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The multinomial logit model revisited: a semi-parametric approach in discrete choice analysis

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journal contribution
posted on 19.12.2011, 13:59 by Baibing LiBaibing Li
The multinomial logit model in discrete choice analysis is widely used in transport research. It has long been known that the Gumbel distribution forms the basis of the multinomial logit model. Although the Gumbel distribution is a good approximation in some applications such as route choice problems, it is chosen mainly for mathematical convenience. This can be restrictive in many other scenarios in practice. In this paper we show that the assumption of the Gumbel distribution can be substantially relaxed to include a large class of distributions that is stable with respect to the minimum operation. The distributions in the class allow heteroscedastic variances. We then seek a transformation that stabilizes the heteroscedastic variances. We show that this leads to a semi-parametric choice model which links the linear combination of travel-related attributes to the choice probabilities via an unknown sensitivity function. This sensitivity function reflects the degree of travelers’ sensitivity to the changes in the combined travel cost. The estimation of the semi-parametric choice model is also investigated and empirical studies are used to illustrate the developed method.

History

School

  • Business and Economics

Department

  • Business

Citation

LI, B., 2011. The multinomial logit model revisited: a semi-parametric approach in discrete choice analysis. Transportation Research Part B: Methodological, 45 (3), pp. p.461 - 473

Publisher

© Elsevier

Version

AM (Accepted Manuscript)

Publication date

2011

Notes

This article was published in the journal, Transportation Research Part B: Methodological [© Elsevier]. The definitive version is available at: http://www.sciencedirect.com/science/article/pii/S0191261510001190

ISSN

0191-2615

Language

en