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Post-secondary education
Growing reliance on student loans and repayment difficulties have raised concerns of a student debt crisis in the United States. However, little is known about the effects of student borrowing on human capital and long-run financial well-being. We use variation induced by recent expansions in federal loan limits, together with administrative schooling, earnings, and credit records, to identify the effects of increased student borrowing on credit-constrained students’ educational attainment, earnings, debt, and loan repayment. Increased student loan availability raises student debt and improves degree completion, later-life earnings, and student loan repayment while having no effect on homeownership or other types of debt.
A growing body of evidence suggests that vocationally focused programs of study substantially improve high-school completion and longer-run economic success. However, the corresponding recommendations to expand vocational programs may have unintended, negative consequences for low-income, academically successful students (i.e., the “missing one offs”) who have the capacity and motivation to attend highly selective universities. This study contributes to our understanding of these issues by examining an innovative, college-preparatory program targeted to academically successful Chilean students attending vocational high schools serving lower-income communities. This program (Escuela Desarrollo de Talentos or EDT) provides academic and social-emotional supports aligned with admission to selective universities. We examine the educational effects of EDT participation using a fuzzy regression-discontinuity design based on its eligibility rules. We find that the EDT program did not increase the probability of graduating from high school but did increase performance in math courses. We also find corresponding evidence suggesting that EDT participation increased math performance on college entrance exams and shifted students away from further postsecondary vocational training and towards matriculation at elite universities.
COVID has led colleges to brace for potential enrollment declines in the Fall, which would devastate budgets and potentially decrease the likelihood a student ever earns a degree. We take an early look at California’s FAFSA applications up through mid-June, to anticipate how students may be responding to this crisis. We find that COVID did not affect most of California’s “traditional” high school graduates due to an early deadline for financial aid, which exists in a number of states. From early March to mid-June, FAFSA applications among freshmen declined 18%, relative to prior years. Although there were initial declines in applications among more experienced students, these quickly rebounded and are now 9% higher relative to prior years. The largest FAFSA increases occurred in counties that saw the most dramatic increases in Unemployment Insurance claims.
College completion rates declined from the 1970s to the 1990s. We document that this trend has reversed--since the 1990s, college completion rates have increased. We investigate the reasons for the increase in college graduation rates. Collectively, student characteristics, institutional resources, and institution attended do not explain much of the change. However, we show that grade inflation can explain much of the change in graduation rates. We show that GPA is a strong predictor of graduation rates and that GPAs have been rising since the 1990s. We also find that increases in college GPAs cannot be explained by student demographics, ability, and school factors. Further, we find that at a public liberal arts college, grades have increased over time conditional on final exam performance.
Enrollment in higher education has risen dramatically in Latin America, especially in Chile. Yet graduation and persistence rates remain low. One way to improve graduation and persistence is to use data and analytics to identify students at risk of dropout, target interventions, and evaluate interventions’ effectiveness at improving student success. We illustrate the potential of this approach using data from eight Chilean universities. Results show that data available at matriculation are only weakly predictive of persistence, while prediction improves dramatically once data on university grades become available. Some predictors of persistence are under policy control. Financial aid predicts higher persistence, and being denied a first-choice major predicts lower persistence. Student success programs are ineffective at some universities; they are more effective at others, but when effective they often fail to target the highest risk students. Universities should use data regularly and systematically to identify high-risk students, target them with interventions, and evaluate those interventions’ effectiveness.
This study used college dormitory room and social group assignment data to investigate the peer effect on the probability of college students switching their major fields of study. The results revealed strong evidence of peer effects on students’ decisions to switch majors. In particular, the number of a student’s peers who have the same major significantly reduces the student’s likelihood of switching majors; however, when a same-major peer switches majors, it significantly increases a student’s probability of switching majors. This study also found that peers’ majors affected students’ choice of destination majors. Students in the same peer group are more likely to choose the same destination majors, compared to non-peers. Finally, we found that in general peer effects at the dormitory room level, both in choice and persistence of major, were stronger than were peer effects at the social group level.
We provide the first estimated economic impacts of students’ access to an entire sector of public higher education in the U.S. Approximately half of Georgia high school graduates who enroll in college do so in the state’s public four-year sector, which requires minimum SAT scores for admission. Regression discontinuity estimates show enrollment in public four-year institutions boosts students’ household income around age 30 by 20 percent, and has even larger impacts for those from low income high schools. Access to this sector has little clear impact on student loan balances or other measures of financial health. For the marginal student, enrollment in such institutions has large private returns even in the short run and positive returns to state budgets in the long run.
Family and social networks are widely believed to influence important life decisions but identifying their causal effects is notoriously difficult. Using admissions thresholds that directly affect older but not younger siblings’ college options, we present evidence from the United States, Chile, Sweden and Croatia that older siblings’ college and major choices can significantly influence their younger siblings’ college and major choices. On the extensive margin, an older sibling’s enrollment in a better college increases a younger sibling’s probability of enrolling in college at all, especially for families with low predicted probabilities of enrollment. On the intensive margin, an older sibling’s choice of college or major increases the probability that a younger sibling applies to and enrolls in that same college or major. Spillovers in major choice are stronger when older siblings enroll and succeed in more selective and higher-earning majors. The observed spillovers are not well-explained by price, income, proximity or legacy effects, but are most consistent with older siblings transmitting otherwise unavailable information about the college experience and its potential returns. The importance of such personally salient information may partly explain persistent differences in college-going rates by geography, income, and other determinants of social networks.
Selective college admissions are fundamentally a question of tradeoffs: Given capacity, admitting one student means rejecting another. Research to date has generally estimated average effects of college selectivity, and has been unable to distinguish between the effects on students gaining access and on those losing access under alternative admissions policies. We use the introduction of the Top Ten Percent rule and administrative data from the State of Texas to estimate the effect of access to a selective college on student graduation and earnings outcomes. We estimate separate effects on two groups of students. The first--highly ranked students at schools which previously sent few students to the flagship university--gain access due to the policy; the second--students outside the top tier at traditional "feeder" high schools--tend to lose access. We find that students in the first group see increases in college enrollment and graduation with some evidence of positive earnings gains 7-9 years after college. In contrast, students in the second group attend less selective colleges but do not see declines in overall college enrollment, graduation, or earnings. The Top Ten Percent rule, introduced for equity reasons, thus also seems to have improved efficiency.
We examine through a field experiment whether outreach and support provided through an AI-enabled chatbot can reduce summer melt and improve first-year college enrollment at a four-year university and at a community college. At the four-year college, the chatbot increased overall success with navigating financial aid processes, such that student take up of educational loans increased by four percentage points. This financial aid effect was concentrated among would-be first-generation college goers, for whom loan acceptances increased by eight percentage points. In addition, the outreach increased first-generation students’ success with course registration and fall semester enrollment each by three percentage points. For the community college, where the randomized experiment could not be robustly implemented due to limited cell phone number information, we present a qualitative analysis of organizational readiness for chatbot implementation. Together, our findings suggest that proactive outreach to students is likely to be most successful when targeted to those who may be struggling (for example, in keeping up with required administrative tasks). Yet, such targeting requires university systems to have ready access to and ability to make use of their administrative data.