IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v43y2021ics1544612321000738.html
   My bibliography  Save this article

Using Soccer Games as an Instrument to Forecast the Spread of COVID-19 in Europe

Author

Listed:
  • Gómez, Juan-Pedro
  • Mironov, Maxim

Abstract

We provide strong empirical support for the contribution of soccer games held in Europe to the spread of the COVID-19 virus in March 2020. We analyze more than 1,000 games across 194 regions from 10 European countries. Daily cases of COVID-19 grow significantly faster in regions where at least one soccer game took place two weeks earlier, consistent with the existence of an incubation period. These results weaken as we include stadiums with smaller capacity. We discuss the relevance of these variables as instruments for the identification of the causal effect of COVID-19 on firms, the economy, and financial markets.

Suggested Citation

  • Gómez, Juan-Pedro & Mironov, Maxim, 2021. "Using Soccer Games as an Instrument to Forecast the Spread of COVID-19 in Europe," Finance Research Letters, Elsevier, vol. 43(C).
    • Handle: RePEc:eee:finlet:v:43:y:2021:i:c:s1544612321000738
    DOI: 10.1016/j.frl.2021.101992
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612321000738
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2021.101992?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Alex Edmans & Diego García & Øyvind Norli, 2007. "Sports Sentiment and Stock Returns," Journal of Finance, American Finance Association, vol. 62(4), pages 1967-1998, August.
    2. Dhaval M. Dave & Andrew I. Friedson & Drew McNichols & Joseph J. Sabia, 2020. "The Contagion Externality of a Superspreading Event: The Sturgis Motorcycle Rally and COVID-19," NBER Working Papers 27813, National Bureau of Economic Research, Inc.
    3. Nikolaou, Paraskevas & Dimitriou, Loukas, 2020. "Identification of critical airports for controlling global infectious disease outbreaks: Stress-tests focusing in Europe," Journal of Air Transport Management, Elsevier, vol. 85(C).
    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. Iyer, Subramanian Rama & Simkins, Betty J., 2022. "COVID-19 and the Economy: Summary of research and future directions," Finance Research Letters, Elsevier, vol. 47(PB).
    2. Jonas Dehning & Sebastian B. Mohr & Sebastian Contreras & Philipp Dönges & Emil N. Iftekhar & Oliver Schulz & Philip Bechtle & Viola Priesemann, 2023. "Impact of the Euro 2020 championship on the spread of COVID-19," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

    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. Wright, Austin L. & Sonin, Konstantin & Driscoll, Jesse & Wilson, Jarnickae, 2020. "Poverty and economic dislocation reduce compliance with COVID-19 shelter-in-place protocols," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 544-554.
    2. Jeffrey E. Harris, 2020. "Geospatial Analysis of the September 2020 Coronavirus Outbreak at the University of Wisconsin – Madison: Did a Cluster of Local Bars Play a Critical Role?," NBER Working Papers 28132, National Bureau of Economic Research, Inc.
    3. Stefano DellaVigna, 2009. "Psychology and Economics: Evidence from the Field," Journal of Economic Literature, American Economic Association, vol. 47(2), pages 315-372, June.
    4. Liu, Siqi & Yin, Chao & Zeng, Yeqin, 2021. "Abnormal investment and firm performance," International Review of Financial Analysis, Elsevier, vol. 78(C).
    5. Samahita, Margaret & Holm, Håkan J., 2020. "Mining for Mood Effect in the Field," Working Papers 2020:2, Lund University, Department of Economics.
    6. Antonio Samagaio & Eduardo Couto & Jorge Caiado, 2009. "Sporting, financial and stock market performance in English football: an empirical analysis of structural relationships," CEMAPRE Working Papers 0906, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
    7. Christopher Boyce & Mikolaj Czajkowski & Nick Hanley & Charles Noussair & Michael Townsend & Steve Tucker, 2015. "The effects of emotions on preferences and choices for public goods," Discussion Papers in Environment and Development Economics 2015-08, University of St. Andrews, School of Geography and Sustainable Development.
    8. Siganos, Antonios & Vagenas-Nanos, Evangelos & Verwijmeren, Patrick, 2014. "Facebook's daily sentiment and international stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 730-743.
    9. Ehrmann, Michael & Jansen, David-Jan, 2022. "Stock return comovement when investors are distracted: More, and more homogeneous," Journal of International Money and Finance, Elsevier, vol. 129(C).
    10. Nicolau, Juan L., 2012. "The effect of winning the 2010 FIFA World Cup on the tourism market value: The Spanish case," Omega, Elsevier, vol. 40(5), pages 503-510.
    11. Chen, Yangyang & Goyal, Abhinav & Veeraraghavan, Madhu & Zolotoy, Leon, 2020. "Terrorist attacks, investor sentiment, and the pricing of initial public offerings," Journal of Corporate Finance, Elsevier, vol. 65(C).
    12. Shaun P. Hargreaves Heap & Daniel John Zizzo, 2011. "Emotions and Chat in a Financial Markets Experiment," Working Paper Series 10, The Paul Woolley Centre for Capital Market Dysfunctionality, University of Technology, Sydney.
    13. Obaid, Khaled & Pukthuanthong, Kuntara, 2022. "A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news," Journal of Financial Economics, Elsevier, vol. 144(1), pages 273-297.
    14. David Hirshleifer & Ming Jian & Huai Zhang, 2018. "Superstition and Financial Decision Making," Management Science, INFORMS, vol. 64(1), pages 235-252, January.
    15. Chad Cotti & Bryan Engelhardt & Joshua Foster & Erik Nesson & Paul Niekamp, 2021. "The relationship between in‐person voting and COVID‐19: Evidence from the Wisconsin primary," Contemporary Economic Policy, Western Economic Association International, vol. 39(4), pages 760-777, October.
    16. Doyle, John R. & Chen, Catherine Huirong, 2012. "A multidimensional classification of market anomalies: Evidence from 76 price indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(5), pages 1237-1257.
    17. Yochi Cohen-Charash & Charles A Scherbaum & John D Kammeyer-Mueller & Barry M Staw, 2013. "Mood and the Market: Can Press Reports of Investors' Mood Predict Stock Prices?," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-15, August.
    18. Abudy, Menachem (Meni) & Mugerman, Yevgeny & Shust, Efrat, 2022. "The Winner Takes It All: Investor Sentiment and the Eurovision Song Contest," Journal of Banking & Finance, Elsevier, vol. 137(C).
    19. Tao Chen & Erin P. K. So & Isabel K. M. Yan, 2021. "Are crises sentimental?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 962-985, January.
    20. Levy, Tamir & Yagil, Joseph, 2011. "Air pollution and stock returns in the US," Journal of Economic Psychology, Elsevier, vol. 32(3), pages 374-383, June.

    More about this item

    Keywords

    COVID-19; Soccer; Super-spreaders; Instrumental variables; Identification strategy;
    All these keywords.

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • G01 - Financial Economics - - General - - - Financial Crises

    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:eee:finlet:v:43:y:2021:i:c:s1544612321000738. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    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.