A Bayesian Semiparametric Approach for Endogeneity and Heterogeneity in Choice Models

Management Science 60(5):1161-1179, 2014

20 Pages Posted: 28 May 2013 Last revised: 20 Aug 2019

See all articles by Yang Li

Yang Li

Cheung Kong Graduate School of Business

Asim Ansari

Columbia Business School - Marketing

Abstract

Marketing variables that are included in consumer discrete choice models are often endogenous. Extant treatments using likelihood-based estimators impose parametric distributional assumptions, such as normality, on the source of endogeneity. These assumptions are restrictive as misspecified distributions have an impact on parameter estimates and associated elasticities. The normality assumption for endogeneity can be inconsistent with some marginal cost specifications given a price setting process, although being consistent with other specifications. In this paper we propose a heterogeneous Bayesian semiparametric approach for modeling choice endogeneity which offers a flexible and robust alternative to parametric methods. Specifically, we construct centered Dirichlet process mixtures (CDPM) to allow uncertainty over the distribution of endogeneity errors. In a similar vein, we also model consumer preference heterogeneity non-parametrically via a CDPM. Results on simulated data show that incorrect distributional assumptions can lead to poor recovery of model parameters and price elasticities, whereas, the proposed semiparametric model is able to robustly recover the true parameters in an efficient fashion. In addition, the CDPM offers the benefits of automatically inferring the number of mixture components that are appropriate for a given data set and is able to reconstruct the shape of the underlying distributions for endogeneity and heterogeneity errors. We apply our approach to two scanner panel data sets. Model comparison statistics indicate the superiority of the semiparametric specification and the results show that parameter and elasticity estimates are sensitive to the choice of distributional forms. Moreover, the CDPM specification yields evidence of multimodality, skewness, and outlying observations in these real data sets.

Keywords: Discrete Choice, Endogeneity, Semiparametric Bayesian, Centered Dirichlet Process Mixture, Heterogeneity

Suggested Citation

Li, Yang and Ansari, Asim, A Bayesian Semiparametric Approach for Endogeneity and Heterogeneity in Choice Models. Management Science 60(5):1161-1179, 2014. Available at SSRN: https://ssrn.com/abstract=2270993 or http://dx.doi.org/10.2139/ssrn.2270993

Yang Li (Contact Author)

Cheung Kong Graduate School of Business ( email )

Oriental Plaza, Tower E2
One East Chang An Avenue
Beijing, Beijing 100738
China
+861085188858 (Phone)

HOME PAGE: http://english.ckgsb.edu.cn/?q=node/381

Asim Ansari

Columbia Business School - Marketing ( email )

New York, NY 10027
United States

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