IDEAS home Printed from https://ideas.repec.org/p/hal/cesptp/hal-03206951.html
   My bibliography  Save this paper

Forecasting National Medal Totals at the Summer Olympic Games Reconsidered

Author

Listed:
  • Nicolas Scelles

    (MMU - Manchester Metropolitan University)

  • Wladimir Andreff

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, UP1 - Université Paris 1 Panthéon-Sorbonne)

  • Liliane Bonnal

    (UFR Sciences économiques [Poitiers] - Université de Poitiers – Faculté de Sciences économiques - UP - Université de Poitiers = University of Poitiers, CRIEF [Poitiers] - Centre de recherche sur l'intégration économique et financière - UP - Université de Poitiers = University of Poitiers)

  • Madeleine Andreff

    (Université Gustave Eiffel)

  • Pascal Favard

    (IRJI - Institut de recherche juridique interdisciplinaire - UT - Université de Tours)

Abstract

This article aims at explaining national medal totals at the 1992–2016 Summer Olympic Games (n = 1,289 observations) and forecasting them in 2016 (based on 1992–2012 data) and 2020 with a set of variables similar to previous studies, as well as a regional (subcontinents) variable not tested previously in the literature in English.

Suggested Citation

  • Nicolas Scelles & Wladimir Andreff & Liliane Bonnal & Madeleine Andreff & Pascal Favard, 2020. "Forecasting National Medal Totals at the Summer Olympic Games Reconsidered," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03206951, HAL.
    • Handle: RePEc:hal:cesptp:hal-03206951
    DOI: 10.1111/ssqu.12782
    Note: View the original document on HAL open archive server: https://hal.science/hal-03206951v1
    as

    Download full text from publisher

    File URL: https://hal.science/hal-03206951v1/document
    Download Restriction: no
    File URL: https://libkey.io/10.1111/ssqu.12782?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Aaron Lowen & Robert O. Deaner & Erika Schmitt, 2016. "Guys and Gals Going for Gold," Journal of Sports Economics, , vol. 17(3), pages 260-285, April.
    4. Forrest, David & Sanz, Ismael & Tena, J.D., 2010. "Forecasting national team medal totals at the Summer Olympic Games," International Journal of Forecasting, Elsevier, vol. 26(3), pages 576-588, July.
    5. Vagenas, George & Vlachokyriakou, Eleni, 2012. "Olympic medals and demo-economic factors: Novel predictors, the ex-host effect, the exact role of team size, and the “population-GDP” model revisited," Sport Management Review, Elsevier, vol. 15(2), pages 211-217.
    6. Pravin K. Trivedi & David M. Zimmer, 2014. "Success at the Summer Olympics: How Much Do Economic Factors Explain?," Econometrics, MDPI, vol. 2(4), pages 1-34, December.
    7. Andrew B. Bernard & Meghan R. Busse, 2004. "Who Wins the Olympic Games: Economic Resources and Medal Totals," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 413-417, February.
    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. David Forrest & J. D. Tena & Carlos Varela-Quintana, 2023. "The influence of schooling on performance in chess and at the Olympics," Empirical Economics, Springer, vol. 64(2), pages 959-982, February.
    2. Christoph Schlembach & Sascha L. Schmidt & Dominik Schreyer & Linus Wunderlich, 2020. "Forecasting the Olympic medal distribution during a pandemic: a socio-economic machine learning model," Papers 2012.04378, arXiv.org, revised Jun 2021.
    3. 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.
    4. Franklin G. Mixon Jr. & Richard J. Cebula, 2022. "Property Rights Freedom and Innovation: Eponymous Skills in Women's Gymnastics," Journal of Sports Economics, , vol. 23(4), pages 407-430, May.
    5. 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).
    6. Emilio Gómez-Déniz & Nancy Dávila-Cárdenes & Alejandro Leiva-Arcas & María J. Martínez-Patiño, 2021. "Measuring Efficiency in the Summer Olympic Games Disciplines: The Case of the Spanish Athletes," Mathematics, MDPI, vol. 9(21), pages 1-15, October.
    7. David Forrest & J.D Tena & Carlos Varela-Quintana, 2020. "Who wins at the Chess Olympics? The role of resources and education capital," Working Papers 202013, University of Liverpool, Department of Economics.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. Marcus Noland, 2016. "Russian Doping in Sports," Working Paper Series WP16-4, Peterson Institute for International Economics.
    3. Johan Rewilak, 2021. "The (non) determinants of Olympic success," Journal of Sports Economics, , vol. 22(5), pages 546-570, June.
    4. 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.
    5. Martin Grancay & Tomas Dudas, 2018. "Olympic Medals, Economy, Geography and Politics from Sydney to Rio," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 22(2), pages 409-441, Spring.
    6. Marcus Noland & Kevin Stahler, 2017. "An Old Boys Club No More," Journal of Sports Economics, , vol. 18(5), pages 506-536, June.
    7. Yun Hyeong Choi & Qingyuan Wei & Luyao Zhang & Seong-Jin Choi, 2022. "The Impact of Cultural Distance on Performance at the Summer Olympic Games," SAGE Open, , vol. 12(1), pages 21582440221, March.
    8. 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.
    9. Franklin G. Mixon Jr. & Richard J. Cebula, 2022. "Property Rights Freedom and Innovation: Eponymous Skills in Women's Gymnastics," Journal of Sports Economics, , vol. 23(4), pages 407-430, May.
    10. 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.
    11. Wladimir Andreff, 2012. "Is Hosting the Games Enough to Win? A predictive economic model of medal wins at 2014 Winter Olympics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00794057, HAL.
    12. Alexandre de Cássio Rodrigues & Carlos Alberto Gonçalves & Tiago Silveira Gontijo, 2019. "A two-stage DEA model to evaluate the efficiency of countries at the Rio 2016 Olympic Games," Economics Bulletin, AccessEcon, vol. 39(2), pages 1538-1545.
    13. David Forrest & J. D. Tena & Carlos Varela-Quintana, 2023. "The influence of schooling on performance in chess and at the Olympics," Empirical Economics, Springer, vol. 64(2), pages 959-982, February.
    14. David Forrest & Adams Ceballos & Ramón Flores & Ian G. McHale & Ismael Sanz & J.D. Tena, 2012. "Explaining and Forecasting National Team Medals Totals at the Summer Olympic Games," Chapters, in: Wolfgang Maennig & Andrew Zimbalist (ed.), International Handbook on the Economics of Mega Sporting Events, chapter 13, Edward Elgar Publishing.
    15. Emilio Gómez-Déniz & Nancy Dávila-Cárdenes & Alejandro Leiva-Arcas & María J. Martínez-Patiño, 2021. "Measuring Efficiency in the Summer Olympic Games Disciplines: The Case of the Spanish Athletes," Mathematics, MDPI, vol. 9(21), pages 1-15, October.
    16. Xuepeng Liu & Emanuel Ornelas & Huimin Shi, 2024. "Was COVID-19 a Game Changer for the Tokyo and Beijing Olympics?," Journal of Sports Economics, , vol. 25(7), pages 866-886, October.
    17. M. Flegl & L. A. Andrade, 2018. "Measuring countries’ performance at the Summer Olympic Games in Rio 2016," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 823-846, November.
    18. 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.
    19. 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.
    20. Javier Otamendi & Luis M. Doncel, 2014. "Medal Shares in Winter Olympic Games by Sport: Socioeconomic Analysis After Vancouver 2010," Social Science Quarterly, Southwestern Social Science Association, vol. 95(2), pages 598-614, June.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hal:cesptp:hal-03206951. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.