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Congestion by accident? A two-way relationship for highways in England

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  • Pasidis, Ilias

Abstract

This paper aims to estimate the causal effect of accidents on traffic congestion and vice versa. In order to identify both effects of this two-way relationship, I use dynamic panel data techniques and open access ‘big data’ of highway traffic and accidents in England for the period 2012–2014. The research design is based on the daily-and-hourly specific mean reversion pattern of highway traffic, which can be used to define a recurrent congestion benchmark. Using this benchmark, I am able to identify the causal effect of accidents on non-recurrent traffic congestion. A positive relationship between traffic congestion and road accidents would yield multiplicative benefits for policies that aim at reducing either of these issues. Additionally, I explore the duration of the effect of an accident on congestion, the ‘rubbernecking’ effect, as well as heterogeneous effects in the most congested highway segments. Then, I test the use of methods which employ the bulk of information in big data and other methods using a very reduced sample. In my application, both approaches produce similar results. Finally, I find a non-linear negative effect of traffic congestion on the probability of an accident.

Suggested Citation

  • Pasidis, Ilias, 2019. "Congestion by accident? A two-way relationship for highways in England," Journal of Transport Geography, Elsevier, vol. 76(C), pages 301-314.
    • Handle: RePEc:eee:jotrge:v:76:y:2019:i:c:p:301-314
    DOI: 10.1016/j.jtrangeo.2017.10.006
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    References listed on IDEAS

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    Cited by:

    1. Miquel-Àngel Garcia-López & Ilias Pasidis & Elisabet Viladecans-Marsal, 2022. "Congestion in highways when tolls and railroads matter: evidence from European cities [The congestion relief benefit of public transit: evidence from Rome]," Journal of Economic Geography, Oxford University Press, vol. 22(5), pages 931-960.
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    3. Shr, Yau-Huo & Hsu, Wen & Hwang, Bing-Fang & Jung, Chau-Ren, 2023. "Air quality and risky behaviors on roads," Journal of Environmental Economics and Management, Elsevier, vol. 118(C).

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    More about this item

    Keywords

    Accidents; Traffic congestion; Big data; Highways; England;
    All these keywords.

    JEL classification:

    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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