By Julen Esteban-Pretel and Junichi Fujimoto
Unemployment, job finding, and job separation rates exhibit patterns of decline as worker age increases in the U.S. We build and numerically simulate a search and matching model of the labor market that incorporates a life-cycle structure to account for these empirical facts. The model features random match quality, which, with positive probability, is not revealed until production takes place. We show that the model, calibrated to U.S. data, is able to reproduce the empirical patterns of unemployment and job transition rates over the entire life-cycle. Both decreasing distance to retirement as a worker ages, and ex ante unknown match quality, are essential in delivering these results. We then explore, both analytically and numerically, the efficiency implications of the model.
Labor search models are getting ever closer to replicate the intricate dynamics of the labor market. Here, it is shown that they can follow labor market flows through the life cycle without needing too much complexity.