Fosgerau, Mogens and Bierlaire, Michel (2007): Circumventing the problem of the scale: discrete choice models with multiplicative error terms.
Download (328kB) | Preview
We propose a multiplicative specification of a discrete choice model that renders choice probabilities independent of the scale of the utility. The scale can thus be random with unspecified distribution. The model mostly outperforms the classical additive formulation over a range of stated choice data sets. In some cases, the improvement in likelihood is greater than that obtained from adding observed and unobserved heterogeneity to the additive specification. The multiplicative specification makes it unnecessary to capture scale heterogeneity and, consequently, yields a significant potential for reducing model complexity in the presence of heteroscedasticity. Thus the proposed multiplicative formulation should be a useful supplement to the techniques available for the analysis of discrete choices. There is however a cost to be paid in terms of increased analytical complexity relative to the additive formulations.
|Item Type:||MPRA Paper|
|Institution:||Technical University of Denmark|
|Original Title:||Circumventing the problem of the scale: discrete choice models with multiplicative error terms|
|Keywords:||Multivariate extreme value; logsum|
|Subjects:||C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C25 - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions|
|Depositing User:||Mogens Fosgerau|
|Date Deposited:||08. Jul 2007|
|Last Modified:||02. Mar 2013 04:24|
Ben-Akiva, M. E. and Lerman, S. R. (1985). Discrete Choice Analysis: Theory and Application to Travel Demand, MIT Press, Cambridge,Ma. Bhat, C. R. (1997). Covariance heterogeneity in nested logit models: econometric structure and application to intercity travel, Transportation Research Part B: Methodological 31(1): 11-21. Bierlaire, M. (2003). BIOGEME: a free package for the estimation of discrete choice models, Proceedings of the 3rd Swiss Transportation Research Conference, Ascona, Switzerland. www.strc.ch. Bierlaire, M. (2005). An introduction to BIOGEME version 1.4. biogeme.ep.ch. Bierlaire, M., Axhausen, K. and Abay, G. (2001). Acceptance of modal innovation: the case of the Swissmetro, Proceedings of the 1st Swiss Transportation Research Conference, Ascona, Switzerland. www.strc.ch. Caussade, S., Ortuzar, J., Rizzi, L. I. and Hensher, D. A. (2005). Assessing the influence of design dimensions on stated choice experiment estimates, Transportation Research Part B: Methodological 39(7): 621-640. Daly, A. and Bierlaire, M. (2006). A general and operational representation of generalised extreme value models, Transportation Research Part B: Methodological 40(4): 285-305. De Shazo, J. and Fermo, G. (2002). Designing choice sets for stated preference methods: the effects of complexity on choice consistency, Journal of Environmental Economics and Management 44: 123-143. Fosgerau, M. (2006). Investigating the distribution of the value of travel time savings, Transportation Research Part B: Methodological 40(8): 688-707. Fosgerau, M. (forthcoming). Using nonparametrics to specify a model to measure the value of travel time, Transportation Research Part A . Fosgerau, M. and Bierlaire, M. (2006). Discrete choice models with multiplicative error terms, Technical Report TRANSP-OR 060831, Transport and Mobility Laboratory, Ecole Polytechnique Federale de Lausanne. Jenkinson, A. F. (1955). Frequency distribution of the anjual maximum (or minimum) values of meteorological elements, Quarterly journal of the Royal Meteorological Society 81: 158-171. Koenig, A., Abay, G. and Axhausen, K. (2003). Time is money: the valuation of travel time savings in switzerland, Proceedings of the 3rd Swiss Transportation Research Conference. http://www.strc.ch/Paper/Koenig.pdf. Koppelman, F. and Sethi, V. (2005). Incorporating variance and covariance heterogeneity in the generalized nested logit model: an application to modeling long distance travel choice behavior, Transportation Research Part B: Methodological 39(9): 825-853. McFadden, D. (1978). Modelling the choice of residential location, in A. Karlquist et al. (ed.), Spatial interaction theory and residential location, North-Holland, Amsterdam, pp. 75-96. McFadden, D. and Train, K. (2000). Mixed MNL models for discrete response, Journal of Applied Econometrics 15(5): 447-470. McFadden, D. L. (2000). Disaggregate behavioral travel demand's RUM side: a 30-year retrospective, International Association for Travel Behaviour Conference, Gold Coast, Queensland. Small, K. A. and Rosen, H. S. (1981). Applied welfare economics with discrete choice models, Econometrica 49(1): 105-130. Swait, J. and Adamowicz, W. (2001). Choice environment, market complexity, and consumer behavior: a theoretical and empirical approach for incorporating decision complexity into models of consumer choice, Organizational Behavior and Human Decision Processes 86(2): 141-167. Train, K. and Weeks, M. (2005). Discrete choice models in preference space and willingness-to-pay space, in R. Scarpa and A. Alberini (eds), Applications of simulation methods in environmental and resource economics, The Economics of Non-Market Goods and Resources, Springer, pp. 1-16.
Available Versions of this Item
- Circumventing the problem of the scale: discrete choice models with multiplicative error terms. (deposited 08. Jul 2007) [Currently Displayed]