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Nonparametric Identification of Multinomial Choice Demand Models with Heterogeneous Consumers

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  • Steven T. Berry
  • Philip A. Haile

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.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 15276.

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Date of creation: Aug 2009
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Handle: RePEc:nbr:nberwo:15276

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Citations

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Cited by:
  1. Christopher T. Conlon & Julie Holland Mortimer, 2013. "Demand Estimation under Incomplete Product Availability," American Economic Journal: Microeconomics, American Economic Association, American Economic Association, vol. 5(4), pages 1-30, November.
  2. Steven T. Berry & Philip A. Haile, 2009. "Identification of a Heterogeneous Generalized Regression Model with Group Effects," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University 1732, Cowles Foundation for Research in Economics, Yale University.
  3. Steven T. Berry & Philip Haile, 2010. "Identification in Differentiated Products Markets Using Market Level Data," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University 1744R, Cowles Foundation for Research in Economics, Yale University, revised May 2012.
  4. Cerquera Dussán, Daniel & Ullrich, Hannes, 2010. "Consumer welfare and unobserved heterogeneity in discrete choice models: The value of alpine road tunnels," ZEW Discussion Papers 10-095, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  5. Matzkin, Rosa L., 2012. "Identification in nonparametric limited dependent variable models with simultaneity and unobserved heterogeneity," Journal of Econometrics, Elsevier, Elsevier, vol. 166(1), pages 106-115.
  6. Fox, Jeremy T. & Kim, Kyoo il & Ryan, Stephen P. & Bajari, Patrick, 2012. "The random coefficients logit model is identified," Journal of Econometrics, Elsevier, Elsevier, vol. 166(2), pages 204-212.
  7. Olivier Allais & Fabrice Etile & Sebastien Lecocq, 2013. "Mandatory Labels, taxes and market forces : An empirical evaluation of fat policies," Working Papers 221517, Institut National de la Recherche Agronomique, France.
  8. Yingying Dong & Arthur Lewbel, 2012. "Simple Estimators for Binary Choice Models with Endogenous Regressors," Working Papers 111204, University of California-Irvine, Department of Economics.
  9. Burda, Martin & Harding, Matthew & Hausman, Jerry, 2012. "A Poisson mixture model of discrete choice," Journal of Econometrics, Elsevier, Elsevier, vol. 166(2), pages 184-203.
  10. Eric Gautier & Yuichi Kitamura, 2011. "Nonparamatric estimation in random coefficients binary choice models," Working Papers hal-00403939, HAL.
  11. repec:hal:wpaper:halshs-00736556 is not listed on IDEAS
  12. Handel, Benjamin R. & Misra, Kanishka & Roberts, James W., 2013. "Robust firm pricing with panel data," Journal of Econometrics, Elsevier, Elsevier, vol. 174(2), pages 165-185.

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