IDEAS home Printed from https://ideas.repec.org/p/tor/tecipa/tecipa-585.html
   My bibliography  Save this paper

Is Uber a substitute or complement for public transit?

Author

Listed:
  • Jonathan D. Hall
  • Craig Palsson
  • Joseph Price

Abstract

How Uber affects public transit ridership is a relevant policy question facing cities worldwide. Theoretically, Uber's effect on transit is ambiguous: while Uber is an alternative mode of travel, it can also increase the reach and flexibility of transit's fixed-route, fixed-schedule service. We use a difference-in-differences design to measure the effect of Uber on public transit ridership. The design exploits variation across U.S. metropolitan areas in both the intensity of Uber penetration (as measured using data from Google Trends) and the timing of Uber entry. We find that Uber is a complement for the average transit agency. This average effect masks considerable heterogeneity, with Uber being more of a complement in larger cities and for smaller transit agencies. Comparing the effect across modes, we find that Uber's impact on bus ridership follows the same pattern as for total ridership, though for rail ridership, it is a complement for larger agencies.

Suggested Citation

  • Jonathan D. Hall & Craig Palsson & Joseph Price, 2017. "Is Uber a substitute or complement for public transit?," Working Papers tecipa-585, University of Toronto, Department of Economics.
  • Handle: RePEc:tor:tecipa:tecipa-585
    as

    Download full text from publisher

    File URL: https://www.economics.utoronto.ca/public/workingPapers/tecipa-585.pdf
    File Function: Main Text
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jessica Lynn Peck, 2017. "New York City Drunk Driving After Uber," Working Papers 13, City University of New York Graduate Center, Ph.D. Program in Economics.
    2. Stephens-Davidowitz, Seth, 2014. "The cost of racial animus on a black candidate: Evidence using Google search data," Journal of Public Economics, Elsevier, vol. 118(C), pages 26-40.
    3. Angela K. Dills & Sean E. Mulholland, 2018. "Ride‐Sharing, Fatal Crashes, and Crime," Southern Economic Journal, John Wiley & Sons, vol. 84(4), pages 965-991, April.
    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. Jeffrey L. Hoopes & Daniel H. Reck & Joel Slemrod, 2015. "Taxpayer Search for Information: Implications for Rational Attention," American Economic Journal: Economic Policy, American Economic Association, vol. 7(3), pages 177-208, August.
    6. Jonathan V. Hall & Alan B. Krueger, 2015. "An Analysis of the Labor Market for Uber's Driver-Partners in the United States," Working Papers 587, Princeton University, Department of Economics, Industrial Relations Section..
    7. David H. Autor, 2003. "Outsourcing at Will: The Contribution of Unjust Dismissal Doctrine to the Growth of Employment Outsourcing," Journal of Labor Economics, University of Chicago Press, vol. 21(1), pages 1-42, January.
    8. 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.
    9. Frank Goetzke, 2008. "Network Effects in Public Transit Use: Evidence from a Spatially Autoregressive Mode Choice Model for New York," Urban Studies, Urban Studies Journal Limited, vol. 45(2), pages 407-417, February.
    10. Peter Cohen & Robert Hahn & Jonathan Hall & Steven Levitt & Robert Metcalfe, 2016. "Using Big Data to Estimate Consumer Surplus: The Case of Uber," NBER Working Papers 22627, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    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. Teltser, Keith & Lennon, Conor & Burgdorf, Jacob, 2021. "Do ridesharing services increase alcohol consumption?," Journal of Health Economics, Elsevier, vol. 77(C).
    2. Scott Duke Kominers & Alexander Teytelboym & Vincent P Crawford, 2017. "An invitation to market design," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 33(4), pages 541-571.
    3. Berger, Thor & Chen, Chinchih & Frey, Carl Benedikt, 2018. "Drivers of disruption? Estimating the Uber effect," European Economic Review, Elsevier, vol. 110(C), pages 197-210.
    4. 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).
    5. 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).
    6. Sutirtha Bagchi, 2018. "A Tale of Two Cities: An Examination of Medallion Prices in New York and Chicago," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 53(2), pages 295-319, September.
    7. Sen Li & Kameshwar Poolla & Pravin Varaiya, 2020. "Impact of Congestion Charge and Minimum Wage on TNCs: A Case Study for San Francisco," Papers 2003.02550, arXiv.org, revised Feb 2021.
    8. Asplund, Disa & Pyddoke, Roger, 2020. "Optimal fares and frequencies for bus services in a small city," Research in Transportation Economics, Elsevier, vol. 80(C).
    9. Agrawal, David R. & Zhao, Weihua, 2023. "Taxing Uber," Journal of Public Economics, Elsevier, vol. 221(C).
    10. 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.
    11. Ariel Goldszmidt & John A. List & Robert D. Metcalfe & Ian Muir & V. Kerry Smith & Jenny Wang, 2020. "The Value of Time in the United States: Estimates from Nationwide Natural Field Experiments," NBER Working Papers 28208, National Bureau of Economic Research, Inc.
    12. 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.
    13. Joana Naritomi, 2019. "Consumers as Tax Auditors," American Economic Review, American Economic Association, vol. 109(9), pages 3031-3072, September.
    14. 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.
    15. Zhou, You, 2020. "Ride-sharing, alcohol consumption, and drunk driving," Regional Science and Urban Economics, Elsevier, vol. 85(C).
    16. Pyddoke, Roger & Lindgren, Hanna, 2018. "Outcomes from new contracts with “strong” incentives for increasing ridership in bus transport in Stockholm," Research in Transportation Economics, Elsevier, vol. 69(C), pages 197-206.
    17. 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.
    18. Berde, Éva, 2018. "Uber és taxi egymás mellett - új piaci modellek hagyományos árdiszkriminációval [Uber and taxi firms side by side. The Ublyft" business model with traditional price discrimination]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(6), pages 650-666.
    19. Yoshifumi Konishi & Akari Ono, 2024. "Is Ride-sharing Good for Environment?," Keio-IES Discussion Paper Series 2024-014, Institute for Economics Studies, Keio University.
    20. Brodeur, Abel & Nield, Kerry, 2018. "An empirical analysis of taxi, Lyft and Uber rides: Evidence from weather shocks in NYC," Journal of Economic Behavior & Organization, Elsevier, vol. 152(C), pages 1-16.

    More about this item

    Keywords

    public transportation; difference-in-differences;

    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General
    • H42 - Public Economics - - Publicly Provided Goods - - - Publicly Provided Private Goods

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:tor:tecipa:tecipa-585. 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: RePEc Maintainer (email available below). General contact details of provider: .

    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.