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What is behind fare evasion in urban bus systems? An econometric approach

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  • Guarda, Pablo
  • Galilea, Patricia
  • Paget-Seekins, Laurel
  • Ortúzar, Juan de Dios

Abstract

Fare evasion is a problem in many public transport systems around the world and policies to reduce it are generally aimed at improving control and increasing fines. We use an econometric approach to attempt explaining the high levels of evasion in Santiago, Chile, and guide public policy formulation to reduce this problem. In particular, a negative binomial count regression model allowed us to find that fare evasion rates on buses increase as: (i) more people board (or alight) at a given bus door, (ii) more passengers board by a rear door, (iii) buses have higher occupancy levels (and more doors) and (iv) passengers experience longer headways. By controlling these variables (ceteris paribus), results indicate that evasion is greater during the afternoon and evening, but it is not clear that it is higher during peak hours. Regarding socioeconomic variables, we found that fare evasion at bus stops located in higher income areas (municipalities) is significantly lower than in more deprived areas. Finally, based on our results we identified five main methods to address evasion as alternatives to more dedicated fine enforcement or increased inspection; (i) increasing the bus fleet, (ii) improving the bus headway regularity, (iii) implementing off-board payment stations, (iv) changing the payment system on board and (v) changing the bus design (number of doors or capacity). Our model provides a powerful tool to predict the reduction of fare evasion due to the implementation of some of these five operational strategies, and can be applied to other bus public transport systems.

Suggested Citation

  • Guarda, Pablo & Galilea, Patricia & Paget-Seekins, Laurel & Ortúzar, Juan de Dios, 2016. "What is behind fare evasion in urban bus systems? An econometric approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 84(C), pages 55-71.
  • Handle: RePEc:eee:transa:v:84:y:2016:i:c:p:55-71
    DOI: 10.1016/j.tra.2015.10.008
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    References listed on IDEAS

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    1. Bucciol, Alessandro & Landini, Fabio & Piovesan, Marco, 2013. "Unethical behavior in the field: Demographic characteristics and beliefs of the cheater," Journal of Economic Behavior & Organization, Elsevier, vol. 93(C), pages 248-257.
    2. Barabino, Benedetto & Salis, Sara & Useli, Bruno, 2013. "A modified model to curb fare evasion and enforce compliance: Empirical evidence and implications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 58(C), pages 29-39.
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    Cited by:

    1. Yousefzadeh Barri, Elnaz & Farber, Steven & Jahanshahi, Hadi & Beyazit, Eda, 2022. "Understanding transit ridership in an equity context through a comparison of statistical and machine learning algorithms," Journal of Transport Geography, Elsevier, vol. 105(C).
    2. Boyd, Colin, 2020. "Revisiting the foundations of fare evasion research," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 313-324.
    3. Felipe González & Carolina Busco & Katheryn Codocedo, 2019. "Fare Evasion in Public Transport: Grouping Transantiago Users’ Behavior," Sustainability, MDPI, vol. 11(23), pages 1-17, November.
    4. Ramos, Raúl & Silva, Hugo E., 2023. "Fare evasion in public transport: How does it affect the optimal design and pricing?," Transportation Research Part B: Methodological, Elsevier, vol. 176(C).
    5. Allen, Jaime & Muñoz, Juan Carlos & Ortúzar, Juan de Dios, 2019. "On evasion behaviour in public transport: Dissatisfaction or contagion?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 626-651.
    6. Celse, Jérémy & Grolleau, Gilles, 2023. "Fare evasion and information provision: What information should be provided to reduce fare-evasion?," Transport Policy, Elsevier, vol. 138(C), pages 119-128.
    7. Evgeny Alexandrovich Uvarov, 2020. "The Scale of the Shadow Economy in the Sphere of Urban and Suburban Passenger Transportation in Regions of Russia," Spatial Economics=Prostranstvennaya Ekonomika, Economic Research Institute, Far Eastern Branch, Russian Academy of Sciences (Khabarovsk, Russia), issue 2, pages 124-141.
    8. Guzman, Luis A. & Arellana, Julian & Camargo, José Pablo, 2021. "A hybrid discrete choice model to understand the effect of public policy on fare evasion discouragement in Bogotá's Bus Rapid Transit," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 140-153.
    9. Munizaga, Marcela A. & Gschwender, Antonio & Gallegos, Nestor, 2020. "Fare evasion correction for smartcard-based origin-destination matrices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 307-322.
    10. Delbosc, Alexa & Currie, Graham, 2016. "Cluster analysis of fare evasion behaviours in Melbourne, Australia," Transport Policy, Elsevier, vol. 50(C), pages 29-36.
    11. Gramsch, Benjamin & Guevara, C. Angelo & Munizaga, Marcela & Schwartz, Daniel & Tirachini, Alejandro, 2022. "The effect of dynamic lockdowns on public transport demand in times of COVID-19: Evidence from smartcard data," Transport Policy, Elsevier, vol. 126(C), pages 136-150.
    12. Nazam Ali & Shoichiro Nakayama & Hiromichi Yamaguchi, 2021. "Analysis of Bus Fare Structure to Observe Modal Shift, Operator Profit, and Land-Use Choices through Combined Unified Transport Model," Sustainability, MDPI, vol. 14(1), pages 1-17, December.
    13. Cantillo, Angel & Raveau, Sebastián & Muñoz, Juan Carlos, 2022. "Fare evasion on public transport: Who, when, where and how?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 156(C), pages 285-295.
    14. Porath, Keiko & Galilea, Patricia, 2020. "Temporal analysis of fare evasion in Transantiago: A socio-political view," Research in Transportation Economics, Elsevier, vol. 83(C).
    15. Troncoso, Rodrigo & de Grange, Louis, 2017. "Fare evasion in public transport: A time series approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 311-318.
    16. Brotcorne, L. & Escalona, P. & Fortz, B. & Labbé, M., 2021. "Fare inspection patrols scheduling in transit systems using a Stackelberg game approach," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 1-20.

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