How Has the Post-9/11 GI Bill Affected Veteran Students’ College Loans? A Longitudinal Analysis of NPSAS Using Propensity Score Weighting

References

• Armona, L., Chakrabarti, R., & Lovenheim, M. F. (2022). Student debt and default: The role of for-profit colleges. Journal of Financial Economics, 144(1), 67–92. https://doi.org/10.1016/j.jfineco.2021.12.008
   Web of Science ®Google Scholar
• Baird, M., Kofoed, M., Miller, T., & Wenger, J. (May 31, 2018). For-profit higher education responsiveness to price shocks: An investigation of changes in Post 9–11 GI Bill allowed maximum tuitions. SSRN Electronic Journal. http://dx.doi.org/10.2139/ssrn.3174763
   Google Scholar
• Barr, A. (2015). From the battlefield to the schoolyard: The short-term impact of the Post-9/11 GI Bill. Journal of Human Resources, 50(3), 580–613. https://doi.org/10.3368/jhr.50.3.580
   Web of Science ®Google Scholar
• Barr, A. (2019). Fighting for education: Financial aid and degree attainment. Journal of Labor Economics, 37(2), 509–544. https://doi.org/10.1086/700191
   Web of Science ®Google Scholar
• Barr, A., Kawano, L., Sacerdote, B., Skimmyhorn, W., & Stevens, M. (2021). You can’t handle the truth: The effects of the post-9/11 Gi Bill on higher education and earnings (No. w29024). National Bureau of Economic Research.
   Google Scholar
• Baum, S., Ma, J., Pender, M., & Libassi, C. J. (2019). Trends in Student Aid 2019. College Board. https://research.collegeboard.org/pdf/trends-student-aid-2019-full-report.pdf
   Google Scholar
• Boatman, A., Evans, B. J., & Soliz, A. (2017). Understanding loan aversion in education: Evidence from high school seniors, community college students, and adults. Aera Open, 3(1), 1–16. https://doi.org/10.1177/2332858416683649
   Web of Science ®Google Scholar
• Boyington, B., & Kerr, E. (2021). 20 years of tuition growth at national universities. U.S. News & world report. https://www.usnews.com/education/best-colleges/paying-for-college/articles/2017-09-20/see-20-years-of-tuition-growth-at-national-universities
   Google Scholar
• Cellini, S. R., & Chaudhary, L. (2014). The labor market returns to a for-profit college education. Economics of Education Review, 43, 125–140. https://doi.org/10.1016/j.econedurev.2014.10.001
   Web of Science ®Google Scholar
• Chen, R., & Wiederspan, M. (2014). Understanding the determinants of debt burden among college graduates. The Journal of Higher Education, 85(4), 565–598. https://doi.org/10.1353/jhe.2014.0020
   Web of Science ®Google Scholar
• Denning, J. T., & Jones, T. R. (2019). Maxed out? The effect of larger student loan limits on borrowing and education outcomes. IZA Working Papers, 12239.
   Google Scholar
• Denning, J. T., Marx, B. M., & Turner, L. J. (2019). ProPelled: The effects of grants on graduation, earnings, and welfare. American Economic Journal: Applied Economics, 11(3), 193–224. https://doi.org/10.1257/app.20180100
   Web of Science ®Google Scholar
• Dortch, C. (2021). The Post-9/11 GI Bill: A primer. Congressional Research Service, R42755. https://crsreports.congress.gov
   Google Scholar
• Erwin, C., & Binder, M. (2020). Does broad-based merit aid improve college completion? Evidence from New Mexico’s lottery scholarship. Education Finance and Policy, 15(1), 164–190. https://doi.org/10.1162/edfp_a_00270
   Web of Science ®Google Scholar
• Evans, B. J., & Nguyen, T. D. (2019). Monetary substitution of loans, earnings, and need-based aid in postsecondary education: The impact of pell grant eligibility. Economics of Education Review, 70, 1–19. https://doi.org/10.1016/j.econedurev.2019.02.004
   Web of Science ®Google Scholar
• Federal Reserve Bank of New York. (2022). Quarterly report on household debt and credit, 2022: Q1. https://www.newyorkfed.org/medialibrary/interactives/householdcredit/data/pdf/hhdc_2022q1.pdf
   Google Scholar
• Guo, S., & Fraser, M. W. (2014). Propensity score analysis: Statistical methods and applications (Vol. 11). Sage.
   Google Scholar
• Houle, J. N. (2014). Disparities in debt: Parents’ socioeconomic resources and young adult student loan debt. Sociology of Education, 87(1), 53–69. https://doi.org/10.1177/0038040713512213
   Web of Science ®Google Scholar
• James, O. R. (2011). Predatory ed: The conflict between public good and for-profit higher education. JC & UL, 38, 45. https://heinonline.org/HOL/P?h=hein.journals/jcolunly38&i=57
   Google Scholar
• Kofoed, M. S. (2020). Where have all the GI Bill dollars gone?: Veteran usage and expenditure of the post 9/11 GI Bill. Brookings. https://www.brookings.edu/wp-content/uploads/2020/10/ES-10.13.20-Kofoed-2.pdf
   Google Scholar
• Lee, V., & Looney, A. (2019). Understanding the 90/10 rule: How reliant are public, private, and for-profit institutions on federal aid? The Brookings Institution.
   Google Scholar
• Liu, V. Y. T., & Belfield, C. (2020). The labor market returns to for-profit higher education: Evidence for transfer students. Community College Review, 48(2), 133–155. https://doi.org/10.1177/0091552119886659
   Web of Science ®Google Scholar
• Long, B. T. (2004). How do financial aid policies affect colleges? The institutional impact of the Georgia HOPE scholarship. Journal of Human Resources, 39(4), 1045–1066. https://doi.org/10.2307/3559038
   Web of Science ®Google Scholar
• Looney, A., & Yannelis, C. (2019). How useful are default rates? Borrowers with large balances and student loan repayment. Economics of Education Review, 71, 135–145. https://doi.org/10.1016/j.econedurev.2018.10.004
   Web of Science ®Google Scholar
• Ma, J., Baum, S., Pender, M., & Libassi, C. J. (2018). Trends in college pricing. The College Board.
   Google Scholar
• Marx, B. M., & Turner, L. J. (2018). Borrowing trouble? Human capital investment with opt-in costs and implications for the effectiveness of grant aid. American Economic Journal: Applied Economics, 10(2), 163–201. https://doi.org/10.1257/app.20160127
   Web of Science ®Google Scholar
• McGuire, M. A. (2012). Subprime education - for-profit colleges and the problem with title IV federal student aid. Duke Law Journal, 62(119), 119–160. https://heinonline.org/HOL/P?h=hein.journals/duklr62&i=123
   Google Scholar
• Page, L. C., Kehoe, S. S., Castleman, B. L., & Sahadewo, G. A. (2019). More than dollars for scholars: The impact of the dell scholars program on college access, persistence and degree attainment. Journal of Human Resources, 54(3), 683–725. https://www.muse.jhu.edu/article/729943
   Web of Science ®Google Scholar
• Park, R. S. E., & Scott-Clayton, J. (2018). The impact of pell grant eligibility on community college students’ financial aid packages, labor supply, and academic outcomes. Educational Evaluation and Policy Analysis, 40(4), 557–585. https://doi.org/10.3102/0162373718783868
   Web of Science ®Google Scholar
• Price, D. (2004). Educational debt burden amount student borrowers: An analysis of the baccalaureate & beyond panel, 1997 follow-up. Research in Higher Education, 45(7), 701–737. https://doi.org/10.1023/B:RIHE.0000044228.54798.4c
   Web of Science ®Google Scholar
• Riegel, D. J. (2013). Closing the 90/10 Loophole in the Highland Education Act: How to Stop Exploitation of Veterans, Protect American Taxpayers, and Restore Market Incentives to the For-Profit College Industry. The George Washington Law Review, 81(1), 259–291. https://heinonline.org/HOL/P?h=hein.journals/gwlr81&i=273
   Web of Science ®Google Scholar
• Shrider, E. A., Kollar, M., Chen, F., & Semega, J. (2021) Income and poverty in the United States: 2020. U.S. Government Publishing Office. https://www.census.gov/content/dam/Census/library/publications/2021/demo/p60-273.pdf
   Google Scholar
• Snyder, T. D., De Brey, C., & Dillow, S. A. (2018). Digest of education statistics 2016 (NCES 2017–094). National Center for Education Statistics.
   Google Scholar
• St. Clair, T., & Cook, T. D. (2015). Difference-in-differences methods in public finance. National Tax Journal, 68(2), 319–338. https://doi.org/10.17310/ntj.2015.2.04
   Web of Science ®Google Scholar
• Stuart, E. A., Huskamp, H. A., Duckworth, K., Simmons, J., Song, Z., Chernew, M., & Barry, C. L. (2014). Using propensity scores in difference-in-differences models to estimate the effects of a policy change. Health Services & Outcomes Research Methodology, 14(4), 166–182. https://doi.org/10.1007/s10742-014-0123-z
   PubMedGoogle Scholar
• U.S. Department of Veterans Affairs. (2009). Veterans benefits administration annual benefits report fiscal year 2008. http://benefits.va.gov/
   Google Scholar
• U.S. Department of Veterans Affairs. (2017). Veterans benefits administration annual benefits report fiscal year 2016. http://benefits.va.gov/
   Google Scholar
• U.S. Department of Veterans Affairs. (2018). Veterans benefits administration annual benefits report fiscal year 2017. http://benefits.va.gov/
   Google Scholar
• Veterans Legal Clinic. (2016). Underserved: How the VA wrongfully excludes veterans with bad paper. National Veterans Legal Services Program.
   Google Scholar
• Zhang, L. (2018). Veterans going to college: Evaluating the impact of the Post-9/11 GI Bill on college enrollment. Educational Evaluation and Policy Analysis, 40(1), 82–102. https://doi.org/10.3102/0162373717724002
   Web of Science ®Google Scholar
• Zhang, L. (2022). How did the Post-9/11 GI Bill affect veteran students’ undergraduate college choices?: An application of propensity scores in difference-in-differences models. Harvard Educational Review, 92(1), 1–31. https://doi.org/10.17763/1943-5045-92.1.1
   Web of Science ®Google Scholar