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Investigating the distribution of the value of travel time savings

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  • Mogens Fosgerau

    (Danish Transport Research Institute)

Abstract

The distribution of the value of travel time savings (VTTS) is investigated employing various nonparametric techniques on a large, high quality data set. When background variables are not included in the model it is found that the right 13% tail of the distribution is not observed and hence the mean VTTS cannot be evaluated. This conclusion changes when background variables are introduced into a semiparametric model. A partially constrained Johnson SB distribution allowing evaluation of the mean VTTS is accepted against the nonparametric alternative and is preferred among 16 candidates for parametric VTTS distributions. The resulting mean VTTS is plausible but three times larger than the mean VTTS evaluated from a simple logit model and half as big as that arising from a model assuming a lognormal distribution for the VTTS. Such findings indicate the importance of properly accounting for the distribution when estimating the mean VTTS. The present findings may be used to guide the choice of mixing distribution in a mixed logit model.

Suggested Citation

  • Mogens Fosgerau, 2004. "Investigating the distribution of the value of travel time savings," Urban/Regional 0411006, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpur:0411006
    Note: Type of Document - pdf; pages: 37. Replaces earlier paper: Nonparametric and semiparametric estimation of the distribution of the value of travel time savings
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/urb/papers/0411/0411006.pdf
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    value of travel time savings; time; transport; VTTS; distribution; nonparametric; semiparametric; Klein-Spady; Zheng; Johnson SB; lognormal;

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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