Spillover Effects of Financial Aid for Education
Does Post-9/11 GI Bill Reduce Veteran SNAP Participation
Bibliographic Data
| ID | 22158118 |
|---|---|
| Authors | Projesh Ghosh (0000-0002-5182-7492, Lewin Group (United States), corresponding author), Sarmistha Pal (0000-0003-3813-2108), Sebastian Negrusa (0000-0001-7750-2189, Lewin Group (United States)) |
| Year | 2021 |
| Volume | 6 |
| Issue | 3 |
| Pages | 110-122 |
| Publication date | 2021-02-08 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Veterans Studies (JOURNAL) |
| Journal identifiers | ISSN: 2470-4768 • E-ISSN: 2470-4768 |
| Publisher | Virginia Tech Libraries (PUBLISHER) |
| DOI | 10.21061/jvs.v6i3.203 |
| OpenAlex | W3131067265 |
| Language | EN |
| References cited | 16 |
Many veterans rely on the Supplemental Nutrition Assistance Program (SNAP). We study the change in the veterans’ reliance on SNAP in response to the GI Bill, the veterans’ financial aid for higher education. Using the unanticipated increase in educational benefits due to the Post-9/11 GI Bill and employing a difference-in-differences approach, we estimate that the benefit increase lowered veteran SNAP participation by about 28%, the effect being larger among new veterans. These findings reflect changes in the veterans’ choices that are attributable to wealth effects, SNAP eligibility criteria, and human capital accumulation. SNAP eligibility typically expires when the veteran attends college, and a larger educational benefit increases the veterans’ probability of college attendance. Furthermore, a college degree increases future earnings, which reduces the veterans’ SNAP reliance in the longer run. Quantifying these relationships provides insights into how financial aid for education in general improves veterans’ economic well-being and may help break some veterans’ dependence on SNAP and similar welfare programs
Attendance · Demographic economics · Earnings · Economic growth · Economics · Human capital · Snap · Spillover effect · Supplemental Nutrition Assistance Program · Veterans Affairs · Welfare · Financial Literacy, Pension, Retirement Analysis · Gender, Labor, and Family Dynamics · Medicine · Poverty, Education, and Child Welfare · Psychology · Finance
Computing Interaction Effects and Standard Errors in Logit and Probit Models
Multivariate Probit Regression using Simulated Maximum Likelihood
How Much Does the Supplemental Nutrition Assistance Program Reduce Food Insecurity?
Interaction terms in logit and probit models
How Much Should We Trust Differences-In-Differences Estimates?
Supplemental Nutrition Assistance Program (SNAP) Use Among Active-Duty Military Personnel, Veterans, and Reservists
| Highly cited | No |
|---|