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Highlights
| • | Club ownership structures influence both investments and efficiency. | ||||
| • | In France, clubs owned by private majority investors tend to decrease efficiency. | ||||
| • | In England, foreign majority investors tend to be less efficient. | ||||
| • | We identify three ownership types with different objective functions and efficiencies. | ||||
| • | Future research should study whether the UEFA FFP encourages efficient management. | ||||
Abstract
Professional European football clubs have been hypothesized to maximize sporting or financial objectives. The authors analyze the impact of various ownership structures on the realized management efficiency in maximizing profitability and national sporting success. Therefore, they apply the time-varying stochastic frontier model by CitationBattese & Coelli (1995) to an unbalanced panel from England and France between 2006 and 2012. French professional football is characterized by a shift towards private investors. Results show that clubs majority-owned by private investors are less efficient than other clubs in French Ligue 1. In English professional football, the majority of takeovers is pursued by foreign investors. Although previous researchers have shown that foreign investors increase financial resources and team investments, the authors demonstrate that foreign investors reduce both financial and sporting efficiency. The analysis of survival and financial team efficiencies of club ownership structures indicates that clubs tend to compete by investments rather than efficiency.
Notes
1 Seasons spanning two years (e.g., 2011/12) will be referred to by the later year (e.g., 2012).
2 Managerial efficiency and inefficiency are inter-related concepts that will be used throughout this study depending on the context of its use. The technical efficiency is defined as exponential function of the negative inefficiency value u: TE = e−u. Generally, we will show clubs’ efficiency scores rather than inefficiency values due to its more intuitive interpretation. The stochastic frontier methodology applied later in this paper does explain managerial inefficiency.
3 In England, public corporations listed at the stock market are typically registered as “public limited company” (PLC), while private companies are usually registered as “private limited company” (Ltd.). In France, most clubs are registered as “Société Anonyme Sportive Professionnelle” (SASP) or “Société Anonyme à Objet Sportif” (SAOS). Some of them are still controlled by member associations, while most clubs have transferred the majority of shares to private owners.
4 By ‘health of the league’, CitationSloane (1971) refers to Rottenberg’s uncertainty of outcome hypothesis.
5 The interested reader shall be pointed to CitationCoase (1960, Citation1988) and CitationSzymanski (2007) for a more detailed theoretical explanation and analysis of the Coase theorem.
6 For a more detailed literature review on the impact of private investors in European professional football, we refer to CitationRohde & Breuer (2017b).
7 Efficiency scores summarize the efficiency of a decision making unit on a scale from 0 to 1, with 1 indicating full efficiency.
8 While our empirical model is based on panel data, we have not been able to obtain panel data on the wealth of private owners. However, static analyses by CitationRohde and Breuer (2016b) based on data by Forbes and Deloitte indicate that owner origin is a good proxy for the wealth of owners.
9 Note that − in contrast to franchise values − here market values refer to the total value of a team’s players as indicator of team talent.
10 The profit transformation of the form log(Profit) = log(Profit + |ProfitMin| + 1) is a standard approach in economics literature (e.g., CitationBerger & Mester, 1997; CitationMaudos, Pastor, Perez, & Quesada, 2002)
11 The log transformation follows the equation: LN_ODDS_RANK = LN((X-Pit)/Pit), whereby X is equal to the number of ranks in the league (which is 20 in both Ligue 1 and the English Premier League), and Pit is the league position achieved by club i in season t.
12 We perform our analysis with the novel “sfpanel” command introduced by CitationBelotti et al., 2012. The “sfpanel” command is a new Stata command for panel data stochastic frontier models that allows estimating a much wider range of SFA models with time-varying inefficiency compared to Stata’s official “xtfrontier” command.
13 We would like to thank Julio del Corral for his recommendations on revising the original sample selection for the national sporting success model.
14 A metafrontier approach explicitly caters for non-homogeneous technologies. This may apply, for example, to firms operating under different technologies. In our case, clubs operate in different leagues or divisions with different regulations and other sample characteristics.
15 The Cobb-Douglas functional form is based on strong assumptions on demand elasticities and elasticities of substitution. These assumptions are relaxed in the translog model.
16 The transition probabilities for INV_MAJ_FOR in the Ligue 1 sample account to <2% to transition from not majority-owned to majority-owned by a foreign investor.
17 Technically, the equality of coefficients between two samples may be compared through a Wald test in a nested model. However, to our best knowledge, this approach is not feasible for the coefficients in the inefficiency function of the SFA model by CitationBattese and Coelli (1995).
18 An anonymous referee challenged whether the positive influence of team talent on profits as established mostly in the US major leagues would also generally be true in the European football setting. We tested this hypothesis in sub-samples of profit- and loss-generating teams, and found that team market values have a positive and significant influence on profits in the profit-generating team sample, but not in the loss-generating team sample. This confirms the hypothesis by the referee of a “murkier” relationship between profits and market values in European football.
19 We have also cross-checked if the results are influenced by specific big spenders like Roman Abramovich or Sheikh Mansour, and our results are robust to eliminations of individual clubs like Chelsea London or Manchester City from the analysis. The foreign investor coefficient remains positive and significant.
20 See endnote 2.
21 Note, however, that we can only observe realized profit and win maximization, and not the underlying objective function
22 We thank an anonymous referee for this valuable contribution.