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Public transport fare elasticities from smartcard data: Evidence from a natural experiment

Author

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  • Kholodov, Yaroslav
  • Jenelius, Erik
  • Cats, Oded
  • van Oort, Niels
  • Mouter, Niek
  • Cebecauer, Matej
  • Vermeulen, Alex

Abstract

This paper develops a method for analysing the elasticity of travel demand to public transport fares. The methodology utilizes public transport smartcard data for collecting disaggregate full population data about passengers’ travel behaviour. The study extends previous work by deriving specific fare elasticities for distinct socioeconomic (e.g., car ownership and income) groups and public transport modes (metro, trains and buses), and by considering the directionality of the fare change. The case study involves a public transport fare policy introduced by the regional administration of Stockholm County in January 2017, where the zonal fare system for single-trip tickets was replaced by a flat-fare policy. The overall fare elasticity of travel funds is found to be −0.46. User sensitivity grows along with the journey distance. Metro users demonstrate the lowest sensitivity, followed by bus and commuter train riders. Low socioeconomic groups, in particular with respect to car ownership, tend to be less sensitive than the high-factor groups. In addition to the direct effect of changed fares, simplification and unification of the fare scheme appears to have substantially contributed to its attractiveness. The flat fare may allow the geographic disparity of public transport travel to be reduced and new users to be attracted from remote areas who are more prone to own cars.

Suggested Citation

  • Kholodov, Yaroslav & Jenelius, Erik & Cats, Oded & van Oort, Niels & Mouter, Niek & Cebecauer, Matej & Vermeulen, Alex, 2021. "Public transport fare elasticities from smartcard data: Evidence from a natural experiment," Transport Policy, Elsevier, vol. 105(C), pages 35-43.
    • Handle: RePEc:eee:trapol:v:105:y:2021:i:c:p:35-43
    DOI: 10.1016/j.tranpol.2021.03.001
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    References listed on IDEAS

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    1. Whelan, Gerard & Batley, Richard & Shires, Jeremy & Wardman, Mark, 2008. "Optimal fares regulation for Britain's railways," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(5), pages 807-819, September.
    2. Wang, Zi-jia & Li, Xiao-hong & Chen, Feng, 2015. "Impact evaluation of a mass transit fare change on demand and revenue utilizing smart card data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 213-224.
    3. Oded Cats & Yusak O. Susilo & Triin Reimal, 2017. "The prospects of fare-free public transport: evidence from Tallinn," Transportation, Springer, vol. 44(5), pages 1083-1104, September.
    4. Zi-jia Wang & Feng Chen & Bo Wang & Jian-ling Huang, 2018. "Passengers’ response to transit fare change: an ex post appraisal using smart card data," Transportation, Springer, vol. 45(5), pages 1559-1578, September.
    5. Liu, Yan & Wang, Siqin & Xie, Bin, 2019. "Evaluating the effects of public transport fare policy change together with built and non-built environment features on ridership: The case in South East Queensland, Australia," Transport Policy, Elsevier, vol. 76(C), pages 78-89.
    6. Holmgren, Johan, 2007. "Meta-analysis of public transport demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 1021-1035, December.
    7. Benedetto Barabino & Cristian Lai & Alessandro Olivo, 2020. "Fare evasion in public transport systems: a review of the literature," Public Transport, Springer, vol. 12(1), pages 27-88, March.
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