Stability of Mixed Logit Parameter Estimation

References

• Amemiya, T. Advanced Econometrics. Harvard University Press, Cambridge, MA. (1985).
   Google Scholar
• Ben-Akiva, M., D. Bolduc and M. Bradley. Estimation of travel model choice models with randomly distributed values of time. Transportation Research Record. No 1413, pp88–97. (1993).
   Google Scholar
• Ben-Akiva, M. and S.R. Lerman. Discrete Choice Analysis: Theory and Application to Travel Demand. MIT Press, Cambridge, MA. (1985).
   Google Scholar
• Bhat, C. Accommodating variations in responsiveness to level-of-service variables in travel model choice models. Transportation Research A. Volume 32, pp455–507. (1998).
   Google Scholar
• Brownstone, D. and K. Train. Forecasting new product penetration with flexible substitution patterns. Journal of Econometrics. Volume 89, pp109–129. (1999).
   Google Scholar
• Bunch, D. Estimability in the multinomial probit model. Transportation Research B. Volume 25, pp1–12. (1991).
   Google Scholar
• Bunch, D. and R. Kitamura. Multinomial Probit Estimation Revisited: Testing New Algorithms and Evaluation of Alternative Model Specification of Household Car Ownership. Transportation Research Group Report UCD-TRG-RR-4. University of California, Davis. (1989).
   Google Scholar
• Dansie, B.R. Parameter estimability in the multinomial probit model. Transportation Research B. Volume 19, No 6, pp526–528. (1985).
   Google Scholar
• Fukuda, D. and S. Morishige. Applicability of improved individual choice models to recreational destination choice behavior. Infrastructure Planning Review. Volume 22, No 2, pp655–658 (Japanese). (1999).
   Google Scholar
• Greene, W.H. Econometric Analysis (fourth ed). Prentice-Hall, Upper Saddle River, NJ. (2000).
   Google Scholar
• Hensher, D.A. and W.H. Greene. The mixed logit model: The state of practice. Transportation. Volume 30, No 2, pp133–176. (2003).
   Google Scholar
• Kitamura, R. and D.S. Bunch. Heterogeneity and state dependence in household car ownership: A panel analysis using ordered-response probit models with error components. In M. Koshi (ed), Transportation and Traffic Theory. pp477- 496. Elsevier, New York (1990).
   Google Scholar
• Liesenfeld, R. and J.-F. Richard. The Multinomial Multiperiod Probit Model: Identification and Efficient Estimation. Economics Working Paper. No 2007- 26. Department of Economics, Christian Albrechts Universität, Kiel. Germany (2007).
   Google Scholar
• Maddala, G.S. Limited-dependent and Qualitative Variables in Econometrics. Cambridge University Press, Cambridge. (1983).
   Google Scholar
• McFadden, D. Conditional logit analysis of qualitative choice behavior. In P. Zarembka (ed). Frontiers in Econometrics. Academic Press. New York (1974).
   Google Scholar
• McFadden, D. and K. Train. Mixed MNL models of discrete response. Journal of Applied Econometrics. Volume 15, pp447–470. (2000).
   Google Scholar
• Shimizu, T., T. Yai and K. Sakai. A study on the similarity among alternatives in railway route choice model. Infrastructure Planning Review. Volume 21, No 1, pp459–460 (Japanese). (1998).
   Google Scholar
• Train, K.E. Discrete Choice Methods with Simulation. Cambridge University Press, Cambridge, MA. (2003).
   Google Scholar
• Train, K.E. Halton Sequences for Mixed Logit. Working paper, Department of Economics, Berkeley. (1999).
   Google Scholar
• Train, K., D. McFadden and M. Ben-Akiva. The demand for local telephone service: A fully discrete model of residential calling patterns and service choice. Rand Journal of Economics. Volume 18, pp109–123. (1987).
   Google Scholar
• Walker, J., M. Ben-Akiva and D. Bolduc. Identification of the logit kernel (or mixed logit) model: dispelling misconceptions of identification. Transportation Research Record. No 1805, pp86–98. (2002).
   Google Scholar
• Weeks, M. The multinomial probit model revisited: A discussion of parameter estimability, identification and specification testing. Journal of Economic Surveys. Volume 11, No 3, pp297–320. (1997).
   Google Scholar