I present three essays on the economics of sport, examining salary discrimination in Major LeagueBaseball (MLB), determinants of dismissals of college football coaches, and star player effects onattendance in the National Basketball Association (NBA).New Evidence of Salary Discrimination in Major League BaseballSalary discrimination in MLB has largely been discarded as a research topic. However traditionalquantitative methods (particularly least squares regression) have concentrated on the effect of race for theaverage player. This is not where we should expect to find discrimination, as the relative cost ofdiscriminating against a better player is surely higher.I use quantile regression to uncover salary discrimination against black players in the lower half of thesalary distribution. Not only are the premia for white and Hispanic players statistically significant, butthey are large: up to 25% for the bottom quintile of players. I also demonstrate that racial effects may beobscured in typical baseball salary regressions when they suffer from omitted variable bias, brought aboutby failing to properly consider speed and fielding ability.Win or Go Home: Why College Football Coaches Get FiredModels of dismissals of sports executives frequently ignore the development of expectations regardingperformance. I explore the interplay between these expectations and the coachs tenure by examiningdismissals of college football head coaches from 1983 to 2006. Using a discrete-time hazard model, Idemonstrate that schools use prior performance in two ways: to evaluate the ability of the coach, and toestablish performance standards for retention. As recent performance is more relevant for estimatingability, I show that stronger recent performances decrease the chance of dismissal, but stronger historicperformances increase the chance of dismissal. Results describe a continual learning process on the part ofschools. I also consider the effects of race, insider-ness, rivalries, and rules violations on retention.Day to Day with the NBA SuperstarsI use censored regression (Tobit) analysis on NBA game-level attendance data to examine the superstarexternality effect identified by Berri and Schmidt (2006): star players increase road attendance, and sincehome teams (at least in the NBA) retain 100% of the gate revenues, this constitutes an externality.Game-level data has several advantages over the season-level data employed by Berri and Schmidt: theability to directly control for sellouts, estimation of dynamic intra-season attendance effects, and the lackof sensitivity to star player distribution. A new intra-season effect estimated is a superstar substitution effectaccounting for a star’s negative effect on attendance at adjacent games, partially mitigating the superstarexternality.
PDF
download
878987797
028-85220240
