I am an assistant professor in the Department of Strategy and Policy, NUS Business School, National University of Singapore. I have research interests in technological change, labor economics, public economics, and various topics in applied microeconomics.
PhD in Economics, 2023
University of Rochester
MA in Economics, 2018
Yonsei University
BA in Applied Statistics, 2014
Yonsei University
Abstract: While growing evidence indicates that the opioid crisis has led to a reduction in local labor supply, whether this decline can be attributable to worker flow in and out of the local area remains unclear. Using over 130 million online job profiles of workers in the US, this paper investigates the effect of the opioid crisis on workers’ location choices. Our job profile data capture worker-level job transitions from 2007 to 2019, allowing us to measure the inflow and outflow of workers for every county pair. We use a difference-in-differences design that leverages geographic variation in exposure to the 2010 reformulation of OxyContin, which led to a large transition from prescription opioids to illicit opioids. We find strong evidence that this transition toward illicit opioids resulted in an increased net outflow of workers away from counties more affected by the reformulation relative to those less affected. Moreover, we show that the increase in net outflow is more pronounced among higher-skilled workers, leading to a substantial decrease in the average skill level of the workers in highly exposed areas. Finally, we investigate the economic consequences of the net outflow among high-skilled workers and demonstrate that the reformulation is associated with a decline in local innovation in terms of patent filings and startup formation. Overall, our findings suggest that the opioid crisis adversely affects both the quantity and quality of local labor supply by influencing workers’ location choices, eventually leading to a deterioration in the economic prospects of affected areas.
Abstract: While growing evidence suggests that the opioid crisis has reduced employment levels, little is known about how the crisis has affected job skill requirements—tools that employers use to screen job candidates. Using data on the near universe of US job vacancies, this paper studies the impact of the opioid crisis on employers’ job skill requirements. Specifically, we investigate the effect of the reformulation of OxyContin, which represents one of the most substantial reductions in the availability of abusable prescription opioids. Prior studies have documented that the reformulation resulted in a large transition from prescription opioids to more dangerous illicit opioids. Using a difference-in-differences event study design that exploits firm-level variation in exposure to reformulation, we show that this transition toward illicit opioids has reduced employment at the firm level. Furthermore, we find that firms have increased requirements for cognitive and computer skills in response to this crisis. Finally, we find that the reformulation has resulted in reductions in local store sales, firm revenue, and firm capital stock, highlighting how the opioid crisis may impact firms’ hiring decisions by affecting various aspects of firms’ constraints and considerations. Our findings emphasize the distributional consequences of this crisis: less-skilled workers may experience a disproportionate impact from the increased skill requirements, even among workers without a history of opioid use disorders.
Abstract: This paper evaluates the impact of high-tech clusters on labor market inequalities by focusing on a place-based industrial policy called “Made in China 2025.” The policy targeted to attract high-tech firms to the industry clusters in the “pilot” cities by providing historical fiscal and regulatory incentives. Leveraging the staggered roll-out of the policy across the pilot cities and representative online job posting data, we conduct an eventstudy analysis to investigate the causal impacts of the high-tech clusters on job openings and wages across occupations and regions. We find that the policy led to a significant increase in job vacancies and offered wages in the pilot cities but with a widening wage gap between routine and non-routine occupations. This policy lowered job openings and wages in neighboring areas of the pilot cities in the short run, but they quickly recovered owing to the positive spillover effects of the high-tech clusters. We also demonstrate that building the high-tech clusters reduced the net income of routine job workers by substantially raising housing costs in the pilot cities. Our results suggest that policymakers should be cautious about occupational and regional inequalities when constructing high-tech clusters in developing countries.
Abstract: This paper studies how firm-level investment and labor demand respond to a reduction in capital cost in the automation process. Using the bonus depreciation policy in the recent U.S. tax reform as an exogenous variation in capital cost, we find that the policy-driven reduction in capital cost lowers labor demand while increasing investment. The positive policy effect on investment is observed only for the eligible capital: machinery and equipment. Using detailed firm-level information on skill and patent compositions, we also find that the reduction in labor demand concentrates in job positions with few software skills and firms with high automation-related technologies, supporting the displacement effect of automation. We illuminate the mechanisms and welfare implications behind the empirical results by introducing a model of automation based on the task-based framework. Linking the reduced-form estimates and the model, we recover capital-labor substitution elasticity by skill and technology levels and find that the task displacement effect of automation accounts for the parameter’s heterogeneity. Our results support the public concern that automated capital could replace some types of workers and show that investment stimulus for machinery and equipment accelerates automation.
Abstract: This paper examines how the labor market effects of import competition vary across Black, Hispanic, and white populations. For a given level of exposure to imports from China, we find no evidence that minority workers are relatively more harmed than white workers in terms of their manufacturing employment. However, exposure to trade shocks varies greatly across groups. Black workers are less likely to live in areas or work in industries facing import competition, resulting in less negative effects of the China shock on manufacturing employment relative to whites. Black workers also benefit disproportionately from the shift towards non-manufacturing employment resulting from the China shock, partially due to their overrepresentation in services at baseline. In contrast, Hispanic workers are overrepresented in exposed industries, though not in exposed geographic areas, meaning that on net they face greater manufacturing employment losses relative to whites. In addition, they experience relative losses in non-manufacturing employment, largely due to their lower educational attainment and baseline industry mix. Overall, the China shock increased the Hispanic-white employment gap by about 5%, though these effects are short lived and converge later in the time period we study. However, the China shock narrowed the Black-white employment gap by about 15%. While many labor market trends in recent decades have served to exacerbate Black-white gaps, import competition is a modest offsetting force.
Spring 2024
TA: Fall 2020, Spring 2021, Fall 2021, Spring 2022, Fall 2022
TA: Spring 2018