IDEAS home Printed from https://ideas.repec.org/a/taf/ginixx/v28y2002i1p59-75.html
   My bibliography  Save this article

Modeling Selection Bias in Studies of Sanctions Efficacy

Author

Listed:
  • Irfan Nooruddin

Abstract

Sanctions rarely work but they continue to be used frequently by policymakers. I argue that previous studies of sanctions ignore the problem of strategic censoring by focusing only on cases of observed sanctions. In this paper, I develop a unified model of sanction imposition and success and test it using a simultaneous equation censored probit model. This selection-corrected sanction model finds that the process by which sanctions are imposed is linked to the process by which some succeed while others fail, and that the unmeasured factors that lead to sanction imposition are negatively related to their success.

Suggested Citation

  • Irfan Nooruddin, 2002. "Modeling Selection Bias in Studies of Sanctions Efficacy," International Interactions, Taylor & Francis Journals, vol. 28(1), pages 59-75, January.
  • Handle: RePEc:taf:ginixx:v:28:y:2002:i:1:p:59-75
    DOI: 10.1080/03050620210394
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03050620210394
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03050620210394?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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:taf:ginixx:v:28:y:2002:i:1:p:59-75. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/GINI20 .

    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.