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Pricing urban congestion: A structural random utility model with traffic anticipation

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  • Viauroux, Christelle

Abstract

We design and estimate a game theoretic congestion pricing mechanism in which the regulator aims at reducing urban traffic congestion by price discriminating travelers according to their value of time (VOT). Travelers' preferences depend on their observable characteristics, on the endogenous amount of congestion anticipated, on their marginal utility (MU) of income and on some unobserved factors. Using a French household survey, we estimate the demand models to simulate different pricing mechanisms. We find that unobserved determinants of transportation demand are significant and are used to measure the anticipated time spent in traffic and the comfort of traveling: diverging from these expectations is felt as more discomfort than if no expectations were formed a priori. However, some of this discomfort is derived from travelers' marginal utility of income: the lost time in traffic is clearly “unpleasant” because of its opportunity cost. When the regulator and the transportation provider share common objectives, we show that a great welfare improvement can be achieved when implementing a homogenous pricing that accurately accounts for travelers VOT.

Suggested Citation

  • Viauroux, Christelle, 2011. "Pricing urban congestion: A structural random utility model with traffic anticipation," European Economic Review, Elsevier, vol. 55(7), pages 877-902.
  • Handle: RePEc:eee:eecrev:v:55:y:2011:i:7:p:877-902
    DOI: 10.1016/j.euroecorev.2011.04.001
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    References listed on IDEAS

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    Cited by:

    1. Börjesson, Maria & Kristoffersson, Ida, 2014. "Assessing the welfare effects of congestion charges in a real world setting," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 339-355.
    2. Delle Site, Paolo & Salucci, Marco Valerio, 2013. "Transition choice probabilities and welfare analysis in random utility models with imperfect before–after correlation," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 215-242.

    More about this item

    Keywords

    Bayesian game; Endogenous congestion; Value of time; Modes reputation; Optimal pricing; Welfare; Structural estimation;

    JEL classification:

    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • D6 - Microeconomics - - Welfare Economics

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