IDEAS home Printed from https://ideas.repec.org/a/oup/amlawe/v20y2018i2p512-535..html
   My bibliography  Save this article

Statistical (and Racial) Discrimination, “Ban the Box”, and Crime Rates

Author

Listed:
  • Murat C Mungan

Abstract

This article studies interactions between criminal behavior and employment dynamics in a setting where employees belong to one of two groups. Employers can statistically discriminate based on group membership as well as criminal records. It first shows that “self-fulfilling expectations” cannot exist when there are diminishing returns to deterrence from increasing expected sanctions. This eliminates the possibility of multiple equilibria within groups, and suggests that statistical discrimination by employers can only be motivated by differences across groups’ criminal tendencies. This type of statistical discrimination typically leads to an increase in crime, and the article identifies sufficient conditions for this result. This suggests that societies in which group membership is salient (e.g. due to racial heterogeneity) are, ceteris paribus, likely to have higher crime rates. Attempting to fix the negative impacts of statistical discrimination through policies that reduce the visibility of criminal records (e.g. ban the box) increases crime further. Moreover, such policies cause greater negative effects for law abiding members of the higher-criminal-tendency group, which is consistent with the unintended consequences associated with ban the box campaigns discussed in the empirical literature.

Suggested Citation

  • Murat C Mungan, 2018. "Statistical (and Racial) Discrimination, “Ban the Box”, and Crime Rates," American Law and Economics Review, American Law and Economics Association, vol. 20(2), pages 512-535.
  • Handle: RePEc:oup:amlawe:v:20:y:2018:i:2:p:512-535.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/aler/ahy008
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:oup:amlawe:v:20:y:2018:i:2:p:512-535.. 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/aler .

    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.