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Bayesian procedures as a numerical tool for the estimation of an intertemporal discrete choice model

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  • Peter Haan
  • Daniel Kemptner
  • Arne Uhlendorff

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

Suggested Citation

  • Peter Haan & Daniel Kemptner & Arne Uhlendorff, 2015. "Bayesian procedures as a numerical tool for the estimation of an intertemporal discrete choice model," Empirical Economics, Springer, vol. 49(3), pages 1123-1141, November.
    • Handle: RePEc:spr:empeco:v:49:y:2015:i:3:p:1123-1141
    DOI: 10.1007/s00181-014-0906-7
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    Cited by:

    1. Akinc, Deniz & Vandebroek, Martina, 2018. "Bayesian estimation of mixed logit models: Selecting an appropriate prior for the covariance matrix," Journal of choice modelling, Elsevier, vol. 29(C), pages 133-151.
    2. Jia, Zhiyang & Vattø, Trine Engh, 2021. "Predicting the path of labor supply responses when state dependence matters," Labour Economics, Elsevier, vol. 71(C).
    3. Kassie, Girma T. & Zeleke, Fresenbet & Birhanu, Mulugeta Y. & Scarpa, Riccardo, 2020. "Reminder Nudge, Attribute Nonattendance, and Willingness to Pay in a Discrete Choice Experiment," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304208, Agricultural and Applied Economics Association.
    4. Zhiyang Jia & Trine E. Vattø, 2016. "The path of labor supply adjustment. Sources of lagged responses to tax-benefit reforms," Discussion Papers 854, Statistics Norway, Research Department.

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    More about this item

    Keywords

    Bayesian estimation; Discrete choice models; Intertemporal labor supply behavior; C11; C25; J22;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply

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    1. Bayesian procedures as a numerical tool for the estimation of an intertemporal discrete choice model (Emp Econ 2015) in ReplicationWiki

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