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A Generalized Estimating Equation in Longitudinal Data to Determine an Efficiency Indicator for Football Teams

Author

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  • Anna Crisci

    (Pegaso Telematic University)

  • Luigi D’Ambra

    (University of Naples, Federico II)

  • Vincenzo Esposito

    (Quadrans S.R.L)

Abstract

Over the years football has attracted enormous interest from various fields of study, attracting attention both for its sporting and social aspects. Professional business operators consider football an important industry with enormous potential both in terms of its size and growth, and also because of indirect benefits due to the popularity gained by investors and management of football teams. The focus of the analysis has been on what characterizes most football clubs, and determines their particular economic and financial needs. The aim of this paper is to establish an efficiency measurement for football team financial resource allocation. In particular, we analysed the impact that the income statement, Net equity and Team value variables have on the points achieved by football teams playing in “Serie A” championship (Italian league). The method used in our study is a generalized estimating equation (GEE) for longitudinal count data. In addition we consider a coefficient of determination in the GEE approach based on Wald Statistics, and we propose a modified Mallow’s Cp for choosing the best model. Finally we propose an AFRSport index based on the differences between observed and theoretical points, in order to identify those teams that efficiently employ their financial resources.

Suggested Citation

  • Anna Crisci & Luigi D’Ambra & Vincenzo Esposito, 2019. "A Generalized Estimating Equation in Longitudinal Data to Determine an Efficiency Indicator for Football Teams," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 249-261, November.
    • Handle: RePEc:spr:soinre:v:146:y:2019:i:1:d:10.1007_s11205-018-1891-6
    DOI: 10.1007/s11205-018-1891-6
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    References listed on IDEAS

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    1. Wei Pan, 2001. "Akaike's Information Criterion in Generalized Estimating Equations," Biometrics, The International Biometric Society, vol. 57(1), pages 120-125, March.
    2. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    3. Hin, Lin-Yee & Carey, Vincent J. & Wang, You-Gan, 2007. "Criteria for WorkingCorrelationStructure Selection in GEE: Assessment via Simulation," The American Statistician, American Statistical Association, vol. 61, pages 360-364, November.
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    Cited by:

    1. Francesco Campanella & Luana Serino & Anna Crisci & Antonello D'Ambra, 2021. "The role of corporate governance in environmental policy disclosure and sustainable development. Generalized estimating equations in longitudinal count data analysis," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 28(1), pages 474-484, January.

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