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Jonathan Smith
We investigate whether and how Achieve Atlanta’s college scholarship and associated services impact college enrollment, persistence, and graduation among Atlanta Public School graduates experiencing low household income. Qualifying for the scholarship of up to $5,000/year does not meaningfully change college enrollment among those near the high school GPA eligibility thresholds. However, scholarship receipt does have large and statistically significant effects on early college persistence (i.e., 14%) that continue through BA degree completion within four years (22%). We discuss how the criteria of place-based programs that support economically disadvantaged students may influence results for different types of students.
For decades, pundits, politicians, college administrators, and academics have lamented the dismal rates of civic engagement among students who enroll in courses and eventually major in science, technology, engineering, and mathematics (i.e., STEM) fields. However, the research supporting this conclusion has faced distinct challenges in terms of data quality. Does STEM actually decrease the odds that young people will be actively involved in democracy? This paper assesses the relationship between studying STEM and voting. To do so, we create a dataset of over 23 million students in the U.S. matched to national validated voting records. The novel dataset is the largest known individual-level dataset in the U.S. connecting high school and college students to voting outcomes. It also contains a rich set of demographic and academic variables, to account for many of the common issues related to students' selection into STEM coursework. We consider two measures of STEM participation ---Advanced Placement (AP) Exam taking in high school and college major. Using both measures, we find that, unconditionally, STEM students are slightly more likely to vote than their non-STEM peers. After including the rich set of controls, the sign reverses and STEM students are slightly less likely to vote than their non-STEM peers. However, these estimated relationships between STEM and voting are small in magnitude---about the same effect size as a single get-out-the-vote mailer---and we can rule out even very modest causal effects of marginally more STEM coursework on voting for the typical STEM student. We cannot rule out modest effects for a few subfields. Our analyses demonstrate that, on average, marginally more STEM coursework in high school and college does not contribute to the dismally low participation rates among young people in the U.S.
Early research on the returns to higher education treated the postsecondary system as a monolith. In reality, postsecondary education in the United States and around the world is highly differentiated, with a variety of options that differ by credential (associates degree, bachelor’s degree, diploma, certificate, graduate degree), the control of the institution (public, private not-for-profit, private for-profit), the quality/resources of the institution, field of study, and exposure to remedial education. In this Chapter, we review the literature on the returns to these different types of higher education investments, which has received increasing attention in recent decades. We first provide an overview of the structure of higher education in the U.S. and around the world, followed by a model that helps clarify and articulate the assumptions employed by different estimators used in the literature. We then discuss the research on the return to institution type, focusing on the return to two-year, four-year, and for-profit institutions as well as the return to college quality within and across these institution types. We also present the research on the return to different educational programs, including vocational credentials, remedial education, field of study, and graduate school. The wide variation in the returns to different postsecondary investments that we document leads to the question of how students from different backgrounds sort into these different institutions and programs. We discuss the emerging research showing that lower-SES students, especially in the U.S., are more likely to sort into colleges and programs with lower returns as well as results from recent U.S.-based interventions and policies designed to support success among students from disadvantaged backgrounds. The Chapter concludes with some broad directions for future research.
Millions of high school students who take an Advanced Placement (AP) course in one of over 30 subjects can earn college credit by performing well on the corresponding AP exam. Using data from four metro-Atlanta public school districts, we find that 15 percent of students’ AP courses do not result in an AP exam. We predict that up to 32 percent of the AP courses that do not result in an AP exam would result in a score of 3 or higher, which generally commands college credit at colleges and universities across the United States. Next, we examine disparities in AP exam-taking rates by demographics and course taking patterns. Most immediately policy relevant, we find evidence consistent with the positive impact of school district exam subsidies on AP exam-taking rates. In fact, students on free and reduced-price lunch (FRL) in the districts that provide a higher subsidy to FRL students than non-FRL students are more likely to take an AP exam than their non-FRL counterparts, after controlling for demographic and academic covariates.
Using administrative data from Georgia, we provide the first study of the full set of college entrance exam-taking strategies, including who takes the ACT and the SAT (or both), when they take the exams, and how many times they take each exam. We have several main findings. First, one-third of exam takers take both the ACT and SAT. Second, we see pronounced disparities in several measures of exam-taking strategy by free- and reduced-price lunch status, even after including a rich set of controls, but not by underrepresented minority status. Third, we find evidence that taking more total exams leads to higher admissions-relevant test scores and a higher likelihood of enrolling in colleges with relatively high graduation rates and earnings. However, these relationships with test scores and college enrollment are smaller for those who take both the ACT and SAT, as opposed to retaking the same exam multiple times.
How do college non-completers list schooling on their resumes? The negative signal of not completing might outweigh the positive signal of attending but not persisting. If so, job-seekers might hide non-completed schooling on their resumes. To test this we match resumes from an online jobs board to administrative educational records. We find that fully one in three job-seekers who attended college but did not earn a degree omit their only post-secondary schooling from their resumes. We further show that these are not casual omissions but are strategic decisions systematically related to schooling characteristics, such as selectivity and years of enrollment. We also find evidence of lying, and show which degrees listed on resumes are most likely untrue. Lastly, we discuss implications. We show not only that this implies a commonly held assumption, that employers perfectly observe schooling, does not hold, but also that we can learn about which college experiences students believe are most valued by employers.
Younger siblings take more advanced high school course end of year exams when their older siblings perform better in those same exams. Using a regression discontinuity and data from millions of siblings who take Advanced Placement (AP) exams, we show that younger siblings with older siblings who marginally “pass” an AP exam are more likely to take at least one AP exam, increase the total number of AP exams, and are more likely to take the same exam as their sibling. The largest impacts are found among sisters, but we do not see differential effects in coursework where females are underrepresented.
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.