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

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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)

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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.

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Publisher Info
Paper provided by CIRJE, Faculty of Economics, University of Tokyo in its series CIRJE F-Series with number CIRJE-F-193.

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Length: 21 pages
Date of creation: Feb 2003
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Handle: RePEc:tky:fseres:2003cf193

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  1. J. P. Nielsen & O. B. Linton, . "An Optimization Interpretation of Integration and Backfitting Estimators for Separable Nonparametric Models," Sonderforschungsbereich 373 1996-88, Humboldt Universitaet Berlin.
  2. Hausman, Jerry & McFadden, Daniel, 1984. "Specification Tests for the Multinomial Logit Model," Econometrica, Econometric Society, vol. 52(5), pages 1219-40, September. [Downloadable!] (restricted)
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  3. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September. [Downloadable!] (restricted)
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  4. Abe, Makoto, 1999. "A Generalized Additive Model for Discrete-Choice Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 271-84, July.
  5. McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240. [Downloadable!] (restricted)
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  1. Thomas Kneib & Bernhard Baumgartner & Winfried Steiner, 2007. "Semiparametric multinomial logit models for analysing consumer choice behaviour," AStA Advances in Statistical Analysis, Springer, vol. 91(3), pages 225-244, October. [Downloadable!] (restricted)
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