IDEAS home Printed from https://ideas.repec.org/a/aea/aejpol/v12y2020i1p418-53.html
   My bibliography  Save this article

The Marginal Cost of Traffic Congestion and Road Pricing: Evidence from a Natural Experiment in Beijing

Author

Listed:
  • Jun Yang
  • Avralt-Od Purevjav
  • Shanjun Li

Abstract

Severe traffic congestion is ubiquitous in large urban centers. This paper provides the first causal estimate of the relationship between traffic density and speed and optimal congestion charges using real-time fine-scale traffic data in Beijing. The identification relies on plausibly exogenous variation in traffic density induced by Beijing's driving restriction policy. Optimal congestion charges range from 5 to 39 cents per km depending on time and location. Road pricing would increase traffic speed by 11 percent within the city center and lead to an annual welfare gain of ¥1.5 billion from reduced congestion and revenue of ¥10.5 billion.

Suggested Citation

  • Jun Yang & Avralt-Od Purevjav & Shanjun Li, 2020. "The Marginal Cost of Traffic Congestion and Road Pricing: Evidence from a Natural Experiment in Beijing," American Economic Journal: Economic Policy, American Economic Association, vol. 12(1), pages 418-453, February.
    • Handle: RePEc:aea:aejpol:v:12:y:2020:i:1:p:418-53
    DOI: 10.1257/pol.20170195
    as

    Download full text from publisher

    File URL: https://www.aeaweb.org/doi/10.1257/pol.20170195
    Download Restriction: no
    File URL: https://www.aeaweb.org/doi/10.1257/pol.20170195.data
    Download Restriction: no
    File URL: https://www.aeaweb.org/doi/10.1257/pol.20170195.appx
    Download Restriction: Access to full text is restricted to AEA members and institutional subscribers.
    File URL: https://libkey.io/10.1257/pol.20170195?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Anderson, Michael L. & Davis, Lucas W., 2020. "An empirical test of hypercongestion in highway bottlenecks," Journal of Public Economics, Elsevier, vol. 187(C).
    2. Francis Rathinam & Sayak Khatua & Zeba Siddiqui & Manya Malik & Pallavi Duggal & Samantha Watson & Xavier Vollenweider, 2021. "Using big data for evaluating development outcomes: A systematic map," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(3), September.
    3. Shihe Fu & V. Brian Viard, 2022. "A mayors perspective on tackling air pollution," Chapters, in: Charles K.Y. Leung (ed.), Handbook of Real Estate and Macroeconomics, chapter 16, pages 413-437, Edward Elgar Publishing.
    4. Li, Shanjun & Liu, Yanyan & Purevjav, Avralt-Od & Yang, Lin, 2019. "Does subway expansion improve air quality?," Journal of Environmental Economics and Management, Elsevier, vol. 96(C), pages 213-235.
    5. Linn, Joshua & McConnell, Virginia & Pesek, Sophie & Raimi, Daniel, 2023. "Transportation Taxes and Energy Transitions: Alternative Policy Designs for Funding US Road Infrastructure and Pricing Externalities," RFF Working Paper Series 23-09, Resources for the Future.
    6. Cong Peng, 2019. "Does e-commerce reduce traffic congestion? Evidence from Alibaba Single Day shopping event," CEP Discussion Papers dp1646, Centre for Economic Performance, LSE.
    7. Li, Tianshu & Song, Shunfeng & Yang, Yanmin, 2022. "Driving restrictions, traffic speeds and carbon emissions: Evidence from high-frequency data," China Economic Review, Elsevier, vol. 74(C).
    8. Chao Sun & Jian Lu, 2022. "The Relative Roles of Socioeconomic Factors and Governance Policies in Urban Traffic Congestion: A Global Perspective," Land, MDPI, vol. 11(10), pages 1-17, September.
    9. Russo, Antonio & Adler, Martin W. & van Ommeren, Jos N., 2022. "Dedicated bus lanes, bus speed and traffic congestion in Rome," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 298-310.
    10. Russo, Antonio & Adler, Martin W. & Liberini, Federica & van Ommeren, Jos N., 2021. "Welfare losses of road congestion: Evidence from Rome," Regional Science and Urban Economics, Elsevier, vol. 89(C).
    11. Selod,Harris & Soumahoro,Souleymane, 2020. "Big Data in Transportation : An Economics Perspective," Policy Research Working Paper Series 9308, The World Bank.
    12. Peng, Cong, 2019. "Does e-commerce reduce traffic congestion? Evidence from Alibaba Single Day shopping event," LSE Research Online Documents on Economics 103411, London School of Economics and Political Science, LSE Library.
    13. Dudhe, Naini & Benjamin, Colin, 2021. "Entanglement and quantum strategies reduce congestion costs in Pigou networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    14. 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).
    15. Kim, Jinwon, 2022. "Does roadwork improve road speed? Evidence from urban freeways in California," Regional Science and Urban Economics, Elsevier, vol. 93(C).
    16. Chakrabarti, Sandip, 2022. "Passively wait for gridlock, or proactively invest in service? Strategies to promote car-to-transit switches among aspirational urbanites in rapidly developing contexts," Transport Policy, Elsevier, vol. 115(C), pages 251-261.
    17. Gómez Gélvez, Julian & Mojica, Carlos, 2022. "Subsidios al transporte público en América Latina desde una perspectiva de eficiencia: aplicación a Bogotá, Colombia," IDB Publications (Working Papers) 12260, Inter-American Development Bank.
    18. Andrea Baranzini & Stefano Carattini & Linda Tesauro, 2021. "Designing Effective and Acceptable Road Pricing Schemes: Evidence from the Geneva Congestion Charge," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 79(3), pages 417-482, July.

    More about this item

    JEL classification:

    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • P25 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - Urban, Rural, and Regional Economics
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aea:aejpol:v:12:y:2020:i:1:p:418-53. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Michael P. Albert (email available below). General contact details of provider: https://edirc.repec.org/data/aeaaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.