Fighting for Education: Financial Aid and Non-traditional Students
Barr, Andrew, Economics - Graduate School of Arts and Sciences, University of Virginia
Turner, Sarah, Department of Economics, University of Virginia
Older students now account for roughly half of college enrollees, yet little attention is given to the factors that influence these individuals' decisions to enroll in college or complete a degree. I explore how various forms of government aid affect post-secondary decisions. In particular, I estimate the effect of financial aid and unemployment insurance generosity and program parameters on individuals' decisions to enroll and persist in college. Each year, the federal government alone spends tens of billions of dollars on financial aid, yet little is known about how this aid affects older students. Unemployment benefits may provide a similar subsidy to the enrollment of displaced workers, particularly when these individuals are able to maintain benefit receipt while enrolled in college. Both programs reduce the cost of education and have the potential to ease credit constraints that may inhibit human capital investment. I focus on exploring the effects of these programs on two groups of non-traditional students: military veterans and displaced workers.
In the first chapter of my dissertation, coauthored with Sarah Turner and forthcoming in the Journal of Public Economics, I focus on the college enrollment of displaced workers. We examine how changing state labor market conditions and state-specific variation in Unemployment Insurance (UI) interact to affect enrollment outcomes during the Great Recession. We identify a substantial role of the UI program in affecting post-secondary enrollment choices. We provide some of the first evidence that the duration of UI affects a displaced individual’s propensity to enroll, and suggestive evidence that these effects are larger in states with more inclusive approved training laws. These findings identify a substantial overlap between UI policy and post-secondary enrollment decisions, indicating the potential importance of UI in not only providing income but also facilitating investments in skills.
In the second chapter of my dissertation, I explore the hypothesis that many academically prepared individuals enter the military as a way to overcome credit constraints that prevent immediate enrollment in college. I develop a model of human capital investment that generates an empirical prediction to test for the presence of credit constraints among individuals considering military enlistment. I explore this question by examining the enlistment response of individuals to financial aid shocks. I find that the introduction of a merit-aid program decreases the probability that a male enlists in the military by .6 percentage points (a six percent reduction), and that these effects are concentrated among applicants that are more likely to qualify for merit scholarships. These effects are located mainly in low-income areas, supporting the argument that the effects on enlistment are a result of easing financial constraints. These findings potentially rationalize the relatively large number of high-achieving, but frequently low-income, individuals who enter the military for only a few years before separating and enrolling in college. The results also contribute to a broader literature focused on whether credit constraints play an important role in the human capital investment decision.
In the third chapter in my dissertation, I leverage large changes in financial aid generated by the Post-9/11 GI Bill to provide the first rigorous evidence of the effect of aid on the degree attainment of non-traditional students as well as the first evaluation of the longer run effects of the Post-9/11 GI Bill. One of the primary roadblocks to research in this area has been the lack of data that have sufficient numbers of veterans to track enrollment and degree attainment. I have created a new panel combining rich data on the choices of military service members from the Defense Manpower Data Center with postsecondary data from the National Student Clearinghouse (NSC). This dataset contains a large amount of information on the choices of over four million soldiers between 1998 and 2014 and will be a fruitful source for future research. Unique among the GI bills and other federal financial aid programs, the Post-9/11 GI Bill provides different benefit levels depending on both the state and ZIP code of enrollment. Individuals in some areas received almost no change in benefit levels, while those in others received tens of thousands of dollars in additional maximum benefit levels per year. Using multiple quasi-experimental strategies, I find that the higher level of financial aid provided by the Post-9/11 GI Bill increases the likelihood that a veteran obtains a degree within six years of separation by six percentage points, a 30 percent increase. This translates to an increase in degree attainment of between .5 and 1 percentage point for each 1,000 of additional financial aid. I use school specific variation in the size of the benefit increase to demonstrate that the persistence of infra-marginal students contributed to this effect. Finally, I show that a large fraction of veterans did not switch to the new GI Bill when it became available, leaving thousands of dollars in additional benefits on the table. This result bolsters concerns about informational complexity associated with accessing government programs, and motivates one element of an ongoing project that will randomly assign different information treatments to thousands of separating soldiers in the armed forces (with Kelli Bird, Ben Castleman, and Bill Skimmyhorn).
Together, these essays add to the limited evidence on the financial factors that affect the college enrollment and degree attainment of older non-traditional students. Future work will examine (1) whether the additional education gained by these non-traditional students translates into improved labor market or other outcomes, and (2) the extent to which personalized information can help individuals make optimal choices.
PHD (Doctor of Philosophy)
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