Experience

Assistant Professor of Economics

Kenyon College 2023 - Present

Postdoctoral Researcher

NBER 2020 – 2023

Special Sworn Status Researcher

U.S. Census Bureau 2016 - Present

Publications

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Task Mismatch and Salary Penalties: Evidence from the Biomedical PhD Labor Market with Gerald R. Marschke; (Latest Version); Accepted @ Journal of Labor Economics; Based on NBER Working Paper No. 30919 We employ a task-based framework to study the impact of postdoctoral training on the earnings of US-trained biomedical PhDs. Using longitudinal person-level data on both job tasks and salary, we find that a positive postdoc salary premium emerges when the difference between the tasks performed during training and future employment is low and a negative premium emerges when task mismatch is high. Early career biomedical doctorates working in industry perform a greater variety of tasks than those employed as postdoctoral researchers, leading to differences in task-specific human capital that explain the persistent negative returns to postdoctoral training in industry.

Working Papers

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STEM Employment Resiliency During Recessions: Evidence from the COVID-19 Pandemic with James C. Davis, Gerald R. Marschke, and Andrew J. Wang; (Latest Version); R&R @ Research Policy; Based on NBER Working Paper No. 29568 STEM occupational employment suffered smaller peak-to-trough percentage declines than non-STEM employment during both the Great Recession and COVID-19 recession, suggesting a relative resiliency of STEM employment during recessions in the digital age. We exploit the sudden peak-to-trough declines in STEM and non-STEM employment during the COVID-19 recession to measure STEM recession-resiliency during the pandemic, decomposing our difference-in-differences estimate into parts explained by various sources including differences in demographics, educational attainment, job tasks, remote work capability, industry, and STEM knowledge importance on the job. We find that STEM knowledge importance on the job explains the greatest share of STEM employment resiliency, and that workers in non-STEM occupations who nonetheless use STEM knowledge experienced higher employment rates during the pandemic. We show that R&D expenditures and employment also remained resilient, suggesting only a mild effect of the COVID-19 pandemic on innovative activity. Altogether, our findings suggest that increasing opportunities for STEM training—including outside the college-track—may help improve the employment resiliency of workers during future recessions.

Green Card Quotas and the Misallocation of Talent: Evidence from the STEM Doctoral Labor Market; (Latest Version); Submitted The rates of startup formation, business dynamism, and productivity growth in the US economy have declined since the early 2000s, and a growing literature seeks to identify common forces driving these trends. In this paper, I show that binding green card quotas may contribute to these declines by diverting the most highly-skilled workers in the economy away from entrepreneurial ventures resulting in a misallocation of talent. Using a simple job choice framework, I show that the sudden emergence of country-specific green card delays in October 2005 incentivized Chinese and Indian STEM doctorates to seek employment at established firms over startups as the latter are more likely to shut down prior to the resolution of delays. A difference-in-differences analysis reveals that STEM doctorates who faced green card delays reduced their likelihoods of working in US startups over established firms in the first decade of their careers by 42%. This suggests that policies enabling foreign-born STEM doctorates to avoid green card delays or maintain green card eligibility in the face of job destruction are likely to increase the share of such doctorates working at startups early in their careers.

A Machine Learning Approach to Identifying Postdocs in LEHD Data with James C. Davis, Gerald R. Marschke, and Andrew J. Wang (Latest Version) This paper details the creation of the ACS-LEHD Doctorate Panel—a new linked employer-employee longitudinal dataset of the doctoral workforce enabling researchers to analyze the quarterly labor market outcomes of STEM doctorates and postdocs within the secure environment of a Federal Statistical Research Data Center (FSRDC). To impute the quarterly postdoc employment status of doctorates in matched ACS-LEHD data, we train a machine learning algorithm on the small share of data for which quarterly postdoc employment status is known, yielding an out-of-sample imputation accuracy of over 97%. We include a preliminary analysis of the earnings disparity between postdoc-trained and nonpostdoc-trained biomedical doctorates in the ACS-LEHD Doctorate Panel, finding that postdoc-trained biomedical doctorates tend to earn less than their nonpostdoc-trained counterparts, and that this difference in pay narrows, but does not disappear, when including firm and occupation fixed effects.

Work in Progress

Worker Mobility, R&D Human Capital, and Firm Productivity with Erling Barth, James C. Davis, Gerald R. Marschke, and Andrew J. Wang

The Impact of High-Skilled Immigration on Domestic Workers (Working Title) with Richard B. Freeman, Gerald R. Marschke, and Xiupeng Wang

The Impact of High-Skilled Immigration on Firm Innovation and Productivity (Working Title) with Richard B. Freeman, Gerald R. Marschke, and Xiupeng Wang

Foreign IT Workers and Firms’ Investment in IT (Working Title) with Wang Jin, Chewei Liu, and Xiupeng Wang

Conference Proceedings

US Engineering Employment During the COVID-19 Pandemic with James C. Davis, Gerald R. Marschke, and Andrew J. Wang; 2022 ASEE Annual Conference Proceedings (Link) This paper analyzes the employment trajectories of engineering workers—both workers in occupations formally classified as engineering and workers in occupations not formally classified as engineering but where engineering knowledge is important—during the COVID-19 pandemic. We find that the employment rate of workers in engineering occupations fell by 6.6 percentage-points at the onset of the pandemic compared to a 13.1 percentage-point drop among workers in non-engineering jobs, and that workers in jobs where engineering knowledge is important were less likely to suffer employment loss during the pandemic, regardless of whether their occupation is formally classified as a STEM engineering occupation. This suggests that engineering knowledge is beneficial in reducing a worker’s unemployment risk during recessions. We also find that industries with the highest share of engineers as workers tended to experience smaller percentage declines in employment during the pandemic compared to overall US employment, although employment in aerospace and motor vehicle manufacturing industries remained over 10% below pre-recession employment as of 2021Q4.

Teaching Experience

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Assistant Professor

  • Courses

    • Principles of Microeconomics (ECON 101)
      • Fall 2024 (2 sections), Fall 2023 (2 sections)
    • Principles of Macroeconomics (ECON 102)
      • Spring 2024
    • Introduction to Econometrics (ECON 205)
      • Fall 2024
    • Labor Economics (ECON 344)
      • Spring 2024

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Instructor of Record

  • Course Ratings

  • Courses (4 Sections)

    • Intermediate Macroeconomics
      • Spring 2017 (2 sections)
      • Fall 2015 (1 section)
    • Labor Economics
      • Summer 2015 (1 section)

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