Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)

Legacy Department

Applied Economics


Wilson, Paul W

Committee Member

Sauer , Raymond D

Committee Member

Tollison , Robert D

Committee Member

Warner , John T


The common thread behind the three papers presented here is the use of sports data to test economics theories. 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 ten published papers in the last decade.In the first paper we analyze the effect of wage inequality both on team performance and efficiency, using data from Major League Baseball and a stochastic frontier model with a translog production function. Most studies have examined the impact of inequality within a linear 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 allow for a possible non-linear relationship between wage inequality and team performance, and find that most MLB teams have wage structures which are sub-optimal Furthermore using a semi-parametric estimation we find that high efficiency teams have a lower degree of wage inequality than low efficiency teams.
In the second paper 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).
The third paper performs a test of the Coase Theorem (Coase, 1960) using the adoption of the designated hitter rule(DH) by the American League(AL) in 1973 as a natural experiment. We model the decision to change leagues as a latent variable representing the economic calculation made by the decision making unit. Coase Theorem would predict that better hitting pitchers will move to the National League(NL), but since we cannot observe pitchers in AL pitching after 1973, we show the reciprocal of this,i.e. that worse batting pitchers move to the AL. Using a probit model, we find that indeed, for the 1972 and 1973 period, having batting skills two standard deviations below the average, would have increased the pitcher's trade probability by 9.8 percent, holding other variables constant at their means. Before 1972 and after 1973, being a subpar batter would not affect the probability that a pitcher is traded to AL.The change in regime in the AL, represented by the DH rule, opens the door to a test of the CT and of Rottenberg's(1956) novel analysis of the distribution of baseball talent. It appears that baseball owners and executives are not immune to the principles of economics or the CT.

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