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Semiparametric Bayesian estimation of random coefficients discrete choice models

In: Bayesian Econometrics

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  • Sylvie Tchumtchoua
  • Dipak K. Dey

Abstract

Heterogeneity in choice models is typically assumed to have a normal distribution in both Bayesian and classical setups. In this paper, we propose a semiparametric Bayesian framework for the analysis of random coefficients discrete choice models that can be applied to both individual as well as aggregate data. Heterogeneity is modeled using a Dirichlet process, which varies with consumers’ characteristics through covariates. We develop a Markov Chain Monte Carlo algorithm for fitting such model, and illustrate the methodology using two different datasets: a household-level panel dataset of peanut butter purchases, and supermarket chain-level data for 31 ready-to-eat breakfast cereal brands.

Suggested Citation

  • Sylvie Tchumtchoua & Dipak K. Dey, 2008. "Semiparametric Bayesian estimation of random coefficients discrete choice models," Advances in Econometrics, in: Bayesian Econometrics, pages 275-307, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-9053(08)23009-4
    DOI: 10.1016/S0731-9053(08)23009-4
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