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Measuring and Controlling Subway Fare Evasion: Improving Safety and Security at New York City Transit Authority

Author

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  • Reddy, Alla V.
  • Kuhls, Jacqueline
  • Lu, Alex

Abstract

New York City Transit (NYCT) has a comprehensive framework for assessing, managing, and combating subway fare evasion. The automated fare collection (AFC) system, implemented 1994~97, features lessons learned from field trials of prototypes specifically designed to limit fare abuse. Subway crime has decreased 68% since 2000, and annual average subway evasion rate remains low at approximately 1.3%. Today, the Authority measures fare evasion with independent silent observers using stratified random sampling techniques, classifying passenger entries into 19 categories. Evasion rate peaks at 3pm due to students dismissal, otherwise hovers around 0.9% peak, 1.9% off-peak. Busy times and locations have higher evasions per hour but lower evasions per passenger. More evasions occur in lower-income neighbourhoods. Staff presence apparently doesn’t reduce evasions. Results are released to the press on request, promoting transparency and accountability. To combat evasion, NYCT increased fines from 60 to 100 U.S. dollars in 2008. Police issued 68,000 summonses and made 19,000 evasion arrests in 2009. Arrests are a more effective deterrent than summonses; the proportion of arrests versus summonses increased in 2010. Video monitoring equipment is used to identify and apprehend chronic fare abusers, particularly “swipers” who sell subway entries by abusing unlimited fare media.

Suggested Citation

  • Reddy, Alla V. & Kuhls, Jacqueline & Lu, Alex, 2011. "Measuring and Controlling Subway Fare Evasion: Improving Safety and Security at New York City Transit Authority," SocArXiv jrx4u, Center for Open Science.
  • Handle: RePEc:osf:socarx:jrx4u
    DOI: 10.31219/osf.io/jrx4u
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    Cited by:

    1. Krembsler, Jonas & Spiegelberg, Sandra & Hasenfelder, Richard & Kämpf, Nicki Lena & Winter, Thomas & Winter, Nicola & Knappe, Robert, 2024. "Fare revenue forecast in public transport: A comparative case study," Research in Transportation Economics, Elsevier, vol. 105(C).

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