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A Multivariate Model for Multinomial Choices

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  • Bel, K.
  • Paap, R.

Abstract

__Abstract__ Multinomial choices of individuals are likely to be correlated. Nonetheless, econometric models for this phenomenon are scarce. A problem of multivariate multinomial choice models is that the number of potential outcomes can become very large which makes parameter interpretation and inference difficult. We propose a novel Multivariate Multinomial Logit specification, where (i) the number of parameters stays limited; (ii) there is a clear interpretation of the parameters in terms of odds ratios; (iii) zero restrictions on parameters result in independence between the multinomial choices and; (iv) parameter inference is feasible using a composite likelihood approach even if the multivariate dimension is large. Finally, these nice properties are also valid in a fixed-effects panel version of the model.

Suggested Citation

  • Bel, K. & Paap, R., 2014. "A Multivariate Model for Multinomial Choices," Econometric Institute Research Papers EI 2014-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:77168
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    References listed on IDEAS

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    1. Hausman, Jerry A & Wise, David A, 1978. "A Conditional Probit Model for Qualitative Choice: Discrete Decisions Recognizing Interdependence and Heterogeneous Preferences," Econometrica, Econometric Society, vol. 46(2), pages 403-426, March.
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    3. Koen Bel & Dennis Fok & Richard Paap, 2018. "Parameter estimation in multivariate logit models with many binary choices," Econometric Reviews, Taylor & Francis Journals, vol. 37(5), pages 534-550, May.
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    7. Geweke, John F. & Keane, Michael P. & Runkle, David E., 1997. "Statistical inference in the multinomial multiperiod probit model," Journal of Econometrics, Elsevier, vol. 80(1), pages 125-165, September.
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    9. Bo E. Honoré & Ekaterini Kyriazidou, 2000. "Panel Data Discrete Choice Models with Lagged Dependent Variables," Econometrica, Econometric Society, vol. 68(4), pages 839-874, July.
    10. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
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    Keywords

    Discrete Choices; Multivariate analysis; Multinomial Logit; Composite Likelihood;
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