    Higher Education: School's Use of the Antitrust Exemption Has Not
    Significantly Affected College Affordability or Likelihood of
    Student Enrollment to Date (21-SEP-06, GAO-06-963).

    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.
    -------------------------Indexing Terms-------------------------
    REPORTNUM:   GAO-06-963
        ACCNO:   A61250
      TITLE:     Higher Education: School's Use of the Antitrust Exemption
    Has Not Significantly Affected College Affordability or
    Likelihood of Student Enrollment to Date
         DATE:   09/21/2006
      SUBJECT:   Antitrust law
    	     College students
    	     Colleges and universities
    	     Comparative analysis
    	     Cost analysis
    	     Financial analysis
    	     Higher education
    	     Income statistics
    	     Price fixing
    	     Program evaluation
    	     Student financial aid

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    GAO-06-963

         * Results in Brief
         * Background
              * Legal History of Antitrust Exemption for Higher Education In
              * Determining a Student's Financial Need
         * Twenty-Eight Schools Used the Antitrust Exemption to Develop
              * Highly Selective Private4-Year Colleges and Universities For
              * Participating Schools Agreed to a Common Methodology for Ass
         * As the Cost of Attendance at Schools Using the Exemption Ros
              * Cost of Attendance Increased at Schools Using the Exemption
              * Percentage of Students Receiving Institutional Grant Aid and
         * Students Accepted to Both Schools Using the Exemption and Co
         * Implementation of a Common Methodology Has Not Significantly
         * Concluding Observations
         * Agency Comments
         * Appendix I: Statistical Analysis of Expected Family Contribu
         * Appendix II: Econometric Analysis of Effects of the Higher E
         * Theories of the Effects of the Consensus Approach on Financi
         * Sources of Data for the Model
         * Selection of Control Schools
              * Determination of the Appropriate Time Periods for Assessing
         * Specifications of Econometric Models and Estimation Methodol
              * Modeling the Effects of the Consensus Approach Methodology f
              * Comparison of Prices and Financial Aid in CA and Non-CA Scho
              * Model Specifications and Estimation Methodology
         * Estimation Results of the Effects of Attending Meetings and
              * Total Effects of Implementing the Consensus Approach (from t
              * Prior Levels and Differential Effects of the Consensus Appro
         * Limitations of the Study
              * Sample Selection bias
              * Measures of Price
              * Early Decision Admissions
              * Excluded Schools of Comparable Selectivity
              * Limited Data Availability
         * Appendix III: Classification of 1999-2000 Academic Year and
         * Does Academic Year 1999-2000 belong to the Pre- or Post- Con
         * Do the Schools That Only Attended the 568 group Meetings be
              * To Which Group Did Brown Belong-Control or Treatment?
              * To Which Group Did Stanford Belong-Control or Treatment?
              * To Which Group Did USC Belong-Control or Treatment?
         * Appendix IV: Comments from 568 Presidents' Group
         * Appendix V: Consultants and Peer Reviewers
         * Appendix VI: GAO Contact and Staff Acknowledgments
         * Bibliography
              * Order by Mail or Phone

    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

    Contents

    Letter 1

    Results in Brief 4
    Background 6
    Twenty-Eight Schools Used the Antitrust Exemption to Develop a Common
    Methodology for Assessing a Family's Financial Need 9
    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 15
    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 19
    Implementation of a Common Methodology Has Not Significantly Affected
    Affordability or Enrollment at Schools Using the Exemption 20
    Concluding Observations 23
    Agency Comments 23
    Appendix I Statistical Analysis of Expected Family Contributions at
    Schools Using the Exemption and Comparable Schools 27
    Appendix II Econometric Analysis of Effects of the Higher Education
    Antitrust Exemption on College Affordability and Enrollment 32
    Theories of the Effects of the Consensus Approach on Financial Aid 32
    Sources of Data for the Model 33
    Selection of Control Schools 34
    Specifications of Econometric Models and Estimation Methodology 38
    Estimation Results of the Effects of Attending Meetings and Implementing
    the Consensus Approach 62
    Limitations of the Study 70
    Appendix III Classification of 1999-2000 Academic Year and Schools Only
    Attending the 568 Group Meetings 74
    Does Academic Year 1999-2000 belong to the Pre- or Post- Consensus
    Approach Implementation Period? 74
    Do the Schools That Only Attended the 568 group Meetings belong to the
    Control or Treatment Group? 75
    Appendix IV Comments from 568 Presidents' Group 77
    Appendix V Consultants and Peer Reviewers 87
    Appendix VI GAO Contact and Staff Acknowledgments 88
    Bibliography 89

    Tables

    Table 1: Comparison of the Federal Methodology and the College Board's
    Base Institutional Methodology for Need Analysis 9
    Table 2: Schools Using the Antitrust Exemption, as of May 2006 10
    Table 3: Comparison of Consensus Approach Developed by Schools Using the
    Antitrust Exemption Compared to the College Board's Institutional
    Methodology 13
    Table 4: Number of Schools That Did Not Implement Certain Consensus
    Approach Options in School Year 2005-2006 14
    Table 5: Estimated Changes in Amount Paid, Financial Aid, and Enrollment
    at Schools Using the Consensus Approach Compared to Schools Not Using the
    Exemption 21
    Table 6: Schools Included in Analysis of Effects of Exemption 23
    Table 7: Summary Statistics of Expected Family Contributions 29
    Table 8: Tests of Variations in Expected Family Contributions 31
    Table 9: Control and Treatment Schools for Analyzing Effects of the
    Consensus Approach Implementation 37
    Table 10: Summary Statistics of Variables Used in Regression Analysis,
    1995-1996 and 2003-2004: CA Schools 45
    Table 11: Summary Statistics of Variables Used in Regression Analysis,
    1995-1996 and 2003-2004: Non-CA Schools 46
    Table 12: CA and Non-CA Schools: Price and Financial Aid 48
    Table 13: CA and Non-CA Schools-Financial Aid Applicants Only: Price and
    Financial Aid 49
    Table 14: Regression Estimates of Effects of Consensus Approach
    Implementation on Price, Tuition, and Enrollment 59
    Table 15: Regression Estimates of Effects of Consensus Approach
    Implementation on Financial Aid 61
    Table 16: Estimates of Effects of Consensus Approach Implementation on
    Affordability and Enrollment in CA Schools Relative to Non-CA Schools 65
    Table 17: Estimates of Affordability and Enrollment before the Consensus
    Approach Implementation for Particular Groups of Students in Both CA and
    Non-CA Schools 68
    Table 18: Differential Effects of Consensus Approach Implementation on
    Affordability and Enrollment in CA Schools for Particular Groups of
    Students 69
    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 72

    Figures

    Figure 1: Determining a Student's Financial Need 8
    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 16
    Figure 3: Percentage of Students at Schools Using the Antitrust Exemption
    Receiving Various Types of Institutional Grant Aid from 2000 to 2006 17
    Figure 4: Average Amount of Various Institutional Grant Aid Awards at
    Schools Using the Antitrust Exemption from 2000 to 2006 18

    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

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    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.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.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.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.4 The exemption was extended
    most recently in 2001, and is set to expire in 2008.5

    1The 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.

    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.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)

    2U.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."

    3Pub. L. No. 103-325 (1992).

    4Pub. L. No. 103-382 (1994).

    5Pub. L. No. 107-72 (2001).

    6Some financial aid is awarded to students based on merit rather than
    financial need.

    Figure 1: Determining a Student's Financial Need

    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.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.

    7The 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.

    Table 1: Comparison of the Federal Methodology and the College Board's
    Base Institutional Methodology for Need Analysis

                               Federal methodology     Institutional methodology
    Home equity             Not included.           Included.
    Family farm equity      Not included.           Included.
    Student assets          Included, 35 percent of Included, 25 percent of
                               student's net worth     student's net worth
                               expected to be used for expected to be used for
                               college costs. Minimum  college costs. Minimum
                               contribution from       contribution from student
                               student expected.       expected.
    Family assets           Excluded the assets of  Included a fuller range of
                               families whose income   family assets, such as
                               fell below $50,000 and  home equity, other real
                               who filed a simple tax  estate, and business and
                               return.                 farm assets.

                               12 percent of assets    5 percent of assets
                               expected to be used     expected to be used
                               towards college.        towards college.
    Divorced and separated  Excluded noncustodial   Included noncustodial
    families                parent income and       parent income and assets.
                               assets.
    (Noncustodial parent
    contribution)
    Total income            Included only the       Included in total income
                               adjusted gross income   any untaxed income and any
                               reported on federal tax paper depreciation and
                               returns, plus various   business, rental, or
                               categories of untaxed   capital losses that
                               income.                 artificially reduced
                                                       adjusted gross income.
    Medical/elementary and  Not included.           Included.a
    secondary school
    expenses
    Cost of living variance Not included.           Not included.b
    Number of siblings in   Included-divides the    Included-instead of
    college                 parental contribution   dividing by the number in
                               by the number of        college, parental
                               siblings enrolled in    contribution per student
                               college.                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.

    aElementary and secondary school expenses are an option that could be
    added by a school.

    bCost of living variance is an option that could be used by a school.

         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.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                       Middlebury College
    Boston College                        Northwestern University
    Brown University                      Pomona College
    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.

    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.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.

    8568 refers to the section in the Improving America's Schools Act of 1994
    where the exemption is contained.

    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.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.

    9These schools were: California Institute of Technology, Case Western
    University, Harvard University, Stanford University, Syracuse University,
    and University of Southern California.

    10Participation in the 568 Presidents' Group, however, does not prohibit
    members from awarding merit aid.

    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

                               Institutional methodology   Consensus approach
    Home equity             Included. No limit on       Included. Home value
                               amount considered asset     is capped at 2.4 times
                               available to pay for        income minus mortgage
                               college.                    debt.
    Family farm equity      Included.                   Included.
    Student and family      Included, but assets        Included. In general
    assets                  counted separately.         student assets-such as
                                                           prepaid and college
                               25 percent of student's net savings plans are
                               worth expected to be used   combined with family
                               for college costs.          assets. 5 percent of
                                                           family assets expected
                               5 percent of parent's       to be used for
                               assets expected to be used  college. Trust funds
                               for college costs.          will be considered on
                                                           a case by case basis.
    Divorced and separated  Included. Expects           Same as IM.
    families                noncustodial parent to
                               contribute towards college
    (Noncustodial parent)   costs.
    Total income/adjusted   Included in total income    Excluded business and
    gross income            any untaxed income and any  rental losses from
                               paper depreciation and      calculation of income.
                               business, rental, or
                               capital losses which
                               artificially reduced
                               adjusted gross income.
    Medical/elementary and  Included.a                  Included.
    secondary school
    expenses
    Cost of living variance Excluded.b                  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   Included-considers number   Same as IM.
    college                 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.
    One-time income         Not included.c              Excluded income that
    adjustment                                          was not received on an
                                                           annual basis, such as
                                                           unemployment income or
                                                           capital gains.
    Family debt             Not included.               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.

    aPrivate elementary and secondary school tuition allowed at the option of
    the institution.

    bAs an option schools can adjust living expenses based on geographic
    locations.

    cThis 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.

    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

                                                   Number of schools that did not
    Options in the consensus approach                        implement optiona
    Number of siblings in college                                            1
    One-time income adjustments                                              2
    Elementary and secondary school tuition
    expenses                                                                 3
    Medical expenses                                                         3
    Cost of living variances                                                 5
    Divorced and separated families                                          6
    Family and student assets                                                7
    Home equity                                                              7
    Family loan debt                                                         7

    Source: GAO analysis of schools' survey responses.

    aA total of 25 member schools used part or all of the consensus approach.

    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.11 For example, at other private 4-year
    schools there was a 7 percent increase in these costs, from $25, 204 to
    $27, 071.12 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.13

    11All dollar amounts are in 2005 dollars. Data presented for schools using
    the exemption was collected from 26 of the 28 schools using the exemption.

    12Other 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.

    13Comparable schools include the seven schools selected as control schools
    for our econometric analysis.

    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

    Note: Comparable schools include the seven schools selected as control
    schools for our econometric analysis.

    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

    Note: Data collected from 26 of the 28 schools using the antitrust
    exemption.

    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

    Note: Data collected from 26 of the 28 schools using the exemption.

    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.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.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.

    14Variation was measured by the standard deviation of the EFCs.

    15For a more detailed discussion of our analysis see appendix I.

         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.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.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.18

    16GAO'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.

    17The results were similar for need-based institutional grant aid.

    18The discussed effects of the consensus approach are statistically
    significant (i.e., different from zero) at the 5 percent significance
    level or less.

    Table 5: Estimated Changes in Amount Paid, Financial Aid, and Enrollment
    at Schools Using the Consensus Approach Compared to Schools Not Using the
    Exemption

                         Estimated changes of using the consensus
                                       approach on:
                         Amount  Total  Need-based                    Probability
                       students  grant total grant  Total aid (grant,          of
    Student group       paid    aid         aid loans, work-study)  enrollment
    All students                        $6,125b

                                            [$239,
                         $3,021  -$749    $12,011]            -$2,886         38%
    Financial-aid
    applicants         2,177    n/a         n/a                n/a          22
    Low-income                                             12,121b

                         -4,061  3,688       1,956    [1,837, 22,404]          59
    Lower-middle
    income           8,089 c -3,671       6,556             -7,776          95
    Middle income                       20,221a

                                           [6,718,
                          2,320  1,618     33,724]              1,178          26
    Upper-middle
    income            -1,048   -973       2,769             -3,054          18
    High income        3,699   -714      4,687c             -3,856          31
    Asian students                      14,628a

                                           [5,051,
                           -376  5,726     24,206]              3,694           1
    Black students     4,468 -1,227       4,332             -6,542         -26
    Hispanic                             9,532b
    students
                                           [1,006,
                          1,168  1,520     18,059]              3,648         108
    White students                       6,017b

                                             [178,
                          2,588   -491     11,856]             -2,879          19

    Source: GAO analysis (see table 16 in app. II).

    aResult is statistically significant at the 1 percent level or lower.

    bResult is statistically significant at the 5 percent level or lower.

    cResult 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.

    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.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).

    19For a more detailed discussion on our econometric models and the
    limitations of our analysis see appendix II.

    Table 6: Schools Included in Analysis of Effects of Exemption

                                            Comparable schools not using the
    Schools using the consensus approach consensus approach
    Cornell University Duke University   Brandeis University Bryn Mawr College
    Georgetown University University of  New York University Princeton
    Notre Dame Vanderbilt University     University Tulane University
    Wake Forest University Yale          University of Rochester Washington
    University                           University at St. Louis

    Source: GAO analysis.

    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 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.

    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

    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:

               o  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.

               o  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.

               o  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

                              Schools using the exemption    Comparable schools
                                     (568 schools)           (Non-568 schools)
                                    Type 1                    Type 1
    Students                   students   All students   students All students
    Statistic
    Standard deviation           $6,188         $6,447     $6,190       $7,035
    Mean                        $27,166        $31,640    $27,395      $28,747
                                 [$22,576,      [$30,380,  [$22,293,    [$27,924,
                                  $31,757]       $32,900]   $32,497]     $29,571]
    Coefficient of
    variation 1 (V1)               0.27           0.24       0.36         0.35
    Range                       $12,200        $12,886     $9,671       $8,813
    Median                      $30,374        $31,677    $29,225      $31,075
                                 [$25,380,      [$30,394,  [$23,858,    [$30,314,
                                  $35,367]       $32,961]   $34,593]     $31,836]
    Coefficient of
    variation 2 (V2)               0.47           0.49       0.52         0.37
    Number of students            N1=79       N1=1,158      N1=79     N1=2,866
                                     N2=76       N2=1,150      N2=76     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).

    Denoting the estimates of V1 and V2 for the two groups by and , and and ,
    the empirical distribution of was then compared with the empirical
    distribution of to examine whether and 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 , and.1
    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 and 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.

    1We used the KSMIRNOV  command in Stata to perform the tests.

    Table 8: Tests of Variations in Expected Family Contributions

                                 Alternative Test-statistic,
    Variable    Student Data     hypothesis  D               p-value Conclusion
    Coefficient Type 1 N1=79     Non-568     0.1013          0.445   EFCs are similar
    of          N2=79            EFCs are
    variation 1                  smaller     -0.1519         0.162   EFCs are similar
    (V1)
                                 Non-568                             Overall-EFCs are
                                 EFCs are                            similar
                                 larger
    Coefficient Type 1 N1=76     Non-568     0.1447          0.203   EFCs are similar
    of          N2=76            EFCs are
    variation 2                  smaller     -0.1053         0.431   EFCs are similar
    (V2)
                                 Non-568                             Overall-EFCs are
                                 EFCs are                            similar
                                 larger
    Coefficient All              Non-568     0.1724          0.000   Non-568 EFCs are
    of          N1=1,158N2=2,866 EFCs are                            smaller
    variation 1                  smaller     -0.1788         0.000
    (V1)                                                             Non-568 EFCs are
                                 Non-568                             larger
                                 EFCs are
                                 larger                              Overall-Inconclusive
    Coefficient All              Non-568     0.3970          0.000   Non-568 EFCs are
    of          N1=1,150N2=3,653 EFCs are                            smaller
    variation 2                  smaller     -0.0399         0.061
    (V2)                                                             EFCs are similar
                                 Non-568
                                 EFCs are                            Overall-Non-568 EFCs
                                 larger                              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).

    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.1 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:

               o  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.

               o  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.2

               o  National Association of College and University Business
               Officers (NACUBO): This source provided data on school endowment
               from 1992 through 2004.3

               o  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.4 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.5 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.6 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.7 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.8 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.9 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).10 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.11 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.

    1This 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.

    2Student enrollment data was obtained through linear interpolation, and
    faculty data was based on 1998-1999 data.

    3Where necessary, the data were supplemented by data from IPEDS.

                              Selection of Control Schools

    4Schools 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.

    5Although the observers were not members they attended the group's
    meetings. The former members were Bowdoin College and Macalester College.

    6Liberal 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.

    7The number of schools in the two tiers for each type of school was
    between 50 and 90 for each year.

    8We also used endowment data from NACUBO, and school-level data from GAO's
    survey of the schools.

    9We used data for students who were enrolled as freshmen, as of October of
    the academic year, in the NPSAS database.

    Determination of the Appropriate Time Periods for Assessing Effects and
    Classification of Schools that Only Attended the Meetings

    10Although 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.

    11See appendix III for details of the tests.

    Table 9: Control and Treatment Schools for Analyzing Effects of the
    Consensus Approach Implementation

    Academic years Control school (Non-CA)   Treatment school (CA)
    1995-1996      Sample 1: Brandeis        Samples 1, 2, or 3: Boston
    1999-2000 &    University New York       Collegea Cornell Universityb Duke
                      University Princeton      University Georgetown University
    2003-2004      Universityb Tufts         Massachusetts Institute of
                      Universitya,b Tulane      Technologya,b University of Notre
                      University University of  Dame University of
                      Rochester Washington      Pennsylvaniaa,b Vanderbilt
                      University at St. Louis   University Wake Forest University
    1995-1996 &    Sample 2-All of Sample 1  Yale Universityb
                      Plus: Bryn Mawr Collegeb
    2003-2004      Yeshiva Universitya
    1999-2000 &    Sample 3-All of Sample 1
                      Plus: Colgate University
    2003-2004      Lehigh University Whitman
                      College
    1995-1996 &    Sample 4-All of Sample 1  Sample 4-All of Above Plus:
                      Plus: Carnegie Mellon     Columbia Universityb
    1999-2000      University Johns Hopkins
                      University

    Source: GAO analysis.

    aSchools were excluded because there were no data for SAT scores for
    2003-2004.

    bMember of the former Overlap group.

    cMembers of the 568 Group that had not implemented the consensus approach.

    dWere not members of the 568 Group but attended meetings.

    eFormer member of the 568 Group.

    Notes: Schools that Only Attended 568 Group Meetings: Sample 2: Stanford
    Universityd, University of Southern Californiaa,d and Sample 4: Case
    Western Reserve Universitye .

    Member schools that had not implemented the consensus approach: Sample 2:
    Brown University,b,c Sample 3: Dartmouth Collegeb,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 Collegeb

            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.12 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.13 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.

    12 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.

    13In 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.

    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.14 The
    dependent variables were defined as follows:

               o  Price (PRICEijt): 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:

                            o  Tuition (TUITIONijt): The amount of tuition and
                            fees in dollars charged by school j to freshman i who
                            enrolled in an academic year t.15

                            o  Total grant aid (AIDTGRTijt): 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.16

                            o  Need-based grant aid (AIDNDTGRTijt): 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.17

                            o  Total aid package (AIDTOTAMTijt): 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).

               o  Student enrollment (ENRCAijt): An indicator variable for
               student enrollment into a CA school (ENRCAijt). 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.18 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:

               o  Exemption indicator: EMCAjt  19

               The exemption was captured by the implementation of the consensus
               approach by a school.20 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.

               o  School-level characteristics:21

               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.22 The variables used were:

                            o  ENDOWSTUjt: 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.

                            o  RANKAVGjt: 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.

                            o  ENROLUGjt: The 3-year average growth rate (in
                            decimals) of undergraduate enrollment at school j for
                            an academic year t.

                            o  TENUREDjt: The percentage (in decimals) of total
                            faculty at school j that was tenured in an academic
                            year t.

               o  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):

               AY1995t: Equals one for the academic year 1995-1996, and zero
               otherwise AY2003t: Equals one for the academic year 2003-2004, and
               zero otherwise.

               o  Student characteristics:23

               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:

                            o  FINAIDijt: Equals one if a freshman i who enrolled
                            in school j in an academic year t applied for
                            financial aid, and zero otherwise.

                            o  RACE: Equals one if a freshman i who enrolled in
                            school j in an academic year t is:

                            Asian-ASIANijt, and zero otherwise. Black-BLACKijt,
                            and zero otherwise. Hispanic-HISPANICijt, and zero
                            otherwise. White-WHITEijt, and zero otherwise.
                            Foreigner-FOREIGNijt, and zero otherwise. None of the
                            above-OTHERijt, and zero otherwise.24

                            o  INCOME: Equals one for a freshman i who enrolled
                            in school j in an academic year t has household
                            income in the following quintiles:

                            INCLOijt: 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.

                            INCLOMDijt: 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.

                            INCMDijt: 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.

                            INCUPMDijt: 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.

                            INCHIijt: 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.25

               EFCijt: 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.26

               SCORESATijt: 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).27 In general, the values of the variables were similar
               between the two groups of schools.

    14All 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.

    15The tuition amount was the same for all freshmen in a private school.

    16We also estimated an equation for institutional grant aid (AIDINSTGRT)
    and self-help aid (AIDSELFPLUS).

    17We 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.

    18We 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).

    19This variable was from the GAO survey of the CA and non-CA schools.

    20The 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).

    21All the school-level variables are from IPEDS.

    22The 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.

    23All the student-level variables were from NPSAS.

    24We included Native Americans in OTHER because of their relatively small
    numbers.

    25To avoid the dummy-variable trap in the estimation, we excluded white
    students from the racial groups, and high-income students from the income
    groups.

    26The 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.

    27The reported values are probability-weighted.

    Table 10: Summary Statistics of Variables Used in Regression Analysis,
    1995-1996 and 2003-2004: CA Schools

    Variable              Mean          Std         Min                    Max
    School-level
    TUITION            $26,245       $3,557     $18,910                $31,152
    ENDOWSTU          $227,213     $230,768     $44,061             $1,146,129
    RANKAVG                 16            9           2                     27
    ENROLUG                 2%           6%         -1%                    21%
    TENURED                56%          13%         25%                    75%
    Student-level
    PRICE              $30,792      $11,144      $1,065                $52,354
    AIDTGRT             $7,133       $9,866          $0                $40,658
    AIDNDTGRT           $5,526       $8,722          $0                $35,321
    AIDNONDTGRT         $1,607       $4,360          $0                $30,403
    AIDTOTAMT          $12,465      $13,566          $0                $43,195
    AIDSELFPLUS         $4,794       $8,155          $0                $36,730
    EFC                $24,486      $22,268          $0               $115,090
    SCORESAT              1301          144         790                   1600
    FINAID                 76%          n/a         n/a                    n/a
    ASIAN                   9%          n/a         n/a                    n/a
    BLACK                   5%          n/a         n/a                    n/a
    HISPANIC                7%          n/a         n/a                    n/a
    FOREIGN                 2%          n/a         n/a                    n/a
    OTHER                   5%          n/a         n/a                    n/a
    WHITE                  71%          n/a         n/a                    n/a
    INCLO                   5%          n/a         n/a                    n/a
    INCLOMD                11%          n/a         n/a                    n/a
    INCMD                  13%          n/a         n/a                    n/a
    INCUPMD                17%          n/a         n/a                    n/a
    INCHI                  54%          n/a         n/a                    n/a
    Schools       Cornell University, Duke University, Georgetown University,
                     University of Notre Dame, Vanderbilt University, Wake Forest
                     University, Yale University
    Number of
    observations                                                           241

    Source: GAO analysis.

    Note: All values are (probability) weighted averages, and the monetary
    values are in 2005 dollars.

    Table 11: Summary Statistics of Variables Used in Regression Analysis,
    1995-1996 and 2003-2004: Non-CA Schools

    Variable               Mean          Std         Min                   Max
    School-level
    TUITION             $27,031       $2,259     $24,571               $31,714
    ENDOWSTU           $256,147     $329,513     $27,909            $1,504,930
    RANKAVG                  23           12           1                    43
    ENROLUG                  1%           1%         -2%                    4%
    TENURED                 56%          12%         26%                   72%
    Student-level
    PRICE               $28,815      $10,305      $4,569               $50,726
    AIDTGRT             $10,869       $9,792          $0               $32,803
    AIDNDTGRT            $8,573       $9,132          $0               $31,487
    AIDNDTGRT            $2,296       $5,419          $0               $27,919
    AIDTOTAMT           $16,487      $13,875          $0               $48,572
    AIDSELFPLUS          $5,293       $7,686          $0               $48,041
    EFC                 $21,717      $21,724          $0              $105,095
    SCORESAT               1268          151         740                  1590
    FINAID                  80%          n/a         n/a                   n/a
    ASIAN                   12%          n/a         n/a                   n/a
    BLACK                    5%          n/a         n/a                   n/a
    HISPANIC                 4%          n/a         n/a                   n/a
    FOREIGN                  3%          n/a         n/a                   n/a
    OTHER                    3%          n/a         n/a                   n/a
    WHITE                   74%          n/a         n/a                   n/a
    INCLO                   10%          n/a         n/a                   n/a
    INCLOMD                  9%          n/a         n/a                   n/a
    INCMD                   12%          n/a         n/a                   n/a
    INCUPMD                 21%          n/a         n/a                   n/a
    INCHI                   48%          n/a         n/a                   n/a
    Schools       Brandeis University, Bryn Mawr College, New York University,
                     Princeton University, Tulane University, University of
                     Rochester, Washington University at St. Louis
    Number of
    Observations                                                           277

    Source: GAO analysis.

    Note: All values are (probability) weighted averages, and the monetary
    values are in 2005 dollars.

    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.28 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.

    28The reported values are probability-weighted.

    Table 12: CA and Non-CA Schools: Price and Financial Aid

                               CA Schools                    Non-CA Schools
                                         Percentage                      Percentage
    All students  1995-1996 2003-2004 difference  1995-1996 2003-2004 difference
    Pricea          $28,039   $35,488        27%    $28,068   $30,838        10%
    Tuition &
    fees             24,062    29,967         25     25,770    30,447         18
    Total
    observations        150        91                   198        79
    Financial-Aid Applicants Only
    Student
    Applied for
    Financial Aid
    Pricea          $25,845   $32,897        27%    $24,960   $29,705        19%
    Total grant
    aid               9,142     9,775          7     13,391    13,960          4
    Need-based
    total grant       7,771     6,439        -17     11,863     8,122        -32
    Institutional
    grant aid         7,073     6,529         -8     11,297    11,116         -2
    Total aid        16,604    16,046         -3     19,827    22,255         12
    Loans (incl.
    PLUS)             5,954     4,849        -19      5,271     6,669         27
    Work study          710       866         22        986       715        -27
    Number of
    observations        112        72                   152        73
    Student Did
    Not Apply for
    Financial
    Aidb
    Pricea           34,645    44,504         28     37,714    44,292         17
    Number of
    observations         38        19                    46         6
    Total
    observations        150        91                   198        79

    Source: GAO analysis.

    aPrice equals cost of attendance less total grant aid. Cost of attendance
    equals tuition and fees, plus expenses (including room and board, and
    books).

    bFinancial 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.

    Table 13: CA and Non-CA Schools-Financial Aid Applicants Only: Price and
    Financial Aid

                               CA schools                    Non-CA schools
                                         Percentage                      Percentage
                     1995-1996 2003-2004 difference  1995-1996 2003-2004 difference
    Income level
    Low income
    Pricea          $12,566   $10,095        -20    $18,950   $21,886         15
    Total grant                                     $19,093   $21,861         14
    aid             $23,429   $27,020         15
    Need-based                                      $16,849   $17,756          5
    total grant     $21,422   $21,191         -1
    Institutional                                   $14,060   $17,447         24
    grant aid       $17,278   $12,597        -27
    Total aid       $27,385   $35,956         31    $24,772   $26,523          7
    Number of                                            26         8
    observations          9         3
    Lower-middle
    income
    Pricea          $17,613   $30,437         73    $17,623   $20,546         17
    Total grant                                     $20,598   $23,014         12
    aid             $17,531   $14,793        -16
    Need-based                                      $20,417   $15,456        -24
    total grant     $15,762   $12,949        -18
    Institutional                                   $15,742   $19,386         23
    grant aid       $11,735    $9,667        -18
    Total aid       $24,025   $18,409        -23    $28,462   $30,509          7
    Number of                                            22         5
    observations         13        12
    Middle income
    Pricea          $22,146   $30,156         36    $21,240   $25,279         19
    Total grant                                     $17,173   $17,336          1
    aid             $12,277   $12,076         -2
    Need-based                                      $16,053    $9,048        -44
    total grant      $8,293   $10,767         30
    Institutional                                   $16,000   $13,854        -13
    grant aid       $11,096    $9,936        -10
    Total aid       $18,811   $20,743         10    $24,261   $25,176          4
    Number of                                            20        12
    observations         16        10
    Upper-middle
    income
    Pricea          $23,759   $31,631         33    $26,905   $29,524         10
    Total grant                                     $12,030   $13,478         12
    aid             $10,410   $10,374       -0.3
    Need-based                                      $10,289    $6,593        -36
    total grant      $9,732    $5,864        -40
    Institutional                                   $10,900    $7,198        -34
    grant aid        $8,694    $7,719        -11
    Total aid       $16,926   $19,277         14    $19,425   $20,769          7
    Number of                                            32        11
    observations         21        13
    High income
    Pricea          $31,776   $37,127         17    $30,184   $33,806         12
    Total grant                                      $7,941   $10,331         30
    aid              $3,493    $5,468         57
    Need-based                                       $6,185    $5,377        -13
    total grant      $2,810    $1,694        -40
    Institutional                                    $7,062    $8,884         26
    grant aid        $2,532    $3,430         35
    Total aid       $12,393   $10,850        -12    $13,300   $19,797         49
    Number of                                            52        37
    observations         53        34
    Total                                               152        73
    observations        112        72
    Raceb
    Asian
    Pricea          $28,082   $28,756          2    $25,642   $27,624          8
    Total grant                                     $10,827   $17,834         65
    aid              $8,371   $16,265         94
    Need-based                                       $9,900   $14,646         48
    total grant      $7,675   $13,129         71
    Institutional                                    $7,771   $13,376         72
    grant aid        $6,906   $11,607         68
    Total aid       $14,343   $23,037         61    $15,513   $27,425         77
    Number of                                            23        13
    observations         11         5
    Black
    Pricea          $12,702   $22,935         81    $13,530   $17,375         28
    Total grant                                     $23,296   $25,010          7
    aid             $21,360   $19,958         -7
    Need-based                                      $18,517   $15,631        -16
    total grant     $19,836    $8,932        -55
    Institutional                                   $18,582   $21,231         14
    grant aid       $15,046   $17,404         16
    Total aid       $29,572   $24,950        -16    $29,121   $26,707         -8
    Number of                                             8         4
    observations         10         3
    Hispanic
    Pricea          $21,177   $21,529          2    $20,282   $16,694        -18
    Total grant                                     $17,028   $25,993         53
    aid             $15,432   $18,586         20
    Need-based                                      $14,684   $18,611         27
    total grant     $13,514    $13567        0.4
    Institutional                                   $13,187   $17,998         36
    grant aid       $11,960   $13,813         15
    Total aid       $20,110   $25,576         27    $22,446   $32,732         46
    Number of                                            11         2
    observations          7         8
    White
    Pricea          $27,832   $35,099         26    $25,736   $30,952         20
    Total grant                                     $13,028   $12,512         -4
    aid              $6,711    $7,382         10
    Need-based                                      $11,645    $6,249        -46
    total grant      $5,271    $4,284        -19
    Institutional                                   $11,378   $10,187        -10
    grant aid        $5,105    $4,240        -17
    Total aid       $14,635   $14,130         -3    $20,042   $21,005          5
    Number of                                           103        49
    observations         81        48
    Total                                               152        73
    observations        112        72

    Source: GAO analysis.

    aPrice equals cost of attendance less total grant aid. Cost of attendance
    equals tuition and fees, plus expenses (including room and board, and
    books).

    bData 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.

    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.29
    The reported estimates were based on the fixed-effects estimators, using
    probability weights, and the standard errors were robust.30

    29The 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.

    30The 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.

    Price, Tuition, and Financial Aid Equations:

    Let Yijt 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 (PRICEijt).31 The regression equations
    were specified generally as follows:

    (1)

    where I and S are vectors of school (institution)-level and student-level
    variables, and EMCA represents the consensus approach implementation; q
    (time specific fixed-effects) and th (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.32

    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 bywhere 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).33 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.

    31The same model specification is used to estimate the financial aid
    equations, and tuition equation, which excludes the student-level
    variables.

    32In 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.

    33This effect can be tested as a linear restriction if the joint test of
    significance of EMCA and the terms involving EMCA is significant.

    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 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, andis an indicator equal to one if the
    student is black, and zero otherwise. Then, using equation 1, the equation
    for this example is:

    (1.1)

    Now consider a white student who is a financial aid applicant in school j
    at time t.34 The predicted price for a white student if j is a CA school
    is:

    34White students are excluded from the race groups in the estimation to
    avoid the dummy trap.

    (1.2)

    and the predicted price if j is not a CA school is:

    (1.3)

    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:

    (1.4)

    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:

    (1.5)

    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.35

    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.36
    See the regression estimates for price and tuition in table 14, and those
    for the financial aid variables in table 15.37

    35The 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.

    36The statistical procedure we used is AREG in Stata.

    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.38 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.39

    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:

    37The 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.

    38The $4,800 decrease is approximately equal to $250,000 x -(0.01935).

    39As discussed earlier, similar arguments can be obtained for the tuition
    and financial aid variables.

    (2)

    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).40

    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.41

    The marginal effect of the consensus approach implementation is captured
    by the effects of AY2003 on enrollment in CA schools. Specifically, this
    equals,

    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.

    40The model could not be estimated with school specific fixed-effects
    because they predict successes or failures perfectly.

    41In 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.

    The marginal effect of the student characteristics is captured by the
    effects of S on enrollment in CA schools. Specifically, this equals,

    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.42 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.

    42We 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.

    Table 14: Regression Estimates of Effects of Consensus Approach
    Implementation on Price, Tuition, and Enrollment

    Variable                         Price             Tuition      Enrollment
    EMCA                        43,743.75a   -1,720.72 [0.512]             n/a
                                      [0.002]
    AY2003                      12,133.55a   5,650.28a [0.000] 0.25751 [0.631]
                                      [0.000]
    Student-level
    FINAID                      -7,573.33a                 n/a 0.01292 [0.854]
                                      [0.000]
    FINAID*                 190.21 [0.911]                 n/a      -0.30976 b
                                                                          [0.015]
    ASIAN                         1,084.13                 n/a        -0.01069
                                      [0.363]                             [0.910]
    ASIAN*                      -7,109.66c                 n/a        -0.08486
                                      [0.055]                             [0.613]
    BLACK                       -9,444.68a                 n/a 0.19398 [0.129]
                                      [0.000]
    BLACK*                 -566.20 [0.921]                 n/a        -0.20422
                                                                          [0.339]
    HISPANIC                    -4,686.31a                 n/a 0.06790 [0.574]
                                      [0.007]
    HISPANIC*                    -1,610.12                 n/a        0.35354b
                                      [0.588]                             [0.021]
    FOREIGN                       3,398.09                 n/a        -0.25968
                                      [0.230]                             [0.221]
    FOREIGN*                    10,588.17b                 n/a        0.36734c
                                      [0.026]                             [0.054]
    OTHER                        -2,047.09                 n/a 0.02366 [0.887]
                                      [0.407]
    OTHER*                       -1,077.16                 n/a        0.30781c
                                      [0.727]                             [0.059]
    EFC                           0.10871a                 n/a        2.30e-06
                                      [0.000]                             [0.190]
    EFC*                          -0.00745                 n/a       -3.43e-06
                                      [0.872]                             [0.219]
    INCLO                       -8,427.06a                 n/a        -0.15253
                                      [0.000]                             [0.196]
    INCLO*                       -6,507.64                 n/a        -0.15185
                                      [0.274]                             [0.489]
    INCLOMD                     -8,696.19a                 n/a        -0.03045
                                      [0.000]                             [0.797]
    INCLOMD*                     -1,789.68                 n/a 0.16593 [0.384]
                                      [0.593]
    INCMD                       -4,804.25a                 n/a 0.06859 [0.506]
                                      [0.000]
    INCMD*                  945.64 [0.771]                 n/a        -0.16166
                                                                          [0.303]
    INCUPMD                      -1,434.39                 n/a        -0.03378
                                      [0.163]                             [0.689]
    INCUPMD*                     -1,715.73                 n/a        -0.07025
                                      [0.522]                             [0.657]
    SCORESAT                 -2.48 [0.430]                 n/a 0.00024 [0.227]
    SCORESAT*                -7.82 [0.383]                 n/a 0.00013 [0.764]
    School-level
    ENDOWSTU                     -0.01935a    -0.00401a[0.008]             n/a
                                      [0.001]
    ENDOWSTU*                    -0.01056b     0.00038 [0.831]             n/a
                                      [0.044]
    RANKAVG                       -464.33c    -151.06c [0.064]             n/a
                                      [0.051]
    RANKAVG*                      -798.05a       36.28 [0.792]             n/a
                                      [0.000]
    ENROLUG                      19,038.16   35,553.57 [0.133]             n/a
                                      [0.785]
    ENROLUG*                     -45,843.9 -44,159.24c [0.095]             n/a
                                      [0.518]
    TENURED                     33,100.97a     -610.06 [0.492]             n/a
                                      [0.000]
    TENURED*                    -25,823.9b    4,632.48 [0.315]             n/a
                                      [0.014]
    Constant                    29,651.89a  28,746.01a [0.000]             n/a
                                      [0.000]
    Test statistic of       22.97a [0.000]     375.71a [0.000]  37.68b [0.050]
    modeld
    R-squared                         0.62                0.99            0.06
    Sample size                        518                  28             518
    Joint test for EMCA      2.85a [0.000]        1.15 [0.460]  18.70b [0.133]
    Linear restriction        1.18 [0.240]       -0.59 [0.586]             n/a
    test for EMCAe

    Source: GAO analysis.

    aStatistically significant at the 1 percent level or lower. P-values are
    in brackets.

    bStatistically significant at the 5 percent level or lower. P-values are
    in brackets.

    cStatistically significant at the 10 percent level or lower. P-values are
    in brackets.

    dF-statistic values for the price and tuition equations, and chi-square
    values for the enrollment equation.

    et-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.

    Table 15: Regression Estimates of Effects of Consensus Approach
    Implementation on Financial Aid

                                                Need-based grant
    Variable                Total grant aid               aid        Total aid
    EMCA                        -28,705.63c        -15,512.93      -50,805.28b
                                       [0.066]           [0.178]          [0.016]
    AY2003                 2,159.46 [0.348] -1,511.37 [0.522]        7,385.03c
                                                                          [0.062]
    Student-level
    FINAID                              n/a               n/a              n/a
    FINAID*                             n/a               n/a              n/a
    ASIAN                   -722.86 [0.649]   -740.76 [0.590]        -2,638.73
                                                                          [0.221]
    ASIAN*                 6,970.89 [0.142] 6,546.91c [0.066] 8,275.76 [0.221]
    BLACK                 7,914.65a [0.000] 4,796.63b [0.026]        8,425.58a
                                                                          [0.000]
    BLACK*                 2,546.02 [0.656] -2,267.21 [0.514]   965.32 [0.862]
    HISPANIC              4,709.93b [0.023]  2,826.32 [0.140] 2,281.05 [0.389]
    HISPANIC*              2,038.96 [0.570]    206.79 [0.947] 2,606.82 [0.622]
    FOREIGN                      -5,754.55b -4,634.40 [0.132]      -11.961.86a
                                       [0.031]                            [0.002]
    FOREIGN*                    -10,965.98b       -10,414.55b      -11,659.21c
                                       [0.032]           [0.032]          [0.068]
    OTHER                  4,656.42 [0.169]  5,229.39 [0.129] 4,196.89 [0.349]
    OTHER*                -2,813.57 [0.481] -1,725.88 [0.667]        -4,098.47
                                                                          [0.496]
    EFC                   -0.16058a [0.000]        -0.149889a       -0.187923a
                                                         [0.000]          [0.000]
    EFC*                   0.044382 [0.397]   0.03185 [0.472] 0.006624 [0.929]
    INCLO                 7,178.94a [0.000] 7,932.99a [0.000] 3,276.04 [0.177]
    INCLO*                 7,346.13 [0.239] 6,955.88c [0.096]        14,970.89
                                                                          [0.020]
    INCLOMD               8,227.84a [0.000] 8,747.21a [0.000]        7,153.01a
                                                                          [0.001]
    INCLOMD*               2,830.62 [0.395]  3,585.08 [0.198] 3,678.72 [0.359]
    INCMD                 5,084.33a [0.000] 3,488.27b [0.015]        4,116.59b
                                                                          [0.040]
    INCMD*                 1,835.35 [0.617]  4,773.69 [0.134] 5,366.73 [0.339]
    INCUPMD               2,215.09c [0.093]  1,699.48 [0.161] 1,643.62 [0.419]
    INCUPMD*                 600.56 [0.851]   -473.12 [0.873] 2,503.61 [0.632]
    SCORESAT                   1.23 [0.729]  -0.51436 [0.882]    -3.05 [0.561]
    SCORESAT*                 10.81 [0.306]      1.97 [0.775]    18.18 [0.170]
    School-level
    ENDOWSTU                0.00684 [0.317]   0.01056 [0.144] -0.00583 [0.512]
    ENDOWSTU*              0.001786 [0.774]   0.00272 [0.644]        0.015595c
                                                                          [0.092]
    RANKAVG                   88.79 [0.773]    406.70 [0.114]    58.30 [0.888]
    RANKAVG*                 140.56 [0.571]     38.06 [0.859]   566.66 [0.178]
    ENROLUG                      -36,447.82       -238,689.4a       -12,713.12
                                       [0.623]           [0.004]          [0.922]
    ENROLUG*              30,780.66 [0.683]        246,969.5a        32,081.77
                                                         [0.003]          [0.807]
    TENURED               -4,340.32 [0.545]  5,070.34 [0.486] 8,685.55 [0.530]
    TENURED*              15,405.02 [0.204] 16,399.34 [0.103]        11,726.97
                                                                          [0.514]
    Constant               8,727.25 [0.375]  -1331.71 [0.878]        17,640.66
                                                                          [0.209]
    F value of model         14.81a [0.000]    16.36a [0.000]    8.79a [0.000]
    R-squared                          0.55              0.54             0.36
    Sample size                         409               409              409
    F value of joint test      1.13 [0.328]     1.83b [0.026]    1.60c [0.067]
    t value of linear                   n/a     2.05b [0.041]     0.64 [0.525]
    restriction

    Source: GAO analysis.

    aStatistically significant at the 1 percent level or lower. P-values are
    in brackets.

    bStatistically significant at the 5 percent level or lower. P-values are
    in brackets.

    cStatistically 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.

      Estimation Results of the Effects of Attending Meetings and Implementing the
                                  Consensus Approach43

    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. 44

    43Due 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.

    44All tests are performed using the 5 percent or lower level of
    significance.

    Total Effects of Implementing the Consensus Approach (from table 16)

    Prices:45

    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.46

    Tuition:47

    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:48

    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:49

    45The results were similar when we limited the data to only students who
    applied for financial aid.

    46The 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.

    47The 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).

    48The value of the effect of the CA on institutional grant aid was $1,331,
    but not significant.

    49The 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.

    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
    $12,011.50 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:51

    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
    $22,404.52

    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.

    50The 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.

    51The value of the effect of the CA implementation on self-help aid
    (loans, including PLUS, and work study) was $1,034, but not significant.

    52The 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.

    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                                        Need-based            Probability
    approach                                                 total                     of
    on...              Price   Tuition  Total grant aid  grant aid  Total aid  enrollment
    All students      $3,021     -$433            -$749    $6,125b    -$2,886         38%

                   [-$2,026, [-$2,465,        [-$6,967,     [$239, [-$11,805,   [8%, 67%]
                     $8,068]   $1,599]          $5,470]   $12,011]    $6,034]
    Financial-aid     $2,177       n/a              n/a        n/a        n/a         22%
    applicants
                   [-$3,319,                                                       [-11%,
                     $7,673]
                                                                                     54%]
    Low income       -$4,061       n/a           $3,688     $1,956   $12,121b      [-52%,

                  [-$15,583,                  [-$8,511,  [-$5,232,   [$1,837,       170%]
                     $7,461]
                                               $15,887]    $9,144]   $22,404]
    Lower-middle     $8,089c       n/a          -$3,671     $6,556    -$7,776         95%
    income
                     [-$263,           Higher Education  [-$2,145, [-$19,776,        [6%,
                    $16,441]           [-$12,487,Higher
                                       Education Higher   $15,257]    $4,224]       184%]
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                       Education Higher
                                              Education

                                                $5,145]
    Middle income    $2,320d       n/a           $1,618   $20,221a     $1,178         26%

                   [-$8,043,                 [-$11,221,   [$6,718, [-$19,616,      [-41%,
                    $12,682]
                                               $14,457]   $33,724]   $21,971]        93%]
    Upper-middle     -$1,048       n/a            -$973     $2,769    -$3,054         18%
    income
                   [-$7,641,                  [-$7,801,  [-$3,986, [-$13,177,      [-47%,
                     $5,545]
                                                $5,855]    $9,524]    $7,068]        82%]
    High income       $3,699       n/a            -$714    $4,687c    -$3,856         31%

                     [-$824,                  [-$6,905,    [-$449, [-$12,817,       [-6%,
                     $8,222]
                                                $5,476]    $9,824]    $5,104]        68%]
    Asian              -$376       n/a           $5,726   $14,628a     $3,694          1%
    students
                  [-$10,426,                  [-$5,671,   [$5,051, [-$13,693,      [-78%,
                     $9,674]
                                               $17,123]   $24,206]   $21,082]        80%]
    Black             $4,468       n/a          -$1,227     $4,332    -$6,542        -26%
    students
                   [-$7,452,                 [-$13,238,  [-$4,992, [-$20,353,     [-142%,
                    $16,387]
                                               $10,783]   $13,657]    $7,269]        91%]
    Hispanic         $1,168d       n/a           $1,520    $9,532b     $3,648        108%
    students
                   [-$6,744,                  [-$8,300,   [$1,006,  [-$8,981,       [-6%,
                     $9,079]
                                               $11,341]   $18,059]   $16,278]       222%]
    White             $2,588       n/a            -$491    $6,017b    -$2,879         19%
    students
                   [-$2,403,                  [-$6,766,     [$178, [-$11,922,      [-14%,
                     $7,578]
                                                $5,784]   $11,856]    $6,164]        52%]
    Number of            518        28              409        409        409         518
    observations
    Schools

    CA Schools: Cornell University, Duke University, Georgetown University, University of
    Notre Dame, Vanderbilt University, Wake Forest University, Yale University

    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.

    aStatistically significant at the 1 percent level or lower.

    bStatistically significant at the 5 percent level or lower.

    cStatistically 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.

    Prior Levels and Differential Effects of the Consensus Approach on Affordability
    and Enrollment for Students with Particular Characteristics53

    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.

    53The 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.

    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

                                              Need-based
                                      Total  total grant              Probability
    Students            Price  grant aid          aid  Total aid of enrollment
    Financial-aid
    applicantsd      -$7,573a        N/A          N/A        N/A            1%
    Low incomee      -$8,427a    $7,179a      $7,933a     $3,276          -15%
    Lower-middle
    incomee          -$8,696a    $8,228a      $8,747a   -$7,153a           -3%
    Middle incomee   -$4,804a    $5,084a      $3,488b    $4,117b            7%
    Upper-middle
    incomee           -$1,434    $2,215c       $1,699     $1,644           -3%
    High income           N/A        N/A          N/A        N/A           N/A
    Asian studentsf    $1,084      -$723        -$740    -$2,639           -1%
    Black studentsf  -$9,445a    $7,915a      $4,797b    $8,426a           19%
    Hispanic
    studentsf        -$4,686a    $4,710b       $2,826     $2,281            7%
    White students        N/A        N/A          N/A        N/A           N/A
    Number of
    observations          518        409          409        409           518
    Schools         CA Schools: Cornell University, Duke University,
                       Georgetown University, University of Notre Dame,
                       Vanderbilt University, Wake Forest University, Yale
                       University

                       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.

    aStatistically significant at the 1 percent level or lower.

    bStatistically significant at the 5 percent level or lower.

    cStatistically significant at the 10 percent level or lower.

    dThe estimates are relative to non-financial aid applicants.

    eThe estimates are relative to high income students.

    fThe 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.

    Table 18: Differential Effects of Consensus Approach Implementation on
    Affordability and Enrollment in CA Schools for Particular Groups of
    Students

                                              Need-based
                                      Total  total grant            Probability
    Students            Price  grant aid          aid  Total aid of enrollment
    Financial-aid
    applicantsd          $190        N/A          N/A        N/A         -31%b
    Low-incomee       -$6,508     $7,346      $6,956c   $14,971b          -15%
    Lower-middle
    incomee           -$1,790     $2,831       $3,585     $3,679           17%
    Middle incomee       $946     $1,835       $4,774     $5,367          -16%
    Upper-middle
    incomee           -$1,716       $601        -$473     $2,504           -7%
    High income           n/a        n/a          n/a        n/a           n/a
    Asian studentsf  -$7,110c     $6,971      $6,547c     $8,276           -9%
    Black studentsf     -$566     $2,546      -$2,267       $965          -20%
    Hispanic
    studentsf         -$1,610     $2,039         $207     $2,607          35%b
    White students        n/a        n/a          n/a        n/a           n/a
    Number of
    observations          518        409          409        409           518
    Schools         CA Schools: Cornell University, Duke University,
                       Georgetown University, University of Notre Dame,
                       Vanderbilt University, Wake Forest University, Yale
                       University

                       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.

    aStatistically significant at the 1 percent level or lower.

    bStatistically significant at the 5 percent level or lower.

    cStatistically significant at the 10 percent level or lower.

    dThe estimates are relative to non-financial aid applicants.

    eThe estimates are relative to high income students.

    fThe 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.

                                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.54 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.55 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.

    54We 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.

    55See Kim (2005).

    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

                                  CA Schools                    Non-CA Schools
                        1995-1996 2003-2004 Difference  1995-1996 2003-2004 Difference
    Price
    All students
    Observed              $28,039   $35,488     $7,449    $28,068   $30,838     $2,770
    Predicted             $30,791   $37,171     $6,380    $25,386   $27,882     $2,496
    Financial-aid
    Observed              $25,845   $32,897     $7,052    $24,960   $29,705     $4,745
    Predicted             $28,222   $34,352     $6,130    $22,347   $27,330     $4,983
    Non financial-aid
    Observed              $34,645   $44,504     $9,859    $37,714   $44,292     $6,578
    Predicted             $38,771   $46,625     $7,854    $35,127   $34,973      -$154
    Low income
    Observed              $12,566   $10,095    -$2,471    $18,950   $21,886     $2,936
    Predicted             $14,272   $11,389    -$2,833    $13,613   $18,106     $4,493
    Lower-middle-income
    Observed              $19,220   $30,437    $11,217    $17,623   $20,546     $2,923
    Predicted             $20,650   $32,075    $11,425    $15,156   $19,501     $4,345
    Middle-income
    Observed              $24,785   $34,201     $9,416    $22,560   $26,069     $3,509
    Predicted             $26,035   $36,438    $11,838    $21,092   $20,764      -$328
    Upper-middle-income
    Observed              $26,285   $32,310     $6,025    $29,429   $34,305     $4,876
    Predicted             $31,423   $35,121     $3,698    $26,566   $27,616     $1,050
    High income
    Observed              $32,616   $39,496     $6,880    $33,137   $34,138     $1,001
    Predicted             $35,538   $41,043     $5,505    $31,129   $32,582     $1,453
    Financial aid-

    All students
    Total grant aid
    Observed               $9,142    $9,775       $633    $13,391   $13,960       $569
    Predicted             $10,285   $11,877     $1,592    $12,181   $13,194     $1,013
    Need-based grant
    aid
    Observed               $7,771    $6,439    -$1,332    $11,863    $8,122    -$3,741
    Predicted              $7,443    $6,170    -$1,273    $12,277    $9,151    -$3,126
    Total aid
    Observed              $16,604   $16,046      -$558    $19,827   $22,255     $2,428
    Predicted             $17,998   $17,957       -$41    $18,425   $20,127     $1,702

    Source: GAO analysis.

    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:1

    (1) y = b01 + b11 x1 + b21 x2 + u, u ~ N(0,s2), for group = 1995-1996
    (g1), and

    (2) y = b02 + b12 x1 + b22 x2 + u, u ~ N(0,s2) for group = 1999-2000 (g2).

    Pooling the two groups of data we estimated,

    (3) y = b01 + b11 x1 + b21 x2 + (b02-b01)g2 + (b12-b11)g2x1 +
    (b22-b21)g2x2 + u, where g2 is an indicator variable.

    The test examines the hypothesis that the added coefficients are jointly
    zero: (b02-b01) = (b12-b11) = (b22-b21) = 0.

    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).

    1See http://www.stata.com/support/faqs/stat/chow3.html for details.

    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.2

    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.3

    2As 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.

    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.

    3The 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.

    Appendix IV: Comments from 568 Presidents' Group

    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

    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.

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    Highlights of GAO-06-963 , a report to congressional committees

    September 2006

    HIGHER EDUCATION

    Schools' Use of the Antitrust Exemption Has Not Significantly Affected
    College Affordability or Likelihood of Student Enrollment to Date

    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.

    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.
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