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Covariance heterogeneity in nested logit models: Econometric structure and application to intercity travel

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  • Bhat, Chandra R.
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    Abstract

    The nested logit model relaxes the 'independence of irrelevant alternatives' (IIA) property of the multinomial logit model by grouping alternatives based on their degree of substitution. Alternatives in a nest exhibit an identical degree of increased sensitivity relative to alternatives not in the nest. An assumption maintained in the nested logit is that the degree of sensitivity among nested alternatives is invariant across agents making the choice. This assumption might be untenable in many situations. In this paper, we propose an extension of the nested logit model to allow heterogeneity (across agents) in the covariance among nested alternatives based on observed agent characteristics. We label this model as the COVNL model. The multinomial logit, the nested logit, and the COVNL model are estimated to examine the impact of improved rail service on weekday, business travel in the Toronto-Montreal corridor. The empirical results show that not accounting for covariance heterogeneity in the nested logit formulation leads to a statistically inferior data fit and also to biased model estimates of the effects of level-of-service variables.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

    Volume (Year): 31 (1997)
    Issue (Month): 1 (February)
    Pages: 11-21

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    Handle: RePEc:eee:transb:v:31:y:1997:i:1:p:11-21

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    1. Jain, Dipak C & Vilcassim, Naufel J & Chintagunta, Pradeep K, 1994. "A Random-Coefficients Logit Brand-Choice Model Applied to Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 317-28, July.
    2. Hausman, Jerry & McFadden, Daniel, 1984. "Specification Tests for the Multinomial Logit Model," Econometrica, Econometric Society, vol. 52(5), pages 1219-40, September.
    3. Vassilis A. Hajivassiliou & Axel Borsch-Supan, 1990. "Smooth Unbiased Multivariate Probability Simulators for Maximum Likelihood Estimation of Limited Dependent Variable Models," Cowles Foundation Discussion Papers 960, Cowles Foundation for Research in Economics, Yale University.
    4. Horowitz, Joel L., 1991. "Reconsidering the multinomial probit model," Transportation Research Part B: Methodological, Elsevier, vol. 25(6), pages 433-438, December.
    5. Manski, Charles F & Lerman, Steven R, 1977. "The Estimation of Choice Probabilities from Choice Based Samples," Econometrica, Econometric Society, vol. 45(8), pages 1977-88, November.
    6. Brownstone, David & Small, Kenneth A, 1989. "Efficient Estimation of Nested Logit Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(1), pages 67-74, January.
    7. Chamberlain, Gary, 1980. "Analysis of Covariance with Qualitative Data," Review of Economic Studies, Wiley Blackwell, vol. 47(1), pages 225-38, January.
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    Cited by:
    1. Christiaan Behrens & Eric Pels, 2009. "Intermodal Competition in The London-Paris Passenger Market: High-Speed Rail and Air Transport," Tinbergen Institute Discussion Papers 09-051/3, Tinbergen Institute.
    2. Behrens, Christiaan & Pels, Eric, 2012. "Intermodal competition in the London–Paris passenger market: High-Speed Rail and air transport," Journal of Urban Economics, Elsevier, vol. 71(3), pages 278-288.
    3. Fosgerau, Mogens & Bierlaire, Michel, 2007. "Circumventing the problem of the scale: discrete choice models with multiplicative error terms," MPRA Paper 3901, University Library of Munich, Germany.
    4. Li, Baibing, 2011. "The multinomial logit model revisited: A semi-parametric approach in discrete choice analysis," Transportation Research Part B: Methodological, Elsevier, vol. 45(3), pages 461-473, March.
    5. Fosgerau, M. & Bierlaire, M., 2009. "Discrete choice models with multiplicative error terms," Transportation Research Part B: Methodological, Elsevier, vol. 43(5), pages 494-505, June.
    6. Michael Scheidler & Reinhard Hujer & Joachim Grammig, 2005. "Discrete choice modelling in airline network management," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 467-486.
    7. Kim, Sooil & Haab, Timothy C., 2005. "Generalized Estimation Methods for Non-i.i.d. Binary Data: An Application to Dichotomous Choice Contingent Valuation," 2005 Annual meeting, July 24-27, Providence, RI 19138, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    8. Colombo, Sergio & Hanley, Nicholas & Louviere, Jordan, 2008. "Modelling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture," Stirling Economics Discussion Papers 2008-28, University of Stirling, Division of Economics.
    9. F Alpizar & F Carlsson & P Martinsson, 2003. "Using Choice Experiments for Non-Market Valuation," Economic Issues Journal Articles, Economic Issues, vol. 8(1), pages 83-110, March.
    10. Wen, Chieh-Hua & Koppelman, Frank S., 2001. "The generalized nested logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 627-641, August.
    11. GRAMMIG, Joachim & HUJER, Reinhard & SCHEIDLER, Michael, 2001. "The econometrics of airline network management," CORE Discussion Papers 2001055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Su, Qing & Zhou, Liren, 2012. "Parking management, financial subsidies to alternatives to drive alone and commute mode choices in Seattle," Regional Science and Urban Economics, Elsevier, vol. 42(1-2), pages 88-97.
    13. Edoardo Marcucci & Valerio Gatta, 2011. "Dissecting Preference Heterogeneity In Consumer Stated Choices," Working Papers 0311, CREI UniversitĂ  degli Studi Roma Tre, revised 2011.

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