Essays in Job Mobility
dc.contributor.advisor | Arcidiacono, Peter | |
dc.contributor.author | Gyetvai, Attila | |
dc.date.accessioned | 2021-05-19T18:08:47Z | |
dc.date.available | 2021-05-19T18:08:47Z | |
dc.date.issued | 2021 | |
dc.department | Economics | |
dc.description.abstract | This dissertation explores three aspects of job mobility in three essays. The first essay, "Job Mobility Within and Across Occupations," 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; in turn, low-skill occupations feature higher non-wage amenities but larger non-pecuniary costs of switching to high-skill jobs. As a result, workers who start their careers in the bottom 10 percent of the wage distribution in a high-skill occupation surpass those who start in the top 5 percent of a low-skill occupation in 5 years. I find that occupationally heterogeneous labor market frictions are the key drivers of these 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. The second essay, "Conditional Choice Probability Estimation of Continuous-Time Job Search Models," introduces a novel framework to analyze mobility across jobs and out of unemployment. My coauthors and I adapt the conditional choice probability estimation method to a continuous-time job search environment. To do so, the proposed framework incorporates preference shocks into the canonical job search model, 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, this method makes it possible to estimate rich, possibly non-stationary, job search models without having to solve any differential equations, and in some cases even avoiding optimization altogether. 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. The third essay, "Coworker Networks and the Role of Occupations in Job Finding," asks which former coworkers help displaced workers find jobs. My coauthor and I 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. | |
dc.identifier.uri | ||
dc.subject | Labor economics | |
dc.title | Essays in Job Mobility | |
dc.type | Dissertation |