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Experimental effects of an absent crowd on performance and refereeing decisions during Covid-19

Author

Listed:
  • Alex Bryson

    (University College London)

  • Peter Dolton

    (University Of Sussex)

  • J James Reade

    (University of Reading)

  • Dominik Schreyer

    (Otto Beisheim School of Management, Düsseldorf, Germany)

  • Carl Singleton

    (University of Reading)

Abstract

The Covid-19 pandemic has induced worldwide natural experiments on the effects of crowds. We exploit one of these experiments currently taking place over several countries in almost identical settings: professional football matches played behind closed doors. We find large and statistically significant effects on the number of yellow cards issued by referees. Without a crowd, fewer cards were awarded to the away teams, reducing home advantage. These results have implications for the influence of social pressure and crowds on the neutrality of refereeing decisions.

Suggested Citation

  • Alex Bryson & Peter Dolton & J James Reade & Dominik Schreyer & Carl Singleton, 2020. "Experimental effects of an absent crowd on performance and refereeing decisions during Covid-19," DoQSS Working Papers 20-04, Quantitative Social Science - UCL Social Research Institute, University College London.
    • Handle: RePEc:qss:dqsswp:2004
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    References listed on IDEAS

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    1. Sutter, Matthias & Kocher, Martin G., 2004. "Favoritism of agents - The case of referees' home bias," Journal of Economic Psychology, Elsevier, vol. 25(4), pages 461-469, August.
    2. Pettersson-Lidbom, Per & Priks, Mikael, 2010. "Behavior under social pressure: Empty Italian stadiums and referee bias," Economics Letters, Elsevier, vol. 108(2), pages 212-214, August.
    3. J. James Reade & Dominik Schreyer & Carl Singleton, 2020. "Echoes: what happens when football is played behind closed doors?," Economics Discussion Papers em-dp2020-14, Department of Economics, University of Reading.
    4. Fischer, Kai & Haucap, Justus, 2020. "Does crowd support drive the home advantage in professional soccer? Evidence from German ghost games during the COVID-19 pandemic," DICE Discussion Papers 344, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    5. Collins, Alan & McKenzie, Jordi & Vaughan Williams, Leighton, 2019. "When is a talent contest not a talent contest? Sequential performance bias in expert evaluation," Economics Letters, Elsevier, vol. 177(C), pages 94-98.
    6. Babatunde Buraimo & David Forrest & Robert Simmons, 2010. "The 12th man?: refereeing bias in English and German soccer," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(2), pages 431-449, April.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Mauro Caselli & Paolo Falco, 2021. "When the Mob Goes Silent: Uncovering the Effects of Racial Harassment through a Natural Experiment," DEM Working Papers 2021/01, Department of Economics and Management.
    2. Beiderbeck, Daniel & Frevel, Nicolas & von der Gracht, Heiko A. & Schmidt, Sascha L. & Schweitzer, Vera M., 2021. "The impact of COVID-19 on the European football ecosystem – A Delphi-based scenario analysis," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    3. Kai Fischer & Justus Haucap, 2020. "Does Crowd Support Drive the Home Advantage in Professional Soccer? Evidence from German Ghost Games during the Covid-19 Pandemic," CESifo Working Paper Series 8549, CESifo.
    4. Scoppa, Vincenzo, 2021. "Social pressure in the stadiums: Do agents change behavior without crowd support?," Journal of Economic Psychology, Elsevier, vol. 82(C).
    5. Luke S. Benz & Michael J. Lopez, 2023. "Estimating the change in soccer’s home advantage during the Covid-19 pandemic using bivariate Poisson regression," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 205-232, March.
    6. Kai Fischer & Justus Haucap, 2020. "Betting Market Efficiency in the Presence of Unfamiliar Shocks: The Case of Ghost Games during the Covid-19 Pandemic," CESifo Working Paper Series 8526, CESifo.
    7. Bryson, Alex & Dolton, Peter & Reade, J. James & Schreyer, Dominik & Singleton, Carl, 2021. "Causal effects of an absent crowd on performances and refereeing decisions during Covid-19," Economics Letters, Elsevier, vol. 198(C).
    8. Dominik Schreyer & Sascha L. Schmidt & Benno Torgler, 2020. "Using reminders with different reward opportunities to reduce no-show behavior: Empirical evidence from a large-scale field experiment in professional sport," CREMA Working Paper Series 2020-19, Center for Research in Economics, Management and the Arts (CREMA).
    9. Wen‐Jhan Jane, 2022. "Choking or excelling under pressure: Evidence of the causal effect of audience size on performance," Bulletin of Economic Research, Wiley Blackwell, vol. 74(1), pages 329-357, January.
    10. Alex Bryson & Peter Dolton & J. James Reade & Dominik Schreyer & Carl Singleton, 2021. "What we can learn about economics from professional sport during Covid-19," National Institute of Economic and Social Research (NIESR) Discussion Papers 525, National Institute of Economic and Social Research.
    11. J. James Reade & Dominik Schreyer & Carl Singleton, 2021. "Stadium attendance demand during the COVID-19 crisis: early empirical evidence from Belarus," Applied Economics Letters, Taylor & Francis Journals, vol. 28(18), pages 1542-1547, October.

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    More about this item

    Keywords

    Attendance; Coronavirus; Covid-19; Home Advantage; Natural Experiments; Referee Bias; Social Pressure;
    All these keywords.

    JEL classification:

    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • B55 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Social Economics
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

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