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Improving the fit of structural models of congestion

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  • Jonathan D. Hall

Abstract

We need structural models of traffic congestion to answer a wide variety of questions, but the standard models fail to match the data on travel times across the day. I establish the nature and magnitude of the problem, and show its source lies in how we model agent preferences, not in the specifics of the congestion technology. The poor fit of the models suggests that we are abstracting away from features with a first-order impact on model predictions, which limits our ability to use these models to evaluate counterfactuals quantitatively and---when agents are heterogeneous---qualitatively as well. I explore several ways of improving the fit of these models, concluding with recommendations for tractable and intuitive ways of doing so.

Suggested Citation

  • Jonathan D. Hall, 2017. "Improving the fit of structural models of congestion," Working Papers tecipa-590, University of Toronto, Department of Economics.
    • Handle: RePEc:tor:tecipa:tecipa-590
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    Cited by:

    1. Hall, Jonathan D., 2018. "Pareto improvements from Lexus Lanes: The effects of pricing a portion of the lanes on congested highways," Journal of Public Economics, Elsevier, vol. 158(C), pages 113-125.
    2. Kim, Jinwon, 2019. "Estimating the social cost of congestion using the bottleneck model," Economics of Transportation, Elsevier, vol. 19(C), pages 1-1.

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    More about this item

    Keywords

    Structural model; Congestion; Model fit; Calibration; Dynamic; Bottleneck Model; Traffic;
    All these keywords.

    JEL classification:

    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics
    • H4 - Public Economics - - Publicly Provided Goods

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