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Does Better Sports Performance Generate Higher Revenues in the English Premier League? A Panel Data Approach

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  • Marina Schloesser

    (Mendel University in Brno, Czech Republic)

  • Václav Adamec

    (Mendel University in Brno, Czech Republic)

Abstract

In this paper, we examined the relationship of sports performance and revenue generation in the English Premier League (EPL) to understand how performance on the field impacts financial performance of professional football clubs. Further, we verified if increased wage expenses help improve sports performance. Independent dynamic models were estimated by GMM on panel data including N = 28 EPL teams and on a reduced data set excluding the top six teams (N = 22), spanning from the 2008/2009 to 2018/2019 seasons (T = 11). The results of the GMM models confirmed that sports performance and revenue generation significantly correlate. Teams with better sports performance do generate higher revenues. Additionally, higher wage expenses result in better sports performance. A positive relationship of the variables in both hypotheses were established in both directions (full data). In all analyses of reduced data, the parameters of interest are nonsignificant. Dependencies exist due to the top teams.

Suggested Citation

  • Marina Schloesser & Václav Adamec, 2023. "Does Better Sports Performance Generate Higher Revenues in the English Premier League? A Panel Data Approach," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 9(1), pages 21-36.
    • Handle: RePEc:men:journl:v:9:y:2023:i:1:p:21-36
    DOI: 10.11118/ejobsat.2023.006
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    References listed on IDEAS

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    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Richard Blundell & Stephen Bond & Frank Windmeijer, 2000. "Estimation in dynamic panel data models: improving on the performance of the standard GMM estimator," IFS Working Papers W00/12, Institute for Fiscal Studies.
    3. Isidoro Guzmán & Stephen Morrow, 2007. "Measuring efficiency and productivity in professional football teams: evidence from the English Premier League," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 15(4), pages 309-328, November.
    4. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, February.
    5. Kaddour Hadri, 2000. "Testing for stationarity in heterogeneous panel data," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 148-161.
    6. Marc Rohde & Christoph Breuer, 2016. "Europe’s Elite Football: Financial Growth, Sporting Success, Transfer Investment, and Private Majority Investors," IJFS, MDPI, vol. 4(2), pages 1-20, June.
    7. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    8. Dieter J. Haas, 2003. "Productive efficiency of English football teams-a data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 24(5), pages 403-410.
    9. Sloane, Peter J, 1971. "The Economics of Professional Football: The Football Club as a Utility Maximiser," Scottish Journal of Political Economy, Scottish Economic Society, vol. 18(2), pages 121-146, June.
    10. António S. Ribeiro & Francisco Lima, 2012. "Portuguese football league efficiency and players' wages," Applied Economics Letters, Taylor & Francis Journals, vol. 19(6), pages 599-602, April.
    11. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    12. Yves Croissant & Giovanni Millo, 2018. "Panel Data Econometrics with R," Post-Print hal-01699532, HAL.
    13. Emilios C. C Galariotis & Christophe Germain & Constantin Zopounidis, 2017. "A combined methodology for the concurrent evaluation of the business, financial and sports performance of football clubs: the case of France," Post-Print hal-02879864, HAL.
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    Keywords

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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • J30 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - General
    • Z23 - Other Special Topics - - Sports Economics - - - Finance

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