Bayesian procedures as a numerical tool for the estimation of an intertemporal discrete choice model
Peter Haan,
Daniel Kemptner () and
Arne Uhlendorff
Empirical Economics, 2015, vol. 49, issue 3, 1123-1141
Abstract:
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 that 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 that 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 intertemporal discrete choice models. Copyright Springer-Verlag Berlin Heidelberg 2015
Keywords: Bayesian estimation; Discrete choice models; Intertemporal labor supply behavior; C11; C25; J22 (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:empeco:v:49:y:2015:i:3:p:1123-1141
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DOI: 10.1007/s00181-014-0906-7
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