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Bayesian Procedures as a Numerical Tool for the Estimation of Dynamic Discrete Choice Models

  • Peter Haan
  • Daniel Kemptner
  • Arne Uhlendorff

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.

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File URL: http://www.diw.de/documents/publikationen/73/diw_01.c.399474.de/dp1210.pdf
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Paper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 1210.

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Length: 18 p.
Date of creation: 2012
Date of revision:
Handle: RePEc:diw:diwwpp:dp1210
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  1. Akay, Alpaslan, 2009. "Dynamics of the Employment Assimilation of First-Generation Immigrant Men in Sweden: Comparing Dynamic and Static Assimilation Models with Longitudinal Data," IZA Discussion Papers 4655, Institute for the Study of Labor (IZA).
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