Ömer Faruk Koru


I'm a Visiting Assistant Professor of Economics at Penn State.

I received my Ph.D. in Economics from the University of Pennsylvania in 2021.

My research focuses on macroeconomics, labor economics, and inequality.

I am on the 2022/23 job market.

You can download my CV here.

Contact: oqk5084@psu.edu


This paper analyzes the impact of a decrease in the price of capital on the distribution of factor income through the heterogeneous impact across firms. I consider a directed search model with convex cost vacancy posting. In order to economize on vacancy costs, firms can either offer high wages to increase the filling rate or automate more to decrease labor demand. Theoretically, I show that highly productive firms automate more, and a decrease in the price of capital leads to higher automation. This leads to a lower labor share, a higher wage premium for non-routine workers, and higher residual wage dispersion. Quantitatively, the model implies that at the aggregate level, a decrease in labor share is offset by the increase in capital share. Reallocation and firm-level decrease in labor share generate a seven p.p. decrease in aggregate. Unemployment risk generates inefficiency in the model, and with progressive taxation, the capital subsidy can increase the welfare of the new generation by 10%.

Over the last 50 years, the share of wealth held by the richest 1% of individuals in the US has increased by 30%. This paper analyzes the effects of improvements in automation technology on the rise of the top wealth share. I build an incomplete market model with entrepreneurs and a collateral constraint. Automation impacts wealth concentration through two channels. First, it decreases the severity of diseconomies of scale in the entrepreneurial sector, and, hence, it increases income concentration. Since wealth distribution follows income distribution, it affects wealth concentration. Second, it raises capital demand, which tightens the collateral constraint and, in turn, increases the dispersion of the return to capital. I calibrate the model to the 1968 US economy to quantitatively analyze the impact of an improvement in automation. I analyze the impact of an unexpected increase in automation technology to the 2016 level. In the model, the capital share of income equals the automation level; hence, I measure the increase in automation by the change in the capital share. In the new steady state, the top wealth share increases by 8%. In other words, the model can explain one-fourth of the rise in the wealth share of the top 1%. In consumption equivalence terms, workers’ welfare increased by 4% and entrepreneurs’ welfare increased by 8%.

For almost 40 years, top income inequality has increased sharply in the US. At the same time, there have been major improvements in automation technology. It is well-known that top income is well approximated by a Pareto distribution. In this paper, we provide a theory that links automation technology to the Pareto tail of income distribution. We construct a model in which managing labor is more difficult than managing capital. We model this as a convex cost of labor, and that model generates a decreasing returns to scale production function. An improvement in automation enables entrepreneurs to substitute labor with capital and decreases the severity of diseconomies of scale. This leads to higher returns on entrepreneurial skills, a decrease in the Pareto parameter, and an increase in top income inequality. We rationalize the convex cost of labor using a theory of efficiency wages. Using cross-industry and cross-country data, we provide evidence that there is a significant correlation between automation and top income inequality.

Recent empirical work shows a strong positive correlation between job-to-job transition rates and nominal wage growth in the U.S. First, using time series regressions, structural monetary policy shocks, and survey data on search effort we provide evidence that inflationary shocks cause higher job-to-job transitions in the subsequent years. Second, to understand the aggregate implications, we build a structural model with aggregate shocks and competitive on-the-job search in which wages react sluggishly to inflation. In periods with high inflation, the decline in real wages incentivizes the employees to search on-the-job more actively, to negotiate a new contract, but also to be less selective in their search behavior. This creates a fundamental trade-off: increased search effort leads to more job-to-job transitions while being less selective reduces the expected efficiency gain in each transition. Therefore, the effect on output becomes ambiguous. Third, we calibrate the model to the U.S. economy and confirm that the output response to inflation shock is non-monotonic. Importantly, our paper highlights a novel role for inflation: the monetary authority can stimulate productivity with an inflationary shock through job-to-job transitions.

Education:

  • Ph. D., Economics, 2021

University of Pennsylvania, Philadelphia, PA, USA.

  • MA, Economics, 2015

Sabanci University, Istanbul, Turkey.

  • BA, Economics (with minor in Mathematics), 2013

Sabanci University, Istanbul, Turkey.