IDEAS home Printed from https://ideas.repec.org/p/cdl/uctcwp/qt5w9045hh.html
   My bibliography  Save this paper

Nature and/or nurture? Analyzing the determinants of transit ridership across US urbanized areas

Author

Listed:
  • Taylor, Brian D
  • Miller, Douglas
  • Iseki, Hiroyuki
  • Fink, Camille

Abstract

Public subsidy of transit services has increased dramatically in recent years, with little effect on overall ridership. Quite obviously, a clear understanding of the factors influencing transit ridership is central to decisions on investments in and the pricing and deployment of transit services. Yet the literature about the causes of transit use is quite spotty; most previous aggregate analyses of transit ridership have examined just one or a few systems, have not included many of the external, control variables thought to influence transit use, and have not addressed the simultaneous relationship between transit service supply and consumption. This study addresses each of these shortcomings by (1) conducting a cross-sectional analysis of transit use in 265 US urbanized areas, (2) testing dozens of variables measuring regional geography, metropolitan economy, population characteristics, auto/highway system characteristics, and transit system characteristics, and (3) constructing two-stage simultaneous equation regression models to account for simultaneity between transit service supply and consumption. We find that most of the variation in transit ridership among urbanized areas – in both absolute and relative terms – can be explained by factors outside of the control of public transit systems: (1) regional geography (specifically, area of urbanization, population, population density, and regional location in the US), (2) metropolitan economy (specifically, personal/household income), (3) population characteristics (specifically, the percent college students, recent immigrants, and Democratic voters in the population), and (4) auto/highway system characteristics (specifically, the percent carless households and nontransit/non-SOV trips, including commuting via carpools, walking, biking, etc.). While these external factors clearly go a long way toward determining the overall level of transit use in an urbanized area, we find that transit policies do make a significant difference. The observed range in both fares and service frequency in our sample could account for at least a doubling (or halving) of transit use in a given urbanized area. Controlling for the fact that public transit use is strongly correlated with urbanized area size, about 26% of the observed variance in per capita transit patronage across US urbanized areas is explained in the models presented here by service frequency and fare levels. The observed influence of these two factors is consistent with both the literature and intuition: frequent service draws passengers, and high fares drive them away.

Suggested Citation

  • Taylor, Brian D & Miller, Douglas & Iseki, Hiroyuki & Fink, Camille, 2008. "Nature and/or nurture? Analyzing the determinants of transit ridership across US urbanized areas," University of California Transportation Center, Working Papers qt5w9045hh, University of California Transportation Center.
    • Handle: RePEc:cdl:uctcwp:qt5w9045hh
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/5w9045hh.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. repec:cdl:uctcwp:qt96t810rj is not listed on IDEAS
    2. Wardman, Mark, 0. "A review of British evidence on time and service quality valuations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 37(2-3), pages 107-128, April.
    3. Jeffrey Brown & Daniel Hess & Donald Shoup, 2001. "Unlimited Access," Transportation, Springer, vol. 28(3), pages 233-267, August.
    4. Bresson, Georges & Dargay, Joyce & Madre, Jean-Loup & Pirotte, Alain, 2003. "The main determinants of the demand for public transport: a comparative analysis of England and France using shrinkage estimators," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(7), pages 605-627, August.
    5. Holmgren, Johan, 2007. "Meta-analysis of public transport demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 1021-1035, December.
    6. De Witte, Astrid & Macharis, Cathy & Lannoy, Pierre & Polain, Céline & Steenberghen, Thérèse & Van de Walle, Stefaan, 2006. "The impact of "free" public transport: The case of Brussels," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(8), pages 671-689, October.
    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. Javier D. Donna, 2021. "Measuring long‐run gasoline price elasticities in urban travel demand," RAND Journal of Economics, RAND Corporation, vol. 52(4), pages 945-994, December.
    2. Donna, Javier D., 2018. "Measuring Long-Run Price Elasticities in Urban Travel Demand," MPRA Paper 90260, University Library of Munich, Germany.
    3. Hwang, Hyeonjun & Lee, Myoung-jae, 2020. "A simple makeover can increase bus ridership: The story of Tayo bus," Transport Policy, Elsevier, vol. 97(C), pages 103-112.
    4. Efthymiou, Dimitrios & Antoniou, Constantinos & Tyrinopoulos, Yannis & Skaltsogianni, Eleana, 2018. "Factors affecting bus users’ satisfaction in times of economic crisis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PA), pages 3-12.
    5. Deepa, L. & Rawoof Pinjari, Abdul & Krishna Nirmale, Sangram & Srinivasan, Karthik K. & Rambha, Tarun, 2022. "A direct demand model for bus transit ridership in Bengaluru, India," Transportation Research Part A: Policy and Practice, Elsevier, vol. 163(C), pages 126-147.

    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. Redman, Lauren & Friman, Margareta & Gärling, Tommy & Hartig, Terry, 2013. "Quality attributes of public transport that attract car users: A research review," Transport Policy, Elsevier, vol. 25(C), pages 119-127.
    2. Souche, Stéphanie, 2009. "Un exemple d’estimation de la demande de transport urbain," Revue d'économie régionale et urbaine, Editions NecPlus, vol. 2009(04), pages 759-779, December.
    3. T. M. Fullerton & A. G. Walke, 2013. "Public transportation demand in a border metropolitan economy," Applied Economics, Taylor & Francis Journals, vol. 45(27), pages 3922-3931, September.
    4. 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.
    5. Sebri, Maamar, 2015. "Use renewables to be cleaner: Meta-analysis of the renewable energy consumption–economic growth nexus," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 657-665.
    6. Souche, Stéphanie, 2010. "Measuring the structural determinants of urban travel demand," Transport Policy, Elsevier, vol. 17(3), pages 127-134, May.
    7. Holmgren, Johan, 2007. "Meta-analysis of public transport demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 1021-1035, December.
    8. Xiaohong Chen & Xiang Wang & Hua Zhang & Jia Li, 2014. "The Diversity and Evolution Process of Bus System Performance in Chinese Cities: An Empirical Study," Sustainability, MDPI, vol. 6(11), pages 1-17, November.
    9. 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.
    10. Mark Wardman, 2012. "Review and meta-analysis of U.K. time elasticities of travel demand," Transportation, Springer, vol. 39(3), pages 465-490, May.
    11. Hannes Wallimann & Kevin Blattler & Widar von Arx, 2021. "Do price reductions attract customers in urban public transport? A synthetic control approach," Papers 2111.14613, arXiv.org, revised Mar 2022.
    12. Guzman, Luis A. & Beltran, Carlos & Bonilla, Jorge & Gomez Cardona, Santiago, 2021. "BRT fare elasticities from smartcard data: Spatial and time-of-the-day differences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 335-348.
    13. 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.
    14. Jan U. Becker & Sönke Albers, 2016. "The limits of analyzing service quality data in public transport," Transportation, Springer, vol. 43(5), pages 823-842, September.
    15. Lee, Ming-Tsung & Yeh, Chao-Fu, 2019. "Causal effects between bus revenue vehicle-kilometers and bus ridership," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 54-64.
    16. Wallimann, Hannes & Blättler, Kevin & von Arx, Widar, 2023. "Do price reductions attract customers in urban public transport? A synthetic control approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    17. George N. Botzoris, 2020. "Economic Crisis and its Impact on Sustainable Urban Transport," International Journal of Economics and Financial Issues, Econjournals, vol. 10(1), pages 33-41.
    18. Yaman, Firat & Offiaeli, Kingsley, 2022. "Is the price elasticity of demand asymmetric? Evidence from public transport demand," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 318-335.
    19. Nan Yang & Yong Long Lim, 2018. "Temporary Incentives Change Daily Routines: Evidence from a Field Experiment on Singapore’s Subways," Management Science, INFORMS, vol. 64(7), pages 3365-3379, July.
    20. Bouscasse, Hélène & de Lapparent, Matthieu, 2019. "Perceived comfort and values of travel time savings in the Rhône-Alpes Region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 370-387.

    More about this item

    Keywords

    ;
    ;
    ;

    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:cdl:uctcwp:qt5w9045hh. 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: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucbus.html .

    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.