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Hybrid Choice Models: Progress and Challenges

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Author Info
Axel Börsch-Supan ()
Moshe Ben-Akiva
Kenneth Train
Daniel McFadden (Mannheim Research Institute for the Economics of Aging (MEA))

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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 explanatory variables, heterogeneity, and latent segmentation. Both progress and challenges related to the development of the hybrid choice model are presented.

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Publisher Info
Paper provided by Mannheim Research Institute for the Economics of Aging (MEA), University of Mannheim in its series MEA discussion paper series with number 02009.

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Date of creation: 20 Jan 2002
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Handle: RePEc:mea:meawpa:02009

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Postal: MEA - Mannheimer Forschungsinstitut Ökonomie und Demographischer Wandel, L13, 17, University of Mannheim, 68131 Mannheim
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Web page: http://www.mea.uni-mannheim.de/

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Z00 - Other Special Topics - - General - - - General

References listed on IDEAS
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.:

  1. Kenneth Train, 2000. "Halton Sequences for Mixed Logit," Department of Economics, Working Paper Series 1035, Department of Economics, Institute for Business and Economic Research, UC Berkeley. [Downloadable!]
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  2. 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.
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  3. 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.
  4. Daniel McFadden, 2001. "Economic Choices," American Economic Review, American Economic Association, vol. 91(3), pages 351-378, June. [Downloadable!] (restricted)
  5. 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. [Downloadable!]
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  1. Dirk Temme & Marcel Paulssen & Till Dannewald, 2007. "Integrating latent variables in discrete choice models – How higher-order values and attitudes determine consumer choice," SFB 649 Discussion Papers SFB649DP2007-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
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