Exact Structural Inference in Optimal Job-Search Models.

This paper is a study of the exact posterior distributions of parameters in a stationary optimal job search model. The author exploits the simple latent structure of the search model when all job offers are observed to stimulate posterior distributions of structural parameters when the latent structure is imperfectly observed. These simulations enable him to show the unusual shape of the job search likelihood when the data are durations and accepted wages. The author also develops an algorithm to resample simulated posterior distributions in order to impose on the model the implications of fully optimal search. The methods are illustrated using simulated data.