CCP Estimation of Continuous-Time Job Search Models

This research project will provide new and innovative ways to analyze decisions to accept or decline job offers. Job search models are widely used in labor economics to address fundamental questions related to labor supply in a changing environment. The key to these models is that it takes time and effort for individuals to find a job.

Even though these models are popular, it is often difficult to know if all important characteristics of the model can be recovered from data on labor market transitions and accepted wages. This project will develop a new and innovative framework that allows the researcher to learn about these characteristics from labor market data; the models are also considerably much simpler for empirical analysis than previous models.

This simpler estimation method will make these models accessible to a broader set of empirical researchers. The project will then apply the proposed method to a rich longitudinal data set from the Hungarian labor market to analyze job search behavior over the course of the unemployment spell. The results of this research project will provide better understanding of people’s decisions to accept or not accept job offers and therefore provide guidance into policies to improve the functional of labor markets. It therefore contributes to US economic growth.

This project adapts the conditional choice probability (CCP) estimation method to a continuous-time job search environment. The proposed framework incorporates preference shocks into the search framework, resulting in a tight connection between value functions and conditional choice probabilities. This approach makes it possible to establish constructive identification of all model parameters, which in turn translates into a simple and tractable estimation procedure.

This model is applied to a rich longitudinal data set from the Hungarian labor market. The proposed application will provide new insights on the extent to which the job offer arrival rates as well as the utility of unemployment vary over the course of unemployment. It will also make it possible to evaluate the role played by search effort adjustment in these variations over the course of unemployment.

The results of this research project will provide better understanding of people’s decisions to accept or not accept job offers and therefore provide guidance into policies to improve the functional of labor markets and increase economic growth.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.