IDEAS home Printed from https://ideas.repec.org/p/isu/genstf/200303010800001211.html
   My bibliography  Save this paper

Can Racially Unbiased Police Perpetuate Long-Run Discrimination?

Author

Listed:
  • Bunzel, Helle
  • Marcoul, Philippe

Abstract

We develop a stylized dynamic model of highway policing in which a non-racist police officer exhibits a cognitive bias: relative overconfidence. The officer is given incentives to arrest criminals but faces a per stop cost which increases when the racial mix of her stops differs from that of the population. Every period, she observes the racial composition of jail inmates (generated from arrests made by her peers) and forms estimates about the crime rates of each race. In some settings, her overconfidence leads her to overestimate the crime rate of one race relative to another causing the long-run racial composition of the jail population to deviate from the “fair” one (one where the racial mix in jails is identical to that in the criminal population). We compare this to a situation where officers have detailed stop data on each race, similar to data being currently collected in many US states.

Suggested Citation

  • Bunzel, Helle & Marcoul, Philippe, 2003. "Can Racially Unbiased Police Perpetuate Long-Run Discrimination?," ISU General Staff Papers 200303010800001211, Iowa State University, Department of Economics.
  • Handle: RePEc:isu:genstf:200303010800001211
    as

    Download full text from publisher

    File URL: https://dr.lib.iastate.edu/server/api/core/bitstreams/969128b8-57ed-4957-b853-cdfb6cc15030/content
    Download Restriction: no
    ---><---

    More about this item

    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:isu:genstf:200303010800001211. 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: Curtis Balmer (email available below). General contact details of provider: https://edirc.repec.org/data/deiasus.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.