IDEAS home Printed from https://ideas.repec.org/a/cem/jaecon/v20y2017n1p1-28.html

Man vs. machine: An investigation of speeding ticket disparities based on gender and race

Author

Listed:
  • Sarah Marx Quintanar

    (University of Arkansas at Little Rock)

Abstract

This paper analyzes the extent to which police behavior in giving speeding tickets differs from the ticketing pattern of automated cameras, which provide an estimate of the population of speeders. The novel data are obtained from Lafayette, Louisiana court records, and provide specific details about the ticketed driver as well as a wide range of violation characteristics. In contrast to the automated cameras, the probability of a ticketed driver being female is consistently and significantly higher when the ticket was given by a police officer. For African-American drivers this effect is less robust, though in general still positive and significant. This implies that police use gender and race as a determining factor in issuing a speeding ticket. Potential behavioral reasons for this outcome are discussed. The validity of using automated cameras as a population measure for police-issued tickets is thoroughly investigated and supportive evidence is provided.

Suggested Citation

  • Sarah Marx Quintanar, 2017. "Man vs. machine: An investigation of speeding ticket disparities based on gender and race," Journal of Applied Economics, Universidad del CEMA, vol. 20, pages 1-28, May.
    • Handle: RePEc:cem:jaecon:v:20:y:2017:n:1:p:1-28
    as

    Download full text from publisher

    File URL: https://ucema.edu.ar/publicaciones/download/volume20/quintanar.pdf
    File Function: Paper
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. Khondoker Billah & Hatim O. Sharif & Samer Dessouky, 2022. "How Gender Affects Motor Vehicle Crashes: A Case Study from San Antonio, Texas," Sustainability, MDPI, vol. 14(12), pages 1-21, June.
    2. Mahdie Asl-Javadian & Mahmoud Mesbah & Masoud Foroutan Shad, 2024. "How are traffic fines affected by the driver’s car price and the police officer’s discretion? A case study of Isfahan, Iran," Journal of Computational Social Science, Springer, vol. 7(1), pages 1019-1038, April.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

    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:cem:jaecon:v:20:y:2017:n:1:p:1-28. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Lucila Solla (email available below). General contact details of provider: https://edirc.repec.org/data/cemaaar.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.