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Investigating the Competitive Assumption of Multinomial Logit Models of Brand Choice by Nonparametric Modeling

Author

Listed:
  • Makoto Abe

    (Faculty of Economics, University of Tokyo)

  • Yasemin Boztug

    (Institute of Marketing, Humboldt University of Berlin)

  • Lutz Hildebrandt

    (Institute of Marketing, Humboldt University of Berlin)

Abstract

The Multinomial Logit (MNL) model is still the only viable option to study nonlinear responsiveness of utility to covariates nonparametrically. This research investigates whether MNL structure of inter-brand competition is a reasonable assumption, so that when the utility function is estimated nonparametrically, the IIA assumption does not bias the result. For this purpose, the authors compare the performance of two comparable nonpara-metric choice models that differ in one aspect: one assumes MNL com-petitive structure and the other infers the pattern of brands' competition nonparametrically from data.

Suggested Citation

  • Makoto Abe & Yasemin Boztug & Lutz Hildebrandt, 2003. "Investigating the Competitive Assumption of Multinomial Logit Models of Brand Choice by Nonparametric Modeling," CIRJE F-Series CIRJE-F-193, CIRJE, Faculty of Economics, University of Tokyo.
    • Handle: RePEc:tky:fseres:2003cf193
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    References listed on IDEAS

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    Cited by:

    1. Thomas Kneib & Bernhard Baumgartner & Winfried Steiner, 2007. "Semiparametric multinomial logit models for analysing consumer choice behaviour," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 91(3), pages 225-244, October.
    2. Guhl, Daniel & Baumgartner, Bernhard & Kneib, Thomas & Steiner, Winfried J., 2018. "Estimating time-varying parameters in brand choice models: A semiparametric approach," International Journal of Research in Marketing, Elsevier, vol. 35(3), pages 394-414.

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