Higher Education
School's Use of the Antitrust Exemption Has Not Significantly Affected College Affordability or Likelihood of Student Enrollment to Date Gao ID: GAO-06-963 September 21, 2006In 1991 the U.S. Department of Justice sued nine colleges and universities, alleging that they had restrained competition by making collective financial aid determinations for students accepted to more than one of these schools. Against the backdrop of this litigation, Congress enacted a temporary exemption from antitrust laws for higher education institutions in 1992. The exemption allows limited collaboration regarding financial aid practices with the goal of promoting equal access to education. The exemption applies only to institutional financial aid and can only be used by schools that admit students without regard to ability to pay. In passing an extension to the exemption in 2001, Congress directed GAO to study the effects of the exemption. GAO examined (1) how many schools used the exemption and what joint practices they implemented, (2) trends in costs and institutional grant aid at schools using the exemption, (3) how expected family contributions at schools using the exemption compare to those at similar schools not using the exemption, and (4) the effects of the exemption on affordability and enrollment. GAO surveyed schools, analyzed school and student-level data, and developed econometric models. GAO used extensive peer review to obtain comments from outside experts and made changes as appropriate.
Twenty-eight schools--all highly selective, private 4-year institutions--formed a group to use the antitrust exemption and developed a common methodology for assessing financial need, which the group called the consensus approach. The methodology used elements already a part of another need analysis methodology; schools modified this methodology and reached agreement on how to define those elements. By the 2004-2005 school year, 25 of 28 schools in the group were using the consensus approach. Schools' implementation of the approach varied, however, with officials from 12 of the 25 schools reporting that they partially implemented it, in part because they believed it would be costly to do so. Over the last 5 years, tuition, room, and board costs among schools using the antitrust exemption increased by 13 percent compared to 7 percent at all other private 4-year schools not using the exemption. While the amount of institutional aid at schools using the exemption also increased--it did so at a slower rate. The average institutional grant aid award per student increased by 7 percent from $18,675 in 2000-2001 to $19,901 in 2005-2006. There was virtually no difference in the amount students and their families were expected to pay between schools using the exemption and similar schools not using the exemption. While officials from schools using the exemption expected that students accepted to several of their schools would experience less variation in the amount they were expected to pay, GAO found that students accepted to schools using the exemption and comparable schools not using the exemption experienced similar variation in the amount they were expected to pay. Not all schools using the consensus approach chose to adopt all the elements of the methodology, a factor that may account for the lack of consistency in expected family contributions among schools using the exemption. Based on GAO's analysis, schools' use of the consensus approach did not have a significant impact on affordability--the amount students and families paid for college--or affect the likelihood of enrollment at those schools to date. While GAO found that the use of the consensus approach resulted in higher amounts of need-based grant aid awarded to some student groups compared to their counterparts at schools not using the consensus approach, the total amount of grant aid awarded was not significantly affected. It was likely that grant aid awards shifted from non-need-based aid, such as academic and athletic scholarships, to aid based on a student's financial need. Finally, implementing the consensus approach did not increase the likelihood of low-income or minority students enrolling at schools using the consensus approach compared to schools that did not. The group of schools using the exemption reviewed this report and stated it was a careful and objective report. However, they had concerns about the data used in GAO's econometric analysis, which GAO believes were reliable.
GAO-06-963, Higher Education: School's Use of the Antitrust Exemption Has Not Significantly Affected College Affordability or Likelihood of Student Enrollment to Date
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Report to Congressional Committees:
United States Government Accountability Office:
GAO:
September 2006:
Higher Education:
Schools' Use of the Antitrust Exemption Has Not Significantly Affected
College Affordability or Likelihood of Student Enrollment to Date:
GAO-06-963:
GAO Highlights:
Highlights of GAO-06-963, a report to congressional committees
Why GAO Did This Study:
In 1991 the U.S. Department of Justice sued nine colleges and
universities, alleging that they had restrained competition by making
collective financial aid determinations for students accepted to more
than one of these schools. Against the backdrop of this litigation,
Congress enacted a temporary exemption from antitrust laws for higher
education institutions in 1992. The exemption allows limited
collaboration regarding financial aid practices with the goal of
promoting equal access to education. The exemption applies only to
institutional financial aid and can only be used by schools that admit
students without regard to ability to pay.
In passing an extension to the exemption in 2001, Congress directed GAO
to study the effects of the exemption. GAO examined (1) how many
schools used the exemption and what joint practices they implemented,
(2) trends in costs and institutional grant aid at schools using the
exemption, (3) how expected family contributions at schools using the
exemption compare to those at similar schools not using the exemption,
and (4) the effects of the exemption on affordability and enrollment.
GAO surveyed schools, analyzed school and student-level data, and
developed econometric models. GAO used extensive peer review to obtain
comments from outside experts and made changes as appropriate.
What GAO Found:
Twenty-eight schools”all highly selective, private 4-year
institutions”formed a group to use the antitrust exemption and
developed a common methodology for assessing financial need, which the
group called the consensus approach. The methodology used elements
already a part of another need analysis methodology; schools modified
this methodology and reached agreement on how to define those elements.
By the 2004-2005 school year, 25 of 28 schools in the group were using
the consensus approach. Schools‘ implementation of the approach varied,
however, with officials from 12 of the 25 schools reporting that they
partially implemented it, in part because they believed it would be
costly to do so.
Over the last 5 years, tuition, room, and board costs among schools
using the antitrust exemption increased by 13 percent compared to 7
percent at all other private 4-year schools not using the exemption.
While the amount of institutional aid at schools using the exemption
also increased”it did so at a slower rate. The average institutional
grant aid award per student increased by 7 percent from $18,675 in 2000-
2001 to $19,901 in 2005-2006.
There was virtually no difference in the amount students and their
families were expected to pay between schools using the exemption and
similar schools not using the exemption. While officials from schools
using the exemption expected that students accepted to several of their
schools would experience less variation in the amount they were
expected to pay, GAO found that students accepted to schools using the
exemption and comparable schools not using the exemption experienced
similar variation in the amount they were expected to pay. Not all
schools using the consensus approach chose to adopt all the elements of
the methodology, a factor that may account for the lack of consistency
in expected family contributions among schools using the exemption.
Based on GAO‘s analysis, schools‘ use of the consensus approach did not
have a significant impact on affordability”the amount students and
families paid for college”or affect the likelihood of enrollment at
those schools to date. While GAO found that the use of the consensus
approach resulted in higher amounts of need-based grant aid awarded to
some student groups compared to their counterparts at schools not using
the consensus approach, the total amount of grant aid awarded was not
significantly affected. It was likely that grant aid awards shifted
from non-need-based aid, such as academic and athletic scholarships, to
aid based on a student‘s financial need. Finally, implementing the
consensus approach did not increase the likelihood of low-income or
minority students enrolling at schools using the consensus approach
compared to schools that did not.
The group of schools using the exemption reviewed this report and
stated it was a careful and objective report. However, they had
concerns about the data used in GAO‘s econometric analysis, which GAO
believes were reliable.
[Hyperlink, http://www.gao.gov/cgi-bin/getrpt?GAO-06-963.]
To view the full product, including the scope and methodology, click on
the link above. For more information, contact Cornelia Ashby at (202)
512-7215 or ashbyc@gao.gov.
[End of section]
Contents:
Letter:
Results in Brief:
Background:
Twenty-Eight Schools Used the Antitrust Exemption to Develop a Common
Methodology for Assessing a Family's Financial Need:
As the Cost of Attendance at Schools Using the Exemption Rose, the
Amount of Institutional Grant Aid They Provided to Students Increased
at a Slower Rate:
Students Accepted to Both Schools Using the Exemption and Comparable
Schools Had No Appreciable Difference in the Amount They Would Be
Expected to Contribute Towards College:
Implementation of a Common Methodology Has Not Significantly Affected
Affordability or Enrollment at Schools Using the Exemption:
Concluding Observations:
Agency Comments:
Appendix I: Statistical Analysis of Expected Family Contributions at
Schools Using the Exemption and Comparable Schools:
Appendix II: Econometric Analysis of Effects of the Higher Education
Antitrust Exemption on College Affordability and Enrollment:
Theories of the Effects of the Consensus Approach on Financial Aid:
Sources of Data for the Model:
Selection of Control Schools:
Specifications of Econometric Models and Estimation Methodology:
Estimation Results of the Effects of Attending Meetings and
Implementing the Consensus Approach:
Limitations of the Study:
Appendix III: Classification of 1999-2000 Academic Year and Schools
Only Attending the 568 Group Meetings:
Does Academic Year 1999-2000 belong to the Pre-or Post-Consensus
Approach Implementation Period?
Do the Schools That Only Attended the 568 group Meetings belong to the
Control or Treatment Group?
Appendix IV: Comments from 568 Presidents' Group:
Appendix V: Consultants and Peer Reviewers:
Appendix VI: GAO Contact and Staff Acknowledgments:
Bibliography:
Tables:
Table 1: Comparison of the Federal Methodology and the College Board's
Base Institutional Methodology for Need Analysis:
Table 2: Schools Using the Antitrust Exemption, as of May 2006:
Table 3: Comparison of Consensus Approach Developed by Schools Using
the Antitrust Exemption Compared to the College Board's Institutional
Methodology:
Table 4: Number of Schools That Did Not Implement Certain Consensus
Approach Options in School Year 2005-2006:
Table 5: Estimated Changes in Amount Paid, Financial Aid, and
Enrollment at Schools Using the Consensus Approach Compared to Schools
Not Using the Exemption:
Table 6: Schools Included in Analysis of Effects of Exemption:
Table 7: Summary Statistics of Expected Family Contributions:
Table 8: Tests of Variations in Expected Family Contributions:
Table 9: Control and Treatment Schools for Analyzing Effects of the
Consensus Approach Implementation:
Table 10: Summary Statistics of Variables Used in Regression Analysis,
1995-1996 and 2003-2004: CA Schools:
Table 11: Summary Statistics of Variables Used in Regression Analysis,
1995-1996 and 2003-2004: Non-CA Schools:
Table 12: CA and Non-CA Schools: Price and Financial Aid:
Table 13: CA and Non-CA Schools--Financial Aid Applicants Only: Price
and Financial Aid:
Table 14: Regression Estimates of Effects of Consensus Approach
Implementation on Price, Tuition, and Enrollment:
Table 15: Regression Estimates of Effects of Consensus Approach
Implementation on Financial Aid:
Table 16: Estimates of Effects of Consensus Approach Implementation on
Affordability and Enrollment in CA Schools Relative to Non-CA Schools:
Table 17: Estimates of Affordability and Enrollment before the
Consensus Approach Implementation for Particular Groups of Students in
Both CA and Non-CA Schools:
Table 18: Differential Effects of Consensus Approach Implementation on
Affordability and Enrollment in CA Schools for Particular Groups of
Students:
Table 19: Comparison of Observed and Predicted Price and Financial Aid
Variables in CA and Non-CA Schools: Pre--and Post--Consensus Approach
Implementation Period:
Figures:
Figure 1: Determining a Student's Financial Need:
Figure 2: Average Tuition, Fees, and Room and Board at Schools Using
the Antitrust Exemption Compared to All Other Private 4-Year Not-For-
Profit Schools and Comparable Schools, School Years 2000 to 2005:
Figure 3: Percentage of Students at Schools Using the Antitrust
Exemption Receiving Various Types of Institutional Grant Aid from 2000
to 2006:
Figure 4: Average Amount of Various Institutional Grant Aid Awards at
Schools Using the Antitrust Exemption from 2000 to 2006:
Abbreviations:
CA: Consensus Approach:
EFC: expected family contribution:
IPEDS: Integrated Postsecondary Education Data System:
MIT: Massachusetts Institute of Technology:
NPSAS: National Postsecondary Student Aid Study:
United States Government Accountability Office:
Washington, DC 20548:
September 21, 2006:
Congressional Committees:
In 1991, the U.S. Department of Justice sued nine colleges and
universities, alleging that by collectively making financial aid
determinations for students accepted to more than one of these schools,
the schools had unlawfully conspired to restrain trade in violation of
the Sherman Act. Specifically, Justice argued that by agreeing upon the
amount of money that the families of admitted students would be
expected to pay towards their student's education, these schools were
engaging in price fixing. Justice and the schools ultimately reached
settlements that ended these activities. These schools, which are among
the nation's most prestigious private universities, had engaged in
these activities for more than 30 years.
Against the backdrop of this litigation, in 1992 Congress enacted a
temporary exemption from the antitrust laws for higher education
institutions that has been renewed several times and is set to expire
in 2008. Under the exemption, schools are allowed a limited degree of
collaboration on financial aid practices in the hope that it would
further the government's goal of promoting equal access to educational
opportunities for students, including low income and minority students.
Under the exemption, schools that admit students without regard to
ability to pay would be able to develop and use common principles of
financial aid policies and make changes to formulas used to calculate
financial aid awards, but not discuss specific students' awards.
Specifically, such schools would be allowed to engage in the following
joint practices:
1. agreeing to award financial aid only on the basis of demonstrated
financial need;
2. using common principles of analysis for determining financial need;
3. using a common aid application form; and:
4. exchanging, through an independent third party, financial
information submitted by students and their families.
The exemption only applies to an institution's own aid. Federal aid,
which is allocated based on a statutory formula, was not targeted by
the exemption. Proponents of the exemption believe that common
principles could lead to a more equitable allocation of aid, make
attendance at schools using the exemption more affordable, and, in
turn, increase enrollment of low income students at these schools.
Moreover, proponents believe that allowing schools to use common
principles for determining financial need should reduce variation among
schools in what a family is expected to pay and enable students to
choose a school without making cost the defining factor. On the other
hand, some are concerned that exempting schools from antitrust laws
would reduce competition. Specifically, with less competition, some
students would pay more for college because their opportunities to
consider price differences when choosing schools would be diminished.
In passing the 2001 extension to the exemption, Congress directed GAO
to study whether the exemption resulted in changes in the amount
students and their families would pay for college. In response to this
mandate, we determined: (1) how many schools used the exemption and
what joint practices these schools implemented, (2) trends in cost of
attendance and institutional grant aid at schools using the exemption,
(3) how expected family contributions at schools using the exemption
compare to those at similar schools that did not use the exemption, and
(4) the effects of the exemption on affordability and enrollment.
To determine the number of schools that made use of the exemption since
1992, we reviewed literature and studies on the exemption, interviewed
higher education associations, and reviewed documents that identified a
group of schools that were using the exemption. We interviewed
officials of these schools, reviewed reports of their activities, and
collected information on their financial aid policies. To determine if
other schools might have formed groups to participate in activities
allowed under the exemption, we also surveyed selected similar schools
and found no such other groups.
To determine trends in cost of attendance--tuition, room, and board--
and institutional grant aid at the schools using the exemption, we
collected data from them and supplemented it with information available
from the U.S. Department of Education's Integrated Postsecondary
Education Data System (IPEDS) for school years 2000-2001 through 2005-
2006. We received data from 26 of the 28 schools using the exemption.
We determined that the IPEDS and institutional data were sufficiently
reliable and valid for purposes of our review.
To determine how expected family contributions (EFC) at schools using
the exemption compared to those at similar schools not using the
exemption, we collected and compared student-level EFC data from both
sets of schools as of April 1, 2006. To assess the extent of variation
in EFC across multiple schools, we isolated the EFCs of individual
students accepted at (1) multiple schools using the exemption, (2)
multiple schools not using the exemption, and (3) both schools using
the exemption and schools that did not. While EFC determinations of
students accepted at both schools using the exemption and those that
did not best show the extent of variation because it allows us to
control for differences in student characteristics, this group of
students was small. Thus, we supplemented our analysis with data from
the other two groups listed. Based on our discussions with school
officials on the steps taken to ensure reliability of the EFC data, we
determined that the data were sufficiently reliable and valid for
purposes of our review. See appendix I for further details of our
statistical analysis.
To assess the effects of the exemption on affordability and enrollment,
we developed econometric models to examine the effects of the exemption
on tuition, financial aid (including grants and loans), amount paid for
college (measured by the total cost of attendance less total grant
aid), and student enrollment at schools using the exemption.
Determining "effect" requires both a treatment group (those schools
using the exemption) and a control group (a comparable set of schools
that did not use the exemption) as well as controlling for variations
in the actions of the schools over time that are independent of the
exemption. Differences found between the two groups in terms of
affordability and enrollment (effects) can then be attributed to the
exemption (treatment). GAO's econometric analysis was focused on the
mandate from Congress that requires us to examine the effects of the
exemption. It is different from a market-specific analysis conducted in
an antitrust investigation and is not intended to address whether or
not conduct may be taking place that might violate the antitrust laws
in the absence of the exemption. In order to find a comparative set of
schools, we used the U.S. News and World Report annual rankings of the
"best colleges." We obtained school-level data from IPEDS and student-
level data from the National Postsecondary Student Aid Study for
academic years 1995-1996, 1999-2000, and 2003-2004. We also collected
data from other sources, including a GAO survey of the schools using
the exemption and the comparable schools. We analyzed whether there
were any effects on affordability and enrollment at schools using the
exemption for all students and whether there were differences by family
income or race. We also controlled for other factors that could cause
changes in affordability and enrollment, such as school or student
characteristics. Because of data limitations, we were not able to
include all schools using the exemption in the treatment group.
Nevertheless, there were sufficient similarities between the excluded
schools and the schools we included in our model to allow for a
meaningful analysis. In developing the models, we reviewed several
studies on the economics of higher education. We provided a detailed
draft outline of our econometric methodology, including a description
of the types and sources of data we used, to outside experts with whom
we consulted on the design and analysis because of their in-depth
knowledge of antitrust law and the economics of higher education. We
also provided a draft of our report to peer reviewers in academia and
incorporated their comments when appropriate. See appendixes II and III
for a detailed explanation of our econometric analysis. We conducted
our work in accordance with generally accepted government auditing
standards between May 2005 and September 2006.
Results in Brief:
Twenty-eight schools--all highly selective, private 4-year
institutions--formed a group to use the antitrust exemption, and of the
four collaborative activities allowed, the group has engaged in only
one--development of a common methodology for assessing financial need,
which the group called the "consensus approach." With respect to the
other three activities allowed under the exemption, the schools either
chose not to engage in the activities or piloted them on a limited
basis. For example, three schools in the group attempted to share
student-level financial aid data through a third party. However, the
schools reported that because the effort was too burdensome and yielded
little useful information, they chose not to continue. The consensus
approach to need analysis developed by the group is based on elements
already a part of another need analysis methodology that considers a
family's income and assets to determine a student's ability to pay for
college. Schools modified some elements of that methodology and reached
agreement on how to define those elements. Although schools in the
group agreed to the concept of the consensus approach, the schools
varied in their implementation of the methodology. Schools that
partially implemented or did not implement the consensus approach often
cited concerns about potential increased costs associated with
implementing the methodology. Twenty five of the 28 schools implemented
the consensus approach methodology; three did not. Schools that chose
to use part or all of the elements of the consensus approach did so
between 2002 and 2005.
Over the last 5 years, tuition, room, and board costs at the group of
schools using the exemption increased, and while the amount of grant
aid these schools provided to students also increased, it did so at a
slower rate. Between school years 2000-2001 and 2004-2005, tuition,
room, and board increased by 13 percent, from $38,319 to $43,164,
compared to a 7 percent increase at other private 4-year not-for-profit
schools. Average institutional grant aid awards increased by 7 percent
from $18,675 to $19,901 at schools using the exemption, and the
percentage of students receiving such aid increased from 37 to 40
percent, from school years 2000-2001 to 2005-2006. Among students
receiving institutional grant aid awards, the percent of students who
received need-based institutional grant aid at schools using the
exemption increased from 34 to 36 percent, and the percent of students
receiving non-need-based institutional grant aid awards (i.e., academic
or athletic scholarships) also increased slightly from 2 to 4 percent.
We found virtually no difference in the amounts students and their
families were expected to pay at schools using the exemption compared
to similar schools not using the exemption. Average expected family
contribution (EFC) for students accepted at schools using the exemption
was $27,166 and for those accepted at comparable schools not using the
exemption was $27,395 in school year 2005-2006. While officials from
schools using the exemption expected that students accepted to several
of their schools would experience less variation in their EFC, we found
that the variation in the EFC for a student who was accepted to several
schools using the exemption was similar to the variation in EFC that
same student received from schools not using the exemption. The
variation in EFCs for these students was about $6,000 at both sets of
schools. Not all schools using the consensus approach chose to adopt
all the elements of the methodology, a factor that may account for the
lack of consistency in EFCs among schools using the exemption. For
example, seven schools chose not to use the consensus method for
considering home equity that could have contributed to the variation in
EFCs at schools using the exemption.
Based on our analysis, schools' use of the consensus approach did not
have a significant impact on affordability--the amount students and
families paid for college, which is measured by the total cost of
attendance less total grant aid--or affect the likelihood of enrollment
at schools using the exemption. While we found that the use of the
consensus approach resulted in higher amounts of need-based grant aid
awarded to some student groups (middle income, Asian students, and
Hispanic students) compared to their counterparts at schools not using
the consensus approach, the total amount of grant aid awarded did not
significantly change. It is likely that because the change in total
grant aid was similar compared to the change at schools not using the
consensus approach, the increase in need-based grant aid was offset by
a decrease in non-need-based aid, such as academic scholarships. We
also found that low income students at schools using the consensus
approach, compared to those at schools not using the consensus
approach, received a significantly higher amount of total aid, which
includes both grants and loans. However, the amount of grant aid that
these students received did not significantly change, which suggest
they likely received more aid in the form of loans, which they would
need to repay. Additionally, implementing the consensus approach did
not affect the likelihood of low-income or minority students enrolling
at schools using the consensus approach compared to schools that did
not. Because we have data for only one year after implementation, it is
possible that some eventual effects of the consensus approach may not
be captured. The effects of using the consensus approach could be
gradual, rather than immediate, and therefore may not be captured until
later years.
We provided the group of schools using the antitrust exemption,
Secretary of Education, and Attorney General with a copy of our draft
report for review and comments. The group of schools using the
exemption reviewed a draft of this report and stated it was a careful
and objective report, but raised concerns about the data used in our
econometric analysis and the report's tone and premise. We believe that
the data we used were reliable to support our conclusions. The group of
schools using the exemption also provided technical comments, which we
incorporated where appropriate. The group's written comments appear in
appendix IV. The Department of Education reviewed the report and did
not have any comments. The Department of Justice provided technical
comments, which we incorporated where appropriate.
Background:
Legal History of Antitrust Exemption for Higher Education Institutions:
In the early 1990's the U.S. Department of Justice (Justice) sued nine
universities and colleges, alleging that their practice of collectively
making financial aid decisions for students accepted to more than one
of their schools restrained trade in violation of the Sherman
Act.[Footnote 1] By consulting about aid policies and aid decisions,
through what was known as the Overlap group, the schools made certain
that students who were accepted to more than one Overlap school would
be expected to contribute the same towards their education. Thus,
according to Justice, "fixing the prices" students would be expected to
pay. All but one school, Massachusetts Institute of Technology (MIT),
settled with Justice out of court, ending the activities of the Overlap
group. The District Court ruled that MIT's joint student aid decisions
in the Overlap group violated the Sherman Act. On appeal, the Third
Circuit Court of Appeals agreed with the District Court that the
challenged practices were commercial activity subject to the antitrust
laws. However, it reversed the judgment and directed the District Court
to more fully consider the procompetitive and noneconomic
justifications advanced by MIT during the court proceedings and whether
social benefits attributable to the practices could have been achieved
by means less restrictive of competition.[Footnote 2] In recognition of
the importance of financial aid in achieving the government's goal of
educational access, but also mindful of the importance of antitrust
laws in ensuring the benefits of competition, the Congress passed a
temporary antitrust exemption.[Footnote 3] In 1994, Congress extended
the exemption and specified the four collective activities in which
schools that admit students on a need-blind basis could
engage.[Footnote 4] The exemption was extended most recently in 2001,
and is set to expire in 2008.[Footnote 5]
Determining a Student's Financial Need:
For many students, financial aid is necessary in order to enroll in and
complete a postsecondary education. In school year 2004-2005, about
$113 billion in grant, loan, and work-study aid was awarded to students
from a variety of federal, state, and institutional sources.[Footnote
6] Need analysis methodologies are used to determine the amount of
money a family is expected to contribute toward the cost of college and
schools use this information in determining how much need-based
financial aid they will award. For the purposes of awarding federal
aid, expected family contribution (EFC) is defined in the Higher
Education Act of 1965, as amended, as the household financial resources
reported on the Free Application for Federal Student Aid, minus certain
expenses and allowances. The student's EFC is then compared to the cost
of attendance to determine if the student has financial need. (see fig.
1):
Figure 1: Determining a Student's Financial Need:
[See PDF for image]
Source: GAO analysis of the Higher Education Act.
[End of figure]
While the federal methodology is used to determine a student's
eligibility for federal aid, some institutions use this methodology to
award their own institutional aid. Others prefer a methodology
developed by the College Board (called the institutional methodology)
or their own methodology.[Footnote 7] Schools that use the
institutional methodology require students to complete the College
Scholarship Service/Financial Aid PROFILE application and the College
Board calculates how much they and their families will be expected to
contribute toward their education. Schools that use these alternative
methodologies feel they better reflect a family's ability to pay for
college because they consider many more factors of each family's
financial situation than the federal methodology. For example, the
institutional methodology includes home and farm equity when
calculating a family's ability to pay for college, while the federal
methodology excludes them. See table 1 below for a comparison of the
federal methodology to the institutional methodology.
Table 1: Comparison of the Federal Methodology and the College Board's
Base Institutional Methodology for Need Analysis:
Home equity;
Federal methodology: Not included;
Institutional methodology: Included.
Family farm equity;
Federal methodology: Not included;
Institutional methodology: Included.
Student assets;
Federal methodology: Included, 35 percent of student's net worth
expected to be used for college costs. Minimum contribution from
student expected;
Institutional methodology: Included, 25 percent of student's net worth
expected to be used for college costs. Minimum contribution from
student expected.
Family assets;
Federal methodology: Excluded the assets of families whose income fell
below $50,000 and who filed a simple tax return; 12 percent of assets
expected to be used towards college;
Institutional methodology: Included a fuller range of family assets,
such as home equity, other real estate, and business and farm assets; 5
percent of assets expected to be used towards college.
Divorced and separated families; (Noncustodial parent contribution);
Federal methodology: Excluded noncustodial parent income and assets;
Institutional methodology: Included noncustodial parent income and
assets.
Total income;
Federal methodology: Included only the adjusted gross income reported
on federal tax returns, plus various categories of untaxed income;
Institutional methodology: Included in total income any untaxed income
and any paper depreciation and business, rental, or capital losses that
artificially reduced adjusted gross income.
Medical/elementary and secondary school expenses;
Federal methodology: Not included;
Institutional methodology: Included.[A].
Cost of living variance;
Federal methodology: Not included;
Institutional methodology: Not included.[B].
Number of siblings in college;
Federal methodology: Included--divides the parental contribution by the
number of siblings enrolled in college;
Institutional methodology: Included--instead of dividing by the number
in college, parental contribution per student reduced by 40 percent for
2 in college and by 55 percent for 3.
Source: GAO analysis.
Notes: The institutional methodology is the base one provided by the
College Board to schools. A school may select other options available
in the institutional methodology when assessing a student's financial
need.
[A] Elementary and secondary school expenses are an option that could
be added by a school.
[B] Cost of living variance is an option that could be used by a
school.
[End of table]
Twenty-Eight Schools Used the Antitrust Exemption to Develop a Common
Methodology for Assessing a Family's Financial Need:
Twenty-eight schools formed a group under the antitrust exemption and
engaged in one of the four activities allowable under the exemption.
School officials believed that the one activity--development of a
common methodology for assessing financial need--would help reduce
variation in amounts students were expected to pay when accepted to
multiple schools and allow students to base their decision on which
school to attend on factors other than cost. In developing the common
methodology, called the consensus approach, schools modified an
existing need analysis methodology and reached agreement on how to
treat each element of the methodology. While the schools reached
agreement on a methodology, implementation of the methodology among the
schools varied.
Highly Selective Private4-Year Colleges and Universities Formed a Group
to Participate in Activities Allowable under the Exemption:
Twenty-eight schools, all of which have need-blind admission policies
as required under the law, formed the 568 Presidents' Group in 1998
with the intent to engage in activities allowed by the antitrust
exemption.[Footnote 8] Members of the group are all private 4-year
schools that have highly selective admissions policies. One member
school dropped out of the group because the school no longer admitted
students on a need-blind basis. (See table 2 below for a list of
current and former member schools.)
Table 2: Schools Using the Antitrust Exemption, as of May 2006:
Amherst College:
Boston College;
Middlebury College:
Northwestern University.
Pomona College.
Brown University
Claremont McKenna College;
Rice University.
Columbia University;
Swarthmore College.
Cornell University;
University of Chicago.
Dartmouth College;
University of Notre Dame.
Davidson College;
University of Pennsylvania.
Duke University;
Vanderbilt University.
Emory University;
Wake Forest University.
Georgetown University;
Wellesley College.
Grinnell College;
Wesleyan University.
Haverford College;
Williams College.
Massachusetts Institute of Technology;
Yale University.
Source: GAO analysis.
Note: Bowdoin College and Macalester College were once members of the
group.
[End of table]
Membership is open to colleges and universities that have need blind
admissions policies in accordance with the law. Member schools must (1)
sign a certificate of compliance confirming the institution's need-
blind admissions policy and (2) submit a signed memorandum of
understanding that indicates willingness to participate in the group
and adhere to its guidelines. Additionally, members share in paying the
group's expenses.
In addition to the group's 28 members, 6 schools attended meetings of
the group to observe and listen to discussions, but have not become
members.[Footnote 9] In order to attend meetings, observer schools were
required to provide a certificate of compliance stating that they had a
need-blind admission policy. Observer schools explained that their
participation was based on a desire to be aware of what similar schools
were thinking in terms of need analysis methodology, as well as have an
opportunity to participate in these discussions. Despite these
benefits, observer schools said they preferred not to join as members
because they did not wish to agree to a common approach to need
analysis or they did not want to lose institutional independence.
Other institutions with need-blind admissions reported that, although
eligible to participate in activities allowed by the exemption, they
were not interested or not aware of the group formed to use the
antitrust exemption. Some told us that they did not understand how
students would benefit from the schools' participation in such
activities. Others cited limited funding to make changes to their need
analysis methodology and concerns that they would lose the ability to
award merit aid to students.[Footnote 10]
Participating Schools Agreed to a Common Methodology for Assessing
Financial Need, but Schools Varied in Their Implementation of the
Methodology:
Of the four activities allowed under the antitrust exemption, the 28
schools engaged in only one--development of the consensus approach for
need analysis. With respect to the other three activities allowed under
the exemption, the schools either chose to not engage in the activities
or piloted them on a limited basis. For example, three schools in the
group attempted to share student-level financial aid data through a
third party. However, they reported that because the effort was too
burdensome and yielded little useful information, they chose not to
continue. The group also expressed little need or interest in creating
another common aid application form as such a form already existed.
Schools also decided to leave open the option to award aid on a non-
need basis.
According to the officials representing the 28 schools, the main
purpose of the group was to discuss ways to make the financial aid
system more understandable to students and their families and commit to
developing a common methodology for assessing a family's ability to pay
for college, which they called the consensus approach. Developing an
agreed upon common approach to need analysis, according to school
officials, might help decrease variation in what families were expected
to pay when accepted to multiple schools, allowing students to base
their decision on what school to attend on factors other than cost.
School officials also believed that agreeing to a common need analysis
methodology would produce expected family contributions that were
reasonable and fair for families and allow schools to better target
need-based aid. The group did not address the composition of a
student's financial aid package; specifically, what combination of
grants, loans, or work-study a student would receive.
In developing the consensus approach for need analysis, the schools
modified elements already in the College Board's institutional
methodology, but member schools agreed to treat these elements the same
when calculating a student's EFC. Some of the modifications that the
group made to College Board's institutional methodology were later
incorporated into the institutional methodology. The consensus approach
and the institutional methodology similarly treat income from the non-
custodial parent, and both account for the number of siblings in
college in the same manner when calculating a student's expected family
contribution. However, there are differences in how each methodology
treats a family's home equity and a student's assets. For example, the
institutional methodology uses a family's entire home equity in its
assessment of assets available to pay for college, while the consensus
approach limits the amount of home equity that can be included.
According to one financial aid officer at a member school, including
the full amount of a family's home equity was unfair to many parents
because in some areas of the country the real estate market had risen
so rapidly that equity gains inflated a family's assets. Officials
representing some member schools stated that adjustments to home equity
would likely affect middle and upper income families more than lower
income families who are less likely to own a home. Table 3 below
further illustrates the differences and similarities between the
consensus approach and the institutional methodology.
Table 3: Comparison of Consensus Approach Developed by Schools Using
the Antitrust Exemption Compared to the College Board's Institutional
Methodology:
Home equity;
Institutional methodology: Included. No limit on amount considered
asset available to pay for college;
Consensus approach: Included. Home value is capped at 2.4 times income
minus mortgage debt.
Family farm equity;
Institutional methodology: Included;
Consensus approach: Included.
Student and family assets;
Institutional methodology: Included, but assets counted separately; 25
percent of student's net worth expected to be used for college costs; 5
percent of parent's assets expected to be used for college costs;
Consensus approach: Included. In general student assets--such as
prepaid and college savings plans are combined with family assets. 5
percent of family assets expected to be used for college. Trust funds
will be considered on a case by case basis.
Divorced and separated families; (Noncustodial parent);
Institutional methodology: Included. Expects noncustodial parent to
contribute towards college costs;
Consensus approach: Same as IM.
Total income/adjusted gross income;
Institutional methodology: Included in total income any untaxed income
and any paper depreciation and business, rental, or capital losses
which artificially reduced adjusted gross income;
Consensus approach: Excluded business and rental losses from
calculation of income.
Medical/elementary and secondary school expenses;
Institutional methodology: Included.[A];
Consensus approach: Included.
Cost of living variance;
Institutional methodology: Excluded.[B];
Consensus approach: Adjusted living expenses based on geographic
location. Takes into consideration that it is more costly to live in
some areas of the country.
Number of siblings in college;
Institutional methodology: Included-- considers number of children
enrolled in college, but instead of dividing by the number in college,
it reduced the parental contribution for each student by 40 percent if
2 in college and by 55 percent if 3;
Consensus approach: Same as IM.
One-time income adjustment;
Institutional methodology: Not included.[C];
Consensus approach: Excluded income that was not received on an annual
basis, such as unemployment income or capital gains.
Family debt;
Institutional methodology: Not included;
Consensus approach: Made allowance for debt payments on loans incurred
by parents for student's education.
Source: GAO analysis.
Note: The consensus approach is being compared to the base
institutional methodology. Schools may choose to implement other
options available under the institutional methodology when assessing a
student's financial need.
[A] Private elementary and secondary school tuition allowed at the
option of the institution.
[B] As an option schools can adjust living expenses based on geographic
locations.
[C] This is not in the base IM; however, a financial aid officer can
adjust for this on a case-by-case basis, consistent with professional
judgment.
[End of table]
In addition, under the consensus approach schools agreed to a common
calendar for collecting data from families. Members continue to
maintain the ability to exercise professional judgment in assessing a
family's ability to pay when there are unique or extenuating financial
circumstances.
Twenty-five of 28 schools implemented the consensus approach; 3 did
not. While 13 schools implemented all the elements of the consensus
approach, the remaining schools varied in how they implemented the
methodology. As shown in table 4 below, seven schools chose not to use
the consensus approach method for accounting for family loan debt, home
equity, and family and student assets.
Table 4: Number of Schools That Did Not Implement Certain Consensus
Approach Options in School Year 2005-2006:
Options in the consensus approach: Number of siblings in college;
Number of schools that did not implement option[A]: 1.
Options in the consensus approach: One-time income adjustments;
Number of schools that did not implement option[A]: 2.
Options in the consensus approach: Elementary and secondary school
tuition expenses;
Number of schools that did not implement option[A]: 3.
Options in the consensus approach: Medical expenses;
Number of schools that did not implement option[A]: 3.
Options in the consensus approach: Cost of living variances;
Number of schools that did not implement option[A]: 5.
Options in the consensus approach: Divorced and separated families;
Number of schools that did not implement option[A]: 6.
Options in the consensus approach: Family and student assets;
Number of schools that did not implement option[A]: 7.
Options in the consensus approach: Home equity;
Number of schools that did not implement option[A]: 7.
Options in the consensus approach: Family loan debt;
Number of schools that did not implement option[A]: 7.
Source: GAO analysis of schools' survey responses.
[A] A total of 25 member schools used part or all of the consensus
approach.
[End of table]
The 25 schools that implemented the consensus approach did so between
2002 and 2005. Member schools reported that they preferred to use the
consensus approach as opposed to other available need analysis
methodologies because it was more consistent and fairer than
alternative methodologies. Moreover, according to institution
officials, they believed the new methodology had not reduced price
competition and had resulted in the average student receiving more
financial aid. In some cases, if using the consensus approach lowered a
student's EFC, the institution would then allocate more money for
financial aid than it would have if it had used a different need
analysis methodology. For some schools the consensus approach was not
that different from the methodology their institution already had in
place, but other schools said that fully implementing the consensus
approach cost their school more money. Among schools that partially
implemented the consensus approach, many explained they did not fully
implement the new methodology because it would have been too costly.
As the Cost of Attendance at Schools Using the Exemption Rose, the
Amount of Institutional Grant Aid They Provided to Students Increased
at a Slower Rate:
The cost to attend the schools participating under the exemption rose
over the past 5 years by over 10 percent while cost increases at all
other private schools rose at about half that rate. At the same time,
the percentage of students receiving institutional aid increased and
institutions increased the amount of such aid they provided students,
although at a slower rate than cost increases.
Cost of Attendance Increased at Schools Using the Exemption
Corresponding to Increases at Other Private Schools:
During the past 5 years, the cost of attendance--tuition, fees, room,
and board--at schools using the exemption increased by approximately 13
percent from $38,319 in school year 2000-2001 to $43,164 in school year
2004-2005, a faster rate than other schools.[Footnote 11] For example,
at other private 4-year schools there was a 7 percent increase in these
costs, from $25, 204 to $27, 071.[Footnote 12] Additionally, as figure
2 illustrates, among a set of schools that were comparable to the
schools using the exemption, costs increased by 9 percent from $40,238
to $43,939 over that same time period.[Footnote 13]
Figure 2: Average Tuition, Fees, and Room and Board at Schools Using
the Antitrust Exemption Compared to All Other Private 4-Year Not-For-
Profit Schools and Comparable Schools, School Years 2000 to 2005:
[See PDF for image]
Source: GAO analysis of IPEDS data.
Note: Comparable schools include the seven schools selected as control
schools for our econometric analysis.
[End of figure]
Percentage of Students Receiving Institutional Grant Aid and the Amount
Schools Provided Them Increased:
Over the same time period, the percentage of students who received any
form of institutional grant aid at schools using the exemption
increased by 3 percentage points, from 37 to 40 percent, as illustrated
by figure 3.
Figure 3: Percentage of Students at Schools Using the Antitrust
Exemption Receiving Various Types of Institutional Grant Aid from 2000
to 2006:
[See PDF for image]
Source: GAO analysis of institutional data.
Note: Data collected from 26 of the 28 schools using the antitrust
exemption.
[End of figure]
Among students receiving institutional grant aid, the percentage of
students receiving need-based grant aid increased from 34 to 36 percent
from 2000 to 2006. The percentage of students receiving non-need-based
grant aid also increased slightly, from 2 to 4 percent. Non-need-based
aid is awarded based on a student's academic or athletic achievement
and includes fellowships, stipends, or scholarships. The majority of
schools using the exemption did not offer any non-need-based
institutional grant aid in school year 2005-2006. However, in 2005-2006
some schools did, allocating non-need-based grant aid to between 16 to
54 percent of their students.
As the cost of attendance and percentage of students receiving
institutional aid rose, participating institutions increased the amount
of such aid they provided students, although the percentage increases
in aid were smaller. As shown in figure 4, the average need-based grant
aid award across the schools using the exemption increased from $18,925
to $20,059, or 6 percent. The average amount of non-need-based grant
aid awards dropped slightly from $12,760 in 2000-01 to $12,520 in 2005-
06, or 2 percent. Overall, the average total institutional grant aid
awarded to students, which included both need and non-need-based aid,
increased from $18,675 in 2000-01 to $19,901 in 2005-06, or 7 percent.
Figure 4: Average Amount of Various Institutional Grant Aid Awards at
Schools Using the Antitrust Exemption from 2000 to 2006:
[See PDF for image]
Source: GAO analysis of institutional data.
Note: Data collected from 26 of the 28 schools using the exemption.
[End of figure]
Students Accepted to Both Schools Using the Exemption and Comparable
Schools Had No Appreciable Difference in the Amount They Would Be
Expected to Contribute Towards College:
There was virtually no difference in the amounts students and their
families were expected to pay between schools using the exemption and
similar schools not using the exemption. Average EFC was $27,166 for
students accepted at schools using the exemption, and $27,395 for those
accepted at comparable schools not using the exemption in school year
2005-2006. Moreover, the variation in the EFC for a student who was
accepted to several schools using the exemption was similar to the
variation in EFC that same student received from schools not using the
exemption. The variation in EFCs for these students was about $6,000 at
both sets of schools.[Footnote 14] Because the number of such students
was small, we also analyzed variation in EFCs for students who were
accepted only at schools using the exemption and compared it to the
variation for students who were only accepted at comparable schools not
using the exemption.[Footnote 15] We found slightly greater variation
among EFCs for students who were accepted at schools using the
exemption; however, because we could not control for student
characteristics, factors external to the exemption could explain this
result, such as differences in a family's income or assets.
Although officials from schools using the exemption expected that
students accepted at several of those schools would experience less
variation in the amounts they were expected to pay, none of our
analyses confirmed this. The lack of consistency in EFCs among schools
using the exemption may be explained by the varied implementation of
the consensus approach. As previously mentioned, not all schools using
the consensus approach chose to adopt all the elements of the
methodology. For example, seven schools chose not to use the consensus
approach to home equity, which uses a percentage of the home equity in
calculating the EFC. Using another method for assessing a family's home
equity could significantly affect a student's EFC. For instance, we
estimated that a family residing in Maryland with an income of $120,000
and $350,000 in home equity would have an EFC of $58,243 if a school
chose not to implement the home equity option in the consensus
approach. Under the consensus approach, the amount of home equity
included in asset calculations would be capped and only $38,000 of the
home's equity would be included in the calculation of EFC. The same
family would then have an EFC of $42,449 if the school chose to
implement the option.
Implementation of a Common Methodology Has Not Significantly Affected
Affordability or Enrollment at Schools Using the Exemption:
Based on our econometric analysis, schools' use of the consensus
approach did not have a significant impact on affordability, nor did it
cause significant changes in the likelihood of student enrollment at
schools using the consensus approach compared to schools that were not
using the consensus approach.[Footnote 16] As shown in table 5, while
we found that the consensus approach resulted in higher need-based
grant aid awards for some student groups (middle income, Asian
students, and Hispanic students) compared to similar students at
schools that were not using the consensus approach, this increase was
likely offset by decreases in non-need-based grant aid, such as
academic or athletic scholarships.[Footnote 17] Thus, total grant aid
awarded was not affected by the consensus approach because the increase
in need-based aid was likely offset by decreases in non-need-based
grant aid.[Footnote 18]
Table 5: Estimated Changes in Amount Paid, Financial Aid, and
Enrollment at Schools Using the Consensus Approach Compared to Schools
Not Using the Exemption:
Student group: All students;
Estimated changes of using the consensus approach on: Amount students
paid: $3,021;
Estimated changes of using the consensus approach on: Total grant aid: -
$749;
Estimated changes of using the consensus approach on: Need-based total
grant aid: $6,125[B]; [$239, $12,011];
Estimated changes of using the consensus approach on: Total aid (grant,
loans, work-study): -$2,886;
Estimated changes of using the consensus approach on: Probability of
enrollment: 38%.
Student group: Financial-aid applicants;
Estimated changes of using the consensus approach on: Amount students
paid: 2,177;
Estimated changes of using the consensus approach on: Total grant aid:
n/a;
Estimated changes of using the consensus approach on: Need-based total
grant aid: n/a;
Estimated changes of using the consensus approach on: Total aid (grant,
loans, work-study): n/a;
Estimated changes of using the consensus approach on: Probability of
enrollment: 22.
Student group: Low-income;
Estimated changes of using the consensus approach on: Amount students
paid: -4,061;
Estimated changes of using the consensus approach on: Total grant aid:
3,688;
Estimated changes of using the consensus approach on: Need-based total
grant aid: 1,956;
Estimated changes of using the consensus approach on: Total aid (grant,
loans, work-study): 12,121[B]; [1,837, 22,404];
Estimated changes of using the consensus approach on: Probability of
enrollment: 59.
Student group: Lower-middle income;
Estimated changes of using the consensus approach on: Amount students
paid: 8,089 [C];
Estimated changes of using the consensus approach on: Total grant aid: -
3,671;
Estimated changes of using the consensus approach on: Need-based total
grant aid: 6,556;
Estimated changes of using the consensus approach on: Total aid (grant,
loans, work-study): -7,776;
Estimated changes of using the consensus approach on: Probability of
enrollment: 95.
Student group: Middle income;
Estimated changes of using the consensus approach on: Amount students
paid: 2,320;
Estimated changes of using the consensus approach on: Total grant aid:
1,618;
Estimated changes of using the consensus approach on: Need-based total
grant aid: 20,221[A]; [6,718, 33,724];
Estimated changes of using the consensus approach on: Total aid (grant,
loans, work-study): 1,178;
Estimated changes of using the consensus approach on: Probability of
enrollment: 26.
Student group: Upper-middle income;
Estimated changes of using the consensus approach on: Amount students
paid: -1,048;
Estimated changes of using the consensus approach on: Total grant aid: -
973;
Estimated changes of using the consensus approach on: Need-based total
grant aid: 2,769;
Estimated changes of using the consensus approach on: Total aid (grant,
loans, work-study): -3,054;
Estimated changes of using the consensus approach on: Probability of
enrollment: 18.
Student group: High income;
Estimated changes of using the consensus approach on: Amount students
paid: 3,699;
Estimated changes of using the consensus approach on: Total grant aid: -
714;
Estimated changes of using the consensus approach on: Need-based total
grant aid: 4,687[C];
Estimated changes of using the consensus approach on: Total aid (grant,
loans, work-study): -3,856;
Estimated changes of using the consensus approach on: Probability of
enrollment: 31.
Student group: Asian students;
Estimated changes of using the consensus approach on: Amount students
paid: -376;
Estimated changes of using the consensus approach on: Total grant aid:
5,726;
Estimated changes of using the consensus approach on: Need-based total
grant aid: 14,628[A]; [5,051, 24,206];
Estimated changes of using the consensus approach on: Total aid (grant,
loans, work-study): 3,694;
Estimated changes of using the consensus approach on: Probability of
enrollment: 1.
Student group: Black students;
Estimated changes of using the consensus approach on: Amount students
paid: 4,468;
Estimated changes of using the consensus approach on: Total grant aid: -
1,227;
Estimated changes of using the consensus approach on: Need-based total
grant aid: 4,332;
Estimated changes of using the consensus approach on: Total aid (grant,
loans, work-study): -6,542;
Estimated changes of using the consensus approach on: Probability of
enrollment: -26.
Student group: Hispanic students;
Estimated changes of using the consensus approach on: Amount students
paid: 1,168;
Estimated changes of using the consensus approach on: Total grant aid:
1,520;
Estimated changes of using the consensus approach on: Need-based total
grant aid: 9,532[B]; [1,006, 18,059];
Estimated changes of using the consensus approach on: Total aid (grant,
loans, work-study): 3,648;
Estimated changes of using the consensus approach on: Probability of
enrollment: 108.
Student group: White students;
Estimated changes of using the consensus approach on: Amount students
paid: 2,588;
Estimated changes of using the consensus approach on: Total grant aid: -
491;
Estimated changes of using the consensus approach on: Need-based total
grant aid: 6,017[B]; [178, 11,856];
Estimated changes of using the consensus approach on: Total aid (grant,
loans, work-study): -2,879;
Estimated changes of using the consensus approach on: Probability of
enrollment: 19.
Source: GAO analysis (see table 16 in app. II).
[A] Result is statistically significant at the 1 percent level or
lower.
[B] Result is statistically significant at the 5 percent level or
lower.
[C] Result is statistically significant at the 10 percent level or
lower.
Notes: The estimates in brackets are the confidence levels of the
estimates that are significant at the 5 percent or lower level.
n/a means not applicable because of data limitations.
All the monetary values are in 2005 dollars.
Amount students paid is defined as tuition, room, board, fees, and
other expenses minus grant aid.
Total grant aid includes both need-and non-need-based aid from federal,
state, institutional and other sources.
Total aid includes grants, loans, and work-study aid from federal,
state, institutional, and other sources.
The effect of the consensus approach on need-based institutional grant
aid was $6,020, significant at the 5 percent level, with confidence
interval between $512 and $11,528.
The value of the effect of the consensus approach on institutional
grant aid was $1,331, but not statistically significant.
[End of table]
A different effect was found when low-income students at schools using
the consensus approach were compared to their counterparts at schools
not using the consensus approach. As shown in table 5, low income
students at schools using the consensus approach received, on average,
a significantly higher amount of total aid--about $12,121, which
includes both grants and loans. However, the amount of grant aid that
these students received did not significantly change, suggesting that
that they likely received more aid in the form of loans, which would
need to be repaid, or work-study. Our analysis of the effects of the
consensus approach on various racial groups showed no effect on
affordability for these groups compared to their counterparts at
schools not using the consensus approach. While Asian, white, and
Hispanic students received more need-based grant aid compared to their
counterparts at schools not using the consensus approach, their overall
grant aid awards did not change.
Finally, as shown in table 5, there were no statistically significant
effects of the consensus approach on student enrollment compared to the
enrollment of students at schools not using the consensus approach. In
particular, the consensus approach did not significantly increase the
likelihood of enrollment of low-income or minority students or any
student group.
Our econometric analysis has some limitations that could have affected
our findings.[Footnote 19] For example, we could not include all the
schools using the consensus approach in our analysis because there were
no data available for some of them. However, there were enough
similarities (in terms of "best college" ranking, endowment, tuition
and fees, and percentage of tenured faculty) between the included and
excluded participating schools that allowed for a meaningful analysis.
(See table 6 for a list of schools included in our analysis).
Table 6: Schools Included in Analysis of Effects of Exemption:
Schools using the consensus approach:
Cornell University
Duke University
Georgetown University
University of Notre Dame
Vanderbilt University
Wake Forest University
Yale University;
Comparable schools not using the consensus approach:
Brandeis University
Bryn Mawr College
New York University
Princeton University
Tulane University
University of Rochester
Washington University at St. Louis.
Source: GAO analysis.
[End of table]
Moreover, the data for our post-consensus approach period was collected
in 2003-2004--the first or second year that some schools were using the
consensus approach. Because we have data for only one year after
implementation, it is possible that some eventual effects of the
consensus approach may not be captured. The effects of using the
consensus approach could be gradual, rather than immediate, and
therefore may not be captured until later years.
Concluding Observations:
By providing an exemption to antitrust laws enabling schools to
collaborate on financial aid policies, the Congress hoped that schools
would better target aid, making college more affordable for low income
and other underrepresented groups. The exemption has not yet yielded
these outcomes. Nor did our analysis find an increase in prices that
some feared would result from increased collaboration among schools.
Initial implementation of the approach has been varied; some schools
have not fully implemented the need analysis methodology, and many
schools are still in the initial years of implementation. As is often
the case with new approaches, it may be too soon to fully assess the
outcomes from this collaboration.
Agency Comments:
We provided the group of schools using the antitrust exemption, the
Secretary of Education, and the Attorney General with a copy of our
draft report for review and comments. The group of schools using the
exemption provided written comments, which appear in appendix IV. In
general, the group stated that our study was a careful and objective
report, but raised some concerns about the data used in our econometric
analysis and the report's tone and premise. Specifically, they raised
concerns about the selection of treatment and control schools for our
econometric analysis. As we noted in the report, we selected schools
for selection in treatment and control groups based, in part, on the
availability of student-level data in the NPSAS. Some schools that used
the consensus approach were not included because there were no data
available for them. However, we believe there were enough similarities
between the included and excluded schools to allow for a meaningful
analysis. The group also stated that a number of conclusions were based
on a very small number of observations. In appendix II, we acknowledge
the small sample size of the data could make the estimates less
precise, especially for some of the subgroups of students we
considered. However, we performed checks to ensure that our estimates
were reliable and believe that we can draw conclusions from our
analysis. With respect to the tone and premise of the report, the group
raised concerns about using low income students as "a yardstick for
judging the success of the Consensus Approach." When passing the
exemption, Congress hoped that it would further the government's goal
of promoting equal access to educational opportunities for students.
Need-based grant aid is one way to make college more affordable for the
neediest students to help them access a post-secondary education. The
group also highlighted several positive outcomes from their
collaboration, including a more transparent aid system and more
engagement by college presidents in aid-related discussions, topics
which our study was not designed to address. The group provided
technical comments, which we incorporated where appropriate. Education
reviewed the report and did not have any comments. The Department of
Justice provided technical comments, which we incorporated where
appropriate.
We are sending copies of this report to the Secretary of Education,
Attorney General, appropriate congressional committees, and other
interested parties. In addition, the report will be available at no
charge on GAO's Web site at [Hyperlink, http://www.gao.gov].
If you or your staff have any questions please call me on (202) 512-
7215. Contact points for our Offices of Congressional Relations and
Public Affairs may be found on the last page of this report. Other
contacts and staff acknowledgments are listed in appendix VI.
Signed by:
Cornelia M. Ashby, Director:
Education, Workforce and Income Security Issues:
List of Congressional Committees:
The Honorable Arlen Specter:
Chairman:
The Honorable Patrick J. Leahy:
Ranking Minority Member:
Committee on the Judiciary:
United States Senate:
The Honorable F. James Sensenbrenner, Jr.
Chairman:
The Honorable John Conyers, Jr.
Ranking Minority Member:
Committee on the Judiciary:
House of Representatives:
[End of section]
Appendix I: Statistical Analysis of Expected Family Contributions at
Schools Using the Exemption and Comparable Schools:
We compared variation in expected family contributions (EFCs) between
students who were admitted to both schools using the exemption and
comparable schools that did not. We collected data on student EFCs from
27 of the 28 schools using the exemption and 55 schools that had
similar selectivity and rankings as schools using the exemption. The
data included the student's EFC calculated by the schools as of April
1, 2006, based on their need analysis methodology. We determined that
these data would most likely reflect the school's first EFC
determination for a student and thus would be best for comparison
purposes. We then matched students across both sets of schools to
identify students accepted to more than one school (which we call cross-
admits).
Our sample consisted of data for the following three types of cross-
admit students:
1. Students accepted to several schools using the exemption and several
schools that were not (type 1 students);
2. Students accepted to only schools using the exemption (type 2
students); and:
3. Students accepted to only schools not using the exemption (type 3
students).
Data from the type 1 sample provided the most suitable data for our
analysis because it controlled for student characteristics. However,
because this sample was relatively small, we used the other samples to
supplement the analysis.
Once the cross-admits were identified, the EFCs for each student were
used to evaluate the mean and median as measures of location and the
standard deviation and range as measures of variation. Given the
potential scale factor, the variation measures were standardized. The
standard deviation was standardized by dividing it by the mean, and the
range was standardized by dividing it by the median. The two resulting
variation measures were the coefficient of variation (V1) and its
robust counterpart (V2), respectively.
These two measures of variation were estimated for each and every
student. The estimates were grouped for both sets of schools. We
labeled schools using the exemption as "568 schools" and comparable
schools that were not as "non-568 schools."
Table 7 reports various estimates averaged over students in each group.
The table generally shows similar group averages for the mean, standard
deviation, median, and range that were used to compute V1 and V2. The
values reported are the averages for all the students in each group.
There are fewer observations for the 568 schools than for the non-568
school, except for type 1 students where the number of observations
were equal because the students were in both groups of colleges. In
addition, we imposed the following three conditions:
* First, for the coefficient of variation V1, we excluded all
observations where the standard deviations were zero. The zero standard
deviations are excluded because some of the non-568 schools that use
only the federal methodology to calculate EFCs report the same EFCs for
a student and are likely to bias the results. None of the observations
with zero standard deviations that we excluded involved a 568 school.
* Second, for the coefficient of variation V2, we excluded all
observations where the medians were zero because we could not construct
this measure that was obtained by dividing the range by the median.
* And, third, for the coefficient of variation V2, we excluded
observations where the standardized variation exceeded 3 based on the
observed distributions of the data.
The test results were similar when none of those conditions were
imposed.
Table 7: Summary Statistics of Expected Family Contributions:
Students: Statistics: Standard deviation;
Schools using the exemption (568 schools): Type 1 students: $6,188;
Schools using the exemption (568 schools): All students: $6,447;
Comparable schools (Non-568 schools): Type 1 students: $6,190;
Comparable schools (Non-568 schools): All students: $7,035.
Students: Statistics: Mean;
Schools using the exemption (568 schools): Type 1 students: $27,166;
[$22,576, $31,757];
Schools using the exemption (568 schools): All students: $31,640;
[$30,380, $32,900];
Comparable schools (Non-568 schools): Type 1 students: $27,395;
[$22,293, $32,497];
Comparable schools (Non-568 schools): All students: $28,747; [$27,924,
$29,571].
Students: Statistic: Coefficient of variation 1 (V1);
Schools using the exemption (568 schools): Type 1 students: 0.27;
Schools using the exemption (568 schools): All students: 0.24;
Comparable schools (Non-568 schools): Type 1 students: 0.36;
Comparable schools (Non-568 schools): All students: 0.35.
Students: Statistic: Range;
Schools using the exemption (568 schools): Type 1 students: $12,200;
Schools using the exemption (568 schools): All students: $12,886;
Comparable schools (Non-568 schools): Type 1 students: $9,671;
Comparable schools (Non-568 schools): All students: $8,813.
Students: Statistic: Median;
Schools using the exemption (568 schools): Type 1 students: $30,374;
[$25,380, $35,367];
Schools using the exemption (568 schools): All students: $31,677;
[$30,394, $32,961];
Comparable schools (Non-568 schools): Type 1 students: $29,225;
[$23,858, $34,593];
Comparable schools (Non-568 schools): All students: $31,075; [$30,314,
$31,836].
Students: Statistic: Coefficient of variation 2 (V2);
Schools using the exemption (568 schools): Type 1 students: 0.47;
Schools using the exemption (568 schools): All students: 0.49;
Comparable schools (Non-568 schools): Type 1 students: 0.52;
Comparable schools (Non-568 schools): All students: 0.37.
Students: Statistic: Number of students;
Schools using the exemption (568 schools): Type 1 students: N1=79;
Schools using the exemption (568 schools): All students: N1=1,158;
Comparable schools (Non-568 schools): Type 1 students: N1=79;
Comparable schools (Non-568 schools): All students: N1=2,866.
Schools using the exemption (568 schools): Type 1 students: N2=76;
Schools using the exemption (568 schools): All students: All students:
N2=1,150; N2=1,150:
Comparable schools (Non-568 schools): Type 1 students: Type 1 students:
N2=76;
Comparable schools (Non-568 schools): All students: All students:
N2=3,653.
Source: GAO analysis.
Notes: Coefficient of variation 1 (V1) equals standard deviation
divided by mean.
Coefficient of variation 2 (V2) equals range divided by median.
Type 1 consists of students with multiple offers from 568 colleges as
well as offers from non-568 colleges. For the 568 colleges, all
students consist of type 1 and type 2--students with multiple offers
from only 568 colleges. And for the non568 colleges, all students
consist of type 1 and type 3--students with multiple offers from only
non-568 colleges.
The values in brackets are the 95 percent lower and upper bounds
(confidence intervals).
N1 is the sample size for coefficient of variation 1 (V1) and N2 is
sample size for coefficient of variation 2 (V2).
[End of table]
Denoting the estimates of V1 and V2 for the two groups by V1(568) and
V1(non568), and V2(568) and V2(non568), the empirical distribution of
V1(568) was then compared with the empirical distribution of V1(non568)
to examine whether V1(568) and V1(non568) had identical distributions
(that is EFCs for 568 schools were similar in variations to those for
non-568 schools). A similar comparison was made using the robust
measures V2(568), and V2(non568).[Footnote 20] To more closely examine
the difference between the variations in EFCs of cross-admit students
for 568 and non- 568 schools, we performed the Kolmogorov-Smirnov test.
The test examines whether the distributions of the variation measures
V1(568) and V1(non568) were the same. The same analysis was done for
the V2 measures. The test was reported for both samples, consisting of
type 1 students and all students. The results reported in table 8
suggest that there was no difference in EFC variations across the two
groups, using type 1 students. The results using all students, however,
are inconclusive for the V1 estimate, but suggest that non-568 schools
have smaller EFC variation for the V2 estimate. The results based on
the type 1 sample are more useful as a stand-alone descriptive finding,
because this sample controls for student characteristics. The finding
based on the combined data requires further analysis to control for
student characteristics that we were unable to perform due to data
limitations.
Table 8: Tests of Variations in Expected Family Contributions:
Variable: Coefficient of variation 1 (V1);
Student Data: Type 1 N1=79 N2=79;
Alternative hypothesis: Non-568 EFCs are smaller; Non-568 EFCs are
larger;
Test-statistic, D: 0.1013; -0.1519;
p-value: 0.445; 0.162;
Conclusion: EFCs are similar; EFCs are similar. Overall--EFCs are
similar.
Variable: Coefficient of variation 2 (V2);
Student Data: Type 1 N1=76 N2=76;
Alternative hypothesis: Non-568 EFCs are smaller; Non-568 EFCs are
larger;
Test-statistic, D: 0.1447; -0.1053;
p-value: 0.203; 0.431;
Conclusion: EFCs are similar; EFCs are similar. Overall--EFCs are
similar.
Variable: Coefficient of variation 1 (V1);
Student Data: All N1=1,158 N2=2,866;
Alternative hypothesis: Non-568 EFCs are smaller. Non-568 EFCs are
larger;
Test-statistic, D: 0.1724. -0.1788;
p-value: 0.000. 0.000;
Conclusion: Non-568 EFCs are smaller; Non-568 EFCs are larger. Overall--
Inconclusive.
Variable: Coefficient of variation 2 (V2);
Student Data: All N1=1,150 N2=3,653;
Alternative hypothesis: Non-568 EFCs are smaller. Non-568 EFCs are
larger;
Test-statistic, D: 0.3970. -0.0399;
p-value: 0.000. 0.061;
Conclusion: Non-568 EFCs are smaller; EFCs are similar. Overall--Non-
568 EFCs are smaller.
Source: GAO analysis.
Notes: Coefficient of variation 1 (V1) equals standard deviation
divided by mean.
Coefficient of variation 2 (V2) equals range divided by median.
All means students with multiple offers from 568 schools as well as
offers from non-568 schools (type 1), students with multiple offers
from only 568 schools (type 2), and students with multiple offers from
only non-568 schools (type 3).
The p-values are for the Kolmogorov-Smirnov tests of equality of
distribution functions. All tests are interpreted using the 5 percent
or lower level of significance.
N1 is the sample size for coefficient of variation 1 (V1) and N2 is
sample size for coefficient of variation 2 (V2).
[End of table]
[End of section]
Appendix II: Econometric Analysis of Effects of the Higher Education
Antitrust Exemption on College Affordability and Enrollment:
To estimate the effects of schools' implementation of the consensus
approach to need analysis on affordability (measured by price) and
enrollment of freshmen students, we developed econometric models. This
appendix provides information on theories of the exemption effects on
student financial aid, the data sources for our analyses and selection
of control schools, specifications of econometric models and estimation
methodology, our econometric results, and limitations of our analysis.
Theories of the Effects of the Consensus Approach on Financial Aid:
Two theories exist about the effects the consensus approach on student
financial aid. It is important to note that the award of grant aid
represents a discount from the nominal "list price", which lowers the
price students actually pay for college. So, any decision to limit
grant aid would be an agreement to limit discounts to the list price,
and thus may raise the price some students would pay. It is also
important to note that schools admit only a limited number of students.
One of the theories suggests that allowing schools a limited degree of
collaboration could reduce the variation in financial need
determination for an individual student and reduce price competition
among colleges vying for the same students. While the reduced
competition would imply lower financial aid (hence higher prices) for
some students, schools could thus devote more financial aid resources
to providing access to other students, especially disadvantaged
students. This "social benefit theory" assumes that under these
conditions disadvantaged students would receive more grant aid and as a
result, pay less for school. Also, an implicit assumption of this
theory is that the exemption would essentially result in redistribution
of financial aid without necessarily changing the amount of financial
aid resources available. Moreover, because costs to students and their
families would change for some students, enrollment of such students
would be affected.
An opposing theory is that the exemption will allow schools to
coordinate on prices and reduce competition. This "anti-competitive
theory" essentially views coordination by the group as restraining
competition. Specifically, under this theory, allowing an exemption
would result in less grant aid and higher prices on average, especially
for students that schools competed over by offering discounts on the
list price. As a result, the amount of financial aid available to some
students would likely decrease. If prices are higher on average, it
could cause a decrease in enrollment, particularly of disadvantaged
students since they would be less able to afford the higher
prices.[Footnote 21] Our analyses allowed us to test these two theories
with the data available.
Sources of Data for the Model:
To construct our model, we used data from:
* National Postsecondary Student Aid Study (NPSAS): These data,
available at the student-level, served as the primary source for our
study because we were interested in student outcomes of the exemption.
Data were published every 4 years during the period relevant to our
study; hence, we have data for academic years 1995-1996, 1999-2000, and
2003-2004. The data contained student-level information for all
freshmen enrollees in the database, including enrollment in school,
cost of attendance, financial aid, Scholastic Aptitude Test (SAT)
scores, household income, and race. The number of freshmen in the
database for our study was 1,626 in 1995-1996, 272 in 1999-2000, and
842 in 2003-2004.
* Integrated Postsecondary Education Data System (IPEDS): These data,
available at the school level, included tuition and fees, faculty
characteristics, and student enrollment for 1995-1996 and 2003-2004,
there were no data published for 1999-2000. However, some of the data
for 1999-2000 were reported in the subsequent publications. We were
able to construct some data for 1999-2000 through linear interpolation
of the data for 1998-1999 and 2000-2001 or using the data for either
year depending on availability; we believed this was reasonable because
data for these institutions did not vary much over time.[Footnote 22]
* National Association of College and University Business Officers
(NACUBO): This source provided data on school endowment from 1992
through 2004.[Footnote 23]
* GAO Survey: The survey collected data on the activities of the
schools using the higher education antitrust exemption, including when
schools implemented the consensus approach methodology.
Selection of Control Schools:
Determining the effects of the exemption required both a treatment
group (schools using the exemption) and a control group (a comparable
set of schools that did not use the exemption). To find a comparable
set of schools we used data on school rankings based on their
selectivity from years 1994 to 2004 from the U.S. News and World Report
(USNWR). We selected control schools similar to schools using the
antitrust exemption that had comparable student selectivity and quality
of education using the "best schools" rankings information in the
USNWR.[Footnote 24] The combined control and treatment schools were
matched to school-level data from IPEDS, and student-level data from
NPSAS. We selected the control schools based on their ranks in the
years prior to the implementation of the consensus approach--1995-1996
and 1999-2000--and after the implementation of the consensus approach-
-2003-2004. The USNWR published its "best schools" rankings annually in
August or September. Thus, the 2004 publication reflected the
selectivity of the schools during 2003-2004. However, because
publications in prior years--2002 and 2003--provided relevant
information to students who enrolled in 2003-2004, we considered the
rankings published from 2002 through 2004 as important input into
decisions made by students and the schools for 2003-2004. Similarly,
the publications from 1994 through 1996 were used to determine the
selectivity of the schools in 1995-1996, and the publications from 1998
to 2000 were used to determine school selectivity for 1999-2000.
The USNWR published separate rankings for liberal arts schools and
national universities. The schools using or affiliated with the
exemption consisted of 28 current members, two former members, and six
observers.[Footnote 25] These 36 schools comprised the treatment
schools used initially to select the comparable control schools. All 36
treatment schools were private; 13 were liberal arts schools and 23
were national universities.[Footnote 26] To ensure there were enough
control schools for the treatment schools, we initially selected all
the schools ranked in tier 1 (and tier 2 when available) in the USNWR
rankings for each of the two types of institutions--liberal arts
schools and national universities.[Footnote 27] This resulted in 250
schools, including all 36 treatment schools, for nine selected years
(1994 to 1996, 1998 to 2000, and 2002 to 2004). All the treatment
schools were ranked in each of the nine years (except for one school
that was not ranked in 2002). The initial list of 250 schools was
refined further to ensure a proper match in selectivity between the
treatments and controls.
Although we were interested in obtaining an adequate number of control
schools to match the treatment schools, we refined the selection
process to ensure they were comparable using the following conditions.
First, we limited the selection of all the schools (controls and
treatments) to those that were ranked in tier 1. This reduced the
sample of schools from 250 to 106 schools, comprising all 36 treatment
schools and 70 control schools. Second, the list of 106 schools was
used to match school-level data from the IPEDS in each of the three
academic years.[Footnote 28] Third, these data were then matched with
the IPEDS data for each of the three academic years to student-level
data from NPSAS. From the NPSAS, we selected data for cohorts who
entered their freshmen year in each of the three academic
years.[Footnote 29] Fourth, since we used a difference-in-difference
methodology for the analysis, we wanted data for each school in at
least two of the three academic years--one in the pre-treatment and one
in the post-treatment period. We therefore initially constructed four
samples of schools, depending on whether there were matches between all
three academic years, or between any two of the three academic years.
This resulted in 30 schools with data in all three academic years 1995-
1996, 1999-2000, and 2003-2004 (referred to as sample 1). There were 34
schools with data in 1995-1996 and 2003-2004 (sample 2); 35 schools
with data in 1999-2000 and 2003-2004 (sample 3); and 37 schools matched
between 1995-1996 and 1999-2000 (sample 4).[Footnote 30] Finally, we
limited the selection to private schools because all of the treatment
schools are private. We did this because the governance of private
schools generally differed from state-controlled public schools and
these differences were likely to affect affordability and enrollment at
a school.
Determination of the Appropriate Time Periods for Assessing Effects and
Classification of Schools that Only Attended the Meetings:
We also determined the academic year(s) data that would be used to
represent the period before and the period after the implementation of
the consensus approach. Since we had data for only1995-1996, 1999-2000
and 2003-2004, and given that the consensus approach was implemented in
2003-2004 (or in the prior year by some schools) we selected 1995-1996
as the pre-consensus approach period and 2003-2004 as the post-
consensus approach period. Although the 1999-2000 data were relatively
current for the pre-consensus approach period, it is possible that the
1999-2000 data may offer neither strong pre-nor post-consensus approach
information since the period was very close to the formation of the 568
President's Group in 1998. Furthermore, the institutional methodology,
which is a foundation for the consensus approach and used by some of
the control schools in 2003-2004, was revised in 1999. We therefore
investigated whether it was appropriate to include 1999-2000 in the pre-
consensus approach period or in the post-consensus approach period. We
also investigated in which group (control or treatment) the schools
that only attended the 568 President's Group meetings, but had not
become members of the group or implemented the consensus approach,
belonged.
Using the Chow test for pooling data, we determined that 1999-2000
should be excluded from the pre-consensus approach period as well as
from the post-consensus approach period. We also determined that
schools that only attended the 568 President's Group meetings could not
be regarded as control schools or treatment schools in analyzing the
effects of the consensus approach.[Footnote 31] Therefore, the
treatment schools consisted of the group members that implemented the
consensus approach, and the control schools consisted of the schools
that were not members of the 568 Group and did not attend their
meetings. Based on the analysis above, we used the data in sample 2,
which excluded data collected in 1999-2000, for our baseline model
analysis; the period before the consensus approach is 1995-1996 and the
period after is 2003-2004; the control schools that did not use the
consensus approach (non-CA schools) are Brandeis University, Bryn Mawr
College, New York University, Princeton University, Tulane University,
University of Rochester, and Washington University at St. Louis, and
the treatment schools that used the consensus approach (CA schools) are
Cornell University, Duke University, Georgetown University, University
of Notre Dame, Vanderbilt University, Wake Forest University, and Yale
University. The complete list of the schools is in table 9.
Table 9: Control and Treatment Schools for Analyzing Effects of the
Consensus Approach Implementation:
Academic years: 1995-1996 1999-2000 &; 2003-2004;
Control school (Non- CA): Sample 1:
Brandeis University;
New York University;
Princeton University[B];
Tufts University[A,B];
Tulane University;
University of Rochester;
Washington University at St. Louis;
Treatment school (CA):
Samples 1, 2, or 3:
Boston College[A];
Cornell University[B];
Duke University;
Georgetown University;
Massachusetts Institute of Technology[A,B];
University of Notre Dame;
University of Pennsylvania[A,];
Vanderbilt University;
Wake Forest;
University Yale University[B].
Academic years: 1995-1996 &; 2003-2004;
Control school (Non-CA):
Sample 2--All of Sample 1 Plus:
Bryn Mawr College[B];
Yeshiva University[A].
Academic years: 1999-2000 &; 2003-2004;
Control school (Non-CA):
Sample 3--All of Sample 1 Plus:
Colgate University;
Lehigh University;
Whitman College.
Academic years: 1995-1996 &; 1999-2000; Control school (Non-CA):
Sample 4--All of Sample 1 Plus:
Carnegie Mellon University;
Johns Hopkins University;
Treatment school (CA):
Sample 4--All of Above Plus:
Columbia University[B].
Source: GAO analysis.
[A] Schools were excluded because there were no data for SAT scores for
2003-2004.
[B] Member of the former Overlap group.
[C] Members of the 568 Group that had not implemented the consensus
approach.
[D] Were not members of the 568 Group but attended meetings.
[E] Former member of the 568 Group.
Notes: Schools that Only Attended 568 Group Meetings: Sample 2:
Stanford University[D], University of Southern California[A,D] and
Sample 4: Case Western Reserve University[E]
Member schools that had not implemented the consensus approach: Sample
2: Brown University[B,C], Sample 3: Dartmouth College[B,C].
Other 568-Affiliated Schools: Amherst College[B], Bowdoin College[B,E],
California Institute of Technology[D], Claremont McKenna College,
Davidson College, Emory University, Grinnell College, Harvard
University[B,D], Haverford College, Macalester College[E], Middlebury
College[B], Northwestern University, Pomona College, Rice University,
Swarthmore College, Syracuse University[D], University of Chicago,
Wellesley College[B], Wesleyan University[B], Williams College[B]:
[End of table]
Specifications of Econometric Models and Estimation Methodology:
We developed models for analyzing the effects of the implementation of
the consensus approach (CA) on affordability and enrollment of incoming
freshman using the consensus approach.[Footnote 32] We used a
difference-in-difference approach to identify the effects of
implementation of the consensus approach. This approach controlled for
two potential sources of changes in school practices that were
independent of the consensus approach. First, this approach enabled us
to control for variation in the actions of schools over time that were
independent of the consensus approach. Having control schools that
never implemented the consensus approach allowed us to isolate the
effects of the exemption and permitted us to estimate changes over time
that were independent of the consensus approach implementation. Second,
while we had a control group of schools that did not use the consensus
approach, but were otherwise very similar to treatment schools, it is
possible that schools using the consensus approach differed in ways
that would make them more likely to implement practices that are
different from those of other schools.[Footnote 33] The difference-in-
difference approach controlled for this possibility by including data
on schools using the consensus approach both before and after its
adoption. Controlling then for time effects independent of the
consensus approach as well as practices by these schools before
adoption, the effect of the use of the consensus approach could be
estimated. Compared to the schools that did not use the consensus
approach, we expected that the implementation of the consensus approach
would have a significantly greater impact on the schools using the
consensus approach because its use has potential implications for
affordability and enrollment of students in these schools.
Modeling the Effects of the Consensus Approach Methodology for
Financial Need on Affordability and Enrollment:
The basic tenets of financial need analysis are that parents and
students should contribute to the student's education according to
their ability to pay. The CA schools used the consensus approach for
its need analysis methodology and to determine the expected family
contribution (EFC) for each student based on that methodology.
Conversely, the non-CA schools primarily used a need analysis
methodology called the institutional methodology (IM). The difference
between the cost of attendance (COA) and the EFC determines whether a
student has financial need. If so, the school then develops a financial
aid package of grants, loans, and work study from various sources. The
actual amount that students and families pay depends on how much of the
aid received is grant aid. Therefore, the implementation of the
consensus approach was expected to affect the price paid and the
financial aid received by students, and by implication, their
enrollment into schools.
Dependent variables:
The study examined the effects of the implementation of the consensus
approach on two key variables: affordability (measured by price) and
enrollment of freshman. We also estimated other equations to provide
further insights on affordability--tuition, total grant aid, need-based
grant aid, and total aid. All the dependent variables were measured at
the student level, except tuition. Also, all monetary values were
adjusted for inflation using the consumer price index (CPI) in 2005
prices.[Footnote 34] The dependent variables were defined as follows:
* Price (PRICE(ijt)): Price, in dollars, actually paid by freshman i
who enrolled in school j in an academic year t. The variable was
measured as the cost of attendance less total grant aid. The cost of
attendance consisted of tuition and fees, on-campus room and board,
books and supplies, and other expenses such as transportation. Total
grant aid consisted of institutional and non-institutional grant aid;
it excluded self-help aid (loans and work study).
The other dependent variables that we estimated to help provide more
insights into the results for affordability were:
* Tuition (TUITION(ijt)): The amount of tuition and fees in dollars
charged by school j to freshman i who enrolled in an academic year
t.[Footnote 35]
* Total grant aid (AIDTGRT(ijt)): The amount of total grant aid
received, in dollars, by a freshman i who enrolled in school j in an
academic year t. The counterpart to grant aid was self-help
aid.[Footnote 36]
* Need-based grant aid (AIDNDTGRT(ijt)): The amount of need-based grant
aid received, in dollars, by freshman i who enrolled in school j in an
academic year t. The counterpart to need-based aid was non-need-based
aid, which consisted mainly of merit aid.[Footnote 37]
* Total aid package (AIDTOTAMT(ijt)): The amount of total aid received,
in dollars, by freshman i who enrolled in school j in an academic year
t. The total aid consisted of total grants (from the school, the
various levels of government--federal, state--and other sources) and
self-help (includes loans and work-study).
* Student enrollment (ENRCA(ijt)): An indicator variable for student
enrollment into a CA school (ENRCA(ijt)). It equals one if a freshman i
enrolled in an academic year t in school j that was a school using or
later the consensus approach, and zero otherwise. Thus, at t=0 (1995-
1996), a school was designated as a CA school if it implemented the
consensus approach in period t=1 (2003-2004). Students who enrolled in
a non-CA school were assigned a value of zero. In other words, ENRCA
takes a value of one for every student enrolled in a CA school in any
time period (1995-1996 or 2003-2004), and zero otherwise.
Explanatory variables:
Several variables could potentially affect each of the dependent
variables identified above. The explanatory variables we used were
based on economic reasoning, previous studies, and data
availability.[Footnote 38] All the equations used were in quasi reduced-
form specifications. The key explanatory variable of interest was the
exercise of the exemption through the implementation of the consensus
approach by the 568 Group of schools. We were also interested in the
effects of the implementation of the consensus approach on
affordability and enrollment of disadvantaged students. In order to
isolate the relationships between the consensus approach implementation
and each of the dependent variables, we controlled for the potential
effects of other explanatory variables. The following is a complete
list of all the explanatory variables we used:
* Exemption indicator: EMCA(jt)[Footnote 39]
The exemption was captured by the implementation of the consensus
approach by a school.[Footnote 40] EMCA equals one if school j has
implemented CA by academic year t, where t is 2003-2004 and zero
otherwise.
We used other explanatory variables in our equations, in addition to
the exemption indicator for the implementation of the consensus
approach. These variables included school-level characteristics, school
specific fixed-effects, time specific fixed-effects, and student-level
characteristics.
* School-level characteristics:[Footnote 41]
The school variables or attributes varied across the schools (j) and
over time (t), but did not vary across the students (i). The school
characteristics may capture the quality of the schools, expenditures by
the schools that may compete with financial aid for funding, revenue
sources for financial aid, or the preferences of the students.[Footnote
42] The variables used were:
* ENDOWSTU(jt): The interaction between the 3-year average endowment
per student and the 3-year average percentage rate of return on
endowment per student at school j for an academic year t. The inclusion
of the rate of returns from endowments helped minimize the possibility
that developments in financial markets could bias the results
especially if the average endowment per student differed across the two
groups of schools.
* RANKAVG(jt): The average "best schools" rank of school j for an
academic year t. Although we used this variable to select the control
schools that were comparable in selectivity to the treatment schools
before matching the data to the NPSAS data, this variable was included,
due to data limitations, to control for the possibility that the two
groups of schools used in the sample may differ in selectivity.
* ENROLUG(jt): The 3-year average growth rate (in decimals) of
undergraduate enrollment at school j for an academic year t.
* TENURED(jt): The percentage (in decimals) of total faculty at school
j that was tenured in an academic year t.
* Time specific fixed-effects:
These variables captured differences over time that did not vary across
the schools, such as increases in national income that could increase
affordability of schools. This was an indicator variable for the
academic years (time):
AY1995(t): Equals one for the academic year 1995-1996, and zero
otherwise AY2003(t): Equals one for the academic year 2003-2004, and
zero otherwise.
* Student characteristics:[Footnote 43]
All the student-level variables or attributes generally varied across
students (i), across schools (j), and across time (t). The student
characteristics indicated the preferences of the students for a school
as well as the decisions of the schools regarding the students they
admitted. The variables used were:
* FINAID(ijt): Equals one if a freshman i who enrolled in school j in
an academic year t applied for financial aid, and zero otherwise.
* RACE: Equals one if a freshman i who enrolled in school j in an
academic year t is:
Asian--ASIAN(ijt), and zero otherwise. Black--BLACK(ijt), and zero
otherwise. Hispanic--HISPANIC(ijt), and zero otherwise. White--
WHITE(ijt), and zero otherwise. Foreigner--FOREIGN(ijt), and zero
otherwise. None of the above--OTHER(ijt), and zero otherwise.[Footnote
44]
* INCOME: Equals one for a freshman i who enrolled in school j in an
academic year t has household income in the following quintiles:
INCLO(ijt): Below or equal to the 20th percentile, and zero otherwise.
These were low-income students, and the median income for the group was
$13,731 in 2005 dollars.
INCLOMD(ijt): Above the 20th and below or equal to the 40th percentile,
and zero otherwise. These were lower-middle income students, and the
median income for the group was $40,498 in 2005 dollars.
INCMD(ijt): Above the 40th and below or equal to the 60th percentile,
and zero otherwise. These were middle-income students, and the median
income for the group was $59,739 in 2005 dollars.
INCUPMD(ijt): Above the 60th and below or equal to the 80th percentile,
and zero otherwise. These were upper-middle income students, and the
median income for the group was $88,090 in 2005 dollars.
INCHI(ijt): Above the 80th percentile, and zero otherwise. These were
high-income students, and the median income for the group was $145,912
in 2005 dollars.
Since we included minority students (Asian, black, and Hispanic
students) as well as lower income groups (low income and lower-middle
income students) to measure needy students, the minority variables
likely captured nonincome effects.[Footnote 45]
EFC(ijt): Expected family contribution for a freshman i who enrolled in
school j in an academic year t. Although this variable captured the
income of the students, it also reflected other factors that affect
financial aid, such as the number of siblings in college.[Footnote 46]
SCORESAT(ijt): The combined scholastic aptitude test (SAT) scores for
math and verbal of freshman i who enrolled in school j in an academic
year t.
Tables 10 and 11 show summary statistics for the variables listed above
for treatment and control schools in sample 2 (as listed in table
9).[Footnote 47] In general, the values of the variables were similar
between the two groups of schools.
Table 10: Summary Statistics of Variables Used in Regression Analysis,
1995-1996 and 2003-2004: CA Schools:
Variable: School-level; TUITION;
Mean: $26,245;
Std: $3,557;
Min: $18,910;
Max: $31,152.
Variable: School-level; ENDOWSTU;
Mean: $227,213;
Std: $230,768;
Min: $44,061;
Max: $1,146,129.
Variable: School-level; RANKAVG;
Mean: 16;
Std: 9;
Min: 2;
Max: 27.
Variable: School-level; ENROLUG;
Mean: 2%;
Std: 6%;
Min: -1%;
Max: 21%.
Variable: School-level; TENURED;
Mean: 56%;
Std: 13%;
Min: 25%;
Max: 75%.
Variable: Student-level; Variable: PRICE;
Mean: $30,792;
Std: $11,144;
Min: $1,065;
Max: $52,354.
Variable: Student-level; AIDTGRT;
Mean: $7,133;
Std: $9,866;
Min: $0;
Max: $40,658.
Variable: Student-level; AIDNDTGRT;
Mean: $5,526;
Std: $8,722;
Min: $0;
Max: $35,321.
Variable: Student-level; AIDNONDTGRT;
Mean: $1,607;
Std: $4,360;
Min: $0;
Max: $30,403.
Variable: Student-level; AIDTOTAMT;
Mean: $12,465;
Std: $13,566;
Min: $0;
Max: $43,195.
Variable: Student-level; AIDSELFPLUS;
Mean: $4,794;
Std: $8,155;
Min: $0;
Max: $36,730.
Variable: Student-level; EFC;
Mean: $24,486;
Std: $22,268;
Min: $0;
Max: $115,090.
Variable: Student-level; SCORESAT;
Mean: 1301;
Std: 144;
Min: 790;
Max: 1600.
Variable: Student-level; FINAID;
Mean: 76%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; ASIAN;
Mean: 9%;
Std: n/a;
Min: n/a; Max: n/a.
Variable: Student-level; BLACK;
Mean: 5%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; HISPANIC;
Mean: 7%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; FOREIGN;
Mean: 2%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; OTHER;
Mean: 5%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; WHITE;
Mean: 71%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; INCLO;
Mean: 5%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; INCLOMD;
Mean: 11%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; INCMD;
Mean: 13%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; INCUPMD;
Mean: 17%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; INCHI;
Mean: 54%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Schools;
Cornell University;
Duke University;
Georgetown University,
University of Notre Dame,
Vanderbilt University,
Wake Forest University,
Yale University.
Variable: Number of observations;
Max: 241.
Source: GAO analysis.
Note: All values are (probability) weighted averages, and the monetary
values are in 2005 dollars.
[End of table]
Table 11: Summary Statistics of Variables Used in Regression Analysis,
1995-1996 and 2003-2004: Non-CA Schools:
Variable: School-level; TUITION;
Mean: $27,031;
Std: $2,259;
Min: $24,571;
Max: $31,714.
Variable: School-level; ENDOWSTU;
Mean: $256,147;
Std: $329,513;
Min: $27,909;
Max: $1,504,930.
Variable: School-level; RANKAVG;
Mean: 23;
Std: 12;
Min: 1;
Max: 43.
Variable: School-level; ENROLUG;
Mean: 1%;
Std: 1%;
Min: -2%;
Max: 4%.
Variable: School-level; TENURED;
Mean: 56%;
Std: 12%;
Min: 26%;
Max: 72%.
Variable: Student-level; PRICE;
Mean: $28,815;
Std: $10,305;
Min: $4,569;
Max: $50,726.
Variable: Student-level; AIDTGRT;
Mean: $10,869;
Std: $9,792;
Min: $0;
Max: $32,803.
Variable: Student-level; AIDNDTGRT;
Mean: $8,573;
Std: $9,132;
Min: $0;
Max: $31,487.
Variable: Student-level; AIDNDTGRT;
Mean: $2,296;
Std: $5,419;
Min: $0;
Max: $27,919.
Variable: Student-level; AIDTOTAMT;
Mean: $16,487;
Std: $13,875;
Min: $0;
Max: $48,572.
Variable: Student-level; AIDSELFPLUS;
Mean: $5,293;
Std: $7,686;
Min: $0;
Max: $48,041.
Variable: Student-level; EFC;
Mean: $21,717;
Std: $21,724;
Min: $0;
Max: $105,095.
Variable: Student-level; SCORESAT;
Mean: 1268;
Std: 151;
Min: 740;
Max: 1590.
Variable: Student-level; FINAID;
Mean: 80%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; ASIAN;
Mean: 12%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; BLACK;
Mean: 5%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; HISPANIC;
Mean: 4%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; FOREIGN;
Mean: 3%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; OTHER;
Mean: 3%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; WHITE;
Mean: 74%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; INCLO;
Mean: 10%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; INCLOMD;
Mean: 9%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; INCMD;
Mean: 12%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; INCUPMD;
Mean: 21%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Student-level; INCHI;
Mean: 48%;
Std: n/a;
Min: n/a;
Max: n/a.
Variable: Schools;
Brandeis University,
Bryn Mawr College,
New York University,
Princeton University,
Tulane University,
University of Rochester,
Washington University at St. Louis.
Variable: Number of Observations;
Max: 277.
Source: GAO analysis.
Note: All values are (probability) weighted averages, and the monetary
values are in 2005 dollars.
[End of table]
Comparison of Prices and Financial Aid in CA and Non-CA Schools:
Table 12 shows summary statistics on price and financial aid before and
after the implementation of the consensus approach in 2003-04 at the CA
and non-CA schools in sample 2. Similarly, table 13 shows the summary
statistics by income and racial groups.[Footnote 48] It is important to
note that the summary information on the observed differences before
and after the implementation of the consensus approach for the CA and
non-CA schools are heuristic and do not conclusively determine the
potential effects of the implementation of the consensus approach. It
is also important to note that, for any given variable, it is possible
that there are other factors than implementing the consensus approach
that are responsible for the observed differences, including
differences between CA and non-CA schools' student populations or
differences in the characteristics of the schools, or both. For
instance, the price paid by middle-income students increased more in CA
than in non-CA schools. While this may reflect the effect of consensus
approach, it is possible that other factors are responsible for the
differences. For example, the racial composition of middle-income
students might also be different between the two groups, or there may
be systematic differences in endowment growth between the CA and non-CA
schools that affect financial aid to middle-income students. Thus, to
assess the effect of consensus approach, it is necessary to study the
effects of consensus approach while controlling simultaneously for all
factors that influence price and aid policies.
Table 12: CA and Non-CA Schools: Price and Financial Aid:
All students: Price[A];
CA Schools: 1995-1996: $28,039;
CA Schools: 2003-2004: $35,488;
CA Schools: Percentage difference: 27%;
Non-CA Schools: 1995-1996: $28,068;
Non-CA Schools: 2003-2004: $30,838;
Non-CA Schools: Percentage difference: 10%.
All students: Tuition & fees;
CA Schools: 1995-1996: 24,062;
CA Schools: 2003-2004: 29,967;
CA Schools: Percentage difference: 25;
Non-CA Schools: 1995-1996: 25,770;
Non-CA Schools: 2003-2004: 30,447;
Non-CA Schools: Percentage difference: 18.
All students: Total observations;
CA Schools: 1995-1996: 150;
CA Schools: 2003-2004: 91;
CA Schools: Percentage difference:
Non-CA Schools: 1995-1996: 198;
Non-CA Schools: 2003-2004: 79;
Non-CA Schools: Percentage difference: [Empty].
All students: Financial-Aid Applicants Only: Student Applied for
Financial Aid; Price[A];
CA Schools: 1995-1996: $25,845;
CA Schools: 2003-2004: $32,897;
CA Schools: Percentage difference: 27%;
Non-CA Schools: 1995-1996: $24,960;
Non-CA Schools: 2003-2004: $29,705;
Non-CA Schools: Percentage difference: 19%.
All students: Financial-Aid Applicants Only: Student Applied for
Financial Aid: Total grant aid;
CA Schools: 1995-1996: 9,142;
CA Schools: 2003-2004: 9,775;
CA Schools: Percentage difference: 7;
Non-CA Schools: 1995-1996: 13,391;
Non-CA Schools: 2003-2004: 13,960;
Non-CA Schools: Percentage difference: 4.
All students: Financial-Aid Applicants Only: Student Applied for
Financial Aid: Need-based total grant;
CA Schools: 1995-1996: 7,771;
CA Schools: 2003-2004: 6,439;
CA Schools: Percentage difference: -17;
Non-CA Schools: 1995-1996: 11,863;
Non-CA Schools: 2003-2004: 8,122;
Non-CA Schools: Percentage difference: -32.
All students: Financial-Aid Applicants: Student Applied for Financial
Aid: Institutional grant aid;
CA Schools: 1995-1996: 7,073;
CA Schools: 2003-2004: 6,529;
CA Schools: Percentage difference: -8;
Non-CA Schools: 1995-1996: 11,297;
Non-CA Schools: 2003-2004: 11,116;
Non-CA Schools: Percentage difference: -2.
All students: Financial-Aid Applicants: Student Applied for Financial
Aid: Total aid;
CA Schools: 1995-1996: 16,604;
CA Schools: 2003-2004: 16,046;
CA Schools: Percentage difference: -3;
Non-CA Schools: 1995-1996: 19,827;
Non-CA Schools: 2003-2004: 22,255;
Non-CA Schools: Percentage difference: 12.
All students: Financial-Aid Applicants: Student Applied for Financial
Aid: Loans (incl. PLUS);
CA Schools: 1995-1996: 5,954;
CA Schools: 2003-2004: 4,849;
CA Schools: Percentage difference: -19;
Non-CA Schools: 1995-1996: 5,271;
Non-CA Schools: 2003-2004: 6,669;
Non-CA Schools: Percentage difference: 27.
All students: Financial-Aid Applicants: Student Applied for Financial
Aid: Work study;
CA Schools: 1995-1996: 710;
CA Schools: 2003- 2004: 866;
CA Schools: Percentage difference: 22;
Non-CA Schools: 1995-1996: 986;
Non-CA Schools: 2003-2004: 715;
Non-CA Schools: Percentage difference: -27.
All students: Financial-Aid Applicants: Student Applied for Financial
Aid: Number of observations;
CA Schools: 1995-1996: 112;
CA Schools: 2003-2004: 72;
CA Schools: Percentage difference:
Non-CA Schools: 1995-1996: 152;
Non-CA Schools: 2003-2004: 73;
Non-CA Schools: Percentage difference: [Empty].
All students: Student Did Not Apply for Financial Aid[B]; Price[A];
CA Schools: 1995-1996: 34,645;
CA Schools: 2003-2004: 44,504;
CA Schools: Percentage difference: 28;
Non-CA Schools: 1995-1996: 37,714;
Non-CA Schools: 2003-2004: 44,292;
Non-CA Schools: Percentage difference: 17.
All students: Student Did Not Apply for Financial Aid[B]; Number of
observations;
CA Schools: 1995-1996: 38;
CA Schools: 2003-2004: 19;
CA Schools: Percentage difference: [Empty];
Non-CA Schools: 1995-1996: 46;
Non-CA Schools: 2003-2004: 6;
Non-CA Schools: Percentage difference: [Empty].
All students: Total observations;
CA Schools: 1995-1996: 150;
CA Schools: 2003-2004: 91;
CA Schools: Percentage difference: [Empty]
Non-CA Schools: 1995-1996: 198;
Non-CA Schools: 2003-2004: 79;
Non-CA Schools: Percentage difference: [Empty].
Source: GAO analysis.
[A] Price equals cost of attendance less total grant aid. Cost of
attendance equals tuition and fees, plus expenses (including room and
board, and books).
[B] Financial aid data were not available for students who did not
apply for financial aid.
Notes: All values are (probability) weighted averages, and the monetary
values are in 2005 dollars.
[End of table]
Table 13: CA and Non-CA Schools--Financial Aid Applicants Only: Price
and Financial Aid:
Income level; Low Income; Price[A];
CA schools: 1995-1996: $12,566;
CA schools: 2003-2004: $10,095;
CA schools: Percentage difference: -20;
Non-CA schools: 1995-1996: $18,950;
Non-CA schools: 2003-2004: $21,886;
Non-CA schools: Percentage difference: 15.
Income level; Low Income; Total grant aid;
CA schools: 1995-1996: $23,429;
CA schools: 2003-2004: $27,020;
CA schools: Percentage difference: 15;
Non-CA schools: 1995-1996: $19,093;
Non-CA schools: 2003-2004: $21,861;
Non-CA schools: Percentage difference: 14.
Income level; Low Income; Need-based total grant;
CA schools: 1995-1996: $21,422;
CA schools: 2003-2004: $21,191;
CA schools: Percentage difference: -1;
Non-CA schools: 1995-1996: $16,849;
Non-CA schools: 2003-2004: $17,756;
Non-CA schools: Percentage difference: 5.
Income level; Low Income; Institutional grant aid;
CA schools: 1995-1996: $17,278;
CA schools: 2003-2004: $12,597;
CA schools: Percentage difference: -27;
Non-CA schools: 1995-1996: $14,060;
Non-CA schools: 2003-2004: $17,447;
Non-CA schools: Percentage difference: 24.
Income level; Low Income; Total aid;
CA schools: 1995-1996: $27,385;
CA schools: 2003-2004: $35,956;
CA schools: Percentage difference: 31;
Non-CA schools: 1995-1996: $24,772;
Non-CA schools: 2003-2004: $26,523;
Non-CA schools: Percentage difference: 7.
Income level; Low Income; Number of observations;
CA schools: 1995-1996: 9;
CA schools: 2003- 2004: 3;
CA schools: Percentage difference: [Empty];
Non-CA schools: 1995-1996: 26;
Non-CA schools: 2003-2004: 8;
Non-CA schools: Percentage difference: [Empty].
Income level; Lower-middle income; Price[A];
CA schools: 1995-1996: $17,613;
CA schools: 2003-2004: $30,437;
CA schools: Percentage difference: 73;
Non-CA schools: 1995-1996: $17,623;
Non-CA schools: 2003-2004: $20,546;
Non-CA schools: Percentage difference: 17.
Income level; Lower-middle income; Total grant aid;
CA schools: 1995-1996: $17,531;
CA schools: 2003-2004: $14,793;
CA schools: Percentage difference: -16;
Non-CA schools: 1995-1996: $20,598;
Non-CA schools: 2003-2004: $23,014;
Non-CA schools: Percentage difference: 12.
Income level; Lower-middle income; Need-based total grant;
CA schools: 1995-1996: $15,762;
CA schools: 2003-2004: $12,949;
CA schools: Percentage difference: -18;
Non-CA schools: 1995-1996: $20,417;
Non-CA schools: 2003-2004: $15,456;
Non-CA schools: Percentage difference: -24.
Income level; Lower-middle income; Institutional grant aid;
CA schools: 1995-1996: $11,735;
CA schools: 2003-2004: $9,667;
CA schools: Percentage difference: -18;
Non-CA schools: 1995-1996: $15,742;
Non-CA schools: 2003-2004: $19,386;
Non-CA schools: Percentage difference: 23.
Income level; Lower-middle income; Total aid;
CA schools: 1995-1996: $24,025;
CA schools: 2003-2004: $18,409;
CA schools: Percentage difference: -23;
Non-CA schools: 1995-1996: $28,462;
Non-CA schools: 2003-2004: $30,509;
Non-CA schools: Percentage difference: 7.
Income level; Lower-middle income; Number of observations;
CA schools: 1995-1996: 13;
CA schools: 2003- 2004: 12;
CA schools: Percentage difference: [Empty];
Non-CA schools: 1995-1996: 22;
Non-CA schools: 2003-2004: 5;
Non-CA schools: Percentage difference: [Empty].
Income level; Middle income; Price[A];
CA schools: 1995-1996: $22,146;
CA schools: 2003-2004: $30,156;
CA schools: Percentage difference: 36;
Non-CA schools: 1995-1996: $21,240;
Non-CA schools: 2003-2004: $25,279;
Non-CA schools: Percentage difference: 19.
Income level; Middle income; Total grant aid;
CA schools: 1995-1996: $12,277;
CA schools: 2003-2004: $12,076;
CA schools: Percentage difference: -2;
Non-CA schools: 1995-1996: $17,173;
Non-CA schools: 2003-2004: $17,336;
Non-CA schools: Percentage difference: 1.
Income level; Middle income; Need-based total grant;
CA schools: 1995-1996: $8,293;
CA schools: 2003-2004: $10,767;
CA schools: Percentage difference: 30;
Non-CA schools: 1995-1996: $16,053;
Non-CA schools: 2003-2004: $9,048;
Non-CA schools: Percentage difference: -44.
Income level; Middle income; Institutional grant aid;
CA schools: 1995-1996: $11,096;
CA schools: 2003-2004: $9,936;
CA schools: Percentage difference: -10;
Non-CA schools: 1995-1996: $16,000;
Non-CA schools: 2003-2004: $13,854;
Non-CA schools: Percentage difference: -13.
Income level; Middle income; Total aid;
CA schools: 1995-1996: $18,811;
CA schools: 2003-2004: $20,743;
CA schools: Percentage difference: 10;
Non-CA schools: 1995-1996: $24,261;
Non-CA schools: 2003-2004: $25,176;
Non-CA schools: Percentage difference: 4.
Income level; Middle income; Number of observations;
CA schools: 1995-1996: 16;
CA schools: 2003- 2004: 10;
CA schools: Percentage difference: [Empty];
Non-CA schools: 1995-1996: 20;
Non-CA schools: 2003-2004: 12;
Non-CA schools: Percentage difference: [Empty].
Income level; Upper-middle income; Price[A];
CA schools: 1995-1996: $23,759;
CA schools: 2003-2004: $31,631;
CA schools: Percentage difference: 33;
Non-CA schools: 1995-1996: $26,905;
Non-CA schools: 2003-2004: $29,524;
Non-CA schools: Percentage difference: 10.
Income level; Middle income; Total grant aid;
CA schools: 1995-1996: $10,410;
CA schools: 2003-2004: $10,374;
CA schools: Percentage difference: -0.3;
Non-CA schools: 1995-1996: $12,030;
Non-CA schools: 2003-2004: $13,478;
Non-CA schools: Percentage difference: 12.
Income level; Middle income; Need-based total grant;
CA schools: 1995-1996: $9,732;
CA schools: 2003-2004: $5,864;
CA schools: Percentage difference: -40;
Non-CA schools: 1995-1996: $10,289;
Non-CA schools: 2003-2004: $6,593;
Non-CA schools: Percentage difference: -36.
Income level; Middle income; Institutional grant aid;
CA schools: 1995-1996: $8,694;
CA schools: 2003-2004: $7,719;
CA schools: Percentage difference: -11;
Non-CA schools: 1995-1996: $10,900;
Non-CA schools: 2003-2004: $7,198;
Non-CA schools: Percentage difference: -34.
Income level; Middle income; Total aid;
CA schools: 1995-1996: $16,926;
CA schools: 2003-2004: $19,277;
CA schools: Percentage difference: 14;
Non-CA schools: 1995-1996: $19,425;
Non-CA schools: 2003-2004: $20,769;
Non-CA schools: Percentage difference: 7.
Income level; Middle income; Number of observations;
CA schools: 1995-1996: 21;
CA schools: 2003- 2004: 13;
CA schools: Percentage difference: [Empty];
Non-CA schools: 1995-1996: 32;
Non-CA schools: 2003-2004: 11;
Non-CA schools: Percentage difference: [Empty].
Income level; High income; Price[A];
CA schools: 1995-1996: $31,776;
CA schools: 2003-2004: $37,127;
CA schools: Percentage difference: 17;
Non-CA schools: 1995-1996: $30,184;
Non-CA schools: 2003-2004: $33,806;
Non-CA schools: Percentage difference: 12.
Income level; High income; Total grant aid;
CA schools: 1995-1996: $3,493;
CA schools: 2003-2004: $5,468;
CA schools: Percentage difference: 57;
Non-CA schools: 1995-1996: $7,941;
Non-CA schools: 2003-2004: $10,331;
Non-CA schools: Percentage difference: 30.
Income level; High income; Need-based total grant;
CA schools: 1995-1996: $2,810;
CA schools: 2003-2004: $1,694;
CA schools: Percentage difference: -40;
Non-CA schools: 1995-1996: $6,185;
Non-CA schools: 2003-2004: $5,377;
Non-CA schools: Percentage difference: -13.
Income level; High income; Institutional grant aid;
CA schools: 1995-1996: $2,532;
CA schools: 2003-2004: $3,430;
CA schools: Percentage difference: 35;
Non- CA schools: 1995-1996: $7,062;
Non-CA schools: 2003-2004: $8,884;
Non- CA schools: Percentage difference: 26.
Income level; High income; Total aid;
CA schools: 1995-1996: $12,393;
CA schools: 2003-2004: $10,850;
CA schools: Percentage difference: -12;
Non-CA schools: 1995-1996: $13,300;
Non-CA schools: 2003-2004: $19,797;
Non-CA schools: Percentage difference: 49.
Income level; High income; Number of observations;
CA schools: 1995-1996: 53;
CA schools: 2003- 2004: 34;
CA schools: Percentage difference: [Empty];
Non-CA schools: 1995-1996: 52;
Non-CA schools: 2003-2004: 37;
Non-CA schools: Percentage difference: [Empty].
Income level; High income; Total observations;
CA schools: 1995-1996: 112;
CA schools: 2003-2004: 72;
CA schools: Percentage difference: [Empty];
Non-CA schools: 1995-1996: 152;
Non-CA schools: 2003-2004: 73;
Non-CA schools: Percentage difference: [Empty].
Race[B]; Asian; Price[A];
CA schools: 1995-1996: $28,082;
CA schools: 2003-2004: $28,756;
CA schools: Percentage difference: 2;
Non-CA schools: 1995-1996: $25,642;
Non-CA schools: 2003-2004: $27,624;
Non-CA schools: Percentage difference: 8.
Race[B]; Asian; Total grant aid;
CA schools: 1995-1996: $8,371;
CA schools: 2003-2004: $16,265;
CA schools: Percentage difference: 94;
Non-CA schools: 1995-1996: $10,827;
Non-CA schools: 2003-2004: $17,834;
Non-CA schools: Percentage difference: 65.
Race[B]; Asian; Need-based total grant;
CA schools: 1995-1996: $7,675;
CA schools: 2003-2004: $13,129;
CA schools: Percentage difference: 71;
Non-CA schools: 1995-1996: $9,900;
Non-CA schools: 2003-2004: $14,646;
Non-CA schools: Percentage difference: 48.
Race[B]; Asian; Institutional grant aid;
CA schools: 1995-1996: $6,906;
CA schools: 2003-2004: $11,607;
CA schools: Percentage difference: 68;
Non-CA schools: 1995-1996: $7,771;
Non-CA schools: 2003-2004: $13,376;
Non-CA schools: Percentage difference: 72.
Race[B]; Asian; Total aid;
CA schools: 1995-1996: $14,343;
CA schools: 2003-2004: $23,037;
CA schools: Percentage difference: 61;
Non-CA schools: 1995-1996: $15,513;
Non-CA schools: 2003-2004: $27,425;
Non-CA schools: Percentage difference: 77.
Race[B]; Asian; Number of observations;
CA schools: 1995-1996: 11;
CA schools: 2003- 2004: 5;
CA schools: Percentage difference: [Empty];
Non-CA schools: 1995-1996: 23;
Non-CA schools: 2003-2004: 13;
Non-CA schools: Percentage difference: [Empty].
Race[B]; Black; Price[A];
CA schools: 1995-1996: $12,702;
CA schools: 2003-2004: $22,935;
CA schools: Percentage difference: 81;
Non-CA schools: 1995-1996: $13,530;
Non-CA schools: 2003-2004: $17,375;
Non-CA schools: Percentage difference: 28.
Race[B]; Black; Total grant aid;
CA schools: 1995-1996: $21,360;
CA schools: 2003-2004: $19,958;
CA schools: Percentage difference: -7;
Non-CA schools: 1995-1996: $23,296;
Non-CA schools: 2003-2004: $25,010;
Non-CA schools: Percentage difference: 7.
Race[B]; Black; Need-based total grant;
CA schools: 1995-1996: $19,836;
CA schools: 2003-2004: $8,932;
CA schools: Percentage difference: -55;
Non-CA schools: 1995-1996: $18,517;
Non-CA schools: 2003-2004: $15,631;
Non-CA schools: Percentage difference: -16.
Race[B]; Black; Institutional grant aid;
CA schools: 1995-1996: $15,046;
CA schools: 2003-2004: $17,404;
CA schools: Percentage difference: 16;
Non-CA schools: 1995-1996: $18,582;
Non-CA schools: 2003-2004: $21,231;
Non-CA schools: Percentage difference: 14.
Race[B]; Black; Total aid;
CA schools: 1995-1996: $29,572;
CA schools: 2003-2004: $24,950;
CA schools: Percentage difference: -16;
Non-CA schools: 1995-1996: $29,121;
Non-CA schools: 2003-2004: $26,707;
Non-CA schools: Percentage difference: -8.
Race[B]; Black; Number of observations;
CA schools: 1995-1996: 10;
CA schools: 2003- 2004: 3;
CA schools: Percentage difference: [Empty];
Non-CA schools: 1995-1996: 8;
Non-CA schools: 2003-2004: 4;
Non-CA schools: Percentage difference: [Empty].
Race[B]; Hispanic; Price[A];
CA schools: 1995-1996: $21,177;
CA schools: 2003-2004: $21,529;
CA schools: Percentage difference: 2;
Non-CA schools: 1995-1996: $20,282;
Non-CA schools: 2003-2004: $16,694;
Non-CA schools: Percentage difference: -18.
Race[B]; Hispanic; Total grant aid;
CA schools: 1995-1996: $15,432;
CA schools: 2003-2004: $18,586;
CA schools: Percentage difference: 20;
Non-CA schools: 1995-1996: $17,028;
Non-CA schools: 2003-2004: $25,993;
Non-CA schools: Percentage difference: 53.
Race[B]; Hispanic; Need-based total grant;
CA schools: 1995-1996: $13,514;
CA schools: 2003-2004: $13567;
CA schools: Percentage difference: 0.4;
Non-CA schools: 1995-1996: $14,684;
Non-CA schools: 2003-2004: $18,611;
Non-CA schools: Percentage difference: 27.
Race[B]; Hispanic; Institutional grant aid;
CA schools: 1995-1996: $11,960;
CA schools: 2003-2004: $13,813;
CA schools: Percentage difference: 15;
Non-CA schools: 1995-1996: $13,187;
Non-CA schools: 2003-2004: $17,998;
Non-CA schools: Percentage difference: 36.
Race[B]; Hispanic; Total aid;
CA schools: 1995-1996: $20,110;
CA schools: 2003-2004: $25,576;
CA schools: Percentage difference: 27;
Non-CA schools: 1995-1996: $22,446;
Non-CA schools: 2003-2004: $32,732;
Non-CA schools: Percentage difference: 46.
Race[B]; Hispanic; Number of observations;
CA schools: 1995-1996: 7;
CA schools: 2003- 2004: 8;
CA schools: Percentage difference: [Empty];
Non-CA schools: 1995-1996: 11;
Non-CA schools: 2003-2004: 2;
Non-CA schools: Percentage difference: [Empty].
Race[B]; White; Price[A];
CA schools: 1995-1996: $27,832;
CA schools: 2003-2004: $35,099;
CA schools: Percentage difference: 26;
Non-CA schools: 1995-1996: $25,736;
Non-CA schools: 2003-2004: $30,952;
Non-CA schools: Percentage difference: 20.
Race[B]; White; Total grant aid;
CA schools: 1995-1996: $6,711;
CA schools: 2003-2004: $7,382;
CA schools: Percentage difference: 10;
Non-CA schools: 1995-1996: $13,028;
Non-CA schools: 2003-2004: $12,512;
Non-CA schools: Percentage difference: -4.
Race[B]; White; Need-based total grant;
CA schools: 1995-1996: $5,271;
CA schools: 2003-2004: $4,284;
CA schools: Percentage difference: -19;
Non-CA schools: 1995-1996: $11,645;
Non-CA schools: 2003-2004: $6,249;
Non-CA schools: Percentage difference: -46.
Race[B]; White; Institutional grant aid;
CA schools: 1995-1996: $5,105;
CA schools: 2003-2004: $4,240;
CA schools: Percentage difference: -17;
Non-CA schools: 1995-1996: $11,378;
Non-CA schools: 2003-2004: $10,187;
Non-CA schools: Percentage difference: -10.
Race[B]; White; Total aid;
CA schools: 1995-1996: $14,635;
CA schools: 2003-2004: $14,130;
CA schools: Percentage difference: -3;
Non-CA schools: 1995-1996: $20,042;
Non-CA schools: 2003-2004: $21,005;
Non-CA schools: Percentage difference: 5.
Race[B]; White; Number of observations;
CA schools: 1995-1996: 81;
CA schools: 2003- 2004: 48;
CA schools: Percentage difference: [Empty];
Non-CA schools: 1995-1996: 103;
Non-CA schools: 2003-2004: 49;
Non-CA schools: Percentage difference: [Empty].
Race[B]; White; Total observations;
CA schools: 1995-1996: 112;
CA schools: 2003-2004: 72;
CA schools: Percentage difference: [Empty];
Non-CA schools: 1995-1996: 152;
Non-CA schools: 2003-2004: 73;
Non-CA schools: Percentage difference: [Empty].
Source: GAO analysis.
[A] Price equals cost of attendance less total grant aid. Cost of
attendance equals tuition and fees, plus expenses (including room and
board, and books).
[B] Data for other race, including Native American, unidentified race,
and foreign students were too few to report.
Notes: All values are (probability) weighted averages, and the monetary
values are in 2005 dollars.
[End of table]
Model Specifications and Estimation Methodology:
Our econometric analysis is based on panel data, which pooled cross-
sectional and time series data. The cross-sectional data were based on
freshmen who enrolled in CA schools and non-CA schools, and the time
series data were for academic years 1995-1996 and 2003-2004. Where
feasible, we used panel-data estimation appropriate for cross-sectional
and time series data. Also, we used fixed-effects estimation instead of
random-effects estimation because the observations were not randomly
chosen and there were likely to be unobserved school-specific
effects.[Footnote 49] The reported estimates were based on the fixed-
effects estimators, using probability weights, and the standard errors
were robust.[Footnote 50]
Price, Tuition, and Financial Aid Equations:
Let Y(ijt) be the dependent variable for freshman i's outcomes at the
chosen school j in academic year t, where the main outcome variable
studied is affordability represented by price (PRICE(ijt)).[Footnote
51] The regression equations were specified generally as follows:
[See PDF for image]
where I and S are vectors of school (institution)-level and student-
level variables, and EMCA represents the consensus approach
implementation; y (time specific fixed-effects) and q (school specific
fixed-effects) are scalar parameters, and a and e are the constant and
the random error terms, respectively. There are interactions between
EMCA and the school-level variables and between EMCA and the student-
level variables.[Footnote 52]
We were primarily interested in the total effects of the implementation
of the consensus approach on affordability, as well as the effects that
were specific to particular groups of students, such as low-income and
minority students, and students who applied for financial aid.
Using equation 1, the total effect of the CA implementation on price
was estimated by where and are averages of I and S taken over the
observations for the CA schools during the period of the consensus
approach implementation (2003-2004).[Footnote 53] This measures the
effect of the consensus approach implementation on CA schools, relative
to non-CA schools, controlling for time invariant differences in
schools and other variations over time that are common to both groups.
The coefficient measures the unconditional effect of the consensus
approach implementation on price, while and measure the conditional
effects of the consensus approach implementation on price through the
school-level variables and student-level variables, respectively.
The expression for the total effects of the consensus approach
implementation can be evaluated for particular groups of students by
averaging I and S over that particular subset of students. For example,
the effects of the consensus approach implementation on prices paid by
low-income (INCLO) students can be estimated by
[See PDF for image]
where the school-level and student-level variables are averaged over
the low-income students. More specifically, the second term is the
coefficient estimates of each school-level variable multiplied by the
school-level variable averaged over the subset of low-income (INCLO)
students attending CA schools after the consensus approach
implementation; similarly the average is taken for the third term,
which is for the student-level variables.
Alternatively, we can use equation 1 to illustrate the effects of the
consensus approach implementation for particular groups. Consider a
simple example in which there are two student characteristics, and,
where is an indicator variable equal to one if the student is a
financial aid applicant and zero otherwise, and is an indicator equal
to one if the student is black, and zero otherwise. Then, using
equation 1, the equation for this example is:
[See PDF for image]
Now consider a white student who is a financial aid applicant in school
j at time t.[Footnote 54] The predicted price for a white student if j
is a CA school is:
[See PDF for image]
and the predicted price if j is not a CA school is:
[See PDF for image]
The effect of the consensus approach implementation for a financial aid
applicant at school j is then the difference between equations 1.2 and
1.3, which is:
[See PDF for image]
The coefficient measures the effect of adopting the consensus approach
that is invariant across school and student type, the term captures the
differential effect of adopting the consensus approach for a school
with characteristics Ijt, and the third term, , captures the
differential effect of adopting the consensus approach for a white
student who is a financial aid applicant. Repeating the exercise above
for a black student who is a financial aid applicant, the predicted
effect of adopting the consensus approach would be:
[See PDF for image]
The first three terms in equation 1.5 are the same as equation 1.4,
while the fourth term captures the differential effect of the consensus
approach implementation for a black student. In this example, then, the
estimated effect of the consensus approach implementation on financial
aid students would be the weighted average of the terms in equations
1.4 or 1.5, with weights corresponding to the proportions of white and
black financial-aid students across all schools j that adopted the
consensus approach at time t, respectively.
Another estimate of the consensus approach's effect on a particular
group is the estimated differential effect on a group, given by,
holding everything else constant. For example, one can ask how a low-
income student as compared to a high-income student would be affected
by the consensus approach implementation, assuming all other
characteristics of the student and the student's school are held
constant. This estimated effect is simply given by the element of the
vector in that corresponds to INCLO. This differs from the total effect
of the consensus approach implementation discussed above by taking as
given the consensus approach implementation, and by abstracting from
the likelihood that low-income students will have other characteristics
and attend different schools than non low-income students. We will also
discuss the coefficient, which captures the value of the dependent
variable for the particular group in both CA and non-CA schools before
the consensus approach implementation, where necessary.
The total effect of the exemption on price as well as its specific
effects on particular groups will depend on which theory of the
exemption is supported by the data. In particular, we expect price to
be lower for disadvantaged students if the social benefit theory is
valid; on the other hand, price will increase if the anti-competitive
theory is valid. Similarly, the effects of the student-level variables
would depend on the theories of the effects of the exemption. For the
effects of the school-level variables, ENDOWSTU should be negative
because with more resources there is less need to raise tuition and
there will be more funds for grant aid. RANKAVG should be negative
because as the quality of the school decreases tuition as well as grant
aid should decrease. ENROLUG would be negative if higher growth in
student enrollment perhaps means more revenues and less need to raise
tuition. On the other hand, if students' education is on net subsidized
by other sources of school income then ENROLUG would be positive as
increased enrollment increases the costs to the school of providing
education. And TENURED should be positive if more tenured faculty
implies higher quality.[Footnote 55]
We estimated equation 1 for price, as well as for tuition and the
financial aid variables, using probability-weighted regression and
robust standard errors, as well as the fixed-effects estimator for
panel data.[Footnote 56] See the regression estimates for price and
tuition in table 14, and those for the financial aid variables in table
15.[Footnote 57]
The regression models for the price, tuition, and financial aid
variables are all highly significant using the F-values of the models.
See tables 14 and 15. Furthermore, the school-level variables generally
have the expected effects. In particular, for the price equation, a
student enrolled in a school with an endowment per student (ENDOWSTU)
of $250,000 paid about $5,000 lower price.[Footnote 58] Also, a student
paid about $464 less for a school with a unit drop in its selectivity
(RANKAVG). Although the effect is not significant, the positive sign
for ENROLUG suggests that an increase in enrollment growth may result
in a higher price paid, implying that education is net subsidized and
increases in enrollment increases the cost of providing education; and
vice versa. Finally, a student enrolled in a school with 10 percent
higher tenured faculty (TENURED) paid about $3,310 higher. As discussed
earlier, the effects of the student-level variables depend on which
theory of the effects of the higher education exemption is
relevant.[Footnote 59]
Student enrollment equation:
The regression equation for enrollment into a CA school (ENRCAijt)
would depend on student characteristics. Generally, enrollment is the
outcome of decision-making that included application, admission, and
acceptance of the admission offer. The first and third decisions are
made by the student, and the second decision is made by the school.
Therefore, in general, both student-level variables and school-level
variables would be relevant. However, our approach, as indicated in
equation 2, treated the CA schools essentially the same and likewise
for the non-CA schools, with differences between the two groups other
than the consensus approach implementation captured by the constant
term in the regression. The enrollment equation was thus specified as
follows, excluding school-level variables as regressors:
(See PDF for image);
F is the standard normal cumulative probability distribution function.
Similar to equation 1, equation 2 includes student characteristics
(with coefficients r), time fixed-effects captured by AY2003, and the
interaction of the time variable AY2003 with student characteristics
(with coefficients g).[Footnote 60]
The time specific fixed-effect for AY2003 captures any shift, which is
constant across students, toward or away from the CA schools, after the
consensus approach implementation, while the interaction terms between
the AY2003 and the student characteristics capture shifts toward or
away from the CA schools by students with specific
characteristics.[Footnote 61]
The marginal effect of the consensus approach implementation is
captured by the effects of AY2003 on enrollment in CA schools.
Specifically, this equals,
[See PDF for image]
where f is the standard normal probability density function. It should
be noted that if AY2003 affects the probability of enrollment in CA
schools, it would be a valuable suggestive evidence about the potential
impact of the consensus approach implementation. However, it would not
establish that the consensus approach implementation caused the shift.
This is because it is possible that such effects might be due to
changes in other factors at CA schools versus non-CA schools (e.g.,
more rapid endowment growth in the latter than the former). The effect
of the consensus approach implementation is the change in the
probability of enrollment in CA schools relative to non-CA schools as a
result of the consensus approach implementation. The overall effect of
the CA implementation as well as the effects of the consensus approach
implementation on particular groups of students, such as low-income
students and those who applied for financial aid, can be obtained
similar to the discussion above for the price.
The marginal effect of the student characteristics is captured by the
effects of S on enrollment in CA schools. Specifically, this equals,
[See PDF for image]
The effect of the consensus approach implementation on how the
probabilities of enrollment of low-income and minority students, and
those who applied for financial aid, are affected can be obtained
similar to the discussion for the price.
Similar to the discussion for the price equation, the effects of the
exemption and the student-level variables on enrollment into CA schools
will depend on which theory of the exemption is valid. In particular,
the social benefit theory will imply increased likelihood of enrollment
into CA schools, especially of low-income students, because prices will
be lower. While the opposite will occur with the anti-competitive
theory because average price will be higher.
We estimated equation 2 for student enrollment using the probit
estimation, with probability weights and robust standard
errors.[Footnote 62] The regression estimates are in table 14.
The regression model for enrollment in table 14 is significant using
the chi-square of the model. As indicated earlier, we expect the
estimation results will enable us to determine if the likelihood of
enrollment into schools implementing the consensus approach by various
student groups is more consistent with the social benefit theory or the
anti-competitive theory of the effects of the higher education
exemption.
Table 14: Regression Estimates of Effects of Consensus Approach
Implementation on Price, Tuition, and Enrollment:
Variable: EMCA;
Price: 43,743.75[A] [0.002];
Tuition: -1,720.72 [0.512];
Enrollment: n/a.
Variable: AY2003;
Price: 12,133.55[A] [0.000];
Tuition: 5,650.28[A] [0.000];
Enrollment: 0.25751 [0.631].
Variable: Student-level: FINAID;
Price: -7,573.33[A] [0.000];
Tuition: n/a;
Enrollment: 0.01292 [0.854].
Variable: Student-level: FINAID[*];
Price: 190.21 [0.911];
Tuition: n/a;
Enrollment: - 0.30976[ B] [0.015].
Variable: Student-level: ASIAN;
Price: 1,084.13 [0.363];
Tuition: n/a;
Enrollment: - 0.01069 [0.910].
Variable: Student-level: ASIAN*;
Price: -7,109.66[C] [0.055];
Tuition: n/a;
Enrollment: -0.08486 [0.613].
Variable: Student-level: BLACK;
Price: -9,444.68[A] [0.000];
Tuition: n/a;
Enrollment: 0.19398 [0.129].
Variable: Student-level: BLACK*;
Price: -566.20 [0.921];
Tuition: n/a;
Enrollment: - 0.20422 [0.339].
Variable: Student-level: HISPANIC;
Price: -4,686.31[A] [0.007];
Tuition: n/a;
Enrollment: 0.06790 [0.574].
Variable: Student-level: HISPANIC*;
Price: -1,610.12 [0.588];
Tuition: n/a;
Enrollment: 0.35354[B] [0.021].
Variable: Student-level: FOREIGN;
Price: 3,398.09 [0.230];
Tuition: n/a;
Enrollment: - 0.25968 [0.221].
Variable: Student-level: FOREIGN*;
Price: 10,588.17[B] [0.026];
Tuition: n/a;
Enrollment: 0.36734[C] [0.054].
Variable: Student-level: OTHER;
Price: -2,047.09 [0.407];
Tuition: n/a;
Enrollment: 0.02366 [0.887].
Variable: Student-level: OTHER*;
Price: -1,077.16 [0.727];
Tuition: n/a;
Enrollment: 0.30781[C] [0.059].
Variable: Student-level: EFC;
Price: 0.10871[A] [0.000];
Tuition: n/a;
Enrollment: 2.30e-06 [0.190].
Variable: Student-level: EFC*;
Price: -0.00745 [0.872];
Tuition: n/a;
Enrollment: - 3.43e-06 [0.219].
Variable: Student-level: INCLO;
Price: -8,427.06a [0.000];
Tuition: n/a;
Enrollment: - 0.15253 [0.196].
Variable: Student-level: INCLO*;
Price: -6,507.64 [0.274];
Tuition: n/a;
Enrollment: - 0.15185 [0.489].
Variable: Student-level: INCLOMD;
Price: -8,696.19[A] [0.000];
Tuition: n/a;
Enrollment: -0.03045 [0.797].
Variable: Student-level: INCLOMD*;
Price: -1,789.68 [0.593];
Tuition: n/a;
Enrollment: 0.16593 [0.384].
Variable: Student-level: INCMD;
Price: -4,804.25[A] [0.000];
Tuition: n/a;
Enrollment: 0.06859 [0.506].
Variable: Student-level: INCMD*;
Price: 945.64 [0.771];
Tuition: n/a;
Enrollment: - 0.16166 [0.303].
Variable: Student-level: INCUPMD;
Price: -1,434.39 [0.163];
Tuition: n/a;
Enrollment:
-0.03378 [0.689].
Variable: Student-level: INCUPMD*;
Price: -1,715.73 [0.522];
Tuition: n/a;
Enrollment:
-0.07025 [0.657].
Variable: Student-level: SCORESAT;
Price: -2.48 [0.430];
Tuition: n/a;
Enrollment: 0.00024 [0.227].
Variable: Student-level: SCORESAT*;
Price: -7.82 [0.383];
Tuition: n/a;
Enrollment: 0.00013 [0.764].
Variable: School-level; ENDOWSTU;
Price: -0.01935[A] [0.001];
Tuition: -0.00401[A] [0.008];
Enrollment: n/a.
Variable: School-level; ENDOWSTU*;
Price: -0.01056[B] [0.044];
Tuition: 0.00038 [0.831];
Enrollment: n/a.
Variable: School-level; RANKAVG;
Price: -464.33[C] [0.051];
Tuition: -151.06[C] [0.064];
Enrollment: n/a.
Variable: School-level; RANKAVG*;
Price: -798.05[A] [0.000];
Tuition: 36.28 [0.792];
Enrollment: n/a.
Variable: School-level; ENROLUG;
Price: 19,038.16 [0.785];
Tuition: 35,553.57 [0.133];
Enrollment: n/a.
Variable: School-level; ENROLUG*;
Price: -45,843.9 [0.518];
Tuition: -44,159.24[C] [0.095];
Enrollment: n/a.
Variable: School-level; TENURED;
Price: 33,100.97[A] [0.000];
Tuition: -610.06 [0.492];
Enrollment: n/a.
Variable: School-level; TENURED*;
Price: -25,823.9[B] [0.014];
Tuition: 4,632.48 [0.315];
Enrollment: n/a.
Variable: School-level; Constant;
Price: 29,651.89[A] [0.000];
Tuition: 28,746.01[A] [0.000];
Enrollment: n/a.
Variable: School-level; Test statistic of model[D];
Price: 22.97[A] [0.000];
Tuition: 375.71[A] [0.000];
Enrollment: 37.68[B] [0.050].
Variable: School-level; R-squared;
Price: 0.62;
Tuition: 0.99;
Enrollment: 0.06.
Variable: School-level; Sample size;
Price: 518;
Tuition: 28;
Enrollment: 518.
Variable: School-level; Joint test for EMCA;
Price: 2.85[A] [0.000];
Tuition: 1.15 [0.460];
Enrollment: 18.70[B] [0.133].
Variable: School-level; Linear restriction test for EMCA[E];
Price: 1.18 [0.240];
Tuition: -0.59 [0.586];
Enrollment: n/a.
Source: GAO analysis.
[A] Statistically significant at the 1 percent level or lower. P-values
are in brackets.
[B] Statistically significant at the 5 percent level or lower. P-values
are in brackets.
[C] Statistically significant at the 10 percent level or lower. P-
values are in brackets.
[D] F-statistic values for the price and tuition equations, and chi-
square values for the enrollment equation.
[E] t-statistic values for the price and tuition equations, and z-
statistic values for the enrollment equation.
Notes: N/A means data are not available or applicable.
* means interaction terms with EMCA for price and tuition equations,
and interaction terms with AY2003 for the enrollment equation.
Estimates of price and tuition are obtained using fixed-effects models.
Estimates for enrollment are the marginal effects from a probit model.
[End of table]
Table 15: Regression Estimates of Effects of Consensus Approach
Implementation on Financial Aid:
Variable: EMCA;
Total grant aid: -28,705.63[C] [0.066];
Need-based grant aid: -15,512.93 [0.178];
Total aid: -50,805.28[B] [0.016].
Variable: AY2003;
Total grant aid: 2,159.46 [0.348];
Need-based grant aid: -1,511.37 [0.522];
Total aid: 7,385.03[C] [0.062].
Variable: Student-level; FINAID;
Total grant aid: n/a;
Need-based grant aid: n/a;
Total aid: n/a.
Variable: Student-level; FINAID*;
Total grant aid: n/a;
Need-based grant aid: n/a;
Total aid: n/a.
Variable: Student-level; ASIAN;
Total grant aid: -722.86 [0.649];
Need-based grant aid: -740.76 [0.590];
Total aid: -2,638.73 [0.221].
Variable: Student-level; ASIAN*;
Total grant aid: 6,970.89 [0.142];
Need-based grant aid: 6,546.91[C] [0.066];
Total aid: 8,275.76 [0.221].
Variable: Student-level; BLACK;
Total grant aid: 7,914.65[A] [0.000];
Need-based grant aid: 4,796.63[B] [0.026];
Total aid: 8,425.58[A] [0.000].
Variable: Student-level; BLACK*;
Total grant aid: 2,546.02 [0.656];
Need-based grant aid: -2,267.21 [0.514];
Total aid: 965.32 [0.862].
Variable: Student-level; HISPANIC;
Total grant aid: 4,709.93[B] [0.023];
Need-based grant aid: 2,826.32 [0.140];
Total aid: 2,281.05 [0.389].
Variable: Student-level; HISPANIC*;
Total grant aid: 2,038.96 [0.570];
Need-based grant aid: 206.79 [0.947];
Total aid: 2,606.82 [0.622].
Variable: Student-level; FOREIGN;
Total grant aid: -5,754.55[B] [0.031];
Need-based grant aid: -4,634.40 [0.132];
Total aid: -11.961.86[A] [0.002].
Variable: Student-level; FOREIGN*;
Total grant aid: -10,965.98[B] [0.032];
Need-based grant aid: -10,414.55[B] [0.032];
Total aid: -11,659.21[C] [0.068].
Variable: Student-level; OTHER;
Total grant aid: 4,656.42 [0.169];
Need-based grant aid: 5,229.39 [0.129];
Total aid: 4,196.89 [0.349].
Variable: Student-level; OTHER*;
Total grant aid: -2,813.57 [0.481];
Need-based grant aid: -1,725.88 [0.667];
Total aid: -4,098.47 [0.496].
Variable: Student-level; EFC;
Total grant aid: -0.16058[A] [0.000];
Need-based grant aid: -0.149889[A] [0.000];
Total aid: -0.187923[A] [0.000].
Variable: Student-level; EFC*;
Total grant aid: 0.044382 [0.397];
Need-based grant aid: 0.03185 [0.472];
Total aid: 0.006624 [0.929].
Variable: Student-level; INCLO;
Total grant aid: 7,178.94[A] [0.000];
Need-based grant aid: 7,932.99[A] [0.000];
Total aid: 3,276.04 [0.177].
Variable: Student-level; INCLO*;
Total grant aid: 7,346.13 [0.239];
Need-based grant aid: 6,955.88[C] [0.096];
Total aid: 14,970.89 [0.020].
Variable: Student-level; INCLOMD;
Total grant aid: 8,227.84[A] [0.000];
Need-based grant aid: 8,747.21[A] [0.000];
Total aid: 7,153.01[A] [0.001].
Variable: Student-level; INCLOMD*;
Total grant aid: 2,830.62 [0.395];
Need-based grant aid: 3,585.08 [0.198];
Total aid: 3,678.72 [0.359].
Variable: Student-level; INCMD;
Total grant aid: 5,084.33[A] [0.000];
Need-based grant aid: 3,488.27[B] [0.015];
Total aid: 4,116.59[B] [0.040].
Variable: Student-level; INCMD*;
Total grant aid: 1,835.35 [0.617];
Need-based grant aid: 4,773.69 [0.134];
Total aid: 5,366.73 [0.339].
Variable: Student-level; INCUPMD;
Total grant aid: 2,215.09[C] [0.093];
Need-based grant aid: 1,699.48 [0.161];
Total aid: 1,643.62 [0.419].
Variable: Student-level; INCUPMD*;
Total grant aid: 600.56 [0.851];
Need-based grant aid: -473.12 [0.873];
Total aid: 2,503.61 [0.632].
Variable: Student-level; SCORESAT;
Total grant aid: 1.23 [0.729];
Need-based grant aid: -0.51436 [0.882];
Total aid: -3.05 [0.561].
Variable: Student-level; SCORESAT*;
Total grant aid: 10.81 [0.306];
Need-based grant aid: 1.97 [0.775];
Total aid: 18.18 [0.170].
Variable: School-level; ENDOWSTU;
Total grant aid: 0.00684 [0.317];
Need-based grant aid: 0.01056 [0.144];
Total aid: -0.00583 [0.512].
Variable: School-level; ENDOWSTU*;
Total grant aid: 0.001786 [0.774];
Need-based grant aid: 0.00272 [0.644];
Total aid: 0.015595[C] [0.092].
Variable: School-level; RANKAVG;
Total grant aid: 88.79 [0.773];
Need-based grant aid: 406.70 [0.114];
Total aid: 58.30 [0.888].
Variable: School-level; RANKAVG*;
Total grant aid: 140.56 [0.571];
Need-based grant aid: 38.06 [0.859];
Total aid: 566.66 [0.178].
Variable: School-level; ENROLUG;
Total grant aid: -36,447.82 [0.623];
Need-based grant aid: -238,689.4[A] [0.004];
Total aid: -12,713.12 [0.922].
Variable: School-level; ENROLUG*;
Total grant aid: 30,780.66 [0.683];
Need-based grant aid: 246,969.5[A] [0.003];
Total aid: 32,081.77 [0.807].
Variable: School-level; TENURED;
Total grant aid: -4,340.32 [0.545];
Need-based grant aid: 5,070.34 [0.486];
Total aid: 8,685.55 [0.530].
Variable: School-level; TENURED*;
Total grant aid: 15,405.02 [0.204];
Need-based grant aid: 16,399.34 [0.103];
Total aid: 11,726.97 [0.514].
Variable: School-level; Constant;
Total grant aid: 8,727.25 [0.375];
Need-based grant aid: -1331.71 [0.878];
Total aid: 17,640.66 [0.209].
Variable: School-level; F value of model;
Total grant aid: 14.81[A] [0.000];
Need- based grant aid: 16.36[A] [0.000];
Total aid: 8.79[A] [0.000].
Variable: School-level; R-squared;
Total grant aid: 0.55;
Need-based grant aid: 0.54;
Total aid: 0.36.
Variable: School-level; Sample size;
Total grant aid: 409;
Need-based grant aid: 409;
Total aid: 409.
Variable: School-level; F value of joint test;
Total grant aid: 1.13 [0.328];
Need- based grant aid: 1.83[B] [0.026];
Total aid: 1.60[C] [0.067].
Variable: School-level; t value of linear restriction;
Total grant aid: n/a;
Need- based grant aid: 2.05[B] [0.041];
Total aid: 0.64 [0.525].
Source: GAO analysis.
[A] Statistically significant at the 1 percent level or lower. P-values
are in brackets.
[B] Statistically significant at the 5 percent level or lower. P-values
are in brackets.
[C] Statistically significant at the 10 percent level or lower. P-
values are in brackets.
Notes: n/a means data are not available or applicable.
*Means interaction terms with EMCA.
[End of table]
Estimation Results of the Effects of Attending Meetings and
Implementing the Consensus Approach[Footnote 63]
The results of estimating equations 1 and 2 for the total effects of
the CA implementation on affordability and enrollment are summarized in
table 16, based on the regression results in tables 14 and 15. The
results for price and enrollment in table 16 contain the key findings
of the entire study, with the other variables (tuition and financial
aid) providing information that supplements the findings for
price.[Footnote 64]
Total Effects of Implementing the Consensus Approach (from table 16):
Prices:[Footnote 65]
For the average student, the consensus approach implementation did not
significantly change the prices paid by students in CA schools compared
to non-CA schools, including the effects on low-income and minority
students and students who applied for financial aid.[Footnote 66]
Tuition:[Footnote 67]
The CA schools, compared to non-CA schools, did not significantly
change the tuition they charged students as a result of the consensus
approach implementation.
Total grant aid:[Footnote 68]
The consensus approach implementation did not significantly change the
amount of total grant aid received by students in CA schools compared
to non-CA schools.
Need-based total grant aid:[Footnote 69]
The consensus approach implementation increased the amount of need-
based total grant aid received by students in CA schools compared to
non-CA schools by about $6,125, with a confidence interval of between
$239 and $12,011.[Footnote 70] The amounts of need-based grant aid
received by students in CA schools compared to non-CA schools were
higher for middle income students by about $20,221, with a confidence
interval of between $6,718 and $33,724. Asian students received higher
need-based grant aid of about $14,628, with a confidence interval of
between $5,051 and $24,206; Hispanic students received higher need-
based grant aid of about $9,532, with a confidence interval of between
$1,006 and $18,059; and white students received higher need-based grant
aid of about $6,017, with a confidence interval of between $178 and
$11,856.
Total aid:[Footnote 71]
The consensus approach implementation did not significantly change the
amount of total aid received by students in CA schools compared to non-
CA schools. However, low-income students in CA schools received higher
total aid of about $12,121, with a confidence interval of between
$1,837 and $22,404.[Footnote 72]
Enrollment:
The consensus approach implementation did not significantly change the
overall likelihood of enrollment into CA schools compared to non-CA
schools, for all types of students.
Table 16: Estimates of Effects of Consensus Approach Implementation on
Affordability and Enrollment in CA Schools Relative to Non-CA Schools:
Total effect of consensus approach on—: All students;
Price: $3,021; [- $2,026, $8,068];
Tuition: -$433; [-$2,465, $1,599];
Total grant aid: - $749; [-$6,967, $5,470];
Need-based total grant aid: $6,125[B]; [$239, $12,011];
Total aid: -$2,886; [-$11,805, $6,034];
Probability of enrollment: 38%; [8%, 67%].
Total effect of consensus approach on—: Financial-aid applicants;
Price: $2,177; [-$3,319, $7,673];
Tuition: n/a; Total grant aid: n/a;
Need-based total grant aid: n/a;
Total aid: n/a;
Probability of enrollment: 22%; [-11%,; 54%].
Total effect of consensus approach on—: Low income;
Price: -$4,061; [- $15,583, $7,461];
Tuition: n/a;
Total grant aid: $3,688; [-$8,511,; $15,887];
Need-based total grant aid: $1,956; [-$5,232,; $9,144];
Total aid: $12,121[B]; [$1,837,; $22,404];
Probability of enrollment: 59%; [- 52%,; 170%].
Total effect of consensus approach on—: Lower-middle income;
Price: $8,089[C]; [-$263, $16,441];
Tuition: n/a;
Total grant aid: -$3,671; [- $12,487,; $5,145];
Need-based total grant aid: $6,556; [-$2,145,; $15,257];
Total aid: -$7,776; [-$19,776,; $4,224];
Probability of enrollment: 95%; [6%,; 184%].
Total effect of consensus approach on—: Middle income;
Price: $2,320[D]; [-$8,043, $12,682];
Tuition: n/a;
Total grant aid: $1,618; [-$11,221,; $14,457];
Need-based total grant aid: $20,221[A]; [$6,718,; $33,724];
Total aid: $1,178; [-$19,616,; $21,971];
Probability of enrollment: 26%; [-41%,; 93%].
Total effect of consensus approach on—: Upper-middle income;
Price: - $1,048; [-$7,641, $5,545];
Tuition: n/a;
Total grant aid: -$973; [- $7,801,; $5,855];
Need-based total grant aid: $2,769; [-$3,986,; $9,524];
Total aid: -$3,054; [-$13,177,; $7,068];
Probability of enrollment: 18%; [-47%,; 82%].
Total effect of consensus approach on—: High income;
Price: $3,699; [- $824, $8,222];
Tuition: n/a;
Total grant aid: -$714; [-$6,905,; $5,476];
Need-based total grant aid: $4,687[C]; [-$449,; $9,824];
Total aid: -$3,856; [-$12,817,; $5,104];
Probability of enrollment: 31%; [- 6%,; 68%].
Total effect of consensus approach on—: Asian students;
Price: -$376; [-$10,426, $9,674];
Tuition: n/a;
Total grant aid: $5,726; [-$5,671,; $17,123];
Need-based total grant aid: $14,628[A]; [$5,051,; $24,206];
Total aid: $3,694; [-$13,693,; $21,082];
Probability of enrollment: 1%; [-78%,; 80%].
Total effect of consensus approach on—: Black students;
Price: $4,468; [-$7,452, $16,387];
Tuition: n/a;
Total grant aid: -$1,227; [-$13,238,; $10,783];
Need-based total grant aid: $4,332; [-$4,992,; $13,657];
Total aid: -$6,542; [-$20,353,; $7,269];
Probability of enrollment: - 26%; [-142%,; 91%].
Total effect of consensus approach on—: Hispanic students;
Price: $1,168[D]; [-$6,744, $9,079];
Tuition: n/a;
Total grant aid: $1,520; [- $8,300,; $11,341];
Need-based total grant aid: $9,532[B]; [$1,006,; $18,059];
Total aid: $3,648; [-$8,981,; $16,278];
Probability of enrollment: 108%; [-6%,; 222%].
Total effect of consensus approach on—: White students;
Price: $2,588; [-$2,403, $7,578];
Tuition: n/a;
Total grant aid: -$491; [-$6,766,; $5,784];
Need-based total grant aid: $6,017[B]; [$178,; $11,856];
Total aid: -$2,879; [-$11,922,; $6,164];
Probability of enrollment: 19%; [- 14%,; 52%].
Total effect of consensus approach on—: Number of observations;
Price: 518;
Tuition: 28;
Total grant aid: 409;
Need-based total grant aid: 409;
Total aid: 409;
Probability of enrollment: 518.
Schools; CA Schools:
Cornell University,
Duke University,
Georgetown University,
University of Notre Dame,
Vanderbilt University,
Wake Forest University,
Yale University;
Schools; Non-CA Schools:
Brandeis University,
Bryn Mawr College,
New York University,
Princeton University,
Tulane University,
University of Rochester,
Washington University at St. Louis.
Source: GAO analysis.
[A] Statistically significant at the 1 percent level or lower.
[B] Statistically significant at the 5 percent level or lower.
[C] Statistically significant at the 10 percent level or lower.
[D] Effects were negative when data for only financial aid applicants
were used.
Notes: The values in brackets are the 95 percent confidence intervals
for the estimates that are significant at the 5 percent level or lower.
"n/a" means data are not available or applicable.
All the monetary values are in 2005 dollars.
Results are based on tables 14 and 15.
The calculated values are based on where the average values are for all
students.
The estimates are based on where the average values are for the
relevant k subgroup of students.
[End of table]
Prior Levels and Differential Effects of the Consensus Approach on
Affordability and Enrollment for Students with Particular
Characteristics[Footnote 73]
We discuss the estimates of affordability and the likelihood of
enrollment in both the schools that adopted the consensus approach and
those that did not, of students with particular characteristics, before
the consensus approach was implemented. The estimates are reported in
table 17, based on tables 14 and 15. These estimates could help explain
the extent to which the consensus approach affected particular groups
of students. For instance, if certain students were receiving higher
financial aid awards prior to the consensus approach, they may be less
likely to receive much higher awards as a result of its adoption. We
also discuss the differential effects on students with particular
characteristics that the consensus approach may have had on
affordability and enrollment at those schools. The estimates are
reported in table 18, based on tables 14 and 15. As already discussed,
these estimates indicate how the consensus approach affected students
with particular characteristics, assuming all the other characteristics
of the students are held constant.
Prices:
Some students paid lower prices prior to the CA implementation; in
particular, financial aid applicants relative to non-financial aid
applicants; low income, lower-middle income, middle-income students
relative to high-income students; and black and Hispanic students
relative to white students. But there were no significant differential
effects of implementing the consensus approach on prices paid by these
groups of students in CA schools.
Total grant aid:
Some students received higher total grant aid prior to the consensus
approach implementation; in particular, low-income, lower-middle
income, middle-income, black, and Hispanic students.
Need-based total grant aid:
Some students received higher need-based aid prior to the consensus
approach implementation; in particular, low-income, lower-middle
income, middle-income, and black students. But there were no
significant differential effects of implementing the consensus approach
on prices paid by these groups of students.
Total aid:
Some students received higher total aid prior to the consensus approach
implementation; in particular, middle-income, and black students. But
lower-middle income students received lower total aid prior to the
consensus approach implementation. Only low-income students in CA
schools received higher aid, compared to high-income students, as a
result of implementing the consensus approach.
Enrollment:
Students generally were not more or less likely to enroll in a CA
school prior to the consensus approach implementation. However,
implementing the consensus approach lowered the likelihood of
enrollment of financial-aid students, compared to non-financial aid
applicants, while the likelihood of enrollment of Hispanic students
increased, compared to white students, in CA schools.
Table 17: Estimates of Affordability and Enrollment before the
Consensus Approach Implementation for Particular Groups of Students in
Both CA and Non-CA Schools:
Students: Financial-aid applicants[D];
Price: -$7,573[A];
Total grant aid: N/A;
Need-based total grant aid: N/A;
Total aid: N/A;
Probability of enrollment: 1%.
Students: Low income[E];
Price: -$8,427[A];
Total grant aid: $7,179[A];
Need-based total grant aid: $7,933[A];
Total aid: $3,276;
Probability of enrollment: -15%.
Students: Lower-middle income[E];
Price: -$8,696[A];
Total grant aid: $8,228[A];
Need-based total grant aid: $8,747[A];
Total aid: - $7,153[A];
Probability of enrollment: -3%.
Students: Middle income[E];
Price: -$4,804[A];
Total grant aid: $5,084[A];
Need-based total grant aid: $3,488[B];
Total aid: $4,117[B];
Probability of enrollment: 7%.
Students: Upper-middle income[E];
Price: -$1,434;
Total grant aid: $2,215[C];
Need-based total grant aid: $1,699;
Total aid: $1,644;
Probability of enrollment: -3%.
Students: High income;
Price: N/A;
Total grant aid: N/A;
Need-based total grant aid: N/A;
Total aid: N/A;
Probability of enrollment: N/A.
Students: Asian students[F];
Price: $1,084;
Total grant aid: -$723;
Need-based total grant aid: -$740;
Total aid: -$2,639;
Probability of enrollment: -1%.
Students: Black students[F];
Price: -$9,445[A];
Total grant aid: $7,915[A];
Need-based total grant aid: $4,797[B];
Total aid: $8,426[A];
Probability of enrollment: 19%.
Students: Hispanic students[F];
Price: -$4,686[A];
Total grant aid: $4,710[B];
Need-based total grant aid: $2,826;
Total aid: $2,281;
Probability of enrollment: 7%.
Students: White students;
Price: N/A;
Total grant aid: N/A;
Need-based total grant aid: N/A;
Total aid: N/A;
Probability of enrollment: N/A.
Students: Number of observations;
Price: 518;
Total grant aid: 409;
Need-based total grant aid: 409;
Total aid: 409;
Probability of enrollment: 518.
Schools; CA Schools:
Cornell University,
Duke University,
Georgetown University,
University of Notre Dame,
Vanderbilt University,
Wake Forest University,
Yale University;
Schools; Non-CA Schools:
Brandeis University,
Bryn Mawr College,
New York University,
Princeton University,
Tulane University,
University of Rochester,
Washington University at St. Louis.
Source: GAO analysis.
[A] Statistically significant at the 1 percent level or lower.
[B] Statistically significant at the 5 percent level or lower.
[C] Statistically significant at the 10 percent level or lower.
[D] The estimates are relative to non-financial aid applicants.
[E] The estimates are relative to high income students.
[F] The estimates are relative to white students.
Notes: Results are from tables 14 and 15, based on the coefficient in
equations 1 and 2. For instance, the value for price for financial-aid
applicants is based on the estimated coefficient FINAID in table 14.
N/A means data are not available or applicable.
All the monetary values are in 2005 dollars.
[End of table]
Table 18: Differential Effects of Consensus Approach Implementation on
Affordability and Enrollment in CA Schools for Particular Groups of
Students:
Students: Financial-aid applicants[D];
Price: $190;
Total grant aid: N/ A;
Need-based total grant aid: N/A;
Total aid: N/A;
Probability of enrollment: -31%[B].
Students: Low-income[E];
Price: -$6,508;
Total grant aid: $7,346;
Need- based total grant aid: $6,956[C];
Total aid: $14,971[B];
Probability of enrollment: -15%.
Students: Lower-middle income[E];
Price: -$1,790;
Total grant aid: $2,831;
Need-based total grant aid: $3,585;
Total aid: $3,679;
Probability of enrollment: 17%.
Students: Middle income[E];
Price: $946;
Total grant aid: $1,835;
Need- based total grant aid: $4,774;
Total aid: $5,367;
Probability of enrollment: -16%.
Students: Upper-middle income[E];
Price: -$1,716;
Total grant aid: $601;
Need-based total grant aid: -$473;
Total aid: $2,504;
Probability of enrollment: -7%.
Students: High income;
Price: n/a;
Total grant aid: n/a;
Need-based total grant aid: n/a;
Total aid: n/a;
Probability of enrollment: n/a.
Students: Asian students[F];
Price: -$7,110[C];
Total grant aid: $6,971;
Need-based total grant aid: $6,547[C];
Total aid: $8,276;
Probability of enrollment: -9%.
Students: Black students[F];
Price: -$566;
Total grant aid: $2,546;
Need-based total grant aid: -$2,267;
Total aid: $965;
Probability of enrollment: -20%.
Students: Hispanic students[F];
Price: -$1,610;
Total grant aid: $2,039;
Need-based total grant aid: $207;
Total aid: $2,607;
Probability of enrollment: 35%[B].
Students: White students;
Price: n/a;
Total grant aid: n/a;
Need-based total grant aid: n/a;
Total aid: n/a;
Probability of enrollment: n/a.
Students: Number of observations;
Price: 518;
Total grant aid: 409;
Need-based total grant aid: 409;
Total aid: 409;
Probability of enrollment: 518.
Schools; CA Schools:
Cornell University,
Duke University,
Georgetown University,
University of Notre Dame,
Vanderbilt University,
Wake Forest University,
Yale University;
Schools; Non-CA Schools:
Brandeis University,
Bryn Mawr College,
New York University,
Princeton University,
Tulane University,
University of Rochester,
Washington University at St. Louis.
Source: GAO analysis.
[A] Statistically significant at the 1 percent level or lower.
[B] Statistically significant at the 5 percent level or lower.
[C] Statistically significant at the 10 percent level or lower.
[D] The estimates are relative to non-financial aid applicants.
[E] The estimates are relative to high income students.
[F] The estimates are relative to white students.
Notes: Results are from tables 14 and 15, based on the coefficient in
equations 1 and 2. For instance, the value for price for financial-aid
applicants is based on the estimated coefficient FINAID* in table 14.
N/A means data are not available or applicable.
All the monetary values are in 2005 dollars.
[End of table]
Limitations of the Study:
Sample Selection bias:
The findings of the study could be limited by the potential of
selection bias if the CA schools had characteristics that we could not
control for that made them more inclined to adopt the consensus
approach and independently influenced the outcome variables. We believe
that this is not a serious problem with the estimation since the
difference-in-difference approach includes CA schools before the
implementation of the CA, implying the latter selection problem would
require significant change over a short time span in the character of
these schools. Furthermore, a key factor that might motivate schools to
join the 568 Group is the legacy of the Overlap group. The 568 Group
has objectives that are similar to those stated by the Overlap group--
to be able to offer financial aid to more needy students. Our test
indicated that the chances of a former Overlap group member joining or
not joining the 568 Group did not differ between the two groups of
schools in our sample.[Footnote 74] Thus, the similarity between the
two groups, in terms of a school joining the 568 Group, implied the
potential for selection bias may be small.
Measures of Price:
In our analysis, the total grant aid does not include self-help aid
(loans and work study). However, if the true amount of total grant aid
should include some proportion of self-help aid, then its exclusion
would lead to an underestimation of total grant aid. Nonetheless, we
believe this did not significantly affect our results since we found
that the consensus approach implementation did not affect self-help
aid.
Early Decision Admissions:
It may be that early admit students pay higher prices because early
decision admission might be used by need-blind schools as a screening
mechanism to indirectly identify a student's willingness-to-pay. Under
the early decision process a non-financial aid student is therefore
more likely to be admitted than a financial-aid student of comparable
quality.[Footnote 75] We did not expect the early decision process to
affect our results because while the process might help identify a
student with a higher willingness to pay, it is the student's ability
to pay that determines the need-based aid offered by the 568 Group.
Furthermore, the total probability of enrollment of a financial-aid
applicant was similar to that of a non-financial aid applicant both
before and after the consensus approach implementation, even though the
consensus approach implementation tended to decrease the likelihood of
enrollment of financial-aid students.
Excluded Schools of Comparable Selectivity:
We could not include all the schools affiliated with the 568 Group in
the analysis because of data limitations. (See the list of unmatched
treatment schools in table 9.) However, there were several similarities
(in terms of "best college" ranking, endowment, tuition and fees, and
percentage of tenured faculty) as well as differences (in terms of
freshmen enrollment) between the included and excluded CA colleges.
Limited Data Availability:
The data were available for only one academic year period after
implementation of the consensus approach. This could mask potential
effects of the consensus approach since these effects could be gradual,
rather than immediate, and therefore take time to for the effects to be
captured. Also, the small sample size of the data could make the
estimates less precise, especially for some of the subgroups of
students we considered. However, we checked to ensure that the
estimates were consistent with the data by estimating the predicted
values corresponding to the observed mean values for price, the key
variable of interest, and the financial aid variables. The results,
presented in table 19, show that the predictions of our model are
consistent qualitatively with the observed data.
Table 19: Comparison of Observed and Predicted Price and Financial Aid
Variables in CA and Non-CA Schools: Pre--and Post--Consensus Approach
Implementation Period:
Price; All students; Observed;
CA Schools: 1995-1996: $28,039;
CA Schools: 2003-2004: $35,488;
CA Schools: Difference: $7,449;
Non-CA Schools: 1995- 1996: $28,068;
Non-CA Schools: 2003-2004: $30,838;
Non-CA Schools: Difference: $2,770.
Price; All students; Predicted;
CA Schools: 1995-1996: $30,791;
CA Schools: 2003-2004: $37,171;
CA Schools: Difference: $6,380;
Non-CA Schools: 1995- 1996: $25,386;
Non-CA Schools: 2003-2004: $27,882;
Non-CA Schools: Difference: $2,496.
Price; Financial-aid; Observed;
CA Schools: 1995-1996: $25,845;
CA Schools: 2003-2004: $32,897;
CA Schools: Difference: $7,052;
Non-CA Schools: 1995- 1996: $24,960;
Non-CA Schools: 2003-2004: $29,705;
Non-CA Schools: Difference: $4,745.
Price; Financial-aid; Predicted;
CA Schools: 1995-1996: $28,222;
CA Schools: 2003-2004: $34,352;
CA Schools: Difference: $6,130;
Non-CA Schools: 1995- 1996: $22,347;
Non-CA Schools: 2003-2004: $27,330;
Non-CA Schools: Difference: $4,983.
Price; Non financial-aid; Observed;
CA Schools: 1995-1996: $34,645;
CA Schools: 2003-2004: $44,504;
CA Schools: Difference: $9,859;
Non-CA Schools: 1995- 1996: $37,714;
Non-CA Schools: 2003-2004: $44,292;
Non-CA Schools: Difference: $6,578.
Price; Non financial-aid; Predicted;
CA Schools: 1995-1996: $38,771;
CA Schools: 2003-2004: $46,625;
CA Schools: Difference: $7,854;
Non-CA Schools: 1995- 1996: $35,127;
Non-CA Schools: 2003-2004: $34,973;
Non-CA Schools: Difference: -$154.
Price; Low income; Observed;
CA Schools: 1995-1996: $12,566;
CA Schools: 2003-2004: $10,095;
CA Schools: Difference: -$2,471;
Non-CA Schools: 1995-1996: $18,950;
Non-CA Schools: 2003-2004: $21,886;
Non-CA Schools: Difference: $2,936.
Price; Low income; Predicted;
CA Schools: 1995-1996: $14,272;
CA Schools: 2003-2004: $11,389;
CA Schools: Difference: -$2,833;
Non-CA Schools: 1995-1996: $13,613;
Non-CA Schools: 2003-2004: $18,106;
Non-CA Schools: Difference: $4,493.
Price; Lower-middle-income; Observed;
CA Schools: 1995-1996: $19,220;
CA Schools: 2003-2004: $30,437;
CA Schools: Difference: $11,217;
Non-CA Schools: 1995-1996: $17,623;
Non-CA Schools: 2003-2004: $20,546;
Non-CA Schools: Difference: $2,923.
Price; Lower-middle-income; Predicted;
CA Schools: 1995-1996: $20,650;
CA Schools: 2003-2004: $32,075;
CA Schools: Difference: $11,425;
Non-CA Schools: 1995-1996: $15,156;
Non-CA Schools: 2003-2004: $19,501;
Non-CA Schools: Difference: $4,345.
Price; Middle-income; Observed;
CA Schools: 1995-1996: $24,785;
CA Schools: 2003-2004: $34,201;
CA Schools: Difference: $9,416;
Non-CA Schools: 1995- 1996: $22,560;
Non-CA Schools: 2003-2004: $26,069;
Non-CA Schools: Difference: $3,509.
Price; Middle-income; Predicted;
CA Schools: 1995-1996: $26,035;
CA Schools: 2003-2004: $36,438;
CA Schools: Difference: $11,838;
Non-CA Schools: 1995-1996: $21,092;
Non-CA Schools: 2003-2004: $20,764;
Non-CA Schools: Difference: -$328.
Price; Upper-middle-income; Observed;
CA Schools: 1995-1996: $26,285;
CA Schools: 2003-2004: $32,310;
CA Schools: Difference: $6,025;
Non-CA Schools: 1995- 1996: $29,429;
Non-CA Schools: 2003-2004: $34,305;
Non-CA Schools: Difference: $4,876.
Price; Upper-middle-income; Predicted;
CA Schools: 1995-1996: $31,423;
CA Schools: 2003-2004: $35,121;
CA Schools: Difference: $3,698;
Non-CA Schools: 1995- 1996: $26,566;
Non-CA Schools: 2003-2004: $27,616;
Non-CA Schools: Difference: $1,050.
Price; High income; Observed;
CA Schools: 1995-1996: $32,616;
CA Schools: 2003-2004: $39,496;
CA Schools: Difference: $6,880;
Non-CA Schools: 1995- 1996: $33,137;
Non-CA Schools: 2003-2004: $34,138;
Non-CA Schools: Difference: $1,001.
Price; High income; Predicted;
CA Schools: 1995-1996: $35,538;
CA Schools: 2003-2004: $41,043;
CA Schools: Difference: $5,505;
Non-CA Schools: 1995- 1996: $31,129;
Non-CA Schools: 2003-2004: $32,582;
Non-CA Schools: Difference: $1,453.
Financial aid--; All students; Total grant aid; Observed;
CA Schools: 1995-1996: $9,142;
CA Schools: 2003-2004: $9,775;
CA Schools: Difference: $633;
Non-CA Schools: 1995-1996: $13,391;
Non-CA Schools: 2003-2004: $13,960;
Non-CA Schools: Difference: $569.
Financial aid--; All students; Total grant aid; Predicted;
CA Schools: 1995-1996: $10,285;
CA Schools: 2003-2004: $11,877;
CA Schools: Difference: $1,592;
Non-CA Schools: 1995- 1996: $12,181;
Non-CA Schools: 2003-2004: $13,194;
Non-CA Schools: Difference: $1,013.
Financial aid--; All students; Need-based grant aid; Observed;
CA Schools: 1995-1996: $7,771;
CA Schools: 2003-2004: $6,439;
CA Schools: Difference: -$1,332;
Non-CA Schools: 1995-1996: $11,863;
Non-CA Schools: 2003-2004: $8,122;
Non-CA Schools: Difference: -$3,741.
Financial aid--; All students; Need-based grant aid; Predicted;
CA Schools: 1995-1996: $7,443;
CA Schools: 2003-2004: $6,170;
CA Schools: Difference: -$1,273;
Non-CA Schools: 1995- 1996: $12,277;
Non-CA Schools: 2003-2004: $9,151;
Non-CA Schools: Difference: -$3,126.
Financial aid--; Total aid; Observed;
CA Schools: 1995-1996: $16,604;
CA Schools: 2003-2004: $16,046;
CA Schools: Difference: -$558;
Non-CA Schools: 1995- 1996: $19,827;
Non-CA Schools: 2003-2004: $22,255;
Non-CA Schools: Difference: $2,428.
Financial aid--; Total aid; Predicted;
CA Schools: 1995-1996: $17,998;
CA Schools: 2003-2004: $17,957;
CA Schools: Difference: -$41;
Non-CA Schools: 1995- 1996: $18,425;
Non-CA Schools: 2003-2004: $20,127;
Non-CA Schools: Difference: $1,702.
Source: GAO analysis.
[End of table]
[End of section]
Appendix III: Classification of 1999-2000 Academic Year and Schools
Only Attending the 568 Group Meetings:
We conducted tests to determine whether to use data collected in
academic year 1999-2000 and whether schools that attended meetings of
the 568 President's group but did not implement the consensus approach
could be included in our analysis. First, the academic year 1999-2000
was very close to the establishment of the 568 President's Group, which
occurred in 1998. The 1999-2000 academic year might have been a
transitional period, and it would therefore not be appropriate to use
the data as part of the period before the 568 Group implemented the
consensus approach. Second, there were five schools, among the schools
with data available for our econometric analysis, that either only
attended the 568 Group meetings (Case Western Reserve University,
Stanford University, and University of Southern California) or were
members of the 568 Group but had not implemented the CA as of 2003
(Brown University and Dartmouth College). We therefore investigated
which group--control or treatment--each of the five schools belonged.
Does Academic Year 1999-2000 belong to the Pre-or Post-Consensus
Approach Implementation Period?
We used the data for sample 4 to investigate if data collected in 1999-
2000 belonged in the pre-CA period (with data collected in 1995-1996).
Although both samples 1 and 4 have data for 1995-1996 and 1999-2000, we
chose sample 4 because it was the larger sample. See table 9 in
appendix II for the list of the schools in each sample and the academic
years for which data were available.
The tests were performed using the Chow test, which is of the
form:[Footnote 76]
(1) (See PDF for image) and:
(2) (See PDF for image).
Pooling the two groups of data we estimated,
(3) (See PDF for image):
where g2 is an indicator variable.
The test examines the hypothesis that the added coefficients are
jointly zero: (See PDF for image).
An insignificant test statistic (a small test statistic and a large p-
value) suggests that the above equality holds, and there is no
difference between the estimates for 1999-2000 and the group with which
it is compared (1995-1996). On the other hand, a significant statistic
(a large test statistic and a small p-value) suggests that the above
equality does not hold and the 1999-2000 is different from the group
with which it is compared (1995-1996).
We combined 1999-2000 with 1995-1996 and tested if the coefficients for
1999-2000 differed from that of 1995-1996, using sample 4. The tests
were done for price, the key variable affecting student outcomes for
schools. We performed a joint test that the added coefficients in
equation 3 are jointly zero. The F-value is 1.71, and significant with
a p-value of 0.0375. This implied that data collected in 1999-2000 did
not belong to with the 1995-1996 data in the pre-CA period.[Footnote
77]
Similarly, we examined if 1999-2000 belonged to the post-CA period by
combining 1999-2000 with 2003-2004, using sample 3. The F-value of the
joint test is 8.36, and significant with a p-value of 0.0. This implied
that 1999-2000 data did not belong to with the 2003-2004 data in the
post-CA period.
These results suggest that it was more appropriate to exclude 1999-2000
from the analysis, implying that samples 1 and 2, which have data for
the pre-CA period (1995-1996) and the post-CA period (2003-2004) would
be more appropriate. However, because sample 2 was larger than sample
1, our subsequent analysis used sample 2.
Do the Schools That Only Attended the 568 group Meetings belong to the
Control or Treatment Group?
We performed an analysis similar to that described above to determine
whether schools that only attended meetings--Brown University, Case
Western Reserve University, Dartmouth College, Stanford University, and
University Southern California (USC)--belonged in the treatment or
control group. We determined whether the behavior of each of these
schools was more consistent with the control schools or the treatment
schools after the consensus approach implementation, using data for
2003-2004. Since we had determined from the above analysis that samples
1 and 2 are more appropriate for our subsequent analysis, we focus on
sample 2, the larger sample, for these tests.[Footnote 78]
To Which Group Did Brown Belong--Control or Treatment?
Similar to the analysis in section above, we included Brown in the
control group and tested if the coefficients for Brown differed from
the control group. We performed a joint test and obtained an F-value of
25.68, significant at 0.00. This implied that Brown did not belong to
the control group. For the treatment group test, the F-value was 7.37,
significant at 0.00. This also implied that Brown did not belong to the
treatment group. Thus, Brown did not belong to either the control or
treatment group.
To Which Group Did Stanford Belong--Control or Treatment?
The F-value for the control group test was 19.16, significant at 0.00,
and the F-value for the treatment group test was 5.59, significant at
0.00. This implied that Stanford did not belong to either the control
or treatment group.
To Which Group Did USC Belong--Control or Treatment?
We tested for which group USC belonged by excluding the SAT scores
variable (SCORESAT) from the model since the data were not available
for 2003-2004. The F-value for the control group test was 23.23,
significant at 0.00, and the F-value for the treatment group test was
12.54, significant at 0.00. This implied that USC did not belong to
either the control or treatment group.
Based on the above analysis, we determined that the best data for our
analysis was sample 2, and we excluded all five schools that only
attended the 568 Group meetings but did not implement the consensus
approach.
[End of section]
Appendix IV: Comments from 568 Presidents' Group:
Williams College Williamstown, Massachusetts 01267:
Morton Owen Schapiro:
President & Professor of Economics:
P.O. Box 687:
TEL: (413) 597-4233:
FAX: (413) 597-4015:
E-mail: mschapiro@williams.edu:
September 5, 2006:
To: Andrea Sykes:
United States Government Accountability Office:
From: Morton Owen Schapiro:
Chairman of the 568 Presidents' Group and:
President and Professor of Economics, Williams College:
Re: A Response to the Draft Report on the Activities of the 568 Group:
Thank you very much for providing the opportunity to respond to your
draft report on the activities associated with the 568 Presidents'
Group and its use of the Consensus Approach methodology. As you agreed
in communication with Jim Belvin, chairman of the 568 Group's Technical
Committee, your draft report has now been reviewed by a number of
financial aid directors from 568 schools, by several of our government
relations experts, and by a group of economists with special expertise
in education finance (I am a proud member of this last group). I am
happy to respond on behalf of all these individual reviewers.
In summary, while we appreciate the fact that the GAO has completed
another in a long line of careful and objective reports, we have a
number of questions about the data as presented and analyzed in your
draft report and, perhaps even more importantly, about its premise and
tone.
The Premise for the Study and the Tone of the Draft:
The anti-trust statute upon which the 568 exemption is granted
provides, among other things, need-blind institutions the right to
create a common approach for determining parent ability to pay. We
believe that the 568 Presidents' Group has developed a carefully
crafted methodological construct. The 568 Presidents' Group and this
new methodology have resulted in the following positive outcomes:
* the aid system is now more transparent, reducing confusion among
parents and students;
* by pioneering a variety of new approaches, some adopted nationally
via The College Board and its institutional methodology, we have
redefined family ability to pay in a fairer and more logical manner;
* we have provided the 568 Group's financial aid community with a forum
for discussing ways in which college applicants and their parents can
be better served as they seek ways to finance their higher education
expenses;
* we have empowered aid directors to exercise carefully defined
professional judgment in support of students with unusual
circumstances;
* we have increased the number of schools that are need-blind as
several institutions have adopted that practice in order to gain
membership in the 568 Group community; and:
* we have engaged college presidents more fully in setting policy for
the administration and distribution of financial aid grant resources on
their campuses.
At the same time, we have avoided the worries raised when the exemption
was first issued. There is no evidence that exempting our institutions
from antitrust laws has stifled competition or that there has been any
collusion aimed at reducing student aid expenditures at member
institutions. To the contrary, our efforts have led to increased access
to need-based financial aid, an increase in the average need-based
grant awarded to students attending both 568 Group and other
institutions, increased need-based grant funding available to low-
income students, and increased need-based grant funding for middle-
income students.
The combination of a range of positive impacts, along with the complete
absence of any evidence of individuals being hurt through this limited
anti-trust exemption, implies strongly that the public interest has
been served by the 568 exemption. We respectfully suggest that the tone
of your report - including its title - presents a somewhat misleading
picture of the substance of your findings. An alternative title could
be "Schools' Use of the Antitrust Exemption Enhances Transparency and
Equity Without Increasing the Net Price."
We turn next to some concerns and suggestions regarding your empirical
analysis. Those of us experienced in these kinds of studies know very
well that data limitations hinder even the most careful analyses.
Treatment and Control Groups-the Selection Process:
We worry that the selection process for the treatment and control
institutions may have biased your empirical results. We note, for
example, that Princeton, the wealthiest (in terms of endowment per
student) and most generous institution in the country, is included in
the Control Group while MIT, one of the most generous 568 institutions,
was left out of the Treatment Group (you indicate that MIT was excluded
because they failed to submit SAT data while officials at MIT state
that all data were submitted as requested). We believe that the
construction of these groups would almost certainly serve to lower
average grants for the Treatment Group while increasing average grants
for the Control Group.
Much is made of the apparent increase in so-called merit awards. In
reviewing the actions of the Treatment Group, we find that non-
athletic, merit awards have increased very little, if at all. This
would appear to be confirmed by Figure 4 on page 18. We do note that
four of the institutions included in the Treatment Group offer athletic
merit scholarships while only one of the institutions included in the
Control Group awards funds based on athletic merit. We believe that
this fact has served to skew the data by suggesting that non-need-based
aid funding has increased at a faster rate than has need-based aid.
Given that almost thirty institutions helped craft the Consensus
Approach and have implemented it in one fashion or another, analyzing
the results of only seven almost certainly skews the data. Why, for
example, include only research universities? And why not include
Amherst and Williams, both full participants in the creation and
implementation of the Consensus Approach?
The Use of Low-Income Students as a Standard of Comparison:
We have serious worries about the use of low-income students as a
yardstick for judging the success of the Consensus Approach. While we
understand that the GAO has every right to choose the standard by which
the Consensus Approach is judged, we would make several points in this
regard:
* The Federal Methodology (FM) establishes maximum aid eligibility for
students receiving federal funds. This expected family contribution
(EFC) is based on consideration of the parents' (custodial and step-
parent if appropriate) and a student's ability to support educational
expenses during the enrollment period. The Consensus Approach, with the
exception of assets saved in the student's name, judges only the
parent's ability to support educational expenses. Summer savings
expectations, which constitute the largest portion of the student
contribution, are established individually by Consensus Approach
schools. As 568 institutions use the Consensus Approach for the Parent
Contribution rather than EFCs, it is inappropriate to compare EFCs
established by participating institutions with those established by the
Federal Methodology.
* The "overaward provision" embedded in federal Title IV regulations
establishes an EFC cap for each student receiving federal student aid.
Institutions may not lower the student's FM EFC without documentable
cause or the exercising of professional judgment. Further, low-income
EFCs are almost all income driven. FM does not provide institutions
with the option of eliminating or reducing reported and continuing
family income.
In this regard, it is essential to point out that FM EFCs are not
always consistent with EFC results as developed by the Consensus
Approach. In fact, recent changes in the FM state tax tables have
resulted in FM EFCs that often exceed those generated by the Consensus
Approach. As a result, 568 institutions are increasingly forced to
increase contributions above the levels set by the Consensus Approach
simply to avoid violating the federal Title IV "overaward" provision.
Said another way, average Consensus Approach contributions are higher
than they would otherwise be because of the need to comply with the
federal overaward provision. This, of course, lowers the amount of need-
based grant available to students.
* The changes to the Institutional Methodology (IM) made by the 568
Group when creating the Consensus Approach were driven by policy rather
than results. To that end, we focused on IM policies and practices
that, in our judgment, failed to recognize the "paying for college"
realities faced by today's families. The cost-of-living tables
developed by our group are a perfect example. Although our efforts
specifically did not target particular income groups, we did make
common sense changes that we felt would expand access and encourage
families to look ahead and begin planning for college. These changes
ultimately affected families with resources, including considerable
amounts of home equity, funds saved in their children's names, etc.
Because middle-and upper-middle- income families are more likely to
have such resources, they are also more likely to benefit from
Consensus Approach changes. Likewise, low- income families benefit from
the Consensus Approach if they have or acquire such resources.
* Finally, we would be remiss if we did not reiterate our concern with
your interpretation of Congressional intent. In reviewing the exemption
and the discussions that surrounded the creation and extension of
Section 568, we did not interpret Congressional intent to have focused
on making college more affordable for low-income students or other
under-represented groups. Instead, we understood Congress to have had a
more general interest in creating a stable environment grounded in
common sense that reduced confusion among applicant families, began to
moderate parent contributions, and retained and expanded public
confidence in need-based aid as a vehicle for helping to insure access
to higher education opportunities.
The 568 Presidents' Group Serves as a Workshop for Need-Analysis Theory
and Practice:
As noted earlier, the work of the 568 Presidents' Group as reflected in
the Consensus Approach, has served to influence the more broadly used
Institutional Methodology. Additionally, many institutions have
unilaterally incorporated various aspects of the Consensus Approach
into their individual institutional need-analysis methodologies. The
effect of this intellectual cross pollination should not be overlooked
as it has, no doubt, served to reduce the differences in results across
a wider group of institutions.
To this point, an important, but overlooked aspect of the 568 exemption
is that it has allowed qualified institutions to work collectively to
refine and improve the manner in which family ability to pay is
defined. Almost all 568 Group institutions are spending additional need-
based grant funds as a result of the more generous Consensus Approach
and its flattening of parent contributions. Absent the 568 antitrust
exemption, this important benefit would be lost.
Data Concerns:
The following comments address our concerns about data collection and
interpretation.
* The study indicates on pages 17-18 that, over five years, average
need- based grant awards for the Treatment Group increased by 6% while
costs of attendance increased by 13%. Data available to the 568 Group
suggest that the former figure may be low. Of the four institutions in
the Treatment Group that are also members of the Consortium on
Financing Higher Education (Cornell, Duke, Georgetown, and Yale), data
from that organization indicate that during the four-year period (2000-
1 to 2004- 5) for which such numbers are available, average grant aid
increase by 28% (inflation adjusted) from $16,690 to $21,832. While the
data from the other three non-COFHE schools in the Treatment Group may
mitigate these figures some, your 6% figure still strikes our
collective experience and intuition as being far too low.
* In figure 1, page 7, the cost of attendance includes "family" and
disability expenses. Federal cost of attendance rules specify that cost-
of-living expenses may include only those incurred by the enrolled
student, not the family. Disability expenses are included only where
such expenses can be shown to be non-discretionary and unreimbursed.
* Table 1, page 8, indicates that a cost-of-living variance is not
included in the Institutional Methodology. In fact, the Institutional
Methodology has adopted the cost-of-living tables developed by the 568
Group.
* Page 9 notes that twenty-eight schools formed a group that, among
other things, developed a common methodology for assessing financial
needs. In fact, the work of the 568 Group has been limited to
developing a Consensus Approach for determining Parent Contributions.
Need is a product of many factors, including each institution's cost of
attendance, summer savings requirements, and packaging policies.
* Page 10 indicates that membership is open to institutions that, among
other things "pay membership dues." This is technically incorrect.
Participating institutions share the Group's expenses but pay no
membership dues.
* Footnote 7 on page 10 indicates that Macalester College attended
meetings but did not join the 568 Group. Although Macalester later
withdrew from the Group because it was no longer eligible, it was a
founding member.
* Paragraph 2 on page 11 indicates that "Some school officials also
noted that awarding aid only on the basis of need was a very
contentious issue and would greatly limit the number of schools willing
to participate in the group." In fact, several 568 institutions make
merit awards. There have been no discussions about limiting a
participating institution's desire to award merit aid.
* Table 3 on page 13 indicates that the Institutional Methodology and
the Consensus Approach treat divorced and separated parents in the same
manner. In fact, the Consensus Approach developed an innovative
approach for such families. This approach has in large part been
adopted by the Institutional Methodology.
* Comparing pricing practices at 568 Group schools with those at all
other private 4-year schools seems inappropriate. There are over a
thousand independent colleges and universities in the U.S., almost all
of which are ineligible for 568 Group membership because they are not
need-blind and few of which would be interested in making use of the
Consensus Approach or, for that matter, the Institutional Methodology.
* Figure 3, page 17 indicates that the number of students receiving
various types of institutional grant aid increased and then decreased
during the period from 2000 to 2006. While this is likely true, it
should be noted that this is a predictable result of an improving
economy. As families' circumstances improve, their ability to support
educational expenses increases while their aid eligibility decreases.
The number receiving aid will likewise increase if and when the economy
declines.
* In Table 5 and Table 16 the report notes that total need-based grant
aid is $20,221 higher per student, on average, at CA schools. This
seems to be inconsistent with other data presented in the report. For
example, Table 13 indicates that the average need-based grant for
middle-income students was only $10,767 in 2003-2004.
* A number of conclusions appear to have been based on a very small
number of observations, all within one academic year. Table 12 on page
46, for example, reports on students not receiving aid at CA schools
using only 19 observations while only 6 observations are used to report
similar data for non-CA schools.
Likewise, Table 13 on page 47 characterizes 2003-2004 low-income data
for CA institutions using only 3 observations. The 2003-2004 lower-
middle-income data at non-CA schools is based on 5 observations.
Limitations of the Study:
Sample Selection Bias:
This observation states "Furthermore, a key factor that might motivate
schools to join the 568 Group is the legacy of the Overlap group." (p.
69) In fact, only six members of the 28 member 568 Group were also
members of the Overlap group. It should be noted that Overlap group
institutions actually compared results and tried to agree on a common
response. Members of the 568 Group have used the antitrust exemption to
accomplish the purpose for which it was intended, i.e., the creation of
a common approach to need analysis managed locally by individual
institutions. Results are not compared nor are they standardized.
Early Decision Admissions:
This observation notes "It is likely that early admit students tend to
pay full price because early decision admission can be used by need-
blind schools as a screening mechanism to indirectly identify a
student's willingness-to-pay." (p. 69) Although many 568 institutions
use the Consensus Approach for early decision, the fact that each of
these schools is need-blind means that the decision to admit is made
before aid eligibility is determined. Moreover, early decision programs
have traditionally resulted in yields far in excess of regular decision
programs. Yields are often above 90% because students who apply for
early decision have determined that they will attend if they are
admitted and offered aid.
Post-treatment Period:
The draft report notes "The data were available for only one academic
year period after implementation of the Consensus Approach. This could
mask potential effects of the consensus approach since these effects
could be gradual, rather that immediate, and therefore take time (to)
for the effects to be captured." (p. 70) We certainly agree with this
point, but would suggest that no conclusions be reached until
additional results are available for review.
Summary:
Although the 568 Presidents' Group and its Consensus Approach to
determining parent ability to pay are relatively new phenomena, we
believe that your study confirms the value of the 568 antitrust
exemption and the manner in which it has been used. Its successes
include an increase in average need-based grant funding, enhanced
transparency, improved ability for families to plan for future
educational expenses, greater public confidence in need-based aid, more
engagement by presidents in aid-related discussions, and growth in the
number of institutions offering need-blind admissions. As a result of
these successes, we believe that the work of the 568 Presidents' Group
should be celebrated and promoted. We would encourage you to reflect
this success in your report to Congress.
Thank you very much for providing us with the opportunity to respond to
your draft report.
[End of section]
Appendix V: Consultants and Peer Reviewers:
Hashem Dezhbakhsh, Ph.D.
Professor of Economics:
Emory University:
Dennis Epple, Ph.D.
Thomas Lord Professor of Economics:
Graduate School of Industrial Administration:
Carnegie Mellon University:
Janet Netz, Ph.D.
Founding Partner:
ApplEcon LLC:
Richard Romano, Ph.D.
Gerald L. Gunter Professor of Economics:
Department of Economics:
Warrington College of Business:
University of Florida:
Lawrence White, Ph.D.
Arthur E. Imperatore Professor of Economics:
Department of Economics:
Leonard N. Stern School of Business:
New York University:
Gordon C. Winston, Ph.D.
Orrin Sage Professor of Political Economy, Emeritus:
Director of the Williams Project on the Economics of Higher Education:
Department of Economics:
Williams College:
[End of section]
Appendix VI: GAO Contact and Staff Acknowledgments:
GAO Contact:
Cornelia M. Ashby, Director, (202) 512-7215:
Staff Acknowledgments:
The following individuals made important contributions to the report:
Sherri Doughty, Assistant Director; Andrea Sykes; John A. Karikari;
Angela Miles; Daniele Schiffman; John Mingus; Dayna Shah; Richard
Burkard; Susan Bernstein; Rachel Valliere; Robert Alarapon; Thomas
Weko; and L. Jerome Gallagher.
[End of section]
Bibliography:
Avery, C. and C. Hoxby."Do and Should Financial Aid Packages Affect
Students' College Choices?" National Bureau of Economic Research
Working Paper, No. 9482. 2003.
Bamberger, G., and D. Carlton."Antitrust and Higher Education: MIT
Financial Aid (1993)." Case 11. The Antitrust Revolution (Third
Edition: 1993).
Carlton, D., G. Bamberger, and R. Epstein. "Antitrust and Higher
Education: Was There A Conspiracy to Restrict Financial Aid?" RAND
Journal of Economics, vol. 26, no. 1 (Spring 1995): 131-147.
Epple, D., R. Romano, S. Sarpca, and H. Sieg. "Profiling in Bargaining
Over College Tuitions," unpublished paper. January 21, 2005.
Hill, C., and G. Winston. "Access: Net prices, Affordability, and
Equity At a Highly Selective College." unpublished paper. December
2001.
Hill, C., G. Winston, and S. Boyd. "Affordability: Family Incomes and
Net Prices at Highly Selective Private Colleges and Universities." The
Journal of Human Resurces, vol. XL, no. 4 (2005): 769-790.
Hoxby, C. "Benevolent Colluders? The Effects of Antitrust Action on
College Financial Aid and Tuition." National Bureau of Economic
Research Working Paper, No. 7754. June 2000.
Kim, M. "Early Decision and Financial Aid Competition Among Need-Blind
Colleges and Universities." unpublished paper. May 1, 2005.
Morrison, R. "Price Fixing Among Elite Colleges and Universities," The
University of Chicago Law Review, vol. 59 (1992): 807-835.
Netz, J. "Non-Profits and Price-Fixing: The Case of the Ivy League."
unpublished paper. November 1999.
Netz, J. "The End of Collusion?: Competition After Justice and the Ivy
League Settle." unpublished paper. Fall 2000.
Salop, S., and L. White. "Antitrust Goes to College," Journal of
Economic Perspectives, vol. 5, no. 3 (Summer 1991): 193-2002.
Shepherd, G. "Overlap and Antitrust: Fixing prices in a Smoke-Filled
Classroom," The Antitrust Bulletin. Winter (1995): 859-884.
Winston, G., and C. Hill. "Access to the Most Selective Private
Colleges by High-Ability, Low-Income Students: Are They Out There?"
unpublished paper. October 2005.
FOOTNOTES
[1] The schools sued were: Brown University, Columbia University,
Cornell University, Dartmouth College, Harvard College, Massachusetts
Institute of Technology, Princeton University, University of
Pennsylvania, and Yale University.
[2] U.S. v. Brown, 5 F.3d 658 (3rd Cir. 1993). The Department of
Justice and MIT subsequently entered into a settlement agreement in
which MIT agreed to certain "Standards of Conduct."
[3] Pub. L. No. 103-325 (1992).
[4] Pub. L. No. 103-382 (1994).
[5] Pub. L. No. 107-72 (2001).
[6] Some financial aid is awarded to students based on merit rather
than financial need.
[7] The College Board is a not-for-profit membership association
composed of more than 5,000 schools, colleges, universities, and other
educational organizations. In conjunction with financial aid
professionals and economists, the College Board developed its own
methodology to measure a family's ability to pay for college.
[8] 568 refers to the section in the Improving America's Schools Act of
1994 where the exemption is contained.
[9] These schools were: California Institute of Technology, Case
Western University, Harvard University, Stanford University, Syracuse
University, and University of Southern California.
[10] Participation in the 568 Presidents' Group, however, does not
prohibit members from awarding merit aid.
[11] All dollar amounts are in 2005 dollars. Data presented for schools
using the exemption was collected from 26 of the 28 schools using the
exemption.
[12] Other private 4-year schools include not-for-profit institutions
and do not include for-profit institutions. This set of schools
includes schools that do not have need-blind admission policies and
therefore would not be able to participate in activities allowed under
the exemption.
[13] Comparable schools include the seven schools selected as control
schools for our econometric analysis.
[14] Variation was measured by the standard deviation of the EFCs.
[15] For a more detailed discussion of our analysis see appendix I.
[16] GAO's econometric analysis was focused on the mandate from
Congress that requires us to examine the effects of the exemption. It
is different from a market-specific analysis conducted in an antitrust
investigation, and is not intended to address whether or not conduct
may be taking place that might violate the antitrust laws in the
absence of the exemption.
[17] The results were similar for need-based institutional grant aid.
[18] The discussed effects of the consensus approach are statistically
significant (i.e., different from zero) at the 5 percent significance
level or less.
[19] For a more detailed discussion on our econometric models and the
limitations of our analysis see appendix II.
[20] We used the KSMIRNOV command in Stata to perform the tests.
[21] This theory is consistent with the idea that non-profit
organizations have an incentive to exercise market power despite not
directly capturing profits, because the extra resources from exercising
market power allow them to invest in other areas they deem important;
e.g., schools may charge high prices to students because it could
enable them to offer higher salaries to attract high-caliber faculty.
[22] Student enrollment data was obtained through linear interpolation,
and faculty data was based on 1998-1999 data.
[23] Where necessary, the data were supplemented by data from IPEDS.
[24] Schools were ranked annually based on various criteria (including
selectivity, faculty and financial resources, graduation rate, and
alumni satisfaction) in various publications--particularly in the
USNWR, the Peterson's Four-Year Schools, and the Barron's Profiles of
American Schools. The rankings of the schools by the different
publishers were generally similar, but since the data were readily
available in the USNWR we chose its rankings. Using the published
rankings helped avoid a possible bias from arbitrarily picking the
schools. Furthermore, these rankings were widely used and generally
stable over time.
[25] Although the observers were not members they attended the group's
meetings. The former members were Bowdoin College and Macalester
College.
[26] Liberal arts schools emphasize undergraduate education and award
at least half of their degrees in the liberal arts discipline, and most
are private. National universities offer a wide range of undergraduate
majors as well as master's and doctoral degrees, and many emphasize
research.
[27] The number of schools in the two tiers for each type of school was
between 50 and 90 for each year.
[28] We also used endowment data from NACUBO, and school-level data
from GAO's survey of the schools.
[29] We used data for students who were enrolled as freshmen, as of
October of the academic year, in the NPSAS database.
[30] Although the sample periods used by Hoxby (2000) and Netz (2000)
are much earlier than what we used, our list of schools is reasonably
consistent with theirs. Similarly, our list of schools was consistent
with the schools in the Consortium for Financing Higher Education
(COFHE), which are some of the most selective private schools in the
U.S.
[31] See appendix III for details of the tests.
[32] We did not separate the effects of the CA into the effects of only
attending the 568 Group meetings and the effects of only implementing
the CA, although some schools only attended meetings and had not
implemented the CA, because in table 9 there are only three schools in
sample 2 that would serve as treatments or serve as controls if we
investigate the effects of only attending meetings or the effects of
only implementing the CA, respectively.
[33] In addition to having the control schools, we also controlled for
a number of school characteristics that are discussed below. It is only
the possibility of changes in differences between treatment and control
schools that were not measurable or not observable that might lead to
bias in estimating the effects of the consensus approach
implementation. For example, schools adopting the consensus approach
might differ in their objectives concerning their preferred student
body. As discussed next in the text, the difference-in-difference
approach provided controls for such possibilities.
[34] All the dependent variables were from NPSAS, except tuition, which
was from IPEDS. We used the general price level instead of the price
index for higher education to adjust the monetary values because the
former better reflected potential substitution effects between college
education and other expenditures by households. Furthermore, sector-
specific price indexes generally tend to be more volatile.
[35] The tuition amount was the same for all freshmen in a private
school.
[36] We also estimated an equation for institutional grant aid
(AIDINSTGRT) and self-help aid (AIDSELFPLUS).
[37] We also estimated an equation for need-based institutional aid
(AIDNDINST) and non-need-based grant aid (AIDNONDTGRT), which was the
difference between total grant aid and need-based aid. However, we did
not have enough data to estimate merit-only aid.
[38] We relied on several previous studies, including Avery and Hoxby
(2003), Carlton et al. (1995), Bamberger and Carlton (1993), Epple et
al. (2005), Hill et al. (2005), Hoxby (2000), Kim (2005), Netz (1999,
2000), Hill and Winston (2001), Morrison (1992), Salop and White
(1991), Shepherd (1995), and Winston and Hill (2005).
[39] This variable was from the GAO survey of the CA and non-CA
schools.
[40] The CA schools are the 568 schools that have either implemented
the consensus approach fully or in part by implementing some of the
options under that need analysis methodology for financial aid. Of the
seven CA schools in sample 2 in table 9, only three had not fully
implemented the consensus approach (Georgetown, Vanderbilt, and Wake
Forest).
[41] All the school-level variables are from IPEDS.
[42] The school specific fixed-effects were estimated using the fixed-
effects estimator, where feasible. This effect captured differences
among the schools that did not vary over time, such as location,
memberships in athletic conferences and other organizations such as the
former Overlap group. Also, several school-level variables could not be
used in the models because the variables did not vary over time, and
were therefore expected to be captured by the school specific fixed-
effects.
[43] All the student-level variables were from NPSAS.
[44] We included Native Americans in OTHER because of their relatively
small numbers.
[45] To avoid the dummy-variable trap in the estimation, we excluded
white students from the racial groups, and high-income students from
the income groups.
[46] The EFC is the federal calculation, which differs significantly
from the EFC calculated by the CA schools, and to some extent from the
EFC calculated by the non-CA schools. We found a negative relationship
between the number of siblings and EFC using the limited data on
siblings, although the link was not strong.
[47] The reported values are probability-weighted.
[48] The reported values are probability-weighted.
[49] The panel data were unbalanced because there were different
observations on the freshmen for each school in each academic year. An
important purpose in combining cross-sectional and time series data was
to control for individual school-specific unobservable effects, which
may be correlated with the covariates in the models. An advantage of
using the fixed-effects estimator was that there was no need to assume
that the unobserved school-specific effects were independent of the
covariates. However, unlike the random-effects estimator, the fixed-
effects estimator did not allow the inclusion of time-invariant
variables, such as the former Overlap group and membership in sports
associations, as covariates.
[50] The weights are the probability weights from the number of
students in the sample for each school, and the robust estimates of the
standard errors are based on the Huber/White sandwich estimator. All
estimates were obtained using Stata.
[51] The same model specification is used to estimate the financial aid
equations, and tuition equation, which excludes the student-level
variables.
[52] In the estimated equations, the interaction terms between EMCA and
other variables have the suffixes "*;" for example ENDOWSTU* is the
interaction term between ENDOWSTU and EMCA.
[53] This effect can be tested as a linear restriction if the joint
test of significance of EMCA and the terms involving EMCA is
significant.
[54] White students are excluded from the race groups in the estimation
to avoid the dummy trap.
[55] The effects of these variables on tuition were expected to be
similar to that of price. On the other hand, the effects of these
school-level variables on the financial aid variables were expected to
be opposite to that of price.
[56] The statistical procedure we used is AREG in Stata.
[57] The regression estimates for the financial aid variables excluded
non financial-aid applicants, which reduced the number of observations
but not the number of schools. Similar results were obtained for the
price equation when the estimates were based on only financial-aid
applicants. The regression estimates for tuition were obtained by
excluding student-level variables because students at a school were
charged the same tuition.
[58] The $4,800 decrease is approximately equal to $250,000 x -
(0.01935).
[59] As discussed earlier, similar arguments can be obtained for the
tuition and financial aid variables.
[60] The model could not be estimated with school specific fixed-
effects because they predict successes or failures perfectly.
[61] In the estimated equations, the interaction terms between AY2003
and other variables have the suffixes "*;" for example INCLO* is the
interaction term between INCLO and AY2003.
[62] We could not use the panel data estimation technique for probit
(XTPROBIT) because of lack of convergence. Similar results were
obtained when the estimates were based on only students who applied for
financial-aid.
[63] Due to lack of sufficient data, we could not obtain separate
estimates of the effects of attending meetings only or the effects of
implementing the consensus approach only because it involved only two
schools--Brown and Stanford. Also, we could not obtain separate
estimates of the effects of implementing fully or partly the consensus
approach because only three of the seven CA schools in sample 2
(Georgetown, Vanderbilt, and Wake Forest) had not fully implemented the
CA.
[64] All tests are performed using the 5 percent or lower level of
significance.
[65] The results were similar when we limited the data to only students
who applied for financial aid.
[66] The effect of the consensus approach implementation on lower-
middle income was positive and significant at the 10 percent level. We
performed several tests for the total effects of the consensus approach
on prices. First, the effect was significant at the 5 percent level
when data for only students who applied for financial aid were used.
Second, the total effect of the CA on prices was $3,488 and significant
at the 5 percent level when ENROLUG and ENROLUG* were excluded from the
model. Third, because prices are bounded at the lower end at zero and
at the upper end at the cost of attendance, we also estimated the price
equation using Tobit regressions. The total effect of the consensus
approach on prices was negative and insignificant (at the 10 percent
level). Unlike the fixed-effects estimates, the Tobit estimates were
unweighted and the standard errors were not robust.
[67] The results are based on the seven CA and the seven non-CA schools
in tables 11 and 12. Similar results were obtained when we included the
schools that had no SAT scores in AY 2003-2004--three CA schools
(Boston, MIT, and Pennsylvania) and two non-CA schools (Tufts and
Yeshiva).
[68] The value of the effect of the CA on institutional grant aid was
$1,331, but not significant.
[69] The effect of the CA on need-based institutional aid was generally
similar to need-based total grant aid. The effect was about $6,020 and
significant at the 5 percent level, with a confidence interval of
between $512 and $11,528.
[70] The value of the effect of the CA on non-need-based grant aid was
estimated to be about -$6,873, though not significant; the F-test of
the joint significance of EMCA and its interactive terms had a p-value
of 14 percent, and the test of the total effect of the CA had a p-value
of 2.1 percent.
[71] The value of the effect of the CA implementation on self-help aid
(loans, including PLUS, and work study) was $1,034, but not
significant.
[72] The value of the total effect of the CA on total aid was estimated
to be about $7,140, though not significant; the F-test of the joint
significance of EMCA and its interactive terms had a p-value of 20
percent, and the test of the total effect of the CA had a p-value of
1.4 percent.
[73] The results for financial aid applicants are relative to non
financial aid applicants, those for the income groups are relative to
the high-income students, and those for the racial groups are relative
to the white students.
[74] We tested for the equality of the proportions of CA schools and
non-CA schools that were members of the former of the Overlap group. We
used the 11 CA schools and the 14 non-CA schools in samples 1 through 4
in table 9. The CA schools had 5 Overlap members and the non-CA schools
had 3 Overlap members.
[75] See Kim (2005).
[76] See [Hyperlink, http://www.stata.com/support/faqs/stat/chow3.html]
for details.
[77] As expected, the estimates from the pooling (equation 3) are the
same as for the separate estimates (equations 1 and 2). Also the
residual variances from equations 1 and 2 were similar, suggesting that
the pooling was appropriate. This applies to all the other Chow tests
we performed.
[78] The test was not performed for Case Western Reserve and Dartmouth
because they are in samples 4 and 3, respectively. Samples 3 and 4
cannot be used because there are no data for 1995-1996 and 2003-2004,
respectively.
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