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A Flexible Class of Discrete Choice Models

Author

Listed:
  • S. R. Dalal

    (Bell Communications Research, Inc.)

  • R. W. Klein

    (Bell Communications Research, Inc.)

Abstract

In this paper, we propose a flexible class of discrete choice models. These models are flexible in that members of this class can approximate any discrete choice model obtained from utility maximization. All members of this class are intuitively easy to understand, consistent with utility maximization and do not suffer from the “independence of irrelevant alternatives” problem. In addition, there are members of this class for which maximum likelihood is a feasible estimation method even when the number of alternatives and/or attributes is large. Furthermore, appropriateness of specific functional forms can be explored graphically. We examine the properties of this class intuitively, theoretically, and in an empirical example.

Suggested Citation

  • S. R. Dalal & R. W. Klein, 1988. "A Flexible Class of Discrete Choice Models," Marketing Science, INFORMS, vol. 7(3), pages 232-251.
  • Handle: RePEc:inm:ormksc:v:7:y:1988:i:3:p:232-251
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    File URL: http://dx.doi.org/10.1287/mksc.7.3.232
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    References listed on IDEAS

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    1. Clements, Kenneth W & Johnson, Lester W, 1983. "The Demand for Beer, Wine, and Spirits: A Systemwide Analysis," The Journal of Business, University of Chicago Press, vol. 56(3), pages 273-304, July.
    2. Barten, A. P., 1969. "Maximum likelihood estimation of a complete system of demand equations," European Economic Review, Elsevier, vol. 1(1), pages 7-73.
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    Cited by:

    1. Mattsson, Lars-Göran & Weibull, Jörgen W. & Lindberg, Per Olov, 2014. "Extreme values, invariance and choice probabilities," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 81-95.
    2. Allender, William J. & Richards, Timothy J., 2009. "Measures of Brand Loyalty," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49536, Agricultural and Applied Economics Association.
    3. Manrai, Ajay K., 1995. "Mathematical models of brand choice behavior," European Journal of Operational Research, Elsevier, vol. 82(1), pages 1-17, April.
    4. Poirier, Dale J., 1996. "A Bayesian analysis of nested logit models," Journal of Econometrics, Elsevier, vol. 75(1), pages 163-181, November.
    5. F. Javier Casado-Izaga, 2000. "Location decisions: The role of uncertainty about consumer tastes," Journal of Economics, Springer, vol. 71(1), pages 31-46, February.

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    Keywords

    approximating discrete choice models;

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