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Estimating the social cost of congestion using the bottleneck model

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  • Kim, Jinwon

Abstract

This paper uses the bottleneck model of Vickrey (1969) to empirically measure the social cost of traffic congestion in the US. Using a detailed trip-level data, we estimate extra travel time over and above hypothetical free-flow travel time, which we call “queuing time”, for each average commute trip. The estimated individual queuing time implies that the annual cost of congestion borne by all US commuters is about 29 billion dollars. We find that a higher level of congestion in a city may be attributed to a smaller per capita road stock in the city. This paper also empirically quantifies a toll that depends both on the commuter's arrival time and trip distance.

Suggested Citation

  • Kim, Jinwon, 2019. "Estimating the social cost of congestion using the bottleneck model," Economics of Transportation, Elsevier, vol. 19(C), pages 1-1.
    • Handle: RePEc:eee:ecotra:v:19:y:2019:i:c:1
    DOI: 10.1016/j.ecotra.2019.100119
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    Cited by:

    1. Jinwon Kim & Jucheol Moon & Dongyun Yang, 2024. "Pigouvian Congestion Tolls and the Welfare Gain: Estimates for California Freeways," Working Papers 2402, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    2. Bi, Hui & Ye, Zhirui & Zhao, Jiahui & Chen, Enhui, 2020. "Real trip costs: Modelling intangible costs of urban online car-hailing in Haikou," Transport Policy, Elsevier, vol. 96(C), pages 128-140.
    3. Tscharaktschiew, Stefan & Reimann, Felix, 2021. "On employer-paid parking and parking (cash-out) policy: A formal synthesis of different perspectives," Transport Policy, Elsevier, vol. 110(C), pages 499-516.
    4. Raghu Bir Bista & Surendra Paneru, 2021. "Does Road Traffic Congestion Increase Fuel Consumption of Households in Kathmandu City?," Journal of Economic Impact, Science Impact Publishers, vol. 3(2), pages 67-79.
    5. Qiu, Feng & Tong, Qingmeng, 2021. "A spatial difference-in-differences approach to evaluate the impact of light rail transit on property values," Economic Modelling, Elsevier, vol. 99(C).
    6. Witsarut Achariyaviriya & Yoshitsugu Hayashi & Hiroyuki Takeshita & Masanobu Kii & Varameth Vichiensan & Thanaruk Theeramunkong, 2021. "Can Space–Time Shifting of Activities and Travels Mitigate Hyper-Congestion in an Emerging Megacity, Bangkok? Effects on Quality of Life and CO 2 Emission," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
    7. Jinwon Kim & Jucheol Moon, 2022. "Congestion Costs and Scheduling Preferences of Car Commuters in California: Estimates Using Big Data," Working Papers 2201, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    8. Li, Zhi-Chun & Huang, Hai-Jun & Yang, Hai, 2020. "Fifty years of the bottleneck model: A bibliometric review and future research directions," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 311-342.
    9. Fosgerau, Mogens & Kim, Jinwon, 2019. "Commuting and land use in a city with bottlenecks: Theory and evidence," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 182-204.
    10. Kapatsila, Bogdan & Collins, Damian & Grisé, Emily, 2024. "Assessing mode-specific transport affordability in a car-centric city," Journal of Transport Geography, Elsevier, vol. 114(C).
    11. Kim, Jinwon, 2022. "Does roadwork improve road speed? Evidence from urban freeways in California," Regional Science and Urban Economics, Elsevier, vol. 93(C).

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    More about this item

    Keywords

    Traffic congestion; Bottleneck; Economic inefficiency; Causal effect;
    All these keywords.

    JEL classification:

    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics
    • H2 - Public Economics - - Taxation, Subsidies, and Revenue
    • D6 - Microeconomics - - Welfare Economics

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