Skip to main content

Tuition Discounting for Revenue Management

Abstract

Over the past decade, institutionally-funded financial aid (or “tuition discounts”) have been the fastest-growing item within most public four-year college and university operating budgets. One explanation for this trend is due to the changing structure of public colleges’ revenue streams, as tuition and fees have replaced state appropriations as a viable and predictable source of funding. This analysis explores the extent to which expenditures on institutionally-funded financial aid generates additional revenue for public four-year colleges and universities. Using institutional data (n = 174) from 2002 to 2008, the analysis implements a generalized method of moments (GMM) technique and concludes that aid indeed can be leveraged for revenue generation. However, this relationship is only sustainable to a certain point. When unfunded tuition discount rates exceed approximately 13%, institutions may experience diminishing revenue returns to this financial aid investment.

This is a preview of subscription content, access via your institution.

Fig. 1

Notes

  1. Hereafter, “tuition and fees” is referred to as “tuition.”

  2. Tuition discount rates are calculated by dividing total institutional aid expenditures by gross tuition revenue, as advocated by Baum and Lapovsky (2006).

References

  • Allan, R., & Lapovsky, L. (2005, July). Financial aid: Does it matter whether it’s funded? Business Officer Magazine.

  • Angrist, J. D. (2006). Instrumental variables methods in experimental criminological research: What, why and how? Journal of Experimental Criminology, 2(1), 23–44.

    Article  Google Scholar 

  • Archibald, R. B., & Feldman, D. H. (2008). Explaining increases in higher education costs. The Journal of Higher Education, 79(3), 268–295.

    Article  Google Scholar 

  • Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economic Studies, 58(2), 277–297.

    Article  Google Scholar 

  • Austin, D. A. (2010). Do lower lender subsidies reduce guaranteed student loan supply? Education Finance and Policy, 5(2), 138–176.

    Article  Google Scholar 

  • Baum, S., & Lapovsky, L. (2006). Tuition discounting: Not just a private practice. New York: The College Board.

    Google Scholar 

  • Baum, S., & Ma, J. (2010). Tuition discounting: Institutional aid patterns at public and private colleges and universities, 2000–01 to 2008–09 (p. 8). New York: The College Board.

    Google Scholar 

  • Baum, C. F., Schaffer, M. E., & Stillman, S. (2003). Instrumental variables and GMM: Estimation and testing. Stata Journal, 3(1), 1–31.

    Google Scholar 

  • Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143.

    Article  Google Scholar 

  • Blundell, R., Bond, S., & Windmeijer, F. (2000). Estimation in dynamic panel data models: Improving on the performance of the standard GMM estimator. Advances in Econometrics, 15, 53–92.

    Article  Google Scholar 

  • Bond, S. R. (2002). Dynamic panel data models: A guide to micro data methods and practice. Portuguese Economic Journal, 1(2), 141–162.

    Article  Google Scholar 

  • Bound, J., Jaeger, D. A., & Baker, R. M. (1995). Problems with instrumental variables estimation when the correlation between the instruments and the endogenous explanatory variable is weak. Journal of the American Statistical Association, 90(430), 443–450.

    Article  Google Scholar 

  • Bowen, H. R. (1980). The costs of higher education. San Francisco: Jossey-Bass.

    Google Scholar 

  • Breneman, D., Doti, J., & Lapovsky, L. (2001). Financing private colleges and universities: The role of tuition discounts. In M. B. Paulsen & J. C. Smart (Eds.), The finance of higher education: Theory, research, policy, and practice (pp. 279–461). New York: Algora Publishing.

    Google Scholar 

  • Brewer, D., Gates, S., & Goldman, C. (2002). In pursuit of prestige. Santa Monica: RAND Corporation.

    Google Scholar 

  • Brinkman, P., & Morgan, A. (2010). Financial planning: Strategies and lessons learned. Planning for Higher Education, 38(3), 5–14.

    Google Scholar 

  • Chen, R., & DesJardins, S. L. (2010). Investigating the impact of financial aid on student dropout risks: Racial and ethnic differences. The Journal of Higher Education, 81(2), 179–208.

    Article  Google Scholar 

  • Cheslock, J. J. (2006). Applying economics to institutional research on higher education revenues. New Directions for Institutional Research, 2006(132), 25–41.

    Article  Google Scholar 

  • College Board. (2010). SAT-ACT concordance tables. Retrieved October 14, 2010, from http://professionals.collegeboard.com/data-reports-research/sat/sat-act.

  • Curs, B. R. (2008). The effects of institutional merit-based aid on the enrollment decisions of needy students. Enrollment Management Journal, 2(1), 10–31.

    Google Scholar 

  • Curs, B. R., & Dar, L. (2010). Does state financial aid affect institutional aid? An analysis of the role of state policy on postsecondary institutional pricing strategies. SSRN eLibrary. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1641489

  • Curs, B. R., & Singell, L. D. (2010). Aim high or go low? Pricing strategies and enrollment effects when the net price elasticity varies with need and ability. The Journal of Higher Education, 81(4), 515–543.

    Article  Google Scholar 

  • Davis, J. S. (2003). Unintended consequences of tuition discounting. Indianapolis: Lumina Foundation.

    Google Scholar 

  • DesJardins, S. L., & McCall, B. P. (2010). Simulating the effects of financial aid packages on college student stopout, reenrollment spells, and graduation chances. The Review of Higher Education, 33(4), 513–541.

    Article  Google Scholar 

  • Desrochers, D., Lenihan, C., & Wellman, J. (2010). Trends in college spending, 1998–2008 (p. 56). Washington, DC: Delta Project on Postsecondary Education Costs, Productivity, and Accountability.

    Google Scholar 

  • Doyle, W. R. (2010). Changes in institutional aid, 1992–2003: The evolving role of merit aid. Research in Higher Education, 51(8), 789–810.

    Article  Google Scholar 

  • Doyle, W. R., Delaney, J. A., & Naughton, B. A. (2009). Does institutional aid compensate for or comply with state policy? Research in Higher Education, 50(5), 502–523.

    Article  Google Scholar 

  • Duffy, E. A., & Goldberg, I. (1998). Crafting a class: College admissions and financial aid, 1955–1994. Princeton: Princeton University Press.

    Google Scholar 

  • Ehrenberg, R., Zhang, L., & Levin, J. (2006). Crafting a class: The trade-off between merit scholarships and enrolling lower-income students. The Review of Higher Education, 29(2), 195–211.

    Article  Google Scholar 

  • Halaby, C. N. (2004). Panel models in sociological research: Theory into practice. Annual Review of Sociology, 30, 507–544.

    Article  Google Scholar 

  • Heller, D. (2006). State support of higher education: Past, present, and future. In D. M. Priest & E. P. S. John (Eds.), Privatization and public universities (pp. 11–37). Bloomington: Indiana University Press.

    Google Scholar 

  • Hossler, D. (2000). The role of financial aid in enrollment management. New Directions for Student Services, 2000(89), 77–90.

    Article  Google Scholar 

  • Hossler, D. (2004). Refinancing public universities: Student enrollment, incentive-based budgeting, and incremental revenue. In E. P. St. John & M. D. Parsons (Eds.), Public funding of higher education: Changing contexts and new rationales (pp. 145–163). Baltimore: Johns Hopkins University Press.

    Google Scholar 

  • Hossler, D. (2006). Students and families as revenue: The impact on institutional behaviors. In D. M. Priest & E. P. S. John (Eds.), Privatization and public universities (pp. 109–128). Bloomington: Indiana University Press.

    Google Scholar 

  • Hossler, D., Ziskin, M., Gross, J. P., Kim, S., & Cekic, O. (2009). Student aid and its role in encouraging persistence. In C. Smart (Ed.), Higher education: Handbook of theory and research (pp. 389–425). New York: Agathon Press.

    Chapter  Google Scholar 

  • Johnstone, D. B. (2004). The economics and politics of cost sharing in higher education: Comparative perspectives. Economics of Education Review, 23(4), 403–410.

    Article  Google Scholar 

  • Johnstone, B. D., & Marcucci, P. N. (2010). Financing higher education worldwide. Baltimore: John Hopkins University Press.

    Google Scholar 

  • Kiviet, J. F. (1995). On bias, inconsistency, and efficiency of various estimators in dynamic panel data models 1. Journal of Econometrics, 68(1), 53–78.

    Article  Google Scholar 

  • Lapovsky, L. (2007). Critical endowment policy issues. New Directions for Higher Education, 2007(140), 99–110.

    Article  Google Scholar 

  • Lasher, W., & Sullivan, C. (2005). Follow the money: The changing world of budgeting in higher education. In J. C. Smart (Ed.), Higher education: Handbook of theory and research (Vol. 19, pp. 197–240). Dordrecht: Kluwer Academic Publishers.

    Chapter  Google Scholar 

  • Martin, R. E. (2004). Tuition discounting without tears. Economics of Education Review, 23(2), 177–189.

    Article  Google Scholar 

  • Martin, R. E. (2005). Cost control college access and competition in higher education. Northhampton: Edward Elgar Publishing.

    Google Scholar 

  • Massa, R. J., & Parker, A. S. (2007). Fixing the net tuition revenue dilemma: The Dickinson College story. New Directions for Higher Education, 140, 87–98.

    Article  Google Scholar 

  • McPherson, M. S., & Schapiro, M. O. (1998). The student aid game: Meeting need and rewarding talent in American higher education. Princeton: Princeton University Press.

    Google Scholar 

  • McPherson, M. S., & Schapiro, M. O. (2006). US higher education finance. In E. Hanushek & F. Welch (Eds.), Handbook of the economics of education (Vol. 2, pp. 1403–1434). Amsterdam: Elsevier Press.

    Chapter  Google Scholar 

  • Nickell, S. (1981). Biases in dynamic models with fixed effects. Econometrica, 49(6), 1417–1426.

    Article  Google Scholar 

  • Perna, L. W. (2010). Toward a more complete understanding of the role of financial aid in promoting college enrollment: The importance of context. Higher Education: Handbook of Theory and Research, 25, 129–179.

    Article  Google Scholar 

  • Perna, L., Lundy-Wagner, V., Yee, A., Brill, L., & Tadal, T. (2010). Showing them the money: The role of institutional financial aid policies and communication strategies in attracting low-income students. In A. Kezar (Ed.), Recognizing and serving low-income students in higher education: An examination of institutional policies, practices, and culture. New York: Routledge.

    Google Scholar 

  • Potter, D. A., & Sidar, A. G., Jr. (1978). No-need/merit awards: A survey of their use at four-year public and private colleges and universities. New York: College Entrance Examination Board.

    Google Scholar 

  • Redd, K. E. (2000). Discounting toward disaster: Tuition discounting, college finances, and enrollments of low-income undergraduates. Indianapolis, IN: USA Group Foundation.

    Google Scholar 

  • Reed, M., & Shireman, R. (2008). Time to reexamine institutional cooperation on financial aid (p. 35). Washington, DC: The Institute for College Access and Success.

    Google Scholar 

  • Roodman, D. (2006). How to do xtabond2: An introduction to difference and system GMM in Stata. Washington, DC: Center for Global Development.

    Google Scholar 

  • Roodman, D. (2009). A note on the theme of too many instruments. Oxford Bulletin of Economics and Statistics, 71(1), 135–158.

    Article  Google Scholar 

  • Stock, J. H., & Yogo, M. (2002). Testing for weak instruments in linear IV regression. NBER Working Paper #284.

  • Summers, J. A. (2004). Net tuition revenue generation at private liberal arts colleges. Education Economics, 12(3), 219.

    Article  Google Scholar 

  • Thelin, J. R. (2004). A history of American higher education. Baltimore: The Johns Hopkins University Press.

    Google Scholar 

  • Titus, M. A. (2009). The production of bachelor’s degrees and financial aspects of state higher education policy: A dynamic analysis. The Journal of Higher Education, 80(4), 439–468.

    Article  Google Scholar 

  • U.S. Department of Education. (2009). 2007–08 National Postsecondary Student Aid Study (NPSAS:08): Undergraduate data analysis system. Retrieved October 8, 2010, from http://nces.ed.gov/surveys/npsas/.

  • Weisbrod, B. A., Ballou, J. P., & Asch, E. D. (2008). Mission and money: Understanding the university. Cambridge: Cambridge University Press.

    Google Scholar 

  • Wilkinson, R. (2005). Aiding students, buying students: Financial aid in America. Nashville: Vanderbilt University Press.

    Google Scholar 

  • Windmeijer, F. (2005). A finite sample correction for the variance of linear efficient two-step GMM estimators. Journal of Econometrics, 126(1), 25–51.

    Article  Google Scholar 

  • Wooldridge, J. M. (2002). Econometric analysis of cross section and panel data. Cambridge: MIT Press.

    Google Scholar 

  • Zhang, L. (2007). Nonresident enrollment demand in public higher education: An analysis at national, state, and institutional levels. The Review of Higher Education, 31(1), 1–25.

    Article  Google Scholar 

Download references

Acknowledgments

The author would like to thank David Tandberg and two anonymous reviewers for comments on previous versions of this paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nicholas W. Hillman.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Hillman, N.W. Tuition Discounting for Revenue Management. Res High Educ 53, 263–281 (2012). https://doi.org/10.1007/s11162-011-9233-4

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11162-011-9233-4

Keywords

  • Institutional aid
  • Enrollment management
  • Revenue generation
  • GMM