Joint with Todd Elder and Steven J. Haider. Published in Journal of Human Resources (2025)
We examine the evolution of this elasticity over the last four decades. We find robust evidence that the elasticity weakly increased between 2000 and 2020, representing a striking reversal from the sizable declines for single and married women between 1979 and 2000.
Published in Applied Economics Letters (2023)
Using data from Add Health and exploiting idiosyncratic variation in the share of female peers across grades within schools, I find positive but small effects of a higher share of female peers for male students.
Published in CES Working Paper Series (2025)
This paper proposes a new methodology for estimating the coverage rate of the Post-Secondary Employment Outcomes data product (PSEO) and assesses how representative PSEO is of the broader population of college graduates.
Joint with Riley Acton and Salem Rogers. Published in EdWorkingPaper and IZA (2023)
We study the effects of increased school spending caused by Wisconsin’s Sparsity Aid Program. The increased spending had little effect on standardized test scores, but modestly increased college enrollment and completion for students with a low likelihood of attending or completing college.
This paper uses survey data and a dynamic structural model to study how college students choose their credit hour enrollment, labor supply, and borrowing, paying particular attention to the role of wages, financial resources and beliefs.
This paper uses novel survey data on college students’ beliefs about the returns to schoolwork to explain variation in their reported schoolwork hours.
Joint with Emin Dinlersoz and Andrew Foote
This paper uses administrative data to document the business formation activities of postsecondary graduates.
Joint with Andrew Foote and Lawrence Warren
This paper measures the accuracy of survey responses on educational attainment in the American Community Survey and Current Population Survey using linked administrative data on degree attainment.
Joint with Lee Tucker and Lawrence Warren
This paper uses PSEO and LEHD data to estimate the effects of AI exposure on recent college graduates.
This paper proposes a framework for selecting the optimal CIP code aggregation level and provides estimates of errors from aggregating using PSEO microdata.