IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0315054.html

Evaluation of Global South’s efficiency at the Summer Olympics

Author

Listed:
  • Julian Alexander Klöcker
  • Frank Daumann

Abstract

States differ significantly in international sports competitions in how they use the resources they have and whether they do so in an efficient manner. In this paper, we investigate the efficiency of the nations from the so-called “Global South”, in total 52 states, during the 2000–2024 Summer Olympics. By doing this, our paper is the first using the Bayesian stochastic frontier analysis for exploring the performance of the states of the Global South. We perform an age decomposition, which shows that the 25–29 and 30–34 age cohorts contribute the most to Olympic performance. Our findings also suggests that transient efficiencies are higher than persistent efficiencies in a majority of the analyzed nations. Our analysis represents an important contribution in analyzing developing states‘ efficiency in elite sports.

Suggested Citation

  • Julian Alexander Klöcker & Frank Daumann, 2025. "Evaluation of Global South’s efficiency at the Summer Olympics," PLOS ONE, Public Library of Science, vol. 20(1), pages 1-17, January.
    • Handle: RePEc:plo:pone00:0315054
    DOI: 10.1371/journal.pone.0315054
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0315054
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0315054&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0315054?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
    ---><---

    References listed on IDEAS

    as
    1. Nguyen Khac Minh & Giang Thanh Long, 2008. "Factor productivity and efficiency of the Vietnamese economy in transition," Asia-Pacific Development Journal, United Nations Economic and Social Commission for Asia and the Pacific (ESCAP), vol. 15(1), pages 93-117, June.
    2. Eike Emrich & Markus Klein & Werner Pitsch & Christian Pierdzioch, 2012. "On the determinants of sporting success – A note on the Olympic Games," Economics Bulletin, AccessEcon, vol. 32(3), pages 1890-1901.
    3. S Lozano & G Villa & F Guerrero & P Cortés, 2002. "Measuring the performance of nations at the Summer Olympics using data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(5), pages 501-511, May.
    4. Kamil Makieła & Błażej Mazur, 2020. "Bayesian Model Averaging and Prior Sensitivity in Stochastic Frontier Analysis," Econometrics, MDPI, vol. 8(2), pages 1-22, April.
    5. Johann Graf Lambsdorff, 2003. "How Corruption Affects Productivity," Kyklos, Wiley Blackwell, vol. 56(4), pages 457-474, November.
    6. Bernd Frick & Robert Simmons, 2008. "The impact of managerial quality on organizational performance: evidence from German soccer," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 29(7), pages 593-600.
    7. Gary Koop & Mark F J Steel, 1999. "Bayesian Analysis of Stochastic Frontier Models," Edinburgh School of Economics Discussion Paper Series 19, Edinburgh School of Economics, University of Edinburgh.
    8. Skevas, Ioannis, 2024. "Accounting for technology heterogeneity in the measurement of persistent and transient inefficiency," Economic Modelling, Elsevier, vol. 137(C).
    9. C. P. Barros & G. Rossi, 2014. "A Bayesian stochastic frontier of Italian football," Applied Economics, Taylor & Francis Journals, vol. 46(20), pages 2398-2407, July.
    10. Chen, Hong & Wang, Xi & Singh, Baljeet, 2021. "Transient and persistent inefficiency traps in Chinese provinces," Economic Modelling, Elsevier, vol. 97(C), pages 335-347.
    11. Pranab Bardhan, 1997. "Corruption and Development: A Review of Issues," Journal of Economic Literature, American Economic Association, vol. 35(3), pages 1320-1346, September.
    12. van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April.
    13. Leo Kahane, 2005. "Production Efficiency and Discriminatory Hiring Practices in the National Hockey League: A Stochastic Frontier Approach," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 27(1), pages 47-71, August.
    14. Ralph Ramos & Veerle De Bosscher & Aurélie Pankowiak & Christian Wisdom Valleser, 2023. "Contexts shaping the development and success of elite sport systems: a scoping review," Sport Management Review, Taylor & Francis Journals, vol. 26(5), pages 649-676, October.
    15. T. Potts, 2014. "Governance, corruption and Olympic success," Applied Economics, Taylor & Francis Journals, vol. 46(31), pages 3882-3891, November.
    16. Luis Antonio Andrade Rosas, 2019. "Quantitative and qualitative impact of GDP on sport performance and its relation with corruption and other social factors," Nóesis. Revista de Ciencias Sociales y Humanidades, Nóesis. Revista de Ciencias Sociales y Humanidades, vol. 28, pages 15-37, 55.
    17. 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.
    18. Barros, Carlos Pestana & Assaf, A.George & de Araujo, Ari Francisco, 2011. "Cost performance of Brazilian soccer clubs: A Bayesian varying efficiency distribution model," Economic Modelling, Elsevier, vol. 28(6), pages 2730-2735.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. C. P. Barros & O. H. dos S. Figueiredo & Silvestre Dumbo, 2016. "A performance assessment of the Angolan soccer league," Applied Economics, Taylor & Francis Journals, vol. 48(29), pages 2711-2720, June.
    3. Carlos Pestana Barros & Peter Wanke & Otávio Figueiredo, 2015. "The Brazilian Soccer Championship: an efficiency analysis," Applied Economics, Taylor & Francis Journals, vol. 47(9), pages 906-915, February.
    4. C. P. Barros & Dércio Mandlaze & Scott Tainsky, 2016. "The efficiency of Mozambique soccer league: the Moçambola," Applied Economics, Taylor & Francis Journals, vol. 48(31), pages 2965-2971, July.
    5. Maria Kravtsova & Aleksey Oshchepkov, 2019. "Market And Network Corruption," HSE Working papers WP BRP 209/EC/2019, National Research University Higher School of Economics.
    6. Gerd Muehlheusser & Sandra Schneemann & Dirk Sliwka & Niklas Wallmeier, 2018. "The Contribution of Managers to Organizational Success," Journal of Sports Economics, , vol. 19(6), pages 786-819, August.
    7. Dzhumashev, Ratbek, 2014. "Corruption and growth: The role of governance, public spending, and economic development," Economic Modelling, Elsevier, vol. 37(C), pages 202-215.
    8. 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.
    9. Lakshmi, Geeta & Saha, Shrabani & Bhattarai, Keshab, 2021. "Does corruption matter for stock markets? The role of heterogeneous institutions," Economic Modelling, Elsevier, vol. 94(C), pages 386-400.
    10. Li, Yongjun & Liang, Liang & Chen, Yao & Morita, Hiroshi, 2008. "Models for measuring and benchmarking olympics achievements," Omega, Elsevier, vol. 36(6), pages 933-940, December.
    11. Miguel Jara & Dimitri Paolini & Juan Dios Tena Horrillo, 2015. "Management Efficiency in Football: An Empirical Analysis of Two Extreme Cases," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 36(5), pages 286-298, July.
    12. Méon, Pierre-Guillaume & Weill, Laurent, 2010. "Is Corruption an Efficient Grease?," World Development, Elsevier, vol. 38(3), pages 244-259, March.
    13. Carlos Pestana Barros & Gaël Bertrand & Laurent Botti & Scott Tainsky, 2014. "Cost efficiency of French rugby clubs," Applied Economics, Taylor & Francis Journals, vol. 46(23), pages 2721-2732, August.
    14. 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.
    15. Young Hoon Lee, 2009. "Frontier Models and their Application to the Sports Industry," Working Papers 0903, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised 2009.
    16. 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).
    17. 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.
    18. Salinas-Jimenez, M del Mar & Salinas-Jimenez, Javier, 2007. "Corruption, efficiency and productivity in OECD countries," Journal of Policy Modeling, Elsevier, vol. 29(6), pages 903-915.
    19. Leonardo Becchetti & Luca Corazzini & Vittorio Pelligra, 2021. "Trust and Trustworthiness in Corrupted Economic Environments," Games, MDPI, vol. 12(1), pages 1-26, February.
    20. 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.

    More about this item

    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:plo:pone00:0315054. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.