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Long distance mode choice and distributions of values of travel time savings in three European countries

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  • de Lapparent, M.,
  • Axhausen , K.W.
  • Frei, A.

Abstract

The study presented in this paper uses Stated Preferences (SP) data on mode choice collected as part of a recent survey on long distance travel undertaken in three European countries. The purpose of this article is twofold. It aims at exploring the impacts of the choice of mixing probability distributions while accounting for unobserved taste heterogeneity and it aims at focusing on the derived estimation of the distributions of values of travel time savings (VTTS). We compare eleven distributions, each having particular properties in terms of domain, location, scale, and shape. Due to the repetitive nature of the SP experiments, we estimate mixtures of Multinomial Logit (MNL) models for panel data. The results show that the mixing distributions differ from one country to another, suggesting existence of European disparities as it regards long-distance mode choice. The results also show that long-distance travellers pay a lot more attention to access and egress travel times to and from the main mode than to total travel time with the main mode.

Suggested Citation

  • de Lapparent, M., & Axhausen , K.W. & Frei, A., 2013. "Long distance mode choice and distributions of values of travel time savings in three European countries," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 53, pages 1-7.
  • Handle: RePEc:sot:journl:y:2013:i:53:p:1
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    File URL: https://www.openstarts.units.it/dspace/handle/10077/8687
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    1. McFadden, Daniel & Ruud, Paul A, 1994. "Estimation by Simulation," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 591-608, November.
    2. Fosgerau, Mogens, 2006. "Investigating the distribution of the value of travel time savings," Transportation Research Part B: Methodological, Elsevier, vol. 40(8), pages 688-707, September.
    3. Kenneth Train ., 2000. "Halton Sequences for Mixed Logit," Economics Working Papers E00-278, University of California at Berkeley.
    4. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    5. Hess, Stephane, 2007. "Posterior analysis of random taste coefficients in air travel behaviour modelling," Journal of Air Transport Management, Elsevier, vol. 13(4), pages 203-212.
    6. Joan L. Walker & Moshe Ben-Akiva & Denis Bolduc, 2007. "Identification of parameters in normal error component logit-mixture (NECLM) models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(6), pages 1095-1125.
    7. Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, vol. 57(5), pages 1027-1057, September.
    8. Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
    9. Bhat, Chandra R., 2003. "Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences," Transportation Research Part B: Methodological, Elsevier, vol. 37(9), pages 837-855, November.
    10. Lee, Lung-Fei, 1995. "Asymptotic Bias in Simulated Maximum Likelihood Estimation of Discrete Choice Models," Econometric Theory, Cambridge University Press, vol. 11(3), pages 437-483, June.
    11. Mackie, P.J. & Jara-Díaz, S. & Fowkes, A.S., 0. "The value of travel time savings in evaluation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 37(2-3), pages 91-106, April.
    12. V A Hajivassiliou, 1997. "Some Practical Issues in Maximum Simulated Likelihood," STICERD - Econometrics Paper Series 340, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    13. David Hensher, 2006. "The Signs of the Times: Imposing a Globally Signed Condition on Willingness to Pay Distributions," Transportation, Springer, vol. 33(3), pages 205-222, May.
    14. Fosgerau, Mogens & Hess, Stephane, 2008. "Competing methods for representing random taste heterogeneity in discrete choice models," MPRA Paper 10038, University Library of Munich, Germany.
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    Cited by:

    1. Arbués, Pelayo & Baños, José F. & Mayor, Matías & Suárez, Patricia, 2016. "Determinants of ground transport modal choice in long-distance trips in Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 84(C), pages 131-143.
    2. Bouscasse, Hélène & de Lapparent, Matthieu, 2019. "Perceived comfort and values of travel time savings in the Rhône-Alpes Region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 370-387.

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