Deferred Costs, Delayed Credentials:High Debt among Community College Transfer Students

Student Financial Aid Research Network ConferenceJune 20, 2013Jeff WebsterAssistant Vice-President, Research & Analytical ServicesChris FernandezResearch Specialist, Research & Analytical ServicesTG

Transfer students are more likely to borrow

Cumulative debt varies by school sector

Native students receive more institutional aid

Post-transfer borrowing drives indebtedness

Borrower rates vary slightly by race/ethnicity

Hispanic students who transfer borrow more than those who are native

Native students receive more institutional aid

Hispanics borrow heavily post-transfer

New Research Questions

• How does the population of transfer student bachelor’s grads differ significantly from the population of “native” bachelor’s grads?

• Do these differences have a significant impact on grant aid and/or student borrowing?

Data and Methods

• Data source: Baccalaureate & Beyond (2009)• Descriptive statistics w/ counterfactual method

informing multivar regression• “Transfer”: first postsecondary institution= “2-yr

public”• “Native”: number of institutions attended before

graduation= “one”• “Public” = 4-yr public • “Private”= 4-yr private non-profit

Income Distribution- Public

1-10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-1000%

2%

4%

6%

8%

10%

12%

14%

16%Borrowers at Public institutions

Transfer NativeIncome decile

U.S. Dept of Education, Baccalaureate and Beyond 2009 (B&B:09)

Income Distribution- Private

1-10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-1000%2%4%6%8%

10%12%14%16%18%

Borrowers at Private institutions

Transfer Native

Income decile

U.S. Dept of Education, Baccalaureate and Beyond 2009 (B&B:09)

Borrowing by income decile- Public

1-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100$0

$5,000

$10,000

$15,000

$20,000

$25,000Borrowers at Public institutions

Transfer NativeIncome decile

U.S. Dept of Education, Baccalaureate and Beyond 2009 (B&B:09)

Borrowing by income decile- Private

1-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 $-

$5,000

$10,000

$15,000

$20,000

$25,000

$30,000

$35,000 Borrowers at Private institutions

Transfer NativeIncome decile

U.S. Dept of Education, Baccalaureate and Beyond 2009 (B&B:09)

Counterfactual Method for Estimating Effects of Population Distributions• Recalculate transfer borrowing as a weighted average of subgroup

averages given native student population distribution statistics• Difference between actual and hypothetical is an estimate of the

effect of disparate population distributions

CBLt=∑ i(Wi,n)(Bi,t)

“The counterfactual borrowing level for transfer students equals the sum for all income groups (in this case) of the weight (%) of a group for native

students multiplied by average borrowing for that group for transfer students”

CBLt(public)= $20,959 CBLt(private)=$29,363

Actual public= $21,121 Actual private=$29,961• Suggests possible influence of lower incomes for transfer students at

only public institutions; however, no control for covariates & other factors

Counterfactual Method- Most significant results

Variable Public Counterfactual Private Counterfactual

Dependence (-)$1,380 $857

SAT/ACT equiv. (-)$2,047 $1,476

Time to degree (-)$2,142 $1,346

Tuition/fees $735 $1,684

Tuition/fees; native to transfer (-)$769 (-)$3,085

• Better prepared private transfers go to higher priced schools, take on more debt

• Private transfers experience half the “savings premium” of lower cost schools vs. native students

Factors without Apparent Effect

• Race/ethnicity: Transfer graduates slightly more diverse• Geographic region: Both transferring and debt vary significantly

by region, but they aren’t linked. Transfers see better outcomes in the southwest & far west

• Housing: Transfer students’ slightly greater tendency to live off-campus had a very minor impact

• Sex/gender: Only difference is high borrowing among female transfer students at private institutions due to income disparity

• Family type: Transfer students more likely to be married and/or have dependents

• Financial aid participation: similar rates• Employment/earnings: Transfers work and earn more• Credits transferred: No apparent relationship to borrowing

Breaking down grant aid• Breakdown by tuition/fees and income showed that

transfer students at public institutions receive similar grant funding; transfer students at private institutions tend to receive less grant funding

• Breakdown of private institution transfer student’s grant aid by tuition/fees, source, and type– By source: transfers receive similar state and federal grant

aid but far less institutional aid– By type: transfers receive less need aid (except most

expensive schools) and far less merit aid– this despite significantly lower median incomes

• SAT & intensity control changed rates, not amounts

Results of a Simple Regression Model• Regress cumulative borrowing on patterned factors

b S.E. t p-value Lower 95% Upper 95%

Intercept 21430.81 2303 9.305 0.000 16889.16 25972.46

CC Transfer -1437.48 726.6 -1.979 0.049 -2870.27 -4.69

Income -0.03 0.01 -4.082 0.000 -0.05 -0.02

SAT -4.94 1.93 -2.560 0.011 -8.74 -1.13

Time to degree 67.67 18.78 3.604 0.000 30.64 104.70

Private sector 5053.58 1636 3.089 0.002 1827.46 8279.70

Tuition/fees 0.62 0.09 6.603 0.000 0.43 0.80

Grants -0.37 0.08 -4.410 0.000 -0.54 -0.21

Results of a Simple Regression Model• CC transfer: $1,500 less borrowing• Attending a private institution: $5,000 more borrowing

(while controlling for tuition/fees)• SAT: $5 per point less borrowing• Grants: $0.37 per dollar less borrowing• Time to degree: $68 per month more borrowing• Caveats: associations, not causation

– Large amount of unaccounted variability; R2<.15

Regression for transfers only

b S.E. t p-value Lower 95% Upper 95%

Intercept 18805.235 4138.35 4.544 0.000 10644.401 26966.068

Income -0.064 0.01 -5.035 0.000 -0.089 -0.039

SAT -0.343 3.57 -0.096 0.924 -7.392 6.707

Time to degree 41.202 31.46 1.310 0.192 -20.845 103.248

Private sector 5880.209 2801.16 2.099 0.037 356.329 11404.090

Tuition/fees 0.752 0.18 4.262 0.000 0.404 1.100

Grants -0.711 0.17 -4.086 0.000 -1.053 -0.368

Regression for transfers only• Private 4-yr enrollment: increase to $5,880 more

borrowing (from $5,053)• Grants: increase to $0.71 per dollar less borrowing

(from $0.37)• Regression for only private institutions showed

higher borrowing for transfers, but not statistically significant (sampling issues)

Conclusions • All else equal, starting at a CC is associated with less

borrowing• All else is not equal; demographic, behavioral, and

institutional differences contribute to higher borrowing for transfers

• Demographic and behavioral factors more influential at publics

• Institutional factors more influential at privates• Transfers receive similar grants at publics• Transfers receive significantly lower grants at privates,

even when controlling for other factors

Student/counseling implications• New argument against “undermatching”: initial 4-yr

enrollment carries bigger rewards, lower risks, and (often) similar/lower debt

• However, overmatching may be worse for many who would’ve enrolled in a CC

• Old message: finish on time, make sure credits transfer• New messages: caution with transfer to private

institutions; apply to multiple colleges; try to get financial aid letters before enrollment

Policy implications• Policy infrastructure for transfer needs reform• Emphasis on articulations, robust academic &

financial support/advising for transfers, & need-based grant aid at 4-years

• Course flexibility (scheduling, online, etc.) and 60 credit cap for associate degrees

• Aid flexibility, not time restrictions• Enhanced oversight, accountability, and/or

incentives for transfer outcomes at 4-yr’s• Transfers must be explicitly included in efforts to

improve outcomes for higher risk students

© 2010 Texas Guaranteed Student Loan CorporationTo order additional copies, or to request permission to reproduce any of the information provided,

please call TG Communications at (800) 252-9743.

Jeff WebsterAssistant Vice-presidentResearch and Analytical Services, TGjeff.webster@tgslc.org

Look for this report in Fall 2013 at www.tgslc.org/research