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Gold, Silver, and Bronze: Determining National Success in Men’s and Women’s Summer Olympic Events

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  • Leeds Eva Marikova

    (Department of Economics and Business, Moravian College, Bethlehem, PA 18018, USA)

  • Leeds Michael A.

    (Department of Economics, Temple University, Philadelphia, PA 19122, USA.)

Abstract

We add to the literature on Olympic performance by explicitly studying the determinants of women’s performance at the Games.We estimate separate models of medal production for men and women over the last four Summer Olympic Games. The production of medals is a function of capital, labor, and total factor productivity (TFP). We use real GDP per capita and population - two variables that appear in almost all Olympic studies - as proxies for capital and labor. Our measure of TFP is a vector of variables that captures a nation’s willingness and ability to marshal its resources to promote Olympic performance and variables that determine its willingness to support its women. Because the dependent variable is a count measure, we estimate the production function using a negative binomial framework. We find that the determinants of success by a nation’s women closely resemble the determinants for its men. We also show that some determinants of gold medal counts differ from the determinants of silver and bronze medals. Our findings suggest that nations can improve the medal performance of men and women by following policies that increase the political and economic participation of women.

Suggested Citation

  • Leeds Eva Marikova & Leeds Michael A., 2012. "Gold, Silver, and Bronze: Determining National Success in Men’s and Women’s Summer Olympic Events," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(3), pages 279-292, June.
  • Handle: RePEc:jns:jbstat:v:232:y:2012:i:3:p:279-292
    DOI: 10.1515/jbnst-2012-0307
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    References listed on IDEAS

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    Cited by:

    1. Marcus Noland & Kevin Stahler, 2017. "An Old Boys Club No More," Journal of Sports Economics, , vol. 18(5), pages 506-536, June.
    2. Johan Rewilak, 2021. "The (non) determinants of Olympic success," Journal of Sports Economics, , vol. 22(5), pages 546-570, June.
    3. Schlembach, Christoph & Schmidt, Sascha L. & Schreyer, Dominik & Wunderlich, Linus, 2022. "Forecasting the Olympic medal distribution – A socioeconomic machine learning model," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    4. Carl Singleton & J. James Reade & Johan Rewilak & Dominik Schreyer, 2021. "How big is home advantage at the Olympic Games?," Economics Discussion Papers em-dp2021-13, Department of Economics, University of Reading.
    5. Marcus Noland & Kevin Stahler, 2016. "Asian Participation and Performance at the Olympic Games," Asian Economic Policy Review, Japan Center for Economic Research, vol. 11(1), pages 70-90, January.
    6. Frank Daumann & Florian Follert & Daniel Hamacher & Lasse Plöhn, 2023. "The early bird catches the worm: The impact of first‐mover advantage on long‐term elite team sport success," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(3), pages 1465-1475, April.
    7. Nicolas Scelles & Wladimir Andreff & Liliane Bonnal & Madeleine Andreff & Pascal Favard, 2020. "Forecasting National Medal Totals at the Summer Olympic Games Reconsidered," Social Science Quarterly, Southwestern Social Science Association, vol. 101(2), pages 697-711, March.
    8. Christian Pierdzioch & Eike Emrich, 2013. "A Note on Corruption and National Olympic Success," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 41(4), pages 405-411, December.
    9. Marcus Noland, 2016. "Russian Doping in Sports," Working Paper Series WP16-4, Peterson Institute for International Economics.
    10. Barth, Michael & Emrich, Eike & Daumann, Frank, 2017. "Evaluation of sporting success in Austria: An institutional economics analysis," Working Papers of the European Institute for Socioeconomics 20, European Institute for Socioeconomics (EIS), Saarbrücken.

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