IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v163y2022icp20-42.html
   My bibliography  Save this article

Covid-19 and optimal urban transport policy

Author

Listed:
  • De Borger, Bruno
  • Proost, Stef

Abstract

Covid-19 has important implications for public transport operations. Increased teleworking and the perceived infection risk on public transport vehicles have drastically reduced demand in many cities. At the same time, physical distancing has effectively reduced available peak-period public transport capacity. In this paper, we use a simple model to study the effect of these changes on second-best optimal pricing and frequency provision, assuming that car use is underpriced. A numerical application reflecting the public transport situation in Brussel is provided. Results include the following. First, more telework and the increased perceived infection risk have opposite effects on the fare, so that it may be optimal not to change the fare at all. Optimal frequency is likely to decline. Second, holding the fare and frequency constant at their pre-Covid second-best optimal values, more telework reduces the public transport deficit if car use is underpriced. Third, extending the model to allow for passengers with different vulnerability towards Covid-19, allowing fare and frequency differentiation implies that vulnerable users will face higher fares only if their risk perception is sufficiently higher than that of the non-vulnerable, and car use is not too much underpriced. Occupancy rates will be lower for the vulnerable passengers. Fourth, the numerical results for Brussels show that telework and a high perceived infection risk for workers may yield a welfare optimum whereby commuters do almost not use public transport. Offering a low frequency suffices to deal with the captive demand by school children and students. Lastly, reserved capacity for the vulnerable users and stimuli for walking and biking to school may be useful policies to deal with the crowding risk.

Suggested Citation

  • De Borger, Bruno & Proost, Stef, 2022. "Covid-19 and optimal urban transport policy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 163(C), pages 20-42.
  • Handle: RePEc:eee:transa:v:163:y:2022:i:c:p:20-42
    DOI: 10.1016/j.tra.2022.06.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856422001665
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tra.2022.06.012?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mohring, Herbert, 1972. "Optimization and Scale Economies in Urban Bus Transportation," American Economic Review, American Economic Association, vol. 62(4), pages 591-604, September.
    2. Richard Batley & John Bates & Michiel Bliemer & Maria Börjesson & Jeremy Bourdon & Manuel Ojeda Cabral & Phani Kumar Chintakayala & Charisma Choudhury & Andrew Daly & Thijs Dekker & Efie Drivyla & Ton, 2019. "New appraisal values of travel time saving and reliability in Great Britain," Transportation, Springer, vol. 46(3), pages 583-621, June.
    3. Ian W. H. Parry & Kenneth A. Small, 2009. "Should Urban Transit Subsidies Be Reduced?," American Economic Review, American Economic Association, vol. 99(3), pages 700-724, June.
    4. Leonardo J. Basso & Hugo E. Silva, 2014. "Efficiency and Substitutability of Transit Subsidies and Other Urban Transport Policies," American Economic Journal: Economic Policy, American Economic Association, vol. 6(4), pages 1-33, November.
    5. Behrens, Kristian & Kichko, Sergei & Thisse, Jacques-Francois, 2024. "Working from home: Too much of a good thing?," Regional Science and Urban Economics, Elsevier, vol. 105(C).
    6. de Palma, André & Lindsey, Robin & Monchambert, Guillaume, 2017. "The economics of crowding in rail transit," Journal of Urban Economics, Elsevier, vol. 101(C), pages 106-122.
    7. 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.
    8. Alfredo Aloi & Borja Alonso & Juan Benavente & Rubén Cordera & Eneko Echániz & Felipe González & Claudio Ladisa & Raquel Lezama-Romanelli & Álvaro López-Parra & Vittorio Mazzei & Lucía Perrucci & Darí, 2020. "Effects of the COVID-19 Lockdown on Urban Mobility: Empirical Evidence from the City of Santander (Spain)," Sustainability, MDPI, vol. 12(9), pages 1-18, May.
    9. Proost, Stef & Dender, Kurt Van, 2008. "Optimal urban transport pricing in the presence of congestion, economies of density and costly public funds," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(9), pages 1220-1230, November.
    10. 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.
    11. Börjesson, Maria & Fung, Chau Man & Proost, Stef, 2017. "Optimal prices and frequencies for buses in Stockholm," Economics of Transportation, Elsevier, vol. 9(C), pages 20-36.
    12. Daron Acemoglu & Victor Chernozhukov & Ivàn Werning & Michael D. Whinston, 2020. "A Multi-Risk SIR Model with Optimally Targeted Lockdown," CeMMAP working papers CWP14/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Sergio Jara-Díaz & Antonio Gschwender, 2003. "Towards a general microeconomic model for the operation of public transport," Transport Reviews, Taylor & Francis Journals, vol. 23(4), pages 453-469, July.
    14. De Borger, Bruno & Wouters, Sandra, 1998. "Transport externalities and optimal pricing and supply decisions in urban transportation: a simulation analysis for Belgium," Regional Science and Urban Economics, Elsevier, vol. 28(2), pages 163-197, March.
    15. Michael L. Anderson, 2014. "Subways, Strikes, and Slowdowns: The Impacts of Public Transit on Traffic Congestion," American Economic Review, American Economic Association, vol. 104(9), pages 2763-2796, September.
    16. De Borger, Bruno & Proost, Stef, 2015. "The political economy of public transport pricing and supply decisions," Economics of Transportation, Elsevier, vol. 4(1), pages 95-109.
    17. Frankena, Mark W., 1981. "The effects of alternative urban transit subsidy formulas," Journal of Public Economics, Elsevier, vol. 15(3), pages 337-348, June.
    18. Jeffrey E. Harris, 2020. "The Subways Seeded the Massive Coronavirus Epidemic in New York City," NBER Working Papers 27021, National Bureau of Economic Research, Inc.
    19. Hensher, David A. & Beck, Matthew J. & Wei, Edward, 2021. "Working from home and its implications for strategic transport modelling based on the early days of the COVID-19 pandemic," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 64-78.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Karimi, Sina & Samadzad, Mahdi & Lesteven, Gaele, 2024. "Navigating public transport during a pandemic: Key lessons on travel behavior and social equity from two surveys in Tehran," Transportation Research Part A: Policy and Practice, Elsevier, vol. 184(C).
    2. Mašek Jaroslav & Pálková Adriana & Blaho Peter & Halajová Štefánia & Jursová Simona & Šipuš Denis, 2023. "Proposal for Using IT Solutions in Public Passenger Transport in Slovak Republic to Reduce the Spread of COVID-19," LOGI – Scientific Journal on Transport and Logistics, Sciendo, vol. 14(1), pages 181-191, January.
    3. Jorge De Andres-Sanchez & Angel Belzunegui-Eraso & Mar Souto-Romero, 2023. "Perception of the Effects of Working from Home on Isolation and Stress by Spanish Workers during COVID-19 Pandemic," Social Sciences, MDPI, vol. 12(2), pages 1-25, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hörcher, Daniel & Tirachini, Alejandro, 2021. "A review of public transport economics," Economics of Transportation, Elsevier, vol. 25(C).
    2. Hörcher, Daniel & De Borger, Bruno & Seifu, Woubit & Graham, Daniel J., 2020. "Public transport provision under agglomeration economies," Regional Science and Urban Economics, Elsevier, vol. 81(C).
    3. Börjesson, Maria & Fung, Chau Man & Proost, Stef, 2017. "Optimal prices and frequencies for buses in Stockholm," Economics of Transportation, Elsevier, vol. 9(C), pages 20-36.
    4. Börjesson, Maria & Fung, Chau Man & Proost, Stef & Yan, Zifei, 2018. "Do buses hinder cyclists or is it the other way around? Optimal bus fares, bus stops and cycling tolls," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 326-346.
    5. Xuto, Praj & Anderson, Richard J. & Graham, Daniel J. & Hörcher, Daniel, 2021. "Optimal infrastructure reinvestment in urban rail systems: A dynamic supply optimisation approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 251-268.
    6. Martin W Adler & Federica Liberini & Antonio Russo & Jos N. van Ommeren, 2021. "The congestion relief benefit of public transit: evidence from Rome," Journal of Economic Geography, Oxford University Press, vol. 21(3), pages 397-431.
    7. Giagnorio, Mirko & Börjesson, Maria & D'Alfonso, Tiziana, 2024. "Introducing electric buses in urban areas: Effects on welfare, pricing, frequency, and public subsidies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 185(C).
    8. De Borger, Bruno & Proost, Stef, 2015. "The political economy of public transport pricing and supply decisions," Economics of Transportation, Elsevier, vol. 4(1), pages 95-109.
    9. 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.
    10. Guillaume Monchambert & Stef Proost, 2019. "How Efficient are Intercity Railway Prices and Frequencies in Europe?: Comparing a Corridor in Belgium and in France," Journal of Transport Economics and Policy, University of Bath, vol. 53(4), pages 323-32-347.
    11. Zhang, Junlin & Yang, Hai & Lindsey, Robin & Li, Xinwei, 2020. "Modeling and managing congested transit service with heterogeneous users under monopoly," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 249-266.
    12. Bull, Owen & Muñoz, Juan Carlos & Silva, Hugo E., 2021. "The impact of fare-free public transport on travel behavior: Evidence from a randomized controlled trial," Regional Science and Urban Economics, Elsevier, vol. 86(C).
    13. Tirachini, Alejandro & Proost, Stef, 2021. "Transport taxes and subsidies in developing countries: The effect of income inequality aversion," Economics of Transportation, Elsevier, vol. 25(C).
    14. Davis, Lucas W., 2021. "Estimating the price elasticity of demand for subways: Evidence from Mexico," Regional Science and Urban Economics, Elsevier, vol. 87(C).
    15. Hörcher, Daniel & De Borger, Bruno & Graham, Daniel J., 2023. "Subsidised transport services in a fiscal federation: Why local governments may be against decentralised service provision," Economics of Transportation, Elsevier, vol. 34(C).
    16. Basso, Leonardo J. & Jara-Díaz, Sergio R., 2012. "Integrating congestion pricing, transit subsidies and mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(6), pages 890-900.
    17. Asplund, Disa & Pyddoke, Roger, 2020. "Optimal fares and frequencies for bus services in a small city," Research in Transportation Economics, Elsevier, vol. 80(C).
    18. Durrmeyer, Isis & Martinez, Nicolas, 2022. "The Welfare Consequences of Urban Traffic Regulations," TSE Working Papers 22-1378, Toulouse School of Economics (TSE).
    19. Jara-Díaz, Sergio & Fielbaum, Andrés & Gschwender, Antonio, 2020. "Strategies for transit fleet design considering peak and off-peak periods using the single-line model," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 1-18.
    20. Ihab Kaddoura & Benjamin Kickhöfer & Andreas Neumann & Alejandro Tirachini, 2015. "Agent-based optimisation of public transport supply and pricing: impacts of activity scheduling decisions and simulation randomness," Transportation, Springer, vol. 42(6), pages 1039-1061, November.

    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:eee:transa:v:163:y:2022:i:c:p:20-42. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.