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Testing Predicted Choices Against Observations in Probabilistic Discrete-Choice Models

Author

Listed:
  • Joel L. Horowitz

    (University of Iowa)

  • Jordan J. Louviere

    (University of Utah)

Abstract

Probabilistic discrete-choice models, such as multinomial logit models, are widely used to predict changes in market shares or total demand resulting from changes in policy variables under management control. These models often are evaluated in terms of their ability to predict choices in a holdout sample. This paper presents a new test for comparing predicted and observed choices. The results of a Monte Carlo experiment indicate that the new test has good finite-sample properties and high power in several circumstances likely to arise frequently in applications.

Suggested Citation

  • Joel L. Horowitz & Jordan J. Louviere, 1993. "Testing Predicted Choices Against Observations in Probabilistic Discrete-Choice Models," Marketing Science, INFORMS, vol. 12(3), pages 270-279.
  • Handle: RePEc:inm:ormksc:v:12:y:1993:i:3:p:270-279
    DOI: 10.1287/mksc.12.3.270
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    Cited by:

    1. Ram Shrestha & John Loomis, 2003. "Meta-Analytic Benefit Transfer of Outdoor Recreation Economic Values: Testing Out-of-Sample Convergent Validity," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 25(1), pages 79-100, May.
    2. Kamolthip, Sarun & Seenprachawong, Udomsak, 2016. "Validity of Internet-based Stated Preference Data in Modeling Waterfall Recreation Site Choice," Asian Journal of Applied Economics, Kasetsart University, Center for Applied Economics Research, vol. 23(2), December.
    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. Horowitz, Joel & Keane, Michael & Bolduc, Denis & Divakar, Suresh & Geweke, John & Gonul, Fosun & Hajivassiliou, Vassilis & Koppelman, Frank & Matzkin, Rosa & Rossi, Peter & Ruud, Paul, 1994. "Advances in Random Utility Models," MPRA Paper 53026, University Library of Munich, Germany.
    5. Poudel, Rajendra & Collins, Alan & Gazal, Kathryn & Wang, Jingxin, 2020. "Benefit transfer estimation of willingness-to-pay for U.S. wetlands conservation," Forest Policy and Economics, Elsevier, vol. 115(C).

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