TY  - RPRT
        AU  - Haan, Peter
AU  - Kemptner, Daniel
AU  - Uhlendorff, Arne
        TI  - Bayesian Procedures as a Numerical Tool for the Estimation of Dynamic Discrete Choice Models
        PY  - 2012/May/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 6544
        UR  - https://www.iza.org/publications/dp6544
        AB  - Dynamic discrete choice models usually require a general specification of unobserved heterogeneity. In this paper, we apply Bayesian procedures as a numerical tool for the estimation of a female labor supply model based on a sample size which is typical for common household panels. We provide two important results for the practitioner: First, for a specification with a multivariate normal distribution for the unobserved heterogeneity, the Bayesian MCMC estimator yields almost identical results as a classical Maximum Simulated Likelihood (MSL) estimator. Second, we show that when imposing distributional assumptions which are consistent with economic theory, e.g. log-normally distributed consumption preferences, the Bayesian method performs well and provides reasonable estimates, while the MSL estimator does not converge. These results indicate that Bayesian procedures can be a beneficial tool for the estimation of dynamic discrete choice models.
        KW  - dynamic discrete choice models
KW  - intertemporal labor supply behavior
KW  - Bayesian estimation
        ER  -