenditures on institutional aid 0.256 3.9 0.010 0.000 *

Log of previous year’s student/faculty ratioa 0.032 31.6 0.014 0.028 *

Log of philanthropic revenuea -0.077 -13.0 0.009 0.000 *

Log of per capita income in the state 0.195 5.1 0.037 0.000 *

1991 0.000 — 0.024 0.986

1992 -0.005 — 0.024 0.819

1993 -0.001 — 0.024 0.983

1994 0.000 — 0.024 0.997

1995 0.013 — 0.025 0.583

1996 0.022 — 0.025 0.382

Dummy variable for zero values in log of previous year’s 0.006 — 0.017 0.707

 research expenditures

Dummy variable for zero values in log of previous year’s -0.116 — 0.062 0.062

 expenditures on plant maintenance and operation

Dummy variable for zero values in log of FTE students 0.904 — 0.202 0.000 *

Dummy variable for zero values in log of expenditures 1.646 — 0.117 0.000 *

 on institutional aid

Dummy variable for zero values in log of undergraduate -9.264 — 0.357 0.000 *

 tuition

Dummy variable for zero values in log of previous 0.335 — 0.187 0.072

 year’s student service expenditures

Constant 2.560 — 0.454 0.000 *

Percentage

Probability

percent change

associated

variable

with a 1

in tuition

Standard

error of the

estimate

independent

change in the

a 1 percent

variable)

Coefficient

change in

change in the

independent

(percentage

tuition

associated with

significance

square Model

Root mean

N error (RMSE) “R-squared”
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

92

Table 31.—Coefficients for the simultaneous equation estimation of undergraduate tuition on selected

Table 31.—institutional and external characteristics for private not-for-profit bachelor's institutions:

Table 31.—1989–90 to 1995–96—Continued

Equation 2

Log of first-time freshmen FTE students 0.074 13.4 0.034 0.028 *

Log of instruction expenditures 0.158 6.3 0.018 0.000 *

Log of expenditures on institutional aid 0.252 4.0 0.011 0.000 *

Log of average faculty compensation 0.281 3.6 0.082 0.001 *

Log of institutional support expenditures -0.001 -1378.4 0.015 0.962

Log of academic support expenditures -0.001 -1743.1 0.008 0.941

Log of student services expenditures 0.038 26.1 0.014 0.007 *

Log of philanthropic revenue -0.099 -10.1 0.009 0.000 *

Log of federal grants and contracts 0.001 1440.9 0.001 0.270

Log of revenue from state and local sources 0.001 1638.3 0.002 0.770

Ratio of graduate FTE enrollment to total FTE -0.051 — 0.079 0.520

 enrollment

1991 -0.006 — 0.024 0.800

1992 -0.006 — 0.024 0.796

1993 0.005 — 0.024 0.821

1994 0.015 — 0.024 0.527

1995 0.030 — 0.024 0.218

1996 0.049 — 0.024 0.040 *

Dummy variable for zero values in log of revenue from -0.016 — 0.011 0.152

 state and local sources

Dummy variable for zero values in log of federal grants 0.000 — 0.009 0.995

 and contracts

Dummy variable for zero values in log of FTE students 0.481 — 0.253 0.058

Dummy variable for zero values in log of on institutional -9.171 — 0.354 0.000 *

 aid

Dummy variable for zero values in log of expenditures 1.627 — 0.118 0.000 *

 undergraduate tuition

Dummy variable for zero values in log of student 0.357 — 0.188 0.057

 service expenditures

Constant 3.028 — 0.514 0.000 *

Endogenous variables: Log of undergraduate tuition; log of first-time freshmen FTE students

Exogenous variables: all other variables

—Not applicable.

*Relatively strong relationship.

a

These variables may be acting as suppressor variables in Equation 1. This could have resulted from a disordinal interaction effect, it

could be a statistical artifact of the sample, or the model could be misspecified.

NOTE: "N" refers to the number of observations, not the number of institutions; each institution has one observation for each year.

For logged independent variables, the second column is the reciprocal of the first. The coefficients of the dummy variables

for the years can be interpreted as the change in tuition since the base year (1990), adjusting statistically for the covariation of the

independent variables, by taking the inverse log (to base e) of the estimated coefficient and subtracting 1 from it. In the case of 

bachelor's institutions, for example, the change from 1990 to 1996 is 2.2 percent in Equation 1 and 5.1 percent in Equation 2.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System

(IPEDS), Full Collection Years 1989 to 1996; Bureau of Economic Analysis, Regional Accounts Data, Personal Income for States:

1958–98, released July 1999.

Coefficient

(percentage Percentage

change in change in the

tuition independent

associated with variable

a 1 percent associated

change in the with a 1 Standard

independent percent change error of the

variable) in tuition estimate Probability
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

93

• Price of inputs. Higher tuitions at bachelor’s institutions were associated with higher

expenditures, including instruction expenditures, institutional aid expenditures, student

services expenditures, and average faculty compensation levels. A 3.6 percent increase

in average faculty compensation levels, a 4.0 percent increase in institutional aid, or a

6.3 percent increase in instruction expenditures—controlling for all of the other independent variables—was associated with a one percent increase in tuition.

• Availability of nontuition revenue. Higher tuition was associated with lower levels of

philanthropic revenue. A 10.1 percent decrease in philanthropic revenue was associated with a one percent increase in tuition.

• Change over time. After controlling for enrollment and other independent variables in

the equation, prices increased by 5.1 percent over the six-year period.

The results of the reduced form equation generally support these findings. While the student/faculty ratio was not related to tuition, several other factors were, including plant maintenance and transfers, research expenditures, institutional support expenditures, and the ratio of

graduate to total enrollment (table 32).

Discussion

Across the three groups of private not-for-profit institutions, the trend analysis found that,

on average, undergraduate tuition rose in inflation-adjusted terms and that gross tuition revenue

accounted for increasing proportions of total E&G revenue over the period 1988–89 to 1995–96

(table 33). At the same time, the proportion of revenue from endowment income and private

gifts, grants, and contracts decreased. On the expenditure side, instruction expenditures continued to constitute the largest proportion of total E&G expenditures, while institutional scholarships and fellowships was one of the fastest growing expenditure categories and made up an

increasing proportion of total E&G expenditures.

The models suggest that pricing decisions at private not-for-profit institutions over the period 1989–90 to 1995–96 were related to both “internal” institutional budget circumstances

(which are reflected in aggregate in the trend data) and “external” factors (table 34). At research/doctoral institutions, for example, higher institutional costs—especially institutional aid

and average faculty compensation levels—and lower levels of revenue from nontuition sources,

such as endowment income and private gifts, grants, and contracts, were associated with higher

levels of undergraduate tuition. At the same time, variables representing “external” factors also

were related to tuition levels, such as the price of attending public institutions in the same state,

in-state consumer purchasing power (as measured by average per capita state income), and the

availability of financial aid for students (as measured by institutional aid expenditures). Similar

results were found for private not-for-profit comprehensive and bachelor’s institutions, although
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

94

Table 32.—Coefficients for the reduced form regression of undergraduate tuition on selected institutional

Table 32.—and external characteristics for private not-for-profit bachelor's institutions: 1989–90 to 1995–96

Adjusted Model

N R-squared R-squared significance

Model 3157 0.589 0.585 0.000* 

Correlation

coefficient

with Reduced Standard

dependent form error of the

variable coefficient estimate Probability

Log of previous year’s instruction expenditures 0.527 0.141 0.046 0.002* 

Log of average tuition at public 4-year institutions in the state 0.400 0.203 0.024 0.000* 

Log of previous year’s expenditures on plant maintenance and transfers 0.184 -0.081 0.012 0.000* 

Log of the proportion of undergraduates enrolled in the state 0.269 -0.017 0.014 0.226 

 attending private not-for-profit 4-year institutions

Log of previous year’s research expenditures 0.356 0.024 0.007 0.000* 

Log of previous year’s student service expenditures 0.403 0.021 0.034 0.540 

Log of expenditures on institutional aid 0.457 0.164 0.011 0.000* 

Log of previous year’s student/faculty ratio -0.272 0.041 0.031 0.179 

Log of philanthropic revenue 0.151 -0.126 0.011 0.000* 

Log of per capita income in the state 0.410 0.359 0.062 0.000* 

Log of instruction expenditures 0.535 0.056 0.047 0.233 

Log of average faculty compensation 0.591 0.489 0.045 0.000* 

Log of institutional support expenditures 0.330 0.068 0.020 0.001* 

Log of academic support expenditures 0.404 0.027 0.013 0.046* 

Log of student services expenditures 0.416 0.112 0.034 0.001* 

Log of federal grants and contracts 0.079 0.000 0.001 0.974 

Log of revenue from state and local sources 0.188 -0.023 0.004 0.000* 

Ratio of graduate FTE enrollment to total FTE enrollment 0.120 0.212 0.093 0.023* 

1991 -0.063 -0.002 0.023 0.916 

1992 -0.028 -0.035 0.023 0.134 

1993 -0.007 -0.040 0.023 0.091 

1994 0.035 -0.047 0.024 0.048* 

1995 0.062 -0.040 0.024 0.094 

1996 0.086 -0.039 0.025 0.111 

Dummy variable for zero values in log of previous year’s research expenditures -0.319 0.029 0.033 0.376 

Dummy variable for zero values in log of previous year’s expenditures on 

 plant maintenance and operation

-0.043 -0.724 0.109 0.000* 

Dummy variable for zero values in log of revenue from state and local sources -0.213 -0.114 0.024 0.000* 

Dummy variable for zero values in log of federal grants and contracts -0.067 0.043 0.018 0.016* 

Dummy variable for zero values in log of expenditures on institutional aid -0.048 1.087 0.117 0.000* 

Dummy variable for zero values in log of undergraduate tuition -0.310 -8.753 0.343 0.000* 

Dummy variable for zero values in log of student service expenditures 0.024 0.793 0.427 0.064 

Dummy variable for zero values in log of previous year’s student service 

 expenditures

0.024 0.098 0.428 0.819 

Constant — -4.387 0.626 0.000* 

—Not applicable.

*Relatively strong relationship.

NOTE: “N” refers to the number of observations, not the number of institutions; each institution has one observation for each year.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System

(IPEDS), Full Collection Years 1989 to 1996; Bureau of Economic Analysis, Regional Accounts Data, Personal Income for States:

1958–98, released July 1999.
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

95

Table 33.—Summary of inflation-adjusted trends in tuition and selected revenue and expenditures categories

Table 33.—at private not-for-profit institutions: 1988–89 to 1995–96

Research/doctoral Comprehensive Bachelor's

Average annual percent change in in-state

 undergraduate tuition for FY, FT students

3.6 4.1 3.7 

Tuition revenue:

 Average annual percent change 3.5 3.8 3.4 

 Average proportion of total E&G revenue 49.0 72.0 64.1 

 Percentage point change as a proportion of 

 total E&G revenue 

1.3 5.1 4.2 

Revenue from endowment and private gifts:

 Average annual percent change, endowment 

 income

1.4 -1.0 1.5 

 Average annual percent change, private gifts 1.8 -0.2 1.1 

 Average proportion of total E&G revenue, 

 both sources 

18.1 11.6 21.7 

 Percentage point change as a proportion of 

 total E&G revenue, both sources 

-2.0 -3.1 -2.2 

Instruction expenditures:

 Average annual percent change 3.3 1.9 2.0 

 Average proportion of total E&G expenditures 36.0 32.7 28.7 

 Percentage point change as a proportion of 

 total E&G expenditures 

0.3 -1.9 -0.8 

Scholarships and fellowships expenditures:

 Average annual percent change 6.7 6.6 5.4 

 Average proportion of total E&G expenditures 12.8 20.4 23.4 

 Percentage point change as a proportion of 

 total E&G expenditures 

3.0 5.0 4.5 

 Average annual percent change in 

 institutional scholarships and fellowships

8.7 10.2 8.5 

NOTE: Dollar amounts were converted to constant 1999 dollars using the CPI-U (1982–84 = 100) before annual changes were

calculated. Average percentage changes were calculated as averages of the annual changes. All revenue and expenditure

categories are per full-time equivalent (FTE) student. Shares of total revenues and expenditures were calculated as averages over

the eight-year period.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data

System (IPEDS), Full Collection Years 1989 to 1996.

there were some differences in the costs that were found to have a relationship with tuition. In

particular, instruction expenditures were related to tuition at private not-for-profit comprehensive

and bachelor’s institutions.

In general, the results of the model were comparable with those of the original Westat/Pelavin study, suggesting that many of the factors associated with prices at private not-for-
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

96

Table 34.—Significant relationships with undergraduate tuition at private not-for-profit institutions:

Table 34.—1989–90 to 1995–96

Research/

doctoral Comprehensive Bachelor's

Equation 1 (“external” factors):

Log of first-time freshmen FTE students ***

Log of previous year’s instruction expenditures * *

Log of average tuition at public 4-year institutions in the state ***

Log of previous year’s expenditures on plant maintenance and transfers

Log of the proportion of undergraduates enrolled in the state attending *

 private not-for-profit 4-year institutions 

Log of previous year’s research expenditures * *

Log of previous year’s student service expenditures ***

Log of expenditures on institutional aid ***

Log of previous year’s student/faculty ratio ***

Log of philanthropic revenue ***

Log of per capita income in the state ***

Equation 2 (“internal” institutional factors):

Log of first-time freshmen FTE students * *

Log of instruction expenditures * *

Log of expenditures on institutional aid ***

Log of average faculty compensation ***

Log of institutional support expenditures *

Log of academic support expenditures

Log of student services expenditures * *

Log of philanthropic revenue ***

Log of federal grants and contracts *

Log of revenue from state and local sources *

Ratio of graduate FTE enrollment to total FTE enrollment *

*Relatively strong relationship.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data

(IPEDS), Full Collection Years 1989 to 1996; Bureau of Economic Analysis, Regional Accounts Data, Personal Income for 

States: 1958–98, released July 1999.

profit institutions in the late 1980s continued to be related in the 1990s. As in the original study,

the model results suggest that the three groups of institutions—research/doctoral, comprehensive,

and bachelor’s institutions—face different competitive environments and institutional budgeting

decisions. Various cost elements were related to tuition, but differently for specific types of private not-for-profit institutions. Nontuition revenue was related to prices at research/doctoral institutions, where nontuition revenue makes up a higher proportion of total E&G revenue on

average. Institutional aid was related to tuition levels at all three groups of institutions, but made

up higher proportions of total E&G expenditures at comprehensive and bachelor’s institutions,

which may face more competitive environments.
Chapter IV: Revenues, Expenditures, and Prices at Private Not-for-Profit Four-Year Institutions

97

In considering these findings, it is important to keep in mind that many of the variables included in the models were acting as proxies for expected relationships. Given an improved ability

to measure certain factors, the model results would likely differ to an unknown extent. Nonetheless, the results of the models are generally consistent with theoretical expectations regarding the

institutional budget constraints and external, competitive environments faced by private not-forprofit institutions.
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99

Chapter V: Financial Aid and Prices at Higher Education

Institutions

This chapter focuses on the last analytical component of Phase I of the NCES Study of

College Costs and Prices, an analysis of the potential relationship of financial aid to prices. In the

1998 mandate, Congress asked NCES to explore how institutional financial aid affects price increases, and the extent to which federal financial aid is involved in this relationship. To fully address this question, two conditions are important: 1) the development (or determination) of

appropriate theoretical models of institutional behavior given relationships among prices, institutional aid, federal aid, and other relevant factors, by type of aid and for different groups of institutions; and 2) the availability of data that measure these relationships over time at the

institutional level. Neither of these conditions is satisfactorily met. Although the analysis presented in this chapter cannot fully answer the questions posed by Congress, it contributes to the

knowledge framing the debate by combining a discussion of the current status of research models

and available data with an analysis of newly available data on tuition and financial aid at public

and private not-for-profit institutions.

The following sections first highlight the previous theoretical and empirical work conducted in this area, including different perspectives about the nature of the relationship between

various forms of financial aid and prices at colleges and universities. Some of the limitations of

currently available data are then described, along with the impact of these limitations on research

models. Finally, the results of a series of correlational linear regression models are presented,

using recent data on tuition and aid packaging that were collected as a result of a mandate in the

1998 amendments.

Review of Previous Work

The issue of whether various forms of financial aid “cause” tuition increases remains unresolved. Since the mid-1980s, some analysts and policymakers have argued that increases in the

availability of federal aid provide incentives to institutions to increase tuition levels. According

to this perspective, although the incentives may have lessened in recent years—particularly in aid

programs in which most students already receive the maximum amounts—federal aid may still

“enable” tuition increases by making college attendance more affordable, therefore increasing

demand. Others have argued that most higher education institutions do not function like for-
Chapter V: Financial Aid and Prices at Higher Education Institutions

100

profit entities, since all students in public and private not-for-profit institutions receive a “discount” on full prices because of public or institutional subsidies. Institutions may choose instead

to use increased aid subsidies to lower their tuition levels. Still others have argued that a theoretical basis for the relationship between the volume of federal loan aid (as opposed to loan terms

and conditions) and price cannot be established.63 In the 1990s, the debate appears to have differentiated between types of aid and become focused on the possible relation of federal loan aid to

price.64

Federal Grant Aid and Tuition

Given that grant aid directly decreases the net price paid by students,65 some have surmised

that colleges would raise their tuition to capture additional grant aid dollars if they could. In one

study, McPherson and Schapiro (1991) tested the hypothesis that increases in federal student aid

are related to increased tuition growth. Using data from academic years 1978–79 and 1985–86,

they developed a simultaneous-equations model of various institutional choices, using changes in

per student levels of various financial variables including tuition and federal grant aid. They

found no evidence of a relationship between federal grant aid and tuition increases for private

not-for-profit 4-year institutions. They did find, however, that during this time period public 4-

year institutions tended to raise tuition by $50 for every $100 increase in federal student aid. This

finding was consistent with their hypothesis that only public institutions would have tuition levels that would give them an incentive to increase tuition to capture additional student aid.66

More recently, however, McPherson and Schapiro have cautioned that those incentives may

no longer exist, given current public tuition levels and federal aid maximums. A subsequent

analysis by Coopers and Lybrand (1997), using data for academic years 1989–90 and 1994–95,

appeared to confirm McPherson and Schapiro’s results regarding the lack of a relationship between changes in federal aid and changes in tuition at private not-for-profit institutions. The

findings regarding public 4-year institutions were weak, and the authors felt that the relationship

between federal grants and tuition may no longer hold. This research was persuasive to the Na-

 

63There also exists a theoretical difficulty in establishing the proper incentive valuation for loans.

64For discussions of different aspects of these arguments, see Winston (1998); McPherson and Schapiro (1991, 1998);

Hauptman and Krop (1998).

65Although not necessarily on a dollar-for-dollar basis because of other institutional decisions, such as institutional aid; see

Turner (1998).

66The average awards in the Federal Pell Grant program are relatively low and “only in the rare case where Pell meets full need

below the maximum would an increase in a college’s tuition allow that student to receive a larger Pell grant” (McPherson and

Schapiro 1998, p. 83). Turner (1998) also postulates that the greatest pressure on sticker price would occur at institutions that

have a price of attendance below the maximum award amount, as well as at institutions that have considerable market power or a

high percentage of Pell Grant eligible students. Another way to look at this issue would be to examine the proportion of aid recipients who are “maxed-out,” and therefore raising tuition would not bring additional aid dollars into the institutions for those

students.
Chapter V: Financial Aid and Prices at Higher Education Institutions

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tional Commission on the Cost of Higher Education in its report to Congress in 1998, which concluded that the evidence showed no relationship between federal grant aid and prices. Nevertheless, some methodological drawbacks to these studies have been noted,67 and the studies did not

explicitly address the issue of a possible impact through student demand. The issue is unlikely to

be fully resolved until better data become available and/or more research is conducted.

Federal Student Loans and Tuition

Research on the possible relationship of federal loan aid to prices has been even less conclusive, suggesting that if such a relationship does exist, it may be indirect. Some researchers

have pointed to the fact of rapidly escalating loan volumes and increases in college prices over

time. In a paper prepared for the National Commission on the Cost of Higher Education,

Hauptman and Krop (1998) used trend data to support a theory that the increases in availability

of revenue through growth in federal loan volume has “facilitated the ability” of colleges and

universities, especially private ones, to raise tuition and engage in the practice of tuition discounting. Other researchers failed to find evidence to support the theory. The Coopers and Lybrand study, which tested the relation between federal aid and tuition (based on McPherson and

Schapiro’s model) but also included data on student loan subsidies, found a small negative relationship in the private not-for-profit 4-year sector but no relationship in the public 4-year sector.

After reviewing the available research, the Cost Commission decided that the research did not

allow them to reach a definitive conclusion about the possible relation of federal loan aid to college prices.68

To complicate the issue, loan volume may not affect tuition levels directly, but rather may

influence student demand through the impact of loan terms and conditions (e.g., interest rates).

Economic theory assumes the existence of capital markets—in other words, financing mechanisms, such as consumer loans, are available to allow economic transactions—while loan terms

and conditions may affect prices through their impact on consumer preferences (leading to shifts

in the demand curve). However, to date empirical research has not attempted to model this system of relationships.

A recent study (Berkner 2000) examined the issue from the perspective of students’ increasing demand for student loans due to higher costs of attendance. According to the study,

which looked at public and private not-for-profit 4-year institutions over two periods (1989–90 to

 

67For example, both studies were based on changes measured between two specific years, and some relevant variables may not

have been included in the models. See Oberg (1997); Pearson and Baldi (1998).

68Note that increased loan volume might reflect students’ choices about how to fund their non-tuition costs. As noted by

Johnstone in his commissioned paper (see Volume 2), most of these non-tuition costs are outside the control of the institution or

government, and would be incurred regardless of whether or not the student attended college.
Chapter V: Financial Aid and Prices at Higher Education Institutions

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1992–93 and 1992–93 to 1995–96), the borrowing rates of full-time, first-time undergraduates

did not vary directly with tuition levels. For public institutions, the average increases in tuition

were the same in both periods, while the increases in borrowing were much greater during the

second period. In addition, borrowing rates increased to similar levels regardless of the tuition

level. At private not-for-profit institutions, tuition increases were greater during the first period,

while borrowing rates and average loan amounts were greater during the second period. With

some exceptions, borrowing rates increased to similar levels regardless of whether tuition was

relatively low or high.

Federal Tax Credits and Tuition

A relatively new issue related to federal aid and prices has been added to the mix, with the

federal tuition tax credits enacted in 1997. Several analysts have speculated that the tax credits

will provide incentives to institutions and states to increase their tuitions and/or to change their

financial aid policies.69 The data that would allow this issue to be researched empirically are not

yet available; therefore, to date it has not been addressed in the research literature.

Institutional Aid, Federal Aid, and Tuition

Regardless of whether institutional aid is viewed as a reduction in the price faced by students (a price discount) or as an expenditure item, it is inextricably bound up in the debate surrounding college prices and financial aid. The use of institutional financial aid to discount tuition

has become a complex but important part of understanding institutional financing, especially

among private not-for-profit institutions. Several studies have documented the recent increases in

institutional aid as well as comparative trends in net prices, gross revenue trends, enrollment

trends, and other factors at private not-for-profit institutions.70 Nevertheless, little research has

been done that examines the direct and indirect relationships among these factors as well as financial aid, accounting for all of the relevant interrelationships, in large part due to the lack of

national data that would allow such analysis.71

Many observers have postulated that tuition levels might have risen less if less revenue had

been put into institutional aid. The results presented in the previous two chapters of this report

provide support for a positive correlation between changes in institutional aid expenditures and

 

69See for example Conklin (1998); Kane (1999); Wolanin (2001).

70Evidence presented in the commissioned paper submitted by Lapovsky (presented in Volume 2 of this study, along with the

other commissioned papers) highlights recent increases in tuition discounting. Also see Redd (2000) for a discussion of tuition

discounting compared with net tuition revenue, enrollment, and other factors at private not-for-profit institutions.

71The practice of discounting also has implications for access, borrowing, and other factors that complicate the issue.
Chapter V: Financial Aid and Prices at Higher Education Institutions

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changes in price—in other words, larger increases in expenditures on institutional aid are associated with larger increases in tuition.72 For private not-for-profit 4-year institutions, a simultaneous equations model found institutional aid to have a positive relationship with tuition for

research/doctoral, comprehensive, and bachelor’s institutions. For public institutions, a correlational regression model found that changes in institutional aid expenditures had a positive association with changes in tuition for research/doctoral and comprehensive institutions.73 However,

a simple correlation over time between nominal tuition and institution aid in the aggregate cannot

capture the whole picture of whether institutional grants are “driving” tuition increases;74 ideally,

net prices should be examined in a more complex model capturing the simultaneous relationships

among net prices, sticker prices, costs, enrollment demand, and other factors.

Various arguments also have been made regarding the effect of federal aid on the use of institutional aid by higher education institutions. Federal aid may offset or substitute for an

institution’s own financial aid through the aid packaging process, thereby allowing the institution

to reduce or shift its aid spending. In some cases, federal aid such as matching grants may actually encourage higher levels of institutional aid.75 The available evidence is conflicting. In their

paper, Hauptman and Krop (1998) argue that the growing availability of federal loans made it

possible for a “high tuition/high aid” strategy at many private not-for-profit institutions, in which

loans made up a large proportion of the greater amount of aid required by students who became

“needy” as a result of the higher prices being charged. McPherson and Schapiro’s (1991) analysis

found a relationship between increases in federal grant aid and increases in institutional aid

spending at private not-for-profit institutions. They hypothesized that these institutions do not

use federal aid—at least, federal grants—as a substitute for institutional aid, but rather as a complement. The Coopers and Lybrand (1997) study also found a positive relationship between federal grant aid and institutional aid at private not-for-profit institutions, but found a small

redistribution of institutional aid to needy students for public 4-year institutions.

It is likely that the relationship between federal aid and institutional aid depends on the type

of aid as well as the specific characteristics of institutions. For example, results of research by

Oberg (1997) suggest that different federal grant aid programs may have different effects on institutional aid; Pell Grants offset institutional aid, while campus-based grants that have matching

requirements spurred increases in institutional aid. The effect of student loans on institutional aid

 

72The models, which were updates of previous models, did not include any other forms of financial aid.

73The model found a negative correlation between changes in institutional aid and tuition for the small number of public bachelor’s institutions, suggesting that institutional aid was acting as a suppressor variable.

74In fact, in the public sector, a positive association between nominal tuition and institutional aid may signal that net prices faced

by students are falling, because institutional grants at some institutions would need to be financed out of nontuition revenue.

75For example, because of the increased need to support needy students with institutional resources; see McPherson and Schapiro (1998).
Chapter V: Financial Aid and Prices at Higher Education Institutions

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is not clear and has not been addressed by much research. At the same time, in presenting a theoretical framework for how the allocation of financial aid by institutions might adjust to an infusion of federal subsidies (Pell Grants), Turner (1998) suggests that outcomes will vary depending

on institutions’ initial resource levels and preferences for need-based financial aid.76 In thinking

about this issue, it is also helpful to consider the extent of the overlap of aid recipients. Even if

every dollar of aid was offset, not all students receive both federal and institutional aid; therefore,

there would still be a reduction in the aggregate net prices paid.

Interrelationships Among Factors

The above-mentioned relationships are likely to be further complicated by simultaneous

interrelationships. As noted by Pearson and Baldi (1998), correlations between financial aid and

tuition may (or may not) appear to exist, but in any case the “true” relationships are probably not

direct links. There may be simultaneous effects of changes in revenue on expenditures, of expenditures on tuition, of institutional aid on tuition, of tuition on institutional aid, of federal aid on

tuition, of federal aid on institutional aid, of tuition on student need, and many other factors.

Thus, any analysis of the impact of changes in financial aid on tuition needs to recognize that

other factors influence tuition, not solely those related to institutional behavior.

For example, when external financial aid does not meet student need, there may be increased demand for institutionally funded aid. This is consistent with the hypothesis that when

federal student aid is falling, institutions will increase tuition in order to pay for more institutional aid (and vice versa: in times of increasing federal aid, this suggests that the rate of increase

in tuition will be slower). The complication, however, is that increases in federal aid may simultaneously increase the need for additional institutional aid, if they encourage additional lowincome students to enroll. The direct net effect of increased federal aid on institutional aid, and

its indirect effect on tuition, is therefore unclear a priori. A longitudinal structural model that

takes into account the relationships among independent variables would be necessary to fully unravel these relationships (Pearson and Baldi 1998). Estimation of such a model, however, requires that variables can be defined and measured with available data.

 

76Although the Pell program increases the total reservoir of funds available for financial aid, it does not reduce net costs equally

across different types of institutions. A dollar for dollar reduction in the net cost to students would occur only under very restrictive assumptions. The Pell subsidy changes the effective budget constraint, and the initial position of the institution is relevant to

the outcome. Institutions with large financial aid budgets before the introduction of Pell subsidies would have smaller changes in

net cost. See Turner (1998).
Chapter V: Financial Aid and Prices at Higher Education Institutions

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Data and Methods

In 1999, NCES administered the Institutional Prices and Student Financial Aid Survey

(IPSFA) for the first time, a new web-based survey that attempted to capture recent data on tuition and financial aid packaging for each college and university, including the percentage of students receiving federal grants, state grants, institutional grants, and student loans, as well as the

average amounts received. The data focus on first-time, full-time, degree/certificate-seeking undergraduates. This new data collection was initiated in response to the 1998 HEA amendments,

which mandated that NCES improve its data collection process and make timely data available to

parents and students in an easily understandable format. These new data provide an opportunity

to re-examine the possibility of a relationship between financial aid and tuition in the late 1990s

on a preliminary basis.

To understand existing patterns of student aid at higher education institutions, descriptive

statistics are presented in the following section for each of seven institutional types: private notfor-profit 4-year institutions (divided into research/doctoral, comprehensive, and bachelor’s institutions), public 4-year institutions (also divided into research/doctoral, comprehensive, and

bachelor’s institutions), and public 2-year institutions. These statistics include the average percentage of undergraduates receiving each type of aid, as well as the average amounts of aid received by these students. In addition, data are provided on the average numbers of first-time, fulltime, degree/certificate-seeking undergraduates and changes in the typical amount of tuition

charged to these students.

The data were analyzed through linear regression procedures in order to explore the relationship, if any, between the change in tuition over time (the dependent variable) and aid packaging, while accounting for other variables such as changes in revenues/expenditures, student

characteristics, market characteristics, and other independent variables. The model attempts to

identify variables associated with larger or smaller tuition increases, i.e., the characteristics of

institutions with larger or smaller tuition increases, but does not attempt to identify the potential

interdependence among decisions to increase tuition and other decisions related to expenditures,

revenues, and institutional aid. Therefore, the findings must be interpreted within the context of a

dynamic decisionmaking environment that involves indirect as well as direct effects.

The seven groups of institutions were examined separately. In each of these models, the

following variables from the IPSFA dataset were included:
Chapter V: Financial Aid and Prices at Higher Education Institutions

106

• Dependent variable: Real dollar change in in-state tuition for first-time, full-time, degree/certificate-seeking undergraduates77

• Independent variables:

• Tuition level in the base year

• Number of first-time, full-time, degree/certificate-seeking undergraduates

• Percentage of undergraduates who are first time, full time, and seeking a degree or

certificate, multiplied times the percentage of first-time, full-time, degree/certificate-seeking undergraduates who received aid from any source

• Percentage of first-time, full-time, degree/certificate-seeking undergraduates receiving federal grants multiplied times the average amount received

• Percentage of first-time, full-time, degree/certificate-seeking undergraduates receiving state grants multiplied times the average amount received

• Percentage of first-time, full-time, degree/certificate-seeking undergraduates receiving institutional grants multiplied times the average amount received

• Percentage of first-time, full-time, degree/certificate-seeking undergraduates receiving student loans multiplied times the average amount received

Although variables measuring the change in financial aid over time would be more appropriate, only one year of aid data was available at the time of this analysis. These variables were

included in the models in order to test the theory that financial aid is related to changes in tuition

levels, while controlling for some additional variables that are relevant to pricing decisions. Additional independent variables were added to each model in order to capture factors, other than

financial aid, that appear to be associated with pricing decisions (see table 35 for the list of variables.)

The choice of these variables took into account the models and results presented in Chapters III and IV. The following bullets describe the basis for the additional variables chosen for the

financial aid models presented in this chapter, for each type of institution:

• For private not-for-profit 4-year institutions, the chosen variables had relationships

with undergraduate tuition in the reduced form models presented in Chapter IV. In

these cases, the independent variables were expected to be associated with the pricing

decisions of these institutions, and the results of the Chapter IV models appeared to

 

77In general, in-state tuition does not differ much, if at all, from out-of-state tuition at private not-for-profit institutions. In fact,

in 1999–2000, in-state differed from out-of-state undergraduate tuition at only 4 of the 770 private not-for-profit institutions

included in the universe, and the average tuition levels differed by less than one-half of one percent. Therefore, although the variable for in-state tuition was used in the analysis, it is referred to here simply as undergraduate tuition when it applies to private

not-for-profit institutions.
Chapter V: Financial Aid and Prices at Higher Education Institutions

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Table 35.—Variables included in the financial aid regression models

INSTATCH Dollar change in in-state tuition for first-time, full-time undergraduates, 1997–98 to 1999–2000, 

in constant dollars (dependent variable)

INSTAC98 1997–98 tuition, in constant dollars

FTUG99 Number of first-time, full-time, degree/certificate-seeking undergraduates in 1999

FTUGAP2 Percentage of first-time, full-time, degree/certificate-seeking undergraduates who receive any aid 

times the percentage of first-time, full-time, degree/certificate-seeking undergraduates

FEDGPAC Percentage of first-time, full-time, degree/certificate-seeking undergraduates receiving federal 

grants times the average amount received, in constant dollars

STGPAC Percentage of first-time, full-time, degree/certificate-seeking undergraduates receiving state 

grants times the average amount received, in constant dollars

INGPAC Percentage of first-time, full-time, degree/certificate-seeking undergraduates receiving 

institutional grants times the average amount received, in constant dollars

LOANPAC Percentage of first-time, full-time,degree/certificate-seeking undergraduates receiving student 

loans times the average amount received, in constant dollars

ACADIFF Dollar change in academic support expenditures, in constant dollars (1995–96 to 1997–98 for 

publics, 1993–94 to 1995–96 for private not-for-profit)

AVC2DIFF Dollar change in average faculty compensation, in constant dollars (1995–96 to 1997–98 for 

private not-for-profit)

AVTFDIFF Dollar change in average tuition at public four-year institutions in the state, in constant dollars 

(1995–96 to 1997–98 for private not-for-profit)

FDGRDIFF Dollar change in revenue from federal grants and contracts, in constant dollars (1995–96 to 

1997–98 for publics, 1993–94 to 1995–96 for private not-for-profit); for private not-for-profit, 

less federal aid

INSPDIFF Dollar change in institutional support expenditures, in constant dollars (1995–96 to 1997–98 for 

publics, 1993–94 to 1995–96 for private not-for-profit)

INSTDIFF Dollar change in instruction expenditures, in constant dollars (1995–96 to 1997–98 for publics, 

1993–94 to 1995–96 for private not-for-profit)

LOCALE Degree of urbanicity of the institution, where 1=large city, 2=mid-size city, 3=urban fringe of 

large city, 4=urban fringe of mid-size city, 5=large town, 6=small town, 7=rural (public twoyears)

PCTCERT Percentage of awards granted in 1996–97 that were certificates (public two-years)

PERFT98R Percent of total fall 1998 enrollment that was full time (publics)

PERMIN98 Percent of total fall 1998 enrollment that was minority (publics)

PHILDIFF Dollar change in revenue from endowment and private gifts, in constant dollars (1993–94 to 

1995–96 for private not-for-profit)

PLNTDIFF Dollar change in plant maintenance expenditures, in constant dollars (1995–96 to 1997–98 for 

publics)
Chapter V: Financial Aid and Prices at Higher Education Institutions

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Table 35.—Variables included in the financial aid regression models—Continued

PLTRDIFF Dollar change in plant operations and maintenance plus transfers, in constant dollars (1993–94 to 

1995–96 for private not-for-profit)

RESDIFF Dollar change in research expenditures, in constant dollars (1993–94 to 1995–96 for private notfor-profit)

STAPDIFF Dollar change in revenue from state appropriations, in constant dollars (1995–96 to 1997–98 for 

publics)

STGRDIFF Dollar change in revenue from state grants and contracts, in constant dollars (1995–96 to 

1997–98 for publics)

STINCDIF Dollar change in average per capita income by state, in constant dollars (1995–96 to 1997–98 for 

private not-for-profit)

STLODIFF Dollar change in state/local revenue less state/local aid, in constant dollars (1993–94 to 1995–96 

for private not-for-profit)

STUDDIFF Dollar change in student services expenditures, in constant dollars (1993–94 to 1995–96 for 

private not-for-profit)

TRIBAL98 Dummy variable for public 2-year institutions that were classified as tribal colleges in 1998

YRINDFAD Dummy variable for cases that use 1997–98 financial aid data instead of 1998–99 data

FTUGAPDM Dummy variable for cases in which percentage of students receiving any aid were missing

ACADUMD Dummy variable for cases in which data for ACADDIFF were missing

AVC2DUMD Dummy variable for cases in which data for AVC2DIFF were missing

FDGRDUMD Dummy variable for cases in which data for FDGRDIFF were missing

INSPDUMD Dummy variable for cases in which data for INSPDIFF were missing

INSTDUMD Dummy variable for cases in which data for INSTDIFF were missing

LOCALDUM Dummy variable for cases in which data for LOCALE were missing

CERTDUM Dummy variable for cases in which data for PCTCERT were missing

PERFTDUM Dummy variable for cases in which data for PERFT98R were missing

PERMIND Dummy variable for cases in which data for PERMIN98 were missing

PHILDUMD Dummy variable for cases in which data for PHILDIFF were missing

PLNTDUMD Dummy variable for cases in which data for PLNTDIFF were missing

PLTRDUMD Dummy variable for cases in which data for PLTRDIFF were missing

RESDUMD Dummy variable for cases in which data for RESDIFF were missing

STAPDUMD Dummy variable for cases in which data for STAPDIFF were missing

STGRDUMD Dummy variable for cases in which data for STGRDIFF were missing

STLODUMD Dummy variable for cases in which data for STLODIFF were missing

STUDDUMD Dummy variable for cases in which data for STUDDIFF were missing
Chapter V: Financial Aid and Prices at Higher Education Institutions

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confirm the expected relationships. The relationships of these variables with tuition

may reflect internal institutional budget constraints or external conditions such as student choices.

• For public 4-year institutions, the chosen variables had associations with the change in

in-state undergraduate tuition in regression models that included a range of institutional revenue and expenditure variables, from Chapter III. The most important variable that appeared to be related to tuition-setting decisions was the change in revenue

from state appropriations, an association that is supported by expectations regarding

public control over pricing, financial aid, and admissions decisions at these institutions. In addition, two variables related to student characteristics that were not in the

Chapter III models were added in an attempt to capture the possible effects of differences in the composition of student bodies on institutional costs: the percentage of students that attended full time, and the percentage of students who were minorities.

• Public 2-year institutions posed a special case, as the regression model in Chapter III

did not appear to fit the data well and any associations were small.78 In this case, the

variables that had the highest correlations with the dependent variable (change in tuition) were chosen from a range of revenue and expenditure variables, student enrollment characteristics, and other factors that appeared to measure differences among

public 2-year institutions.79

As mentioned above, these regression models allow a preliminary exploration of the relationship between changes in tuition for undergraduate students and student financial aid, revenue

and expenditure changes, and student enrollment and other characteristics. However, there are

considerable data limitations in these models: for example, the availability of only one year of

financial aid data and a lack of comparably recent financial data (especially for private not-forprofit institutions).80 IPSFA data on loans include all sources of student loans; federal subsidized

and unsubsidized, institutional, and private loans cannot be disaggregated. In addition, the IPSFA

aid variables focus on the packaging of various forms of student aid in terms of the percentage of

students receiving aid and the average amount received, and therefore cannot be used to explore

the possibility of a revenue interaction at the institutional level between federal aid and institutional aid. Due in large part to the accounting standards used by the institutions themselves, information on financial aid collected through the IPEDS system for the available years is

incomplete, especially regarding student loan volume, which cannot be isolated from tuition

revenue in the IPEDS Finance survey data. Finally, financial data such as instruction expendi-

 

78In addition, in the Chapter III model, in-district tuition and fees was used as the dependent variable; however, in-district tuition

was not available through IPSFA to be used in the model in this chapter.

79The latter variables were chosen because of their relevance to distinguishing public 2-year institutions, as described in Phipps,

Shedd, and Merisotis (2001).

80For example, the most recent IPEDS finance data that is available for private not-for-profit institutions is for 1995–96, due to

changes in the survey instrument to reflect the new FASB standards.
Chapter V: Financial Aid and Prices at Higher Education Institutions

110

tures cannot be isolated for undergraduate students, making any comparison with undergraduate

tuition inexact.

The models presented here attempt to add to the previous work in this area by providing an

initial examination of tuition and financial aid—including student loan aid—with newly available data on patterns of receipt and average amounts of financial aid. Given the limitations highlighted above, however, it is important to point out that the models cannot fully address the

questions asked in the 1998 HEA amendments. Ideally, a more detailed analysis might examine

the changes in aid packaging over time in comparison to changes in tuition and other relevant

factors, while accounting for simultaneous interrelationships among expenditures, revenues, and

prices (in particular, the potential effects of tuition revenue on expenditures and the potential effects of the availability of federal aid revenue on the use of institutional aid). Studies might also

test the effect of loan subsidies (terms and conditions) on demand over time, keeping in mind

that different models will be applicable for different institutional types, as market and political

forces have varying influences on tuition-setting at public and private not-for-profit institutions.

Data Sources

The main source of data for the regression analyses is IPSFA, which includes institutional

information on price of attendance (for three years, 1997–98 to 1999–2000) and student financial

aid (for one year, either 1997–98 or 1998–99). These data were supplemented with data from

IPEDS for 1993–94 to 1997–98, depending on the most recent year available. Academic tuition,

financial aid, finance, and salary variables were adjusted for inflation to 1999 dollars using the

Consumer Price Index (CPI-U, 1982–84 = 100).

The universe of institutions was drawn from public 2-year and 4-year and private not-forprofit 4-year institutions that are Title-IV participating, degree-granting, and located in the 50

states and the District of Columbia. Public and private not-for-profit 4-year institutions were

further divided by Carnegie classification into research/doctoral, comprehensive, and bachelor’s

institutions.81 As the financial aid variables in the IPSFA dataset are based on first-time, fulltime, degree/certificate-seeking undergraduate students, institutions that enrolled less than 50

first-time, full-time, degree/certificate-seeking undergraduate students were excluded from the

analysis.82 In addition, the analysis excluded cases in which tuition data were missing (or zero),

cases that were missing data for the financial aid variables (federal grants, state grants, institutional grants, and loans), and cases in which the financial aid year indicator was missing. The to-

 

81Private not-for-profit bachelor’s institutions were further divided into tuition quartiles during the regression modeling, due to

an interaction effect (see findings below).

82IPSFA data for 1999–2000 were used to define and measure all of these selection criteria.
Chapter V: Financial Aid and Prices at Higher Education Institutions

111

tal number of public institutions remaining in the universe was 1,407 (research/doctoral = 145;

comprehensive = 254; bachelor’s = 74; 2-year = 934). The total number of private not-for-profit

institutions was 770 (research/doctoral = 77; comprehensive = 222; bachelor’s = 471).83

For the remaining institutions, missing data were addressed by inserting the mean amounts

for each variable (calculated by institutional type).84 Prior to the regression modeling, the frequency distributions of each variable were examined and bivariate relationships between variables were explored through scatterplots and correlation matrices. In addition, averages were

compiled for each institutional type, including such variables as the change in tuition, the number

of first-time, full-time, degree/certificate-seeking undergraduates, the percentage of students receiving various forms of financial aid, and the average amounts of aid received.

The regression models were reduced in order to eliminate variables that did not add to the

model’s ability to explain the variation in the dependent variable, and to avoid spurious findings.85 Each model was reduced (and the coefficients were estimated) using the backward elimination method.86 The results of the financial aid models are presented for each institutional type,

including the following statistics: multiple and adjusted R-squared; the model probability; the

number of valid cases; the Pearson’s correlation coefficient of each independent variable with the

dependent variable; the regression coefficients; the standardized (Beta) coefficients; and the

probability of the t statistic for each independent variable.87 (See Appendix A for details regarding data and regression procedures.)

Trends in Tuition and Financial Aid

Average amounts and percentage changes are reported on an inflation-adjusted basis wherever applicable.

 

83The original number of public 2-year and 4-year institutions in the IPSFA dataset was 1,794. The various selection criteria and

missing data procedures eliminated 387 institutions, 22 percent of the total. For private not-for-profit 4-year institutions, the

original number in the IPSFA dataset was 1,571 and 801 were eliminated through the selection criteria and cleaning process (51

percent of the total). Although many institutions were eliminated from the original dataset through this process, the final groups

of institutions enroll 94 percent of first-time, full-time, degree/certificate-seeking undergraduates at public 4-year and 2-year

institutions and 93 percent of the total number at private not-for-profit 4-year institutions. See Appendix A for details on how

many institutions were eliminated at each step, as well as bias analyses of the differences in the characteristics of institutions

included in and excluded from the final universe.

84Separate dummy variables were created to identify the cases with missing data.

85In previous chapters, already existing models were being updated; they were not reduced because the original models had not

been reduced.

86In the backward elimination method, all of the independent variables are entered, then at each step the variable that changes Rsquared the least is removed. The procedure continues until the removal of any variable in the model results in a meaningful

change in R-squared.

87Note that because the population is a census, some of these statistics were displayed not to measure significance, but rather to

gauge the explanatory power of the model as a whole (model probability) or the strength of the relationships between the independent variables and the dependent variable (probability of the t statistic).
Chapter V: Financial Aid and Prices at Higher Education Institutions

112

Public Research/Doctoral Institutions

The sub-group of 145 public research/doctoral institutions comprised 21.1 percent of firsttime, full-time, degree/certificate-seeking undergraduate enrollment at all public and private notfor-profit institutions in 1999. Between 1997–98 and 1999–2000, in-state tuition for first-time,

full-time, degree/certificate-seeking undergraduates at public research/doctoral institutions increased by 2.9 percent on average, or $73 in constant 1999 dollars. These institutions averaged

2,646 first-time, full-time, degree/certificate-seeking undergraduates in 1999, 16.6 percent of all

undergraduate students enrolled. An average of 68.5 percent of these first-time, full-time undergraduates received aid from any source (table 36).

Table 36.—Average changes in tuition, numbers of first-time, full-time, degree/certificate-seeking

Table 36.—undergraduates, percentages receiving aid, and aid amounts received at public research/

Table 36.—doctoral institutions

Change in in-state tuition for first-time, full-time undergraduates, 1997–98 to 1999–2000, in 

 constant 1999 dollars $73

Percentage change in in-state tuition for first-time, full-time undergraduates, 1997–98 to 

 1999–2000 2.9

Number of first-time, full-time, degree/certificate-seeking undergraduates, 1999–2000 2,646

Percentage of all undergraduates who are first-time, full-time, degree/certificate-seeking, 

 1999–2000 16.6

Percentage of first-time, full-time, degree/certificate-seeking undergraduates who received 

 aid from any source 68.5

Percentage receiving federal grants 28.3

Average amount of federal grants received $2,262

Percentage receiving state grants 26.9

Average amount of state grants received $1,742

Percentage receiving institutional grants 30.9

Average amount of institutional grants received $2,576

Percentage receiving student loans 45.4

Average amount of student loans received $3,490

N = 145

NOTE: Aid variables are for either 1997–98 or 1998–99.

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).

The percentages of these undergraduates who received aid, as well as the average amounts

of aid received, varied by type of aid. On average, 28.3 percent received federal grant aid, with an

average amount of $2,262. About 26.9 percent received an average amount of $1,742 in state

grant aid, 30.9 percent received an average of $2,576 in institutional grant aid, and 45.4 percent

received an average of $3,490 in student loans.
Chapter V: Financial Aid and Prices at Higher Education Institutions

113

Public Comprehensive Institutions

The sub-group of 254 public comprehensive institutions comprised 15.4 percent of firsttime, full-time, degree/certificate-seeking undergraduate enrollment at all public and private notfor-profit institutions in 1999. At public comprehensive institutions, in-state tuition for first-time,

full-time, degree/certificate-seeking undergraduates increased by 3.3 percent between 1997–98

and 1999–2000, or $84 in constant 1999 dollars. The average number of first-time, full-time, degree/certificate-seeking undergraduates was 1,107, 17.4 percent of all undergraduates enrolled at

these institutions. An average of 71.3 percent of these first-time, full-time, degree/certificateseeking undergraduates received aid from any source (table 37).

Table 37.—Average changes in tuition, numbers of first-time, full-time, degree/certificate-seeking

Table 37.—undergraduates, percentages receiving aid, and aid amounts received at public comprehensive

Table 37.—institutions

Change in in-state tuition for first-time, full-time undergraduates, 1997–98 to 1999–2000, in 

 constant 1999 dollars $84

Percentage change in in-state tuition for first-time, full-time undergraduates, 1997–98 to 

 1999–2000 3.3

Number of first-time, full-time, degree/certificate-seeking undergraduates, 1999–2000 1,107

Percentage of all undergraduates who are first-time, full-time, degree/certificate-seeking, 

 1999–2000 17.4

Percentage of first-time, full-time, degree/certificate-seeking undergraduates who received 

 aid from any source 71.3

Percentage receiving federal grants 38.0

Average amount of federal grants received $2,098

Percentage receiving state grants 31.6

Average amount of state grants received $1,414

Percentage receiving institutional grants 25.8

Average amount of institutional grants received $1,696

Percentage receiving student loans 47.1

Average amount of student loans received $2,689

N = 254

NOTE: Aid variables are for either 1997–98 or 1998–99.

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).

The percentages of students receiving aid and the average amounts of aid they received

varied by type of aid. About 38.0 percent of first-time, full-time, degree/certificate-seeking undergraduates received federal grant aid, with an average amount of $2,098. On average, 31.6 percent received an average amount of $1,414 in state grant aid, 25.8 percent received an average of

$1,696 in institutional grant aid, and 47.1 percent received an average of $2,689 in student loans.
Chapter V: Financial Aid and Prices at Higher Education Institutions

114

Public Bachelor’s Institutions

The sub-group of 74 public bachelor’s institutions comprised 2 percent of first-time, fulltime, degree/certificate-seeking undergraduate enrollment at all public and private not-for-profit

institutions in 1999. At public bachelor’s institutions, an average of 480 first-time, full-time, degree/certificate-seeking undergraduates were enrolled at each institution in 1999, about 17.8 percent of all undergraduate students enrolled in that year. The typical in-state tuition charged to

these students increased by 3.4 percent between 1997–98 and 1999–2000, or $82 in constant

1999 dollars. An average of 71.5 percent of these undergraduates received aid from any source

(table 38).

Table 38.—Average changes in tuition, numbers of first-time, full-time, degree/certificate-seeking

Table 38.—undergraduates, percentages receiving aid, and aid amounts received at public bachelor's

Table 38.—institutions

Change in in-state tuition for first-time, full-time undergraduates, 

 1997–98 to 1999–2000, in constant 1999 dollars

$82

Percentage change in in-state tuition for first-time, full-time 

 undergraduates, 1997–98 to 1999–2000

3.4

Number of first-time, full-time, degree/certificate-seeking 

 undergraduates, 1999–2000

480

Percentage of all undergraduates who are first-time, full-time, 

 degree/certificate-seeking, 1999–2000

17.8

Percentage of first-time, full-time, degree/certificate-seeking 

 undergraduates who received aid from any source

71.5

Percentage receiving federal grants 44.1

Average amount of federal grants received $2,064

Percentage receiving state grants 29.2

Average amount of state grants received $1,259

Percentage receiving institutional grants 28.3

Average amount of institutional grants received $1,613

Percentage receiving student loans 49.5

Average amount of student loans received $2,659

N = 74

NOTE: Aid variables are for either 1997–98 or 1998–99.

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).

As at other institutions, the percentage and average amounts varied by type of aid. About

44.1 percent of these students received federal grant aid, with an average amount of $2,064. On

average, 29.2 percent received an average of $1,259 in state grant aid, 28.3 percent received an

average of $1,613 in institutional grant aid, and 49.5 percent received an average of $2,659 in

student loans.
Chapter V: Financial Aid and Prices at Higher Education Institutions

115

Public 2-Year Institutions

The sub-group of 934 public 2-year institutions comprised 27.1 percent of first-time, fulltime, degree/certificate-seeking undergraduate enrollment at all public and private not-for-profit

institutions in 1999. The average in-state tuition charged to first-time, full-time, degree/certificate-seeking undergraduates at public 2-year institutions increased by 4.9 percent between 1997–98 and 1999–2000. These institutions averaged 528 first-time, full-time,

degree/certificate-seeking undergraduates in 1999, 15.9 percent of all undergraduates enrolled,

and 56.8 percent of these undergraduates received aid from any source (table 39).

Table 39.—Average changes in tuition, numbers of first-time, full-time, degree/certificate-seeking

Table 39.—undergraduates, percentages receiving aid, and aid amounts received at public 2-year

Table 39.—institutions

Change in in-state tuition for first-time, full-time undergraduates, 

 1997–98 to 1999–2000, in constant 1999 dollars

$32

Percentage change in in-state tuition for first-time, full-time 

 undergraduates, 1997–98 to 1999–2000

4.9

Number of first-time, full-time, degree/certificate-seeking 

 undergraduates, 1999–2000

528

Percentage of all undergraduates who are first-time, full-time, 

 degree/certificate-seeking, 1999–2000

15.9

Percentage of first-time, full-time, degree/certificate-seeking

 undergraduates who received aid from any source

56.8

Percentage receiving federal grants 40.9

Average amount of federal grants received $1,846

Percentage receiving state grants 25.9

Average amount of state grants received $758

Percentage receiving institutional grants 14.0

Average amount of institutional grants received $683

Percentage receiving student loans 16.6

Average amount of student loans received $1,789

N = 934

NOTE: Aid variables are for either 1997–98 or 1998–99.

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).

Given their relatively low tuition levels, both the average amounts of aid received and percentages of students receiving various types of aid tended to be low in comparison with 4-year

institutions. About 40.9 percent of first-time, full-time, degree/certificate-seeking undergraduates

at public 2-year institutions received federal grant aid, with an average amount of $1,846. On average, 25.9 percent received $758 in state grant aid, 14.0 percent received $683 in institutional

grant aid, and 16.6 percent received an average of $1,789 in student loans.
Chapter V: Financial Aid and Prices at Higher Education Institutions

116

Private Not-for-Profit Research/Doctoral Institutions

The sub-group of 77 private not-for-profit research/doctoral institutions comprised 5.8 percent of first-time, full-time, degree/certificate-seeking undergraduate enrollment at all public and

private not-for-profit institutions in 1999. On average, private not-for-profit research/doctoral

institutions had 1,375 first-time, full-time, degree/certificate-seeking undergraduates in 1999,

about 23.6 percent of all undergraduate students enrolled. The typical tuition charged to these

students increased by about 5.0 percent between 1997–98 and 1999–2000, or about $905 (table

40).

Table 40.—Average changes in tuition, numbers of first-time, full-time, degree/certificate-seeking

Table 40.—undergraduates, percentages receiving aid, and aid amounts received at private not-for-profit

Table 40.—research/doctoral institutions

Change in in-state tuition for first-time, full-time undergraduates, 

 1997–98 to 1999–2000, in constant 1999 dollars

$905

Percentage change in in-state tuition for first-time, full-time 

 undergraduates, 1997–98 to 1999–2000

5.0

Number of first-time, full-time, degree/certificate-seeking 

 undergraduates, 1999–2000

1,375

Percentage of all undergraduates who are first-time, full-time, 

 degree/certificate-seeking, 1999–2000

23.6

Percentage of first-time, full-time, degree/certificate-seeking 

 undergraduates who received aid from any source

72.0

Percentage receiving federal grants 24.7

Average amount of federal grants received $3,276

Percentage receiving state grants 23.8

Average amount of state grants received $3,259

Percentage receiving institutional grants 64.7

Average amount of institutional grants received $9,640

Percentage receiving student loans 55.4

Average amount of student loans received $3,968

N = 77

NOTE: Aid variables are for either 1997–98 or 1998–99.

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).

On average, 72.0 percent of these undergraduates received aid from any source. As at public institutions, both the percentages of students receiving aid and the average amounts received

vary by type of aid. About 24.7 percent of first-time, full-time, degree/certificate-seeking undergraduates received federal grant aid, with an average amount of $3,276. About 23.8 percent received an average amount of $3,259 in state grant aid, 64.7 percent received an average of $9,640

in institutional grant aid, and 55.4 percent received an average of $3,968 in student loans.
Chapter V: Financial Aid and Prices at Higher Education Institutions

117

Private Not-for-Profit Comprehensive Institutions

The sub-group of 222 private not-for-profit comprehensive institutions comprised 5.6 percent of first-time, full-time, degree/certificate-seeking undergraduate enrollment at all public and

private not-for-profit institutions in 1999. On average, tuition for first-time, full-time, degree/certificate-seeking undergraduates at private not-for-profit comprehensive institutions increased by 5.2 percent between 1997–98 and 1999–2000, or about $660. These institutions

averaged 461 first-time, full-time, degree/certificate-seeking undergraduates, 20.8 percent of all

undergraduate students enrolled. An average of 86.5 percent of these first-time, full-time, degree/certificate-seeking undergraduates received aid from any source (table 41). On average, 32.9

percent of these undergraduates received federal grant aid, with an average amount of $2,528,

36.8 percent received an average of $2,734 in state grant aid, 79.4 percent received an average of

$5,475 in institutional grant aid, and 66.8 percent received an average of $3,705 in student loans.

Table 41.—Average changes in tuition, numbers of first-time, full-time, degree/certificate-seeking

Table 41.—undergraduates, percentages receiving aid, and aid amounts received at private not-for-profit

Table 41.—comprehensive institutions

Change in in-state tuition for first-time, full-time undergraduates, 

 1997–98 to 1999–2000, in constant 1999 dollars

$660

Percentage change in in-state tuition for first-time, full-time 

 undergraduates, 1997–98 to 1999–2000

5.2

Number of first-time, full-time, degree/certificate-seeking 

 undergraduates, 1999–2000

461

Percentage of all undergraduates who are first-time, full-time, 

 degree/certificate-seeking, 1999–2000

20.8

Percentage of first-time, full-time, degree/certificate-seeking

 undergraduates who received aid from any source

86.5

Percentage receiving federal grants 32.9

Average amount of federal grants received $2,528

Percentage receiving state grants 36.8

Average amount of state grants received $2,734

Percentage receiving institutional grants 79.4

Average amount of institutional grants received $5,475

Percentage receiving student loans 66.8

Average amount of student loans received $3,705

N = 222

NOTE: Aid variables are for either 1997–98 or 1998–99.

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).
Chapter V: Financial Aid and Prices at Higher Education Institutions

118

Private Not-for-Profit Bachelor’s Institutions

The sub-group of 471 private not-for-profit bachelor’s institutions comprised 8.3 percent of

first-time, full-time, degree/certificate-seeking undergraduate enrollment at all public and private

not-for-profit institutions in 1999. On average, private not-for-profit bachelor’s institutions enrolled 320 first-time, full-time, degree/certificate-seeking undergraduates in 1999, 27.7 percent of

all undergraduates. The typical tuition charged to these undergraduates increased by 4.6 percent

between 1997–98 and 1999–2000, or about $571. About 85.7 percent of these students received

aid from any source. On average, 35.5 percent received federal grant aid, with an average amount

of $2,502; 38.8 percent received $2,521 in state grant aid, 76.9 percent received $6,063 in institutional grant aid, and 65.9 percent received an average of $3,514 in student loans (table 42).

Table 42.—Average changes in tuition, numbers of first-time, full-time, degree/certificate-seeking 

Table 42.—undergraduates, percentages receiving aid, and aid amounts received at private not-forTable 42.—profit bachelor's institutions

Highest Middle Lowest

All tuition two tuition tuition

institutions quartile quartiles quartile

Change in in-state tuition for first-time, full-time undergraduates, 

 1997–98 to 1999–2000, in constant 1999 dollars

$571 $649 $588 $457 

Percentage change in in-state tuition for first-time, full-time 

 undergraduates, 1997–98 to 1999–2000

4.6 3.2 4.8 5.8 

Number of first-time, full-time, degree/certificate-seeking 

 undergraduates, 1999–2000

320 437 267 311 

Percentage of all undergraduates who are first-time, full-time, 

 degree/certificate-seeking, 1999–2000

27.7 31.8 25.5 28.2 

Percentage of first-time, full-time, degree/certificate-seeking

 undergraduates who received aid from any source

85.7 75.7 89.9 87.3 

Percentage receiving federal grants 35.5 20.9 35.3 50.7 

Average amount of federal grants received $2,502 $2,879 $2,436 $2,259 

Percentage receiving state grants 38.8 24.8 44.0 42.5 

Average amount of state grants received $2,521 $2,739 $2,589 $2,164 

Percentage receiving institutional grants 76.9 71.7 86.4 63.0 

Average amount of institutional grants received $6,063 $10,980 $5,155 $2,984 

Percentage receiving student loans 65.9 59.0 71.1 62.2 

Average amount of student loans received $3,514 $3,546 $3,615 $3,276 

N = 471

NOTE: Aid variables are for either 1997–98 or 1998–99. Tuition quartiles are based on in-state undergraduate tuition for

1997–98.

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).
Chapter V: Financial Aid and Prices at Higher Education Institutions

119

Model Results

Overall, the regression models found no associations between most of the aid packaging

variables and the change in tuition. The single exception is institutional aid, which was found to

have a positive association for two groups of institutions: public comprehensive institutions and

private not-for-profit comprehensive institutions. These results, although focusing on the aspect

of aid packaging rather than aid volume or subsidies, generally confirm the findings of previous

statistical modeling efforts. As discussed, the regression models presented here are limited in

terms of their ability to capture changes in aid packaging over time or to address the interaction

of revenue from federal loan aid and institutional aid.

Below, the results of the reduced regression models for public and private not-for-profit institutions are highlighted for each institutional type. For each regression model, the independent

variables remaining after the backward elimination procedure are presented; removal of each of

these variables would mean a meaningful decrease in the “explanatory” power of the model. One

can interpret the results as pointing to the independent variables that have an association with the

change in tuition, adjusting statistically for the covariation of all other variables in the model.

Public Research/Doctoral Institutions

The reduced regression model did not reveal a relationship between the aid variables and

the change in tuition at public research/doctoral institutions (table 43). Several variables did have

a relationship with the change in tuition, however, including the following:

• The change in revenue from state appropriations. Larger increases in tuition were associated with larger decreases in the revenue from state appropriations. This is consistent with the findings of Chapter III, which suggest that changes in government

appropriations are related to tuition-setting decisions at public institutions.

• The percentage of students who were minorities. Larger increases in tuition were associated with lower proportions of minority students.

• The number of first-time, full-time, degree/certificate-seeking undergraduates. Larger

increases in tuition were associated with higher numbers of these students.

• The percentage of students who were attending full time. Larger increases in tuition

were associated with lower proportions of full-time students.

• The tuition level in the base year. Larger increases in tuition were associated with

lower tuition levels in the base year.
Chapter V: Financial Aid and Prices at Higher Education Institutions

120

Table 43.—Coefficients for reduced regression of the change in in-state tuition for first-time, full-time, 

Table 43.—degree/certificate-seeking undergraduates on selected financial aid, revenue, expenditure, and 

Table 43.—institutional characteristics for public research/doctoral institutions

N

Multiple RsquaredAdjusted RsquaredModel 

significance

Model 145 0.289 0.259 0.000* 

Correlation 

coefficient 

with change 

in tuition

Regression 

coefficient

Standardized 

(Beta) 

coefficient Probability

Constant — 594.725 — 0.000* 

Base year (1997–98) tuition level -0.162 -0.037 -0.166 0.026* 

Number of first-time, full-time, degree/certificate-seeking

 undergraduates

0.021 0.049 0.272 0.003* 

Change in revenue from state appropriations -0.336 0.000 -0.403 0.000* 

Dummy variable for cases in which data for PLNTDIFF

 were missing

0.168 191.264 0.175 0.016* 

Percent of total fall 1998 enrollment that was minority -0.249 -3.702 -0.222 0.003* 

Percent of total fall 1998 enrollment that was full time -0.149 -4.990 -0.245 0.005* 

—Not applicable.

*Relatively strong relationship.

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA); U.S. Education Department, National Center for Education Statistics, Integrated Postsecondary

Education Data System (IPEDS), Full Collection Years 1994 to 1998.

Excluded variables: FTUGAP2, FTUGAPDM, YRINDFAD, FEDGPAC, STGPAC, INGPAC, LOANPAC,

 ACADDIFF, INSPDIFF, PLNTDIFF

Together, the variables remaining in the regression model after the backward elimination

process accounted for 28.9 percent of the variation in the change in in-state tuition at these

schools.

Public Comprehensive Institutions

When the regression model was applied to this group of schools, the institutional aid variable had a positive association with the change in tuition. However, the model did not reveal relationships for the other aid variables (table 44). Other variables that had a relationship with the

change in tuition are the following:

• The change in revenue from state appropriations. As expected for public institutions,

larger increases in tuition were associated with larger decreases in the revenue from

state appropriations.

• The change in instruction expenditures. Larger increases in tuition were associated

with larger increases in expenditures for instruction.
Chapter V: Financial Aid and Prices at Higher Education Institutions

121

Table 44.—Coefficients for reduced regression of the change in in-state tuition for first-time, full-time, 

Table 44.—degree/certificate-seeking undergraduates on selected financial aid, revenue, expenditure, and 

Table 44.—institutional characteristics for public comprehensive institutions

Multiple Adjusted Model 

N R-squared R-squared significance

Model 254 0.214 0.198 0.000* 

Correlation 

coefficient Standardized 

with change Regression (Beta) 

in tuition coefficient coefficient Probability

Constant — 161.160 — 0.003* 

Base year (1997–98) tuition level -0.044 -0.043 -0.166 0.005* 

Number of first-time, full-time, degree/certificate-seeking 0.009 0.057 0.154 0.015* 

 undergraduates

Percentage of FT, FT undergraduates receiving institutional 0.103 0.001 0.159 0.006* 

 grants times the average amount received

Change in revenue from state appropriations -0.322 0.000 -0.466 0.000* 

Change in instruction expenditures 0.185 0.000 0.207 0.000* 

 PERMIN98, PERFT98R, FDGRDIFF, FDGRDUMD, STGRDIFF, STGRDUMD

— Not applicable.

*Relatively strong relationship.

Student Financial Aid Survey (IPSFA); U.S. Education Department, National Center for Education Statistics, 

Integrated Postsecondary Education Data System (IPEDS), Full Collection Years 1994 to 1998.

Excluded variables: FTUGAP2, FTUGAPDM, YRINDFAD, FEDGPAC, STGPAC, LOANPAC, STAPDUMD, 

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and 

• The tuition level in the base year. Larger increases in tuition were associated with

lower tuition levels in the base year.

• The number of first-time, full-time, degree/certificate-seeking undergraduates. Larger

increases in tuition were associated with higher numbers of these students.

Together, the variables remaining in the reduced regression model accounted for 21.4 percent of the variation in the change in in-state tuition at public comprehensive institutions.

Public Bachelor’s Institutions

The reduced regression model did not reveal a relationship between any of the aid variables

and the change in tuition at public bachelor’s institutions (table 45). However, the change in the

revenue from state appropriations did have an association, with institutions with larger decreases

in state appropriations revenue tending to have larger increases in tuition. Together, the variables

remaining in the reduced regression model, including the change in state appropriations, accounted for only 14.3 percent of the variation in the change in tuition.
Chapter V: Financial Aid and Prices at Higher Education Institutions

122

Table 45.—Coefficients for reduced regression of the change in in-state tuition for first-time, full-time, 

Table 45.—degree/certificate-seeking undergraduates on selected financial aid, revenue, expenditure, and 

Table 45.—institutional characteristics for public bachelor's institutions

Multiple Adjusted Model 

N R-squared R-squared significance

Model 74 0.143 0.119 0.004* 

Correlation 

coefficient Standardized 

with change Regression (Beta) 

in tuition coefficient coefficient Probability

Constant — 115.146 — 0.000* 

Change in revenue from state appropriations -0.197 0.000 -0.280 0.013* 

Dummy variable for cases in which data for PERFT98R 0.254 451.180 0.260 0.021* 

 were missing

LOANPAC, STAPDUMD, INSTDIFF, ACADDIFF, INSPDIFF, PLNTDIFF, PERMIN98, PERFT98R

— Not applicable.

*Relatively strong relationship.

Financial Aid Survey (IPSFA); U.S. Education Department, National Center for Education Statistics, Integrated 

Postsecondary Education Data System (IPEDS), Full Collection Years 1994 to 1998.

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student 

Excluded variables: INSTAC98, FTUG99, FTUGAP2, YRINDFAD, FEDGPAC, STGPAC, INGPAC, 

Public 2-Year Institutions

The reduced regression model did not reveal a relationship between the aid variables and

the change in tuition at public 2-year institutions (table 46). Several variables did have an association, including the following:

• The change in revenue from state grants and contracts. Larger increases in tuition

were associated with larger decreases in the revenue from state grants and contracts.

• The percentage of students who were minorities. Larger increases in tuition were associated with lower proportions of minority students.

• The tuition level in the base year. Larger increases in tuition were associated with

lower tuition levels in the base year.

• The percentage of awards granted that were certificates. Institutions that awarded

higher proportions of certificates tended to have larger increases in tuition.
Chapter V: Financial Aid and Prices at Higher Education Institutions

123

Table 46.—Coefficients for reduced regression of the change in in-state tuition for first-time, full-time, 

Table 46.—degree/certificate-seeking undergraduates on selected financial aid, revenue, expenditure, and 

Table 46.—institutional characteristics for public 2-year institutions

Multiple Adjusted Model 

N R-squared R-squared significance

Model 934 0.084 0.077 0.000* 

Correlation 

coefficient Standardized 

with change Regression (Beta) 

in tuition coefficient coefficient Probability

Constant — 91.618 — 0.000* 

Base year (1997–98) tuition level -0.006 -0.023 -0.114 0.003* 

Dummy variable for cases that use 1997–98 financial aid -0.153 -66.721 -0.124 0.000* 

 data

Change in revenue from state grants and contracts -0.133 0.000 -0.147 0.000* 

Percent of total fall 1998 enrollment that was minority -0.149 -1.295 -0.139 0.000* 

Dummy variable for cases in which data for PERMIN98 0.061 119.066 0.065 0.040* 

 were missing

Dummy variable for public 2-year institutions that were -0.123 -218.831 -0.088 0.007* 

 classified as tribal colleges

Percentage of awards granted that were certificates 0.108 0.791 0.086 0.009* 

STGRDUMD, LOCALE, LOCALDUM, CERTDUM

— Not applicable.

*Relatively strong relationship.

Financial Aid Survey (IPSFA); U.S. Education Department, National Center for Education Statistics, Integrated 

Postsecondary Education Data System (IPEDS), Full Collection Years 1994 to 1998.

Excluded variables: FTUG99, FTUGAP2, FTUGAPDM, FEDGPAC, STGPAC, INGPAC, LOANPAC, 

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student 

Together, the variables remaining in the reduced regression model accounted for only 8.4

percent of the variation in the change in tuition. As in the model presented in Chapter III, this

suggests that there are many factors affecting pricing decisions at public 2-year institutions that

are not captured by this model.

Private Not-for-Profit Research/Doctoral Institutions

None of the variables remained in the reduced regression model for private not-for-profit

research/doctoral institutions after the backward elimination procedure. Thus, the reduced regression model did not reveal an association between any of the independent variables and the

change in tuition. The variable closest to having a relationship was the number of first-time, fulltime, degree/certificate-seeking undergraduates, which had a positive association at the .10 level

(table 47).
Chapter V: Financial Aid and Prices at Higher Education Institutions

124

Table 47.—Coefficients for reduced regression of the change in in-state tuition for first-time, full-time, 

Table 47.—degree/certificate-seeking undergraduates on selected financial aid, revenue, expenditure, and 

Table 47.—institutional characteristics for private not-for-profit research/doctoral institutions

Multiple Adjusted Model 

N R-squared R-squared significance

Model 77 0.044 0.031 0.069

Correlation 

coefficient Standardized 

with change Regression (Beta) 

in tuition coefficient coefficient Probability

Constant — 725.282 — 0.000* 

Number of first-time, full-time, degree/certificate-seeking 0.209 0.131 0.209 0.069a

 undergraduates

STUDDIFF, ACADDIFF, FDGRDIFF, ACADDUMD, FDGRDUMD, AVC2DIFF, AVTFDIFF

— Not applicable.

*Relatively strong relationship.

here for informational purposes.

Financial Aid Survey (IPSFA); U.S. Education Department, National Center for Education Statistics, Integrated 

Postsecondary Education Data System (IPEDS), Full Collection Years 1994 to 1998.

Excluded variables: INSTAC98, FTUGAP2, YRINDFAD, FEDGPAC, STGPAC, INGPAC, LOANPAC, 

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student 

a

This model actually reduced to the constant, with a regression coefficient of 904.852. However, the prior model is presented

Private Not-for-Profit Comprehensive Institutions

When the regression model was applied to this group of institutions, the institutional aid

variable had a positive association with the change in tuition. However, the model did not reveal

relationships for the other aid variables (table 48). Other variables that had an association were

the following:

• The number of first-time, full-time, degree/certificate-seeking undergraduates. Larger

increases in tuition were associated with higher numbers of these students.

• The change in average per capita income in the state. Institutions located in states in

which average incomes increased the most tended to have larger increases in tuition.

Together, the variables remaining in the reduced regression model accounted for only about

10 percent of the variation in the change in tuition, indicating that this model does not capture

pricing decisions well at these institutions.
Chapter V: Financial Aid and Prices at Higher Education Institutions

125

Table 48.—Coefficients for reduced regression of the change in tuition for first-time, full-time, degree/

Table 48.—certificate-seeking undergraduates on selected financial aid, revenue, expenditure, and 

Table 48.—institutional characteristics for private not-for-profit comprehensive institutions

Multiple Adjusted Model 

N R-squared R-squared significance

Model 222 0.100 0.088 0.000* 

Correlation 

coefficient Standardized 

with change Regression (Beta) 

in tuition coefficient coefficient Probability

Constant — 102.418 — 0.455 

Number of first-time, full-time, degree/certificate-seeking 0.219 0.320 0.217 0.001* 

 undergraduates

Percentage of FT, FT undergraduates receiving institutional 0.188 0.000 0.186 0.004* 

 grants times the average amount received

Change in average state per capita income 0.138 0.149 0.130 0.044* 

ACADDIFF, ACADDUMD, AVC2DIFF, AVC2DUMD, AVTFDIFF, PHILDIFF, PHILDUMD, RESDIFF, 

STLODIFF, STLODUMD

— Not applicable.

*Relatively strong relationship.

Financial Aid Survey (IPSFA); U.S. Education Department, National Center for Education Statistics, Integrated 

Postsecondary Education Data System (IPEDS), Full Collection Years 1994 to 1998.

Excluded variables: INSTAC98, FTUGAP2, FTUGAPDM, YRINDFAD, FEDGPAC, STGPAC, LOANPAC, 

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student 

Private Not-for-Profit Bachelor’s Institutions

The initial reduced regression model for all private not-for-profit bachelor’s institutions indicated a negative association between the institutional aid variable and the change in tuition

when controlling for all other factors (in comparison, the bivariate correlation between the two

variables was small and positive). Further examination of the data suggested that this relationship

was influenced by an interaction effect between the institutional aid variable and the base level of

tuition in 1997–98.88 When private not-for-profit bachelor’s institutions were divided into subgroups based on the base year tuition level (highest quartile, middle quartiles, and lowest quartile), the results were the following:

 

88An interaction effect occurs when the strength or direction of a relationship between two (or more) variables is different depending on the value of some other variable. The interaction was detected by examining the partial correlations of institutional

aid and the change in tuition, accounting for each of the independent variables, which suggested that the base year of tuition was

modifying the relationship (the partial correlation was -.1143, compared to the simple correlation of .015). In addition, the interaction term for the base year level of tuition and institutional aid was related to the dependent variable in a one-way analysis of

variance, ANOVA (where the two variables suspected of interacting were dichotomized around their median values) and when

adding a multiplicative interaction term to the equation and re-running the regression. Suspected interaction effects were not

examined in Chapters III and IV because the analyses used previously existing models and further exploration of the results was

beyond the scope of the analyses.
Chapter V: Financial Aid and Prices at Higher Education Institutions

126

The reduced regression models for all three subgroups did not reveal a relationship between

the aid variables and the change in tuition for first-time, full-time, degree/certificate-seeking undergraduates between 1997–98 and 1999–2000 (tables 49, 50, and 51).

• For institutions in the highest tuition quartile, the number of first-time, full-time, degree/certificate-seeking undergraduates had a positive relationship with the change in

tuition. It accounted for 3.6 percent of the variation in the change in tuition.

• For institutions in the middle tuition quartiles, two dummy variables representing

missing data were the only variables remaining in the reduced regression model, accounting for 2.6 percent of the variation in the change in tuition.

• For institutions in the lowest tuition quartile, several variables had a positive relationship with the change in tuition, including the base level of tuition and the change in research expenditures. Together, the variables remaining in the reduced regression model

accounted for 9.5 percent of the variation in the change in tuition.

Table 49.—Coefficients for reduced regression of the change in tuition for first-time, full-time, degree/

Table 49.—certificate-seeking undergraduates on selected financial aid, revenue, expenditure, and 

Table 49.—institutional characteristics for private not-for-profit bachelor’s institutions in the highest tuition

Table 49.—quartile

Multiple Adjusted Model 

N R-squared R-squared significance

Model 117 0.036 0.028 0.040* 

Correlation 

coefficient Standardized 

with change Regression (Beta) 

in tuition coefficient coefficient Probability

Constant — 361.968 — 0.021* 

Number of first-time, full-time, degree/certificate-seeking 0.191 0.658 0.191 0.040* 

 undergraduates

ACADDIFF, AVC2DIFF, AVC2DUMD, AVTFDIFF, PHILDIFF, RESDIFF, RESDUMD, STLODIFF, 

STLODUMD, STINCDIF, STUDDIFF, PLTRDIFF, PLTRDUMD, INSPDIFF, INSTDIFF, INSTDUMD

— Not applicable.

*Relatively strong relationship.

NOTE: Tuition quartile is based on in-state undergraduate tuition for 1997–98.

Financial Aid Survey (IPSFA); U.S. Education Department, National Center for Education Statistics, Integrated 

Postsecondary Education Data System (IPEDS), Full Collection Years 1994 to 1998.

Excluded variables: INSTAC98, FTUGAP2, YRINDFAD, FEDGPAC, STGPAC, INGPAC, LOANPAC, 

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student 
Chapter V: Financial Aid and Prices at Higher Education Institutions

127

Table 50.—Coefficients for reduced regression of the change in in-state tuition for first-time, full-time, 

Table 50.—degree/certificate-seeking undergraduates on selected financial aid, revenue, expenditure, and 

Table 50.—institutional characteristics for private not-for-profit bachelor’s institutions in the middle tuition 

Table 50.—quartiles

Multiple Adjusted Model 

N R-squared R-squared significance

Model 237 0.026 0.018 0.046* 

Correlation 

coefficient 

with change 

in tuition

Regression 

coefficient

Standardized 

(Beta) 

coefficient Probability

Constant — 582.306 — 0.000* 

Dummy variable for cases in which data for STLODIFF 

were missing

0.074 831.370 0.297 0.014* 

Dummy variable for cases in which data for PLTRDIFF 

were missing

-0.016 -875.350 -0.266 0.027* 

INGPAC, LOANPAC, ACADDIFF, AVC2DIFF, AVTFDIFF, PHILDIFF, RESDIFF, RESDUMD, STLODIFF, 

STINCDIF, STUDDIFF, PLTRDIFF, INSPDIFF, INSTDIFF, INSTDUMD

— Not applicable.

*Relatively strong relationship.

NOTE: Tuition quartile is based on in-state undergraduate tuition for 1997–98.

Financial Aid Survey (IPSFA); U.S. Education Department, National Center for Education Statistics, Integrated 

Postsecondary Education Data System (IPEDS), Full Collection Years 1994 to 1998.

Excluded variables: INSTAC98, FTUG99, FTUGAP2, FTUGAPDM, YRINDFAD, FEDGPAC, STGPAC, 

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student 

Table 51.—Coefficients for reduced regression of the change in tuition for first-time, full-time, degree/certifiTable 51.—cate-seeking undergraduates on selected financial aid, revenue, expenditure, and institutional 

Table 51.—characteristics for private not-for-profit bachelor’s institutions in the lowest tuition quartile

Multiple Adjusted Model

N R-squared R-squared significance

Model 117 0.095 0.071 0.010* 

Correlation 

coefficient Standardized 

with change Regression (Beta) 

in tuition coefficient coefficient Probability

Constant — -88.826 — 0.725

Base year (1997–98) tuition level 0.180 0.065 0.181 0.046* 

Dummy variable for cases that use 1997–98 financial aid 0.162 399.566 0.187 0.040* 

 data

Change in research expenditures 0.180 0.001 0.178 0.050* 

Excluded variables: FTUG99, FTUGAP2, FTUGAPDM, FEDGPAC, STGPAC, INGPAC, LOANPAC, 

ACADDIFF, AVC2DIFF, AVC2DUMD, AVTFDIFF, PHILDIFF, RESDUMD, STLODIFF, STLODUMD, 

STINCDIF, STUDDIFF, PLTRDIFF, PLTRDUMD, INSPDIFF, INSTDIFF, INSTDUMD

—Not applicable.

*Relatively strong relationship.

NOTE: Tuition quartile is based on in-state undergraduate tuition for 1997–98.

Financial Aid Survey (IPSFA); U.S. Education Department, National Center for Education Statistics, Integrated 

Postsecondary Education Data System (IPEDS), Full Collection Years 1994 to 1998.

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student 
Chapter V: Financial Aid and Prices at Higher Education Institutions

128

Discussion

The IPSFA data revealed that patterns of financial aid differ considerably among the types

of institutions. Nevertheless, some trends appear to be common within each broad institutional

sector (table 52):

• At public 4-year institutions, the percentage of first-time, full-time, degree/certificateseeking undergraduates who received aid from any source tended to be more than twothirds on average, ranging from 68.5 percent at research/doctoral institutions to 71.5

percent at bachelor’s institutions. The average percent receiving aid and average

amount received varied by type of aid, but in general the highest figures were for student loan aid at all three groups of public 4-year institutions.

• Public 2-year institutions presented a distinctly different situation, in which on average

56.8 percent of first-time, full-time, degree/certificate-seeking undergraduates received

aid from any source, the highest percentage and average amount was for federal grant

aid, and relatively low percentages of students received student loans or institutional

aid.

• At private not-for-profit 4-year institutions, about three-quarters of first-time, full-time,

degree/certificate-seeking undergraduates received aid from any source, ranging from

72.0 percent at research/doctoral institutions to 86.5 percent at comprehensive institutions. For all three groups of private not-for-profit institutions, the highest average percentages of students receiving aid were for institutional aid, and the average amounts

of institutional aid received were considerably higher than the amounts of other aid.

The averages for other types of aid varied according to institutional type, although student loan aid had the second highest percentages and average amounts.

In the 1998 amendments to the HEA, Congress directed NCES to explore how institutional

financial aid affects price increases, and the extent to which federal financial aid is involved in

this relationship. These questions propose specific relationships to be tested, i.e., the possibility

of a direct relationship between financial aid and tuition increases, as well as an indirect relationship through the interaction of federal aid and institutional aid. Given the limitations described in

this chapter, the regression models presented examined associations between recent measures of

student aid and tuition using the IPSFA data, while recognizing that evaluating relationships

among independent variables would involve a more complex and dynamic framework. The relationships found in these regression models point to the independent variables that have an association with the change in tuition, adjusting for the covariation of all other variables in the model.

The associations were inevitably influenced by the chosen model, involving the variables that

were included, as well as those variables that were excluded due to data limitations.89

 

89Note especially that “sticker” price is used as the dependent variable in these models, rather than net price. If the ratio of net

price to sticker price is changing over time, the models may be misspecified.
Chapter V: Financial Aid and Prices at Higher Education Institutions

129

Table 52.—Summary of financial aid patterns at public and private not-for-profit institutions

Private not-for-profit

Research/ Compre- Research/ Compredoctoral hensive Bachelor's 2-year doctoral hensive Bachelor's

Average percentage of first-time, full-time

 undergraduates receiving financial aid:

 Aid from any source 68.5 71.3 71.5 56.8 72.0 86.5 85.7

 Federal grants 28.3 38.0 44.1 40.9 24.7 32.9 35.5

 State grants 26.9 31.6 29.2 25.9 23.8 36.8 38.8

 Institutional grants 30.9 25.8 28.3 14.0 64.7 79.4 76.9

 Loan aid 45.4 47.1 49.5 16.6 55.4 66.8 65.9

Average amounts of aid received ($):

 Federal grants $2,262 $2,098 $2,064 $1,846 $3,276 $2,528 $2,502 

 State grants 1,742 1,414 1,259 758 3,259 2,734 2,521 

 Institutional grants 2,576 1,696 1,613 683 9,640 5,475 6,063 

 Loan aid 3,490 2,689 2,659 1,789 3,968 3,705 3,514 

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Surveys (IPSFA).

Public

Keeping these provisions in mind, the models used the most recent available data on financial aid patterns and did not find evidence of a relationship between financial aid and tuition in

any of the seven groups of institutions (table 53). The single exception was institutional aid,

which was associated with changes in tuition at two groups of institutions: public and private

not-for-profit comprehensive institutions. Other independent variables found to be related to the

change in tuition included the change in revenue from state appropriations—which was associated at public 4-year institutions—the level of tuition in the base year, and the number of firsttime, full-time, degree/certificate-seeking undergraduates.

At the same time, the low R-squared values found for these models suggest that more remains unexplained than explained by the models. This may be due to the limitations of available

data, or to misspecification of the model. For example, some highly relevant variables may not

have been included in the model, or the independent variables may not have been measured appropriately (for example, the change in financial aid, if available, may be a better variable to include than financial aid in a given year). The decisions regarding choice of model might be

informed by the development of theories that account for differences by type of aid and institution, and for simultaneous relationships among variables. Given the limitations of this study, the

results presented in this chapter can only suggest aspects of how a more complex model might be

structured.
Table 53.—Significant relationships with the change in undergraduate tuition at public and private not-for-profit institutions: 

Private Private

not-for- not-for- Private no

Public Public profit profit Highest 

 research/ compre- Public Public research/ compre- tuition 

doctoral hensive bachelor's 2-year doctoral hensive quartile 

Federal grant aidState grant aidInstitutional grant aid * *Loan aidTuition in base year * * * Change in state appropriations revenue * * *Number of FT, FT undergraduates * * * * *Percent minority students * *Percent full-time students *Change in instruction expenditures *Percent certificates awarded *Change in state grants and contracts *Change in per capita state income *Change in research expenditures 

*Relatively strong relationship.SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student Financial Aid Survey (IPSFDepartment ofEducation, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Full Collection Years 
131

Chapter VI: Summary of Findings and Conclusions

This report, the final product of Phase I of the NCES Study of College Costs and Prices,

has examined trends in prices, expenditures, revenues, and enrollment over the past decade and

has explored the relationships among these variables at public and private not-for-profit colleges

and universities. The goals of Phase I of the study were twofold:

1) To revisit the question left unanswered by the Cost Commission about the relations

between prices and costs, and the relation of federal financial aid and institutional aid

to price increases; and

2) To examine the usefulness of existing statistical models for testing the relationships

between revenues and costs, and prices in higher education.

The approach taken to meet these goals reflects the constraints of resources and the limitations of available data. NCES initially proposed to respond to Congress’ mandate with a national

study collecting new institutional data and investigating the reciprocal relationships among variables over time. However, funds were not appropriated by Congress to allow such a collection of

new data or the development of new statistical models to analyze them. As a result, existing

models and data were used to investigate the relationship among prices, expenditures, and revenues. Due to the diversity of higher education institutions and the differences in influences and

decisionmaking structures, the analysis separated public and private not-for-profit institutions

and then divided these sectors into broad sub-groups to better address differences. Recognizing

the limits of such analysis, NCES decided to extend the empirical research by requesting expert

opinions from national researchers in the field.

The analysis in the report has been presented in four separate sections: Chapter II summarized the discussion of the commissioned papers, Chapter III presented the results of research

about the public sector; Chapter IV focused on the private not-for-profit sector; and Chapter V

explored the relation between financial aid packaging and tuition increases. This section briefly

reiterates the major conclusions that can be drawn from across these sections, followed by a

summary of trends in prices, revenues, and expenditures. The report ends with conclusions about

the efficacy of the research models for future work on the topic.
Chapter VI: Summary of Findings and Conclusions

132

Major Conclusions from the Data Analyses

The conclusions that have been reached from the trend analyses and models in this report

are consistent with earlier research, extended to a longer period of time and expanded to include

work on public 2-year institutions and financial aid packaging.

General Findings

The detailed analyses found variations in the nature and strength of the relationships between costs and prices across types of institutions, and within types of institutions over time.

This is consistent with previous research, as well as with the opinions of the expert authors.

• In both the public and private not-for-profit sectors, average tuition charges increased

at a faster rate than inflation over the period of the analyses, and tuition charges also

increased faster than most expenditure categories within the institutions. The share of

overall revenue coming from tuition has increased on average for all institutional types

in both sectors.

• For the public 4-year institutions, the single most important factor associated with tuition increases was decreasing revenue from government appropriations, with state appropriations making up the majority of such revenue. Although increases in instruction

expenditures were associated with increases in tuition at public 4-year institutions, the

proportion of total expenditures for instruction declined slightly over the time period

examined.

• Within the public sector, the regression models found that changes in revenue and expenditure categories explained a very low percentage of the variation in tuition for 2-

year institutions. Whether this is attributable to the differences in funding between 2-

year and other public institutions, or differences in students and programs, cannot be

determined with these data.

• The research shows that prices at private not-for-profit institutions were related to both

“internal” institutional budget constraints and “external” market conditions. In the private not-for-profit sector, there is no single overriding factor consistently related to

tuition.

• For all three groups of private not-for-profit institutions, “internal” institutional constraints—higher costs (institutional aid and average faculty compensation levels) and

lower levels of revenue from nontuition sources (endowment income and private gifts,

grants, and contracts)—were associated with higher levels of undergraduate tuition. At

the same time, “external” factors such as the availability of aid for students, the price

of attending public institutions in the same state, and in-state consumer purchasing

power were also associated with tuition levels. Some differences were found regarding

the other independent variables that were related to tuition—for example, instruction

expenditures were associated with tuition at comprehensive and bachelor’s institutions,

but not at research/doctoral institutions. These differences suggest that the three groups
Chapter VI: Summary of Findings and Conclusions

133

of institutions face different competitive environments, although the findings were difficult to interpret.

• Regarding the relation between financial aid and tuition, the regression models found

no associations between most of the aid packaging variables (federal grants, state

grants, and loans) and changes in tuition in either the public or private not-for-profit

sectors. The single exception is institutional aid, which was found to have a positive

association with tuition increases for public comprehensive and private not-for-profit

comprehensive institutions.

Summary of Trends

On average, inflation-adjusted, in-state undergraduate tuition levels rose through the 1990s

for all institutional types, as evidenced by the institutions examined in detail in Chapters III and

IV of this report:

• In the public sector, between 1988–89 and 1997–98, on average in-state undergraduate

tuition and fees increased annually by 4.1 percent at research/doctoral institutions, 4.2

percent at comprehensive institutions, 4.3 percent at bachelor’s institutions, and 3.4

percent at 2-year institutions, in inflation-adjusted terms.

• In the private not-for-profit sector, between 1988–89 and 1995–96, on average undergraduate tuition and fees increased annually by 3.6 percent at research/doctoral institutions, 4.1 percent at comprehensive institutions, and 3.7 percent at bachelor’s

institutions.

Gross tuition revenue accounted for increasing proportions of total E&G revenue for all institutional types, although, on average, public institutions continued to rely more on state appropriations than on tuition revenue. Public institutions in particular faced substantial changes in the

composition of their revenue sources in the 1990s.

• Over the period 1988–89 to 1997–98, the proportion of total E&G revenue from tuition

in public research/doctoral institutions increased by 5.4 percentage points, 8.4 percentage points at public comprehensive institutions, 8.0 percentage points at bachelor’s institutions, and 5.6 percentage points at public 2-year institutions. The proportion of

total E&G revenue from state appropriations decreased over the period; on average, the

proportion decreased by 9.8 percentage points at research/doctoral institutions, 11.3

percentage points at comprehensive institutions, 6.9 percentage points at bachelor’s institutions, and 3.2 percentage points at 2-year institutions.

• Despite the changes in composition of E&G revenue, on average state appropriations

continued to make up a larger proportion than tuition revenue at public institutions. In

1997–98, tuition revenue at public research/doctoral institutions averaged 23.8 percent

of total E&G revenue in contrast to 38.9 percent from state appropriations. At public

comprehensive institutions, tuition revenues comprised 31.1 percent of total revenues

compared to 47.0 percent from state appropriations; 31.5 percent compared to 44.6
Chapter VI: Summary of Findings and Conclusions

134

percent at public bachelor’s institutions; and 20.7 percent compared to 41.1 percent at

public 2-year institutions.

• Tuition revenue tended to make up the largest single component of total E&G revenue

at private not-for-profit institutions on average in 1995–96, comprising 49.3 percent at

research/doctoral institutions, 73.5 percent at comprehensive institutions, and 64.8 percent at bachelor’s institutions.

• The proportion of E&G revenue accounted for by tuition revenue at private not-forprofit institutions also increased: from 1988–89 to 1995–96, by 1.3 percentage points

at research/doctoral institutions, by 5.1 percentage points at comprehensive institutions, and by 4.2 percentage points at bachelor’s institutions. The proportion of revenue from other, nontuition sources, such as endowment income, decreased slightly

over this period.

On average, instruction expenditures continued to constitute the largest proportion of total

E&G expenditures for all institutional types, while expenditures for scholarships and fellowships—specifically, institutional scholarships and fellowships—was one of the fastest growing

expenditure categories.

• At public institutions, instruction expenditures made up the largest proportion of total

E&G expenditures in 1997–98—34.7 percent at research/doctoral institutions, 40.5

percent at comprehensive institutions, 37.6 percent at bachelor’s institutions, and 42.8

percent at 2-year institutions. However, from 1988–89 to 1997–98, instruction decreased slightly as a proportion of total E&G expenditures—on average, by 1.9 percentage points at research/doctoral institutions, by 2.5 percentage points at

comprehensive institutions, by 1.6 percentage points at bachelor’s institutions, and by

4.0 percentage points at 2-year institutions. The second largest expenditure categories

in 1997–98 were research (18.9 percent) at research/doctoral institutions, scholarships

and fellowships at comprehensive and bachelor’s institutions (12.1 percent and 14.5

percent, respectively), and institutional support (14.4 percent) at 2-year institutions.

• Expenditures for scholarships and fellowships—specifically institutional aid—at public institutions were one of the fastest growing expenditure categories. Over the period

of 1988–89 to 1997–98, institutional aid increased annually by 8.1 percent on average

at research/doctoral institutions in inflation-adjusted terms, 7.7 percent at comprehensive institutions, 8.0 percent at bachelor’s institutions, and 6.8 percent at 2-year institutions. As a result, scholarships and fellowships made up an increasing proportion of

total E&G expenditures at public institutions over this period—increasing by 1.8 percentage points at research/doctoral institutions, by 2.2 percentage points at comprehensive institutions, by 1.1 percentage points at bachelor’s institutions, and by 3.9

percentage points at 2-year institutions.

• At private not-for-profit institutions, instruction expenditures made up the largest proportion of total E&G expenditures in 1995–96—35.4 percent at research/doctoral institutions, 31.7 percent at comprehensive institutions, and 28.3 percent at bachelor’s

institutions. From 1988–89 to 1995–96, instruction expenditures increased slightly (0.3
Chapter VI: Summary of Findings and Conclusions

135

percentage points) as a proportion of total E&G expenditures at research/doctoral institutions, but decreased by 1.9 percentage points at comprehensive institutions and by

0.8 percentage points at bachelor’s institutions. Scholarships and fellowships were the

second largest category, accounting for 14.3 percent of total E&G expenditures at research/doctoral institutions, 22.6 percent at comprehensive institutions, and 25.1 percent at bachelor’s institutions.

• Institutional scholarships and fellowships at private not-for-profit institutions were one

of the fastest growing expenditure categories. Over the period of 1988–89 to 1995–96,

institutional aid increased annually by 8.7 percent on average at research/doctoral institutions in inflation-adjusted terms, by 10.2 percent at comprehensive institutions,

and by 8.5 percent at bachelor’s institutions. As a result, scholarships and fellowships

made up an increasing proportion of total E&G expenditures at private not-for-profit

institutions over this period—increasing by 3.0 percentage points at research/doctoral

institutions, by 5.0 percentage points at comprehensive institutions, and by 4.5 percentage points at bachelor’s institutions.

In Chapter V, analysis of the recently collected IPSFA data revealed patterns of financial

aid that differed among the groups of institutions, but which appeared to show some common

tendencies within each institutional sector.

• Among all groups of institutions, over half of first-time, full-time, degree/certificateseeking undergraduates received aid from any source, ranging from 56.8 percent at

public 2-year institutions to 85.7 percent at private not-for-profit bachelor’s institutions.

• At public 4-year institutions, the average percent receiving aid and average amount received varied by type of aid, but in general the highest figures were for student loan

aid. Public 2-year institutions presented a distinctly different situation, in which the

highest percentages and average amounts were for federal grant aid while relatively

low percentages of students received student loans or institutional aid.

• At private not-for-profit 4-year institutions, the highest average percentages of students

receiving aid were for institutional aid, while student loan aid tended to be the second

highest.

Limitations of the Research

Although this research improves and expands upon previous studies of costs and prices, it

remains limited with regard to answering some of Congress’ specific questions. Some, but not

all, of the limitations were caused by the reliance on existing institutional typologies and previously collected national data. Several changes to national data collection systems (and the underlying financial reporting standards at postsecondary education institutions) would be needed

to more fully answer Congress’ questions, including: more detailed institutional classification

systems; comparable financial accounting standards between the public and private not-for-profit
Chapter VI: Summary of Findings and Conclusions

136

sectors; detailed net price data; information on sources of revenue for institutional aid; standard

definitions for items such as merit aid and technology costs; isolation of revenue and expenditure

data by level of student; and information on marketing bands/peer groups, especially for sectors

in which competition heavily influences institutional decisionmaking.

Some of these limitations could conceivably be overcome through the collection of new

data over an appropriate period of time. In fact, recent changes were made to the accounting

standards used by private not-for-profit institutions and have been incorporated into national data

collection mechanisms; similar changes are expected for public institutions in the future. Nonetheless, new or revised data collection will not overcome all of the relevant research issues. For

instance, the continuing differences in accounting standards are likely to complicate the collection of comparable data on capital and depreciation costs for some time to come. The nature of

technology means that much of the costs of technology will always be hidden, as these expenditures are embedded within other functions. Perhaps most importantly, the production function of

higher education—the essential fact that the nature of the inputs also influences the costs of production and the value of the outputs—and the existence of multiple sources of revenue at postsecondary education institutions means that cost analysis (or any other purely quantitative

analysis) will always be somewhat limited in what it can reveal.

Conclusions about Research Models

As evidenced in this report, available national datasets can be used to describe and analyze

aggregate trends in costs, prices, and subsidies, for broad groups of institutions. These data also

allow regression models that can determine the associations between revenue and expenditure

variables and tuition—i.e., as one decreases, the other tends to increase. It is important to keep in

mind that the statistical models presented in this report are correlational in nature and cannot lead

to definitive conclusions regarding the interrelationships among changes in variables over time.

This research may be helpful in developing theories about the effects of expenditures, revenues,

financial aid, and other variables on prices. It is less useful in testing such theories, however. Ideally, simultaneous equation models should be constructed to explore the direct and indirect effects of costs, revenues, financial aid, market conditions and other external influences, family

resources, and college prices.90

In the process of performing the analyses in this report and in summarizing the opinions of

the expert authors, several conclusions emerged regarding the appropriateness of research models

 

90For a discussion of a conceptual framework for a structural equation model, see Pearson and Baldi (1998).
Chapter VI: Summary of Findings and Conclusions

137

designed to explore financial relationships in postsecondary education. The following considerations should be kept in mind:

• Public and private not-for-profit institutions operate in distinct circumstances, and

should be modeled separately.

• Greater disaggregation of institutions below the level of the Carnegie classification

should be done for institutions among both public and private not-for-profit institutions, as the current groups mask important differences in access to resources and market position. The classification of institutions by decile of subsidy, as suggested by

Winston in his commissioned paper (see Volume 2), may be an appropriate mechanism. For public 2-year institutions, consideration must be given to the criteria that

might be used to create sub-divisions to help distinguish among this large group of diverse institutions.91

• It is important to recognize, however, that the ability to carry out analyses on subgroups of institutions is limited by the number of cases needed to conduct accurate and

useful statistical analyses.

• To analyze relationships, more needs to be known about the interaction of enrollments

across sectors, and about the consequences of pricing decisions in the public sector on

student demand in the private sector. It might also be helpful to look at higher education systems within a particular state and the interactions among different types of institutions.

• Examining the relationships both between student aid and prices, and between federal

aid and institutional aid, requires distinguishing among different types of grant aid,

need-based loan aid, and unsubsidized loan aid, as well as between the volume of aid

and the terms and conditions of capital.

• The phenomenon of “tuition discounting” needs much more comprehensive analysis

than is possible with existing data and accounting conventions. Greater precision is

needed to understand the extent of merit aid in tuition discounting, and the relation of

merit aid to other forms of aid. The studies of institutional discounting referred to in

Lapovsky’s paper (see Volume 2) have been limited to the private not-for-profit sector.

It is widely believed that some form of tuition discounting, or differential pricing policies, is also an increasingly common pattern in public institutions.

• Given that existing models of change in prices tend to leave much of the variation unexplained, it might be useful to model government policy variables, such as changes in

student loan terms and conditions.

In addition, as McPherson and Schapiro note in their commissioned paper (see Volume 2),

more work is needed on theoretical explanations of observed trends and patterns in costs, revenues, prices, and other factors, including development of theories regarding the behavior of notfor-profit institutions in response to external changes, such as decreases in subsidies, and the im-

 

91An NCES report (Phipps, Shedd, and Merisotis 2001) may be helpful in this regard.
Chapter VI: Summary of Findings and Conclusions

138

pact of state policies on the behavior of public institutions. Any statistical model exploring these

issues will have to be based on sound theories of institutional and student behavior. At the same

time, constructing and estimating a simultaneous equation model that explores the interrelationships among variables will depend upon the existence of well defined, relevant data collected

over a reasonably long period of time (e.g., five or more years).
139

References

Allan, Ronald G. (1999). “Tuition Discounts, Institutional Student Aid and Scholarships Allowances.” Washington, DC: Sallie Mae Education Institute.

Baum, Sandy. (1996). A Primer on Economics for Financial Aid Professionals. Jointly sponsored

by The College Board and NASFAA, June. Available on the NASFAA website:

www.nasfaa.org.

Berkner, Lutz. (2000). Trends in Undergraduate Borrowing: Federal Student Loans in 1989-90,

1992-93, and 1995-96 (NCES 2000-151). U.S. Department of Education, National Center for

Education Statistics. Washington, DC: U.S. Government Printing Office.

Berry, William D. and Feldman, Stanley. (1985). Multiple Regression in Practice. Sage University Paper Series on Quantitative Applications in the Social Sciences No. 50. Newbury

Park, CA: Sage Publications.

Bowen, Howard R. (1980). The Costs of Higher Education: How Much Do Colleges and Universities Spend per Student and How Much Should They Spend. San Francisco, CA: Jossey-Bass

Publishers, Inc.

Bradburd, Ralph M., and Mann, Duncan P. (1990). “The Market for Higher Education: An Economic Analysis.” In Pelavin Associates, Inc., 1991, Background Papers Prepared for the

“Study of the Escalating Costs of Higher Education.” Prepared under contract for the U.S.

Education Department.

Cohen, Jacob. (1988). Statistical Power Analysis for the Behavioral Sciences, 2nd Edition.

Hillsdale, NJ: Lawrence Erlbaum Associates.

Conklin, Kristen. (1998). Federal Tuition Tax Credits and State Higher Education Policy. San

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Coopers and Lybrand, L.L.P. (1997). “The Impact of Federal Student Assistance on College Tuition Levels.” Washington, DC, September.
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Davis, Jerry S. (1997). College Affordability: A Closer Look at the Crisis. Washington, DC: Sallie Mae Education Institute.

Fowler, William J., Jr. and Monk, David H. (2001). A Primer for Making Cost Adjustments in

Education (NCES 2001-323). U.S. Department of Education, National Center for Education

Statistics. Washington, DC: U.S. Government Printing Office.

Hauptman, Arthur M., and Krop, Cathy. (1998). “Federal Student Aid and the Growth in College

Costs and Tuition: Examining the Relationship.” In National Commission on the Cost of

Higher Education, Straight Talk About College Costs and Prices (pp. 70-83). Phoenix, AZ:

Oryx Press.

Jenny, Hans H. (1996). Cost Accounting in Higher Education. Washington, DC: National Association of College and University Business Officers (NACUBO).

Kane, Thomas J. (1999). “Student Aid After Tax Reform: Risks and Opportunities.” In Jacqueline E. King (ed.), Financing a College Education: How It Works, How It’s Changing (pp.

137-150). Phoenix, AZ: The American Council on Education and The Oryx Press.

Kennedy, Peter. (1998). A Guide to Econometrics, Fourth Edition. Cambridge, MA: The MIT

Press.

McPherson, Michael, and Schapiro, Morton Owen. (1991). Keeping College Affordable: Government and Educational Opportunity. Washington, DC: The Brookings Institution.

McPherson, Michael, and Schapiro, Morton Owen. (1998). The Student Aid Game: Meeting

Need and Rewarding Talent in American Higher Education. Princeton, NJ: Princeton University Press.

National Commission on the Cost of Higher Education. (1998). Straight Talk About College

Costs and Prices. Phoenix, AZ: Oryx Press, January.

Oberg, John H. (1997). “Testing Federal Student-Aid Fungibility in Two Competing Versions of

Federalism.” Publius: The Journal of Federalism, 27(1): 115-134.

Pearson, Roy J., and Baldi, Stephane. (1997). “Student Aid and Tuition: Toward a Causal Analysis.” In National Commission on the Cost of Higher Education, Straight Talk About College

Costs and Prices (pp. 93-101). Phoenix, AZ: Oryx Press.
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Redd, Kenneth E. (2000). Discounting Toward Disaster: Tuition Discounting, College Finances,

and Enrollments of Low-Income Undergraduates. New Agenda Series, 3(2). Indianapolis,

IN: USA Group Foundation, December.

Stringer, William L., and Cunningham, Alisa F. with Colleagues. (1999). Cost, Price, and Public

Policy: Peering into the Higher Education Black Box. New Agenda Series, 1(3). Indianapolis, IN: USA Group Foundation, August.

Turner, Sarah E. (1998). “Does Federal Aid Affect the Price Students Pay for College? Evidence

from the Pell Program.” Unpublished paper, University of Virginia.

U.S. General Accounting Office (GAO). (1998). Higher Education: Tuition Increases and Colleges’ Efforts to Contain Costs (GAO/HEHS-98-227). Washington, DC: U.S. Government

Printing Office, September.

Westat Inc. and Pelavin Associates. (1994). An Analysis of Institutional Decision Making—Final

Report on Estimation Results. Prepared for the U.S. Education Department, Office of the Under Secretary.

Winston, Gordon C. (1998). “College Costs: Subsidies, Intuition, and Policy.” In National Commission on the Cost of Higher Education, Straight Talk About College Costs and Prices (pp.

117-127). Phoenix, AZ: Oryx Press.

Yanikoski, Richard A., and Wilson, Richard F. (1984). “Differential Pricing of Undergraduate

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143

Appendix A—Technical Notes and Methodology

Integrated Postsecondary Education Data System

The Integrated Postsecondary Education Data System (IPEDS) is a comprehensive database

that encompasses all identified institutions whose primary purpose is to provide postsecondary

education. IPEDS consists of institutional-level data that can be used to describe trends in higher

education at the institutional, state, and/or national levels.

Postsecondary education is defined within IPEDS as the provision of formal instructional

programs whose curriculum is designed primarily for students who have completed the requirements for a high school diploma or its equivalent. This includes academic, vocational, and continuing professional education programs, and excludes avocational and adult basic education

programs.

IPEDS includes information about baccalaureate or higher degree-granting institutions, 2-

year award institutions, and less-than-2-year institutions (i.e. institutions whose awards usually

result in terminal occupational awards or are creditable toward a formal 2-year or higher award).

Each of these three categories is further disaggregated by control (public; private not-for-profit;

and private for-profit), resulting in nine institutional categories or sectors.

Specialized, but compatible, reporting formats have been developed for these nine sectors

of postsecondary education providers. In general, the surveys/reports developed for postsecondary institutions granting baccalaureate and higher degrees are the most extensive; forms for the

2-year and less-than-2-year awards granting sectors request less data. This design feature accommodates the varied operating characteristics, program offerings, and reporting capabilities

that differentiate postsecondary institutional sectors while yielding comparable statistics for all

sectors.

Data are collected from approximately 11,000 postsecondary institutions. IPEDS has been

designed to produce national-, state-, and institutional-level data for most postsecondary institutions. However, prior to 1993, only national-level estimates from a sample of institutions were

available for the private, less-than-2-year institutions.
Appendix A—Technical Notes and Methodology

144

Until recently, data in IPEDS were organized into several survey areas.92 For this report, the

most important surveys include the following:

• Institutional Characteristics, including institutional names and addresses; congressional districts; counties; telephone numbers; tuition; control or affiliation; calendar

systems; levels of degrees and awards offered; types of programs; and accreditation for

all postsecondary education institutions in the United States and outlying territories.

• Fall Enrollment, including information about full- and part-time enrollment by racial/ethnic category and sex for undergraduates, first-professional, and graduate students. Age distributions by level of enrollment and sex were collected in oddnumbered years, and first-time degree-seeking student enrollments by residence status

were collected in even-numbered years.

• Financial Statistics, including each institution’s current fund revenues by source (e.g.,

tuition and fees, government, gifts); current fund expenditures by function (e.g., instruction, research); assets and indebtedness; and endowment investments.

• Salaries, Tenure, and Fringe Benefits of Full-time Instructional Faculty, including information about full-time instructional faculty by gender and tenure status, and outlays

for salaries and fringe benefits.

Other components of IPEDS provided data on fall staff, degrees and certificates awarded,

and library resources. Detailed information about IPEDS is available at the National Center for

Education Statistics Web site (http://nces.ed.gov).

At the time this report was written, Finance survey data for 1996–97 and 1997–98 were

available only for public institutions and did not include imputations. Finance data were available

only until 1995–96 for private not-for-profit institutions. This was due to the changes in the

IPEDS Finance survey incorporated in Fiscal Year 1997 as a result of the changes in Financial

Accounting Standards Board (FASB) guidelines for private not-for-profit institutions.

Also, some of the data from the Salaries, Tenure, and Fringe Benefits of Full-time Instructional Faculty survey are suppressed in the public use data files for reasons of confidentiality. For

this report, the restricted data files were used. Because a restricted file was unavailable for 1989–

90, suppressed data fields were estimated through interpolation from data for subsequent years.

Institutional Prices and Student Financial Aid Survey

The Institutional Prices and Student Financial Aid Survey (IPSFA) was a Web-based survey administered by NCES in the 1999–2000 data collection cycle to collect institutional infor-

 

92In 1999-2000, the IPEDS collection framework was converted to a web-based system, and changes were made to the fields

collected.
Appendix A—Technical Notes and Methodology

145

mation on price of attendance, student financial aid, and other characteristics. The original IPSFA

survey was planned as a pilot study to test institutions’ ability both to provide data on these issues and to submit data via the Web. In 2000–2001, various components of IPSFA were incorporated into the redesigned IPEDS surveys, which are now administered through a Web-based data

collection process.

The IPSFA universe of institutions was based on the IPEDS universe. Data were collected

from more than 6,000 institutions, including public, private not-for-profit, and private for-profit

institutions at the 4-year, 2-year, and less-than-2-year levels.

Data in IPSFA were organized into several subcomponents, including the following:

• Institutional Characteristics, including institutional names, addresses; telephone numbers; web addresses; and control or affiliation.

• Student Count, including information about the number and percentage of first-time,

full-time, degree/certificate-seeking undergraduates.

• Academic Tuition, including the in-state and out-of-state tuition levels charged to firsttime, full-time degree/certificate-seeking undergraduates for three years (1997–98 to

1999–2000), as well as charges for books and supplies, room and board, and other expenses.

• Financial Aid, including information on the percentage of first-time, full-time degree/certificate-seeking undergraduates receiving federal grants, state grants, institutional grants, and loan aid for either 1997–98 or 1998–99, as well as the average

amounts of aid received.

At the time this report was written, the IPSFA data for 1999–2000 had been edited but did

not include imputations.

Bureau of Economic Analysis Regional Accounts Data

The Bureau of Economic Analysis (BEA) at the U.S. Department of Commerce collects

state personal income data under its State Annual Series. The model presented in Chapter IV of

this report uses the state per capita income data released in July 1999, the most recent estimates

available at the time the analysis was performed. Estimates of state personal income, per capita

personal income, population, disposable personal income, and per capita disposable personal income for 1969 to 1998 for all states, regions, and the United States were available for download

from the BEA’s Web site. The per capita personal income estimates were computed from administrative records and other sources, using the mid-year population estimates of the Bureau of
Appendix A—Technical Notes and Methodology

146

the Census. For more information, see the Bureau of Economic Analysis Web site

(http://www.bea.doc.gov).

Accuracy of Estimates

Most of the statistics in this report are estimates derived from a population. In using a census of an entire population there is not a sampling error, but there is still the possibility of nonsampling error.

Nonsampling errors can be attributed to a number of sources: inability to obtain complete

information about all institutions (i.e., some institutions refused to participate, or participated but

answered only certain items); ambiguous definitions; differences in interpreting questions; inability or willingness to give correct information; mistakes in recording or coding data; and other

errors of collecting, processing, and imputing missing data.

To compensate for nonresponse, adjustments are often made, referred to as imputations.

Imputations are usually made separately within various groups of institutions that have similar

characteristics. If a particular institution responded in previous and later years, simple interpolations may also be used to substitute for a missing response.

In addition to nonsampling errors, sampling errors may have occurred in the estimates of

state per capita personal income, which were used in the simultaneous equation model presented

in Chapter IV. Although BEA produced its estimates of state per capita income based on samples, the estimates were aggregated to the state level and the standard errors are likely to be very

small. The standard error is a measure of the variability due to sampling when estimating a parameter; very small standard errors signify that a high level of precision would be expected from

a particular sample.

Most of the estimates in this report were produced using the SPSS 10.0 software package.

SPSS makes it possible for users to specify and generate a variety of univariate and multivariate

analyses, including linear regression analysis. In addition, the STATA 6.0 software package was

used to produce the estimates for the simultaneous equation models presented in Chapter IV, using the three-stage least squares procedure.
Appendix A—Technical Notes and Methodology

147

IPEDS Data Used in Chapters III and IV

Selection Criteria

The trend analyses and statistical models presented in Chapters III and IV used panels of

institutions constructed from IPEDS data, over the period 1988–89 to 1997–98 for public institutions and 1988–89 to 1995–96 for private not-for-profit institutions. The difference in time periods is a result of the changes in FASB guidelines for private not-for-profit institutions, which

were incorporated into the IPEDS finance survey beginning in Fiscal Year 1997.

As the dependent variable in these models was first-time, full-time undergraduate tuition

and fees, the panel criteria targeted postsecondary institutions that primarily serve full-time, undergraduate students. To an extent, this attempted to mitigate the fact that IPEDS revenue and

expenditure data cannot be broken down by level of student. It is also common practice in cost

studies to select a group of institutions that are somewhat comparable, and the criteria used here

are similar to those used in other contemporary studies.93

To create the panels, institutional characteristics data were used to define and measure selection criteria, using 1997–98 data for public institutions and 1995–96 data for private not-forprofit institutions. Institutions were drawn from all Title IV participating, degree-granting institutions located in the 50 states and the District of Columbia. Both 4-year and 2-year institutions

were included for public institutions, while only 4-year institutions were included for private notfor-profit institutions. The 4-year institutions were further divided by Carnegie classification into

research/doctoral, comprehensive, and bachelor’s institutions (institutions classified as

“other/specialized” or not classified were excluded). Institutions that enrolled less than 200 FTE

students were excluded from the universe. Finally, for 4-year institutions only, institutions with

less than 50 percent undergraduate fall headcount enrollment and institutions with less than 25

percent full-time fall headcount enrollment were excluded.

Parent/Child Institutions

The IPEDS surveys allow “parent” institutions to report data for campuses or branch institutions, or the “child” institutions may report information on their own. In many cases, schools

reported data separately for campuses or branch institutions for some IPEDS surveys but not others, or reported data separately in certain years but in the aggregate in other years. To deal with

these inconsistencies across surveys and/or years, financial data were disaggregated, using the

 

93See, for example, GAO (1998); Coopers and Lybrand (1997); Winston (1998).
Appendix A—Technical Notes and Methodology

148

distribution of FTE enrollment across branch campuses to allocate revenues and expenditures.

When the discrepancies could not be resolved, institutions were eliminated from the universe.

Missing Data and Outliers

In cleaning the data for the remaining institutions, it was important to impute for missing

data so that the panel institutions had data for all years.94 As a first step, institutions that had

missing data in key variables (tuition, fall enrollment, credit hour activity, total revenue, and

scholarships and fellowships) for a certain number of years were eliminated from the universe.

The cut-offs chosen were 3 or more years out of 10 years for public 4-year institutions, 6 or more

years out of 10 years for public 2-year institutions, and 6 or more years out of 8 years for private

not-for-profit institutions.95 For institutions remaining in the universe after this cut-off, a simple

interpolation procedure based on previous and subsequent years was used to impute for missing

data.

After the imputation of missing data, the distributions of all of the variables were examined

to spot any errors caused by imputations or estimations. Errors in imputation were corrected

whenever possible. Data reported by the institutions were not altered, even in the case of outliers.

However, for the public institutions only, in order to deal with remaining outliers that appeared to

be extreme but could not be corrected, certain variables were Winsor trimmed from the top and

bottom of the distribution by 1 or 2 percentiles, i.e., cases with extreme outliers in specific variables were removed from the analysis. The trimming process was done consistently within each

institutional type; that is, for each group of public institutions, the variables that were trimmed

for the ten-year time period also were trimmed in each of the sub-periods. Public 2-year institutions presented a particular obstacle, as the widespread existence of extreme outliers made trimming of virtually all the variables necessary; although this group had the largest number of cases

(813), approximately 10 percent of the cases were eliminated due to the trimming process.

 

94Note that full imputations (defined as response status = 4) already in the dataset were treated as missing data so that imputations would be consistent across all data.

95The cut-offs were chosen for each type of institutions such that the fewest number of years could be used without eliminating

more than a quarter of the institutions.
Appendix A—Technical Notes and Methodology

149

Variable Definition

After the panels were created and imputations were made, all financial data were adjusted

for inflation using the Consumer Price Index (CPI-U, 1982–84 = 100).96 Financial variables were

adjusted to constant 1999 dollars.

Revenue and expenditure variables were calculated on a per FTE student basis, where FTE

was generated from reported or estimated fall instructional activity (credit/contact hours). One

component of the IPEDS Institutional Characteristics survey is instructional credit/contact hour

activity for undergraduates, graduate students, and professional students. To generate total FTE

for each institution, a formula was used.97 Since instructional activity data were collected only for

1991–92 and later years, instructional activity values were estimated for the years in which they

were not available. To estimate the values, ratios of total FTE generated from credit hour activity

to total headcount fall enrollment were calculated separately for undergraduates, graduate students, and professional students (for the nearest year in which instructional activity data were

available); these ratios were applied to total enrollment for years in which instructional activity

data were missing. A similar procedure was used to estimate first-time freshman FTE for the

model in Chapter IV.

For the panels of private not-for-profit institutions, the final dataset was rearranged such

that the structure included seven records for each institution, one for each year. Dummy variables

were then inserted to identify the years. Because of the need for lagged variables in the simultaneous equations model (see Chapter IV), the time period for the model extended from 1989–90

to 1995–96, while the data (for some variables) began in 1988–89. Also, natural logarithms were

taken of the model variables.98 In cases in which variables contained missing, zero, or negative

values (for which logarithms return no value), zero values were inserted into the logged variables

and separate dummy variables were created to identify these cases. Negative values occurred in

some computed variables due to the imputation process.

 

96The Consumer Price Index for All Urban Consumers (CPI-U) measures changes in relation to a base period, in this case the

average index level for a 36-month period covering 1982, 1983, and 1984, which is set equal to 100.

97For quarter calendar systems, one FTE is equivalent to 15 credit hours (300 contact hours) for undergraduates, 12 credit hours

for graduate students, and 16 credit hours for professional students; for semester, trimester, and other calendar systems, one FTE

is equivalent to 15 credit hours (450 contact hours) for undergraduates, 12 credit hours for graduate students, and 16 credit hours

for professional students.

98Logs were not taken of the ratio of graduate to total enrollment due to the large number of zero values, especially for comprehensive and bachelor’s institutions.
Appendix A—Technical Notes and Methodology

150

Final Universe for Chapters III and IV

The various procedures described above eliminated institutions from the original dataset

(tables A1 and A2). The final datasets comprised four panels of public institutions with data for

all years of the ten-year period, and three panels of private not-for-profit 4-year institutions with

data for all years of the eight-year period. The total number of public institutions remaining in the

panels was 1,235 (research/doctoral = 135; comprehensive = 221; bachelor’s = 66; 2-year = 813).

The total number of private not-for-profit institutions remaining in the panels was 690 (research/doctoral = 47; comprehensive = 192; bachelor’s = 451).

Although the final universe includes 64 percent of the original number of public 4- and 2-

year institutions with data, the institutions remaining in the panels comprised 84 percent of undergraduate enrollment at all public 4-year institutions and 81 percent of undergraduate enrollment at all 2-year institutions in 1997–98. The final universe of private not-for-profit 4-year

institutions includes 34 percent of the original number, but captures 63 percent of the total undergraduate enrollment within these institutions.

In order to examine the differences between the final universe and the institutions that were

excluded, a bias analysis was performed for each institutional type, using the original IPEDS data

files.99 In general, the institutions excluded from the analysis were fairly similar to those included

in the final universe on a range of variables measuring tuition, revenues, expenditures, and enrollment (tables A3 to A9). Some exceptions were:

• Of public 4-year institutions, research/doctoral institutions excluded from the universe

had higher proportions of graduate students and higher revenues and expenditures per

FTE, on average, than included institutions (table A3).100 Excluded comprehensive institutions tended to have fewer students, on average (table A4).

• Of public 2-year institutions, excluded institutions had fewer students and slightly

higher revenues and expenditures per FTE student, on average, than 2-year institutions

included in the final universe (table A6).

• Of private not-for-profit 4-year institutions, research/doctoral institutions excluded

from the final universe had higher proportions of graduate students and higher revenues and expenditures per FTE, on average, than included institutions (table A7).101

 

99Note that many institutions had missing data for the variables examined; no attempts were made to impute for missing data, for

either the included institutions or the eliminated institutions.

100Note that one institution in particular, a graduate/professional school in health sciences, appeared to be pulling up the financial averages.

101Again, a few institutions appeared to be highly influencing the financial averages.
Appendix A—Technical Notes and Methodology

151

Table A1.—Final universe of public 4-year and 2-year institutions for Chapter III

Percentage of

Number original number

Original number of public 4-year and 2-year institutions in IPEDS in 1997–98 1,921 100.0 

 Less institutions removed through the parent/child procedure 94 4.9 

 Sub-total 1,827 95.1 

 Less institutions removed through selection criteria 333 17.3 

 Sub-total 1,494 77.8 

 Less institutions removed due to missing data 211 11.0 

 Sub-total 1,283 66.8 

 Less institutions excluded due to specialized, other, or missing Carnegie 48 2.5 

 classification

Final universe 1,235 64.3 

NOTE: Selection criteria were: Title IV participation, degree-granting status, location in the 50 states and the District of

Columbia, enrollment (at least 200 full-time equivalent enrollment), and percentage of undergraduate and full-time enrollment

(at least 50 percent undergraduate and 25 percent full-time enrollment, respectively; relevant only for 4-year institutions).

SOURCE: U.S. Education Department, National Center for Education Statistics, Integrated Postsecondary Education Data

System (IPEDS), Full 1998 Collection Year.

Table A2.—Final universe of private not-for-profit 4-year institutions for Chapter IV

Percentage of

Number original number

Original number of private not-for-profit 4-year institutions in IPEDS in 2004 100.0 

 1995–96 

 Less institutions removed through the parent/child procedure 92 4.6 

 Sub-total 1912 95.4 

 Less institutions removed through selection criteria 1001 50.0 

 Sub-total 911 45.5 

 Less institutions removed due to missing data 101 5.0 

 Sub-total 810 40.4 

 Less institutions excluded due to specialized, other, or missing Carnegie 120 6.0 

 classification

Final universe 690 34.4 

NOTE: Selection criteria were: Title IV participation, degree-granting status, location in the 50 states and the District of

Columbia, enrollment (at least 200 full-time equivalent enrollment), and percentage of undergraduate and full-time enrollment

(at least 50 percent undergraduate and 25 percent full-time enrollment, respectively).

SOURCE: U.S. Education Department, National Center for Education Statistics, Integrated Postsecondary Education Data

System (IPEDS), Full 1996 Collection Year.
Appendix A—Technical Notes and Methodology

152

Table A3.—Final universe of public research/doctoral institutions in Chapter III compared to excluded

Table A3.—institutions: 1997–98

Final Excluded

universe N institutions N

 Total 135 16

Average in-state undergraduate tuition $3,420 135 $3,140 15

Average percent change in in-state undergraduate 81.1 135 104.2 14

 tuition since 1989–90

Average revenues per FTE:

 Tuition $5,071 132 $5,186 15

 State appropriations $8,269 132 $10,699 15

 Total current revenue $26,950 132 $44,906 15

 Tuition as a percentage of total revenue 21.8 132 24.6 15

 State appropriations revenue as a percentage of 34.1 132 32.1 15

 total revenue

Average expenditures per FTE:

 Instruction $7,330 132 $11,198 15

 Research $4,020 132 $8,835 15

 Academic support $2,000 132 $6,286 15

 Student services $904 132 $1,198 15

 Institutional support $1,625 132 $2,764 15

 Scholarships and fellowships $1,619 132 $2,070 15

 Institutional scholarships and fellowships $583 130 $944 12

 E&G expenditures $21,152 132 $37,976 15

 Total current expenditures $26,773 132 $45,995 15

 Instruction as a percentage of total expenditures 30.1 132 42.0 15

Average enrollment:

 FTE undergraduates 13,703 135 14,837 14

 Total headcount enrollment 20,754 135 19,470 16

 Undergraduate headcount enrollment 15,691 135 14,809 16

 First-time, full-time headcount enrollment 2,630 135 2,488 16

 Percent undergraduate 76.1 135 68.2 16

 Percent full-time 73.9 135 75.5 16

NOTE: Educational and general (E&G) expenditures include the following functional categories: instruction, research, public

service, academic support, student services, institutional support, plant operation and maintenance, scholarships and fellowships,

and mandatory and non-mandatory transfers. Full-time equivalent (FTE) enrollment was calculated from instructional (credit/

contact hour) activity, as described in this appendix.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data

System (IPEDS), Full Collection Years 1990 and 1998.
Appendix A—Technical Notes and Methodology

153

Table A4.—Final universe of public comprehensive institutions in Chapter III compared to excluded

Table A4.—institutions: 1997–98

Final Excluded

universe N institutions N

 Total 221 54

Average in-state undergraduate tuition $2,834 221 $2,463 54

Average percent change in in-state undergraduate 87.4 213 81.1 52

 tuition since 1989–90

Average revenues per FTE:

 Tuition $3,534 220 $3,689 52

 State appropriations $5,378 218 $6,260 51

 Total current revenue $13,059 220 $15,305 52

 Tuition as a percentage of total revenue 27.5 220 25.2 52

 State appropriations revenue as a percentage of 41.5 218 43.3 51

 total revenue

Average expenditures per FTE:

 Instruction $4,505 220 $5,089 52

 Research $330 200 $391 46

 Academic support $1,046 220 $1,236 52

 Student services $883 220 $979 52

 Institutional support $1,319 220 $1,804 52

 Scholarships and fellowships $1,347 220 $1,626 52

 Institutional scholarships and fellowships $316 215 $264 38

 E&G expenditures $11,106 220 $13,157 52

 Total current expenditures $12,854 220 $14,992 52

 Instruction as a percentage of total expenditures 35.6 220 35.1 52

Average enrollment:

 FTE undergraduates 6,247 221 3,856 53

 Total headcount enrollment 8,758 221 6,123 54

 Undergraduate headcount enrollment 7,351 221 4,978 54

 First-time, full-time headcount enrollment 1,148 221 717 54

 Percent undergraduate 84.7 221 81.0 54

 Percent full-time 70.1 221 59.5 54

NOTE: Educational and general (E&G) expenditures include the following functional categories: instruction, research, public

service, academic support, student services, institutional support, plant operation and maintenance, scholarships and fellowships,

and mandatory and non-mandatory transfers. Full-time equivalent (FTE) enrollment was calculated from instructional (credit/

contact hour) activity, as described in this appendix.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data

System (IPEDS), Full Collection Years 1990 and 1998.
Appendix A—Technical Notes and Methodology

154

Table A5.—Final universe of public bachelor's institutions in Chapter III compared to excluded institutions:

Table A5.—1997–98

Final Excluded

universe N institutions N

 Total 66 20

Average in-state undergraduate tuition $2,943 66 $2,699 16

Average percent change in in-state undergraduate 80.3 66 126.6 14

 tuition since 1989–90

Average revenues per FTE:

 Tuition $3,367 65 $3,164 17

 State appropriations $4,982 61 $4,787 15

 Total current revenue $12,291 65 $12,063 17

 Tuition as a percentage of total revenue 29.0 65 30.9 17

 State appropriations revenue as a percentage of 40.0 61 32.5 15

 total revenue

Average expenditures per FTE:

 Instruction $3,968 65 $4,089 17

 Research $162 52 $400 16

 Academic support $907 65 $1,085 17

 Student services $967 65 $941 17

 Institutional support $1,292 65 $1,956 17

 Scholarships and fellowships $1,519 65 $2,004 17

 Institutional scholarships and fellowships $317 62 $204 14

 E&G expenditures $10,536 65 $9,887 17

 Total current expenditures $12,310 65 $10,892 17

 Instruction as a percentage of total expenditures 33.9 65 68.7 17

Average enrollment:

 FTE undergraduates 2,416 66 2,716 18

 Total headcount enrollment 3,059 66 4,150 18

 Undergraduate headcount enrollment 3,005 66 4,031 18

 First-time, full-time headcount enrollment 529 66 488 18

 Percent undergraduate 98.0 66 96.8 18

 Percent full-time 72.5 66 62.8 18

NOTE: Educational and general (E&G) expenditures include the following functional categories: instruction, research, public

service, academic support, student services, institutional support, plant operation and maintenance, scholarships and fellowships,

and mandatory and non-mandatory transfers. Full-time equivalent (FTE) enrollment was calculated from instructional (credit/

contact hour) activity, as described in this appendix.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data

System (IPEDS), Full Collection Years 1990 and 1998.
Appendix A—Technical Notes and Methodology

155

Table A6.—Final universe of public 2-year institutions in Chapter III compared to excluded institutions:

Table A6.—1997–98

Final Excluded

universe N institutions N

 Total 813 467

Average in-state undergraduate tuition $1,431 787 $1,225 376

Average percent change in in-state undergraduate 86.1 768 143.7 253

 tuition since 1989–90

Average revenues per FTE:

 Tuition $1,907 769 $1,963 157

 State appropriations $3,800 748 $6,513 129

 Total current revenue $9,714 769 $14,517 157

 Tuition as a percentage of total revenue 20.3 769 15.3 157

 State appropriations revenue as a percentage of 39.4 769 47.7 129

 total revenue

Average expenditures per FTE:

 Instruction $3,836 769 $5,396 157

 Academic support $702 768 $1,227 124

 Student services $861 769 $1,261 138

 Institutional support $1,291 769 $2,078 145

 Scholarships and fellowships $1,104 769 $1,909 133

 Institutional scholarships and fellowships $123 633 $118 86

 E&G expenditures $8,967 769 $12,686 157

 Total current expenditures $9,575 769 $13,495 157

 Instruction as a percentage of total expenditures 40.2 769 43.9 157

Average enrollment:

 FTE undergraduates 3,107 813 1,361 354

 Total (undergraduate) headcount enrollment 5,442 813 2,829 368

 First-time, full-time headcount enrollment 957 813 525 368

 Percent full-time 41.3 813 52.1 368

NOTE: Educational and general (E&G) expenditures include the following functional categories: instruction, research, public

service, academic support, student services, institutional support, plant operation and maintenance, scholarships and fellowships,

and mandatory and non-mandatory transfers. Full-time equivalent (FTE) enrollment was calculated from instructional (credit/

contact hour) activity, as described in this appendix.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data

System (IPEDS), Full Collection Years 1990 and 1998.
Appendix A—Technical Notes and Methodology

156

Table A7.—Final universe of private not-for-profit research/doctoral institutions in Chapter IV compared to

Table A7.—excluded institutions: 1995–96

Final Excluded

universe N institutions N

 Total 47 38

Average in-state undergraduate tuition $16,266 46 $15,194 34

Average percent change in in-state undergraduate 50.5 46 46.9 31

 tuition since 1989–90

Average revenues per FTE:

 Tuition $16,362 47 $16,646 37

 Federal grants and contracts $5,314 47 $18,449 37

 Private gifts $3,096 47 $13,703 37

 Endowment income $2,799 47 $8,706 37

 Total current revenue $44,688 47 $97,365 37

 Tuition as a percentage of total revenue 48.2 47 43.0 37

 Philanthropic revenue as a percentage of total revenue 12.7 47 15.4 37

Average expenditures per FTE:

 Instruction $11,682 47 $15,323 37

 Research $4,652 47 $22,934 37

 Academic support $2,699 47 $3,954 37

 Student services $1,558 47 $1,601 37

 Institutional support $3,389 47 $7,070 37

 Scholarships and fellowships $4,701 47 $4,232 37

 Institutional scholarships and fellowships $3,744 47 $3,096 36

 E&G expenditures $32,941 47 $65,934 37

 Total current expenditures $44,135 47 $95,852 37

 Instruction as a percentage of total expenditures 28.7 47 28.2 37

Average enrollment:

 FTE undergraduates 5,944 47 4,185 38

 Total headcount enrollment 10,260 47 10,191 38

 Undergraduate headcount enrollment 6,595 47 4,806 38

 First-time, full-time headcount enrollment 1,346 47 911 38

 Percent undergraduate 65.2 47 42.1 38

 Percent full-time 78.6 47 70.1 38

NOTE: Educational and general (E&G) expenditures include the following functional categories: instruction, research, public

service, academic support, student services, institutional support, plant operation and maintenance, scholarships and fellowships,

and mandatory and non-mandatory transfers. Full-time equivalent (FTE) enrollment was calculated from instructional (credit/

contact hour) activity, as described in this appendix.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data

System (IPEDS), Full Collection Years 1990 and 1996.
Appendix A—Technical Notes and Methodology

157

Table A8.—Final universe of private not-for-profit comprehensive institutions in Chapter IV compared to

Table A8.—excluded institutions: 1995–96

Final Excluded

universe N institutions N

 Total 192 62

Average in-state undergraduate tuition $11,267 191 $9,483 61

Average percent change in in-state undergraduate 54.6 187 46.0 58

 tuition since 1989–90

Average revenues per FTE:

 Tuition $11,241 192 $10,301 60

 Federal grants and contracts $1,008 192 $927 60

 Private gifts $1,190 192 $1,190 60

 Endowment income $474 192 $417 60

 Total current revenue $17,712 192 $15,583 60

 Tuition as a percentage of total revenue 65.0 192 68.4 60

 Philanthropic revenue as a percentage of total revenue 9.3 192 8.4 60

Average expenditures per FTE:

 Instruction $4,863 192 $4,426 60

 Research $222 192 $112 60

 Academic support $1,030 192 $1,150 60

 Student services $1,499 192 $1,325 60

 Institutional support $2,248 192 $2,500 60

 Scholarships and fellowships $3,465 192 $2,625 60

 Institutional scholarships and fellowships $2,435 192 $1,609 60

 E&G expenditures $15,337 192 $13,894 60

 Total current expenditures $17,342 192 $15,322 60

 Instruction as a percentage of total expenditures 28.3 192 30.1 60

Average enrollment:

 FTE undergraduates 2,005 192 2,196 62

 Total headcount enrollment 3,181 192 4,446 62

 Undergraduate headcount enrollment 2,392 192 2,812 62

 First-time, full-time headcount enrollment 448 192 394 62

 Percent undergraduate 76.5 192 65.4 62

 Percent full-time 64.7 192 56.8 62

NOTE: Educational and general (E&G) expenditures include the following functional categories: instruction, research, public

service, academic support, student services, institutional support, plant operation and maintenance, scholarships and fellowships,

and mandatory and non-mandatory transfers. Full-time equivalent (FTE) enrollment was calculated from instructional (credit/

contact hour) activity, as described in this appendix.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data

System (IPEDS), Full Collection Years 1990 and 1996.
Appendix A—Technical Notes and Methodology

158

Table A9.—Final universe of private not-for-profit bachelor's institutions in Chapter IV compared to

Table A9.—excluded institutions: 1995–96

Final Excluded

universe N institutions N

 Total 451 88

Average in-state undergraduate tuition $11,628 449 $8,208 83

Average percent change in in-state undergraduate 52.8 440 54.2 67

 tuition since 1989–90

Average revenues per FTE:

 Tuition $11,939 451 $9,162 86

 Federal grants and contracts $1,125 451 $1,779 87

 Private gifts $2,394 451 $3,667 86

 Endowment income $1,625 451 $1,020 86

 Total current revenue $21,956 451 $19,481 86

 Tuition as a percentage of total revenue 55.8 451 49.8 86

 Philanthropic revenue as a percentage of total revenue 16.2 451 19.3 86

Average expenditures per FTE:

 Instruction $5,278 451 $4,280 86

 Research $138 451 $74 87

 Academic support $1,214 451 $1,358 86

 Student services $1,927 451 $1,524 86

 Institutional support $3,036 451 $3,666 86

 Scholarships and fellowships $4,683 451 $3,599 86

 Institutional scholarships and fellowships $3,355 450 $2,036 84

 E&G expenditures $18,655 451 $16,967 86

 Total current expenditures $21,506 451 $19,109 86

 Instruction as a percentage of total expenditures 24.5 451 23.1 86

Average enrollment:

 FTE undergraduates 1,173 451 1,191 87

 Total headcount enrollment 1,422 451 1,740 88

 Undergraduate headcount enrollment 1,355 451 1,643 88

 First-time, full-time headcount enrollment 297 451 277 88

 Percent undergraduate 95.9 451 94.5 88

 Percent full-time 81.7 451 75.2 88

NOTE: Educational and general (E&G) expenditures include the following functional categories: instruction, research, public

service, academic support, student services, institutional support, plant operation and maintenance, scholarships and fellowships,

and mandatory and non-mandatory transfers. Full-time equivalent (FTE) enrollment was calculated from instructional (credit/

contact hour) activity, as described in this appendix.

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data

System (IPEDS), Full Collection Years 1990 and 1996.
Appendix A—Technical Notes and Methodology

159

IPSFA and IPEDS Data Used for Chapter V

Selection Criteria

For the trend analysis and statistical modeling presented in Chapter V, the universe of institutions was drawn from public 2-year and 4-year and private not-for-profit 4-year institutions

that are Title IV participating, degree-granting, and located in the 50 states and the District of

Columbia. Public and private not-for-profit 4-year institutions were further divided by Carnegie

classification into research/doctoral, comprehensive, and bachelor’s institutions102 (institutions

classified as “other/specialized” or not classified were excluded). As the financial aid variables in

the IPSFA dataset are based on first-time, full-time, degree/certificate-seeking undergraduate

students, institutions that enrolled less than 50 first-time, full-time, degree/certificate-seeking undergraduate students were excluded from the analysis. IPSFA data for 1999–2000 were used to

define and measure all of these selection criteria.

Missing Data

In cases in which tuition was missing or zero, cases in which there were missing data for all

of the financial aid variables (federal grants, state grants, institutional grants, and loans), and

cases in which the financial aid year indicator was missing, the institutions were excluded from

the universe. In some cases, missing data were actually implied zeros—for example, where the

percent of students receiving a specific form of aid was reported to be zero, then the average

amount for that type of aid is also zero. The exclusion of cases occurred only after recoding of

these cases.

For the remaining institutions, missing data was addressed by inserting the mean amounts

for each variable (calculated by institutional type). Separate dummy variables were then created

to identify the cases with missing data.

Variable Definition

The final universe of institutions was matched to IPEDS data103 from 1993–94 to 1997–98,

depending on the variable and the type of institution. Academic tuition, financial aid, finance,

 

102Private not-for-profit bachelor’s institutions were further divided into tuition quartiles during the regression modeling, due to

an interaction effect.

103Because the IPSFA data was not coded for parent/child status, the matched IPEDS data included the adjustments made to the

financial variables that distributed the amounts based on FTE, as described in the above section on the creation of the panels of

institutions using IPEDS data.
Appendix A—Technical Notes and Methodology

160

and salary variables were adjusted for inflation using the Consumer Price Index (CPI-U, 1982–84

= 100). All variables were adjusted to 1999 dollars.

Final Universe for Chapter V

The various procedures described above eliminated institutions from the original dataset

(table A10). The total number of public institutions remaining in the universe was 1,407 (research/doctoral = 145; comprehensive = 254; bachelor’s = 74; 2-year = 934), and the total number of private not-for-profit institutions was 770 (research/doctoral = 77; comprehensive = 222;

bachelor’s = 471).

Table A10.—Final universe of institutions for Chapter V

Percentage Percentage

Number of of original Number of of original

institutions number institutions number

Original number of institutions in IPSFA 1,794 100.0 1,571 100.0 

 Less institutions removed through selection criteria 262 14.6 601 38.3 

 Sub-total 1,532 85.4 970 61.7 

 Less institutions removed due to missing data 71 4.0 24 1.5 

 Sub-total 1,461 81.4 946 60.2 

 Less institutions excluded due to specialized, other, 54 3.0 176 11.2 

 or missing Carnegie classification

Final universe 1,407 78.4 770 49.0 

NOTE: Selection criteria were: Title IV participation, degree-granting status, location in the 50 states and the District of

Columbia, and enrollment (at least 50 first-time, full-time, degree/certificate-seeking undergraduates).

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).

2-year institutions

Public 4- and

4-year institutions

Private not-for-profit

Although almost 22 percent of public institutions and 51 percent of private not-for-profit

institutions were eliminated from the original dataset through the selection and missing data processes, the final group of institutions enrolled 93 percent of first-time, full-time, degree/certificate-seeking undergraduates at private not-for-profit 4-year institutions and 94 percent

of the total number at public 4-year and 2-year institutions in 1999. In order to examine the differences between the final universe and the institutions that were excluded, a bias analysis for
Appendix A—Technical Notes and Methodology

161

each type of institution was performed using the original IPSFA data files.104 In general, the institutions excluded from the analysis were fairly similar to those included in the final universe on

a range of variables measuring tuition, enrollment, and financial aid patterns (tables A11 to A17).

Some exceptions occurred, but in most cases the number of excluded institutions was very small,

allowing each institution to be highly influential.

• Of public 4-year institutions, those institutions excluded from the final universe tended

to have lower percentages of students receiving certain forms of aid (tables A11, A12,

and A13). In addition, excluded comprehensive institutions had fewer first-time, fulltime students, on average, and excluded bachelor’s institutions had lower levels of tuition, on average.

• Of private not-for-profit 4-year institutions, the two research/doctoral institutions that

were excluded from the final universe had different characteristics from those included

in the analysis (table A15). Excluded comprehensive and bachelor’s institutions had

lower tuitions, higher proportions of students receiving federal grants, and lower proportions of students receiving institutional grants and loan aid, on average (table A16).

Table A11.—Final universe of public research/doctoral institutions in Chapter V compared to excluded

Table B11.—institutions

Final Excluded

universe N institutions N

 Total 145 6

Average in-state undergraduate tuition, 1999–2000 $3,619 145 $3,138 4

Average percent change in in-state undergraduate tuition, 7.8 128 4.5 3

 1997–98 to 1999–2000

Average enrollment:

 Number of first-time, full-time, degree/certificate-seeking 2,646 145 2,873 4

 undergraduates 

 Percentage of all students who are first-time, full-time, 16.6 145 16.3 4

 degree/certificate-seeking undergraduates 

Average percentage of first-time, full-time undergraduates

 receiving financial aid:

 Aid from any source 68.5 140 63.0 4

 Federal grants 28.3 145 33.8 4

 State grants 26.9 145 22.0 4

 Institutional grants 31.6 142 6.0 4

 Loan aid 45.4 145 28.0 4

Average amounts of aid received:

 Federal grants $2,262 145 $2,467 4

 State grants $1,742 145 $1,628 4

 Institutional grants $2,631 142 $1,335 4

 Loan aid $3,490 145 $2,731 3

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).

 

104Again, many institutions had missing data for the variables examined; no attempts were made to impute for missing data, for

either the included institutions or the eliminated institutions. However, in some cases implied zeros were substituted for missing

fields in order to calculate means.
Appendix A—Technical Notes and Methodology

162

Table A12.—Final universe of public comprehensive institutions in Chapter V compared to excluded

Table B12.—institutions

Final Excluded

universe N institutions N

 Total 254 17 

Average in-state undergraduate tuition, 1999–2000 $2,963 254 $2,671 7 

Average percent change in in-state undergraduate tuition, 8.2 254 15.0 7 

 1997–98 to 1999–2000

Average enrollment:

 Number of first-time, full-time, degree/certificate-seeking 1,107 254 429 13 

 undergraduates 

 Percentage of all students who are first-time, full-time, 17.4 254 7.2 13 

 degree/certificate-seeking undergraduates 

Average percentage of first-time, full-time undergraduates

 receiving financial aid:

 Aid from any source 71.3 242 25.0 9 

 Federal grants 38.0 254 46.8 4 

 State grants 31.9 252 10.0 2 

 Institutional grants 26.6 247 10.7 3 

 Loan aid 47.1 254 29.8 4 

Average amounts of aid received:

 Federal grants $2,098 254 $3,027 4 

 State grants $1,425 252 $1,285 2 

 Institutional grants $1,744 247 $1,833 3 

 Loan aid $2,689 254 $3,479 4 

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).

Table A13.—Final universe of public bachelor's institutions in Chapter V compared to excluded institutions

Final Excluded

universe N institutions N

 Total 74 11 

Average in-state undergraduate tuition, 1999–2000 $3,177 74 $1,520 4 

Average percent change in in-state undergraduate 8.3 69 4.9 4 

 tuition, 1997–98 to 1999–2000

Average enrollment:

Number of first-time, full-time, degree/certificate-seeking 480 74 636 7 

 undergraduates 

Percentage of all students who are first-time, full-time, 17.8 74 25.0 7 

 degree/certificate-seeking undergraduates 

Average percentage of first-time, full-time undergraduates

 receiving financial aid:

 Aid from any source 71.5 74 57.2 6 

 Federal grants 44.1 74 74.2 5 

 State grants 29.6 73 22.8 5 

 Institutional grants 28.7 73 10.3 3 

 Loan aid 50.2 73 10.8 5 

Average amounts of aid received:

 Federal grants $2,064 74 $2,465 4 

 State grants $1,276 73 $688 4 

 Institutional grants $1,635 73 $529 3 

 Loan aid $2,695 73 $1,920 4 

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).
Appendix A—Technical Notes and Methodology

163

Table A14.—Final universe of public 2-year institutions in Chapter V compared to excluded institutions

Final Excluded

universe N institutions N

 Total 934 239 

Average in-state undergraduate tuition, 1999–2000 $1,616 934 $1,486 159 

Average percent change in in-state undergraduate 9.8 774 18.6 153 

 tuition, 1997–98 to 1999–2000

Average enrollment:

 Number of first-time, full-time, degree/certificate-seeking 528 934 280 207 

 undergraduates 

 Percentage of all students who are first-time, full-time, 15.9 934 35.0 204 

 degree/certificate-seeking undergraduates 

Average percentage of first-time, full-time undergraduates

 receiving financial aid:

 Aid from any source 56.8 923 60.4 179 

 Federal grants 40.9 933 47.8 175 

 State grants 26.7 907 29.8 155 

 Institutional grants 15.4 851 14.2 116 

 Loan aid 19.3 806 22.6 93 

Average amounts of aid received:

 Federal grants $1,848 933 $1,905 180 

 State grants $780 907 $857 157 

 Institutional grants $750 851 $588 124 

 Loan aid $2,073 806 $1,882 94 

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).

Table A15.—Final universe of private not-for-profit research/doctoral institutions in Chapter V compared

Table B15.—to excluded institutions

Final Excluded

universe N institutions N

 Total 77 5

Average in-state undergraduate tuition, 1999–2000 $19,599 77 $10,225 1

Average percent change in in-state undergraduate tuition, 10.0 77 5.9 1

 1997–98 to 1999–2000

Average enrollment:

 Number of first-time, full-time, degree/certificate-seeking 1,375 77 21 2

 undergraduates 

 Percentage of all students who are first-time, full-time, 23.6 77 2.0 2

 degree/certificate-seeking undergraduates 

Average percentage of first-time, full-time undergraduates

 receiving financial aid:

 Aid from any source 72.0 77 86.0 2

 Federal grants 24.7 77 65.5 2

 State grants 24.2 76 30.0 1

 Institutional grants 64.7 77 — 0

 Loan aid 55.4 77 81.0 2

Average amounts of aid received:

 Federal grants $3,276 77 $3,286 2

 State grants $3,302 76 $3,479 1

 Institutional grants $9,640 77 — 0

 Loan aid $3,968 77 $4,158 2

—Not applicable.

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).
Appendix A—Technical Notes and Methodology

164

Table A16.—Final universe of private not-for-profit comprehensive institutions in Chapter V compared to

Table B16.—excluded institutions

Final Excluded

universe N institutions N

 Total 222 20

Average in-state undergraduate tuition, 1999–2000 $13,806 222 $8,524 18

Average percent change in in-state undergraduate tuition, 10.1 222 8.1 17

 1997–98 to 1999–2000

Average enrollment:

 Number of first-time, full-time, degree/certificate-seeking 461 222 600 20

 undergraduates 

 Percentage of all students who are first-time, full-time, 21.0 221 20.4 20

 degree/certificate-seeking undergraduates 

Average percentage of first-time, full-time undergraduates

 receiving financial aid:

 Aid from any source 86.5 220 78.0 19

 Federal grants 32.9 222 61.4 16

 State grants 37.1 220 26.5 16

 Institutional grants 79.7 221 52.7 15

 Loan aid 67.1 221 58.1 15

Average amounts of aid received:

 Federal grants $2,528 222 $2,882 16

 State grants $2,759 220 $2,682 16

 Institutional grants $5,499 221 $3,669 15

 Loan aid $3,722 221 $3,437 15

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).

Table A17.—Final universe of private not-for-profit bachelor's institutions in Chapter V compared to

Table B17.—excluded institutions

Final Excluded

universe N institutions N

 Total 471 42

Average in-state undergraduate tuition, 1999–2000 $14,024 471 $7,904 36

Average percent change in in-state undergraduate tuition, 9.6 471 10.2 35

 1997–98 to 1999–2000

Average enrollment:

 Number of first-time, full-time, degree/certificate-seeking 320 471 336 40

 undergraduates 

 Percentage of all students who are first-time, full-time, 27.7 471 26.8 40

 degree/certificate-seeking undergraduates 

Average percentage of first-time, full-time undergraduates

 receiving financial aid:

 Aid from any source 85.7 469 82.4 40

 Federal grants 35.6 470 57.8 32

 State grants 39.0 469 26.2 27

 Institutional grants 76.9 471 44.7 31

 Loan aid 66.3 468 46.6 33

Average amounts of aid received:

 Federal grants $2,507 470 $2,470 32

 State grants $2,531 469 $1,876 28

 Institutional grants $6,063 471 $2,833 31

 Loan aid $3,536 468 $3,073 33

SOURCE: U.S. Department of Education, National Center for Education Statistics, 1999, Institutional Prices and Student

Financial Aid Survey (IPSFA).
Appendix A—Technical Notes and Methodology

165

Statistical Procedures

Descriptive Statistics

For the panels of institutions presented in Chapters III and IV, trend data—averages at the

institutional level—were compiled for each institutional type. Average dollar changes over the

period 1988–89 to 1997–98 (to 1995–96 for private not-for-profit institutions) were calculated as

the difference between the average end year figure and the average base year figure within each

institutional type, in constant dollar terms. Average annual changes, in real percentage terms,

were calculated as the sum of average annual change increments within each institutional type

divided by the number of years; they are therefore averages of institutional averages.

For the private not-for-profit institutions, descriptive statistics regarding the variables included in the simultaneous equation model are provided in tables A18, A19, and A20, including

the following:

• The mean (average), minimum, and maximum values of each variable;

• The standard deviation of each variable, which measures data variability or the spread

of data about the mean (the standard deviation is zero with no spread, and increases as

the spread of the data increases);

• Skewness, which measures lack of symmetry or the extent to which the distribution is

displaced toward one side of the scale (where zero is symmetrical, negative values indicate a skew to the left, and positive values signify a skew to the right); and

• Kurtosis, which measures the size of the tails of a distribution, or the tallness or flatness of the distribution (where smaller values indicate a flatter distribution with relatively small tails, and the normal distribution has a kurtosis of three).

For the analysis presented in Chapter V using IPSFA data, averages were compiled for each

institutional type, including such variables as the change in tuition, the number of first-time, fulltime, degree/certificate-seeking undergraduates, the percentage of students receiving various

forms of financial aid, and the average amounts of aid received.

Magnitude of correlations

For the bivariate correlations reported in the findings section of the Executive Summary,

the strength of the relationships between pairs of variables was provided using a scale of
Appendix A—Technical Notes and Methodology

166

Table A18.—Descriptive statistics of model variables for private not-for-profit research/doctoral institutions:

Table A18.—1989–90 to 1995–96 

Standard

Variable Mean deviation Skewness Kurtosis Minimum Maximum

Log of undergraduate tuition 9.636 0.268 -0.596 2.544 8.810 10.062 

Log of first-time freshmen FTE students 6.945 0.643 -0.735 3.887 4.728 8.449 

Log of previous year’s instruction expenditures 9.196 0.530 0.618 2.720 8.304 10.771 

Log of average tuition at public 4-year institutions 7.965 0.412 -0.616 2.609 6.716 8.548 

 in the state

Log of previous year’s expenditures on plant 8.013 0.932 -4.575 38.929 0.000 9.653 

 maintenance and transfers

Log of the proportion of undergraduates enrolled -1.519 0.662 -0.355 1.984 -2.857 -0.296 

 in the state attending private not-for-profit 4-year

 institutions 

Log of previous year’s research expenditures 7.249 2.191 -1.534 5.735 0.000 9.894 

Log of previous year’s student service expenditures 7.190 0.473 1.101 6.118 6.122 9.140 

Log of expenditures on institutional aid 7.940 0.595 -0.354 2.543 6.240 9.107 

Log of previous year’s student/faculty ratio 2.890 0.291 -0.044 4.486 2.024 3.987 

Log of philanthropic revenue 8.200 1.015 -0.178 2.550 5.676 10.343 

Log of per capita income in the state 10.180 0.127 -0.091 2.248 9.843 10.500 

Log of instruction expenditures 9.224 0.533 0.641 2.771 8.354 10.804 

Log of average faculty compensation 11.274 0.161 -1.080 4.652 10.698 11.626 

Log of institutional support expenditures 8.038 0.404 0.060 3.414 7.021 9.310 

Log of academic support expenditures 7.718 0.606 0.208 3.387 6.080 9.686 

Log of student services expenditures 7.228 0.464 0.982 5.780 6.122 9.140 

Log of federal grants and contracts 7.508 1.694 -0.489 2.241 2.156 9.962 

Log of revenue from state and local sources 5.168 2.273 -1.098 3.438 -0.297 8.947 

Ratio of graduate FTE enrollment to total FTE 0.277 0.098 0.146 2.740 0.072 0.626 

 enrollment

Dummy variable for 1991 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for 1992 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for 1993 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for 1994 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for 1995 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for 1996 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for zero values in log of previous 0.043 0.202 4.533 21.544 0.000 1.000 

 year’s research expenditures

Dummy variable for zero values in log of previous 0.006 0.078 12.709 162.506 0.000 1.000 

 year’s expenditures on plant maintenance and 

 operation

Dummy variable for zero values in log of revenue 0.106 0.309 2.553 7.519 0.000 1.000 

 from state and local sources

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System

(IPEDS), Full Collection Years 1989 to 1996; Bureau of Economic Analysis, Regional Accounts Data, Personal Income for States:

1958-98, released July 1999.

N = 329
Appendix A—Technical Notes and Methodology

167

Table A19.—Descriptive statistics of model variables for private not-for-profit comprehensive institutions:

Table A19.—1989–90 to 1995–96 

Standard

Variable Mean deviation Skewness Kurtosis Minimum Maximum

Log of undergraduate tuition 9.258 0.280 -0.840 4.041 8.071 9.871 

Log of first-time freshmen FTE students 5.618 0.818 -0.375 3.252 2.544 7.918 

Log of previous year’s instruction expenditures 8.407 0.333 0.490 6.329 7.126 10.376 

Log of average tuition at public 4-year institutions 7.922 0.374 -0.320 2.558 6.716 8.762 

 in the state

Log of previous year’s expenditures on plant 7.353 0.850 -5.536 47.642 0.000 9.859 

 maintenance and transfers

Log of the proportion of undergraduates enrolled -1.759 0.578 0.081 2.113 -2.857 -0.296 

 in the state attending private not-for-profit 4-year

 institutions 

Log of previous year’s research expenditures 1.643 2.489 1.093 2.734 -2.745 10.172 

Log of previous year’s student service expenditures 7.164 0.391 -0.420 4.626 5.003 9.175 

Log of expenditures on institutional aid 7.409 0.653 -1.011 5.190 4.116 9.386 

Log of previous year’s student/faculty ratio 2.979 0.322 0.383 9.883 0.663 4.781 

Log of philanthropic revenue 7.111 0.848 -1.496 12.292 0.000 9.701 

Log of per capita income in the state 10.122 0.141 0.216 2.947 9.693 10.500 

Log of instruction expenditures 8.429 0.328 0.332 5.913 7.126 10.376 

Log of average faculty compensation 10.892 0.187 0.193 3.069 10.274 11.758 

Log of institutional support expenditures 7.686 0.341 -0.058 4.367 6.456 9.761 

Log of academic support expenditures 6.747 0.593 -0.425 3.451 4.583 8.916 

Log of student services expenditures 7.202 0.378 -0.390 4.070 5.421 9.175 

Log of federal grants and contracts 3.751 5.466 -5.093 31.607 -30.498 10.728 

Log of revenue from state and local sources 2.774 2.695 0.127 1.413 -4.540 7.567 

Ratio of graduate FTE enrollment to total FTE 0.152 0.097 0.780 3.154 0.000 0.536 

 enrollment

Dummy variable for 1991 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for 1992 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for 1993 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for 1994 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for 1995 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for 1996 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for zero values in log of previous 0.653 0.476 -0.644 1.415 0.000 1.000 

 year’s research expenditures

Dummy variable for zero values in log of previous 0.008 0.090 10.917 120.190 0.000 1.000 

 year’s expenditures on plant maintenance and 

 operation

Dummy variable for zero values in log of revenue from 0.116 0.320 2.397 6.747 0.000 1.000 

 state and local sources

Dummy variable for zero values in log of federal grants 0.402 0.490 0.401 1.161 0.000 1.000 

 and contracts

Dummy variable for zero values in log of philanthropic 0.001 0.039 25.865 670.002 0.000 1.000 

 revenue

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data

System (IPEDS), Full Collection Years 1989 to 1996; Bureau of Economic Analysis, Regional Accounts Data, Personal Income for 

States: 1958-98, released July 1999.

N = 1344
Appendix A—Technical Notes and Methodology

168

Table A20.—Descriptive statistics of model variables for private not-for-profit bachelor's institutions:

Table A20.—1989–90 to 1995–96 

Standard

Variable Mean deviation Skewness Kurtosis Minimum Maximum

Log of undergraduate tuition 9.235 0.531 -4.325 50.158 0.000 10.280 

Log of first-time freshmen FTE students 5.316 0.760 -0.981 6.321 0.000 7.075 

Log of previous year’s instruction expenditures 8.432 0.475 0.679 7.078 5.147 10.807 

Log of average tuition at public 4-year institutions 7.934 0.350 -0.055 2.323 7.098 8.762 

 in the state

Log of previous year’s expenditures on plant 7.489 1.061 -4.387 32.363 0.000 10.488 

 maintenance and transfers

Log of the proportion of undergraduates enrolled -1.743 0.569 -0.910 6.682 -5.412 -0.720 

 in the state attending private not-for-profit

 4-year institutions 

Log of previous year’s research expenditures 1.512 2.457 1.208 2.854 -2.293 9.340 

Log of previous year’s student service expenditures 7.392 0.544 -1.100 15.673 0.000 9.558 

Log of expenditures on institutional aid 7.653 0.998 -2.662 19.807 0.000 10.580 

Log of previous year’s student/faculty ratio 2.779 0.357 -0.626 8.264 0.726 4.709 

Log of philanthropic revenue 7.846 0.921 -0.302 4.340 3.971 10.897 

Log of per capita income in the state 10.082 0.134 0.202 2.898 9.693 10.493 

Log of instruction expenditures 8.452 0.471 0.822 6.225 5.147 10.835 

Log of average faculty compensation 10.821 0.234 0.102 2.679 9.758 11.452 

Log of institutional support expenditures 7.905 0.476 0.400 5.488 5.427 10.275 

Log of academic support expenditures 6.867 0.683 0.268 3.339 4.336 9.555 

Log of student services expenditures 7.417 0.543 -1.142 15.941 0.000 9.628 

Log of federal grants and contracts 3.431 6.332 -4.340 22.953 -30.598 8.947 

Log of revenue from state and local sources 2.309 2.716 -0.258 10.141 -32.578 8.634 

Ratio of graduate FTE enrollment to total FTE 0.026 0.069 5.069 35.904 0.000 0.745 

 enrollment

Dummy variable for 1991 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for 1992 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for 1993 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for 1994 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for 1995 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for 1996 0.143 0.350 2.041 5.167 0.000 1.000 

Dummy variable for zero values in log of previous 0.687 0.464 -0.808 1.653 0.000 1.000 

 year’s research expenditures

Dummy variable for zero values in log of previous 0.013 0.112 8.714 76.938 0.000 1.000 

 year’s expenditures on plant maintenance and 

 operation

Dummy variable for zero values in log of revenue 0.158 0.365 1.871 4.502 0.000 1.000 

 from state and local sources

Dummy variable for zero values in log of federal 0.500 0.500 -0.001 1.000 0.000 1.000 

 grants and contracts

Dummy variable for zero values in log of 0.001 0.036 28.040 787.251 0.000 1.000 

 FTE enrollment

Dummy variable for zero values in log of 0.005 0.071 13.940 195.318 0.000 1.000 

 expenditures on institutional aid

Dummy variable for zero values in log of 0.000 0.018 56.160 3155.000 0.000 1.000 

 undergraduate tuition

Dummy variable for zero values in log of student 0.000 0.018 56.160 3155.000 0.000 1.000 

 service expenditures

Dummy variable for zero values in log of previous 0.000 0.018 56.160 3155.000 0.000 1.000 

 year’s student service expenditures

SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System

(IPEDS), Full Collection Years 1989 to 1996; Bureau of Economic Analysis, Regional Accounts Data, Personal Income for States:

1958-98, released July 1999.

N = 3157
Appendix A—Technical Notes and Methodology

169

magnitudes. Following Cohen (1988), reported magnitudes adopted the notion of a scale of

small, medium, and large sized relationships, qualitative terms that allow interpretation of the

strength of a relationship through the concept of effect size. Cohen suggested that for a scale of

the proportion of variance accounted for (the square of the correlation coefficient, r2

), one might

use a value of 0.01 to signify a small effect size, 0.09 for moderate, and 0.25 for large. Some

latitude is appropriate in determining the scale of effect sizes within the context of the analysis.

The magnitudes reported in the Executive Summary of this report were based on a scale in which

the effect is small if r2

 is less than 0.05, medium if r2 is at least 0.05 but less than 0.25, and large if

r

2 is 0.25 or greater.

Multiple Regression Analysis

For the analysis of public institutions presented in Chapter III, multiple linear regression

procedures were used to explore the associations among various tuition, revenue, and expenditure categories, based upon the framework set forth by GAO (1998). Prior to running the regression analyses, bivariate relationships between variables were examined through scatterplots and

correlation matrices.

Multiple linear regression is a statistical procedure used to relate two or more independent

variables to a dependent variable. According to the general form of the least squares linear regression model, the dependent variable (Y) is assumed to be a function of a set of k independent

variables (X) in a population:

Y XX X = + + ++ + αβ β β ε 11 2 2 ... k k

Through such a model, partial slope coefficients (β) are estimated for each independent

variable, showing the relationship between an independent variable and the dependent variable

holding all other independent variables constant. The intercept (α) represents the expected value

of the dependent variable when all the independent variables equal zero. The error term (ε) is the

deviation of an observed value of the dependent variable from the mean value of the distribution

obtained by repeated observation of values for the dependent variable, and represents both the

effects of variables not explicitly included in the equation, as well as a residual random element

in the dependent variable.

Certain assumptions must be met in order to appropriately estimate population parameters

and conduct tests of statistical significance, including the following:
Appendix A—Technical Notes and Methodology

170

• The dependent variable can be calculated as a linear function of a specific set of independent variables, plus an error term. The coefficients of this linear function are constant. This assumption can be violated if the relationship between the dependent

variable and one of the independent variables is not linear, if the parameters do not remain constant during the period in which the data were collected, or if relevant independent variables were omitted from the model (or irrelevant independent variables

were included). These are errors in the specification of the model.

• For each set of values for the independent variables, the mean value of the error term

must be zero. A violation of this assumption affects the value of the intercept.

• For each set of values for the independent variables, the error terms must have the

same variance and must not be correlated with each other. The problem of heteroskedasticity occurs when the error terms do not have the same variance; autocorrelation

occurs when the error terms are correlated with each other. Both may have implications for estimation of the parameters and inference, especially in conjunction with

other violations of assumptions.

• The observations on the independent variables must be considered fixed in repeated

samples. Several problems are associated with violations of this assumption, including

errors in measuring independent variables and situations in which the dependent variable is determined by the simultaneous interaction of several relationships.

• For each set of values for the independent variables, the error term must be normally

distributed. A violation of this assumption has no effect on the estimated parameters,

but rather is important for tests of statistical significance (and even then, only with

small samples).

• No independent variable can be perfectly linearly related to one or more of the other

independent variables in the model. The problem of multicollinearity is associated with

this assumption, where approximate linear relationships occur among independent

variables, leading to large variances in the parameter estimates of the collinear variables.

One or more of these assumptions may be violated when using empirical data, resulting in

misleading or problematic coefficient estimates.105 It is important to keep in mind that the analyses in this report use census data of a population, making the interpretation of the results (especially tests of statistical significance) slightly different than if the data were from a sample.

Specifically, tests of statistical significance on census data do not measure the probability of

whether sample results can be generalized to a population, but rather can be used to judge the

strength of relationships in the population. Nevertheless, one must be concerned with interpreta-

 

105For a more detailed discussion of the assumptions of multiple linear regression, see Berry and Feldman (1985); and Kennedy

(1998).
Appendix A—Technical Notes and Methodology

171

tion of the results, particularly in a single equation model. Correlation or any statistical relationship between variables does not necessarily mean causation.106

For the multiple linear regression model presented in Chapter III, the equation used takes

the functional form of:

∆ ∆ YY X i i k ki

k

r

=+ + + =

αβ β ε 0 0 ∑

1

() () ( )

where ∆Yi = change in in-state undergraduate tuition (price) at institution i

Y(0)i = tuition in the base year at institution i

∆X(k)i = change in each expenditure/revenue variable (k) at institution i

Following the framework set forward by GAO, the results of the regression models were

presented for each institutional type and each time period, including the following statistics:

• Multiple R-squared, the percent of the variance in the dependent variable accounted for

by the independent variables;

• The adjusted R-squared, which attempts to compensate for the fact that simply adding

more independent variables tends to increase the value of multiple R-squared;

• The model probability, which in the case of census data is displayed to gauge the explanatory power of the model as a whole;

• The number of valid cases;

• The Pearsons correlation coefficient of each independent variable with the dependent

variable (change in tuition), where a correlation coefficient approaching zero suggests

no statistical relationship between the two variables (without controlling for other factors);

• The regression coefficient, which indicates the estimate of the average amount the dependent variable changes with a unit change in each independent variable, after controlling for all the other variables;

• The incremental change in multiple R-squared for each independent variable, or the

extent to which the portion of variation accounted for declines with the deletion of

each variable one at a time (in percentage points); and

 

106As noted by Kennedy (1998), “It is usually assumed that movements in the dependent variable are caused by movements in

the independent variable(s), but the existence of a relationship between these variables proves neither the existence of causality

nor its direction” (p. 66).
Appendix A—Technical Notes and Methodology

172

• The probability of the t statistic for each independent variable, which were displayed as

standard output of statistical software and may be used in this analysis to gauge the

strength of the relationship between the independent variable and the variation in the

dependent variable not accounted for by all the other variables.

Independent variables were identified as “important” if the decline in the portion of variation accounted for (R-squared) by omitting the variable from the model was 10 percentage points

or greater. When independent variables are highly correlated with each other, the usefulness of

assessing the importance of a variable by deleting it from the model is limited because it is difficult to distinguish their independent contribution to the portion of variation accounted for; therefore, in cases in which bivariate correlations are 0.7 or greater, the correlation was noted and the

R-squared change when both variables are deleted from the model was provided.

Reduction Procedures

For the analysis presented in Chapter V, multiple linear regression procedures also were

used to explore the associations among variables. These models were reduced in order to eliminate variables that do not add to the model’s ability to explain the variability in the response and

avoid spurious findings. On the other hand, the models in Chapters III and IV were not reduced

because the analysis updated previously existing models, without altering the models or testing

their significance.

When dealing with a large number of explanatory variables, it is useful to eliminate unnecessary variables both for the sake of simplicity and because unnecessary terms in the model lead

to less precise inference. Variables that are redundant should not both (all) be included in the final model. Multicollinearity exists when variables are nearly redundant; it decreases the precision

of estimated coefficients, and the problem gets worse as more explanatory variables are included

in the model. Automated variable selection procedures, available in standard statistical packages,

allow the reduction of regression models without having to run all of the possible regressions.

One such method of reduction is the backward elimination procedure. In backward elimination, all of the independent variables are entered in one block, then at each step the variable

that changes R-squared the least is removed. The procedure continues until the removal of any

variable in the model results in a meaningful change in R-squared. The partial regression coefficients for all of the variables remaining in the model point to meaningful relationships with the

dependent variable.

The assumptions required for standard linear regression procedures also hold for reduced

regression models, as do the stipulations regarding the use of census data. It is important to note

that different eliminations can result from the order in which variables are tested (i.e., forward,
Appendix A—Technical Notes and Methodology

173

backward, or stepwise). In addition, prediction bias can arise because the final, reduced model is

uniquely related or fitted to the specific data set.

In the case of the models presented in Chapter V, the frequency distributions of each variable were examined and bivariate relationships between variables were explored through scatterplots and correlation matrices prior to the regression modeling. When potential independent

variables had bivariate correlations of 0.7 or higher, only one was included in a particular model;

the exception was the case of dummy variables for missing data.

For the reduced regression models presented in Chapter V, the equations take the functional

form of:

∆ ∆ YY X Z i i k kit

k

r

j ji

j

s

=+ + + + − =

αβ β β ε 0 0 ∑ ∑

1 1

() () () () ( )

where ∆Yi = change in in-state undergraduate tuition (price) at institution i

Y(0)i = tuition in the base year at institution i

X(k)it = aid and other explanatory variables (k) at institution i in year t

∆Z(j)i = change in each expenditure/revenue variable (j) at institution i

Each regression model was reduced (and the coefficients were estimated) using the backward elimination method. The results presented for each institutional type include the same statistics as those presented in Chapter III. In addition, the results include the standardized (Beta)

coefficient, which is the average amount the dependent variable increases when the independent

variable increases one standard deviation and other independent variables are held constant. The

Beta weights express in standardized terms the relative sizes of the partial regression coefficients.

Three-Stage Least Squares

For the analysis of private not-for-profit institutions presented in Chapter IV, a three-stage

least squares procedure was used to estimate the model of simultaneous equations. In a system of

simultaneous equations, a change in any error term changes all of the endogenous (jointly dependent) variables, since they are determined simultaneously. Because any endogenous variables

used as independent variables will be correlated with the error terms, the standard least squares

multiple regression procedure will produce biased estimates.
Appendix A—Technical Notes and Methodology

174

The three-stage least squares procedure, however, allows unbiased estimation of systems of

structural equations where some equations contain endogenous variables among the explanatory

variables. It uses an instrumental variable approach (two-stage least squares) to produce consistent estimates, and generalized least squares to account for the correlation in the error terms

across equations.107

Three-stage least squares is based on several assumptions, including that the error terms in

each structural equation have uniform variance and are not correlated with one another; that errors in different time periods in different equations are independent; and that the variancecovariance matrix is the same in each time period. It is a systems estimating procedure, which

estimates all the identified structural equations together as a set rather than separately. The main

advantage of such a procedure is that it incorporates all available information into its estimates. If

the system is misspecified, however, estimates of all the structural parameters are affected.

In the case of the model presented in Chapter IV, bivariate relationships between variables

were examined through scatterplots and correlation matrices prior to the modeling. Both equations took the functional form of:

ln( ) ln( ) ln( ) Y EX it t it k ( )

k

r

=+ + + k it

=

αβ β ε 0 ∑

1

where Yit = in-state undergraduate tuition (price) at institution i in year t

αt = year-specific constant term

Eit = number of new enrollments at institution i in year t

X(k)it = other factors influencing tuition (k) at institution i in year t

The three-stage least squares procedure was used to estimate the model coefficients simultaneously. As in other analyses, it is important to keep in mind that the data are derived from a

census rather than a sample. Following the framework of the Westat/Pelavin (1994) study, the

results of the updated models included the following statistics:

• “R-squared” for each equation, which measures the correlation between the actual values and the predicted values (the models “goodness of fit”);

 

107Specifically, the procedure is as follows: 1) regress each endogenous variable acting as an independent variable in the equation being estimated on all the exogenous variables in the system and calculate the estimated values; 2) use these estimated values

as instrumental variables for these endogenous variables and calculate the two-stage least squares estimates of the identified

equations; 3) use the two-stage least squares estimates to estimate the structural equations’ errors, and then use these to estimate

the variance-covariance matrix of the structural equations’ errors; 4) apply generalized least squares to the large equation representing all the identified equations of the system. See Kennedy (1998).
Appendix A—Technical Notes and Methodology

175

• The root mean square error (RMSE), which also evaluates the performance of the

model and gives a measure of lack of fit;

• The model probability, which in the case of census data is displayed to gauge the explanatory power of the model as a whole;

• The number of valid observations (given that each institution has one observation for

each of the seven years);

• The estimated coefficients, which (because the variables are logs) indicate the “elasticity,” or the percentage change in the dependent variable associated with a one percent

change in each independent variable, after controlling for all the other variables;

• The standard error of the estimate, as provided by the standard output of statistical

software; and

• The Z statistic for each independent variable, which were displayed as standard output

of statistical software and may be used in this analysis to gauge the strength of the relationship between the independent variable and the variation in the dependent variable

not accounted for by all the other variables.

In addition, reduced form regressions were performed within each institutional type. In reduced form regressions, the simultaneous system is solved such that every endogenous variable is

expressed as a linear function of all of the exogenous variables. The reduced form equations

therefore incorporate all exogenous variables from both equations into one model, with the same

dependent variable, which then can be estimated using the standard linear regression procedure.108 Whereas structural equations explore the direct relationships among variables (and are

based on a stronger set of assumptions), reduced form equations capture the aggregate effect of

the exogenous factors on the endogenous variables, including the indirect effects of the exogenous variables as well as direct effects. Such regressions are useful to support the findings of the

structural model.

 

108According to economic theory, the reduced-form parameters are the long-run multipliers associated with the model; see Kennedy (1998).
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177

Appendix B—Glossary

This glossary describes the variables used in this report. The items were taken from several

sources, including the NCES Integrated Postsecondary Education Data System (IPEDS) and the

Institutional Prices and Student Financial Aid Survey (IPSFA), and the Bureau of Economic

Analysis’ Regional Accounts Data. The variables were imported, manipulated, and relabeled using SPSS (or Stata) statistical software. The glossary is in alphabetical order by the variable label

in SPSS (or Stata), shown in bold, capital letters and displayed along the right-hand column. Underscores in variable names signify the variable is duplicated for each relevant year of data. The

glossary is also divided by source of data.

The variables listed in the index below are approximately in the order they appear in the tables in the report.

Glossary Index

GENERAL INSTITUTIONAL CHARACTERISTICS

Sector of institution...................................... SECTOR

Carnegie classification code.....................CARNEGIE

Revised Carnegie classification code..... CARNEGER

Highest degree offered............................HDEGOFFR

OPE eligibility indicator ............................... OPEIND

CHAPTER III

TREND VARIABLES:

In-state undergraduate tuition in specific

 year ..........................................................TFUG2__R

In-district undergraduate tuition in

 specific year .............................................TFUG1__R

In-state graduate tuition in specific year ...TFGR2__R

Out-of-state undergraduate tuition in

 specific year .............................................TFUG3__R

Total fall enrollment ................................... TOTEF__

FTE fall enrollment...........................................FTE__

FTE first-time enrollment ............................ FTEFF__

Tuition revenue per FTE............................ TUIT3__F

Federal appropriations revenue per FTE... FDAP3__F

State appropriations revenue per FTE........STAP3__F

Local appropriations revenue per FTE ..... LOAP3__F

Federal grants and contracts per FTE .......FDGR3__F

State grants and contracts per FTE ........... STGR3__F

Local grants and contracts per FTE ..........LOGR3__F

Private gifts revenue per FTE .................... PRIV3__F

Endowment income per FTE ...................ENDW3__F

Sales and services revenue per FTE...........SALE3__F

Other revenue per FTE .............................OTHR3__F

Auxiliary enterprise revenue per FTE.......AUXL3__F

Hospital revenue per FTE......................... HOSP3__F

Independent operations revenue per FTE .. INDP3__F

Total revenue per FTE..............................CREV3__F

E&G revenue per FTE ............................. EGREV__F

Instruction expenditures per FTE................INST3__F

Research expenditures per FTE ................... RES3__F

Public service expenditures per FTE ...........PUB3__F

Academic support expenditures per FTE. ACAD3__F

Student services expenditures per FTE..... STUD3__F

Institutional support expenditures per FTE.INSP3__F

Plant operations expenditures per FTE ......PLNT3__F

Scholarships and fellowships expenditures

 per FTE....................................................SCHO3__F

Mandatory transfers per FTE.................. MAND3__F

Non-mandatory transfers per FTE .......... NONM3__F

Auxiliary enterprise expenditures

 per FTE....................................................AUXE3__F

Hospital expenditures per FTE ..................HSPE3__F

Independent operations expenditures

 per FTE.....................................................INDE3__F

Total expenditures per FTE ...................... CEXP3__F
Appendix B—Glossary

178

E&G expenditures per FTE ........................... EG3__F

Institutional aid expenditures per FTE........ IAID3__F

MODEL VARIABLES:

Change in in-state undergraduate

 tuition.......................................................TFUG2__C

Change in in-district undergraduate

 tuition.......................................................TFUG1__C

Change in government appropriations ...... APPR1__C

Change in government grants and

 contracts.................................................. GRNT2__C

Change in philanthropic revenue ............... PHIL1__C

Change in instruction expenditures............ INST3__C

Change in student services expenditures...STUD3__C

Change in institutional scholarships and

 fellowships.................................................IAID3__C

Change in other student-related

 expenditures...............................................STUX__C

Change in research expenditures..................RES3__C

Change in non-student-related

 Expenditures .............................................NONX__C

Level of in-state undergraduate tuition

 in specific year.........................................TFGU2__R

Level of in-district undergraduate tuition

 in specific year.........................................TFUG1__R

Change in amount by which E&G revenues

 exceed/fall short of E&G expenditures. ..... BAL1__C

Change in ratio of graduate to total FTE

 enrollment. .............................................. PERGD__C

CHAPTER IV

TREND VARIABLES:

In-state undergraduate tuition in specific

 year ..........................................................TFUG2__R

In-district undergraduate tuition in

 specific year .............................................TFUG1__R

In-state graduate tuition in specific year ...TFGR2__R

Out-of-state undergraduate tuition in

 specific year .............................................TFUG3__R

Total fall enrollment ................................... TOTEF__

FTE fall enrollment...........................................FTE__

FTE first-time enrollment ............................ FTEFF__

Tuition revenue per FTE............................ TUIT3__F

Federal appropriations revenue per FTE... FDAP3__F

State appropriations revenue per FTE........STAP3__F

Local appropriations revenue per FTE ..... LOAP3__F

Federal grants and contracts per FTE .......FDGR3__F

State grants and contracts per FTE ........... STGR3__F

Local grants and contracts per FTE ..........LOGR3__F

Private gifts revenue per FTE .................... PRIV3__F

Endowment income per FTE ...................ENDW3__F

Sales and services revenue per FTE...........SALE3__F

Other revenue per FTE .............................OTHR3__F

Auxiliary enterprise revenue per FTE.......AUXL3__F

Hospital revenue per FTE......................... HOSP3__F

Independent operations revenue per FTE .. INDP3__F

Total revenue per FTE..............................CREV3__F

E&G revenue per FTE ............................. EGREV__F

Instruction expenditures per FTE................INST3__F

Research expenditures per FTE ................... RES3__F

Public service expenditures per FTE ...........PUB3__F

Academic support expenditures

 per FTE................................................... ACAD3__F

Student services expenditures

 per FTE.................................................... STUD3__F

Institutional support expenditures

 per FTE......................................................INSP3__F

Plant operations expenditures

 per FTE.....................................................PLNT3__F

Scholarships and fellowships expenditures

 per FTE....................................................SCHO3__F

Mandatory transfers per FTE.................. MAND3__F

Non-mandatory transfers per FTE .......... NONM3__F

Auxiliary enterprise expenditures

 per FTE....................................................AUXE3__F

Hospital expenditures per FTE ..................HSPE3__F

Independent operations expenditures

 per FTE.....................................................INDE3__F

Total expenditures per FTE ...................... CEXP3__F

E&G expenditures per FTE ........................... EG3__F

Institutional aid expenditures per FTE........ IAID3__F

Average faculty compensation.....................................

MODEL VARIABLES:

Log of undergraduate tuition........................ TFUGLG

Log of first-time freshmen FTE students ....FTEFFLG

Log of average undergraduate tuition at

 public 4-year institutions in the state........... AVTFLG

Log of proportion of undergraduates

 enrolled at private not-for-profit 4-year

 institutions................................................. PERPRLG

Log of previous year’s instruction

 expenditures per student ...............................INSTLN

Log of previous year’s plant operations

 expenditures and transfers per student .........PLTRLN

Log of previous year’s research

 expenditures per student. ............................... RESLN

Log of previous year’s student/faculty

 ratio per student ........................................ STUFCLN

Log of philanthropic revenue per student ......PHILLG

Log of institutional aid expenditures per

 student........................................................... IAIDLG

Log of previous year’s student services

 expenditures per student. ............................ STUDLN

Log of per capita income in state ................STINCLG

Dummy variable for 1991 ........................ DUMMY91

Dummy variable for 1992 ........................ DUMMY92

Dummy variable for 1993 ........................ DUMMY93

Dummy variable for 1994 ........................ DUMMY94

Dummy variable for 1995 ........................ DUMMY95
Appendix B—Glossary

179

Dummy variable for 1996 ........................ DUMMY96

Zero values in RESLN ................................. RESLND

Zero values in PLTRLN.............................PLTRLND

Zero values in PHILLG ..............................PHILLGD

Zero values in FTELG ................................. FTELGD

Zero values in IAIDLG............................... IAIDLGD

Zero values in TFUGLG........................... TFUGLGD

Zero values in STUDLN........................... STUDLND

Log of instruction expenditures per

 student...........................................................INSTLG

Log of average faculty compensation ...... AVCMPLG

Log of institutional support expenditures

 per student.....................................................INSPLG

Log of academic support expenditures per

 Student ....................................................... ACADLG

Log of student services expenditures per

student......................................................... STUDLG

Ratio of graduate to total FTE enrollment ......PERGD

Log of federal grants and contracts per

 student.........................................................FDGRLG

Log of state and local revenue per student....STLOLG

Zero values in STLOLG ............................STLOLGD

Zero values in FDGRLG........................... FDGRLGD

Zero values in STUDLG........................... STUDLGD

CHAPTER V

AVERAGE VARIABLES:

Dollar change in undergraduate tuition.... INSTATCH

Percentage change in undergraduate

 tuition........................................................... INSTAD

Number of first-time, full-time

 undergraduates............................................. FTUG99

Percentage of students who are first-time,

 full-time undergraduates ............................ FTUGP99

Percentage of first-time, full-time

 undergraduates who receive any aid ....... FTUGAP99

Percentage receiving federal grants ........ FEDGRNTP

Average amount of federal grants

 received..................................................FEDGRNTA

Percentage receiving state grants ...............STGRNTP

Average amount of state grants received .. STGRNTA

Percentage receiving institutional grants.... INGRNTP

Average amount of institutional grants

 received.....................................................INGRNTA

Percentage receiving student loans ........... LOANPCT

Average amount of student loans

 received................................................... LOANAVG

MODEL VARIABLES:

Dollar change in undergraduate tuition.... INSTATCH

Base level of tuition .................................. INSTAC98

Number of first-time, full-time

 undergraduate .............................................. FTUG99

Percentage of undergraduates receiving any aid times

the percentage of first-time, full-time

undergraduates........................................... FTUGAP2

Percentage receiving federal grants times

 the average amount received.....................FEDGPAC

Percentage receiving state grants times the

average amount received.............................. STGPAC

Percentage receiving institutional grants

 times the average amount received ..............INGPAC

Percentage receiving student loans times

 the average amount received.................... LOANPAC

Change in academic support

 expenditures............................................ACADDIFF

Change in average faculty

compensation ............................................AVC2DIFF

Change in average tuition at public

4-year institutions in the state ...................AVTFDIFF

Change in federal grants and contracts .....FDGRDIFF

Change in institutional support

 expenditures.............................................. INSPDIFF

Change in instruction expenditures............ INSTDIFF

Degree of urbanicity .................................... LOCALE

Percentage of awards that were

 certificates................................................. PCTCERT

Percentage of enrollment that was

 full time.................................................... PERFT98R

Percentage of enrollment that was

 minority....................................................PERMIN98

Change in philanthropic revenue ............... PHILDIFF

Change in plant maintenance

 expenditures............................................. PLNTDIFF

Change in plant maintenance

 expenditures plus transfers....................... PLTRDIFF

Change in research expenditures..................RESDIFF

Change in state appropriations revenue .... STAPDIFF

Change in state grants and contracts .........STGRDIFF

Change in per capita income by state.........STINCDIF

Change in state and local revenue............. STLODIFF

Change in student services expenditures...STUDDIFF

Tribal college indicator............................. TRIBAL98

Indicator for cases using 1997-98

 financial aid data.................................... YRINDFAD

Missing value indicator for

 ACADDIFF ........................................... ACADUMD

Missing value indicator for

 AVC2DIFF .......................................... AVC2DUMD

Missing value indicator for

 FDGRDIFF.......................................... FDGRDUMD

Missing value indicator for

 INSPDIFF.................................................INSPUMD

Missing value indicator for

 INSTDIFF..............................................INSTDUMD

Missing value indicator for

 LOCALE.............................................. LOCALDUM

Missing value indicator for

 PCTCERT............................................... CERTDUM
Appendix B—Glossary

180

Missing value indicator for

 PERFT98RF ......................................... PERFTDUM

Missing value indicator for

 PERMIN98 ...............................................PERMIND

Missing value indicator for

 PHILDIFF..............................................PHILDUMD

Missing value indicator for

 PLNTDIFF............................................PLNTDUMD

Missing value indicator for

 PLTRDIFF............................................PLTRDUMD

Missing value indicator for

 RESDIFF ................................................ RESDUMD

Missing value indicator for

 STAPDIFF............................................STAPDUMD

Missing value indicator for

 STGRDIFF .......................................... STGRDUMD

Missing value indicator for

 STLODIFF............................................STLODUMD

Missing value indicator for

 STUDDIFF .......................................... STUDDUMD
Appendix B—Glossary

181

IPEDS VARIABLES

Academic support expenditures per FTE ACAD3__F

Current fund expenditures per FTE student of the reporting institution in a given year, in constant 1999 dollars, for

support services that are an integral part of the institution’s mission, including expenditures for libraries, academic

administration, academic computing support, and curriculum development.

Dollar change in academic support expenditures ACADDIFF

Dollar change in current fund expenditures of the reporting institution for academic support activities, in constant

1999 dollars, over the period 1993-94 to 1995-96 for private not-for-profit institutions and 1995-96 to 1997-98 for

public institutions.

Missing values for ACADDIFF ACADDUMD

This dummy variable indicates missing values for real dollar change in academic support expenditures.

Log of inflation-adjusted academic support expenditures per FTE ACADLG

Natural logarithm of current fund expenditures of the reporting institution for academic support activities per FTE

student, in constant 1999 dollars, for a given year.

Dollar change in revenue from government appropriations per FTE APPR1__C

Dollar change in current fund revenue of the reporting institution from acts of federal, state, and local legislative

bodies for meeting current operating expenses per FTE student, in constant 1999 dollars, for a given time period.

Expenditures for auxiliary enterprises per FTE AUXE3__F

Current fund expenditures per FTE student of the reporting institution in a given year, in constant 1999 dollars, for

auxiliary enterprises such as residence halls and college bookstores.

Revenue from auxiliary enterprises per FTE AUXL3__F

Current fund revenues per FTE student of the reporting institution in a given year, in constant 1999 dollars, from

auxiliary enterprises such as residence halls and college bookstores.

Dollar change in average faculty compensation AVC2DIFF

Dollar change in the inflation-adjusted average salary and fringe benefits for full-time instructional faculty on 9/10-

month or 11/12-month contracts reported by private not-for-profit institutions, 1995-96 to 1997-98.

Missing values for AVC2DIFF AVC2DUMD

This dummy variable indicates missing values for the dollar change in average faculty compensation.

Average faculty compensation AVCMP__R

Average salary and fringe benefits for full-time instructional faculty on 9/10-month or 11/12-month contracts reported by private not-for-profit institutions, in constant 1999 dollars.
Appendix B—Glossary

182

Log of average faculty compensation AVCMPLG

Natural logarithm of the average salary and fringe benefits for full-time instructional faculty on 9/10-month or 11/12-

month contracts reported by private not-for-profit institutions.

Dollar change in average in-state undergraduate tuition at public 4-year institutions

 in the state AVTFDIFF

Change in the average of inflation-adjusted undergraduate tuition amounts reported by public 4-year institutions located in the same state as the institution, over the period 1995-96 to 1997-98 for private not-for-profit institutions.

Undergraduate tuition refers to tuition and required fees for full-time, full-year undergraduate students who are legal

residents of the state in which the reporting institution is located.

Log of average in-state undergraduate tuition at public 4-year institutions

 in the state AVTFLG

Natural logarithm of the average of inflation-adjusted undergraduate tuition amounts reported by public 4-year institutions located in the same state as the institution, for a given year. Undergraduate tuition refers to tuition and required fees for full-time, full-year undergraduate students who are legal residents of the state in which the reporting

institution is located.

Dollar change in the amount by which E&G revenues exceed/fall short of E&G expenditures BAL1__C

Difference, in constant 1999 dollars, between total educational and general expenditures and total educational and

general revenues.

Carnegie classification code CARNEGIE

Indicates the 1994 Carnegie classification of the reporting institution.

• Research Universities I: These institutions offer a full range of bachelor’s programs, are committed to

graduate education through the doctorate, and give high priority to research. They award 50 or more

doctoral degrees each year. In addition, they receive annually $40 million or more in federal support.

• Research Universities II: These institutions offer a full range of bachelor’s programs, are committed to

graduate education through the doctorate, and give high priority to research. They award 50 or more

doctoral degrees each year. In addition, they receive annually between $15.5 million and $40 million in

federal support.

• Doctoral Universities I: These institutions offer a full range of bachelor’s programs and are committed

to graduate education through the doctorate. They award at least 40 doctoral degrees annually in five or

more disciplines.

• Doctoral Universities II: These institutions offer a full range of bachelor’s programs and are committed

to graduate education through the doctorate. They award annually at least 10 doctoral degrees (in three

or more disciplines), or 20 or more doctoral degrees in one or more disciplines.

• Master’s (Comprehensive) Universities and Colleges I: These institutions offer a full range of bachelor’s

programs and are committed to graduate education through the master’s degree. They award 40 or more

master’s degrees annually in three or more disciplines.

• Master’s (Comprehensive) Universities and Colleges II: These institutions offer a full range of bachelor’s programs and are committed to education through the master’s degree. They award 20 or more

master’s degrees annually in one or more disciplines.
Appendix B—Glossary

183

• Bachelor’s (Liberal Arts) Colleges I: These institutions are primarily undergraduate colleges with major

emphasis on bachelor’s degree programs. They award 40 percent or more of their bachelor’s degrees in

liberal arts fields or are less restrictive in admissions.

• Bachelor’s Colleges II: These institutions are primarily undergraduate colleges with major emphasis on

bachelor’s degree programs. They award less than 40 percent of their bachelor’s degrees in liberal arts

fields or are less restrictive in admissions.

• Associate of Arts Colleges: These institutions offer associate of arts certificate or degree programs and,

with few exceptions, offer no bachelor’s degrees.

• Specialized Institutions: These institutions offer degrees ranging from the bachelor’s to the doctorate. At

least 50 percent of the degrees awarded by these institutions are in a single discipline. Examples of specialized institutions include theological seminaries, medical schools, schools of engineering, law

schools, and teachers colleges. This group of institutions also includes tribal colleges.

Revised Carnegie classification code CARNEGER

For 4-year institutions, the Carnegie classification codes of the reporting institutions were regrouped into the following categories for use in this report.

• Research/Doctoral Institutions: Includes Research I, Research II, Doctoral I, and Doctoral II institutions.

• Comprehensive Institutions: Includes Master’s (Comprehensive) I and II institutions.

• Bachelor’s Institutions: Includes Bachelor’s I and II colleges.

• Other/Specialized Institutions: Includes institutions with other Carnegie classification codes as well as

institutions that had not been classified in the 1994 system.

PCTCERT missing CERTDUM

This dummy variable was created to indicate missing values for percentage of 1996-97 awards that were certificates.

Total expenditures per FTE CEXP3__F

Total current fund expenditures per FTE student of the reporting institution in a given year, in constant 1999 dollars.

In IPEDS, these expenditures are divided into the following functional areas: instruction, research, public service,

academic support, student services, institutional support, plant operation and maintenance, scholarships and fellowships, mandatory transfers, non-mandatory transfers, auxiliary enterprises, hospitals, and independent operations.

Total revenue per FTE CREV3__F

Total current fund revenue of the reporting institution per FTE student in a given year, in constant 1999 dollars. Current funds revenues include all unrestricted gifts, grants, and other resources earned during the reporting period, and

restricted resources to the extent that such funds were expended for current operating purposes. In IPEDS, these

revenues are divided according to the following sources of funds: tuition and fees; federal, state, and local appropriations; federal, state, and local grants and contracts; private gifts, grants, and contracts; endowment income; sales

and services of educational activities; auxiliary enterprises; hospitals; other sources; and independent operations.
Appendix B—Glossary

184

1991 DUMMY91

This dummy variable indicates data for 1990-91.

1 = 1991

0 = Otherwise

1992 DUMMY92

This dummy variable indicates data for 1991-92.

1 = 1992

0 = Otherwise

1993 DUMMY93

This dummy variable indicates data for 1992-93.

1 = 1993

0 = Otherwise

1994 DUMMY94

This dummy variable indicates data for 1993-94.

1 = 1994

0 = Otherwise

1995 DUMMY95

This dummy variable indicates data for 1994-95.

1 = 1995

0 = Otherwise

1996 DUMMY96

This dummy variable indicates data for 1995-96.

1 = 1996

0 = Otherwise

Total E&G expenditures per FTE EG3__F

Total current fund expenditures of the reporting institution per FTE student in a given year, in constant 1999 dollars,

for activities that fall in the following functional categories: instruction, research, public service, academic support,

student services, institutional support, plant operation and maintenance, scholarships and fellowships, and mandatory

and non-mandatory transfers.
Appendix B—Glossary

185

Total E&G revenue per FTE EGREV__F

Total current fund revenue of the reporting institution per FTE student in a given year, in constant 1999 dollars, from

the following sources: tuition; federal, state, and local appropriations; federal, state, and local grants and contracts;

private gifts, grants, and contracts; endowment income; and sales and services of educational activities.

Revenue from endowment income per FTE ENDW3__F

Current fund revenues per FTE student of the reporting institution in a given year, in constant 1999 dollars, from

endowment and similar funds.

Revenue from federal appropriations per FTE FDAP3__F

Current fund revenues per FTE student of the reporting institution in a given year, in constant 1999 dollars, received

through acts of Congress that are for meeting current operating expenses, not for specific projects or programs.

Revenue from federal grants and contracts per FTE FDGR3__F

Current fund revenues per FTE student of the reporting institution in a given year, in constant 1999 dollars, received

from federal agencies that are for specific research projects or other types of programs.

Dollar change in revenue from federal grants and contracts FDGRDIFF

Dollar change in current fund revenue from federal grants and contracts, in constant 1999 dollars, over the period

1993-94 to 1995-96 for private not-for-profit institutions and 1995-96 to 1997-98 for public institutions.

Missing values for FDGRDIFF FDGRDUMD

This dummy variable indicates missing values for the dollar change in revenue from federal grants and contracts.

Log of federal grants and contracts less federal aid funds per FTE FDGRLG

Natural logarithm of revenue from federal grants and contracts less revenue from federal student financial aid per

FTE student, in constant 1999 dollars, for a given year.

Zero values in FDGRLG FDGRLGD

This dummy variable indicates zero values in log of federal grants and contracts less federal aid funds per FTE.

Total FTE enrollment FTE__

Total full-time equivalent (FTE) fall enrollment of the reporting institution in a given year. FTE was calculated

through the following formula:

For institutions with quarter calendar systems, total undergraduate student credit hour activity of the reporting institution divided by 15; plus total undergraduate student contact hours of the reporting institution

divided by 300; plus total graduate student credit hour activity of the reporting institution divided by 12;

plus total professional student credit hour activity of the reporting institution divided by 16.

For institutions with semester, trimester, and other calendar systems, total undergraduate student credit hour

activity of the reporting institution was divided by 15; plus total undergraduate student contact hours of the

reporting institution divided by 450; plus total graduate student credit hour activity of the reporting institution divided by 12; plus total professional student credit hour activity of the reporting institution divided by

16.
Appendix B—Glossary

186

For years in which credit/contact hour activity was not available, the ratios of total FTE generated from

credit hour activity to total headcount fall enrollment for the nearest year in which instructional activity data

were available (calculated separately for undergraduates, graduate students, and professional students) were

applied to total fall enrollment to estimate FTE values.

First-time freshmen FTE enrollment FTEFF__

Total full-time equivalent (FTE) enrollment of first-time freshmen of the reporting institution in a given year. FTE

estimates were generated by applying the ratio of undergraduate FTE generated from credit hour activity to total undergraduate fall enrollment (for the nearest year in which instructional activity data were available) to the level of

first-time enrollment.

Log of first-time freshmen FTE enrollment FTEFFLG

Natural logarithm of first-time, first-year FTE enrollment of the reporting institution.

Zero values in FTEFFLG FTELGD

This dummy variable indicates zero values in the log of first-time freshmen FTE students.

Dollar change in revenue from government grants and contracts per FTE GRNT2__C

Dollar change in current fund revenue per FTE student of the reporting institution received from federal, state, and

local agencies that is for specific research projects or other types of programs, in constant 1999 dollars, for a given

time period.

Highest degree offered HDEGOFFR

The highest degree offered at the reporting institution. This variable was used to eliminate institutions that were not

degree granting.

Revenue from hospitals per FTE HOSP3__F

Current fund revenues per FTE student of the reporting institution in a given year, in constant 1999 dollars, generated by hospitals operated by the institution.

Expenditures for hospitals per FTE HSPE3__F

Current fund expenditures per FTE student of the reporting institution in a given year, in constant 1999 dollars, for

hospitals operated by the institution.

Dollar change in institutional aid expenditures per FTE IAID3__C

Dollar change in current fund expenditures per FTE student of the reporting institution for institutional scholarships

and fellowships, in constant 1999 dollars, for a given time period.

Expenditures on institutional scholarships and fellowships per FTE IAID3__F

Current fund expenditures per FTE student of the reporting institution in a given year, in constant 1999 dollars, for

institutional aid awarded as outright grants and trainee stipends to individuals enrolled in formal coursework, including aid to students in the form of tuition or fee remission, but not including aid that is exchanged for student

work.
Appendix B—Glossary

187

Log of expenditures per FTE on institutional aid IAIDLG

Natural logarithm of current fund expenditures of the reporting institution for institutional aid per FTE student, in

constant 1999 dollars, for a given year.

Zero values in IAIDLG IAIDLGD

This dummy variable indicates zero values for log of expenditures per FTE on institutional aid.

Expenditures for independent operations per FTE INDE3__F

Current fund expenditures per FTE student of the reporting institution in a given year, in constant 1999 dollars, associated with independent operations.

Revenue from independent operations per FTE INDP3__F

Current fund revenues of the reporting institution per FTE student in a given year, in constant 1999 dollars, associated with independent operations.

Institutional support expenditures per FTE INSP3__F

Current fund expenditures per FTE student of the reporting institution in a given year, in constant 1999 dollars, for

day-to-day operational support of the institution, including expenditures for physical plant operations, general administrative services, legal and fiscal operations, and public relations.

Dollar change in institutional support expenditures INSPDIFF

Dollar change in current fund expenditures of the reporting institution for institutional support activities, in constant

1999 dollars, over the period 1993-94 to 1995-96 for private not-for-profit institutions and 1995-96 to 1997-98 for

public institutions.

Missing values for INSPDIFF INSPDUMD

This dummy variable indicates missing values for the dollar change in institutional support expenditures.

Log of institutional support expenditures per FTE INSPLG

Natural logarithm of current fund expenditures per FTE student of the reporting institution for institutional support

activities, in constant 1999 dollars, for a given year.

Dollar change in instruction expenditures per FTE INST3__C

Dollar change in current fund expenditures per FTE student of the reporting institution for activities directly related

to instruction, in constant 1999 dollars, for a given time period.

Instruction expenditures per FTE INST3__F

Current fund expenditures per FTE student of the reporting institution in a given year, in constant 1999 dollars, for

activities related directly to instruction, including expenditures for faculty compensation, office supplies, and administration of academic departments, as well as expenditures for departmental research and public service that are

not budgeted separately.
Appendix B—Glossary

188

Dollar change in instruction expenditures INSTDIFF

Dollar change in current fund expenditures of the reporting institution for instructional activities over the period

1993-94 to 1995-96 for private not-for-profit institutions and 1995-96 to 1997-98 for public institutions, in constant

1999 dollars.

Missing values for INSTDIFF INSTDUMD

This dummy variable indicates missing values for the dollar change in instruction expenditures.

Log of instruction expenditures per FTE INSTLG

Natural logarithm of current fund expenditures per FTE student of the reporting institution for instructional activities,

in constant 1999 dollars, for a given year.

Log of previous year’s instruction expenditures per FTE INSTLN

Natural logarithm of current fund expenditures per FTE student of the reporting institution for instructional activities

in the previous year, in constant 1999 dollars.

Revenue from local appropriations per FTE LOAP3__F

Current fund revenues per FTE student of the reporting institution in a given year, in constant 1999 dollars, received

through acts of the local legislative body that is for meeting current operating expenses, not for specific projects or

programs.

Missing values for LOCALE LOCALDUM

This dummy variable indicates missing values for the degree of urbanization of the reporting institution’s location.

Degree of urbanization of location of the institution LOCALE

The degree of urbanization of the reporting institution’s location, based on U.S. Census Bureau designations.

Large city = 1

A central city of a CMSA or MSA having a population greater than or equal to 250,000.

Mid-size city = 2

A central city of a CMSA or MSA, having a population less than 250,000.

Urban fringe of a large city = 3

Any incorporated place, CDP, or non-place territory within a CMSA or MSA of a large city and defined as

urban by the Census Bureau.

Urban fringe of a mid-size city = 4

Any incorporated place, CDP, or non-place territory within a CMSA or MSA of a mid-size city and defined

as urban by the Census Bureau.

Large town = 5

Any incorporated place or CDP with a population greater than or equal to 25,000 and located outside a

CMSA or MSA.
Appendix B—Glossary

189

Small town = 6

Any incorporated place or CDP with a population less than 25,000 and greater than or equal to 2,500 and

located outside a CMSA or MSA.

Rural = 7

Any incorporated place, CDP, or non-place territory designated as rural by the Census Bureau.

Revenue from local grants and contracts per FTE LOGR3__F

Current fund revenues per FTE student of the reporting institution in a given year, in constant 1999 dollars, received

from local agencies that are for specific research projects or other types of programs.

Expenditures on mandatory transfers per FTE MAND3__F

Current fund expenditures per FTE student of the reporting institution in a given year, in constant 1999 dollars, for

mandatory transfers from current funds. Mandatory transfers are those that must be made in order to fulfill a binding

legal obligation of the institution.

Expenditures on non-mandatory transfers NONM3__F

Current fund expenditures per FTE student of the reporting institution in a given year, in constant 1999 dollars, for

non-mandatory transfers from current funds. Non-mandatory transfers are those made at the discretion of the governing board to serve a variety of objectives.

Dollar change in non-student-related expenditures per FTE NONX__C

Dollar change in current fund expenditures of the reporting institution for non-student-related activities per FTE student, in constant 1999 dollars, for a given time period. Non-student-related expenditures include public service expenditures, plus pro-rated portions of expenditures for academic support, institutional support, plant operations and

maintenance, and transfers. The pro rata variable was taken from the final report of the National Commission on the

Cost of Higher Education, in which student-related costs were estimated using the proportion of clearly instructional

costs (instruction and student services) divided by total current fund expenditures less transfers, scholarship expenditures, and the partially instructional categories (academic support, institutional support, and plant operations).

OPE eligibility indicator OPEIND

Indicates Office of Postsecondary Education (OPE) eligibility status of reporting institution, i.e., whether institutions

have participation agreements with the U.S. Education Department for Title IV student aid programs.

Institution is eligible = 1

Institution is not listed separately as an eligible institution, but is a branch campus or system office of a

main campus that is eligible = 2

Institution is not eligible = 9

Institutions coded 1 or 2 are considered to be eligible by NCES.

Revenue from other sources per FTE OTHR3__F

Current fund revenues per FTE student of the reporting institution in a given year, in constant 1999 dollars, that are

not covered in other categories.
Appendix B—Glossary

190

Percentage of 1996-97 awards that were certificates PCTCERT

Percentage of degrees and certificates awarded in 1996-97 by the reporting institution (public 2-year institutions

only) that were certificates.

Percentage of 1998 fall enrollment that was full-time PERFT98R

Percentage of total 1998 fall enrollment made up of students classified as full-time at the reporting institution.

Missing values in PERFT98R PERFTDUM

This dummy variable indicates missing values in the percentage of 1998 fall enrollment that was full-time.

Ratio of graduate FTE enrollment to total FTE enrollment PERGD__

Percentage of total FTE enrollment that is graduate FTE enrollment at the reporting institution in a specific year.

Change in ratio of graduate FTE enrollment to total FTE enrollment PERGD__C

Change in the percentage of total FTE enrollment that is graduate FTE enrollment, over a given time period.

Percentage of 1998 fall enrollment that was minority PERMIN98

Percentage of total 1998 fall enrollment that was made up of students classified as minority students, including

Black, non-Hispanic, American Indian or Alaskan Native, Asian or Pacific Islander, and Hispanic students.

Missing values for PERMIN98 PERMIND

This dummy variable indicates missing values for the percentage of 1998 fall enrollment that was minority.

Log of the proportion of undergraduates enrolled in the state who were attending private,

 not-for-profit 4-year institutions PERPRLG

Natural logarithm of the percentage of total undergraduate fall headcount enrollment in the state that was made up of

students enrolled at private not-for-profit 4-year institutions.

Dollar change in philanthropic revenue per FTE PHIL1__C

Dollar change in current fund revenues of the reporting institution from endowment income and private gifts per FTE

student, in constant 1999 dollars, for a given time period.

Dollar change in philanthropic revenue PHILDIFF

Dollar change in current fund revenue, in constant 1999 dollars, from private gifts, grants, and contracts and from

endowment and similar funds, over the period 1993-94 to 1995-96 for private not-for-profit institutions.

Missing values for PHILDIFF PHILDUMD

This dummy variable indicates missing values for the dollar change in philanthropic revenue.
Appendix B—Glossary

191

Log of philanthropic revenue per FTE PHILLG

Natural logarithm of current fund revenue per FTE student, in constant 1999 dollars, from private gifts, grants, and

contracts and from endowment and similar funds, for a given year.

Zero values in PHILLG PHILLGD

This dummy variable indicates zero values for log of philanthropic revenue per FTE.

Expenditures on plant operation and maintenance per FTE PLNT3__F

Current fund expenditures per FTE student of the reporting institution in a given year, in constant 1999 dollars, for

service and maintenance related to grounds and facilities used for education and general purposes, including expenditures for utilities, property insurance, and similar items.

Dollar change in expenditures on plant maintenance and operations PLNTDIFF

Dollar change in current fund expenditures of the reporting institution for plant operations and maintenance, in constant 1999 dollars, over the period 1995-96 to 1997-98 for public institutions.

Dummy variable for PLNTDIFF missing PLNTDUMD

This dummy variable indicates missing values for the dollar change in expenditures on plant maintenance.

Dollar change in expenditures on plant maintenance, plus transfer payments PLTRDIFF

Dollar change in current fund expenditures of the reporting institution for plant operations and maintenance, plus

transfer payments, in constant 1999 dollars, over the period 1993-94 to 1995-96 for private not-for-profit institutions.

Missing values for PLTRDIFF PLTRDUMD

This dummy variable indicates missing values for the dollar change in expenditures on plant operations and maintenance, plus transfer payments.

Log of previous year’s expenditures per FTE on plant maintenance, plus transfer payments PLTRLN

Natural logarithm of current fund expenditures per FTE student of the reporting institution for plant operations and

maintenance, plus transfer payments, in the previous year, in constant 1999 dollars.

Zero values in PLTRLN PLTRLND

This dummy variable indicates zero values for the log of the previous year’s expenditures per FTE on plant operation

and maintenance, plus transfer payments.

Revenue from private gifts, grants, and contracts per FTE PRIV3__F

Current fund revenues per FTE student of the reporting institution in a given year, in constant 1999 dollars, received

from private donors for which no legal consideration is involved, and private contracts for specific goods and services provided to the funder in exchange for the funds.
Appendix B—Glossary

192

Public service expenditures per FTE PUB3__F

Current fund expenditures per FTE student of the reporting institution in a given year, in constant 1999 dollars, for

activities established primarily to provide non-instructional services that benefit external groups and budgeted specifically for such public service.

Dollar change in research expenditures per FTE RES3__C

Dollar change in current fund expenditures per FTE student of the reporting institution for separately funded research activities, in constant 1999 dollars, for a given time period.

Research expenditures per FTE RES3__F

Current fund expenditures per FTE student of the reporting institution in a given year, in constant 1999 dollars, for

activities specifically organized to produce research outcomes, commissioned by an external agency, or budgeted

separately to an internal organizational unit.

Dollar change in research expenditures RESDIFF

Dollar change in current fund expenditures of the reporting institution for research activities, in constant 1999 dollars, over the period 1993-94 to 1995-96 for private not-for-profit institutions.

Missing values for RESDIFF RESDUMD

This dummy variable indicates missing values from the dollar change in research expenditures.

Log of previous year’s research expenditures per FTE RESLN

Natural logarithm of current fund expenditures per FTE student of the reporting institution for research activities in

the previous year, in constant 1999 dollars, for a given year.

Zero values in RESLN RESLND

This dummy variable indicates zero values for the log of the previous year’s research expenditures per FTE.

Revenue from sales and services of educational activities per FTE SALE3__F

Current fund revenues per FTE student of the reporting institution in a given year, in constant 1999 dollars, that are

incidental to the conduct of instruction, research, or public service.

Expenditures on scholarships and fellowships per FTE SCHO3__F

Current fund expenditures per FTE student of the reporting institution in a given year, in constant 1999 dollars, for

outright grants and trainee stipends to individuals enrolled in formal coursework, including aid to students in the

form of tuition or fee remission, but not including aid that is exchanged for student work. Primarily institutional aid

is represented in this category, but some federal aid (such as Pell Grants) and other grants that are distributed through

the institutions are also included.
Appendix B—Glossary

193

Sector of institution SECTOR

Indicates the sector—level and control—of the reporting institution. In this report, the following codes were used:

Public, 4-year

Private not-for-profit, 4-year

Public, 2-year

Revenue from state appropriations per FTE STAP3__F

Current fund revenues per FTE student of the reporting institution in a given year, received through acts of the state

legislative body that are for meeting current operating expenses, not for specific projects or programs.

Dollar change in revenue from state appropriations STAPDIFF

Dollar change in current fund revenue from state appropriations of the reporting institution, in constant 1999 dollars,

over the period 1995-96 to 1997-98 for public institutions.

Missing values for STAPDIFF STAPDUMD

This dummy variable indicates missing values for the dollar change in revenue from state appropriations.

Revenue from state grants and contracts per FTE STGR3__F

Current fund revenues per FTE student of the reporting institution in a given year, in constant 1999 dollars, received

from state agencies that are for specific research projects or other types of programs.

Dollar change in revenue from state grants and contracts STGRDIFF

Dollar change in current fund revenue from state grants and contracts, in constant 1999 dollars, over the period

1995-96 to 1997-98 for public institutions.

Missing values for STGRDIFF STGRDUMD

This dummy variable indicates missing values for the dollar change in revenue from state grants and contracts.

Dollar change in appropriations and grants and contracts from state and local sources,

 less state/local aid funds STLODIFF

Dollar change in current fund revenue of the reporting institution received from acts of state and local legislative

bodies for meeting current operating expenses, and from state and local agencies for specific research projects or

other types of programs, less state and local student financial aid funds, in constant 1999 dollars, over the period

1993-94 to 1995-96 for private not-for-profit institutions.

Missing values for STLODIFF STLODUMD

This dummy variable indicates missing values for the dollar change in appropriations and grants and contracts from

state and local sources, less state/local aid funds.

Log of appropriations and grants and contracts from

state and local sources, less state/local aid funds, per FTE STLOLG

Natural logarithm of current fund revenue per FTE student of the reporting institution received from acts of state and

local legislative bodies for meeting current operating expenses, and from state and local agencies for specific re-
Appendix B—Glossary

194

search projects or other types of programs, less state and local student financial aid funds, in constant 1999 dollars,

for a given year.

Zero values in STLOLG STLOLGD

This dummy variable indicates zero values in the log of appropriations and grants and contracts from state and local

sources, less state/local aid funds per FTE.

Dollar change in student services expenditures per FTE STUD3__C

Dollar change in current fund expenditures of the reporting institution for student services activities per FTE student,

in constant 1999 dollars, for a given time period.

Student services expenditures per FTE STUD3__F

Current fund expenditures per FTE student of the reporting institution in a given year, in constant 1999 dollars, for

admissions, registrar activities, and activities whose primary purpose is to contribute to students’ well-being and development, including expenditures for career guidance, financial aid administration, and student health services.

Dollar change in student services expenditures STUDDIFF

Dollar change in current fund expenditures of the reporting institution for student services activities, in constant 1999

dollars, over the period 1993-94 to 1995-96 for private not-for-profit institutions.

Missing values for STUDDIFF STUDDUMD

This dummy variable indicates missing values for the dollar change in student services expenditures.

Log of student services expenditures per FTE STUDLG

Natural logarithm of current fund expenditures of the reporting institution for student services activities per FTE

student, in constant 1999 dollars, for a given year.

Zero values in STUDLG STUDLGD

This dummy variable indicates zero values for log of student services expenditures per FTE.

Log of previous year’s student services expenditures per FTE STUDLN

Natural logarithm of current fund expenditures per FTE student of the reporting institution for student services activities in the previous year, in constant 1999 dollars.

Zero values in STUDLN STUDLND

This dummy variable indicates zero values for log of previous year’s student services expenditures per FTE.

Log of previous year’s student/faculty ratio STUFCLN

Natural logarithm of the ratio of total FTE students to the total number of full-time instructional faculty on 9/10-

month or 11/12-month contracts reported by the institution for the previous year.
Appendix B—Glossary

195

Dollar change in other student-related expenditures per FTE STUX__C

Dollar change in current fund expenditures of the reporting institution for other student-related activities per FTE

student, in constant 1999 dollars, for a given time period. Other student-related expenditures include pro-rated portions of expenditures for academic support, institutional support, plant operations and maintenance, and transfers.

The pro rata variable was taken from the final report of the National Commission on the Cost of Higher Education,

in which student-related costs were estimated using the proportion of clearly instructional costs (instruction and student services) divided by total current fund expenditures less transfers, scholarship expenditures, and the partially

instructional categories (academic support, institutional support, and plant operations).

Level of in-state graduate tuition TFGR2__R

Graduate tuition and required fees for full-time, full-year students who are legal residents of the state in which the

reporting institution is located, for a specific year, in constant 1999 dollars.

Dollar change in in-district undergraduate tuition TFUG1__C

The change in undergraduate tuition and required fees for full-time, full-year students who are legal residents of the

locality in which the reporting institution is located, in constant 1999 dollars, for a given time period (only used for

public 2-year institutions).

Level of in-district undergraduate tuition TFUG1__R

Undergraduate tuition and required fees for full-time, full-year students who are legal residents of the locality in

which the reporting institution is located, for a specific year, in constant 1999 dollars (only used for public 2-year

institutions).

Dollar change in in-state undergraduate tuition TFUG2__C

The dollar change in undergraduate tuition and required fees for full-time, full-year students who are legal residents

of the state in which the reporting institution is located, in constant 1999 dollars, for a given time period.

Level of in-state undergraduate tuition TFUG2__R

Undergraduate tuition and required fees for full-time, full-year students who are legal residents of the state in which

the reporting institution is located, for a specific year, in constant 1999 dollars.

Level of out-of-state undergraduate tuition TFUG3__R

Undergraduate tuition and required fees for full-time, full-year students who are not legal residents of the state in

which the reporting institution is located, for a specific year, in constant 1999 dollars.

Log of in-state undergraduate tuition TFUGLG

Natural logarithm of in-state undergraduate tuition and required fees for full-time, full-year students who are legal

residents of the state in which the reporting institution is located, for a specific year, in constant 1999 dollars.

Zero values in TFUGLG TFUGLGD

This dummy variable was created to indicate zero values for the log of in-state undergraduate tuition.
Appendix B—Glossary

196

Undergraduate fall headcount enrollment TOTEF__

Total number of undergraduate students enrolled in the fall semester in courses creditable toward a diploma, certificate, degree, or other formal award, for a given year.

Tribal College indicator TRIBAL98

This dummy variable indicates whether the reporting public 2-year institution was classified as a Tribal College in

1998.

Tuition revenue per FTE TUIT3__F

Current fund revenues per FTE student of the reporting institution in a given year, in constant 1999 dollars, from

charges assessed against students for education purposes, including tuition and fee remissions or exemptions as well

as tuition and fee revenue that is remitted to the state.

BEA REGIONAL ACCOUNTS DATA VARIABLES

Change in average per capita income in the state STINCDIF

Dollar change in the average per capita income of the state in which the reporting institution is located, in constant

1999 dollars, over the period 1995-96 to 1997-98 for private not-for-profit institutions.

Log of average per capita income in the state STINCLG

Natural logarithm of the average per capita income of the state in which the reporting institution is located, in constant 1999 dollars, for a given year.

IPSFA VARIABLES

Percentage of undergraduates receiving federal grants times average inflation-adjusted

 amount received FEDGPAC

Percentage of first-time, full-time, degree/certificate-seeking undergraduates receiving federal grants times average

amount received for the reporting institution, in constant 1999 dollars (for 1998-99, unless otherwise indicated).

Percentage of first-time undergraduates receiving federal grants FEDGRNTP

Percentage of first-time, full-time, degree/certificate-seeking undergraduates receiving federal grants for the reporting institution (for 1998-99, unless otherwise indicated).

Average amount of federal grants received FEDGRNTA

Average amount of federal grants received by first-time, full-time, degree/certificate-seeking undergraduates for the

reporting institution, in constant 1999 dollars (for 1998-99, unless otherwise indicated).

Number of first-time undergraduates in 1999 FTUG99

Number of first-time, full-time, degree/certificate-seeking undergraduates at the reporting institution in 1999.
Appendix B—Glossary

197

Percentage of students who are first-time undergraduates FTUGP99

Percentage of all students who are first-time, full-time, degree/certificate-seeking undergraduates in 1999 at the reporting institution.

Percentage of first-time undergraduates who receive aid from any source FTUGAP99

Percentage of all first-time, full-time, degree/certificate-seeking undergraduates who receive financial aid from any

source, including federal grants, state grants, institutional grants, and student loans (for 1998-99, unless otherwise

indicated) for the reporting institution.

Percentage of first-time undergraduates receiving aid from any source times the number of

 first-time undergraduates FTUGAP2

Percentage of first-time, full-time, degree/certificate-seeking undergraduates who receive financial aid from any

source, including federal grants, state grants, institutional grants, and student loans (for 1998-99, unless otherwise

indicated), times the percentage of first-time, full-time, degree/certificate-seeking undergraduates in 1999, for the

reporting institution.

Missing values in FTUGAP FTUGAPDM

This dummy variable indicates missing values in the percentage of first-time undergraduates receiving aid from any

source times the number of first-time undergraduates.

Percentage of first-time undergraduates receiving institutional

grants times the average amount received INGPAC

Percentage of first-time, full-time degree/certificate-seeking undergraduates receiving institutional grants times the

average amount received, in constant 1999 dollars (for 1998-99, unless otherwise indicated) for the reporting institution.

Percentage of first-time undergraduates receiving institutional grants INGRNTP

Percentage of first-time, full-time, degree/certificate-seeking undergraduates receiving institutional grants at the reporting institution (for 1998-99, unless otherwise indicated).

Average amount of institutional grants received INGRNTA

Average amount of institutional grants received by first-time, full-time, degree/certificate-seeking undergraduates for

the reporting institution, in constant 1999 dollars (for 1998-99, unless otherwise indicated).

1997-98 in-state undergraduate tuition INSTAC98

1997-98 in-state tuition for first-time, full-time, degree/certificate-seeking undergraduates who are legal residents of

the state in which the reporting institution is located, in constant 1999 dollars.

Percentage change in in-state undergraduate tuition INSTAD

Percentage change in in-state tuition for first-time, full-time, degree-certificate-seeking undergraduates who are legal

residents of the state in which the reporting institution is located, 1997-98 to 1999-2000, in constant 1999 dollars.
Appendix B—Glossary

198

Dollar change in in-state undergraduate tuition INSTATCH

Dollar change in in-state tuition for first-time, full-time, degree/certificate-seeking undergraduates who are legal

residents of the state in which the reporting institution is located, 1997-98 to 1999-2000, in constant 1999 dollars.

Average amount of student loans received LOANAVG

Average amount of student loans received by first-time, full-time, degree/certificate-seeking undergraduates for the

reporting institution, in constant 1999 dollars (for 1998-99, unless otherwise indicated).

Percentage of first-time undergraduates receiving student loans times the average

 amount received LOANPAC

Percentage of first-time, full-time degree/certificate-seeking undergraduates receiving student loans times the average amount received for the reporting institution, in constant 1999 dollars (for 1998-99, unless otherwise indicated).

Percentage of first-time undergraduates receiving student loans LOANPCT

Percentage of first-time, full-time, degree/certificate-seeking undergraduates receiving student loans at the reporting

institution (for 1998-99, unless otherwise indicated).

Percentage of first-time undergraduates receiving state grants times the average

 amount received STGPAC

Percentage of first-time, full-time degree/certificate-seeking undergraduates receiving state grants times the average

amount received for the reporting institution, in constant 1999 dollars (for 1998-99, unless otherwise indicated).

Percentage of first-time undergraduates receiving state grants STGRNTP

Percentage of first-time, full-time, degree/certificate-seeking undergraduates receiving state grants at the reporting

institution (for 1998-99, unless otherwise indicated).

Average amount of state grants received STGRNTA

Average amount of state grants received by first-time, full-time, degree/certificate-seeking undergraduates for the

reporting institution, in constant 1999 dollars (for 1998-99, unless otherwise indicated).

1997-98 financial aid data indicator YRINDFAD

This dummy variable indicates institutions that reported financial aid data for 1997-98 instead of 1998-99.