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Mixed Logit Estimation of the Value of Travel Time

  • Algers, Staffan

    (Royal Institute of Technology)

  • Bergström, Pål

    (Trade och Capital Markets)

  • Dahlberg, Matz

    ()

    (Department of Economics)

  • Lindqvist Dillén, Johanna

    ()

    (Royal Institute of Technology, Stockholm)

In this paper we use mixed logit specifications to allow parameters to vary in the population when estimating the value of time for long-distance car travel. Our main conclusion is that the estimated value of time is very sensitive to how the model is specified: we find that it is significantly lower when the coefficients are assumed to be normally distributed in the population, as compared to the traditional case when they are treated as fixed. In our most richly parameterised model, we find a median value of time of 57 SEK per hour, with the major part of the mass of the value of time distribution closely centred around the median value. The corresponding figure when the parameters are treated as fixed is 89 SEK per hour. Furthermore, our finding that the ratio of coefficients in a mixed logit specification differ significantly from the ones in a traditional logit specification is contrary to the results obtained by Brownstone & Train (1996) and Train (1997). Whether the ratios will differ or not depends on the model and the data generating process at hand.

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Paper provided by Uppsala University, Department of Economics in its series Working Paper Series with number 1998:15.

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Length: 33 pages
Date of creation: 07 Aug 1998
Date of revision:
Handle: RePEc:hhs:uunewp:1998_015
Contact details of provider: Postal: Department of Economics, Uppsala University, P. O. Box 513, SE-751 20 Uppsala, Sweden
Phone: + 46 18 471 25 00
Fax: + 46 18 471 14 78
Web page: http://www.nek.uu.se/
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  1. Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January.
  2. Borsch-Supan, Axel & Hajivassiliou, Vassilis A., 1993. "Smooth unbiased multivariate probability simulators for maximum likelihood estimation of limited dependent variable models," Journal of Econometrics, Elsevier, vol. 58(3), pages 347-368, August.
  3. Hajivassiliou, Vassilis A. & Ruud, Paul A., 1986. "Classical estimation methods for LDV models using simulation," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 40, pages 2383-2441 Elsevier.
  4. McFadden, Daniel & Ruud, Paul A, 1994. "Estimation by Simulation," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 591-608, November.
  5. Vassilis A. Hajivassiliou & Daniel L. McFadden & Paul Ruud, 1993. "Simulation of Multivariate Normal Rectangle Probabilities and their Derivatives: Theoretical and Computational Results," Working Papers _024, Yale University.
  6. Axel Borsch-Supan & Vassilis Hajivassiliou & Laurence J. Kotlikoff & John N. Morris, 1990. "Health, Children, and Elderly Living Arrangements: A Multiperiod-Multinomial Probit Model with Unobserved Heterogeneity and Autocorrelated Errors," NBER Working Papers 3343, National Bureau of Economic Research, Inc.
  7. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
  8. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
  9. Daniel McFadden, 1977. "Modelling the Choice of Residential Location," Cowles Foundation Discussion Papers 477, Cowles Foundation for Research in Economics, Yale University.
  10. Ben-Akiva, M. & Bolduc, D. & Bradley, M., 1993. "Estimation of Travel Choice Models with Randomly Distributed Values of Time," Papers 9303, Laval - Recherche en Energie.
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