Specification Of A Model To Measure - The Value Of Travel Time Savings From Binomial Data
This paper develops a semiparametric methodology for the evaluation of the distribution of the value of travel time savings (VTTS) from binary choice data. Fosgerau (2004) deals with the case of just one time component. This paper extends to the case of several time components. The methodology is applied to a recent large dataset of about 2200 car drivers who undertook a series of stated choice experiments. The VTTS is a fundamental concept in transport economics, being the main yardstick against which transport investments are measured. However, the methodology presented is generally applicable to evaluation of willingness to pay from binary choice data. Current standard-of-practice methodology applies a mixing distribution to a binary choice model in order to take account of individual heterogeneity. While this is definitely progress, there remains the problem of deciding which mixing distribution to apply. This problem is avoided here by using a nonparametric distribution. For prediction of choices, the choice of mixing distribution may matter less but it is absolutely crucial for evaluating willingness to pay. Even so, it is rare to see a justification for the choice of mixing distribution. The paper tests a range of parametric distributions against the semiparametric alternative.
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- 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.
- 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.
- 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 & 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.
- 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.
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