IDEAS home Printed from
MyIDEAS: Login to save this article or follow this journal

Intelligence and bribing behavior in a one-shot game

  • Shaw, Philip
  • Vásquez, William F.
  • LeClair, Mark
Registered author(s):

    We investigate the relationship between intelligence and bribing behavior in a simple one-shot game of corruption. We find a robust relationship between intelligence and the probability of bribing in which a higher intelligence quotient (IQ) leads to a lower probability of bribing in the game. This result holds after controlling for other determinants such as gender, attitude toward corruption, and perceptions of corruption. By revealing the gender of the matched player, we also show that gender perceptions of corruption are strong determinants of bribery.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Article provided by Elsevier in its journal Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics).

    Volume (Year): 44 (2013)
    Issue (Month): C ()
    Pages: 91-96

    in new window

    Handle: RePEc:eee:soceco:v:44:y:2013:i:c:p:91-96
    Contact details of provider: Web page:

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    as in new window
    1. Gachter, Simon & Herrmann, Benedikt & Thoni, Christian, 2004. "Trust, voluntary cooperation, and socio-economic background: survey and experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 55(4), pages 505-531, December.
    2. Dyer, Douglas & Kagel, John H & Levin, Dan, 1989. "A Comparison of Naive and Experienced Bidders in Common Value Offer Auctions: A Laboratory Analysis," Economic Journal, Royal Economic Society, vol. 99(394), pages 108-15, March.
    3. Potrafke, Niklas, 2012. "Intelligence and corruption," Munich Reprints in Economics 19275, University of Munich, Department of Economics.
    4. Vivi Alatas & Lisa Cameron & Ananish Chaudhuri & Nisvan Erkal & Lata Gangadharan, 2006. "Subject Pool Effects in a Corruption Experiment: A Comparison of Indonesian Public Servants and Indonesian Students," Department of Economics - Working Papers Series 975, The University of Melbourne.
    5. Anand V. Swamy & Stephen Knack & Young Lee & Omar Azfar, 2000. "Gender and Corruption," Department of Economics Working Papers 2000-10, Department of Economics, Williams College.
    6. Abigail Barr & Danila Serra, 2008. "The effects of externalities and framing on bribery in a petty corruption experiment," CSAE Working Paper Series 2008-24, Centre for the Study of African Economies, University of Oxford.
    7. Barr, Abigail & Serra, Danila, 2010. "Corruption and culture: An experimental analysis," Journal of Public Economics, Elsevier, vol. 94(11-12), pages 862-869, December.
    8. Kamei, Kenju, 2012. "From locality to continent: A comment on the generalization of an experimental study," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 41(2), pages 207-210.
    9. Jakob Svensson, 2003. "Who Must Pay Bribes and How Much? Evidence from a Cross Section of Firms," The Quarterly Journal of Economics, Oxford University Press, vol. 118(1), pages 207-230.
    10. Dimitrova-Grajzl, Valentina & Grajzl, Peter & Guse, A. Joseph, 2012. "Trust, perceptions of corruption, and demand for regulation: Evidence from post-socialist countries," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 41(3), pages 292-303.
    11. Armantier, Olivier & Boly, Amadou, 2011. "A controlled field experiment on corruption," European Economic Review, Elsevier, vol. 55(8), pages 1072-1082.
    12. Toke S. Aidt, 2003. "Economic analysis of corruption: a survey," Economic Journal, Royal Economic Society, vol. 113(491), pages F632-F652, November.
    13. Kahana, Nava & Qijun, Liu, 2010. "Endemic corruption," European Journal of Political Economy, Elsevier, vol. 26(1), pages 82-88, March.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:eee:soceco:v:44:y:2013:i:c:p:91-96. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.