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Value of travel time changes: Theory and simulation to understand the connection between Random Valuation and Random Utility methods

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  • Ojeda-Cabral, Manuel
  • Chorus, Caspar G.

Abstract

This paper identifies and illustrates the theoretical connection between the Random Valuation (RV) and Random Utility (RU) methods for Value of Travel Time Changes (VTTC) analysis. The RV method has become more and more popular recently, and has been found to lead to very different estimation results than conventional RU models. Previous studies have reported these differences but did not explain them, which limited the confidence in the RV model as a useful foundation for transport policy analysis. In this paper, we first analytically show in what way exactly the two models are different and why they may generate different estimation results. Based on this deeper understanding of the connection and difference between the two models, we formulate hypotheses regarding the conditions under which differences in estimation results are expected to be smaller or larger. Using synthetic data, we empirically test these expectations. Results provide strong support for our hypotheses, allowing us to derive a number of practical recommendations for analysts interested in using the RV and RU models in their VTTC-analysis.

Suggested Citation

  • Ojeda-Cabral, Manuel & Chorus, Caspar G., 2016. "Value of travel time changes: Theory and simulation to understand the connection between Random Valuation and Random Utility methods," Transport Policy, Elsevier, vol. 48(C), pages 139-145.
    • Handle: RePEc:eee:trapol:v:48:y:2016:i:c:p:139-145
    DOI: 10.1016/j.tranpol.2016.03.006
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    References listed on IDEAS

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    1. Fosgerau, Mogens, 2007. "Using nonparametrics to specify a model to measure the value of travel time," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(9), pages 842-856, November.
    2. Börjesson, Maria & Eliasson, Jonas, 2014. "Experiences from the Swedish Value of Time study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 144-158.
    3. Fosgerau, Mogens & Hjort, Katrine & Vincent Lyk-Jensen, Stéphanie, 2007. "An approach to the estimation of the distribution of marginal valuations from discrete choice data," MPRA Paper 3907, University Library of Munich, Germany.
    4. Small, Kenneth A., 2012. "Valuation of travel time," Economics of Transportation, Elsevier, vol. 1(1), pages 2-14.
    5. Cameron, Trudy Ann & James, Michelle D, 1987. "Efficient Estimation Methods for "Closed-ended' Contingent Valuation Surveys," The Review of Economics and Statistics, MIT Press, vol. 69(2), pages 269-276, May.
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    Cited by:

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