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Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market

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  • Steven Berry
  • James Levinsohn
  • Ariel Pakes

Abstract

In this paper, we consider how rich sources of information on consumer choice can help to identify demand parameters in a widely used class of differentiated products demand models. Most important, we show how to use "second-choice" data on automotive purchases to obtain good estimates of substitution patterns in the automobile industry. We use our estimates to make out-of-sample predictions about important recent changes in industry structure.

Suggested Citation

  • Steven Berry & James Levinsohn & Ariel Pakes, 2004. "Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market," Journal of Political Economy, University of Chicago Press, vol. 112(1), pages 68-105, February.
    • Handle: RePEc:ucp:jpolec:v:112:y:2004:i:1:p:68-105
    DOI: 10.1086/379939
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    3. McCulloch, Robert E. & Polson, Nicholas G. & Rossi, Peter E., 2000. "A Bayesian analysis of the multinomial probit model with fully identified parameters," Journal of Econometrics, Elsevier, vol. 99(1), pages 173-193, November.
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    More about this item

    JEL classification:

    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • L9 - Industrial Organization - - Industry Studies: Transportation and Utilities

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    1. Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market (JPE 2004) in ReplicationWiki

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