Advertisement

Research in Higher Education

, Volume 60, Issue 4, pp 438–457 | Cite as

Framing and Labeling Effects in Preferences for Borrowing for College: An Experimental Analysis

  • Brent J. EvansEmail author
  • Angela Boatman
  • Adela Soliz
Article

Abstract

Evidence from behavioral economics suggests that the framing and labeling of choices affect financial decisions. Through a randomized control trial of over six thousand high school seniors, community college students, and adults without a college degree, we identify the existence of both framing and labeling effects in respondents’ preferences for borrowing for postsecondary education. How financially equivalent contracts are framed alters the preferences of high school and community college students. Furthermore, simply labeling a contract a “loan” reduces the likelihood of selecting that option by 8–11 percentage points among those samples. These effects are more pronounced among Black high school respondents and Hispanic high school and community college respondents who are both twice as likely as White respondents to avoid the loan option when it is labeled a “loan.” Finally, we provide suggestive evidence that this labeling effect is driven by more risk averse respondents. Our findings imply that the federal government, states, and institutions should be attentive to the language used when offering and explaining financial aid packages for higher education.

Keywords

Educational economics State and federal aid Student financial aid Student loans 

Notes

Acknowledgements

We thank the Lumina Foundation for their financial support. We also thank Miguel Palacios for his prior research on this topic and his useful insights on our analysis. The views contained herein are not necessarily those of the Lumina Foundation. All errors, omissions, and conclusions are our own.

References

  1. Abraham, K. G., Filiz-Ozbay, E., Ozbay, E. Y., & Turner, L. J. (2018). Framing effects, earnings expectations, and the design of student loan repayment schemes. NBER Working Paper No. 24484.Google Scholar
  2. Addo, F., Houle, J., & Simon, D. (2016). Young, black and (still) in the red: Parental wealth, race and student loan debt. Race and Social Problems, 8, 64–76.CrossRefGoogle Scholar
  3. Avery, C., & Hoxby, C. M. (2004). Do and should financial aid packages affect students’ college choices? In C. Avery & C. M. Hoxby College choices: The economics of where to go, when to go, and how to pay for it (pp. 239–299).Google Scholar
  4. Avery, C., & Turner, S. (2012). Student loans: Do college students borrow too much or not enough? Journal of Economic Perspectives, 26(1), 165–192.CrossRefGoogle Scholar
  5. Banks, S., Salovey, P., Greener, S., Rothman, A., Moyer, A., Beauvais, J., et al. (1995). The effects of message framing on mammography utilization. Healthy Psychology, 14(2), 178–184.CrossRefGoogle Scholar
  6. Boatman, A., Evans, B., Soliz, A. (2014). Applying the lessons of behavioral economics to improve the federal student loan programs: Six policy recommendations. Lumina Foundation.Google Scholar
  7. Boatman, A., Evans, B., & Soliz, A. (2017). Understanding loan aversion in education: Evidence from high school seniors, community college students, and adults. AERA Open, 3(1), 1–16.CrossRefGoogle Scholar
  8. Caetano, G., Palacios, M., & Patrinos, H. A. (2011). Measuring aversion to debt: An experiment among student loan candidates. World Bank Working Paper.Google Scholar
  9. Callender, C., & Jackson, J. (2005). Does the fear of debt deter students from higher education? Journal of Social Policy, 34, 509–540.CrossRefGoogle Scholar
  10. Carnevale, A. P., Rose, S. J., & Cheah, B. (2011). The college payoff: Education, occupations, lifetime earnings. Washington, DC: Georgetown University Center on Education and the Workforce.Google Scholar
  11. College Board. (2015a). Trends in college pricing. New York: College Board.Google Scholar
  12. College Board. (2015b). Trends in student aid. New York: College Board.Google Scholar
  13. Conley, D. (1999). Being black, living in the red: Race, wealth and social policy in America. Berkeley: University of California Press.Google Scholar
  14. Conley, D. (2001). Capital for college: Parental assets and postsecondary schooling. Sociology of Education, 74(1), 59–72.CrossRefGoogle Scholar
  15. Cooper, M. J., Gulen, H., & Rau, P. R. (2005). Changing names with style: Mutual fund name changes and their effects on fund flows. Journal of Finance, 60, 2825–2858.CrossRefGoogle Scholar
  16. Cunningham, A., & Santiago, D. (2008). Student aversion to borrowing: Who borrows and who doesn’t. Washington, DC: Institute for Higher Education Policy.Google Scholar
  17. Delisle, J. (2017). Student and parent perspectives on higher education financing: Findings from a nationally representative survey on income-share agreements. Washington, DC: American Enterprise Institute.Google Scholar
  18. Douglas-Gabriel, D. (2015). Investors buying shares in college students: Is this the wave of the future? Purdue University thinks so. Washington Post.Google Scholar
  19. Eckel, C. C., & Grossman, P. J. (2008). Forecasting risk attitudes: An experimental study using actual and forecast gamble choices. Journal of Economic Behavior & Organization, 68, 1–17.CrossRefGoogle Scholar
  20. ECMC Group Foundation. (2003). Cultural barriers to incurring debt: An exploration of borrowing and impact on access to postsecondary education. Caliber Associates.Google Scholar
  21. Epley, N., Mak, D., & Idson, L. (2006). Bonus or rebate? The Impact of income framing on spending and saving. Journal of Behavioral Decision Making, 19(3), 213–227.CrossRefGoogle Scholar
  22. Fellner, G., & Maciejovsky, B. (2007). Risk attitude and market behavior: Evidence from experimental asset markets. Journal of Economic Psychology, 28(1), 338–350.CrossRefGoogle Scholar
  23. Field, E. (2009). Educational debt burden and career choice: Evidence from a financial aid experiment at NYU Law school. American Economic Journal: Applied Economics, 1, 1–21.Google Scholar
  24. Goldrick-Rab, S., & Kelchen, R. (2013). Making sense of loan aversion: Evidence from Wisconsin. Paper prepared for the University of Michigan Conference on Student Loans.Google Scholar
  25. Grodsky, E., & Jones, M. (2007). Real and imagined barriers to college entry: Perceptions of cost. Social Science Research, 36, 745–766.CrossRefGoogle Scholar
  26. Hillman, N. W. (2015). Borrowing and repaying student loans. Journal of Student Financial Aid, 45(3), Article 5.Google Scholar
  27. Johnson, E., Hershey, J., Meszaros, J., & Kunreuther, H. (1993). Framing, probability distortions, and insurance decisions. Journal of Risk and Uncertainty, 7, 35–51.CrossRefGoogle Scholar
  28. Kane, T. J., & Rouse, C. E. (1995). Labor-market returns to two- and four-year college. American Economic Review, 85, 600–614.Google Scholar
  29. Keller, P., Lipkus, I., & Rimer, B. (2003). Affect, framing and persuasion. Journal of Marketing Research, 40, 54–64.CrossRefGoogle Scholar
  30. Keller, C., & Siegrist, M. (2006). Investing in stocks: The influence of financial risk attitude and values-related money and stock market attitudes. Journal of Economic Psychology, 27(1), 285–303.CrossRefGoogle Scholar
  31. Koppell, J. G., & Steen, J. A. (2004). The effects of ballot position on election outcomes. The Journal of Politics, 66, 267–281.CrossRefGoogle Scholar
  32. Krosnick, J. A., & Alwin, D. F. (1987). An evaluation of a cognitive theory of response-order effects in survey measurement. Public Opinion Quarterly, 51, 201–219.CrossRefGoogle Scholar
  33. Loewenstein, G. (1988). Frames of mind in intertemporal choice. Management Science, 34, 200–214.CrossRefGoogle Scholar
  34. Loewenstein, G., & Prelec, D. (1992). Anomalies in intertemporal choice: Evidence and an interpretation. Quarterly Journal of Economic, 107, 573–597.CrossRefGoogle Scholar
  35. Marcus, J. (2016). Student’s futures as investments: The promise and challenges of income-share agreements. Washington, DC: American Enterprise Institute.Google Scholar
  36. Marx, B. M. & Turner, L. J. (2017). Borrowing trouble? Human capital investment with opt-in costs and implications for the effectiveness of grant aid. Working paper.Google Scholar
  37. Monks, J. (2009). The impact of merit-based financial aid on college enrollment: A field experiment. Economics of Education Review, 28, 99–106.CrossRefGoogle Scholar
  38. Mullainathan, S., Schwartzstein, J., & Shleifer, A. (2008). Coarse thinking and persuasion. Quarterly Journal of Economics, 123, 577–619.CrossRefGoogle Scholar
  39. National Center for Education Statistics (NCES). (2015). The condition of education 2015. Washington, DC: U.S. Department of Education.Google Scholar
  40. National Center for Education Statistics (NCES). (2016). The condition of education 2016. Washington, DC: U.S. Department of Education.Google Scholar
  41. New American & uAspire. (2018). Decoding the cost of college: The case for transparent financial aid award letters. Washington, DC.Google Scholar
  42. Palacious, M., DeSorrento, T., & Kelly, A. P. (2014). Investing in value, sharing risk: Financing higher education through income share agreements. Washington, DC: American Enterprise Institute.Google Scholar
  43. Palameta, B., & Voyer, J. (2010). Willingness to pay for postsecondary education among under-represented groups. Toronto: Higher Education Quality Council of Ontario.Google Scholar
  44. Pew Research Center. (2014). The rising cost of not going to college. Washington, DC: Pew Research Center.Google Scholar
  45. Sabater-Grande, G., & Georgantzis, N. (2002). Accounting for risk aversion in preated prisoners’ dilemma games: An experimental test. Journal of Economic Behavior & Organization, 48(1), 37–50.CrossRefGoogle Scholar
  46. Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211(4481), 453–458.CrossRefGoogle Scholar
  47. Vedder, R. (2015). Income share agreements, and their role in making higher education more affordable. Forbes.Google Scholar
  48. Warneryd, K. E. (1996). Risk attitudes and risky behavior. Journal of Economic Psychology, 17(1), 749–770.CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Peabody CollegeVanderbilt UniversityNashvilleUSA

Personalised recommendations