Do Soccer Associations Really Spend on a Good Thing? Empirical Evidence on Heterogeneity in the Consumer Response to Match Uncertainty of Outcome
Abstract
The purpose of this study is to analyze whether previous results describing the effect of uncertainty of outcome on match attendance in team sports have been driven by heterogeneity in fan demand. We apply censored quantile regression methods and place particular emphasis on the relationship between match uncertainty and attendance demand, as previous results are highly ambiguous. This is the more surprising as each season association and league officials continue to spend millions on enhancing this uncertainty. We also control for season ticket holders, who are unlikely to be influenced by match specificities. Based on data from German soccer, our results indicate that fan demand shows heterogeneity across quantiles and that increasing match uncertainty of outcome exclusively benefits teams who already face strong attendance demand.Download Info
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Bibliographic Info
Paper provided by University of Zurich, Center for Research in Sports Administration (CRSA) in its series Working Papers with number 0009.Length: 35 pages
Date of creation: 2006
Date of revision: 2008
Publication status: forthcoming in: Contemporary Economic Policy
Handle: RePEc:rsd:wpaper:0009
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Related research
Keywords: heterogeneous fan demand; censored quantile regression;Other versions of this item:
- Men-Andri Benz & Leif Brandes & Egon Franck, 2009. "Do Soccer Associations Really Spend On A Good Thing? Empirical Evidence On Heterogeneity In The Consumer Response To Match Uncertainty Of Outcome," Contemporary Economic Policy, Western Economic Association International, vol. 27(2), pages 216-235, 04.
- Men-Andri Benz & Leif Brandes & Egon Franck, 2006. "Do Soccer Associations Really Spend on a Good Thing? Empirical Evidence on Heterogeneity in the Consumer Response to Match Uncertainty of Outcome," Working Papers 0048, University of Zurich, Institute for Strategy and Business Economics (ISU), revised 2008.
- D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models
- L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Recreation; Tourism
References
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Nicholas King & P. Dorian Owen & Rick Audas, 2012.
"Playoff Uncertainty, Match Uncertainty and Attendance at Australian National Rugby League Matches,"
The Economic Record,
The Economic Society of Australia, vol. 88(281), pages 262-277, 06.
- Nicholas King & P Dorian Owen & Rick Audas, 2010. "Playoff Uncertainty, Match Uncertainty and Attendance at Australian National Rugby League Matches," NCER Working Paper Series 61, National Centre for Econometric Research.
- Nicholas King & P. Dorian Owen & Rick Audas, 2010. "Playoff Uncertainty, Match Uncertainty and Attendance at Australian National Rugby League Matches," Working Papers 1007, University of Otago, Department of Economics, revised Aug 2010.
- Humphreys, Brad & Paul, Rodney & Weinbach, Andrew, 2010. "Consumption Benefits and Gambling: Evidence From the NCAA Basketball Betting Market," Working Papers 2010-7, University of Alberta, Department of Economics.
- Coates, Dennis & Humphreys, Brad & Zhou, Li, 2012. "Outcome Uncertainty, Reference-Dependent Preferences and Live Game Attendance," Working Papers 2012-7, University of Alberta, Department of Economics.
- Lahvicka, Jiri, 2010. "Attendance of ice hockey matches in the Czech Extraliga," MPRA Paper 27653, University Library of Munich, Germany.
- Leif Brandes & Egon Franck & Philipp Theiler, 2010. "The Group Size and Loyalty of Football Fans: A Two-Stage Estimation Procedure to Compare Customer Potential Across Teams," Working Papers 0126, University of Zurich, Institute for Strategy and Business Economics (ISU), revised 2011.
- Lahvicka, Jiri, 2012. "Using Monte Carlo simulation to calculate match importance: the case of English Premier League," MPRA Paper 40998, University Library of Munich, Germany.
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