Research

Abstract: Over one-third of college students in the United States transfer between institutions, yet little is known about how transferring affect students' educational and labor market outcomes. Using administrative data from Texas and a regression discontinuity design, I study the effects of a student's transferring to a four-year college from either a two-year or four-year college. To do so, I use applications and admissions data to uncover the unpublished GPA cutoffs that each institution uses in its transfer student admissions and then use these cutoffs as an instrument for transfer. In contrast to past work focused on traditional students, I find negative earnings returns for academically marginal students who transfer from two-year colleges to four-year colleges or from less-resourced four-year colleges to flagship colleges. The mechanisms include transfer students' substituting out of high-paying majors into lower-paying majors, reduced employment and labor market experience, and potential loss of support networks.

Presented at: AEFP 2023, MEA 2023, SOLE 2023, APPAM 2023

Abstract: We study how colleges' ``sticker price'' and institutional financial aid change during and after tuition caps and freezes using a modified event study design. While tuition regulations lower sticker prices, colleges recoup losses by lowering financial aid or rapidly increasing tuition after regulations end. At four-year colleges, regulations lower sticker price by 6.3 percentage points while simultaneously reducing aid by nearly twice as much (11.3 percentage points). At two-year colleges, while regulations lower tuition by 9.3 percentage points, the effect disappears within three years of the end of the regulation. Changes in net tuition vary widely; focusing on four-year colleges, while some students receive discounts up to 5.9 percentage points, others pay 3.8 percentage points more than they would have without these regulations. Students who receive financial aid, enter college right after the regulation is lifted, or attend colleges that are more dependent on tuition benefit less.

Presented at: E-con of Ed Graduate Student Workshop 2020, AEFP 2021, AERA 2022 

Abstract: This article reviews the basic patterns of employment and school enrollment for new labor market entrants in the period leading up to the Great Recession and in the decade thereafter. We find a persistent shift into four-year colleges that began during the Great Recession. At the same time, fewer youth are neither working nor enrolled in school. We see little change in occupational training programs during our study period, in program or in participation rates; in particular, rates of training provided via federal workforce development programs remain low among workforce entrants. The research literature on these programs has advanced but without large effects on policy or practice.

Presented at: ANNALS “What Has Happened to the American Working Class Since the Great Recession?” Conference 2021

Abstract: Graduating from college into a recession is associated with earnings losses, but less is known about how these effects vary across colleges. Using restricted-use data from the National Survey of College Graduates, we study how college quality influences the effects of graduating into worse economic conditions in the context of the Great Recession. We find that earnings losses are concentrated among graduates from relatively high-quality colleges. Key mechanisms include substitution out of the labor force and into graduate school, decreased graduate degree completion, and differences in the economic stability of fields of study between graduates of high- and low-quality colleges.

Presented at: AEFP 2022, APPAM 2022, Census Bureau 2023, Federal Statistical Research Data Center Annual Research Conference 2023

Abstract: This paper contributes to the literature on the causal effect of college quality on student labor market outcomes by exploring mechanisms behind earnings impacts, with a focus on choice of major and occupation. Using data from the NLSY97 and a “selection on observed variables” identification strategy with a rich set of covariates, I find that students who attend high-quality colleges sort into higher-paying occupations. These large and statistically significant effects of college quality on predicted earnings of occupation can account for over half of the earnings return to college quality. On the contrary, predicted earnings by major are not found to be affected by college quality in any economically meaningful or statistically significant way. I apply the framework from Oster (2019) to probe my results for sensitivity, and find that they are robust to a variety of plausible assumptions about the nature of selection on unobserved variables. 

Presented at: AEFP 2020, APPAM 2020

Abstract: Many students attend colleges close to their homes. How important is the proximity of colleges in students’ enrollment choices? In this paper, I explore this question using administrative data on the universe of public high school students in Texas matched to all within-state college enrollment at public 2-year and 4-year colleges. I use an event study analysis around the openings of community colleges to estimate the causal effect of the availability of a 2-year college within 20 minutes driving time of students’ high schools. I find that local students do enroll in the new community colleges, but this enrollment response is primarily substitution away from other colleges rather than the effect of enrollments from new students who otherwise wouldn’t have enrolled in any college. I also find evidence that students who gain access to a more proximate community college have an increased likelihood of completing a 2-year associate’s degree with no difference in their 4-year bachelor’s degree completion rates. This has important policy implications for decisions on where to locate new colleges and which types of students they are most likely to serve. 

Presented at: Interdisciplinary Training Program in Educational Sciences Seminar 2022

Abstract: Empirical economics papers report standard errors that capture the uncertainty in their estimates associated with sampling variation but rarely systematically consider the non-sampling variation that results from researcher design choices. Such choices include measurement of key variables, functional forms of outcome equations, handling of outliers, and handling of missing values. Most papers consider but one or two choices in an ad hoc manner, framing them as one-off sensitivity analyses. In this project, we (1) review the literature on alternative methods for quantifying non-sampling variation, (2) develop a typology of sources of non-sampling variation, (3) develop a framework for quantifying non-sampling variation, and (4) apply the framework to an empirical application. The empirical exercise proceeds in the context of the literature that seeks to estimate the causal effect of college quality on educational and labor market outcomes.

Presented at: Higher Education Working Group 2021, Nordic Econometric Society Conference 2022, WHY Conference 2022, University of Maryland 2023