Nonparametric Identification of Multinomial Choice Demand Models with Heterogeneous Consumers

43 Pages Posted: 25 Aug 2009 Last revised: 29 Sep 2010

See all articles by Steven Berry

Steven Berry

Yale University - Department of Economics; National Bureau of Economic Research (NBER); Yale University - Cowles Foundation

Philip A. Haile

Yale University - Department of Economics; National Bureau of Economic Research (NBER); Yale University - Cowles Foundation

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Date Written: August 2009

Abstract

We consider identification of nonparametric random utility models of multinomial choice using "micro data," i.e., observation of the characteristics and choices of individual consumers. Our model of preferences nests random coefficients discrete choice models widely used in practice with parametric functional form and distributional assumptions. However, the model is nonparametric and distribution free. It allows choice- specific unobservables, endogenous choice characteristics, unknown heteroskedasticity, and high-dimensional correlated taste shocks. Under standard "large support" and instrumental variables assumptions, we show identifiability of the random utility model. We demonstrate robustness of these results to relaxation of the large support condition and show that when it is replaced with a weaker "common choice probability" condition, the demand structure is still identified. We show that key maintained hypotheses are testable.

Suggested Citation

Berry, Steven T. and Haile, Philip A., Nonparametric Identification of Multinomial Choice Demand Models with Heterogeneous Consumers (August 2009). NBER Working Paper No. w15276. Available at SSRN: https://ssrn.com/abstract=1459577

Steven T. Berry (Contact Author)

Yale University - Department of Economics ( email )

28 Hillhouse Ave
New Haven, CT 06520-8264
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National Bureau of Economic Research (NBER)

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Yale University - Cowles Foundation

Box 208281
New Haven, CT 06520-8281
United States

Philip A. Haile

Yale University - Department of Economics ( email )

28 Hillhouse Ave
New Haven, CT 06520-8264
United States
203-432-3568 (Phone)
203-432-6323 (Fax)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Yale University - Cowles Foundation

Box 208281
New Haven, CT 06520-8281
United States

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