Arbeitspapier

Bayesian procedures as a numerical tool for the estimation of dynamic discrete choice models

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.

Language
Englisch

Bibliographic citation
Series: DIW Discussion Papers ; No. 1210

Classification
Wirtschaft
Bayesian Analysis: General
Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
Time Allocation and Labor Supply
Subject
Bayesian Estimation
Dynamic Discrete Choice Models
Intertemporal Labor Supply Behavior

Event
Geistige Schöpfung
(who)
Haan, Peter
Kemptner, Daniel
Uhlendorff, Arne
Event
Veröffentlichung
(who)
Deutsches Institut für Wirtschaftsforschung (DIW)
(where)
Berlin
(when)
2012

Handle
Last update
10.03.2025, 11:45 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Haan, Peter
  • Kemptner, Daniel
  • Uhlendorff, Arne
  • Deutsches Institut für Wirtschaftsforschung (DIW)

Time of origin

  • 2012

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