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Accuracy of congestion pricing forecasts

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  • Eliasson, Jonas
  • Börjesson, Maria
  • van Amelsfort, Dirk
  • Brundell-Freij, Karin
  • Engelson, Leonid

Abstract

This paper compares forecast effects of the Stockholm congestion charges with actual outcomes. The most important concerns during the design of the congestion charging scheme were the traffic reduction in bottlenecks, the increase in public transport ridership, the decrease of vehicle kilometres in the city centre, and potential traffic effects on circumferential roads. Comparisons of forecasts and actual outcomes show that the transport model predicted all of these factors well enough to allow planners to draw correct conclusions regarding the design and preparations for the scheme. The one major shortcoming was that the static assignment network model was unable to predict the substantial reductions of queuing times. We conclude that the transport model worked well enough to be useful as decision support, performing considerably better than unaided “experts’ judgments”, but that results must be interpreted taking the model’s limitations into account. The positive experiences from the Stockholm congestion charges hence seem to be transferable to other cities in the sense that if a charging system is forecast to have beneficial effects on congestion, then this is most likely true.

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  • Eliasson, Jonas & Börjesson, Maria & van Amelsfort, Dirk & Brundell-Freij, Karin & Engelson, Leonid, 2013. "Accuracy of congestion pricing forecasts," Transportation Research Part A: Policy and Practice, Elsevier, vol. 52(C), pages 34-46.
  • Handle: RePEc:eee:transa:v:52:y:2013:i:c:p:34-46
    DOI: 10.1016/j.tra.2013.04.004
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    1. West, Jens & Börjesson, Maria & Engelson, Leonid, 2016. "Accuracy of the Gothenburg congestion charges forecast," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 266-277.
    2. Börjesson, Maria & Brundell-Freij, Karin & Eliasson, Jonas, 2014. "Not invented here: Transferability of congestion charges effects," Transport Policy, Elsevier, vol. 36(C), pages 263-271.
    3. Tariq Munir & Hussein Dia & Hadi Ghaderi, 2021. "A Systematic Review of the Role of Road Network Pricing in Shaping Sustainable Cities: Lessons Learned and Opportunities for a Post-Pandemic World," Sustainability, MDPI, vol. 13(21), pages 1-20, October.
    4. Eliasson, Jonas, 2014. "The role of attitude structures, direct experience and reframing for the success of congestion pricing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 81-95.
    5. Kristoffersson, Ida & Engelson, Leonid & Börjesson, Maria, 2017. "Efficiency vs equity: Conflicting objectives of congestion charges," Transport Policy, Elsevier, vol. 60(C), pages 99-107.
    6. Eliasson, Jonas, 2014. "The Stockholm congestion pricing syndrome: how congestion charges went from unthinkable to uncontroversial," Working papers in Transport Economics 2014:1, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    7. Lorenzo Varela, Juan Manuel & Börjesson, Maria & Daly, Andrew, 2018. "Public transport: One mode or several?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 137-156.
    8. Varela, Juan Manuel Lorenzo & Börjesson, Maria & Daly, Andrew, 2018. "Quantifying errors in travel time and cost by latent variables," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 520-541.
    9. Odeck, James & Welde, Morten, 2017. "The accuracy of toll road traffic forecasts: An econometric evaluation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 73-85.
    10. Börjesson, Maria & Kristoffersson, Ida, 2018. "The Swedish congestion charges: Ten years on," Transportation Research Part A: Policy and Practice, Elsevier, vol. 107(C), pages 35-51.
    11. Börjesson, Maria & Jonsson, R. Daniel & Lundberg, Mattias, 2014. "An ex-post CBA for the Stockholm Metro," Transportation Research Part A: Policy and Practice, Elsevier, vol. 70(C), pages 135-148.
    12. Zannat, Khatun E. & Choudhury, Charisma F. & Hess, Stephane, 2024. "Modelling time-of-travel preferences capturing correlations between departure times and activity durations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 184(C).
    13. Lehe, Lewis J., 2020. "Winners and losers from road pricing with heterogeneous travelers and a mixed-traffic bus alternative," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 432-446.
    14. Börjesson , Maria & Kristoffersson , Ida, 2014. "The Gothenburg congestion charge: effects, design and politics," Working papers in Transport Economics 2014:25, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    15. Börjesson, Maria & Kristoffersson, Ida, 2015. "The Gothenburg congestion charge. Effects, design and politics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 134-146.
    16. Jens West & Maria Börjesson, 2020. "The Gothenburg congestion charges: cost–benefit analysis and distribution effects," Transportation, Springer, vol. 47(1), pages 145-174, February.
    17. West, Jens & Börjesson, Maria, 2016. "The Gothenburg congestion charges: CBA and equity," Working papers in Transport Economics 2016:17, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    18. Ida Kristoffersson & Leonid Engelson, 2018. "Estimating preferred departure times of road users in a large urban network," Transportation, Springer, vol. 45(3), pages 767-787, May.
    19. Berry, Carl & Börjesson, Maria, 2024. "Income and fuel price elasticities of car use on micro panel data," Energy Economics, Elsevier, vol. 135(C).
    20. Börjesson, Maria & Jonsson, R. Daniel & Berglund, Svante & Almström, Peter, 2014. "Land-use impacts in transport appraisal," Research in Transportation Economics, Elsevier, vol. 47(C), pages 82-91.
    21. Börjesson, Maria & Asplund, Disa & Hamilton, Carl, 2023. "Optimal kilometre tax for electric vehicles," Transport Policy, Elsevier, vol. 134(C), pages 52-64.

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    More about this item

    Keywords

    Forecast accuracy; Congestion pricing; Model validation; Policy transfer;
    All these keywords.

    JEL classification:

    • 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

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