Economic Justification for High Salaries in Sport

Justification of the huge salaries paid to some top athletes; an economic perspective. Over the last century there has been much research into the area of Labour Economics, and hence the determinants of supply, demand and wages for labour. In this essay, I will be looking at the unique example of the Sports Labour Market with specific focus on the European Football Market, and use various economic models to justify the huge salaries currently offered to top athletes within this field.

The wages of professional footballers have risen dramatically since the Bosman ruling in December 1995, in which EU football players were given the right to a free transfer at the end of their contracts, with the provision that they were transferring from a club within one EU Association to a club within another EU Association (European Commission, 2012).

This has been supported by various studies, including (Simmons, 1997), who argued that the move towards a free agency had the consequent impact of increasing players’ salaries, as the forgone transfer fees translate into increased salaries, since the bargaining power is transferred to the player. This was reinforced by (Downward, 2000) who found that post-Bosman, the wages within the United Kingdom’s Premier League rose considerably.

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However, these findings conflict with other studies conducted, including (Szymanski, 1999), who argued that the new ruling only lead to increased wages for superstar players who have the greatest bargaining power, and that it did not affect the wages for the average player. During this essay I will first discuss the basic economic principles relating to the labour market, and subsequently introduce various models developed with specific focus on the sports labour market. Demand for labour is “derived demand” because it is dependent on the demand for the final product that the labour produces (R.

Sandy, 2004). The conventional model used to analyse wage determinants states that the demand for labour is dependent on the Marginal Revenue Product of Labour (MRP) which is “the change in revenue that results from the addition of one extra unit (employee) when all other factors are kept equal” (Investopedia, 2012). In the field of sport, the industry is in a real sense selling its athletes, hence the demand for labour is dependent on the athletes “product” which could be viewed as his or her contribution towards the teams win column. The value of a win to the ports franchise is dependent on how the fans respond when the team wins more games. This value could be realised through the many revenue streams that sports franchises currently operate, perhaps most notably in the form of increased ticket sales, increased spending on merchandise and prize money. The “Standard Model” or “Perfect Competition Model” for wage determinants assumes that the sports franchise will operate at the profit maximising level of output, i. e. when the last unit of labour that is added adds as much to the firms revenues as to its costs > MRPL = MCL as shown in Figure 1.

Figure 1– PC Model Revenue and cost Marginal Wage Cost ARP MRP Employment of labour However, there are many limitations to this model, as the labour market for competitive athletes is far more complex. One basic argument against this model is that if in a perfectly competitive industry; firms earn abnormal profits, it assumes that more firms will enter the market and diminish these returns. Nonetheless, there are huge barriers to entry in the professional sports industry, and freedom of entry and exit does not exist.

If we look at the Premier League for example, each club typically has a local monopoly, and due to the nature of the market, one firm may bid up the price of labour as it hires more units, hence in the sense it could be viewed as a monopsonistic market (R. Sandy, 2004). Furthermore, there is uncertainty over quality, as sports teams have uncertainty over both the new players they hire and even experienced players and in the PC model the quality of labour is assumed to be known to the firm. Also due to long-term contracts it is impossible to predict how their skills will deteriorate or improve ver that period and if any injuries will occur. Furthermore, Players have to learn the weaknesses and strengths of their team-mates and to coordinate their strategies. A group of players who have been together for years will be much more effective than a group of equally talented individuals who have just been assembled into a team (R. Sandy, 2004). When establishing a suitable model to justify the enormous wages paid to some top athletes, we should first consider some basic economic principles. By definition, Star players are scarce hence the supply of these star players is highly inelastic.

This in itself would inflate the wage of these players, as the supply of top talent is very limited. To add a unit of player quality the team has to pay a higher price than it paid for its last unit of quality (Robinsion, 2012). However, it has been suggested that the labour supply curve has become more elastic since the globalisation of the sports labour market. Sherwin Rosen’s seminal 1981 paper on the economics of superstars asked the question why “relatively small numbers of people earn enormous amounts of money and seem to dominate the fields in which they engage. Rosen suggests that in superstar markets, "small differences in talent at the top of the distribution will translate into large differences in revenue" (Rosen, 1981). This suggests that the MRP of labour in sports, accelerates at an almost exponential rate as talent or quality increases, and profit-maximisers will operate where MRPL = MCL, hence leading to high salaries. Rosen simple insight was that "... sellers of higher talent charge only slightly higher prices than those of lower talent, but sell much larger quantities; their greater earnings come overwhelmingly from selling larger quantities than from charging higher prices”.

This was tested empirically on the Italian League by Simmons & Lucifora in 2003 and the findings were consistent with Rosen’s hypothesis, and found that relatively small number of performers dominate their industry and earn a disproportionate share of revenue (Simmons C. L. , 2003). Furthermore, in a study conducted by (Depken, 2000), it was found that performance may be affected by the dispersion of pay within teams. Hefound, empirically, that less salary disparity resulted in greater team cohesiveness and more efficient team production.

Another justification given for these huge salaries has been deemed the “Demonstration Effect”. This is a positiveexternality in the sense that a team which hires a superstar may raise the revenues of other teams in the league. This was found by Hausman and Leonard (1997) who established that the presence of a superstar such as Michael Jordan can have a substantial effect on the number of viewers watching NBA basketball games and increase other teams’ revenue as well as his own (Leonard, 1997). Perhaps one of the most important factors relating to salaries is the underlying motive of owners.

There have been various views on whether owners actually employ a utility maximisation or profit maximisation strategy, and in the European Football industry, it could be argued that both forms exist. Gerald Scully investigated the theoretical relationship between a club’s winning percentage, ticket prices, attendance and profits. He stated that the marginal cost of acquiring player talent (T) is given by MC(T). Also, the demand for wins depends on thesize of the franchise market and the elasticity of fans demand for wins.

In this model the term we represents a profit-maximising winning percentage where MC(T) = MR(T), the marginal revenue derived from a particular level of talent, with Te being the profit-maximising level of talent required to produce this outcome. This can be shown in Figure 2 Figure 2 – Scully’s Model Price / Cost Te MC(T) P C D(T) MR(T) Win percentage W2 We W1 However, playing success has a random component due to injuries, mistakes by the referee, or a mismatch between managerial skills and players.

Thus, there is a range of win percentages associated with Te talent such as w1 – w2. In turn this range gives rise to variation in attendance between A1 and A2 in Figure 3. To show the relationship between profit and win percentage Scully uses Figure 4. He shows a horizontal line ? = 0 which describes the club’s break-even point. He also makes the assumption that costs other than talent are fixed. Since Scully assumes that revenue is proportional to the team’s winning percentage, as indicated by ? T) in Figure 3, but that costs are fixed for the season, teams will make positive profits for winning percentages above or close to the profit maximising level, we, as shown by ? 0 Attendance Profit Figure 3Figure 4 ?(T) = TR ? TC A ?3 A3 ?2 A2 ?0 ?1 A1 Win percentage 0 w3 w2 w1 Win Percentage 0 w3 w2 w1 On the other hand, there are some criticisms to this model. Firstly, considering European Football, clubs also compete in European competitions, therefore giving incentive to have T >Te. In addition, Scully’s model focuses on the proportion of games won.

Fans may be more interested in their team contending for a championship. These are not the same; hence in an evenly balanced league a team with nearly 50% wins could be in contention while in a highly unbalanced league a team with 60% wins could be out of contention. The utility maximisation model was introduced by Peter Sloane in 1971, and he viewed that in the case of football this model was intuitively the most appealing in since we may regard football as a consumption activity (Sloane, 1971).

In Sloane’s model the utility U of an owner is a function, u, of; playing success; defined as the percentage of wins, (w); average attendance which adds to the spectacle and atmosphere (a); the competitive balance of the league defined as the standard deviation of league-wide winning percentages (x); having attractive opponents increases the interest in games; and after tax profits minus the threshold level of profit required to stay in business (x); profits add to the stability of the club and help to attract star players.

Thus Utility Maximisation is the function denoted by U = u (w, a, x, ? ), subject to ? r?? 0 + taxes; where ? r equals actual profits and ? 0 equals minimum profits. Both ? r and ? 0 may in fact be negative, in which case the taxes due would be zero. This is possible where the club has access to external sources of finance (f). In this model, the owner might weight each component of the function differently; hence if the owner puts a high weight on w then they will be prepared to trade off some rofit (or make losses) in order to secure additional playing success. Sloane’s model is perhaps even more relevant today, as there has been a recent trend for billionaires to acquire football clubs and spend unprecedented amounts on talent, purely to maximise the amount of wins. Implications of this model could also be used to describe the financial instability of some clubs, and the unbalanced performance of many European Leagues. Figure 5 – Sloane Model

Returns and cost of winning L’’ D TC C TRL L’ S’’ B TRS S’ A 0 W’L W’s WL Ws Win Percentage This result is illustrated in Figure 5, which compares a big city club, L, with a small city club, S, competing in a two-team league. As with the Scully model, it is assumed that costs of producing wins rises linearly and are identical for both clubs. Returns to winning rise initially at an increasing rate, but then at a decreasing rate as interest wanes if a team wins too often.

The total returns to winning schedule for a large city team TRL lies above that for a small city team TRS as the larger population catchment area in the former case means that the large city team will attract more spectators for any given winning percentage. The financial instability arises from the zero sum nature of the wins within the league. If the large city team wins more often, denoted by L’, this means that the small city team will win less often, denoted by S’. Thus the success of one club will drive the other into the area of loss making (anywhere below TC).

Due to the different regulations and restrictions, there is no one-size fits all model, but in the case of European Football, the most influential factor relating to players wages is the motives of the owner. Many high profile clubs in recent times have been criticised for spending endless sums of money to bring in the talent to enable them to win. Perhaps most notably, in the case of Chelsea, Roman Abromavich total spending has surpassed €1bn [ (Jackson, 2012) ], and Chelsea has consistently reported losses with Abramovich’s sole mission of wanting to win the European Champions League.

When looking at Sloane’s model, it could be viewed that in the case of utility maximisation, that Abramovich puts heavy weighting on the winning aspect of the function, with little or no emphasis on profits, and perhaps in this rare example, it could be viewed that he has no have a maximum loss. To overcome this growing trend, UEFA have implemented new rules regarding Financial Fair Play which includes an obligation for clubs, over a period of time, to balance their books or break even.

Under the concept, clubs cannot repeatedly spend more than their generated revenues, and clubs will be obliged to meet all their transfer and employee payment commitments at all times” [ (UEFA, 2012) ]. This would be a new factor that needs to be introduced into economic models. Furthermore, it could be viewed that the traditional business model of Football clubs is changing, as in the case of David Beckham, the increased merchandise sales realised by Real Madrid and LA Galaxy has meant that they have been able to justify his huge salaries ased on the marginal revenue product that he generates. Some superstars can have huge impacts on franchises total revenue, as described in the superstar effect, and clubs are forced to pay all players huge salaries to prevent underperformance due to pay disparity. Bibliography Ross Jackson. (2012, 02 01). Goal. com. Retrieved from http://www. goal. com/en-gb/news/2896/premier-league/2012/02/01/2879167/roman-abramovichs-chelsea-spending-surpasses-1-billion Depken, C. (2000). Wage disparity and team productivity: evidence from major. Economics Letters 67 . Downward, P. . (2000). The Economics of Professional Team Sports. London: Routledge. European Commission. (2012, 12 02). White Paper on Sport. Retrieved from The Organisation of Sport: http://ec. europa. eu/sport/white-paper/swd-the-organisation-of-sport_en. htm#4_2 Investopedia. (2012, 12 02). Marginal Revenue Product. Retrieved from http://www. investopedia. com/terms/m/marginal-revenue-product-mrp. asp#axzz2Duw8EOwf Leonard, J. H. (1997). Superstars in the NBA. Journal of Labour Economics . R. Sandy, P. S. (2004). The Economics of Sport; An International Perspective.

New York: Palgrave Macmillan. Robinsion, T. (2012). The Labour Market for Players Lecture. Manchester. Rosen, S. (1981). The Economics of Superstars. The American Economic Review . Simmons. (1997). Implications of the Bosman Ruling. Economic Affairs , 13-18. Simmons, C. L. (2003). Superstar Effects in Sport : Evidence From Italian Soccer. Journal of Sports Economics . Sloane, P. J. (1971). The Economics of Professional Football: The Football Club As A Utility Maximiser. Scottish Journal of Political Economy . Szymanski, K. &. (1999). Winners and Losers. London: Penguin.

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