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

  • Bajari, Patrick

    (Duke U)

  • Benkard, C. Lanier

    (Stanford U)

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    We study the identification and estimation of Gorman-Lancaster style hedonic models of demand for differentiated products for the case when one product characteristic is not observed. Our identification and estimation strategy is a two-step approach in the spirit of Rosen (1974). Relative to Rosen's approach, we generalize the first stage estimation to allow for a single dimensional unobserved product characteristic, and also allow the hedonic pricing function to have a general, non-additive structure. In the second stage, if the product space is continuous and the functional form of utility is known then there exists an inversion between the consumer's choices and her preference parameters. This inversion can be used to recover the distribution of random coeffcients nonparametrically. For the more common case when the set of products is finite, we use the revealed preference conditions from the hedonic model to develop a Gibbs sampling estimator for the distribution of random coeffcients. We apply our methods to estimating personal computer demand.

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    File URL: http://gsbapps.stanford.edu/researchpapers/library/RP1842.pdf
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    Paper provided by Stanford University, Graduate School of Business in its series Research Papers with number 1842.

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    Date of creation: Jan 2004
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    Handle: RePEc:ecl:stabus:1842
    Contact details of provider: Postal: Stanford University, Stanford, CA 94305-5015
    Phone: (650) 723-2146
    Fax: (650)725-6750
    Web page: http://gsbapps.stanford.edu/researchpapers/
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    1. Amil Petrin, 2002. "Quantifying the Benefits of New Products: The Case of the Minivan," Journal of Political Economy, University of Chicago Press, vol. 110(4), pages 705-729, August.
    2. Patrick Bajari & Matthew E. Kahn, 2002. "Estimating Housing Demand with an Application to Explaining Racial Segregation in Cities," Working Papers 02011, Stanford University, Department of Economics.
    3. Charles F. Manski & John V. Pepper, 2000. "Monotone Instrumental Variables, with an Application to the Returns to Schooling," Econometrica, Econometric Society, vol. 68(4), pages 997-1012, July.
    4. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1, March.
    5. Nevo, Aviv, 2001. "Measuring Market Power in the Ready-to-Eat Cereal Industry," Econometrica, Econometric Society, vol. 69(2), pages 307-42, March.
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    7. Caplin, Andrew & Nalebuff, Barry, 1991. "Aggregation and Imperfect Competition: On the Existence of Equilibrium," Econometrica, Econometric Society, vol. 59(1), pages 25-59, January.
    8. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74, pages 132.
    9. Steven Berry & James Levinsohn & Ariel Pakes, 1998. "Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market," NBER Working Papers 6481, National Bureau of Economic Research, Inc.
    10. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    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.
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    15. repec:att:wimass:9604 is not listed on IDEAS
    16. Ivar Ekeland & James J. Heckman & Lars Nesheim, 2003. "Identification and Estimation of Hedonic Models," CESifo Working Paper Series 1031, CESifo Group Munich.
    17. 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.
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