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The Cost of Traffic: Evidence from the London Congestion Charge

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  • Tang, Cheng Keat

Abstract

This paper exploits the implementation of the London Congestion Charge (LCC) to provide credible estimates on the willingness to pay to avoid traffic using the housing market. This policy curtails road traffic by imposing a fee on anyone driving into the charge zone. My results show that the LCC is associated with significant improvement in traffic conditions and housing values. Instrumenting local traffic conditions with the enforcement of the LCC, and limiting the analysis to properties proximate to the charge boundary, I find that the elasticity of housing values with respect to traffic is -0.30. These findings suggest that the consequential improvement in traffic conditions due to the LCC has generated substantial windfall of more than £3.8 billion for homeowners in the zone.

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  • Tang, Cheng Keat, 2021. "The Cost of Traffic: Evidence from the London Congestion Charge," Journal of Urban Economics, Elsevier, vol. 121(C).
    • Handle: RePEc:eee:juecon:v:121:y:2021:i:c:s0094119020300735
    DOI: 10.1016/j.jue.2020.103302
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    2. Nakamura, Ryota & Albanese, Andrea & Coombes, Emma & Suhrcke, Marc, 2021. "Do Economic Incentives Promote Physical Activity? Evidence from the London Congestion Charge," IZA Discussion Papers 14957, Institute of Labor Economics (IZA).
    3. Stefano Cellini & Francisco Nobre, 2023. "Business Improvement Districts and Housing Markets: Evidence from Neighborhoods in London," School of Economics Discussion Papers 0523, School of Economics, University of Surrey.
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    8. Tassinari, Filippo, 2024. "Low emission zones and traffic congestion: Evidence from Madrid Central," Transportation Research Part A: Policy and Practice, Elsevier, vol. 185(C).
    9. 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).
    10. Tang, Cheng Keat & Gibbons, Stephen, 2024. "Are friends electric? Valuing the social costs of power lines using house prices," Energy Economics, Elsevier, vol. 134(C).
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    13. Shr, Yau-Huo (Jimmy) & Yang, Feng-An & Chen, Yi-Syun, 2023. "The housing market impacts of bicycle-sharing systems," Regional Science and Urban Economics, Elsevier, vol. 98(C).
    14. Pang, Jindong & An, Lan & Shen, Shulin, 2023. "Gasoline prices, traffic congestion, and carbon emissions," Resource and Energy Economics, Elsevier, vol. 75(C).
    15. Austin, Wes & Carattini, Stefano & Gomez-Mahecha, John & Pesko, Michael F., 2023. "The effects of contemporaneous air pollution on COVID-19 morbidity and mortality," Journal of Environmental Economics and Management, Elsevier, vol. 119(C).
    16. Arlinghaus, Johanna Brigitte & Konc, Théo & Mattauch, Linus & Sommer, Stephan, 2024. "The effect of information framing on policy support: Experimental evidence from urban policies," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302449, Verein für Socialpolitik / German Economic Association.
    17. Qixiu Cheng & Jun Chen & Honggang Zhang & Zhiyuan Liu, 2021. "Optimal Congestion Pricing with Day-to-Day Evolutionary Flow Dynamics: A Mean–Variance Optimization Approach," Sustainability, MDPI, vol. 13(9), pages 1-15, April.
    18. Zhang, Yingheng & Li, Haojie & Ren, Gang, 2022. "Quantifying the social impacts of the London Night Tube with a double/debiased machine learning based difference-in-differences approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 163(C), pages 288-303.
    19. Lyu, Xueying, 2022. "Car restriction policies and housing markets," Journal of Development Economics, Elsevier, vol. 156(C).
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