Winning and Wage Inequality in Major League Baseball

Abstract

The effect of wage inequality on team production is an important question in labor economics. Data from sports are well suited to study this problem, with more than 10 published papers in the last decade. We analyze the effect of wage inequality on team performance, using an unique dataset from Major League Baseball. Most studies have examined the impact of inequality within a linear model framework, and found that more equal pay structures enhance team production. This presupposes that there is no limit to beneficial effects of equality in pay, an idea which seems suspect. We specify and model a more reasonable data generating process for sportive contests, based on the differences between relative characteristics of the teams. Monte Carlo experiments reveal that estimating linear models using winning percentage as a dependent variable results in having biased and inconsistent estimates, which confounds any inference based on them, thus favoring our modeling strategy. Using our improved modeling procedure, we allow the relationship between wage inequality and winning to be non-linear, based on an insight by Lazear (1991), and we confirm the existence of an optimum level of wage inequality, finding evidence supporting the tournament theory of Lazear and Rosen (1981).