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The credits that count: how credit growth and financial aid affect college tuition and fees

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  • Katharina Best
  • Jussi Keppo

Abstract

Using a two-stage least squares model, we build a macroeconomic model of supply and demand for US higher education as measured by enrollment. We find that college education benefits (e.g. relative earnings and employment level), credit factors (e.g. student loan amounts and household debt), and financial aid shift demand. Higher tuition prices increase the appeal of higher education for students but credit constraints put a barrier on demand growth. Tuition prices and debt levels are highly correlated, suggesting that students respond to higher tuition prices by borrowing. School's operating costs as well as tuition and non-tuition revenue drive supply. Schools can use tuition prices to signal quality, and relative demand-side price-in-elasticity allows them to raise prices. For the private institution sector alone, we see a higher level of consumer price sensitivity, with schools determining enrollment levels and adjusting tuition price accordingly.

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  • Katharina Best & Jussi Keppo, 2014. "The credits that count: how credit growth and financial aid affect college tuition and fees," Education Economics, Taylor & Francis Journals, vol. 22(6), pages 589-613, December.
    • Handle: RePEc:taf:edecon:v:22:y:2014:i:6:p:589-613
    DOI: 10.1080/09645292.2012.687102
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    References listed on IDEAS

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    1. Joshua D. Angrist & Alan B. Krueger, 2001. "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 69-85, Fall.
    2. Ulla Hämäläinen & Roope Uusitalo, 2008. "Signalling or Human Capital: Evidence from the Finnish Polytechnic School Reform," Scandinavian Journal of Economics, Wiley Blackwell, vol. 110(4), pages 755-775, December.
    3. Nicole M. Fortin, 2006. "Higher-Education Policies and the College Wage Premium: Cross-State Evidence from the 1990s," American Economic Review, American Economic Association, vol. 96(4), pages 959-987, September.
    4. repec:fth:prinin:455 is not listed on IDEAS
    5. Joshua Angrist & Alan Krueger, 2001. "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments," Working Papers 834, Princeton University, Department of Economics, Industrial Relations Section..
    6. Singell, Larry Jr. & Stone, Joe A., 2007. "For whom the Pell tolls: The response of university tuition to federal grants-in-aid," Economics of Education Review, Elsevier, vol. 26(3), pages 285-295, June.
    7. Bridget Terry Long, 2004. "How do Financial Aid Policies Affect Colleges?: The Institutional Impact of the Georgia HOPE Scholarship," Journal of Human Resources, University of Wisconsin Press, vol. 39(4).
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    Cited by:

    1. Xiaodan Hu & Pedro Villarreal, 2019. "Public Tuition on the Rise: Estimating the Effects of Louisiana’s Performance-Based Funding Policy on Institutional Tuition Levels," Research in Higher Education, Springer;Association for Institutional Research, vol. 60(5), pages 636-669, August.
    2. Despard, Mathieu R. & Perantie, Dana & Taylor, Samuel & Grinstein-Weiss, Michal & Friedline, Terri & Raghavan, Ramesh, 2016. "Student debt and hardship: Evidence from a large sample of low- and moderate-income households," Children and Youth Services Review, Elsevier, vol. 70(C), pages 8-18.

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