Current Projects

Firms want to hire the best worker for the job, and they choose
strategies to select an employee accordingly. After the hiring, they learn about the compatibility of the employee. The speed of learning about the quality of the employment relationship would depend on the skill requirement of a job, so would the decision about hiring strategies. This paper analyzes how much do differences in hiring strategies and the speed of learning about the quality across different skill groups contribute to disparities in their labor market outcomes such as job duration, unemployment, and starting wages. It also looks at the interaction between learning about match quality and hiring strategies. The longer it takes to learn, the harder it becomes to detect the mistake of hiring the "wrong" worker, thus, the more likely it is that the firm invests more in selection.

Working Papers

High-skill workers have a lower unemployment rate than their low-skill counterparts. This is because high-skill workers are less likely to become unemployed, not because they are more likely to find a job. This paper proposes an explanation for the skill discrepancy in likelihood of becoming unemployed: high-skill workers are less likely to become unemployed because they are selected more effectively during their hiring process. I use a labor search model with match specific quality to show that skill bias in employee selection practices can account for the differences in job separation probabilities and unemployment rates across skill groups.

Labor matching models with heterogeneous markets are used in unemployment literature to understand the dynamics of aggregate labor markets as well as the cross country differences in labor market outcomes. The heterogeneity is modeled via differences in skill requirements of jobs and skill levels of workers. These models generally assume undirected search for workers and vacancies in the sense that workers and vacancies match regardless of their skill compatibility. Under this assumption, some of the matches will not result in an employment relationship. This paper proposes another way of modeling the matching markets; having sequential job markets. With sequential matching markets, workers can search by the skill requirement of the job. Matching markets being sequential also allows workers to search at multiple job markets within a period. The paper also analyzes the effect of a skill biased technological change on labor market outcomes under each of these assumptions on the matching markets. How matching markets are modeled changes the response of the overall unemployment rate to a skill biased change. The unemployment rate decreases with a skill biased technological change, if the matching markets are sequential. However, with undirected search overall unemployment rate increases with a skill biased technological change.

Empirical research established the fact that there is heterogeneity in labor markets. One important source of heterogeneity is skill. Moreover, data suggest that there is interaction between different skill markets. However, foundations of these sources and their effects on the equilibrium outcomes are not well known. This paper analyzes two of these sources in a heterogeneous agents labor matching environment. The first source of the interaction is the competition between workers of different skill groups for the same type of jobs. The other possible source is vacancies of different skill types competing for firms. The expected profits in different sectors gives firms incentives to open vacancies in these sectors. In models with ex ante homogenous firms, choice of a sector becomes trivial for firms since profits will be zero, due to the free entry condition, in equilibrium in all sectors.  However, in a model with ex ante heterogeneous firms the distribution of different vacancies has nontrivial effects on equilibrium.