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Complexity and Targeting in Federal Student Aid: A Quantitative Analysis

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  • Susan Dynarski
  • Judith E. Scott-Clayton

Abstract

A growing body of empirical evidence shows that some financial aid programs increase college enrollment. Puzzlingly, there is little compelling evidence that Pell Grants and Stafford Loans, the primary federal student aid programs, are effective in achieving this goal. In this paper, we provide an in-depth review of this evidence, which taken as a whole suggests that complexity and uncertainty in the federal aid system undermine its efficacy. We document complexity in the aid system, comparing it in particular to complexity in the tax system. We build on our previous work by showing that complexity in the aid process does little to improve the targeting of both student loans and grants, for both dependent and independent students. We conclude that the current targeting of aid can be reproduced with a much simpler aid process. While we show that the targeting benefits of complexity are small, we further document that the costs are large. We offer new estimates of the compliance costs faced by applicants and the administrative costs borne by the government and colleges. These costs total at least $4 billion per year. The perspective of behavioral economics suggests that the true cost is even higher, since complexity and uncertainty may discourage the target population from applying for student aid.

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  • Susan Dynarski & Judith E. Scott-Clayton, 2008. "Complexity and Targeting in Federal Student Aid: A Quantitative Analysis," NBER Working Papers 13801, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:13801
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    Cited by:

    1. Gabrielle Fack & Julien Grenet, 2015. "Improving College Access and Success for Low-Income Students: Evidence from a Large Need-Based Grant Program," American Economic Journal: Applied Economics, American Economic Association, vol. 7(2), pages 1-34, April.
    2. Andrews, Rodney J. & Imberman, Scott A. & Lovenheim, Michael F., 2020. "Recruiting and supporting low-income, high-achieving students at flagship universities," Economics of Education Review, Elsevier, vol. 74(C).
    3. Booij, Adam S. & Leuven, Edwin & Oosterbeek, Hessel, 2012. "The role of information in the take-up of student loans," Economics of Education Review, Elsevier, vol. 31(1), pages 33-44.
    4. Andrew Barr & Sarah Turner, 2018. "A Letter and Encouragement: Does Information Increase Postsecondary Enrollment of UI Recipients?," American Economic Journal: Economic Policy, American Economic Association, vol. 10(3), pages 42-68, August.
    5. Vivian Yuen Ting Liu, 2020. "Is School Out for the Summer? The Impact of Year-Round Pell Grants on Academic and Employment Outcomes of Community College Students," Education Finance and Policy, MIT Press, vol. 15(2), pages 241-269, Spring.
    6. Linda Babcock & William Congdon & Lawrence Katz & Sendhil Mullainathan, 2012. "Notes on behavioral economics and labor market policy," IZA Journal of Labor Policy, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 1(1), pages 1-14, December.
    7. Steven D. Levitt & John A. List & Susanne Neckermann & Sally Sadoff, 2016. "The Behavioralist Goes to School: Leveraging Behavioral Economics to Improve Educational Performance," American Economic Journal: Economic Policy, American Economic Association, vol. 8(4), pages 183-219, November.
    8. Emily G. Moschini & Gajendran Raveendranathan & Ming Xu, 2022. "Over-optimism About Graduation and College Financial Aid," Department of Economics Working Papers 2022-09, McMaster University.
    9. Jeffrey A. Groen, 2011. "Building Knowledge Stocks Locally," Economic Development Quarterly, , vol. 25(4), pages 316-329, November.
    10. Kramer, Dennis A. & Lamb, Christina & Page, Lindsay C., 2021. "The effects of default choice on student loan borrowing: Experimental evidence from a public research university," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 470-489.
    11. Veronica Rattini, 2022. "The Effects of Financial Aid on Graduation and Labor Market Outcomes: New Evidence from Matched Education-Labor Data," CESifo Working Paper Series 10010, CESifo.
    12. Celeste K. Carruthers & Jilleah G. Welch, 2015. "Not Whether, but Where? Pell Grants and College Choices," Working Papers 2015-04, University of Tennessee, Department of Economics, revised 28 Sep 2015.
    13. Stephanie Riegg Cellini & Claudia Goldin, 2014. "Does Federal Student Aid Raise Tuition? New Evidence on For-Profit Colleges," American Economic Journal: Economic Policy, American Economic Association, vol. 6(4), pages 174-206, November.
    14. Toke Reinholt Fosgaard & Lars Gårn Hansen & Erik Wengström, 2017. "Framing and Misperception in Public Good Experiments," Scandinavian Journal of Economics, Wiley Blackwell, vol. 119(2), pages 435-456, April.
    15. Seth D. Zimmerman, 2014. "The Returns to College Admission for Academically Marginal Students," Journal of Labor Economics, University of Chicago Press, vol. 32(4), pages 711-754.
    16. Hastings, Justine S. & Neilson, Christopher A. & Ramirez, Anely & Zimmerman, Seth D., 2016. "(Un)informed college and major choice: Evidence from linked survey and administrative data," Economics of Education Review, Elsevier, vol. 51(C), pages 136-151.
    17. Bradley L. Hardy & Dave E. Marcotte, 2022. "Ties that bind? Family income dynamics and children’s post-secondary enrollment and persistence," Review of Economics of the Household, Springer, vol. 20(1), pages 279-303, March.
    18. Carruthers, Celeste K. & Welch, Jilleah G., 2019. "Not whether, but where? Pell grants and college choices," Journal of Public Economics, Elsevier, vol. 172(C), pages 1-19.
    19. Kelli Bird & Benjamin L. Castleman, 2016. "Here Today, Gone Tomorrow? Investigating Rates and Patterns of Financial Aid Renewal Among College Freshmen," Research in Higher Education, Springer;Association for Institutional Research, vol. 57(4), pages 395-422, June.
    20. Turner, Nicholas, 2011. "The Effect of Tax-Based Federal Student Aid on College Enrollment," National Tax Journal, National Tax Association;National Tax Journal, vol. 64(3), pages 839-861, September.
    21. Yi, Hongmei & Zhang, Linxiu & Yao, Yezhou & Wang, Aiqin & Ma, Yue & Shi, Yaojiang & Chu, James & Loyalka, Prashant & Rozelle, Scott, 2015. "Exploring the dropout rates and causes of dropout in upper-secondary technical and vocational education and training (TVET) schools in China," International Journal of Educational Development, Elsevier, vol. 42(C), pages 115-123.
    22. Turner, Nicholas, 2010. "The Effect of Tax-Based Federal Student Aid on College Enrollment," University of California at San Diego, Economics Working Paper Series qt6758069g, Department of Economics, UC San Diego.

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    More about this item

    JEL classification:

    • H0 - Public Economics - - General
    • H21 - Public Economics - - Taxation, Subsidies, and Revenue - - - Efficiency; Optimal Taxation
    • I2 - Health, Education, and Welfare - - Education
    • I22 - Health, Education, and Welfare - - Education - - - Educational Finance; Financial Aid
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy

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