1. Deferred Costs, Delayed Credentials: High Debt among Community College Transfer Students Student Financial Aid Research Network Conference June 20, 2013 Jeff Webster Assistant Vice-President, Research & Analytical Services Chris Fernandez Research Specialist, Research & Analytical Services TG

2. Transfer students are more likely to borrow

3. Cumulative debt varies by school sector

4. Native students receive more institutional aid

5. Post-transfer borrowing drives indebtedness

6. Borrower rates vary slightly by race/ethnicity

7. Hispanic students who transfer borrow more than those who are native

8. Native students receive more institutional aid

9. Hispanics borrow heavily post-transfer

10. 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?

11. 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

12. Income Distribution- Public U.S. Dept of Education, Baccalaureate and Beyond 2009 (B&B:09)

13. Income Distribution- Private

14. Borrowing by income decile- Public U.S. Dept of Education, Baccalaureate and Beyond 2009 (B&B:09)

15. Borrowing by income decile- Private U.S. Dept of Education, Baccalaureate and Beyond 2009 (B&B:09)

16. 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 CBL t =∑ i(W i,n )(B i,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” CBL t (public)= $20,959CBL t (private)=$29,363 Actual public= $21,121Actual private=$29,961 Suggests possible influence of lower incomes for transfer students at only public institutions; however, no control for covariates & other factors

17. Counterfactual Method- Most significant results VariablePublic CounterfactualPrivate 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

18. 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

19. 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

20. Results of a Simple Regression Model Regress cumulative borrowing on patterned factors b S.E. t p-valueLower 95%Upper 95% Intercept 21430.8123039.3050.00016889.1625972.46 CC Transfer -1437.48726.6-1.9790.049-2870.27-4.69 Income -0.030.01-4.0820.000-0.05-0.02 SAT -4.941.93-2.5600.011-8.74-1.13 Time to degree 67.6718.783.6040.00030.64104.70 Private sector 5053.5816363.0890.0021827.468279.70 Tuition/fees 0.620.096.6030.0000.430.80 Grants -0.370.08-4.4100.000-0.54-0.21

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; R 2 <.15

22. Regression for transfers only b S.E. t p-valueLower 95%Upper 95% Intercept 18805.2354138.354.5440.00010644.40126966.068 Income -0.0640.01-5.0350.000-0.089-0.039 SAT -0.3433.57-0.0960.924-7.3926.707 Time to degree 41.20231.461.3100.192-20.845103.248 Private sector 5880.2092801.162.0990.037356.32911404.090 Tuition/fees 0.7520.184.2620.0000.4041.100 Grants -0.7110.17-4.0860.000-1.053-0.368

23. 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)

24. 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

25. 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

26. 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

27. © 2010 Texas Guaranteed Student Loan Corporation To order additional copies, or to request permission to reproduce any of the information provided, please call TG Communications at (800) 252-9743. Jeff Webster Assistant Vice-president Research and Analytical Services, TG jeff.webster@tgslc.org Look for this report in Fall 2013 at www.tgslc.org/research