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Public transport congestion costs: The case of the Paris subway

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  • Prud'homme, Rémy
  • Koning, Martin
  • Lenormand, Luc
  • Fehr, Anne

Abstract

The paper argues that congestion in public transportation is alike the much more studied road congestion. It sets out to produce, on the case of the Paris subway, a congestion cost curve linking the willingness to pay for non-congested travel to actual congestion levels. Congestion costs appear high. What travelers would be ready to pay to avoid congestion in the Paris subway is on average about three times the amount of their out-of-pocket payments. An 8% increase in densities experienced over the 2002–2007 period implies a welfare loss of at least 75M€/year. Taking into account the subway congestion costs and the resulting externalities modifies significantly the optimal car-subway mix (from 8% to 24% according to a tentative computable model).

Suggested Citation

  • Prud'homme, Rémy & Koning, Martin & Lenormand, Luc & Fehr, Anne, 2012. "Public transport congestion costs: The case of the Paris subway," Transport Policy, Elsevier, vol. 21(C), pages 101-109.
    • Handle: RePEc:eee:trapol:v:21:y:2012:i:c:p:101-109
    DOI: 10.1016/j.tranpol.2011.11.002
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    References listed on IDEAS

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    Cited by:

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    9. André de Palma & Robin Lindsey & Guillaume Monchambert, 2017. "The Economics of Crowding in Public Transport," Post-Print hal-01203310, HAL.
    10. Paudel, Jayash, 2021. "Bus ridership and service reliability: The case of public transportation in Western Massachusetts," Transport Policy, Elsevier, vol. 100(C), pages 98-107.
    11. Anne Halvorsen & Haris N. Koutsopoulos & Zhenliang Ma & Jinhua Zhao, 2020. "Demand management of congested public transport systems: a conceptual framework and application using smart card data," Transportation, Springer, vol. 47(5), pages 2337-2365, October.
    12. de Palma, André & Kilani, Moez & Proost, Stef, 2015. "Discomfort in mass transit and its implication for scheduling and pricing," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 1-18.
    13. Haywood, Luke & Koning, Martin, 2015. "The distribution of crowding costs in public transport: New evidence from Paris," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 182-201.
    14. Cats, Oded & West, Jens & Eliasson, Jonas, 2015. "Appraisal of increased public transport capacity: the case of a new metro line to Nacka, Sweden," Working papers in Transport Economics 2015:2, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    15. Cats, Oded & West, Jens & Eliasson, Jonas, 2016. "A dynamic stochastic model for evaluating congestion and crowding effects in transit systems," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 43-57.
    16. Ruichang Mao & Yi Bao & Huabo Duan & Gang Liu, 2021. "Global urban subway development, construction material stocks, and embodied carbon emissions," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-11, December.
    17. Palma, Andre de & Lindsey, Robin & Monchambert, Guillaume, 2016. "Optimal Transit Pricing with Crowding and Traffic Congestion: A Dynamic Equilibrium Analysis," 57th Transportation Research Forum (51st CTRF) Joint Conference, Toronto, Ontario, May 1-4, 2016 319276, Transportation Research Forum.
    18. André de Palma & Robin Lindsey & Guillaume Monchambert, 2015. "Optimal fares and capacity decisions for crowded public transport systems," Post-Print hal-01223169, HAL.
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