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Experimental Effects of an Absent Crowd on Performances and Refereeing Decisions during COVID-19

Author

Listed:
  • Bryson, Alex

    () (University College London)

  • Dolton, Peter

    () (University of Sussex)

  • Reade, J. James

    () (University of Reading)

  • Schreyer, Dominik

    () (WHU Vallendar)

  • Singleton, Carl

    () (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

  • Bryson, Alex & Dolton, Peter & Reade, J. James & Schreyer, Dominik & Singleton, Carl, 2020. "Experimental Effects of an Absent Crowd on Performances and Refereeing Decisions during COVID-19," IZA Discussion Papers 13578, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp13578
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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. 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, Reading University.
    3. 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.
    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, University of 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.
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    Cited by:

    1. 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.
    2. 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.
    3. Alex Bryson & Peter Dolton & J. James Reade & Dominik Schreyer & Carl Singleton, 2020. "Causal effects of an absent crowd on performances and refereeing decisions during Covid-19," Economics Discussion Papers em-dp2020-18, Department of Economics, Reading University.
    4. 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).
    5. J. James Reade & Dominik Schreyer & Carl Singleton, 2020. "Stadium attendance demand during the COVID-19 crisis: Early empirical evidence from Belarus," Economics Discussion Papers em-dp2020-20, Department of Economics, Reading University.

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    More about this item

    Keywords

    attendance; Coronavirus; COVID-19; home advantage; natural experiments; referee bias; social pressure;

    JEL classification:

    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • Z20 - Other Special Topics - - Sports Economics - - - General

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