How the reduction of Temporary Foreign Workers led to a rise in vacancy rates in South Korea
Job Market Paper
(Submitted to Journal of Human Capital, Revise and Resubmit received)
This study investigates the causal relationship between the reduction of low-skilled temporary foreign workers (TFWs) and job vacancies in South Korea's manufacturing sectors, utilizing the COVID-19 quarantine policy as a natural experiment. Employing a Difference-in-Differences methodology, the research reveals that sectors with high dependence on TFWs, particularly for permanent positions, experienced significantly elevated vacancy rates for a two-year period following the onset of the pandemic. The inability of native workers to fill these positions highlights the critical role of foreign labor in mitigating labor shortages. Notably, vacancy rates began to decline only after the government relaxed quarantine restrictions, facilitating the re-entry of TFWs into the country. These findings are corroborated by local projection methods.
with Tai Lee (Submitted to Labour Economics)
This study proposes an innovative methodology for quantifying Routine Task Intensity (RTI) and Cognitive Task Intensity (CTI) using Large Language Models to analyze O*NET task descriptions. Employing these LLM-derived measures, we reveal a consistent decline in routine occupations across Service and Sales sectors, with Sales receiving limited attention in existing literature. Regression analysis indicates a significant upward trend in cognitive impact on wages for females, particularly in Service, Sales, and to a lesser extent, Management occupations, while routine coefficients remain stable across five decades. These results underscore the growing significance of cognitive skills, especially for women in the workforce. Despite limitations in LLM output reliability and replicability, our methodology offers a complementary perspective to existing approaches, enabling a comprehensive understanding of labor market transformations.
Automation, Human Task Innovation, and Labor Share
with Seungjin Baek
This study examines the impacts of robotic innovation (RI) and human innovation (HI) on labor share across nine EU countries. Using a general equilibrium model and novel shift-share instruments, we address endogeneity concerns by utilizing International Federation of Robotics data, US patents, and a Cognitive Tasks Index. Our findings show that until 2024, RI's negative impact has exceeded HI's positive effect on labor share. We estimate the elasticity of substitution between labor and non-robot capital at 0.52, and between labor and robots at 2.67. These results offer insights for policymakers addressing declining labor share, emphasizing the importance of fostering human innovation alongside technological advancement.
Market Concentration and Labor Share: An EU Critique of the Superstar Firms Theory (Work in Progress)
with Ju Hyun Pyun and Corinne Stephenson
This study examines the Superstar Firms theory proposed by Autor et al. (2020), focusing on its applicability to European Union (EU) nations. Our findings suggest that the Superstar Firms theory does not adequately explain the decline in labor share observed across EU countries. Contrary to the United States, where market concentration has increased, EU nations have experienced a notable overall decrease in market concentration, as thoroughly investigated by Kalemli-Özcan et al. (2024). Utilizing firm-level data from Historical Bvd Orbis, we initially demonstrate a weak correlation between market concentration and changes in labor share within the EU. Subsequently, we establish the absence of a significant correlation between markup and concentration. Finally, we propose a compelling model tailored to the unique EU context, which elucidates these empirical findings. We conclude that while the Superstar Firms theory offers a robust explanation for trends in the United States, its universal applicability is limited, particularly in the context of the EU.