Productive Efficiency and Salary Distribution: The Case of US Major League Baseball

Abstract

Recent theoretical research suggests that a firm's salary structure can affect the firm's productivity. We investigate the relationship between payroll inequality and production using US Major League Baseball data. Employing panel data methods, this study finds that salary inequality has a significantly negative effect on team success. A general result is that team success in term of wins does not seem to be correlated with efficiency; specifically, some of the least successful teams are also some of the most efficient. In addition, salary inequality does not appear to be correlated with efficiency. Furthermore, revenues generated by teams are not necessarily correlated with team efficiency.n University of North Texas 1 For instance, Hibbs and Locking (2000) examine the salary structure of Swedish industry and find no evidence that more equal salary structures lead to greater productivity.

Pay Dispersion

“…He found that greater player pay dispersion was negatively related to both team and individual performance. Using essentially the same baseball sample used in Bloom (1999) but with a more extensive set of econometric specifications, Jewell & Molina (2004), Depken (2000), and Frick et al (2003) also found a negative relationship between pay dispersion and on-field performance. Jane and colleagues (Jane 2010, Jane et al 2009, San & Jane 2008 found similar negative relationships between pay dispersion and team performance in a series of studies in the Taiwanese professional baseball league.…”

Individual efficiency and club performance: a panel analysis of professional baseball

“…Therefore, club-level efficiency has become the key to winning when each club has a similar fighting capacity. Jewell and Molinan (2004) found that a resourceabundant club in a 'large-market' can still be very successful regardless of inefficiency. However, in this paper we show that club-level efficiency does have an impact on club performance.…”

“…However, the correlation coefficients for all measurements were rather small. Unlike Jewell and Molinan (2004), in this study we try to estimate club-level efficiency based on batters' individual technical efficiencies. As we discussed above, we are aiming to see if club-level efficiencies have a significant impact on clubs' winning percentages.…”

“…After this, Porter and Scully (1982), Payne (1997, 2006), and Kahane (2005) adopted the SFM to analyze baseball, basketball, and hockey data. As a result, most studies in this field employed the SFM to estimate club-level efficiency (Zak et al, 1979;Payne, 1997, 2006;Jewell and Molinan, 2004). Jewell and Molinan (2004) estimated the correlation between 'predicted wins' and a club's production efficiency to see if the club's success was affected by cub-level efficiency.…”

“…As a result, most studies in this field employed the SFM to estimate club-level efficiency (Zak et al, 1979;Payne, 1997, 2006;Jewell and Molinan, 2004). Jewell and Molinan (2004) estimated the correlation between 'predicted wins' and a club's production efficiency to see if the club's success was affected by cub-level efficiency. They adopted the Cobb-Douglas stochastic production frontier and estimated the productive capacity of each club to measure the club in question's 'relative efficiency'.…”