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What Goes into a Medal: Women's Inclusion and Success at the Olympic Games

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  • Marcus Noland
  • Kevin Stahler

Abstract

This paper examines determinants of women's participation and performance in the Olympics. Female inclusion and success are not merely functions of size, wealth, and host advantage, but a more complex process involving the socioeconomic status of women and, more weakly, broad societal attitudes on gender issues. Female labor force participation and educational attainment in particular are tightly correlated with both participation and outcomes, even controlling for per capita income. Female educational attainment is strongly correlated with both the breadth of participation across sporting events and success in those events. Host countries and socialist states also are associated with unusually high levels of participation and medaling by female athletes. Medal performance is affected by large-scale boycotts. Opening competition to professionals may have leveled the playing field for poorer countries. But the historical record for women's medal achievement is utterly distorted by the doping program in the former East Germany, which specifically targeted women. At its peak in the 1970s and 1980s, the program was responsible for 17 percent of the medals awarded to women, equivalent to the medal hauls of the Soviet or American team in 1972, the last Olympics not marred by widespread abuse of performance-enhancing drugs.
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Suggested Citation

  • Marcus Noland & Kevin Stahler, 2016. "What Goes into a Medal: Women's Inclusion and Success at the Olympic Games," Social Science Quarterly, Southwestern Social Science Association, vol. 97(2), pages 177-196, June.
  • Handle: RePEc:bla:socsci:v:97:y:2016:i:2:p:177-196
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    File URL: http://hdl.handle.net/10.1111/ssqu.2016.97.issue-2
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    Cited by:

    1. 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.
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    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. 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.
    5. Marcus Noland, 2016. "Russian Doping in Sports," Working Paper Series WP16-4, Peterson Institute for International Economics.
    6. Barbara Kotschwar & Tyler Moran, 2015. "Pitching a Level Playing Field: Women and Leadership in Sports," Policy Briefs PB15-22, Peterson Institute for International Economics.

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    More about this item

    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • F53 - International Economics - - International Relations, National Security, and International Political Economy - - - International Agreements and Observance; International Organizations
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification

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