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Deriving willingness-to-pay estimates of travel-time savings from individual-based parameters


  • David A Hensher
  • William H Greene
  • John M Rose


There is a small but growing literature that promotes the derivation of distributions of willingness-to-pay (WTP) estimates using information specific to each individual observation. These are referred to as individual conditional distributions, in contrast to approaches that rely on unconditional distributions that use random assignment in the construction of WTP distributions within a sampled population. The interest in alternative specifications is in large measure attributed to the search for empirical ways of deriving the WTP distribution that satisfies a behaviourally acceptable sign and range over the entire domain. In this paper we examine both conditional and unconditional approaches to establishing WTP distributions within the context of a mixed logit model. We find that calculating WTP measures from ratios of individual-level parameters in contrast to drawing them from unconditional population distributions empirically reduces the incidence of extreme values. Our results suggest that although problematic estimates cannot be ruled out, the use of the extra information on each individual’s choices is a valuable input into the derivation of WTP distributions.

Suggested Citation

  • David A Hensher & William H Greene & John M Rose, 2006. "Deriving willingness-to-pay estimates of travel-time savings from individual-based parameters," Environment and Planning A, Pion Ltd, London, vol. 38(12), pages 2365-2376, December.
  • Handle: RePEc:pio:envira:v:38:y:2006:i:12:p:2365-2376

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    3. Masiero, Lorenzo & Hensher, David A., 2010. "Analyzing loss aversion and diminishing sensitivity in a freight transport stated choice experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 349-358, June.
    4. Campbell, Danny & Sinclair, Victoria, 2008. "Mapping preferences for the restoration of environmental damage caused by illegal dumping," 82nd Annual Conference, March 31 - April 2, 2008, Royal Agricultural College, Cirencester, UK 36772, Agricultural Economics Society.
    5. Meyerhoff, Jürgen, 2013. "Do turbines in the vicinity of respondents' residences influence choices among programmes for future wind power generation?," Journal of choice modelling, Elsevier, vol. 7(C), pages 58-71.
    6. Cooper, Bethany & Rose, John & Crase, Lin, 2012. "Does anybody like water restrictions? Some observation in Australian urban communities," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 56(1), March.
    7. Abildtrup, Jens & Garcia, Serge & Olsen, Søren Bøye & Stenger, Anne, 2013. "Spatial preference heterogeneity in forest recreation," Ecological Economics, Elsevier, vol. 92(C), pages 67-77.
    8. Danny Campbell & Riccardo Scarpa & W. Hutchinson, 2008. "Assessing the spatial dependence of welfare estimates obtained from discrete choice experiments," Letters in Spatial and Resource Sciences, Springer, vol. 1(2), pages 117-126, December.
    9. Sobolewski, Maciej & Kopczewski, Tomasz, 2015. "Measuring reservation prices for bundles of fixed telecommunications services," 26th European Regional ITS Conference, Madrid 2015 127182, International Telecommunications Society (ITS).
    10. Rebecca Owusu Coffie & Michael P. Burton & Fiona L. Gibson & Atakelty Hailu, 2016. "Choice of Rice Production Practices in Ghana: A Comparison of Willingness to Pay and Preference Space Estimates," Journal of Agricultural Economics, Wiley Blackwell, vol. 67(3), pages 799-819, September.

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