Job Mobility Within and Across Occupations (Job Market Paper)
Abstract: This paper assesses the impact of occupational mobility on life cycle wage inequality. I develop a model of job mobility which attributes differential returns to occupations to occupationally heterogeneous labor market frictions, compensating differentials, and non-pecuniary job switching costs. I estimate the structural model on linked Hungarian administrative data and use it to quantify the relative importance of each of these mechanisms. High-skill occupations offer higher wages and more stable employment but lower non-wage amenities than low-skill ones. Coupled with less frequent offers and higher costs of switching from low-skill to high-skill jobs, workers who start in high-skill occupations have much steeper wage profiles. I find that occupationally heterogeneous labor market frictions are the key determinants of ex ante wage profiles. These results indicate that occupational heterogeneity in the sources of wage inequality is instrumental to fully account for life cycle wage dynamics.
Conditional Choice Probability Estimation of Continuous-Time Job Search Models (with Peter Arcidiacono, Ekaterina Jardim, and Arnaud Maurel)
Abstract: We propose a new method to estimate continuous-time job search models. Our approach is based on an adaptation of the conditional choice probability estimation methods to a continuous-time job search environment. To do so, the proposed framework incorporates preference shocks into the search framework, resulting in a tight connection between value functions and conditional choice probabilities. Our method, relative to standard estimation methods for continuous-time job search models, yields considerable computational gains. In particular, we can estimate rich nonstationary job search models without having to solve any differential equations, and in some cases even avoiding any optimization. We apply our method to analyze the effect of unemployment benefit expiration on the duration of unemployment and wages using rich longitudinal data from Hungarian administrative records.
Coworker Networks and the Role of Occupations in Job Finding (with Maria Zhu)
Abstract: Which former coworkers help displaced workers find jobs? We answer this question by studying occupational similarity in job finding networks. Using matched employer-employee data from Hungary, this paper relates the unemployment duration of displaced workers to the employment rate of their former coworker networks. Overall, while coworkers from all occupations are helpful in job finding, we find significant heterogeneity by occupation skill-level. For workers in low-skill jobs, coworkers who worked in the same narrow occupation as the displaced worker are the most useful network contacts. For workers in high-skill jobs, coworkers from different occupations are the most useful network contacts.
Work in Progress
Occupational Structure and Firm Performance