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Demand Estimation with Heterogeneous Consumers and Unobserved Product Characteristics: A Hedonic Approach

  • Benkard, C. Lanier

    (Stanford U)

  • Bajari, Patrick
Registered author(s):

    We study the identification and estimation of preferences in hedonic discrete choice models of demand for differentiated products. In the hedonic discrete choice model, products are represented as a finite dimensional bundle of characteristics, and consumers maximize utility subject to a budget constraint. Our hedonic model also incorporates product characteristics that are observed by consumers but not by the economist. We demonstrate that, unlike the case where all product characteristics are observed, it is not in general possible to uniquely recover consumer preference from data on a consumer's choices. However, we provide several sets of assumptions under which preferences can be recovered uniquely, that we think may be satisfied in many applications. Our identification and estimation strategy is a two-stage approach in the spirit of Rosen (1974). In the first stage, we show under some weak conditions that price data can be used to nonparametrically recover the unobserved product characteristics and the hedonic pricing function. In the second stage, we show under some weak conditions that if the product space is continuous and the functional form of utility is known, then there exits an inversion between a consumer's choices an her preference parameters. If the product space is discrete, we propose a Gibbs sampling algorithm to simulate the population distribution of consumers' taste coefficients.

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    File URL: http://gsbapps.stanford.edu/researchpapers/library/RP1691.pdf
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    Paper provided by Stanford University, Graduate School of Business in its series Research Papers with number 1691.

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    Date of creation: Jun 2001
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    Handle: RePEc:ecl:stabus:1691
    Contact details of provider: Postal: Stanford University, Stanford, CA 94305-5015
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    1. Robert C. Feenstra, 1995. "Exact Hedonic Price Indexes," NBER Working Papers 5061, National Bureau of Economic Research, Inc.
    2. Geweke, John & Keane, Michael P & Runkle, David, 1994. "Alternative Computational Approaches to Inference in the Multinomial Probit Model," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 609-32, November.
    3. Jones, Larry E, 1984. "A Competitive Model of Commodity Differentiation," Econometrica, Econometric Society, vol. 52(2), pages 507-30, March.
    4. Richard Blundell & Martin Browning & Ian Crawford, 1997. "Non-parametric Engel curves and revealed preferences," IFS Working Papers W97/14, Institute for Fiscal Studies.
    5. Bartik, Timothy J, 1987. "The Estimation of Demand Parameters in Hedonic Price Models," Journal of Political Economy, University of Chicago Press, vol. 95(1), pages 81-88, February.
    6. Daniel A. Ackerberg & Marc Rysman, 2002. "Unobserved Product Differentiation in Discrete Choice Models: Estimating Price Elasticities and Welfare Effects," NBER Working Papers 8798, National Bureau of Economic Research, Inc.
    7. Charles F. Manski & John V. Pepper, 1998. "Monotone Instrumental Variables with an Application to the Returns to Schooling," NBER Technical Working Papers 0224, National Bureau of Economic Research, Inc.
    8. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1, March.
    9. Caplin, Andrew & Nalebuff, Barry, 1991. "Aggregation and Imperfect Competition: On the Existence of Equilibrium," Econometrica, Econometric Society, vol. 59(1), pages 25-59, January.
    10. Peter Davis, 2006. "Spatial competition in retail markets: movie theaters," RAND Journal of Economics, RAND Corporation, vol. 37(4), pages 964-982, December.
    11. Epple, Dennis, 1987. "Hedonic Prices and Implicit Markets: Estimating Demand and Supply Functions for Differentiated Products," Journal of Political Economy, University of Chicago Press, vol. 95(1), pages 59-80, February.
    12. Hendel, Igal, 1999. "Estimating Multiple-Discrete Choice Models: An Application to Computerization Returns," Review of Economic Studies, Wiley Blackwell, vol. 66(2), pages 423-46, April.
    13. Geweke, John, 1996. "Monte carlo simulation and numerical integration," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 15, pages 731-800 Elsevier.
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