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The accuracy of the multinomial logit model as an approximation to the multinomial probit model of travel demand

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  • Horowitz, Joel

Abstract

The multinomial probit model of travel demand is considerably more general but much less tractable than the better-known multinomial logit model. In an effort to determine the effects of using the relatively simple logit model in situations where the assumptions of probit modeling are satisfied but those of logit modeling are not, the accuracy of the multinomial logit model as an approximation to a variety of three-alternative probit models has been evaluated. Multinomial logit can give highly erroneous estimates of the choice probabilities of multinomial probit models. However, logit models appear to give asymptotically accurate estimates of the ratios of the coefficients of the systematic components of probit utility functions, even when the logit choice probabilities differ greatly from the probit ones. Large estimation data sets are not necessarily needed to enable likelihood ratio tests to distinguish three-alternative probit models from logit models that give seriously erroneous estimates of the probit choice probabilities. Inclusion of alternative-specific dummy variables in logit utility functions cannot be relied upon to reduce significantly the errors of logit approximations to the choice probabilities of probit models whose utility functions do not contain the dummies.

Suggested Citation

  • Horowitz, Joel, 1980. "The accuracy of the multinomial logit model as an approximation to the multinomial probit model of travel demand," Transportation Research Part B: Methodological, Elsevier, vol. 14(4), pages 331-341, December.
  • Handle: RePEc:eee:transb:v:14:y:1980:i:4:p:331-341
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    Cited by:

    1. Martine AUDIBERT & Yong HE & Jacky MATHONNAT, 2017. "What does demand heterogeneity tell us about health care provider choice in rural China?," Working Papers P193, FERDI.
    2. Lucey, Brian & Sevic, Aleksandar, 2010. "Investigating the determinants of banking coexceedances in Europe in the summer of 2008," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(3), pages 275-283, July.
    3. Fischer, M.M. & Nijkamp, P., 1985. "Explanatory discrete spatial data and choice analysis : a state-of-the-art review," Serie Research Memoranda 0006, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    4. Martine Audibert & Yong He & Jacky Mathonnat, 2013. "Multinomial and Mixed Logit Modeling in the Presence of Heterogeneity: A Two-Period Comparison of Healthcare Provider Choice in Rural China," Working Papers halshs-00846085, HAL.
    5. Martine Audibert & Yong He & Jacky Mathonnat, 2020. "Dealing with Demand Heterogeneity on Health Care Provider Choice – The Case of Rural China," Asian Journal of Economics and Empirical Research, Asian Online Journal Publishing Group, vol. 7(2), pages 258-267.
    6. Van Asselt, Joanna & Nian, Yefan & Soh, Moonwon & Morgan, Stephen & Gao, Zhifeng, 2022. "Do plastic warning labels reduce consumers' willingness to pay for plastic egg packaging? – Evidence from a choice experiment," Ecological Economics, Elsevier, vol. 198(C).
    7. Martine AUDIBERT & Yong HE & Jacky MATHONNAT, 2017. "What does demand heterogeneity tell us about health care provider choice in rural China?," Working Papers P193, FERDI.
    8. Martine Audibert & Yong He & Jacky Mathonnat, 2020. "Dealing with Demand Heterogeneity on Health Care Provider Choice –The Case of Rural China," Post-Print halshs-02963761, HAL.
    9. Bunch, David S. & Kitamura, Ryuichi, 1991. "Probit Model Estimation Revisited: Trinomial Models of Household Car Ownership," University of California Transportation Center, Working Papers qt2hr8d4bs, University of California Transportation Center.
    10. Alessandro Lomi, 1993. "A semiparametric random effects approach to unobserved heterogeneity in count data models of organizational founding," Quality & Quantity: International Journal of Methodology, Springer, vol. 27(2), pages 139-155, May.
    11. W C Halperin & G D Richardson & N Gale & C M Costanzo, 1984. "A Generalized Procedure for Comparing Models of Spatial Choice," Environment and Planning A, , vol. 16(10), pages 1289-1301, October.

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