Investigating the distribution of the value of travel time savings
The distribution of the value of travel time savings (VTTS) is investigated employing various nonparametric techniques to a large dataset originating from a stated choice experiment. The data contain choices between a fast and more expensive alternative and a slow and less expensive alternative. Increasing the implicit price of time leads to an increased share of respondents who decline to pay to save time. But a significant proportion of respondents, 13%, remain willing to pay to save time at the highest price of time in the design. This means that the right tail of the VTTS distribution is not observed and hence the mean VTTS cannot be evaluated without additional assumptions. When socio-economic and situational variables are introduced into a semiparametric model it becomes possible to accept that the whole VTTS distribution is observed. Sixteen candidates for parametric VTTS distributions are investigated. Some distributions are simply not able to fit to the empirical distribution while others have very long tails. The mean VTTS is shown to be extremely dependent on the choice of parametric distribution. Requiring that the parametric distribution should be accepted against the nonparametric alternative narrows the field down to five candidates. One of the distributions tested here has also support within the observed range such that the estimated VTTS is bounded by the data.
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- Hensher, David A. & Goodwin, Phil, 2004. "Using values of travel time savings for toll roads: avoiding some common errors," Transport Policy, Elsevier, vol. 11(2), pages 171-181, April.
- Hess, Stephane & Bierlaire, Michel & Polak, John W., 2005. "Estimation of value of travel-time savings using mixed logit models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 221-236.
- Arthur Lewbel & Daniel McFadden & Oliver Linton, 1997.
"Estimating Features of a Distribution from Binomial Data,"
Boston College Working Papers in Economics
442, Boston College Department of Economics, revised 01 Jul 2010.
- Lewbel, Arthur & McFadden, Daniel & Linton, Oliver, 2011. "Estimating features of a distribution from binomial data," Journal of Econometrics, Elsevier, vol. 162(2), pages 170-188, June.
- Arthur Lewbel & Oliver Linton & D. L. McFadden, 2006. "Estimating features of a distribution from binomial data," LSE Research Online Documents on Economics 4418, London School of Economics and Political Science, LSE Library.
- Arthur Lewbel & Oliver Linton & Daniel McFadden, 2001. "Estimating features of a distribution from binomial data," CeMMAP working papers CWP07/01, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Mogens Fosgerau, 2005. "Unit income elasticity of the value of travel time savings," Urban/Regional 0508007, EconWPA.
- Ruud H Koning & Geert Ridder, 1999.
"Discrete Choice and Stochastic Utility Maximization,"
Economics Working Paper Archive
413, The Johns Hopkins University,Department of Economics.
- Ruud H. Koning & Geert Ridder, 2003. "Discrete choice and stochastic utility maximization," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 1-27, 06.
- Lars Hultkrantz & Reza Mortazavi, 2001. "Anomalies in the Value of Travel-Time Changes," Journal of Transport Economics and Policy, London School of Economics and University of Bath, vol. 35(2), pages 285-299, May.
- Kenneth Train, 2003. "Discrete Choice Methods with Simulation," Online economics textbooks, SUNY-Oswego, Department of Economics, number emetr2, December.
- Lee, Lung-fei, 1995. "Semiparametric maximum likelihood estimation of polychotomous and sequential choice models," Journal of Econometrics, Elsevier, vol. 65(2), pages 381-428, February.
- Klein, Roger W & Spady, Richard H, 1993.
"An Efficient Semiparametric Estimator for Binary Response Models,"
Econometric Society, vol. 61(2), pages 387-421, March.
- Klein, R.W. & Spady, R.H., 1991. "An Efficient Semiparametric Estimator for Binary Response Models," Papers 70, Bell Communications - Economic Research Group.
- Walter Beckert, 2007. "Specification and Identification of Stochastic Demand Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(6), pages 669-683.
- John Xu Zheng, 1996. "A consistent test of functional form via nonparametric estimation techniques," Journal of Econometrics, Elsevier, vol. 75(2), pages 263-289, December.
- David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
- Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
- David A. Hensher, 2001. "Measurement of the Valuation of Travel Time Savings," Journal of Transport Economics and Policy, London School of Economics and University of Bath, vol. 35(1), pages 71-98, January.
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