Semiparametric Bayesian estimation of random coefficients discrete choice models

Sylvie Tchumtchoua and Dipak K. Dey

A chapter in Bayesian Econometrics, 2008, pp 275-307 from Emerald Group Publishing Limited

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.

Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-9053(08)23009-4

DOI: 10.1016/S0731-9053(08)23009-4

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