United States General Accounting Office

GAO Report to Congressional Requesters

March 1995 HIGHER EDUCATION

Restructuring Student

Aid Could Reduce

Low-Income Student

Dropout Rate

GAO/HEHS-95-48

GAO United States

General Accounting Office

Washington, D.C. 20548

Health, Education, and

Human Services Division

B-253597 

Letter Date Goes Here

The Honorable Claiborne Pell

Ranking Minority Member, Subcommittee

 on Education, Arts, and Humanities

Committee on Labor and Human Resources

United States Senate

The Honorable Paul Simon

United States Senate

Postsecondary education is a strong determinant of relative wage

earnings. College graduates earn much more than those with only a

high-school education or less, and the differential has been increasing.

Low-income and minority students have traditionally been

underrepresented among college students. For them, federal student

financial assistance programs have become increasingly critical as college

costs have increased faster than the rate of inflation since the 1970s and as

low-income families lost ground relative to high-income families. Federal

assistance to students pursuing higher education has exceeded

$300 billion (in 1994 dollars) over the past 15 years.

While the federal government’s investment to improve college access for

low-income students has been substantial, recent changes in federal

financial aid may inhibit broader college access. A growing proportion of

federal aid has taken the form of loans rather than grants since the 1970s.

With federal grant aid declining in relative terms, students and their

families have had to shoulder a greater share of college expenses. Many

policymakers have expressed concern that this trend in financial aid

patterns, which increases students’ net costs for higher education, has

diminished college access—both initial entry and attendance through

graduation—for low-income students.

As agreed, this report is our second and final product responding to your

request that we compare the relative effectiveness of grants and loans in

helping students stay in college until graduation. In previous testimony,1

we focused on minority students and reported that while grant aid

enhanced the chances that African American and Hispanic students would

stay in college from year to year, loan aid did not. In this study, we focused

on low-income students. We assessed the relative effects of grant and loan

1

Higher Education: Grants Effective at Increasing Minorities’ Chances of Graduating

(GAO/T-HEHS-94-168, May 17, 1994).

Page 1 GAO/HEHS-95-48 Reducing College Dropouts
B-253597 

aid throughout a student’s academic career and then separately by year.

Specifically, we addressed two questions regarding low-income students:

1. Do grants and loans have equivalent effects on helping students stay in

college?

2. Does the timing of grant aid influence the length of time students stay in

college?

To answer these questions, we analyzed two student-level databases to

examine the statistical relationship between grants, loans, and staying in

college. One database comprised a national sample of high school seniors

who began full-time study at 4-year colleges; we traced these students

through college. The other database consisted of a group of relatively

low-income freshmen from a large public 4-year university that

frontloaded2

 some of its institutional grant dollars to improve these

students’ dropout rates.

To complement our statistical analysis and provide additional perspectives

on our findings and observations, we talked to financial aid directors and

students from 12 colleges and universities. We judgmentally selected four

schools from each of three areas—Washington, D.C.; Philadelphia,

Pennsylvania; and Seattle, Washington—for our study. We convened a

discussion panel with financial aid directors from the schools in each area

and asked them for their observations on trends in federal student

financial aid, factors affecting students’ staying in school, and the potential

benefit of frontloading grants. We also interviewed 51 students from these

12 colleges and universities, asking them about their financial aid

packages, the effects working has on their studies, and their thoughts

about debt accumulation. Although the financial aid director and student

responses illustrated ways financial aid affects students, neither group’s

responses were intended to be representative of the respective population

as a whole. (For further details on our scope and methodology, see app. I.)

Results in Brief Grants and loans do not have equivalent effects on low-income students’

staying in college, according to our statistical results. Rather, on average,

grant aid lowers the probability of low-income students’ dropping out,

while loans have no statistically significant impact on their dropping out.

Furthermore, the timing of grant aid influences students’ probability of

2

For our purposes, frontloading grants entails giving students mostly grant aid in the first year and

increasingly substituting loan aid in subsequent years, which culminates in an aid package consisting

mostly of loans in the final school year.

Page 2 GAO/HEHS-95-48 Reducing College Dropouts
B-253597 

dropping out. For example, our results indicated that, on average, for

low-income students, grant aid is relatively more effective during the first

school year than in subsequent years. Sample-specific information from a

university program that frontloaded grants for some students, and

provided them with academic and administrative support, reinforced these

findings. Program participants had substantially lower dropout

probabilities than other comparable students. Financial aid directors and

students with whom we spoke had mixed views on the potential efficacy

of frontloading aid packages. Some thought the approach would be

beneficial, but others raised such concerns as the bait-and-switch aspects

of replacing grant awards with loans in later years.

In view of our statistical results, but noting the limited experience with

frontloading grants, we believe the Department of Education should

conduct a pilot program to evaluate the impact of frontloading on reducing

dropouts among low-income college students. Department officials told us

they would need to further review their legislative authority to determine

whether they could conduct such a pilot or would need to seek additional

authority.

Background Most federal student financial aid programs are authorized under the

Higher Education Act of 1965. Federal student financial assistance

exceeded $30 billion in academic year 1993-94, and most assistance came

from two programs—the Pell grant and Federal Family Education Loan

(FFEL) programs. The Pell grant program, which primarily targets

low-income students, accounted for about $5.7 billion, while the FFEL

program comprised over $21 billion of the total federal aid.3 Maximum

annual awards to students in each program are capped: In 1993-94, the

maximum Pell grant was $2,300, and the maximum subsidized Stafford

loan—the largest of the FFEL loan programs—ranged from $2,625 for

freshmen to $5,500 for seniors.

The Department of Education administers the Pell grant program in

accordance with eligibility criteria and authorized maximum award

amounts set by the Congress. In addition, the Congress effectively limits

actual maximum Pell award amounts each year through the appropriations

process. Actual maximum awards have been less than the authorized

3

Subsidized Stafford loans comprised $14 billion of the FFEL program funds. Students receiving

subsidized loans do not pay interest while attending school or during a grace period after leaving

school. When repayment begins, it is with a below-market interest rate. The remaining $7 billion of the

FFEL program consists of (1) Supplemental Loans for Students, (2) Parent Loans to Undergraduate

Students, and (3) unsubsidized Stafford loans.

Page 3 GAO/HEHS-95-48 Reducing College Dropouts
B-253597 

levels each year since 1980. For example, in 1993-94, the authorized

maximum Pell grant was $3,700, but the appropriation for the program

limited the actual maximum award to $2,300.

Changing Federal Aid

System Coincided With

Rising College Costs

The composition of student financial assistance has changed dramatically

over the past two decades. Although total federal aid has increased since

the late 1970s, loan aid has increased far faster than grant aid. From 1977

to 1980, grant aid exceeded loan aid, but since 1985 loan aid has exceeded

grant aid by about twice as much (see fig. 1).

Figure 1: Loan Aid Surpassed Grant Aid in Early 1980s

Percent of Federal Grants and Loans

0

10

20

30

40

50

60

70

80

1976-77

1978-79

1980-81

1982-83

1984-85

1986-87

1988-89

1990-91

1992-93

Academic Year

Loans

Grants

Budgetary concerns and program changes have limited grant aid for

low-income students. As the deficit rose during the 1980s, policymakers’

Page 4 GAO/HEHS-95-48 Reducing College Dropouts
B-253597 

awareness of budgetary trade-offs and the need to leverage resources

grew. Loans are a less expensive form of aid for federal budgetary

purposes than grants because the budget accounts only for the cost of

interest subsidies and default payments. Thus, for a given federal

expenditure, the government can offer more aid if it is provided as loans.4

In addition, the 1978 Middle Income Student Assistance Act extended

eligibility for Pell grants to higher income students; however,

appropriations did not allow for commensurate increases in program

dollars. Consequently, more students now receive Pell grants, but the

actual maximum award has remained approximately constant in nominal

dollars since 1986.

Cost pressures for low-income families have increased since the late

1970s, as the average cost of 4-year colleges and universities has increased

faster than the inflation rate. Between 1978 and 1992, the average tuition,

room, and board charge at 4-year public colleges and universities rose by

26 percent in real terms.5

 This had two distinct effects. First, college

expenses at the average public university absorbed 11 percent of median

family income in 1978 and 14 percent in 1992. For families at the

20th-income percentile, this charge increased even more, from 22 to

31 percent of income. Second, the actual maximum Pell grant, which

covered over half the costs at the average public 4-year school in 1985,

now covers less than 40 percent.

Low-Income Students Less

Likely to Enroll and Stay in

College

Low-income students are underrepresented among college students.

Low-income students enroll in college at lower rates than high-income

students, although enrollment rates have been rising for all income groups

(see fig. 2).

4

For example, for the same appropriation as a $1,000 grant, the government can lend $3,000 to $4,000.

5

These expenses rose by 52 percent at private colleges and universities.

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Figure 2: College Enrollment Rates Highest for High-Income Students

Enrollment Rate (percent)

0

10

20

30

40

50

60

70

80

1976 1978 1980 1982 1984 1986 1988 1990 1992

Year

Low income

Middle income

High income

Notes: Low income is the bottom 20 percent of the family income distribution, middle income is

the next 60 percent, and high income is the top 20 percent.

The enrollment rate is the percentage of high school graduates in a given year who were enrolled

in college the October following graduation.

We found no data on students’ degree completion by income group.

However, minorities are overrepresented among low-income families, so

their rates serve as a reasonable proxy for low-income students’

graduation rates. Sample data show that minority students are less likely

to stay in school and graduate than white students. For example, in one

sample of students entering 4-year colleges in 1983, 1984, or 1985,

56 percent of white students completed degrees within 6 years, but only

41 percent of Hispanic students and 32 percent of African American

students did so.6

 Policymakers have raised the possibility that reduced

grant aid, relative to the soaring costs of a college education, have

6

These data pertain to 298 National Collegiate Athletic Association Division I schools.

Page 6 GAO/HEHS-95-48 Reducing College Dropouts
B-253597 

adversely affected graduation rates for students at the low end of the

income scale.

Principal Findings

Grants More Effective

Than Loans in Reducing

Dropouts

The composition of financial aid packages and the timing of particular aid

components influence education outcomes. Our results indicated that, for

low-income students, grant aid was effective in reducing dropouts, but

loan aid was not.7

 In addition, grant aid for low-income students was most

effective in the first year, with efficacy decreasing in the second and third

years. The results of the university frontloading program strengthened our

confidence in this finding. Students who received frontloaded grants had a

lower dropout probability than other comparable students. Results of our

statistical work showed the following.

• Grants versus loans: Grants significantly reduced dropout probabilities for

low-income students. In the High School and Beyond database sample, an

additional $1,000 in grant aid for a low-income student reduced the

dropout probability by 14 percent for the award year.8

 Loans did not have

a statistically significant effect for this group—a commensurate increase

in loans did not significantly affect the student’s probability of dropping

out.

• First-year students: Grants were most effective in reducing low-income

students’ dropout probabilities in the first year. For these students, an

additional $1,000 grant in the first year reduced the dropout probability by

23 percent. In the second year, the additional grant reduced the dropout

probability by 8 percent9

 while, in the third year, it had no statistically

discernable effect.

• Frontloading grants: The university’s program for high-need freshmen,

which included frontloading grants, had a significant effect on reducing

dropouts.10 Program participants were 39 percent less likely to drop out in

a year than nonparticipants. For the lowest income students, those below

the poverty line, the program reduced the dropout probability by

64 percent.

7

All results in this section are significant at the 5-percent level unless noted otherwise.

8

A low-income student in this sample was one whose family income was below $21,000.

9

This result was significant only at the 10-percent level.

10Because the program also involved additional student support services, we cannot unequivocally

attribute the entire dropout reduction to frontloading grant money.

Page 7 GAO/HEHS-95-48 Reducing College Dropouts
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These results, with certain qualifications, indicate that frontloading grants

for college students, especially low-income students, could improve

dropout rates. The results pertain only to 4-year college students and thus

have no implication for students at 2-year schools. Also, the frontloading

experiment took place at a university that combined it with other

programs to reduce dropouts, and the results are not generalizable beyond

that school. However, we believe the sum total of our results shows that

frontloading grants holds promise. (For detailed information on the

analyses that led to these results, see app. II.)

Results From Financial Aid

Director Discussion Panels

and Student Interviews

Comments from financial aid directors and students we interviewed

helped us interpret the statistical results. One opinion arising in the

directors’ panels, for example, was that some low-income students are

reluctant to borrow, especially during their first year or two in college.

This observation is consistent with our statistical findings about grants

being more effective than loans in increasing the likelihood that first-year,

low-income students will stay in school. The directors we spoke with were

generally positive about the potential benefits of frontloading grants,

several saying it could help low-income students stay in college by giving

them time to become acclimated to college and reducing financial

pressures when students are most vulnerable to dropping out. One

concern about frontloading was that students might perceive it as a

bait-and-switch policy because it would involve reducing grant awards in

later years. In the student interviews, we sometimes heard that borrowing

was initially difficult for students and that grant aid made the difference in

their being able to start college. Another theme among the students was

that year-to-year consistency was important in their aid packaging, so that

they could plan ahead without disruptions, and that frontloading seemed

contrary to the principle of consistency. (For a discussion of the full range

of comments from financial aid directors and students we spoke with, see

app. III.)

Pilot Frontloading

Program: Departmental

Authority and

Implementation Issues

We discussed with Department officials the value and feasibility of their

conducting a pilot frontloading program. They thought frontloading held

promise and expressed an interest in such a pilot program. They told us

that they might have authority under current law (20 U.S.C. § 1094a(d)

(1988 and Supp. IV 1992)) to conduct a pilot. This law authorizes the

Department to designate institutions that volunteer to participate as

“experimental sites.” These institutions help evaluate the impact and

Page 8 GAO/HEHS-95-48 Reducing College Dropouts
B-253597 

effectiveness of proposed regulations or new management initiatives. The

Secretary of Education may exempt participating institutions from legal

requirements as necessary to conduct the experiments. The officials said

that they had not yet determined whether this authority would permit a

pilot frontloading program and that they might need specific authority

from the Congress to conduct a pilot. We defer to the Department on

whether it currently has the authority to do so or needs additional

authority.

Such a pilot program, moreover, would need to address several

implementation issues. The potential benefits of frontloading could be lost

if institutional aid policies were changed to offset the federal change.

Schools would need to be encouraged to ensure that overall grant aid,

meaning federal and institutional aid combined, were frontloaded. Also,

because eligibility for federal financial aid is based in part on annual

income and other family resources that change over time, the amount of

aid a student qualifies for changes each year. Frontloading would entail

estimating a 4-year package, requiring methods not currently employed in

aid determination. It would also involve adjusting loan limits for third- and

fourth-year students at pilot schools and developing aid award rules for

students who transfer between pilot and nonpilot schools.

In evaluating a pilot program, changes in dropout rates would have to be

interpreted carefully. A policy of frontloading grants might attract students

to college who would not have attended otherwise. Although some of

these students would graduate, on the whole their dropout rate could be

higher than that of the current student population. Frontloading might

reduce the number of dropouts among students who now attend college,

but high dropout rates among this new college population could leave the

overall dropout rate unchanged or higher.

Conclusions Our statistical analysis indicates that loans and grants are not equal

substitutes in terms of affecting education outcomes for low-income

students. Aid packages with relatively high grant levels may improve

low-income students’ access to higher education more than packages that

rely more on loans. In addition, our analysis indicates that the earlier

low-income students receive grant assistance, the more likely they are to

stay in college.

Departure from the conventional approach to dispersing student financial

aid—relatively proportionate amounts each year—could further improve

Page 9 GAO/HEHS-95-48 Reducing College Dropouts
B-253597 

low-income students’ dropout rates. Given that the dropout rate is highest

in students’ first 2 years, frontloading grants would appear to provide

low-income students with the most effective means of financial support

when they are most likely to benefit from it. Restructuring federal grant

programs to feature frontloading could improve low-income students’

dropout rates without changing any student’s overall 4-year allocation of

grants and loans.

Given our statistical results, the mixed views of aid directors and students

we spoke with, and the limited experience with frontloading, we believe

the Department needs to shed light on the matter by undertaking a pilot

program.

Recommendation to

the Department of

Education

We recommend that the Department of Education conduct a pilot program

of frontloading federal grants at a limited number of 4-year schools to

evaluate the impact of frontloading on reducing dropouts among

low-income college students. If, upon review, the Department concludes

that it lacks authority to conduct this pilot, we recommend that the

Department seek legislation from the Congress to authorize the pilot.

Agency Comments As agreed, we did not obtain written comments on the report from the

Department of Education, but we discussed our findings with program

officials. The officials generally agreed with our results and made

suggestions, which we incorporated in the report as appropriate.

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B-253597 

We conducted our review between March 1993 and December 1994 in

accordance with generally accepted government auditing standards. We

are sending copies of this report to the Secretary of Education,

congressional committees, and other interested parties. Please call

Cornelia M. Blanchette or me on (202) 512-7014 if you or your staff have

any questions about this report. Other GAO contacts and contributors are

listed in appendix IV.

Sincerely yours,

Linda G. Morra

Director, Education

 and Employment Issues

Page 11 GAO/HEHS-95-48 Reducing College Dropouts
Contents

Letter 1

Appendix I 

Scope and

Methodology

14

Regression Analyses 14

Discussion Panels With Financial Aid Directors and Interviews

With Students

17

Appendix II 

Detailed Results of

Regression Analyses

20

High School and Beyond Analysis 20

Analysis of Data From a Public University 29

Appendix III 

Summary of

Discussion Panels

With Financial Aid

Directors and

Interviews With

Students

37

Comments From Discussion Panels With Financial Aid Directors 37

Comments From Interviews With Students 43

Appendix IV 

GAO Contacts and

Staff

Acknowledgments

49

Tables Table I.1: Schools GAO Visted 18

Table II.1: Variables Used in Regression Analysis of High School

and Beyond Data

20

Table II.2: Sample Probability of Dropping Out 22

Table II.3: Baseline Regression Results for High School and

Beyond Data

23

Table II.4: Comparison of Grants and Loans for Different

Population Groups

26

Table II.5: Grants More Effective Than Loans for Some Groups 29

Table II.6: Variables Used in Regression Analysis of University

Data

31

Page 12 GAO/HEHS-95-48 Reducing College Dropouts
Contents

Table II.7: High-Need Program Status by Income Level 33

Table II.8: Baseline Regression Results for University Data 34

Table II.9: High-Need Program Participation and Grants Reduce

Dropout Probability for Many Groups

35

Figures Figure 1: Loan Aid Surpassed Grant Aid in Early 1980s 4

Figure 2: College Enrollment Rates Highest for High-Income

Students

6

Figure II.1: Dropout Probabilities Vary as Assumptions Are

Changed

25

Figure II.2: Grant Aid Received by Two Groups of Students 32

Figure II.3: Loan Aid Received by Two Groups of Students 33

Abbreviations

FFEL Federal Family Education Loan

SAT Scholastic Aptitude Test

SEOG Supplemental Education Opportunity Grant

Page 13 GAO/HEHS-95-48 Reducing College Dropouts
Appendix I 

Scope and Methodology

To examine the effects of grants and loans on the probability of students’

staying in college or dropping out, we analyzed two databases: (1) High

School and Beyond, a national survey of students begun in 1980, and

(2) financial aid data from a large public university.11 The two databases

included different information, but they both contained year-by-year totals

for grants and loans each student received, tuition the student paid, and

background information on the student. In addition, we could determine

the number of years a student remained in school and if and when that

student dropped out. We used duration analysis to determine the factors

affecting the probability of staying in college or dropping out. To help

understand the reasoning and decision-making behind our statistical

results, we conducted discussion panels with financial aid directors and

interviews with students at selected schools. Our analysis covered only

students in 4-year undergraduate programs; we did not include community

colleges, proprietary schools, or graduate or professional programs.

Regression Analyses

High School and Beyond

Data

The High School and Beyond survey was first conducted in 1980.

Graduating high school seniors were asked questions about family

background, educational attainment, and future plans. To obtain

information on activities since high school, these same students were then

reinterviewed in 1982, 1984, and 1986. This provided longitudinal

information on students in the initial sample.12 We selected for analysis

those students who began college full time at a 4-year school immediately

after high school. We followed these students through their college years

and noted whether they continued from year to year or dropped out. Our

sample consisted of 3,652 students.

The High School and Beyond survey oversampled African American and

Hispanic students. This oversampling resulted in sufficient observations

on these populations for meaningful results to be obtained for them. We

weighted our sample data so that the proportions of African Americans,

11In consideration of their help and cooperation in providing data to us, we have agreed not to identify

the university.

12The High School and Beyond survey was conducted by the National Center for Education Statistics

of the Department of Education. It is the most recent longitudinal survey the Department has

conducted that has information on students’ completed college careers.

Page 14 GAO/HEHS-95-48 Reducing College Dropouts
Appendix I 

Scope and Methodology

Hispanics, whites, and others would match population proportions.13

Except when we analyzed data separately by race, we reported weighted

means and regression results in all cases.

University Financial Aid

Data

We analyzed financial aid records from a large public university that

recently implemented a new financial aid packaging strategy, which

included frontloading grant money for certain first-year students.14 The

university designated a group of “high-need” first-year students, who

required additional support because they came from economically or

academically disadvantaged backgrounds or both. After these students

had received Pell grants, Supplemental Education Opportunity Grants

(SEOG), and a small Perkins loan,15 they received university grants to cover

remaining need. In the second and later years, their financial aid packages

were weighted with more loans.

Some of the high-need freshmen were less academically prepared than the

university’s average enrollee, officials at the university said, but we could

not identify these students separately in the data. Therefore, to measure

differences in student academic readiness for college, our analysis

included controls for a student’s score on the Scholastic Aptitude Test. In

addition, program participants received additional academic and

administrative support, such as precollege course work in their first year16

and structured advice on course schedules and financial aid options. We

thus do not atttribute program outcomes solely to frontloading.

The university gave us 5 years of data on a cohort of students that began

as full-time, first-year students under the new system in the 1988-89

academic year. We constructed records on the students for the 5 years,

noting the type and amount of aid received each year and how long they

13Specifically, we weighted data according to the proportion of students in the national population

entering 4-year colleges for the first time in 1980.

14Frontloading grant money entails giving students a proportionally higher amount of grant money in

the first year and less grant money, with proportionally more loans, in later years.

15The Pell grant and SEOG programs are the federal government’s two programs targeting grant funds

to low-income students; the Pell grant program is by far the larger program. Perkins loans are also

targeted to low-income students, and their interest rate is lower than that for the much larger Federal

Family Education Loan (formerly Stafford Loan) program.

16Students in the program could take up to two precollege courses out of four courses in each

semester of the first year. A student taking the maximum number of these courses would complete one

semester of college credit in the first full year, after which the student would be required to make

standard academic progress.

Page 15 GAO/HEHS-95-48 Reducing College Dropouts
Appendix I 

Scope and Methodology

remained in school.17 We also had student background data that remained

constant over time.

The data provided by the university did not indicate whether students who

left before graduation had transferred to another school. To identify

transfer students, we matched student records with Pell grant and Stafford

loan data supplied by the Department of Education. For students who

received Pell grants or Stafford loans within three semesters of leaving the

university, we recoded the dependent variable so that we would not count

them as dropouts.

For our analysis, we selected students whose family incomes in their

senior year of high school were below 300 percent of the poverty line. We

did this to ensure that students in and out of the high-need program were

somewhat comparable, although those in the high-need group were still,

on average, from poorer families.

Duration Analysis of the

Two Databases

Our duration analysis examined the probability of a student’s dropping out

in a particular year, given that he or she attended school up to the

beginning of that year. Duration analysis, also known as hazard analysis, is

typically used to estimate factors that result in someone’s remaining in a

particular state (for example, “unemployed” or “in college”) for a short or

long period of time. As some students leave the database by dropping out,

the sample becomes smaller each period. For example, in our data, the

first-year dropout probability was computed for all students in the sample,

but the third-year dropout probability was computed only for those who

completed the first 2 years in college.

Our analysis was a modified hazard model. A hazard model treats the

length of time as the dependent variable. In our analysis, we would have

regressed the number of years in school on the explanatory variables we

chose. However, because we included some independent variables whose

values changed over time, specifically financial aid levels received each

year, this type of hazard model would have been complicated to construct.

Instead, we set the data up so that each person-year was an observation. A

student in college for 1 year, who then dropped out, appeared in the

database only once; someone in school for 4 years appeared as four

17We defined a dropout as a student who left school for more than two consecutive semesters, whether

they ultimately returned or not. If a student took two semesters off and then returned, that student was

not considered to have dropped out, but if the time off were three or more semesters, the student was

considered a dropout as of the last semester in school. Most students who left for more than two

consecutive semesters never appeared again in the data.

Page 16 GAO/HEHS-95-48 Reducing College Dropouts
Appendix I 

Scope and Methodology

separate observations. The dependent variable in our regressions was

whether or not the student dropped out in a given year. We used a logit

model to analyze the resulting database.18

The independent variables of interest were grants and loans. To see

whether the impact of grants and loans varied by certain factors, we

analyzed subsamples of the database based on income group, race, and

year.

Discussion Panels

With Financial Aid

Directors and

Interviews With

Students

We judgmentally selected 12 colleges and universities in three areas. We

chose six public and six private schools, and we selected schools that

varied by such factors as size, tuition, and urbanicity. The schools we

selected are shown in table I.1.

18See Paul D. Allison, Event History Analysis: Regression for Longitudinal Event Data, SAGE University

Paper No. 46 (Newbury Park, Cal.: 1984), pp. 14-19, for further details on this methodology.

Page 17 GAO/HEHS-95-48 Reducing College Dropouts
Appendix I 

Scope and Methodology

Table I.1: Schools GAO Visted

School Location Sector

Undergraduate

population

Tuition,

room,

and

boarda

Washington, D.C., area

George Mason University Fairfax, Va. Public 13,351 $8,728

George Washington

University

Washington, D.C. Private

5,900 $23,768

Howard University Washington, D.C. Private 7,668 $11,676

University of Maryland College Park, Md. Public 23,331 $8,182

Philadelphia, Penn., area

Rutgers University New Brunswick,

N.J.

Public

22,706b $8,841c

Swarthmore College Swarthmore, Penn. Private 1,387 $24,782

Temple University Philadelphia, Penn. Public 18,239 $10,356

University of Pennsylvania Philadelphia, Penn. Private 9,969 $24,638

Seattle, Wash., area

Pacific Lutheran University Tacoma, Wash. Private 2,882 $16,944

Seattle Pacific University Seattle, Wash. Private 2,272 $16,503

University of Washington Seattle, Wash. Public 24,938 $5,760

Western Washington

University

Bellingham, Wash. Public

9,274 $6,227

aIn-state rate for public institutions.

bTotal undergraduate enrollment for seven colleges of Rutgers University in New Brunswick, New

Jersey.

cCosts for Rutgers College, largest of the seven colleges.

Source: Peterson’s Guide to Four-Year Colleges—1995 (Princeton, N.J.: Peterson’s Guides, Inc.,

1994).

To allow interaction between the financial aid directors, we used

discussion panels. For the students, we thought a discussion or focus

group might inhibit some from telling us about their financial situations, so

we interviewed them individually. We did not project from financial aid

director or student responses because we knew our sample was not

representative. Instead, we used the comments to illustrate some of the

thinking that might have led to our quantitative results.

Page 18 GAO/HEHS-95-48 Reducing College Dropouts
Appendix I 

Scope and Methodology

Discussion Panels With

Financial Aid Directors

We held three discussion panels with financial aid directors, bringing

together the four directors in each region.19 We asked them to describe

changes in federal aid policy that they had observed over time and how

these changes had affected institutional or other patterns of financial aid.

We also asked them whether the changes had affected student decisions to

remain in college until graduation. Finally, we asked their opinions on

whether grants are more or less effective than loans and their thoughts on

how students made the trade-off between a small grant and a larger loan

and on frontloading grants.

Student Interviews The colleges and universities identified students for us to interview. We

asked them to select both current students and those who had dropped

out, but none of the schools could give us names and addresses of

dropouts. We did, however, interview some students who had taken time

off and returned to school as well as some transfer students.

In the interviews, we asked students to describe the role of grants and

loans in financing their education and in year-to-year decisions to stay in

school. We asked how they would describe the trade-off between grants

and loans: that is, in general, did they prefer a small grant or a larger loan?

We tried to determine whether debt burden is a major concern and

whether it had caused them to reconsider staying in school, which major

to choose, or whether to go on to graduate or professional school. We also

asked them about work, either as work-study or an outside job, including

the effect on their studies of spending time at work.

19In one city, one director was sick on the day of the discussion so that panel had only three

participants.

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Detailed Results of Regression Analyses

High School and

Beyond Analysis

Grants significantly reduced dropout probabilities for most groups of

students, including low-income, first-year, and minority students,

according to our analysis of the High School and Beyond database. On the

other hand, loans reduced dropout probabilities overall and for

middle-income students but not for others.

The database contained information on the tuition students paid and their

grant and loan awards. It also contained a wide variety of student

background information, including family characteristics and academic

achievement, which we included as controls in our regressions. The

variable definitions, as well as means and standard errors for first-year

observations—that is, for the initial sample before anyone dropped

out—appear in table II.1.

Table II.1: Variables Used in

Regression Analysis of High School

and Beyond Data Variable Description Mean

Standard

deviation

Continuous variables

Base year test Score on a test administered to

sampled students in 1980 56.3 7.1

High school to college Percentage of previous class at

student’s high school that went to

college 54.6 22.5

Family size Number in student’s family 3.52 1.58

Tuition Tuition paid in yeara 5.064 4.548

Grants Grants received in yeara 1.875 3.461

Loans Loans received in yeara 1.489 1.949

Cumulative loans Loans received from start of

college through previous yeara b b

Categorical variables (equal 1 if condition is true)

Family income grouping

(1993 dollars)

Lowest income (below $12,300)

0.050 0.219

Second lowest income

($12,300-$21,000) 0.078 0.269

Third lowest income

($21,000-$28,100) 0.111 0.314

Middle income ($28,100-$35,100) 0.132 0.338

Third highest income

($35,100-43,800) 0.162 0.368

Second highest income

($43,800-$66,600) 0.213 0.410

Highest income (over $66,600) 0.253 0.435

Urban Student went to high school in an

urban area 0.205 0.404

(continued)

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Detailed Results of Regression Analyses

Variable Description Mean

Standard

deviation

Sex Male 0.459 0.498

Female 0.541 0.498

Parents college At least one parent graduated

from college 0.257 0.437

Good grades Student received As and Bs in

high school 0.806 0.396

Region of United States in

which student attended

high school

Northeast

0.281 0.449

South 0.266 0.442

Midwest 0.324 0.468

West 0.130 0.336

Race African American 0.090 0.286

Hispanic 0.030 0.171

White 0.860 0.347

Other race 0.020 0.140

aThousands of 1993 dollars.

bEquals zero for all first-year observations.

Before conducting our regression analysis, we examined crosstabulations

of certain variables with dropouts, the outcome variable. Low-income

students were more likely to drop out of college than middle- and

high-income students. In addition, in our sample, second-year students

were more likely than first- or third-year students to drop out. We also

examined those who dropped out in the first year to determine their

income group; low-income students were again the most likely to drop out.

The sample dropout probabilities are shown in table II.2.

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Detailed Results of Regression Analyses

Table II.2: Sample Probability of

Dropping Out Category of student Dropout rate (percent)

Income Low incomea 14.2

Middle incomeb 10.4

High incomec 6.7

Year First year 8.6

Second year 11.7

Third year 6.7

First year, by income group Low incomea 13.3

Middle incomeb 9.9

High incomec 6.2

aIncome below $21,000.

bIncome from $21,000 to $43,800.

cIncome above $43,800.

Grants More Effective

Than Loans

Grants reduced dropout probabilities more than equal-sized loans in the

baseline model, although both grants and loans had a statistically

significant effect (see table II.3). Because “dropout” is the dependent

variable, the negative coefficient for grants and loans means that an

increase in the value of either variable led to a reduced probability of

dropping out. Results for other variables are as expected: students with

good high school grades and test scores, with parents who went to college,

and from higher income families were the least likely to drop out of

college.

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Detailed Results of Regression Analyses

Table II.3: Baseline Regression Results

for High School and Beyond Data Variable Coefficient Standard error t-value

Constant 0.147 0.355 0.41

Base year testa –0.0309 0.0059 –5.26

High school to collegea –0.00752 0.00181 –4.15

Family size 0.0266 0.0231 1.15

Tuitiona –0.0642 0.0202 –3.18

Grantsa –0.1843 0.0370 –4.99

Loansa –0.0862 0.0412 –2.09

Cumulative loansa 0.0873 0.0337 2.59

Lowest incomea 1.272 0.172 7.38

Second lowest incomea 0.922 0.160 5.78

Third lowest incomea 0.897 0.139 6.44

Middle incomea 0.753 0.136 5.52

Third highest incomea 0.512 0.130 3.95

Second highest incomea 0.407 0.123 3.31

Urban –0.0828 0.0936 –0.89

Female 0.0319 0.0756 0.42

Parents collegea –0.283 0.100 –2.82

Good gradesa –0.880 0.0893 –9.85

Northeastb 0.167 0.100 1.66

South –0.0774 0.0973 –0.80

Westa 0.254 0.120 2.11

African American –0.191 0.132 –1.45

Hispanic –0.00518 0.194 –0.03

Other raceb –0.531 0.297 –1.79

Year 2a 0.305 0.0869 3.51

Year 3a –0.350 0.114 –3.07

Note: Omitted variables were midwest for region, white for race, male for sex, highest income for

income, and first year for year.

aSignificant at the 5-percent level.

bSignificant at the 10-percent level.

Two other dollar variables had significant effects on dropouts. First,

tuition was negatively associated with the probability of dropping out.

Holding all else constant, higher tuition might be expected to lead to a

greater likelihood of dropping out. However, we did not have a measure of

the quality of the college the student was attending; high tuition might, in

fact, have been a proxy for a high-quality college. If high-tuition colleges

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Detailed Results of Regression Analyses

enrolled relatively better quality students who would be less likely than

average to drop out, then tuition would be negatively correlated with the

probability of a student’s dropping out. Second, cumulative loans had a

positive effect on dropping out. This result indicates that although loans in

the current year helped students stay in school, accumulation of loans

over several years may have led students to drop out.

The year 2 coefficient was positive and the year 3 coefficient negative,

indicating that dropouts were more likely in the second year than the first

but least likely of all in the third year.

Probability Results Because we used a logit regression, changes in independent variables

could not be directly interpreted as changes in the probability of dropping

out. Instead, we made a set of assumptions about a student, computed the

probability of that student’s dropping out, and then changed the

assumptions, one at a time, to examine the effects of individual variables.

We first took the baseline results and, holding other variables constant,

changed the amount of grants and loans by $1,000 each. We then examined

the effects of differences in other variables, such as income and race.

Under our initial assumptions, a student had a 9.9 percent probability of

dropping out of college in a given year.20 If the student received $1,000 in

additional grants in the year,21 the dropout probability fell to 9.0 percent,

or by 9 percent (see fig. II.1). With an additional $1,000 loan, on the other

hand, the probability fell to 9.4 percent, a 4-percent decline. Differences in

values of other variables significantly affected dropout probabilities as

well. For example, a student from the lowest of the seven income groups

had a 57 percent greater probability of dropping out than a middle-income

student; one from the highest income group had a 50 percent lower

probability.

20See figure II.1 for baseline assumptions.

21All dollar figures are in 1993 dollars.

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Appendix II 

Detailed Results of Regression Analyses

Figure II.1: Dropout Probabilities Vary

as Assumptions Are Changed Dropout Rate (percent)

0

2

4

6

8

10

12

14

16

Baseline

Grant + $1,000

Loan + $1,000

Lowest income

Highest income

Year 2

Year 3

Assumption

Baseline

Notes: Baseline assumptions are that the student was a white female from a middle-income family

who went to high school in a nonurban area of the northeastern United States, received As and

Bs in high school, and whose parents did not go to college. The following variables were held at

mean values in the baseline simulation for the sample: base year test score, percent of high

school class going to college, family size, tuition, grants, loans, and cumulative loans.

All results are based on coefficients statistically different from zero at the 5-percent level.

Regressions Based on

Different Subsamples

To further analyze the impacts of grants and loans on different types of

students, we performed regressions for subsamples of our sample. We set

the regressions up in the same way as the baseline regressions except for

including only certain observations in each regression: for example, only

students from the two lowest income groups, only first-year observations,

or only African American or Hispanic students. We report first the

coefficient results for selected variables and then probability results.

For low-income, minority, and first-year students, grants were more

effective than loans in reducing dropout probabilities, although the

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Detailed Results of Regression Analyses

differences between the effects of the two types of aid varied across

groups (see table II.4). For low-income students, grants reduced the

dropout probability the most in the first year, and they were decreasingly

effective in the second and third years. Loans never significantly reduced

the dropout probability for low-income students and actually increased the

probability in the third year. The regressions include all other relevant

variables from the baseline regression, but results for these variables are

omitted from this table.

Table II.4: Comparison of Grants and

Loans for Different Population Groups Population Variable Coefficient Standard error t-Value

Overall

Grantsa –0.184 0.037 –4.99

Loansa –0.086 0.041 –2.09

Cumulative

loansa 0.087 0.034 2.59

Year 1

Grantsa –0.136 0.057 –2.37

Loans –0.081 0.066 –1.22

Cumulative

loans c c c

Year 2

Grantsa –0.240 0.061 –3.96

Loansa –0.195 0.074 –2.62

Cumulative

loansa 0.143 0.068 2.12

Year 3

Grantsa –0.169 0.081 –2.07

Loans 0.022 0.083 0.27

Cumulative

loansb 0.087 0.046 1.88

Low income (income categories 1 and 2)

Grantsa –0.313 0.063 –5.00

Loans 0.066 0.085 0.78

Cumulative

loans –0.015 0.086 –0.17

Middle income (income categories 3 through 5)

Grantsa –0.138 0.051 –2.72

Loansa –0.155 0.063 –2.47

Cumulative

loansa 0.153 0.048 3.19

High income (income categories 6 and 7)

(continued)

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Detailed Results of Regression Analyses

Population Variable Coefficient Standard error t-Value

Grantsa –0.186 0.084 –2.23

Loans –0.067 0.071 –0.95

Cumulative

loans 0.047 0.060 0.80

Low income: year 1

Grantsa –0.497 0.105 –4.76

Loans –0.225 0.165 –1.36

Cumulative

loans c c c

Low income: year 2

Grantsb –0.196 0.105 –1.87

Loans –0.058 0.161 –0.36

Cumulative

loans 0.166 0.148 1.12

Low income: year 3

Grants –0.183 0.137 –1.34

Loansa 0.676 0.189 3.59

Cumulative

loansa –0.336 0.149 –2.26

African American

Grantsa –0.133 0.052 –2.55

Loans 0.031 0.073 0.43

Cumulative

loans 0.010 0.067 0.15

Hispanic

Grantsa –0.243 0.071 –3.41

Loansb –0.188 0.109 –1.73

Cumulative

loans 0.123 0.082 1.50

White

Grantsa –0.217 0.055 –3.91

Loansb –0.103 0.057 –1.81

Cumulative

loansa 0.107 0.046 2.29

Other race

Grants 0.081 0.066 1.22

Loans 0.200 0.168 1.19

Cumulative

loans –0.347 0.264 –1.31

(Table notes on next page)

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Detailed Results of Regression Analyses

Note: Overall model includes a constant and controls for base year test, high school to college,

family size, tuition, income, urban, female, parents college, good grades, region, race, year,

grants, loans, and cumulative loans. Subsequent models are for subsamples based on values of

a particular variable; they control for all other variables.

aSignificant at the 5-percent level.

bSignificant at the 10-percent level.

cOmitted from regression because value was zero for all observations.

Probability Results For low-income students, grants decreased the probability of dropping

out, while loans did not (see table II.5). These calculations are based on

the regression results shown in table II.4.

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Detailed Results of Regression Analyses

Table II.5: Grants More Effective Than

Loans for Some Groups

Population Assumption

Dropout probability

(percent)

Change in

probability from

baseline (percent)

Low income (income

categories 1 and 2)

Baseline

15.2 N/A

Grant + $1,000 13.0 –14 a

Loan + $1,000 15.7 +3

Year 1 Baseline 9.9 N/A

Grant + $1,000 9.2 –7 a

Loan + $1,000 9.5 –4

Low income and

year 1

Baseline

9.4 N/A

Grant + $1,000 7.3 –23 a

Loan + $1,000 8.4 –11

Low income and

year 2

Baseline

30.0 N/A

Grant + $1,000 27.7 –8 b

Loan + $1,000 29.3 –2

African American Baseline 11.4 N/A

Grant + $1,000 10.7 –7 a

Loan + $1,000 11.6 +2

Hispanic Baseline 17.4 N/A

Grant + $1,000 15.5 –11 a

Loan + $1,000 15.9 –9 b

Note: Baseline results are the baseline for each group individually. For example, for the

low-income group, the mean levels for evaluation are means for low-income observations; in

previous tables, results for each subpopulation were computed on the basis of the overall sample

means.

aBased on coefficient that is significant at the 5-percent level.

bBased on coefficient that is significant at the 10-percent level.

Analysis of Data From

a Public University

We analyzed financial aid data provided to us by a public university to

examine (1) the relationship between different types of financial aid and

whether students remained in college from year to year and (2) the

effectiveness of a program involving an alternative form of financial aid

packaging. Beginning in the 1988-89 academic year, this university

embarked on a program of giving some of its high-need freshmen aid

consisting entirely, or almost entirely, of grants and having those students

take on loans only in later years. In addition, these students received

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Detailed Results of Regression Analyses

additional academic and administrative support. We refer to this group as

the high-need group and the special aid program as the high-need program.

Our sample consisted of 1,414 first-year students in 1988-89 whose families

had incomes below 300 percent of the poverty line, and we followed this

cohort for 4 years. We restricted the sample so that the students in and out

of the high-need program would be somewhat comparable. We analyzed

the effect of grants, loans, and participation in the program, controlling for

income, Scholastic Aptitude Test (SAT) score, and other factors. Variable

definitions, means, and standard deviations for first-year students are

shown in table II.6.

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Detailed Results of Regression Analyses

Table II.6: Variables Used in

Regression Analysis of University Data

Variable Definition Mean

Standard

deviation

Continuous variables (thousands of 1993 dollars)

Grants Grants received in year 4.789 2.282

Loans Loans received in year 0.817 1.202

Cumulative loans Total loans received prior to

year N/A N/A

College work-study Work study funds received in

year 0.377 0.660

Unmet need Tuition, room, and board, less

financial aid received in year 3.491 2.399

Categorical variables (equal 1 if condition is true)

High-need program Participant in the university’s

high-need program 0.347 0.476

In-state State resident 0.933 0.250

Family income grouping Lowest income (below poverty

level) 0.231 0.422

Middle income (between

poverty and twice poverty level) 0.375 0.484

Highest income (between two

and three times poverty level) 0.394 0.489

Race Asian 0.133 0.340

African American 0.223 0.416

Hispanic 0.178 0.382

White 0.453 0.498

Other race 0.013 0.115

SAT grouping Lowest score (lower than 800

combined math and verbal) 0.234 0.424

Middle score (from 800 to

1190 combined math and

verbal) 0.683 0.465

Highest score (1200 or higher

combined math and verbal) 0.083 0.276

Sex Male 0.409 0.492

Female 0.591 0.492

Aid for High-Need

Freshmen

In our sample, students in the high-need program received more grants

than those not in the program during all 4 years of college, and their loan

amounts were generally low in the first year (see figs. II.2 and II.3). These

students were more likely to come from relatively low-income families

compared with those not in the program (see table II.7), so the higher

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Detailed Results of Regression Analyses

overall amount of grants is not surprising. The differences between

students in and out of the program hold even though our entire sample

was restricted to students from families with income below three times

the poverty line.

Figure II.2: Grant Aid Received by Two

Groups of Students Grant Dollars

0

1000

2000

3000

4000

5000

6000

Year 1: Program

Year 2: Program

Year 3: Program

Year 4: Program

Year 1: Nonprogram

Year 2: Nonprogram

Year 3: Nonprogram

Year 4: Nonprogram

Year and Program Status

20th Percentile

Median

80th Percentile

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Detailed Results of Regression Analyses

Figure II.3: Loan Aid Received by Two

Groups of Students Loan Dollars

0

1000

2000

3000

Year 1: Program

Year 2: Program

Year 3: Program

Year 4: Program

Year 1: Nonprogram

Year 2: Nonprogram

Year 3: Nonprogram

Year 4: Nonprogram

Year and Program Status

20th Percentile

Median

80th Percentile

Table II.7: High-Need Program Status

by Income Level Program

status

Lowest income

(percent)

Middle income

(percent)

Highest income

(percent)

Total

(percent)

Program 44.0 48.9 7.0 100.0

Nonprogram 13.8 31.8 54.4 100.0

Program Involving

Frontloading Reduced

Dropout Probability

Participation in the high-need program reduced the probability of dropping

out, even controlling for financial aid (see table II.8). The coefficient result

for the high-need program means that a student in this program is

39 percent less likely to drop out than one not in the program if other

factors are held constant.

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Table II.8: Baseline Regression Results

for University Data Variable Coefficient Standard error t-Value

Constanta –2.09 0.780 –2.68

Grantsa –0.403 0.0848 –4.75

Loans –0.0350 0.0819 –0.43

Cumulative loans 0.0501 0.0530 0.95

College work-study –0.0416 0.135 –0.31

Unmet need –0.0630 0.0763 –0.83

High-need programa –0.560 0.192 –2.91

In-state 0.462 0.297 1.55

Lowest incomea 0.643 0.203 3.17

Middle incomea 0.460 0.166 2.77

Asiana –0.786 0.275 –2.86

African Americanb 0.326 0.184 1.77

Hispanica 0.439 0.185 2.37

Other race –0.143 0.609 –0.23

Lowest SAT score 0.198 0.314 0.63

Middle SAT score 0.0419 0.268 0.16

Femalea 0.469 0.133 3.54

Year 1a 0.997 0.262 3.81

Year 2a 0.752 0.246 3.06

Year 3 0.0849 0.257 0.33

Note: Omitted variables were nonprogram for high-need program, out of state for in state, highest

income for income, white for race, highest score for SAT grouping, male for sex, and fourth year

for year.

aSignificant at the 5-percent level.

bSignificant at the 10-percent level.

As in the High School and Beyond data, grants were more effective in

reducing the dropout probability than loans. The coefficient on grants

translates into a 25-percent reduction in the probability of dropping out for

a $1,000 increase in grants. Loans did not have a statistically significant

effect.

We also analyzed subsamples of the data separately. Participation in the

high-need program was a significant factor for second-year students and

the lowest and highest income groups (see table II.9). For the lowest

income students, a program participant was 64 percent less likely to drop

out than a nonparticipant. Grants were more effective than loans in

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Detailed Results of Regression Analyses

reducing the probability of dropping out for students in all years, except

for the fourth year when neither had a significant effect, and in all income

groups. Loans did not significantly reduce dropout probabilities for any of

these groups.

Table II.9: High-Need Program

Participation and Grants Reduce

Dropout Probability for Many Groups

Population Variable Coefficient Standard error t-Value

Overall

Grantsa –0.403 0.0848 –4.75

Loans –0.0350 0.0819 –0.43

Cumulative loans 0.0501 0.0530 0.95

High-need programa –0.560 0.192 –2.91

Year 1

Grantsa –0.548 0.142 –3.86

Loans –0.138 0.136 –1.02

Cumulative loans c c c

High-need program –0.402 0.317 –1.27

Year 2

Grantsb –0.313 0.160 –1.96

Loans –0.0901 0.167 –0.54

Cumulative loansb 0.280 0.146 1.92

High-need programa –0.852 0.362 –2.36

Year 3

Grantsa –0.539 0.205 –2.63

Loans –0.0960 0.191 –0.50

Cumulative loans 0.0277 0.126 0.22

High-need program –0.667 0.493 –1.35

Year 4

Grants 0.114 0.267 0.43

Loans 0.205 0.256 0.80

Cumulative loans 0.0210 0.0944 0.22

High-need program –0.425 0.542 –0.78

Lowest income

Grantsb –0.266 0.161 –1.65

Loans 0.148 0.177 0.83

Cumulative loans 0.175 0.138 1.27

High-need programa –1.06 0.400 –2.66

Middle income

Grantsa –0.267 0.135 –1.97

Loans –0.0660 0.132 –0.50

(continued)

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Detailed Results of Regression Analyses

Population Variable Coefficient Standard error t-Value

Cumulative loans –0.0139 0.0824 –0.17

High-need program –0.226 0.280 –0.81

Highest income

Grantsa –0.749 0.168 –4.46

Loans –0.183 0.138 –1.32

Cumulative loans 0.0795 0.0825 0.96

High-need programa –1.071 0.470 –2.28

aSignificant at the 5-percent level.

bSignificant at the 10-percent level.

cOmitted from regression because value was zero for all observations.

Page 36 GAO/HEHS-95-48 Reducing College Dropouts
Appendix III 

Summary of Discussion Panels With

Financial Aid Directors and Interviews With

Students

Some of the financial aid directors in our discussion panels told us that

reductions in federal grants have required students to borrow and work

more while in college. They said that some low-income students are

reluctant to borrow, especially during their first year or two in college.

Some low-income students we talked to told us that borrowing was

initially difficult. Several of them said that with less grant aid, they would

have either not attended or chosen a lower cost college. The directors we

spoke to were generally positive about potential benefits of frontloading

grants, while students tended to emphasize the importance of year-to-year

consistency in their aid packages.

Comments From

Discussion Panels

With Financial Aid

Directors

The federal financial aid shift from grants to loans has put cost pressures

on students, according to financial aid directors we spoke to. Students

have generally borrowed more and, in some cases, worked more than in

the past to meet their educational expenses, according to some of the

directors, but most of them did not believe dropout rates had increased as

a result of the changes. However, some told us this was only because of

institutional aid increases, while one noted that the effects of very recent

increases in borrowing have not yet been felt. Individual student attitudes

toward debt vary, many directors said, and these attitudes can change over

students’ years in college. Some directors expressed concern about

increases in students’ working and the effects on their studies. The

directors generally reacted positively to the idea of frontloading grants,

and they told us some potential advantages as well as pitfalls of such a

program.

Response to Changes in

Federal Financial Aid

Many directors noted that in the last 10 to 15 years, federal funding for

postsecondary student financial aid at their institutions, especially grant

aid, has been level, actually decreasing in constant dollars. This decrease

has put pressure on educational institutions, states, and students to fill the

gap between the federal financial aid available and rising costs.

Schools have responded by substantially increasing their institutional

grant budgets, some directors said. In addition, some schools have

redefined “high-need students,” recognizing that they can adequately serve

only those with the very highest need. Some directors expressed concern

about (1) reaching the limits of their abilities to draw upon endowment

and other outside resources to bolster their financial aid budgets or (2) the

impact this may have on diversity goals for their student body.

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Several directors said that some states have responded by developing

strong state financing programs. Because most state treasuries are not in a

position to fill the gap created by declining federal dollars, discussion in

the financial aid community has explored new and innovative financing

strategies for public institutions. One example is a

high-tuition/high-financial-aid model, under which tuitions are raised and

some of the increased revenue is used to aid students who could no longer

afford to attend.

Students tend to borrow more and, at some schools, work more now than

in the past, some directors said. One director observed that students are

borrowing more to make up the gap between what his school expects

them to save during the summer and what they are able to save, based on

their earnings. Several directors also noted a large upturn in borrowing in

the last year or two. Some directors believe students now hold jobs during

the school year more than they used to, but others said that students work

at about the same rate as in the past.

Changes in Financial Aid

and Student Dropout Rates

In general, most directors said that changes in federal financial aid have

not greatly affected dropout rates for the student population as a whole,

but some directors were concerned about dropout rates for specific

groups. They also stressed the efforts their schools make to retain

students, and they noted that students leave school for nonfinancial as

well as financial reasons.

Some directors were most concerned about educational access for

specific types of students, such as those from working-class families;

minorities, particularly African American males; and out-of-state students

at public institutions. One director expressed concern that some

low-income and minority students do not even apply for college because

of perceptions about high costs and limited financial aid. Another director

stressed that it is not the prospect of large loan balances that deters

low-income students from enrolling at his institution but the difference

between the total education costs and the available financial aid. Another

director stated that the federal government needs to (1) concentrate grant

dollars on needy families who do not have other resources and (2) give

loan money to those who have the means to pay it back. For needy

students, he said, more loans may not help as much as more grants, but,

for less needy students, more loans may help keep them in school.

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Some of the directors discussed their schools’ efforts to retain students

and suggested that changes in federal financial aid would have hurt

students more if their schools had not made such efforts. One director

described his school’s posture toward retaining students as aggressive. He

explained that if a student is withdrawing from his institution for financial

reasons, the financial aid office will work with the student and try to come

up with a solution that will allow him or her to stay. Another director

stated that his office is also geared toward keeping students in school and

that at least for students considering dropping out for financial reasons,

the school is successful approximately 99.5 percent of the time.

Nonfinancial factors also cause students to leave school. For example, one

director said, some students, particularly first-generation students, must

contend with competing demands from their families. Academic

performance also affects whether students remain in college. In fact,

another director stated, students’ grade-point averages are the best

retention indicators because they reflect how well the students are doing

academically and how well students like their academic programs.

Finally, some directors described factors that cause students to take

longer to graduate than they used to, even if they do not drop out. For

example, students may take time off to work because of concern about

indebtedness, or they may change their fields of study several times.

Student Awareness and

Concern About Debt

Student attitudes towards debt vary, financial aid directors said: Some

students are very concerned about borrowing, while others borrow large

amounts to finance their education. Some directors said that low-income

or minority students are more reluctant to borrow than other students.

Directors’ opinions also varied on the effects of larger debt on the choices

students make, such as field of study or postgraduate plans.

Student Attitudes Towards

Debt

Directors’ opinions varied on the degree to which students worry about

accumulating debt. A student’s concern about borrowing depends on a

number of factors, several directors noted, including the student’s year in

college and individual or family attitudes toward accruing debt. For

example, one director thought that students become more concerned

about borrowing as they approach graduation; a second director was

convinced that students are more concerned about debt at the beginning

of their college careers and, over time, develop more confidence about

their ability to support themselves (and therefore pay off debt).

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Students

In general, certain types of students—older, independent students,

students from low-income backgrounds, and graduate or professional

students—tend to be more concerned about indebtedness than others,

according to several of the directors. One director noted that many college

students do not pay attention to how much they have borrowed; they are

just trying to get registered at the beginning of each semester. Another

director stated that parents are more concerned about borrowing than

students, especially once students hit the maximum loan levels.

Minority and Low-Income

Students and Borrowing

The directors discussed some of the barriers to higher education for

minority students. For example, one director said low rates of high school

graduation reduce the pool of minority candidates. In addition, some

directors saw the need for these students to borrow more to finance

higher education as a barrier.

According to one director, placing greater emphasis on loans to finance

higher education has clearly negatively impacted on his public school’s

capacity to recruit talented minority nonresident students. The high-need

minority students who get a full range of aid, including grants, work-study,

and loans, are reluctant to borrow, but they borrow anyway and enroll;

those who get only loans, however, tend not to come. He and another

director also pointed out that the minority students who are highly

qualified academically are sought after by many schools; therefore, these

students are likely to receive attractive financial aid packages.

This director and one other mentioned that reluctance to borrow is found

not only among minority students and their families but also among many

first-generation, low-income college students. These students and their

families fear the unknown, including what their investment in higher

education will actually achieve for them and whether they will be able to

repay the loan after graduation.

Effects of Larger Loan Balances

on Students’ Choices

Several directors thought that financial considerations were not

significantly affecting students’ choice of majors, although directors

opinions varied. One director observed that, for the first 2 years, college is

not the real world for students—it is an extension of their comfortable

family life—and that students do not address career issues and the effect

of their debt until later. She observed that while most students are

concerned with just getting a job after graduation, many also want to

“study their passion” and will not choose a field just for high pay. A second

director explained that his institution has not experienced changed

enrollment patterns at either the undergraduate or the

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graduate/professional level; one would expect to see such changes if

students were greatly concerned about their debt.

In contrast, other directors said students are looking for higher paying

jobs because of high debt levels. At one institution, this has resulted in

increased enrollment in fields such as engineering and decreased

enrollment in fields such as education and nursing.

Finally, a few directors cannot tell what effect increased indebtedness will

have on student choices because much of the increase has taken place in

the last year, they said. It is thus hard to tell what impact the cumulative

debt will have on students when they graduate. Students were not

currently changing majors because of concerns about increased debt,

these directors said, but they were not sure what impact the current

increases in loans will have on students in the future.

The Effects of Students’

Working

Several directors provided a variety of reasons—both financial and

nonfinancial—that students work while attending school. Opinions varied

on whether students are working too much, but some directors agreed

that working more than 20 hours per week is too much. Some directors

spoke enthusiastically about the benefits of the work-study program.

Directors mentioned several finance-related reasons why many students

today work while attending school, for example, to help pay educational

costs, to keep debt levels as low as possible, and to make up for gaps in

their expected family contribution. Directors also mentioned that students

work for nonfinancial reasons—for example, to gain work experience.

Whether students choose to work while in school can also vary by the

individual student’s residence, according to one director—commuters

tend to work more than students living on campus. Finally, a few directors

stated that it is unfortunate that some federal financial aid

programs—specifically the Pell grant program—contain disincentives for

students to work because increased earnings can decrease a student’s

financial aid award.

Working too many hours is only a problem in isolated cases, one director

said. Even if students are working more, according to another, no

evidence shows that this has had a qualitative impact on their academic

work. Another director listed the risks students face when they choose to

work more than 20 hours per week while attending school full time,

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including eroding the quality of their academic experience, isolating them

from campus activities, and extending the time it takes them to graduate.

Some directors cited the numerous and varied benefits of the work-study

program, especially compared with off-campus work. Several directors

mentioned that work-study helps students stay in college because they

become more connected to the institution, develop relationships with

mentors, and learn more about the school. Other benefits they mentioned

included higher academic achievement because hours are controlled and

tend to be more flexible; new skill acquisition, if the work is related to

career goals; and reduced resentment among other students toward

financial aid recipients because they are not being given something for

nothing. Several directors mentioned the immediate need for more

work-study dollars at their schools.

Frontloading Grants Frontloading grants could be beneficial, according to some directors. A

potential benefit of frontloading, according to one director, is that it would

give students more confidence in their ability to manage their debt: They

would not need to borrow until they were sure they could do the work and

finish their college education. Some directors also mentioned that

frontloading could help with retention and increase accessibility for

students from special populations. Some noted that it could assist

institutions in maintaining a more consistent aid policy over time and

result in more uniform aid packages across institutions.

Some directors raised concerns about frontloading. One concern was that

it could be perceived as a bait-and-switch policy, because students were

attracted to schools with large grants only to find that those grants were

not available for all 4 years. Other concerns were that frontloading might

still waste federal resources when students drop out, might not work in

the absence of additional support services, and could concentrate federal

grant dollars in 2-year institutions. In addition, the idea of frontloading is

not based on data about the impact of grants on helping students stay in

college, one director noted.

One director’s recommendations for structuring a frontloading program

included targeting specific populations and combining the program with

income-contingent loans in the later years. Income-contingent loans, for

which monthly repayment amounts are adjusted depending on income,

would make it easier for graduates in low-paying jobs to repay. Another

director stressed that whatever option the federal government chooses, it

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is important to stick to it. According to her, one of the most difficult

problems students face, when beginning their college careers, is that they

cannot be confident that the financial aid they receive the first year will be

available in subsequent years; therefore, they cannot plan accordingly.

Comments From

Interviews With

Students

Many students we interviewed said that without grants they would not be

in school or would not be at that particular school. Although they

generally preferred grants to loans, their answers varied when asked to

choose between small grants and larger loans. The students were generally

concerned about the levels of debt they were accumulating during college,

but a number of them did not believe their debt levels would affect future

decisions they made about careers or postgraduate work. They wanted to

keep loan amounts as low as possible, but many of them would borrow

whatever necessary to finish their college education because they knew

the value of the degree, they said. Most of the students we interviewed

worked while attending school, and many cited benefits of working in

addition to earning money. However, some said the amount they worked

threatened their ability to focus on schoolwork or hurt their grade-point

averages.

Grants Often Affected

Student Choices

Students we spoke to generally preferred grants to loans, and grant

availability sometimes influenced their choices. Some students, however,

indicated they would prefer larger loans to smaller grants, simply because

they needed the larger amount of money to remain in school each year.

Students also had different opinions on whether grants early in their

college careers were more important than grants as they approached

graduation, with many saying year-to-year consistency was important to

them.

Grants Brought Some Students

to Their Current Schools

For some students, the availability of grants helped determine the schools

they attended. Some of these students chose private schools and said they

would not be at those schools without grants. These students often

received grants from their schools of over $10,000, or more than four times

the maximum federal Pell grant, and many of them specifically mentioned

public or community colleges as alternatives if they had not received these

grants. Some students at public schools also said that they might not have

been able to stay in school without grants. Finally, several students said

that they would have worked more or taken time off, extending the time

they needed to complete college.

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The absence of grants also affected some students’ choices. Some of the

students we interviewed began postsecondary education at a community

college, and then transferred to a 4-year school, to minimize costs or debt.

One student who transferred to a public school said that if more grants

had been available in her first year, she would have started at the 4-year

school she now attends. However, other students began at community

colleges for nonfinancial reasons. For example, one student said she may

have started at the community college even if more grant money had been

available her first year because she was returning to school after being out

for several years and the community college made for an easier transition.

Students’ Preferences Vary

When Choice Between Grants

and Loans Is Constrained

We asked students what they would do if their aid package left them short

of what they needed and they had to choose either a small grant or a larger

loan to complete their financial aid offer. The federal cost of a grant is

three to four times that of a loan per dollar of aid, meaning that a grant of

$1,000 costs the federal government about the same as a $3,000 to $4,000

loan. We asked students which they would prefer.

A small grant might not be enough to keep them in school, some students

said; if their need was such that only a large loan would be what they

needed to pay for costs through the year, they would choose the loan.

Some specifically mentioned not wanting to work more than they already

did. Several others said they did not know how they would raise additional

money to cover the remaining gap.

Others would choose small grants over large loans, preferring to make up

the difference with either additional work, reduced living expenses, or an

increased parental contribution. Some of these students said they would

do whatever they could to avoid borrowing more than necessary.

Option of Shifting Grant Money

to Student’s Early Years Drew

Mixed Reaction

We asked students whether they would have preferred an aid packaging

scheme that frontloaded grant aid. Many students said they would not

favor such a packaging plan, preferring grants “spread out” over their

college years. Some saw frontloading as a departure from “consistency” in

aid packaging and said consistency from year to year was important to

them. On the other hand, some students saw advantages to such aid

packaging. One student said that it would be an incentive to start school

and that after 2 years students know the system better and know how to

succeed. Another student reacted positively to the idea that students

would have an opportunity to “prove you can do the work” before

borrowing.

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Students

Students Expressed

Concern About Debt

Levels, but Many Would

Borrow Whatever

Necessary to Stay in

School

Students we interviewed generally did not like borrowing to finance their

education, but many expected to have to do so and thought the education

or degree they would receive was worth going into debt for. Some

students told us that their anticipated debt at graduation worried them or

influenced what they planned to do after graduation, but others said that

their choice of major or planned career was not at all influenced by

earnings potential or the need to repay their loans. Among those whose

attitudes toward borrowing had changed over time, some said that they

had become more reluctant to borrow; others said that they found

borrowing easier as they went further in school.

Students Expected to Borrow

to Attend College

Many students said they were aware of the need to borrow before they

began college. They sometimes mentioned that a parent, sibling, or other

acquaintance had borrowed to attend college; some said borrowing was

“expected,” “the price you have to pay,” or “a necessary evil.” On the other

hand, several students were the first in their families to go to college, so

they told us that accumulating educational debt was a new phenomenon

for them.

Generally, students were in agreement that borrowing was worthwhile,

given the rewards of higher education.22 Many students spoke of it as an

“investment.” In addition, a number of students said they would borrow

whatever was necessary to remain in school.

For Many Students, Borrowing

Did Not Affect Future Plans;

Some Reported Concern

Many students told us that they selected a major or career without regard

to potential earnings or ability to repay loans, but repayment did affect the

choices others made. Some of these students said that they were studying

a certain field because they had always wanted to. Several said that they

would worry about repayment when the time comes. Others, however,

were either worried that their field was not high paying and loan

repayment would thus be difficult or were not concerned because they

knew their field was high paying.

Debt levels also played a role in some students’ plans for further education

in graduate or professional schools. One student said that she was

considering going to law school immediately after graduating because she

knew she could then defer repayment of her undergraduate loans. Other

students, however, wanted to take jobs immediately and begin paying off

their accumulated debt. Some said that they knew they would need to

borrow for additional schooling and (1) did not want to borrow any more

22Again, we spoke to current students, not dropouts or those who never attended college. Attitudes

among those not in college could vary greatly from the attitudes of current students.

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Students

than necessary while undergraduates or (2) wanted to work to repay their

undergraduate loans before borrowing more for postgraduate work.

Attitudes About Loans Often

Changed Over Time

Students’ thinking about loans often changed while they were in college.

For some students, borrowing grew easier as time went on. For these

students, taking out the first loan was “scary” and the families were

hesitant. Several students who began in community colleges and then

transferred to 4-year schools mentioned that they did not need to borrow

until they got to the 4-year school. One of these students, as well as

another who began at a 4-year school, mentioned that it is easier to

borrow with several years of completed schooling under one’s belt. Others

said that borrowing became easier or “routine” after the first loan.

Other students, however, found that borrowing became more difficult as

they approached graduation. For these students, the first loan came at a

time when repayment was far in the future, but repayment loomed much

closer at graduation. One mentioned that the thought of loans

accumulating stayed in the back of her mind; others said the cumulative

amount of their debt, not the amount they borrowed in any one year, was

what concerned them.

Working While in School

Plays an Important Role

Work played a large role in the lives of most of the students we

interviewed. Students worked for the money they earned but also for other

benefits, such as learning about time management, gaining job experience,

and discovering networking opportunities with different offices or

departments in their schools. Those in on-campus jobs told us that they

had more flexibility in scheduling their work hours and also were better

able to make contacts with their schools. Some students said that they

worked as much as they could, but others said that they were working too

much and their studies were suffering.

Students Worked for Money

They Earned

Earning money was the benefit of working that students cited most often.

Many students said they used the money they earned for living expenses.

Others saw work more as one component of their overall plan to finance

their education. For example, several students mentioned that working

helps reduce the amount they need to borrow.

Several students we talked to were concerned enough about finances that

they chose jobs not for convenience but for higher pay, turning down

work-study jobs because of fears the money would run out or because

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Students

other jobs paid more. Another student, however, said she wanted a

work-study job because it paid more than the job she currently held.

Students Found Other Benefits

to Working

Many students said that working helped them budget or manage their time

or that it adds structure or discipline to their schedule. Another benefit of

working was gaining job experience, including particular job skills. Some

students worked in an office setting for the first time and learned to work

with computers. Several also said that work looks good on their resumes

or when applying for future jobs.

Students Tended to Favor

On-Campus Employment

A number of the students we talked to said they preferred on-campus jobs

to off-campus ones. These students said that the main advantages to

working on campus were convenience and flexibility. Some on-campus

jobs allowed students to shift their hours if their school work or other

demands became burdensome; others allowed students to set their own

schedules around their class schedules. Several students working on

campus told us that they could sometimes study while at work, although at

least one student with an off-campus job was also able to study

occasionally. Finally, several students said that the on-campus location

was important simply because they did not have to spend time commuting

to work. For example, one student said she did not have a car and would

not have been able to work off campus.

On-campus jobs also gave some students a sense of being more connected

with their school. Through work, these students said, they made contacts

with campus offices that helped them later on. For example, working in

the financial aid office helped some students learn more about the

financial aid system.

In contrast, students working off campus sometimes mentioned

inconveniences associated with their work. The time spent commuting to

work was an important concern for some. In addition, off-campus jobs

tended to have less flexible hours and schedules. Some students, however,

preferred off-campus work because they could earn more than in an

on-campus work-study job.

Work Sometimes Interfered

With Studies, Especially If More

Than 15 to 20 Hours Per Week

Some students said that working affected their academic studies. These

students worked a range of weekly hours, one student as few as 8 hours

but most over 15 hours per week. One student said that he worked 40

hours per week in 1 year because he had no other financial support; he

had to drop out because of bad grades that year. He transferred, received

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Students

financial aid, and was currently working 22 hours, earning a 3.7

grade-point average.

Other students, with a similar range of hours worked, said that working

did not affect their study time or hurt their grades. Although their hours

varied, these students generally worked fewer than 20 hours per week. In

addition, several said that (1) if they were not working, they would

probably not be using that time for additional studies or (2) students who

work perform better academically than those who do not.

We asked some of the students how much they could work without

hurting their studies or how much would first begin to hurt their studies.

Most responses were in the 15- to 20-hour per week range.

Page 48 GAO/HEHS-95-48 Reducing College Dropouts
Appendix IV 

GAO Contacts and Staff Acknowledgments

GAO Contacts Wayne B. Upshaw, Assistant Director, (202) 512-7006

James W. Spaulding, Project Manager, (202) 512-7035

Acknowledgments In addition to those named above, the following individuals made

important contributions to this report: Jane A. Dunkel assisted conducting

the interviews and discussion panels and helped write the report, Charles

M. Novak assisted with the original conceptualization of the study,

Thomas L. Hungerford developed the statistical model and conducted

initial analyses, Steven R. Machlin and Robert Bifulco performed

additional statistical analyses, Elsie A. M. Picyk performed data

processing, and Luann Moy and Linda Stinson provided methodological

advice on the interviews and discussion panels.

(104733) Page 49 GAO/HEHS-95-48 Reducing College Dropouts
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