Hybrid Choice Models: Progress and Challenges
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 explanatory variables, heterogeneity, and latent segmentation. Both progress and challenges related to the development of the hybrid choice model are presented.
|Date of creation:||20 Jan 2002|
|Date of revision:|
|Contact details of provider:|| Postal: Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy, Amalienstraße 33, 80799 München, Germany|
Web page: http://www.mea.mpisoc.mpg.de/
|Order Information:|| Email: |
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Daniel McFadden, 2001.
American Economic Review,
American Economic Association, vol. 91(3), pages 351-378, June.
- Bolduc, D. & Fortin, B. & Gordon, S., 1995.
"Multinomial Probit Estimation of Spatially Interdependent Choices: An Empirical Comparison of Two New Techniques,"
9508, Laval - Recherche en Politique Economique.
- Denis Bolduc & Bernard Fortin & Stephen Gordon, 1997. "Multinomial Probit Estimation of Spatially Interdependent Choices: An Empirical Comparison of Two New Techniques," International Regional Science Review, , vol. 20(1-2), pages 77-101, April.
- 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.
- 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.
- 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.
- 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.
When requesting a correction, please mention this item's handle: RePEc:mea:meawpa:02009. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Henning Frankenberger)
If references are entirely missing, you can add them using this form.