I am on the 2026-2027 job market.

I am a PhD candidate in the Department of Economics at Ohio State University. I am an applied microeconomist with research and teaching interests in labor economics, applied econometrics, entrepreneurship, and household finance. I study how individuals develop and use human capital to pursue economic opportunities, and how institutions and public policies shape these opportunities. Specifically, I study how workers’ skills acquired on the job influence entry into and success in business ownership, how individuals acquire artificial intelligence (AI)-related skills through higher education, and how financial literacy affects financial inclusion. Methodologically, I draw on a wide variety of administrative and survey data, develop novel measures of economic concepts, and use rigorous econometric methods to investigate economic relationships and identify causal effects.

Contact Information

Email: lee.9962@osu.edu
Address: 252 Bricker Hall, 190 N Oval Mall, Columbus, OH 43210

Working Papers

[JMP] Beyond the Jack-of-All-Trades Hypothesis: The Importance of Business and Specialized Skills for Business Ownership Entry and Success
- [Abstract ↓]
  Lazear's well-known jack-of-all-trades (JOAT) model (2004, 2005) hypothesizes that business owners require balanced skills—an argument supported by numerous empirical studies, typically by showing that the number of prior occupations or employers held by workers is positively associated with business ownership. I extend the JOAT literature by arguing that (a) business owners do not need a balance of all skills, but instead need a set of business skills plus specialized skills relevant to their business; (b) business skills are likely to be more important for incorporated, capital-intensive, "advanced" businesses than for "basic" businesses; and (c) evidence in support of the JOAT hypothesis is likely to be sensitive to whether skill balance is measured directly or via orthodox, prior mobility measures. Using NLSY79 work histories linked to O*NET data to measure business skills, specialized skills, and skill balance, I find that all three arguments are supported by the data: business skills are strong predictors of entry into advanced (but not basic) business ownership; both business and specialized skills are associated with higher revenue and earnings for all business owners; and my direct measure of skill balance is unassociated with all three outcomes, whereas an orthodox (occupation count) measure strongly predicts entry into basic business ownership largely because it reflects involuntary job loss. In short, I find that business owners benefit from being jacks of business trades rather than jacks of all trades.
- Presentations: Southern Economic Association Annual Conference 2025; Federal Reserve Bank of Cleveland–Ohio State University Micro-Macro Workshop 2026; Ohio State University
Can a High School Personal Finance Course Reduce the Gender Gap in Being Unbanked?
- [Abstract ↓]
  Among unpartnered young adults in the United States (whose banking status reflects their own financial decisions rather than a partner's) women are significantly more likely than men to be unbanked, even after accounting for income and education. I determine whether state-mandated high school personal finance courses reduce this gender gap, and if so, through what mechanisms. Using the FDIC National Survey of Unbanked and Underbanked Households (2009–2023) and a heterogeneity-robust difference-in-differences estimator, I find that mandates reduce the likelihood of being unbanked for both women and men, but by significantly more for women, narrowing the gender gap by 43%. The effects are concentrated among women with no education beyond high school and among Black and Hispanic women—groups that face the greatest barriers to financial inclusion. I find evidence that the following mechanisms help explain these effects: First, the mandates increase women's objective financial knowledge relative to men's, although not their self-assessed knowledge. Second, the mandates increase women's self-employment, likelihood of attaining middle-income status, and college completion rates relative to men's. Because mandatory high school financial education reaches individuals "early" and does not rely on voluntary participation, it appears useful for reducing persistent gender disparities in financial inclusion that adult financial education programs struggle to address.
- Presentation: Ohio State University
Restricting Large Firms to Protect Small Businesses: Evidence from Retail Operating-Day Restrictions (with Marco Gonzalez-Navarro and Jaecheol Lee)
- [Abstract ↓]
  Governments often try to protect small businesses by restricting when or where larger rivals can operate. Whether such policies achieve their objectives depends on how much displaced demand is actually transferred to the intended beneficiaries—a question that requires tracing substitution toward other days, locations, or unregulated sellers—yet direct evidence on these margins remains limited. We study South Korea's policy requiring large retail chains to close two days per month, which provides predetermined variation in closure schedules across districts and weeks. Using high-frequency credit card-transaction data, we estimate that only 18% of displaced spending is redirected to small, independent retailers; larger shares are recouped by restricted chains on other shopping days or diverted to other unrestricted retail formats, many of which are operated by large firms. Consistent with these limited transfers, we find no evidence that the policy improves the long-run survival of independent retailers. Mapping the observed substitution patterns into a discrete-choice framework identified by policy-induced variation in travel time to open stores, we estimate that the consumer welfare losses from restricted access are 2.7 times larger than the gains accruing to independent retailers. These findings suggest that restricting large firms can impose meaningful consumer costs while providing little durable support to the small businesses such policies are intended to protect.
- Under review
- Presentations: North American Meetings of the Urban Economics Association 2023; Pacific Conference for Development Economics 2025; European Meeting of the Urban Economics Association 2025; Ohio State University

Work in Progress

Self-Employment Following Job Loss and Subsequent Career Trajectories
- [Abstract ↓]
  Job displacement often leads workers to pursue self-employment, yet little is known about whether these self-employment experiences promote or detract from subsequent earnings growth and employment stability. In this paper, I examine the post-displacement labor market trajectories of workers who enter self-employment after job loss, using data from the 1979 National Longitudinal Survey of Youth (NLSY79). Specifically, I compare subsequent earnings and employment stability between displaced workers who transition into self-employment and similar displaced workers who remain in wage employment, matching on pre-displacement earnings, employment histories, demographic characteristics, and other labor market characteristics. I also examine the characteristics of businesses started by workers who enter self-employment following displacement, including the number of employees and industry classification, to assess whether these businesses generate broader economic benefits beyond individual workers' labor market outcomes. This analysis will reveal the benefits of self-employment to workers' recoveries following job displacement, and inform policies aimed at promoting self-employment as a pathway out of unemployment.
AI-Related Education Is Increasing and Widespread but Unequal (with Saleh Zakerinia, Harrison Youn, Bruce Weinberg, Tian Lou, and Aiday Sikhova)
- [Abstract ↓]
  We develop a comprehensive approach for measuring AI-related education and examine how higher education prepares the workforce for an AI-driven economy. Using a taxonomy of six dimensions of AI-related skills (Core, Foundations, Hardware, Infrastructure, Applications, and Governance) and large language models, we classify all degree and certificate programs in the Integrated Postsecondary Education Data System (IPEDS) as AI-related or not, and use these classifications to document national patterns in AI-related credentials. Using data for Ohio's public postsecondary institutions, we apply our classification to university courses based on descriptions in course catalogs, link these data to student-level enrollment records, and summarize patterns in students' AI-related courses. Finally, using UMETRICS grant data at Ohio State University, we identify instructors engaged in funded AI research and examine which students take courses taught by these instructors. By measuring AI-related education across credentials, coursework, and exposure to AI research, we capture a broader range of AI-related skills developed through higher education than do approaches focused on individuals engaged in developing frontier AI technologies. Our approach provides a broad understanding of the extent to which higher education develops AI-related human capital and how its development varies across fields of study, types of institutions, and student populations. Our framework also lays the groundwork for future research on how AI-related skills shape workers' career trajectories, firm performance, and the broader labor market.
- Presentations: Ohio State University; Association for Public Policy Analysis and Management Fall Conference 2026
AI-Related Human Capital Inflows and Gender Composition in Firms (with Tian Lou and Bruce Weinberg)
- [Abstract ↓]
  How does a business's exposure to AI influence gender disparities in its workforce? Building on the idea that AI technology is transmitted through human capital, we compare gender compositions and wage gaps at firms that hire AI-trained researchers with those at firms in the same narrowly-defined industry that hire researchers in non-AI fields. By linking Elsevier data on grant information with UMETRICS data that track payment records for all university research employees funded by grants, we measure a grant's "AI intensity" based on the AI publication activity of its principal investigators and an employee's "AI exposure" based on their duration and intensity of work on these AI-related grants. We then follow these researchers into the workforce using Ohio UI earnings records and the Quarterly Census of Employment and Wages to identify businesses that are more likely to have adopted advanced AI by hiring AI-trained researchers. We find that firms hiring AI-trained researchers have a lower share of female employees and wider gender pay gaps (even among non-AI-trained workers) than firms in the same industries that do not hire AI-trained researchers. Our findings suggest that AI adoption can influence gender disparities across the broader workforce, beyond AI researchers and those directly involved in AI development or use.
- Presentation: University of Chicago

Pre-Doctoral Publications

The Effect of COVID-19 Stimulus Payments on Household Spending (with Chulhee Lee)
Korean Journal of Social Policy, 51, 2022, 60-88 (in Korean, non-peer reviewed).
The Effect of Child Support Payment Coupons in Response to COVID-19 on Household Spending (with Chulhee Lee)
The Korean Journal of Economic Studies, 69(3), 2021, 5-54 (in Korean, peer reviewed). [Abstract ↓]
This paper examines the household spending effects of child support payment coupons in South Korea, which were granted to subsidize households suffering from COVID-19. The results of difference-in-differences estimation suggest that child support payment coupons increased household spending by a weekly average of 22,355 South Korean Won (KRW) over 10 weeks, which is 8.8% of the treatment group's average consumption for the period of analysis. Child support payment coupons have positive impacts on supporting both children and small-scale business-owners. The effect on household spending is shown to be significantly larger for low-income households, compared to that of the top 20% of households. We find that coupon redemption replaces some of the household spending that would occur if there was no support from the government. The size of the net effect (weekly average of 22,355 KRW over 10 weeks) is determined by the difference between coupon redemption (57,620 KRW) and the size of the substitution effect (35,256 KRW). These results imply that the net effect of the coupons is estimated to be approximately 39% of the coupon redemption for 10 weeks. We also discuss the implications of our findings on the effects and design of government subsidies.

Teaching

Ohio State University

Principles of Microeconomics, Instructor of Record, SU 2023
Principles of Microeconomics, Teaching Assistant, AU 2023
Principles of Macroeconomics, Teaching Assistant, AU 2023
Health Economics, Teaching Assistant, AU 2022
Intermediate Microeconomic Theory with Calculus, Teaching Assistant, AU 2022

Seoul National University

Population and Economy, Teaching Assistant, AU 2019, AU 2020
Economic History, Teaching Assistant, SP 2020