Heterogeneous effects of socioeconomic status on postsecondary educational outcomes: Evidence from the Education Longitudinal Study of 2002

Wright, Harrison (2025): Heterogeneous effects of socioeconomic status on postsecondary educational outcomes: Evidence from the Education Longitudinal Study of 2002.

Abstract

There is extensive economic literature on the returns to higher education, finding substantial benefits. However, access to higher education in the United States is unequal, with students of lower socioeconomic status (SES) attending and completing college at lower rates. This paper studies the effects of SES on these two postsecondary educational outcomes, utilizing data on a cohort of students from the Education Longitudinal Study of 2002 (ELS:2002). Employing both linear probability and probit maximum likelihood models, we analyze the ways SES influences college attendance and completion, while controlling for critical variables such as prior academic performance, high school quality, parental education, and demographic factors to isolate the effects to the financial resources and social capital associated with higher SES. Higher SES is associated with increased probabilities of both attending and completing college, though the marginal effects vary across the range of SES. The average partial effect of a unit increase in the SES variable (which ranges from -2.11 to 1.98) is a 7.3 percentage point increase in the probability of college attendance, and a 7.6 percentage point increase for bachelor’s degree completion. There is significant heterogeneity across the range of the independent variable of interest: changes in SES have the highest (lowest) impact on attendance for low (high)-SES students, while the effect on degree completion is strongest for high-SES students and weakest for low-SES students. These results are tested for robustness to model specifications restricted by gender and race. The findings of this study highlight the continuing inequality in college access and degree attainment, with implications for policymakers and universities.

• Item Type: MPRA Paper
• Language: English
• Keywords: Education; socioeconomic status; college; higher education; inequality; probit
• Subjects: I - Health, Education, and Welfare > I2 - Education and Research Institutions > I24 - Education and Inequality

References

Ai, C., & Norton, E. (2003). Interaction terms in logit and probit models. Economics Letters, 80(1), 123-129. https://doi.org/https://doi.org/10.1016/S0165-1765(03)00032-6

Averett, S., & Burton, M. (1996). College attendance and the college wage premium: differences by gender. Economics of Education Review, 15(1), 37-49. https://doi.org/https://doi.org/10.1016/0272-7757(95)00027-5

Bettinger, E., Long, B., Oreopoulos, P., & Sanbonmatsu, L. (2009). The role of simplification and information in college decisions: results from the H&R Block FAFSA experiment. National Bureau of Economic Research. https://www.nber.org/system/files/working_papers/w15361/w15361.pdf

Bjorklund-Young, A. (2016). Family income and the college completion gap. Institute for Education Policy, Johns Hopkins University.

Blanden, J., Doepke, M., & Stuhler, J. (2022). Educational inequality. National Bureau of Economic Research Working Paper Series, No. 29979. https://doi.org/10.3386/w29979

Bowen, W., Chingos, Matthew., McPherson, M. (2009). Crossing the Finish Line: Completing College at America’s Public Universities. Princeton University Press, 2009.

Carneiro, P., & Heckman, J. (2002). The evidence on credit constraints in post‐secondary schooling. The Economic Journal, 112(482), 705-734.

Carroll, S., & Erkut, E. (2009). How taxpayers benefit when students attain higher levels of education. RAND Corporation. https://doi.org/10.7249/RB9461

Chetty, R. Friedman, J., Saez, E., Turner, N., & Yagan, D. (2020). Income segregation and intergenerational mobility across colleges in the United States. The Quarterly Journal of Economics, Volume 135, Issue 3, August 2020, Pages 1567–1633, https://doi.org/10.1093/qje/qjaa005

Denning, J., Marx, B., & Turner, L. (2019). ProPelled: the effects of grants on graduation, earnings, and welfare. American Economic Journal: Applied Economics, 11 (3): 193–224.

DesJardins, S., Ahlburg, D., & McCall, B. (2006). The effects of interrupted enrollment on graduation from college: racial, income, and ability differences. Economics of Education Review, 25(6), 575-590.

Duncan, O. (1961). A social economic index for all occupations. Free Press. In A.J. Reiss Jr. (Ed.), Occupations and Social Status, Free Press.

Dynarski, S. (2015, June 2). For the poor, the graduation gap is even wider than the enrollment gap. The New York Times. https://www.nytimes.com/2015/06/02/upshot/for-the-poor-the-graduation-gap-is-even-wider-than-the-enrollment-gap.html

Greene, W. (2010). Testing hypotheses about interaction terms in nonlinear models. Economics Letters, 107(2), 291-296. https://doi.org/https://doi.org/10.1016/j.econlet.2010.02.014

Greene, W. (2018). Econometric Analysis. 8th ed. New York: Pearson.

Gutman, L., & Schoon, I. (2013). The impact of non-cognitive skills on outcomes for young people: a literature review. Education Endowment Foundation, University of London. Retrieved from https://discovery.ucl.ac.uk/id/eprint/10125763/.

Jacob, B. (2002). Where the boys aren't: non-cognitive skills, returns to school and the gender gap in higher education. Economics of Education Review, 21(6), 589-598. https://doi.org/https://doi.org/10.1016/S0272-7757(01)00051-6

Kochhar, R. (2024). The state of the American middle class: Who is in it and key trends from 1970 to 2023. Pew Research Center.

Mountjoy, J. (2024). Marginal returns to public universities. National Bureau of Economic Research Working Paper Series, No. 32296. https://doi.org/10.3386/w32296

National Center for Education Statistics, United States Department of Education (2005). Education Longitudinal Study (ELS), 2002. https://doi.org/10.3886/ICPSR04275.v1

National Center for Education, United States Department of Education (2021). Digest of Education Statistics: 2021. https://nces.ed.gov/programs/digest/d15/tables/dt15_104.10.asp

Oreopoulos, P., & Petronijevic, U. (2013). Making college worth it: a review of the returns to higher education. The Future of Children, 23. https://doi.org/10.2307/23409488

Papke, L., & Wooldridge, J. (1996). Econometric methods for fractional response variables with an application to 401 (K) plan participation rates. Journal of Applied Econometrics, 11(6), 619-632.

Pell Grant Preservation and Expansion Act of 2024, S.4595, 118th Congress (2024). https://www.congress.gov/bill/118th-congress/senate-bill/4595/text

Ramsey, J. (1969). Tests for Specification Errors in Classical Linear Least-Squares Regression Analysis. Journal of the Royal Statistical Society. Series B (Methodological), 31(2), 350-371.

Saez, E., & Zucman, G. (2016). Wealth inequality in the United States since 1913: Evidence from capitalized income tax data . The Quarterly Journal of Economics, 131(2), 519-578. https://doi.org/10.1093/qje/qjw004

Sirin, S. (2005). Socioeconomic status and academic achievement: a meta-analytic review of research. Review of Educational Research, 75(3), 417-453.

State Higher Education Executive Officers Association (SHEEO) (2024). State higher education finance: FY 2023. SHEEO. https://shef.sheeo.org/wp-content/uploads/2024/04/SHEEO_SHEF_FY23_Report.pdf

White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838. https://doi.org/10.2307/1912934