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Economic development as major determinant of Olympic medal wins: predicting performances of Russian and Chinese teams at Sochi Games

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  • Wladimir Andreff

Abstract

Starting from an econometric model successfully used to explain and then predict the distribution of medal wins across nations at the Beijing Summer Olympics, a similar model is elaborated on with some different explanatory variables for estimating the determinants of medals won per nation at Winter Games. A Tobit estimation of the model based on data from 1964 to 2010 shows that GDP per capita, population, the endowment in ski and winter sports resorts, and a host country dummy are significant determinants of medal wins at Winter Olympics. Then the estimated model is used for predicting the sporting outcomes at the 2014 Sochi Games with a focus on Russia and China. The Russian team is expected to perform better than in Vancouver 2010 and to be ranked fourth behind the USA, Germany and Canada while the Chinese team would be ranked ninth, a performance doomed to improve in the future given China's swift economic development.

Suggested Citation

  • Wladimir Andreff, 2013. "Economic development as major determinant of Olympic medal wins: predicting performances of Russian and Chinese teams at Sochi Games," International Journal of Economic Policy in Emerging Economies, Inderscience Enterprises Ltd, vol. 6(4), pages 314-340.
    • Handle: RePEc:ids:ijepee:v:6:y:2013:i:4:p:314-340
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    Citations

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    Cited by:

    1. Johan Rewilak, 2021. "The (non) determinants of Olympic success," Journal of Sports Economics, , vol. 22(5), pages 546-570, June.
    2. Todd B. Potts, 2022. "Does it pay to Play by the Rules? Respect for Rule of law, Control of Corruption, and National Success at the Summer Olympics," Journal of Sports Economics, , vol. 23(2), pages 222-245, February.
    3. 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.
    4. Pedro Garcia‐del‐Barrio & Carlos Gomez‐Gonzalez & José Manuel Sánchez‐Santos, 2020. "Popularity and Visibility Appraisals for Computing Olympic Medal Rankings," Social Science Quarterly, Southwestern Social Science Association, vol. 101(5), pages 2137-2157, September.
    5. Marcus Noland, 2016. "Russian Doping in Sports," Working Paper Series WP16-4, Peterson Institute for International Economics.

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