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Post-secondary education
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.
Revealed preferences for equal college access may be due to beliefs that equal access increases societal income or income equality. To isolate preferences for those goods, we implement an online discrete choice experiment using social statistics generated from true variation among commuting zones. We find that, ceteris paribus, the average income that individuals are willing to sacrifice is (i) $4,984 dollars to increase higher education (HE) enrollment by 1 standard deviation (14%); (ii) $1,168 dollars to decrease rich/poor gaps in HE enrollment by 1 standard deviation (8%); (iii) $2,900 to decrease the 90/10 income inequality ratio by 1 standard deviation (1.66). In addition, we find that political affiliation is an important moderator of preferences for equality. While both Democrats and Republicans are willing to trade over $4,000 dollars to increase HE enrollment by 1 standard deviation, Democrats are willing to sacrifice nearly three times more income to decrease either rich/poor gaps in HE enrollment or the 90/10 income inequality ratio by 1 standard deviation.
We study within-family spillovers in college enrollment to show college-going behavior is transmissible between peers. Because siblings’ test scores are weakly correlated, we exploit college-specific admissions thresholds that directly affect older but not younger siblings’ college options. Older siblings’ admissibility substantially increases their own four-year college enrollment rate and quality of college attended. Their improved college choices in turn raise younger siblings’ college enrollment rate and quality of college chosen, particularly for families with low predicted probabilities of college enrollment. Some younger siblings follow their older sibling to the same campus but many upgrade by choosing other colleges. 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 income, geography and other characteristics that define a community.
We examine the effects of a comprehensive college transition program (CCTP) on four psychosocial outcomes associated with postsecondary success: sense of belonging, mattering, and academic and social self-efficacy. The CCTP operates on three four-year campuses and includes a range of supports, including shared academic courses, peer mentoring, and residential or common community spaces. We leverage the randomization of Angrist et al. (2014), but restrict our comparison to scholarship recipients with and without CCTP exposure. To account for differential attrition from the experimental sample, we rely on a “selection on observables” assumption for our primary analysis. Results suggest that the program significantly and substantially increased students’ sense of belonging and mattering, but had no effect on academic or social self-efficacy.
This paper provides the first causal evidence on the impact of college advisor quality on student outcomes. To do so, we exploit a unique setting where students are randomly assigned to faculty advisors during their first year of college. We find that higher advisor value-added (VA) substantially improves freshman year GPA, time to complete freshman year and four-year graduation rates. Additionally, higher advisor VA increases high-ability students’ likelihood of enrolling and graduating with a STEM degree. Our results indicate that allocating resources towards improving the quality of academic advising may play a key role in promoting college success.