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Hybrid Choice Models: Progress and Challenges

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Author Info

  • Ben-Akiva, Moshe

    ()
    (Massachusetts Institute of Technology)

  • McFadden, Daniel

    ()
    (University of California at Berkeley)

  • Train, Kenneth

    ()
    (University of California at Berkeley)

  • Börsch-Supan, Axel

    ()
    (Sonderforschungsbereich 504)

Abstract

We discuss the development of predictive choice models that go beyond the random utility model in its narrowest formulation. Such approaches incorporate several elements of cognitive process that have been identified as important to the choice process, including strong dependence on history and context, perception formation, and latent constraints. A flexible and practical hybrid choice model is presented that integrates many types of discrete choice modeling methods, draws on different types of data, and allows for flexible disturbances and explicit modeling of latent psychological variables, heterogeneity, and latent segmentation. Both progress and challanges related to the development of the hybrid choice model are presented.

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Bibliographic Info

Paper provided by Sonderforschungsbereich 504, Universität Mannheim & Sonderforschungsbereich 504, University of Mannheim in its series Sonderforschungsbereich 504 Publications with number 02-29.

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Length: 15 pages
Date of creation: 22 Mar 2002
Date of revision:
Handle: RePEc:xrs:sfbmaa:02-29

Note: Financial support from the Deutsche Forschungsgemeinschaft, SFB 504, at the University of Mannheim, is gratefully acknowledged.
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  1. Dufour, Jean-Marie & Jasiak, Joann, 2001. "Finite Sample Limited Information Inference Methods for Structural Equations and Models with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(3), pages 815-43, August.
  2. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
  3. BOLDUC, Denis & FORTIN, Bernard & GORDON, Stephen, 1995. "Multinomial Probit Estimation of Spatially Interdependent Choices: an Empirical Comparison of Two New Techniques," Cahiers de recherche 9508, Université Laval - Département d'économique.
  4. McFadden, Daniel L., 2000. "Economic Choices," Nobel Prize in Economics documents 2000-6, Nobel Prize Committee.
  5. Bolduc, Denis, 1999. "A practical technique to estimate multinomial probit models in transportation," Transportation Research Part B: Methodological, Elsevier, vol. 33(1), pages 63-79, February.
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