IDEAS home Printed from https://ideas.repec.org/p/gwc/wpaper/2013-005.html
   My bibliography  Save this paper

Using Forecasting to Detect Corruption in International Football

Author

Listed:
  • J. James Reade

    () (University of Birmingham)

  • Sachiko Akie

    (Akita International University)

Abstract

Corruption is hidden action aimed at influencing the outcome of an event away from its competitive outcome. It is likely common in all walks of life yet its hidden nature makes it diffcult to detect, while its distortionary influence on resource allocation ensures the importance of trying to detect it both practically and economically. This paper further develops methods to detect corrupt activity using data from 63 bookmakers covering over 9,000 international football matches since 2004, in particular assessing a claim made in early 2013 by Europol that the outcomes of almost 300 international matches since 2009 were fixed. We explore the divergence between two kinds of forecasts of match outcomes: those by bookmakers, and those constructed by econometric models. We argue that in the absence of corrupt activity to fix outcomes these two forecasts should be indistinguishable as they are based on the same information sets, and hence any divergence between the two may be indicative of corrupt activity to fix matches. In the absence of corroborating evidence we cannot declare any evidence procured in our manner as conclusive regarding the existence or otherwise of corruption, but nonetheless we argue that is it indicative. We conclude that there is mild evidence regarding potentially corrupt outcomes, and we also point towards yet more advanced strategies for its detection.

Suggested Citation

  • J. James Reade & Sachiko Akie, 2013. "Using Forecasting to Detect Corruption in International Football," Working Papers 2013-005, The George Washington University, Department of Economics, Research Program on Forecasting.
  • Handle: RePEc:gwc:wpaper:2013-005
    as

    Download full text from publisher

    File URL: https://www2.gwu.edu/~forcpgm/2013-005.pdf
    File Function: First version, 2013
    Download Restriction: no

    References listed on IDEAS

    as
    1. Manski, Charles F., 2006. "Interpreting the predictions of prediction markets," Economics Letters, Elsevier, vol. 91(3), pages 425-429, June.
    2. Karen Croxson & J. James Reade, 2011. "Exchange vs Dealers: A High-Frequency Analysis of In-Play Betting Prices," Discussion Papers 11-19, Department of Economics, University of Birmingham.
    3. Gary S. Becker, 1974. "Crime and Punishment: An Economic Approach," NBER Chapters,in: Essays in the Economics of Crime and Punishment, pages 1-54 National Bureau of Economic Research, Inc.
    4. Lewis, Jeffrey B. & Linzer, Drew A., 2005. "Estimating Regression Models in Which the Dependent Variable Is Based on Estimates," Political Analysis, Cambridge University Press, vol. 13(04), pages 345-364, September.
    5. Wolfers, Justin & Zitzewitz, Eric, 2006. "Interpreting Prediction Market Prices as Probabilities," IZA Discussion Papers 2092, Institute for the Study of Labor (IZA).
    6. Forrest, David & Goddard, John & Simmons, Robert, 2005. "Odds-setters as forecasters: The case of English football," International Journal of Forecasting, Elsevier, vol. 21(3), pages 551-564.
    7. Olmo, Jose & Pilbeam, Keith & Pouliot, William, 2011. "Detecting the presence of insider trading via structural break tests," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2820-2828, November.
    8. Preston, Ian & Szymanski, Stefan, 2000. "Racial Discrimination in English Football," Scottish Journal of Political Economy, Scottish Economic Society, vol. 47(4), pages 342-363, September.
    9. Stefani Ray & Pollard Richard, 2007. "Football Rating Systems for Top-Level Competition: A Critical Survey," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 3(3), pages 1-22, July.
    10. Hvattum, Lars Magnus & Arntzen, Halvard, 2010. "Using ELO ratings for match result prediction in association football," International Journal of Forecasting, Elsevier, vol. 26(3), pages 460-470, July.
    11. Leitner, Christoph & Zeileis, Achim & Hornik, Kurt, 2010. "Forecasting sports tournaments by ratings of (prob)abilities: A comparison for the EUROƂ 2008," International Journal of Forecasting, Elsevier, vol. 26(3), pages 471-481, July.
    12. Justin Wolfers, 2006. "Point Shaving: Corruption in NCAA Basketball," American Economic Review, American Economic Association, vol. 96(2), pages 279-283, May.
    13. Goddard, John, 2005. "Regression models for forecasting goals and match results in association football," International Journal of Forecasting, Elsevier, vol. 21(2), pages 331-340.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Alasdair Brown & Fuyu Yang, 2014. "Have Betting Exchanges Corrupted Horse Racing?," University of East Anglia Applied and Financial Economics Working Paper Series 066, School of Economics, University of East Anglia, Norwich, UK..

    More about this item

    Keywords

    Corruption; Forecasting Models; Information and Knowledge;

    JEL classification:

    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    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:gwc:wpaper:2013-005. 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: (Tara M. Sinclair). General contact details of provider: http://edirc.repec.org/data/degwuus.html .

    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 CitEc recognized a reference but did not link an item in RePEc 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 RePEc Author Service 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.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.