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Ömer Faruk Koru
I’m an Assistant Professor of Economics at Weselyan University.
I received my Ph.D. in Economics from the University of Pennsylvania in 2021.
My research focuses on macroeconomics, labor economics, and public economics.
Contact: okoru@wesleyan.edu
Working Papers
Changing Jobs to Fight Inflation: Labor Market Reactions to Inflationary Shocks
Submitted
with Görkem Bostancı , Sergio Villalvazo
We argue that inflationary shocks affect allocative efficiency by changing the rate and the characteristics of workers’ job-to-job transitions. First, using monetary policy shocks and survey data on search effort, we empirically show that a one percentage point rise in inflation increases job-to-job transitions by up to 4.5%, and workers with higher inflation expectations are more likely to search and do so more effectively. Second, we build a general equilibrium model of directed on-the-job search to quantify the aggregate implications of labor market reactions. Higher-than-expected inflation reduces real wages, prompting workers to search more actively and aim lower. This increases job-to-job transitions but lowers the efficiency gains per transition. Therefore, the effect on output is ambiguous. Last, we calibrate the model to the U.S. economy. Inflationary shocks increase reallocation rates, yet allocative efficiency and output decline. Small deflationary shocks (e.g., 2%) increase output in the short run, while others decrease it.
Automation and Top Income Inequality
R&R at the Journal of Economic Theory
This paper develops a theoretical framework linking automation to the thickness of the top income distribution, which is well-approximated by a Pareto distribution. In our model, entrepreneurs face convex labor costs, limiting scalability. Automation enables them to substitute capital for labor, mitigating the diseconomies of scale and increasing returns to entrepreneurial skill, resulting in a decline in the Pareto parameter and a rise in top inequality. We test the model’s predictions using U.S. industry-level data on entrepreneurial income and CEO compensation, and find that greater automation is associated with lower Pareto parameters, wider capital intensity gaps, and higher CEO compensation in capital-intensive firms. These results highlight the role of automation in shaping the upper tail of the income distribution.
Automation and Top Wealth Inequality
This paper studies the impact of automation on wealth concentration in the United States using a dynamic model with a task-based framework and collateral-constrained entrepreneurs. Automation is shown to increase wealth inequality by boosting income concentration and widening capital return dispersion. The calibrated model explains about one-third of the observed rise in the top 1% wealth share. Welfare analysis shows automation raised worker welfare by 5% and entrepreneur welfare by 8%, underscoring its role in expanding wealth inequality through increased capital and entrepreneurial returns.
Technology Adoption by Firms and Distribution of Factor Income
This paper examines how a decrease in capital costs affects factor income distribution through its varied impact across firms. Using a directed search model with convex vacancy posting costs, I explore how firms manage vacancy expenses by either raising wages to improve hiring rates or increasing automation to reduce labor needs. The model shows that more productive firms tend to automate more, and as capital prices fall, automation rises, leading to a lower labor share, a higher wage premium for non-routine workers, and increased residual wage dispersion. Quantitatively, the model suggests that the aggregate decrease in labor share is balanced by an increase in capital share, resulting in a net seven percentage point decline. Additionally, unemployment risk creates inefficiencies, which can be mitigated through progressive taxation and capital subsidies, enhancing the welfare of the new generation.
Work in Progress
Optimal City Level Progressive Taxation