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Using values of travel time savings for toll roads: avoiding some common errors

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  • Hensher, David A.
  • Goodwin, Phil

Abstract

There are many empirical studies on the estimation of values of travel time savings (VTTS), with varying degrees of rigour and relevance, mostly based on the observation that travellers are prepared to spend money to save time. These values are applied to both forecasting the effects of speed changes on behaviour and also for estimation of the social benefit of such savings, in order to calculate value for money of spending public funds on transport investments. The sources of empirical information on such values are not always compatible with the models and software within which the results are used. In recent years, an increasingly important application has been to calculate the potential revenue from tolled roads, and networks with user charges, which offer high speeds at a higher price: here the important issue is not hypothetical willingness to pay, but the actual money that will be handed over. This changes the focus from hypothetical to bankable VTTS. It is shown that some common practices risk substantial error in calculation, affecting the sharing of risk between public and private sectors. A particularly important case is where an average value is taken as representative of a skewed distribution of values--in these circumstances there will be a tendency to overestimate the revenue, and underestimate the traffic impact, of a charge, because for a given mean VTTS, there will be a smaller number of individuals who are prepared to pay the toll. To correct this bias, the main tasks are: establishing a relevant set of trip-purpose specific VTTS distributions and selecting a way of handling the distributions in patronage forecasting, growing VTTS through time, treating the VTTS of car passengers, and establishing an appropriate set of rules for converting disaggregated (or heterogeneous) components of travel time values into a single trip value appropriate to the project being evaluated. Other related problems of the use of values of time relate to the assumption that these values grow in proportion to income, and the extent to which they are confounded with other effects. One troublesome feature is that most, and perhaps all, of the problems discussed tend to produce biases in the same direction, namely to risk overestimating revenue, in the short and long run. This produces a tendency to appraisal bias, which can distort the contractual confidence between partners. Overall, it is likely that current assumptions are underestimating the degree of toll-avoiding behaviour, and overestimating the financial viability of projects.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:trapol:v:11:y:2004:i:2:p:171-181
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    References listed on IDEAS

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    1. Trujillo, Lourdes & Quinet, Emile & Estache, Antonio, 2002. "Dealing with demand forecasting games in transport privatization," Transport Policy, Elsevier, vol. 9(4), pages 325-334, October.
    2. David A. Hensher, 2001. "Measurement of the Valuation of Travel Time Savings," Journal of Transport Economics and Policy, University of Bath, vol. 35(1), pages 71-98, January.
    3. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
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    Cited by:

    1. 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.
    2. Georgina Santos & Erik Verhoef, 2011. "Road Congestion Pricing," Chapters,in: A Handbook of Transport Economics, chapter 23 Edward Elgar Publishing.
    3. Li, Zheng & Hensher, David A., 2012. "Estimating values of travel time savings for toll roads: Avoiding a common error," Transport Policy, Elsevier, vol. 24(C), pages 60-66.
    4. Nakamura, Akihiro & Shishikura, Manabu & Kasuga, Norihiro & Jitsuzumi, Toshiya & Koguchi, Teppei, 2017. "Demand Analysis for Real-Time and Time-Shifted Viewing in the Japanese TV Market," 14th ITS Asia-Pacific Regional Conference, Kyoto 2017: Mapping ICT into Transformation for the Next Information Society 168521, International Telecommunications Society (ITS).
    5. Santos, Georgina & Behrendt, Hannah & Maconi, Laura & Shirvani, Tara & Teytelboym, Alexander, 2010. "Part I: Externalities and economic policies in road transport," Research in Transportation Economics, Elsevier, vol. 28(1), pages 2-45.
    6. Raux, Charles & Souche, Stéphanie & Pons, Damien, 2012. "The efficiency of congestion charging: Some lessons from cost–benefit analyses," Research in Transportation Economics, Elsevier, vol. 36(1), pages 85-92.
    7. Lindsey, Robin & de Palma, André, 2014. "Cost recovery from congestion tolls with long-run uncertainty," Economics of Transportation, Elsevier, vol. 3(2), pages 119-132.
    8. repec:eee:transa:v:105:y:2017:i:c:p:79-94 is not listed on IDEAS
    9. Thor-Erik Hanssen, 2012. "The influence of interview location on the value of travel time savings," Transportation, Springer, vol. 39(6), pages 1133-1145, November.
    10. Sen Gupta, Rajorshi & Vadali, Sharada R, 2007. "Stochastic Dominance Approach to Evaluate Optimism Bias in Truck Toll Forecasts," MPRA Paper 12891, University Library of Munich, Germany, revised 2008.
    11. Brenck, Andreas & Beckers, Thorsten & Heinrich, Maria & von Hirschhausen, Christian, 2005. "Public-private partnerships in new EU member countries of Central and Eastern Europe: An economic analysis with case studies from the highway sector," EIB Papers 10/2005, European Investment Bank, Economics Department.
    12. Savage, Ian, 2010. "The dynamics of fare and frequency choice in urban transit," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(10), pages 815-829, December.
    13. Hensher, David A. & Greene, William H. & Li, Zheng, 2011. "Embedding risk attitude and decision weights in non-linear logit to accommodate time variability in the value of expected travel time savings," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 954-972, August.
    14. Rotaris, Lucia & Danielis, Romeo & Marcucci, Edoardo & Massiani, Jérôme, 2010. "The urban road pricing scheme to curb pollution in Milan, Italy: Description, impacts and preliminary cost-benefit analysis assessment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 359-375, June.
    15. Santos, Georgina & Bhakar, Jasvinder, 2006. "The impact of the London congestion charging scheme on the generalised cost of car commuters to the city of London from a value of travel time savings perspective," Transport Policy, Elsevier, vol. 13(1), pages 22-33, January.
    16. Athias, Laure & Nunez, Antonio, 2008. "The more the merrier? Number of bidders, information dispersion, renegotiation and winner’s curse in toll road concessions," MPRA Paper 10539, University Library of Munich, Germany.
    17. Swärdh, Jan-Erik, 2008. "Is the intertemporal income elasticity of the value of travel time unity?," Working Papers 2008:3, Swedish National Road & Transport Research Institute (VTI).

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