Research
Publications:
Nevertheless She Persisted? Gender Peer Effects in Doctoral STEM Programs (with Bruce Weinberg), Journal of Labor Economics, 2022, vol. 40, issue 2, pages 397-436
Previous version: NBER Working Paper No. 25028
Academic Analytics Research Center Webinar: Presentation Recording
Press Coverage: Inside Higher Ed; Science; Moneyish; Nature; Ladders; Physics World; Pacific Standard; Cleveland Plain Dealer
Semesters or Quarters? The Effect of the Academic Calendar on Postsecondary Student Outcomes (with Stefanie Fischer and Matthew Lang), American Economic Journal: Economic Policy, 2022, vol. 14, issue 1, pages 40-80
Previous version: IZA Discussion Papers No. 12429, Institute of Labor Economics (IZA)
Press Coverage: Research Highlights
Saved By the Morning Bell: School Start Time and Teen Car Accidents, Contemporary Economic Policy, 2018, vol. 26, issue 4, pages 591-606
Signaling in Higher Education: The Effect of Access to Elite Colleges on Choice of Major, Economic Inquiry, 2016, vol. 54, issue 3, pages 1383-1401
Obtaining Critical Values for Test of Markov Regime Switching (with Douglas Steigerwald), Stata Journal, 2014, vol. 14, issue 3, pages 481-498
Nevertheless She Persisted? Gender Peer Effects in Doctoral STEM Programs (with Bruce Weinberg), Journal of Labor Economics, 2022, vol. 40, issue 2, pages 397-436
Previous version: NBER Working Paper No. 25028
Academic Analytics Research Center Webinar: Presentation Recording
Press Coverage: Inside Higher Ed; Science; Moneyish; Nature; Ladders; Physics World; Pacific Standard; Cleveland Plain Dealer
Semesters or Quarters? The Effect of the Academic Calendar on Postsecondary Student Outcomes (with Stefanie Fischer and Matthew Lang), American Economic Journal: Economic Policy, 2022, vol. 14, issue 1, pages 40-80
Previous version: IZA Discussion Papers No. 12429, Institute of Labor Economics (IZA)
Press Coverage: Research Highlights
Saved By the Morning Bell: School Start Time and Teen Car Accidents, Contemporary Economic Policy, 2018, vol. 26, issue 4, pages 591-606
Signaling in Higher Education: The Effect of Access to Elite Colleges on Choice of Major, Economic Inquiry, 2016, vol. 54, issue 3, pages 1383-1401
Obtaining Critical Values for Test of Markov Regime Switching (with Douglas Steigerwald), Stata Journal, 2014, vol. 14, issue 3, pages 481-498
Book Chapters:
Peer Effects in Graduate Programmes (with Bruce Weinberg), “Women in Economics”, edited by Shelly Lundberg, CEPR Press, 2020, pages 65-71.
Peer Effects in Graduate Programmes (with Bruce Weinberg), “Women in Economics”, edited by Shelly Lundberg, CEPR Press, 2020, pages 65-71.
Working Papers:
"Driving, Dropouts, and Drive-Throughs: Mobility Restrictions and Teen Human Capital" (with Christopher Severen), under review
Previous versions: Federal Reserve Bank of Philadelphia Working Paper No. 22-22; EdWorkingPaper No. 23-719; IZA Discussion Paper Series No. 16183
We provide evidence that graduated driver licensing (GDL) laws, originally intended to improve public safety, impact both high school completion and teen employment. Many teens use automobiles to commute to both school and to employment. Because school and work decisions are interrelated, the effects of automobile-specific mobility restrictions are ex ante ambiguous. Combining variation in the timing of both GDL law adoption and changes in compulsory school laws into a triple-difference research design shows that restricting teen mobility significantly reduces high school dropout rates and teen employment. These findings are consistent with a model in which teens use automobiles to access educational distractions (employment or even risky behaviors). We develop a discrete choice model that reflects reduced access to school, work, and other activities, which reveals that limiting access to work alone cannot explain the reduction in high school dropout rates.
"More Often or Longer? The Effect of the Academic Schedule on Postsecondary Academic Outcomes" (with Tuan D. Nguyen), under review
One of the most common scheduling decisions in higher education is the determination of biweekly or triweekly classes. On the surface, these two formats are equivalent in terms of the number of minutes in a course (75 minutes twice a week or 50 minutes three times a week). However, the two structures may have different pros and cons for both students and faculty and it is ambiguous which course format should yield better student outcomes. We leverage more than a decade's worth of administrative transcript data from a large public university in the Midwest to examine the effects of the academic schedule on postsecondary student outcomes. Across a range of model specifications employing department, faculty, and student fixed effects, we find that when a student enrolls in a triweekly class, they earn lower grades, are less likely to take a subsequent course in that same field, and eventually experience a longer time-to-degree.
"Driving, Dropouts, and Drive-Throughs: Mobility Restrictions and Teen Human Capital" (with Christopher Severen), under review
Previous versions: Federal Reserve Bank of Philadelphia Working Paper No. 22-22; EdWorkingPaper No. 23-719; IZA Discussion Paper Series No. 16183
We provide evidence that graduated driver licensing (GDL) laws, originally intended to improve public safety, impact both high school completion and teen employment. Many teens use automobiles to commute to both school and to employment. Because school and work decisions are interrelated, the effects of automobile-specific mobility restrictions are ex ante ambiguous. Combining variation in the timing of both GDL law adoption and changes in compulsory school laws into a triple-difference research design shows that restricting teen mobility significantly reduces high school dropout rates and teen employment. These findings are consistent with a model in which teens use automobiles to access educational distractions (employment or even risky behaviors). We develop a discrete choice model that reflects reduced access to school, work, and other activities, which reveals that limiting access to work alone cannot explain the reduction in high school dropout rates.
"More Often or Longer? The Effect of the Academic Schedule on Postsecondary Academic Outcomes" (with Tuan D. Nguyen), under review
One of the most common scheduling decisions in higher education is the determination of biweekly or triweekly classes. On the surface, these two formats are equivalent in terms of the number of minutes in a course (75 minutes twice a week or 50 minutes three times a week). However, the two structures may have different pros and cons for both students and faculty and it is ambiguous which course format should yield better student outcomes. We leverage more than a decade's worth of administrative transcript data from a large public university in the Midwest to examine the effects of the academic schedule on postsecondary student outcomes. Across a range of model specifications employing department, faculty, and student fixed effects, we find that when a student enrolls in a triweekly class, they earn lower grades, are less likely to take a subsequent course in that same field, and eventually experience a longer time-to-degree.
Work in progress:
"Best and Brightest? The Selectivity of Foreign-Born Ph.D. Recipients in the U.S." (with Joe Staudt and Bruce Weinberg)
This paper examines the selectivity of foreign-born, U.S.-trained Ph.D. recipients, relative to their U.S.-born and trained counterparts, in terms of both their training/laboratory environments in graduate school and their post-graduation labor market outcomes. We find strong evidence of positive selection, both pre- and post-graduation, and across the observed choices that Ph.D. recipients make (e.g. field or sector of employment). Moreover, we find that the selectivity of the foreign-born is largest for Ph.D. recipients who are more firmly attached to the U.S. labor market. Finally, we show that, though this positive selection results in the U.S. attracting the "best and brightest" foreign-born Ph.D. recipients, they tend to study high-demand fields, suggesting that there is minimal reason for concern over "crowding out" of U.S.-born doctorates.
"The Impact of University Peers on Student Outcomes" (with Seong Jeong, Aiday Sikhova, and Bruce Weinberg)
The impact of peers’ ability on students’ outcomes has long been studied. However, little is known about whether and how other characteristics of peers – such as race, gender, socioeconomic and immigration status – affect students’ outcomes. This is especially important considering recent court battles across the country over the impact of affirmative action and immigration policies on students. We identify the effects of peer characteristics on on grades, future course-taking, and major choice using quasi-random variation in the composition of introductory classrooms over time. These introductory courses are often considered an initial gateway for declaring a major in STEM. Focusing on students during their first semester in college minimizes any concern of selection bias as new students typically have little information about instructors and/or classmates before enrolling in a class. We hope to extend this analysis to also investigate the impacts of peers on undergraduate completion rates and labor market outcomes.
“The Effect of Undergraduate Course Offerings on the Gender Gap in Economics Majors”
I investigate how diversity in the selection of courses offered in a department affects the share of women and minority students choosing to major in economics. It is well known that female PhD students in economics disproportionately declare Labor and Health as their fields of specialization. Can offering more classes in these topics at the undergraduate level help to attract more women students to the major? I use faculty turnover in medium-to-small economics departments as a quasi-exogenous shock to course offerings in order to identify the effect on student major choice.
"The Effects of Academic Calendar on Faculty Outcomes" (with Stefanie Fischer, Francesca Truffa, and Ashley Wong)
We explore whether university-level policy changes from a quarter system comprising three 10-week terms to a semester system comprising two 15-week terms has an impact on the teaching schedules, research productivity, and/or promotions of university faculty. Specifically, we investigate whether faculty respond to this type of calendar change through adjusting their teaching schedules or the volume or timing of publications, grant-writing, or patenting. There are many potential costs and benefits associated with a semester calendar, both to students and the faculty/administration, that could affect faculty productivity. For example, semesters break the academic year into longer segments, which provides less scheduling flexibility for faculty. This difference may translate into less time spent devoted to research output, or conversely might increase incentives for teaching buyouts and thus increase grant-writing efforts.
Resting papers:
"Estimation and Inference for Probit Models with Clustered Data"
While a substantial literature addresses the difficulties in conducting proper inference with clustered data in linear models, very little is known about the implications of clustered data in nonlinear models. I study the challenges associated with clustered data for the probit model, specifically. In this model, heteroskedasticity of the error term caused by clustering can impact the identification and estimation of model coefficients and marginal effects, in addition to the usual problems with inference. I outline these issues for the standard case where the number of clusters is large and for the much less studied case where there are very few clusters but the number of individuals within a cluster is large. This case is particularly interesting because, while an application of a two-step estimator to estimate the regression coefficients is straightforward, a method for conducting inference on the marginal effects (typically the quantity of interest) is unclear.
"Best and Brightest? The Selectivity of Foreign-Born Ph.D. Recipients in the U.S." (with Joe Staudt and Bruce Weinberg)
This paper examines the selectivity of foreign-born, U.S.-trained Ph.D. recipients, relative to their U.S.-born and trained counterparts, in terms of both their training/laboratory environments in graduate school and their post-graduation labor market outcomes. We find strong evidence of positive selection, both pre- and post-graduation, and across the observed choices that Ph.D. recipients make (e.g. field or sector of employment). Moreover, we find that the selectivity of the foreign-born is largest for Ph.D. recipients who are more firmly attached to the U.S. labor market. Finally, we show that, though this positive selection results in the U.S. attracting the "best and brightest" foreign-born Ph.D. recipients, they tend to study high-demand fields, suggesting that there is minimal reason for concern over "crowding out" of U.S.-born doctorates.
"The Impact of University Peers on Student Outcomes" (with Seong Jeong, Aiday Sikhova, and Bruce Weinberg)
The impact of peers’ ability on students’ outcomes has long been studied. However, little is known about whether and how other characteristics of peers – such as race, gender, socioeconomic and immigration status – affect students’ outcomes. This is especially important considering recent court battles across the country over the impact of affirmative action and immigration policies on students. We identify the effects of peer characteristics on on grades, future course-taking, and major choice using quasi-random variation in the composition of introductory classrooms over time. These introductory courses are often considered an initial gateway for declaring a major in STEM. Focusing on students during their first semester in college minimizes any concern of selection bias as new students typically have little information about instructors and/or classmates before enrolling in a class. We hope to extend this analysis to also investigate the impacts of peers on undergraduate completion rates and labor market outcomes.
“The Effect of Undergraduate Course Offerings on the Gender Gap in Economics Majors”
I investigate how diversity in the selection of courses offered in a department affects the share of women and minority students choosing to major in economics. It is well known that female PhD students in economics disproportionately declare Labor and Health as their fields of specialization. Can offering more classes in these topics at the undergraduate level help to attract more women students to the major? I use faculty turnover in medium-to-small economics departments as a quasi-exogenous shock to course offerings in order to identify the effect on student major choice.
"The Effects of Academic Calendar on Faculty Outcomes" (with Stefanie Fischer, Francesca Truffa, and Ashley Wong)
We explore whether university-level policy changes from a quarter system comprising three 10-week terms to a semester system comprising two 15-week terms has an impact on the teaching schedules, research productivity, and/or promotions of university faculty. Specifically, we investigate whether faculty respond to this type of calendar change through adjusting their teaching schedules or the volume or timing of publications, grant-writing, or patenting. There are many potential costs and benefits associated with a semester calendar, both to students and the faculty/administration, that could affect faculty productivity. For example, semesters break the academic year into longer segments, which provides less scheduling flexibility for faculty. This difference may translate into less time spent devoted to research output, or conversely might increase incentives for teaching buyouts and thus increase grant-writing efforts.
Resting papers:
"Estimation and Inference for Probit Models with Clustered Data"
While a substantial literature addresses the difficulties in conducting proper inference with clustered data in linear models, very little is known about the implications of clustered data in nonlinear models. I study the challenges associated with clustered data for the probit model, specifically. In this model, heteroskedasticity of the error term caused by clustering can impact the identification and estimation of model coefficients and marginal effects, in addition to the usual problems with inference. I outline these issues for the standard case where the number of clusters is large and for the much less studied case where there are very few clusters but the number of individuals within a cluster is large. This case is particularly interesting because, while an application of a two-step estimator to estimate the regression coefficients is straightforward, a method for conducting inference on the marginal effects (typically the quantity of interest) is unclear.
