How Race Affects Dismissals of College Football Coaches FRANKLIN G. MIXON, JR.* University of Southern Mississippi, Hattiesburg, MS 39406 LEN J. TREVINO Washington State University, Pullman, WA 99164 We employ a discrete-time hazard model and a Blinder-decomposition approach to explore the possibility of racial discrimination in the dismissal and retention of col- lege football coaches by university administrations.A rich data set consisting of 81 institutions over an 11-year period (1990-2000) that contains, in addition to a coach 's race, variableson cumulative winning records, annual on-the-field improvements, and pre-/post-seasongame participationby institutionsand their coaches is employed. Our study finds that black coaches, on average, face a dismissal probability that is 9.6 percentagepoints below that of their nonblack counterparts, ceterisparibus, suggesting that black head coaches may be the beneficiaries offavorable treatment by university administrators. Such a result likely stems from universities' approach to social con- cerns involving race and gender issues. This finding also fits a construct that consid- ers workplace discriminationas multi-dimensional. For example, black representation in the college football coaching ranks may be disproportionatelylow, possibly as a result of discrimination. However once hired, black coaches are given more time to succeed than nonblacks, other things constant. "You have almost as good a chance of seeing an African-American on the cast of Friends as one wearing a head coach's headset on a football sideline" (Caple, 2001). I. Introduction The underrepresentation by blacks among head football coaches employed by Divi- sion IA colleges and universities in the National Collegiate Athletics Association (NCAA) has become a topic of considerable debate in recent years. ESPN.com, cnnsi.com, and The Sporting News have produced investigative journalistic reports on the subject, and many in the media have followed the recent hiring of a black head football coach - Tyrone Willingham - by the University of Notre Dame, an institu- tion often thought of as the symbol of college football (Blaudschun, 2000; Caple, 2001; Sporting News Online, 2001). During the 1990-2000 period, the 81 college football teams representing the major conferences of the NCAA's Division IA list of institu- tions (plus Notre Dame) played 886 individual football seasons. Of these, about 3.8 percent were coached by blacks. Some reports claim that this figure represents racially JOURNAL OF LABOR RESEARCH Volume XXV, Number 4 Fall 2004 646 JOURNAL OF LABOR RESEARCH motivated hiring practices (Hubbard, 2001). This number compares unfavorably with the current percentage of black NFL coaches (6.25 percent), and, more importantly, the 1995 percentage of college graduates who are black (7.00 percent), the midpoint of our sample (StatisticalAbstract of the U.S., 1996). Such numerical comparisons, however, do not constitute an empirical test, and furthermore, fail to recognize that university administrations' treatment of blacks in the college football coaching ranks entails more than their numerical representation. While these facts and figures are interesting, it is also important to examine how race affects the institutional decision to dismiss or retain coaches. Such an examination might reveal (im)partial treatment by race that extends well beyond the hiring stage. Workplace discrimination may be a multi-faceted phenomenon. To undertake such an exploration, we collected a large, rich data set consisting of 81 institutions over an 11 -year period (1990-2000) that reveals information on race, cumulative winning records, annual on-the-field improvements, and pre-/post-season game participation by institutions and their coaches. Many of these variables relate to the increasing monetary considerations in collegiate sports - as Leeds and von All- men (2002, p. 391) report, the average NCAA Division IA football programs earns an annual "profit" of about $3.2 million. These data are employed in a discrete-time hazard model, and our results are then used in a Blinder-decomposition approach to flesh out the possibility of racial discrimination in the dismissal and retention practices of university administrations. Below, we review some of the recent literature on racial discrimination in sports, contrasting its focus with the aim of the present study. II. Racial Discriminationin Sports: A Brief Review of Recent Literature The economics of discrimination has played a prominent role in the field of labor eco- nomics, providing part of the foundation for Gary Becker's Nobel Prize in Economic Science. His work (Becker, 1957) examined discrimination by race, religion, and gen- der, among other considerations such as personality, and became the seminal bench- mark for other important studies. Many subsequent studies have examined both black-white wage differentials and male-female wage differentials; among the exten- sions to Becker's work are Blinder (1973), Oaxaca (1973), Flanagan (1974), and Hirsch and Leppel (1982), to name a few. Recently, economists have extended Becker's work by examining forms of employment discrimination in sports. Among these are Kahn and Sherer (1988), Hoang and Rascher (1999), Bodvarsson and Partridge (2001), and McCormick and Tollison (2001). For a more extensive list of recent work, see Leeds and von Allmen (2002).1 Most of these studies share two common threads: They analyze pay discrimination (or other employment discrimination) in professional basketball, and they usually attrib- ute forms of pay discrimination to customer (fan) discrimination. For example, Kahn and Sherer (1988) report that black compensation in the NBA, ceteris paribus, is about 20 percent below nonblacks' compensation. Furthermore, they report the prediction that, ceteris paribus, replacement by an NBA franchise of one black player with an FRANKLIN G. MIXON, JR. and LEN J. TREVINO 647 identical white player raises home attendance by 8,000-13,000 per season; their evi- dence is also consistent with customer or fan discrimination. Hoang and Rascher (1999) report evidence that white players in the NBA have a 36 percent lower risk of being cut than black players, ceteris paribus, translating to an additional two years of expected career length for whites. Perhaps most important is their finding that the career earn- ings effect of exit discrimination (in the 1980s) was about $500,000 larger than the career earnings effect due to wage discrimination. All of these results are attributed to customer discrimination (Hoang and Rascher, 1999). Of course, customer discrimination studies are not without critics. For instance, McCormick and Tollison (2001) found that NBA salaries are lower for blacks than whites, but the differential is not likely due to customer discrimination. Their data point out that black players actually play more than comparable white players, and they offer a price discrimination theory of the observed pay differential based, in part, on rela- tive supply elasticity differences. This study differs from those listed above in various ways. First, we examine employment discrimination in collegiate football instead of the professional ranks. Sec- ond, our study of discrimination does not look at wages or hiring in the employment process. Instead, we examine the probability that a college football coach is dismissed (or retained) at the end of a given season (or year) as a function of race and other con- trol variables. We do this by way of a unique estimation method, a discrete-time haz- ard model described in more detail in the following section. III. A Frameworkfor Analyzing the Race Effect in College Football The statistical framework for the dismissal decision in college football coaching is based on the lottery-adoption model developed by Caudill et al. (1995). Herein, we assume that the tendency of university i to dismiss coach m at the end of any given football season is given by an unobservable variable, Y*. What is observed, at the end of any given season, is the outcome of the dismissal/retention decision process, Y(Mad- dala, 1983). If Y*>l, the coach is dismissed at the end of the season, and Y=l. If Y*S0, the coach is not dismissed, and Y=0. Again, following Caudill et al. (1995), a reduced- form model of the dismissal tendency can be written: Yi- = xip + Fi' where Xi is a vector of exogenous variables representing institutional/market pressures affecting dismissal; ,Bis a vector of parameters to be estimated; and Ei is a random error term. If Ei follows the standard logistic distribution, the probability of the dismissal of the coach, P, is given by the familiar formula: P(Dismissal)=exp(Xif)/[ I +exp(Xift)]. (2) The probability that a coach is not dismissed in a given year is 1-P. At the end of each year (football season) in the sample, each school either dismisses its coach or does not, with probabilities P and I-P, respectively. 648 JOURNAL OF LABOR RESEARCH Following Caudill et al. (1995), we obtain probabilities like those in equation (2) from a discrete-time hazard model of the dismissal decision. What is actually mod- eled is the timing of the dismissal decision. A university that dismisses its coach at the end of any given season contributes information on the determinants of dismissal, while a school that does not dismiss its coach at the end of that same season provides information about the determinants of retention. IV. A Hazard Model of the Dismissal of College Football Coaches In a hazard model, data on the independent variables in a given year (football season) are used to determine the probability of a coach's dismissal in that year. Although hazard models are widely used in economics, discrete-time hazard models are less com- mon. An example of the latter is provided by Caudill et al. (1995). When possible, discrete-time hazard models are estimated by maximum likelihood. The likelihood function for estimating this model is composed of probabilities of two types (Caudill et al., 1995, p. 557).