NCAA enforcement and competitive balance in college football.
Wilson, Dennis P.
1. Introduction
The National Collegiate Athletic Association (NCAA) is the largest
and best known of the four independent organizations created to regulate
collegiate sports in the United States. (1) These organizations serve to
protect the amateur status of college athletes, sanction athletic events
(especially championships), and to otherwise regulate the behavior of
member schools (and those affiliated with them) in the context of
college athletics. These associations, especially the NCAA, appear to be
cartels in which members agree to codify rules that regulate both the
input (student athlete) and the output (sporting-event) markets
(Fleisher et al. 1988; Fleisber, Goff, and Tollison 1992). As with any
cartel, there are incentives for one or more members to violate the
terms of the agreement. This in turn necessitates enforcement and
punishment mechanisms to mitigate the incentive for members to cheat.
Centralized rule enforcement within a cartel is usually established
to deter behavior deemed suboptimal to the group for which it is
established. However, a lack of data often limits investigation into the
impact of internal rule enforcement within industries, yet a few authors
have studied the impact of antitrust investigations on the concentration
of American industry (Feinberg 1980; Garbade, Silber, and White 1982;
Block and Feinstein 1986; and Nissan 1998 are notable examples). The
NCAA, as an organization of collegiate athletics, provides a unique
instance in which the production of industry members is well defined and
internal enforcement efforts, in the form of investigations and
probations, are well advertised and documented.
While previous analyses of the impact of NCAA enforcement have
predominantly focused on team-specific performance, the more general
question of how NCAA enforcement affects competitive balance, or the
skewness of on-field success, has received less attention. Anecdotal
evidence indicates that college football has been dominated by
relatively few teams over the past few decades, such as Miami (Florida),
Alabama, Nebraska, Notre Dame, and the University of Southern
California, to name a few. Therefore, whether NCAA enforcement efforts
contribute to or detract from the competitive balance of Division IA
football conferences is of interest.
The NCAA is an organization whose members agree to a codified (but
alterable) set of regulations that aim to reduce the ability for some
members to use their substantial resources to skew the distribution of
player talent and on-field success away from smaller, perhaps poorer,
schools. Even though schools are limited in the amount of in-kind and
direct payments they can offer student athletes, the nonmonetary
benefits of attending a school, including academic training, coach and
program reputation, and the possibility of national exposure to
professional scouts, might put smaller schools or lesser programs at a
disadvantage. In response, some members of the NCAA might be motivated to cheat on the NCAA agreement in order to obtain the marginal benefit
of having a prospective student athlete attend their schools. This moral
hazard is the general target of NCAA regulations. Although the NCAA
regulatory structure does not ensure perfect parity, the stated
objective of the NCAA is to limit the desire for schools to violate the
agreement and jeopardize the amateur status of college athletes. To
encourage solidarity, the NCAA has a structured penalty schedule that
can be applied to schools that violate the agreement, which, while
appealable, is generally binding.
How much cheating actually declines after an increase in
enforcement activity is an interesting topic, but data to investigate
this issue are not available. Consequently, a second-best empirical
alternative is to investigate how competitive balance changes with
enforcement activity, which is a test of the impact of the NCAA's
role as the enforcer of the membership agreement. Thus, the level of
cheating is not directly addressed in this study; rather, we investigate
whether competitive balance improves after increases in enforcement
activities.
This article investigates two conflicting hypotheses regarding the
role of NCAA rule enforcement within Division IA football conferences.
The NCAA claims to act in the best interest of the "amateur
spirit" of collegiate sports, thereby ensuring a "level
playing field" and, in turn, encouraging competitive balance, or a
more equitable distribution of playing talent and on-field success (see
Zimbalist 2001 for a detailed industry analysis of college athletics).
However, others posit that as an organization, the NCAA protects the
relative dominance of "big-time" programs (for example, see
Noll 1999) and as a result reduces competitive balance. To date, these
disparate claims have only been tested indirectly. Which hypothesis
provides an appropriate characterization of the NCAA is the empirical
question addressed in this article.
Using data describing 11 major Division IA football conferences
from 1953 through 2003, the impacts of NCAA enforcement efforts are
estimated. We empirically relate competitive balance, as measured by the
Herfindahl-Hirschman Index (HHI), to various measures of enforcement and
punishment and additional control variables in an instrumental variables
approach. The empirical results indicate that NCAA enforcement
activities enhance competitive balance, whereas more severe punishment
tends to reduce competitive balance. Evaluated at the sample means, NCAA
enforcement activity leads to a net improvement in the competitive
environment, which supports proponents of the NCAA who argue that it
ensures a more "level playing field." While the reduction in
competitive balance caused by more severe punishment is likely the
source of anecdotal claims that the NCAA protects the status of dominant
programs, these obvious reductions are generally more than offset by the
less-obvious improvements in competitive balance resulting from NCAA
enforcement efforts.
The remainder of this article is structured as follows. The next
section outlines a brief history of NCAA regulation. Section 3 develops
several testable hypotheses about the impacts of rule enforcement on
competitive balance. Section 4 describes the data, the empirical
methodology, and the results. The final section offers concluding
remarks and avenues for future research.
2. NCAA Enforcement and the Associated Literature
In the first half of the 20th century, the growing popularity of
college athletics and the substantial increase in potential revenues for
many schools provided incentives to engage in actions thought to be
detrimental to student athletes and amateur athletics in general. (2)
These "nefarious" tactics motivated the NCAA to regulate both
the input and output market of college athletics. In 1946, the
"'Principles of Conduct of Intercollegiate Athletics" was
drafted, and two years later this document was incorporated into the
NCAA constitution and became known as the "Sanity Code." The
Sanity Code imposed regulations on the recruitment and retention of
student athletes: Scholarships for athletic activities were restricted
to only tuition and fees, and the financial contact of alumni with
prospective student athletes was limited.
Although the Sanity Code was not the first attempt to regulate the
behavior of member schools, the NCAA considered this regulation more
significant because it created an enforcement mechanism to handle
violations. A Compliance Committee became the arbiter of suspected
violations that had been investigated by the Fact-Finding Committee.
Initially, the only form of punishment available to the Compliance
Committee was the termination of the violator's NCAA membership,
decided by a vote of all NCAA members. However, NCAA members deemed this
punishment too draconian and stripped the Compliance Committee of its
punitive role in 1951. (3)
In 1953, NCAA members agreed to provide the Committee of
Infractions (formally the Compliance Committee) with a continuum of
powers with which to penalize rule violators in a manner less severe
than termination; possible penalties included limiting the number of
scholarships, limiting television appearances, and limiting
participation in postseason play. Credibility was provided to the
Committee of Infractions as punishments could be exacted without general
membership approval. Accordingly, since 1953 the NCAA has had and
employed a credible enforcement mechanism with which to maintain
solidarity of the organization and, by its own claims, to promote the
spirit of amateur sport and competitive balance. (4)
The increasing popularity of college athletics, especially
football, men's basketball, and, to a lesser extent, women's
basketball, has dramatically increased the financial returns available
to university athletic departments. Over the past 20 years, the number
of bowl games comprising postseason collegiate football has increased,
contemporaneously, with increased media and stadium revenues available
to football programs. (5) Therefore, if athletic departments, coaches,
alumni, and boosters expect that violating NCAA regulations will improve
on-field performance in the near-term, the potential gains from cheating
have likely increased. According to Becket's (1968) explanation of
criminal activity, if the gains associated with illegal behavior
increase, either the probability of detection and punishment or the
severity of the penalties imposed must also increase to offset the
incentives of such illegal behavior.
The NCAA penalty schedule is similar to the legal penalties imposed
in general society: More egregious violations carry increased severities
in penalties, whereas minor offenses receive rather trivial punishments.
NCAA punishments may include temporary limitations on scholarships,
television appearances, and postseason play. While the NCAA does have
the ability to prohibit a school or program from competing against other
members, the so-called "death penalty," the only instance of
this extreme punishment was (temporarily) applied to the football
program at Southern Methodist University in 1987.
The intuition underlying the various forms of punishment in the
NCAA seems to be two-fold. First, probations and further penalties seem
intended to reduce the revenue of the sanctioned program or school,
thereby penalizing an athletic program for "ill-gotten'"
gains--past, present, and future-obtained through cheating. Second,
penalties appear to be intended to reduce the ability of the
program/school to recruit new student athletes, thereby reducing the
school's competitive status and ability to generate revenue in the
future.
To date, there has been relatively little direct analysis of NCAA
enforcement efforts in college football. However, three studies provide
a background for the current study. Fleisher, Goff, and Tollison (1992)
investigated the probability that a school's football program would
be investigated by the NCAA and found that a dramatic increase in the
winning percentage of a school's football program had a strong
correlation with an NCAA investigation for possible rules violations.
They also found that football programs tend to suffer significant
reductions in on-field success after NCAA sanctions are imposed.
Eckard (1998) considered competitive balance in seven major
Division IA football conferences before and after NCAA enforcement began
in 1953, using the variance of relative team positions over time to
measure competitive balance. He found that competitive balance improved
for five of the seven conferences, but he generally concluded that the
NCAA acts as a traditional cartel by protecting the stability of
relative team rankings in the conferences under its control.
Depken and Wilson (2004) investigated how competitive balance
across all Division IA football teams has been affected by major changes
in NCAA regulations over time. While Division IA football has become
less balanced over time, several institutional changes have had a
beneficial impact on competitive balance, specifically the creation of
the NCAA, the creation of a credible enforcement mechanism, and the
relegation of many schools to Division IAA status. However, several
other major rule changes, such as increased academic standards and the
creation of the Bowl Championship Series, have reduced competitive
balance. These findings indicate that pressure groups may motivate many
of the institutional changes in the NCAA.
While the Depken and Wilson results indicate a correlation between
various NCAA rule changes and overall competitive balance in Division IA
football, it is perhaps unlikely that the relationships they show hold
when analyzing competitive balance at the conference level. However,
changes in rules can act as proxies for increased vigilance and
enforcement on the part of the NCAA, the direct measure of which is the
innovation in this study.
3. Hypotheses about NCAA Enforcement
From 1953 through 2003, the number of Division IA football teams
varied from a minimum of 104 teams (in 1987) to a maximum of 147 teams
(in 1977). Although the average number of football programs placed on
probation has increased over time, as of 2002, the NCAA employed only 15
field investigators. While NCAA investigators may be quite adept at
detecting cheating, whistle-blowers (both named and anonymous) almost
certainly play an important role in rules enforcement. This follows from
standard cartel theory, which would suggest that the more schools,
sports, coaches, players, parents, fans, teachers, and administrators
involved with NCAA athletics (however tangentially), the less likely it
will be that cheating on the part of any athletic program or team will
remain secret. (6)
Investigating how the competitive balance of Division IA football
conferences changes when competitors are investigated and placed on
probation extends the literature on centralized rules enforcement. While
the NCAA claims that enforcement is specifically aimed at maintaining
the spirit of amateur sport, many view NCAA enforcement as ensuring the
continued dominance of historical "football powers." If the
NCAA's claims are true, enforcement may have the positive byproduct of improving competitive balance. However, if detractors are correct,
NCAA sanctions may lead to a decline in competitive balance.
The conceptual model employed for NCAA enforcement is that of
Becker (1968). In his approach to the economics of crime, the deterrence of illegal behavior is affected by the severity of the punishment (if
illegal behavior is detected) and the probability of being caught
engaged in such illegal behavior. In empirical applications of
Becker's theory, Grogger (1991) and Levitt (1998) discriminate between the influences of deterrence and incapacitation though
punishment. Deterrence effects are created by a higher probability of
detecting prohibited behavior and more severe sanctions when caught
engaged in prohibited behavior. Incapacitation refers to the removal of
lawbreakers from the pool of potential rules violators. This
incapacitation is distinguished from general deterrence because it
precludes criminal actions that otherwise would have taken place.
Incapacitation is an appropriate characterization of programs
placed on probation by the NCAA for a rule violation. While programs on
probation are allowed to continue operations, if a program on probation
for a major rules violation is found guilty of an additional major rule
violation, the NCAA can impose its most draconian sentence: "the
death penalty." Thus, NCAA probations may have two distinct
influences on the amount of cheating that occurs. Those programs on
probation may be effectively incapacitated, while those programs not on
probation might be deterred from future rules violations.
If a team becomes less competitive and loses more games when placed
on probation, the lost games must be transferred to other schools in the
form of wins. If more wins are transferred to below-average teams,
sanctions will improve competitive balance. On the other hand, if more
wins are transferred to above-average teams, sanctions will act to
reduce competitive balance.
Enforcement activity can, therefore, have two different impacts on
competitive balance. If the NCAA uses dramatic short-run improvements in
winning percentage as a trigger to initiate investigations, as suggested
by Fleisher, Goff, and Tollison (1992), programs with less variance in
performance will be less likely to be investigated, ceteris paribus. As
dominant programs with high winning percentages would have less
variation in their on-field success, they may be relatively immune from
investigation. In this case, if probations reduce on-field performance,
NCAA enforcement would likely reduce competitive balance. On the other
hand, if NCAA investigative activity concentrates on programs that
perform at a relatively high level regardless of previous performance,
NCAA enforcement may well improve competitive balance.
The severity of punishment is likely to have only a deleterious effect on competitive balance. The longer a program is on probation, the
less likely it is to be highly competitive contemporaneously. Moreover,
the longer a program is on probation, the greater the damage to the
program's reputation, which affects the program's ability to
recruit high-quality student athletes and its competitiveness well after
the probation period is over. The longer the pending probations, the
more likely it will be that those schools on probation are put at a
disadvantage relative to the other programs in their conference. Hence,
longer probationary periods are expected to reduce competitive balance.
The net effect of enforcement and the severity of punishment
indicates whether enforcement of the NCAA membership agreement
(generally speaking) leads to a net increase or decrease in competitive
balance. If competitive balance suffers a net decline, claims that the
NCAA protects or enhances the rents of dominant programs would be
supported. On the other hand, if competitive balance enjoys a net
improvement, this would support the claims of the NCAA's
proponents.
An empirical test of which regime characterizes the NCAA would
estimate both the impact of enforcement and the impact of punishment on
competitive balance. From such estimation, it is possible to test which
regime is supported by the data, rather than relying simply on
conjecture and rhetoric. The following section empirically analyzes the
impact of NCAA enforcement activity on the competitive balance of
several major Division IA football conferences from 1953 through 2003.
4. The Effect of NCAA Enforcement on Competitive Balance
Empirical Methodology and Data
The dependent variable in the empirical specification is the
competitive balance for conference i in year t, measured using either
the HHI or the natural logarithm of HHI. To measure on-field
performance, and to account for ties (which were possible before 1996),
each team is credited with two points for a win, one point for a tie,
and zero points for a loss, similar to the point system used in the
National Hockey League. (7) Performance points for each team's
conference win-loss-tie record and total performance points for each
conference in each year are calculated. "Market shares" (MS
[member of] 0, 100) are then calculated as each team's performance
points as a percentage of aggregate conference performance points, and
the Herfindahl is calculated as HHI =
[[summation].sup.N.sub.i]M[S.sup.2.sub.i] where N is the number of teams
in the conference. (8)
The performance across teams in a given conference is made
comparable by limiting the focus to intraconference games. Using only
conference games abstracts from differences in the strengths of
out-of-conference scheduling, which could distort competitive balance
across schools in a conference. Although it is standard practice for
each team in a conference to play the same number of conference
opponents, teams do not necessarily play every possible conference
opponent. In conferences with many members, it is not possible for every
team to play all other teams in the conference; therefore, schedules
often rotate over a set number of years. In a given year, one team may
have a relatively strong in-conference schedule while another team
enjoys a relatively weak schedule. Over time these scheduling
inconsistencies are not expected to permanently distort the measure of
competitive balance.
To determine the impact of enforcement and punishment on
competitive balance, the following relationship is estimated:
(1) HH[I.sub.i,t] = [[beta].sub.1]HH[I.sub.i,t-1] + [[beta].sub.2]
[TEAMS.sub.i,t] + [[beta].sub.3] [ENFORCEMENT.sub.i,t] + [[beta].sub.4]
[PUNISHMENT.sub.i,t] + [[epsilon].sub.i,t]
where the [beta]'s are parameters to be estimated, i
identifies the conference, and t identifies time from 1953 through 2003.
The independent variables include the once lagged dependent variable
(HH[I.sub.i,t-1]), the number of teams in the conference, and variables
used to control for the severity of punishment and the level of
enforcement in a conference in a given year. The error term is initially
assumed to be [[epsilon].sub.i,t] = [[alpha].sub.i] + [[gamma].sub.t] +
[u.sub.i.t], where [[alpha].sub.i] is a conference specific effect,
assumed constant over time; [[lambda].sub.t] is a time-specific effect,
assumed constant across conferences: and [u.sub.i,t] is white noise. The
composite error term is accommodated using panel estimators that allow
for conference-specific heteroscedasticity and autocorrelation.
Although the level of the HHI does not reveal much about the
relative standing of any particular team, changes in the concentration
measure can be interpreted as changes in competitive balance. If NCAA
enforcement activity or severity of punishment reduces the winning
percentages of the targeted schools, the Herfindahl measure will
increase (decrease) if those wins are redistributed to above-average
(below-average) teams, corresponding to a reduction (improvement) in
competitive balance.
A potential concern is the inclusion of a lagged dependent variable
in Equation 1. As shown by Nickell (1981), lagged dependent variables
can introduce inconsistency on the order of 1/T, where T is the number
of time periods in the sample. For the conferences in our sample, the
average number of time periods (i.e., years) is 36; therefore, we might
expect a bias of approximately 2.7% in standard panel models. However,
the lagged dependent variable is included for two reasons. First, there
is no general theory for how the competitive balance of a conference
evolves over time; therefore, the lagged dependent variable attempts to
capture the various inputs to the competitive balance of a collegiate
football conference, including coaches, training, injuries, weather, and
other difficult-to-measure inputs to the competitive balance production
function.
Second, it is likely that college football conferences do not fully
adjust from a shock (whether random or otherwise) in a single year. For
example, if a football program is investigated and placed on probation
for four years, during which time the program can offer fewer
scholarships, it is likely that the full impact of the probation will be
felt over time, rather than in a single season. This implies that
modeling a lagged adjustment process is appropriate. The parameter estimate of the lagged dependent variable can be used to determine the
long-run effect of the various explanatory variables included in
Equation 1. The long-run impacts of NCAA enforcement and punishment
activity have not, to date, been estimated, and thus the insight
obtained by including the lagged dependent variable seems worth the
potential loss of consistency.
The remaining explanatory variables attempt to control for
exogenous changes to the environment in which college football teams
participate at the conference level. The variable TEAMS measures the
number of teams in a conference in a given year. Over the past 50 years,
the various conferences included in our sample (and many that are not)
have expanded and contracted on an irregular basis. A general empirical
finding is that more games in a season or more teams in a league
improves competitive balance (see Fort and Quirk 1995; Depken 1999).
Therefore, as the number of teams increases (decreases), the Herfindahl
is expected to decline (increase). The inclusion of this variable
controls for "changes" in the competitive balance that are
simply a function of having more teams in the conference, rather than
having less disparity among existing teams.
A comprehensive measure of enforcement in the NCAA has yet to be
developed. It will prove extremely difficult, if not impossible, to
determine the annual amount of effort, both labor and monetary, that the
NCAA has dedicated to the enforcement of its agreement since 1953.
Without ready knowledge of exactly which and how many resources the NCAA
commits to enforcement, the empirical researcher is left to measure
enforcement as accurately, but also as broadly, as possible. In this
study, the variable ENFORCEMENT is measured two ways: total
football-related investigations and total football-related probations.
(9)
The number of football-related investigations is analogous to
arrests (or indictments), and the number of football-related probations
is analogous to the number of convictions; arrests and convictions are
commonly used in the general crime literature. While neither measure
captures all efforts related to enforcement (for example, resources
expended that did not result in an investigation), the two measures
arguably capture those enforcement efforts expected to influence the
level of cheating by a conference's schools. Both investigations
and new and old (that is, yet-to-expire) probations in a given
conference arguably signal a credible threat that the NCAA will impose
additional sanctions on cheaters. A priori, it is expected that the
total number of pending probations will have a greater impact on
competitive balance than total investigations.
Fleisher, Goff, and Tollison (1992) suggest that dramatic
improvements in winning percentage can trigger an NCAA investigation
(and possibly probation). A dramatic improvement in a team's
winning percentage might also be associated with a change in the
competitive balance measure. This implies that investigations and
probations are likely correlated with [u.sub.it] in Equation 1, for
which an instrumental variables approach is desirable.
As shown by Depken and Wilson (2004), several changes to the NCAA
membership agreement correlated with changes in the competitive balance
of Division IA football as a whole. As additional rules and regulations
are added to the NCAA membership agreement, it is arguably more
difficult for schools to comply. The rule changes would seem to be
natural candidates to instrument for the number of investigations and
probations in a conference in a given year. The following policy changes
were used as instruments: the increase in minimum grade point average
(GPA) standards in 1966, the relegation of some schools to Division IAA
status in 1982, Proposition 48 in 1985, and Proposition 16 in 1992. An
additional instrument is whether the conference is a BCS Conference.
(10) Using these instruments, Durbin-Wu-Hausman tests indicate that,
except for the lagged competitive balance measure, only the enforcement
variable, whether measured by investigations or probations, is
correlated with [u.sub.it] in Equation 1.
The variable PUNISHMENT captures that aspect of the economic theory
of crime associated with the fines incurred if 'caught and
convicted' of violating the NCAA membership agreement. Although
probations often carry additional penalties, including loss of
scholarships, postseason play, or television appearances, these
additional penalties did not prove statistically relevant when added to
Equation 1. Therefore, punishment is measured as the average length of
probations pending (measured in years) in a given year in a given
conference. For example, if three teams were on probation in a
conference in a given year, with School A on probation for two years,
School B on probation for three years, and School C on probation for
tour years, the average length of the pending probations would be 9/3 =
3 years. In many cases there are no pending probations in a conference
in a given year, in which case the average length of pending probations
is coded as a zero.
The data describe 16 different college football conferences from
1953 to 2003: the Atlantic Coast, Big East, Big 6, Big 7, Big Eight, Big
Ten, Big XII, Conference USA, Mid-American, Mountain West, Pacific
Coast, Athletic Association of Western Universities (AAWU), Pacific
Eight, Pacific Ten, Southeastern, Southwest, and the Western Athletic
Conferences. Historical team records were obtained from David Wilson.
(11) The HHI is calculated for each conference and year with market
shares based on intraconference performance points. Several conferences
have existed for only a few years (for example, Conference USA and the
Big XII). However, several of the conferences in our sample can be
combined to form two distinct time series: one for the Big XII and one
for the Pacific 10. In 1947, the Big 6 became the Big 7, which in turn
became the Big 8 in 1960, which in turn merged with four teams from the
defunct Southwest Conference to become the Big 12 in 1996. (12)
Similarly, the Pacific Coast Conference dissolved in 1959, and several
members formed the AAWU, which became the Pacific Eight in 1968, which
in turn joined with Arizona and Arizona State to become the Pacific Ten
in 1979. In these two cases, the historical lineages of the two
conferences are included in a single time series. Thus, the unbalanced
panel used in the estimation comprises 11 time series.
The length of probations, the number of schools on football-related
probation, and the total number of football-related investigations for
each conference-year in the sample were obtained from the NCAA's
Major Infractions Database. (13) While the NCAA maintains a Secondary
Infractions Database, these data are not utilized because of the minor
nature of the infractions and subsequent penalties. (14)
Descriptive statistics of the 401 observations included in the
sample are reported in Table 1. The average Herfindahl was approximately
1490. During the sample period there was approximately one
football-related investigation and one football-related probation in a
conference every two years, although in many conferences there was no
enforcement activity for many years. In conferences in which at least
one football-related investigation took place, the average number of
investigations was 1.40, and the average number of probations pending
was 1.08. This indicates that if a conference came under NCAA scrutiny
to the extent that an investigation was initiated, the NCAA often
investigated more than one team, and investigations were more frequent,
on average, in conferences with more pending probations. This might
indicate that the NCAA uses past "bad" behavior of conference
members as a guide to where to direct enforcement efforts.
The largest number of football-related investigations in a single
year was in the Pacific Coast Conference in 1957, when four of nine
members were investigated. However, a number of conferences experienced
three football-related investigations in a single year: the Atlantic
Coast Conference in 1983 and 1990; the Big 8 Conference in 1989; the Big
Ten Conference in 1976, 1991, and 1999; the Pacific Ten Conference in
1982 and 1997; the Southeastern Conference in 1985 and 1986; and the
Southwest Conference in 1965 and 1987. The largest number of
football-related probations in place at a given time was five in the
Southwest Conference in 1987; the Pacific Ten Conference had four
schools on football-related probation in 1983. The average length of
pending probations over the entire sample period was approximately one
year; however, in conferences in which at least one probation was
pending, the average length of probations increased to 1.69 years.
Probations have become longer over time, perhaps reflecting more
egregious cheating, a smaller chance of detection, or greater potential
gains to cheating. The Big Ten in 2001, 2002, and 2003; the Big XII in
1996 and 1997; the Pacific Ten in 2003; the Southwest in 1994; and the
Western Athletic Conference from 1997 through 2000 each had one
five-year probation pending.
Empirical Results and Discussion
Various specifications of the primary model described in Equation 1
are reported in Table 2. One major distinction between the models is the
form of the dependent variable. The left half of Table 2 reports results
using the level of the Herfindahl as the dependent variable. While
parameter estimates can be interpreted as the marginal influence on the
Herfindahl, a measure from 0 to 10,000, the intuitive interpretation of
the parameter estimates can be elusive. The fight side of Table 2
presents results with the natural log of the Herfindahl as the dependent
variable, in which parameter estimates reflect the percentage change in
the Herfindahl due to a unit change in the explanatory variable. The
upper half of Table 2 reports models using the number of
football-related investigations in a conference as the measure of
enforcement. The lower half reports models using the number of pending
football-related probations as the measure of enforcement.
For each functional form and measure of enforcement, three models
are estimated: traditional instrumental variables two-stage least
squares (IV-2SLS), instrumental variables generalized method of moments (IV-GMM), and the dynamic panel estimator (DPD) developed by Blundell
and Bond (1998). The former two specifications allow for generalized heteroscedasticity and autocorrelation but do not correct for the
potential endogeneity concerns introduced by the lagged dependent
variable; the lagged dependent variable is treated as nonstochastic. The
anticipated bias in the first two specifications is perhaps as great as
2-3%. The dynamic panel data estimator uses the correct instrument for
lagged dependent variable. However, each specification yields very
similar results, indicating that the potential bias (either through the
lagged dependent variable or weak instruments) does not seem to be
serious.
An additional concern is introduced by the potential for
multivariate outliers in the data, especially in the case of the AAWU,
which was reduced to five teams for several years. The dramatic
reduction in the number of teams in that conference artificially
increased the HHI, which is partially accounted for by the inclusion of
the TEAMS variable. However, if the number of teams is not fully able to
accommodate the artificial yet dramatic increase in the HHI, both
inefficiency and potential bias can be introduced into the estimation.
To determine if there are any multivariate outliers, the procedure
proposed by Hadi (1992, 1994) was used to identify four outliers in the
data--the AAWU for the years 1959, 1960, and 1962 and the Western
Athletic Conference in 2001. A dummy variable was created that takes a
value of one for these four conferences in the appropriate years and
zero otherwise; this dummy variable is included in the estimation to
accommodate the outliers. The dummy variable did not dramatically alter
the estimates reported here but did improve the precision of the
parameter estimates.
Initial estimation was undertaken including conference- and
year-specific fixed effects. However, the estimation results were less
than satisfactory because of colinearity problems. The year-specific
effects were, therefore, dropped and replaced with a linear time trend
beginning in 1953 and its quadratic. Neither of these time variables
proved significant, and therefore, the final estimations include only
conference fixed effects, that is, the composite error term in
estimating Equation 1 is actually [[epsilon].sub.it] - [[alpha].sub.i] +
[u.sub.i].
The first-stage regressions are not reported here but are available
from the authors upon request. While the conference-specific effects
were all individually insignificant, the null hypothesis that they were
jointly insignificant was soundly rejected for all specifications. In
general, only a few of the instruments proved individually statistically
significant, although they were jointly significant for each
specification. The excluded instruments consistently significant at the
10% level were the relegation of schools to Division IAA status and
whether the conference was a BCS conference, both of which were
positively related to both the number of investigations or probations.
As shown by Bound, Jaeger, and Baker (1995), the strength of the
instrument set is inversely proportional to the joint significance of
the excluded instruments. Table 2 reports the first-stage F-statistics
on the excluded instruments. While the F-statistics are not as high as
might be hoped, they do indicate that the instrument set is sufficiently
strong in explaining the variation of investigations or probations.
Moreover, for each specification in Table 2, the Jansen test of
overidentifying restrictions cannot be rejected, indicating that the
instruments appear to he exogenous and valid.
Turning attention to the second-stage regression results reported
in Table 2, focusing first on the upper panel, the estimation results
are fairly robust across the various specifications. The parameter
estimate on the lagged dependent variable is consistently positive and
less than one, indicating that the evolution of conference-level
competitive balance is stable and that the number of teams in a
conference reduces the Herfindahl, as would be expected. The number of
football-related investigations consistently correlates with more
competitive balance (i.e., a lower concentration of performance points).
In both the IV-2SLS and IV-GMM specifications, each additional
investigation reduces the Herfindahl by approximately 155 points; the
DPD estimate is a bit lower in absolute value. In all three
specifications, the parameter estimates are statistically different from
zero in a two-tailed test and are safely characterized as less than
zero. The empirical results indicate that an increase in NCAA
enforcement efforts, as reflected in investigatory activity, improves
competitive balance, as reflected in a reduction in the HHI.
However, the severity of punishment, measured by the average length
of pending probations, is associated with a less-competitive
environment. A one-year increase in the average length of pending
probations reduces competitive balance, reflected in an increase in the
HHI of 27 to 35 points. This result is consistent with that of Fleisher
et al. (1988), who found that teams performed worse after being put on
probation.
To put the impacts of enforcement and punishment in perspective,
the right side of the upper half of Table 2 reports the results using
the natural logarithm of HHI as the dependent variable. The lagged
dependent variable indicates that approximately 18-22% of the previous
year's competitive balance is carried over into the next year. This
would indicate that a shock to a conference's competitive balance
(whether random or not) would take between 4.5 and 5.5 years to be fully
dissipated. This time frame is consistent with the eligibility of NCAA
student athletes and seems to indicate that the full effect of
punishment is felt only over time.
Each additional team in a conference reduces the Herfindahl by
approximately 8.6%. Each football-related investigation improves
competitive balance by approximately 6%, whereas a one-year increase in
the average length of pending probations reduces the competitive balance
measure by approximately 1.7%.
The bottom half of Table 2 presents similar estimation results,
replacing the number of football related investigations with the number
of football-related probations. The results are qualitatively consistent
with those in the upper half of Table 2. Approximately 24-27% of the
once-lagged competitive balance is carried over into the next year, and
the number of teams in the conference reduces the Herfindahl. The number
of pending probations in a conference has a statistically significant
and negative impact on the Herfindahl, indicating an improvement in
competitive balance, and the length of probations reduces competitive
balance. Notice that the marginal impacts of the number of probations
and the length of pending probations are greater than the analogous
estimates using investigations as the measure of enforcement. This might
indicate that probations (actual punishment) rather than investigations
(threatened punishment) are the more appropriate measure of enforcement.
While each probation is associated with an investigation, but not
vice-versa, actual probations might influence behavior and, hence,
competitive balance more so than investigations alone.
The instantaneous effects of enforcement and punishment are
reflected in the parameter estimates presented in Table 2; however, the
parameter estimates on the lagged dependent variable indicate a partial
adjustment process in the evolution of competitive balance in college
football conferences on the order of approximately four to five years.
This is intuitively appealing in the case of college football, because
NCAA rules limit student athletes to four years of eligibility in five
years. Therefore, if a football program is placed on probation and loses
scholarships for a number of years, the lost scholarships would be
expected to affect the program's competitiveness over time. This
indicates that the full impact of enforcement and punishment might not
be realized instantaneously.
The long-run impacts of enforcement and punishment can be
calculated as [[beta].sub.LR] = [[beta].sub.i]/(1 - [[beta].sub.tag]),
where [[beta].sub.it] is the parameter estimate of the variable in
question and [[beta].sub.tag] is the parameter estimate of the lagged
dependent variable (see Gujarati 1999, Ch. 14). Returning to the top
panel of Table 2, the empirical results indicate that an additional
football-related investigation improves the Herfindahl by 160-200
points, or by 7.6-10.3%, in the long run. On the other hand, if the
average length of probations increases by a year, the long-run impact is
to reduce competitive balance by increasing the Herfindahl by 36-45
points, or approximately 2%.
When using total probations as the measure of enforcement, the
long-run impacts of punishment and enforcement are more pronounced. An
additional probation generates a long-run improvement in competitive
balance of 222-240 points, or 11.9-12.9%, ceteris paribus. The long-run
impact of a one-year increase in the average length of pending
probations is a reduction in competitive balance by approximately 92-105
points, or 5-6%, ceteris paribus.
The long-run impacts of NCAA enforcement and punishment on the
competitive balance of collegiate football conferences have not,
heretofore, been estimated. The empirical results indicate that the NCAA
does influence member behavior using the credible enforcement mechanism
established in 1953. Although the evidence is indirect, the improvements
in competitive balance associated with enforcement indicate that
increased vigilance by the NCAA increases the overall expected costs of
cheating, reduces cheating, and yields a more equitable distribution of
player talent within a conference. However, the improvements in
competitive balance gained through enforcement do come at a cost: more
severe punishments reduce competitive balance.
Thus, it is natural to question whether the benefits of enforcement
activity outweigh the costs, at least in the dimension of competitive
balance. Proponents of the NCAA claim that enforcement enhances
competitive balance, which would be consistent with
investigations]probations and punishment combining to provide a net
reduction in the HHI. On the other hand, the NCAA's critics claim
that enforcement protects dominant programs, which would be consistent
with investigations/probations and punishment combining to have either
no impact or to cause an increase in the HHI.
To formally test which characterization of the NCAA is supported by
the data, two linear restrictions are tested for each specification. The
first tests whether the benefits outweigh the costs calculated using the
average number of investigations/probations and the average length of
probations for those conferences that had at least one football-related
investigation in that year (H1 in Table 2). This test restricts the
sample to include only those conferences that had direct enforcement
activity in a given year. The second test is more general and uses the
average number of investigations/probations and length of probations for
the entire sample (H2 in Table 2). This test focuses on whether
enforcement and punishment have a beneficial impact on competitive
balance even when no enforcement activity occurred in that conference.
As can be seen in Table 2, the evidence indicates that, in general,
the benefits of investigations/ probations outweigh the costs of
punishment, at least in the dimension of competitive balance. More often
than not the null hypothesis that the costs are greater than or equal to
the benefits of enforcement (i.e., the net effect of enforcement is a
reduction in competitive balance, an increase in the HHI) can be
rejected. Of those conferences with at least one football-related
investigation, the null hypothesis is soundly rejected in each of the 12
specifications. On the other hand, when using the entire sample, the net
benefits of enforcement and punishment are naturally lower and less
statistically robust. In only 10 of the 12 specifications can the null
hypothesis be rejected at conventional confidence levels. Overall, the
evidence indicates that in conferences in which enforcement actually
takes place, the net impact is a noticeable improvement in competitive
balance. In those conferences in which enforcement does not explicitly
occur, the impact of enforcement and punishment is a bit less dramatic;
it either slightly improves or has no net impact on competitive balance.
Is it possible or likely for the Herfindahl to experience a
three-figure decline, as suggested by the net-benefit tests presented in
Table 2? Moreover, if a conference experiences a three-digit drop in its
concentration, is it economically meaningful? Of the 401
conference-years in the sample, 57 correspond with an annual decline in
the HHI of more than 150 points. While many of these changes were caused
by conference expansion, this is not universally true. Table 3a reports
the conferences that experienced an annual decline in the HHI of more
than 150 points and also had at least one football-related investigation
in that year. Table 3b reports those conferences with a reduction in the
HHI of more than 60 points and at least one new football-related
probation.
Both Table 3a and 3b also report the net change in the number of
six-win teams in the conference the year the HHI dropped]5 Over the
sample period, the majority of teams played either 10 or 11 games, not
including conference championships and postseason bowl games. Therefore,
a net increase in the number of six-win teams would not only correspond
with an improvement in competitive balance but might also be important
from the point of view of fans. NCAA bylaws currently require a team to
have at least six wins against Division IA opponents in order to qualify
for a postseason bowl. From Table 3a, the average improvement in the
competitive balance of conferences with at least one football-related
investigation corresponds with an average of 0.26 more six-win teams.
The increase in the number of six-win teams is more pronounced in
conferences in which a new football-related probation is enforced--on
average, 0.52 more teams win at least six games. Thus, the impact of
NCAA enforcement efforts on competitive balance is not merely a
statistical artifact. The improved competitive balance often leads to
additional teams becoming bowl eligible, which likely enhances fan
interest.
Nevertheless, the NCAA could impose sufficiently harsh punishments
such that competitive balance was reduced in net. For example, suppose
one team in a conference was placed on probation for four years,
yielding an average length of pending probations of fours years. If an
additional team were placed on probation for, say, 16 years, the average
length of probation would increase from 4 to 10 years. Using the
estimation results from the bottom half of Table 2, a six-unit increase
in the average length of probations would lead to a 485-point increase
in the Herfindahl, whereas the gain from additional enforcement would be
a 182-point reduction in the Herfindahl. Thus, the extraordinary length
of the second probation would cause a net increase in the HHI of
approximately 300 points, or approximately 16% of the sample-average
HHI. Such an increase in the HHI would represent a dramatic reduction in
the competitive balance of the conference in which the probate team
played, and therefore the NCAA might avoid such draconian punishment, to
include the Death Penalty.
The empirical results support the NCAA's claim that its
enforcement efforts promote a more level playing field among its
members. However, the empirical results also provide insight into a
possible source of the concern expressed by the NCAA's critics. In
a partial analysis, it is true that more severe punishments reduce
competitive balance. However, these obvious reductions are generally
more than offset by the less-easily observed improvements in competitive
balance associated with greater NCAA vigilance, which are likely
reflections of reduced cheating on the part of a conference's
members.
5. Conclusions
This article extends the analysis of Fleisher, Goff, and Tollison
(1992); Eckard (1998); and Depken and Wilson (2004) by presenting an
investigation of the historical impact of NCAA enforcement activity on
the competitive balance of a sample of 11 major Division IA college
football conferences. Fleisher, Goff, and Tollison suggest that NCAA
enforcement might help dominant football programs, a sentiment which
Eckard seems to support. However, these claims contradict the NCAA,
which insists that its enforcement efforts are aimed at promoting
competitive balance. We develop empirical hypotheses that allow the data
to determine which claim is correct. The behavioral model follows Becker
(1968) by allowing punishment and deterrence effects to affect
competitive balance.
Whereas Eckard tests for statistical differences in the variance of
relative team rankings, we employ the HHI. Using both linear and lin-log
specifications, competitive balance is related to once-lagged
competitive balance, the number of teams in the conference, and measures
of enforcement and punishment. Because of a lack of strong theoretical
guidance with regard to how to measure enforcement efforts, two measures
are used: the total number of football-related investigations and the
total number of football-related probations in a given year. We measure
the severity of punishment as the average number length of pending
probations measured in years.
Our empirical analysis recognizes that if Fleisher, Goff, and
Tollison (1992) are correct, it is likely that the number of
investigations/probations is correlated with shocks to competitive
balance--the variables are stochastic regressors. Therefore, we use the
NCAA regime changes investigated by Depken and Wilson (2004) to
instrument for investigations and probations. The results from various
panel instrumental-variables estimators indicate that enforcement
efforts tend to correlate with improved competitive balance, whereas
punishment tends to correlate with reductions in competitive balance.
Moreover, the full effects of enforcement and punishment are only fully
dissipated after four to five years.
Statistical tests indicate that, on average, the benefits of
investigations/probations tend to outweigh the costs of increased
punishment, at least in the dimension of competitive balance. While we
are not able to directly test the impact of investigations/probations
and punishment on the amount of clandestine cheating in the NCAA, it is
likely that the improvements in competitive balance that are correlated
with investigations and probations are reflections of reduced cheating
by NCAA members. The empirical evidence indicates that the net impact of
investigations/probations and punishment is much greater, both in
absolute and statistical terms, in the conferences in which
investigatory behavior actually takes place. While there seems to be a
small amount of positive spillover to other conferences in which NCAA
enforcement efforts are not directly applied, these changes are not
economically significant (although they are statistically significant).
Overall, the empirical results support the NCAA's claim that
enforcement of its membership agreement enhances competitive balance.
The detractors of the NCAA seemingly focus only on the obvious reduction
in competitive balance that occurs when a team is put on probation and
suffers a reduction in on-field success. The empirical results do
indicate that teams placed on probation lose more games to above-average
teams, which might be viewed as an implicit rent-protecting scheme
perpetrated by the NCAA. However, the obvious reductions in competitive
balance are generally more than offset by less-obvious improvements in
competitive balance brought about by reduced cheating by all schools,
whether these schools are on probation or not. Future analysis in this
area might focus on the dollar costs of football-related probations, the
efficiency of the cost of enforcement being borne by those who may have
had no connection with the actions in question, and whether the impacts
of football-related probations extend beyond the gridiron.
Appendix
Conferences and Teams Included in the Sample. School Membership
Periods Reported in Parentheses if Different from Conference Years
Atlantic Coast Conference (1953-2003)
Clemson, Duke, Florida State (1992-2003), Georgia Tech (1983-2003),
Maryland, North Carolina, North Carolina State, South Carolina (1953-1971), Virginia, Wake Forest
Big East Conference (1991-2003)
Boston College, Miami (Florida), Pittsburgh, Rutgers, Syracuse,
Temple, Virginia Tech, West Virginia
Big Ten Conference (1953-2003)
Illinois, Indiana, Iowa, Michigan, Michigan State, Minnesota,
Northwestern, Ohio State, Penn State (1993-2003), Purdue, Wisconsin
Big 6-Big 7-Big 8-Big XII Conference (1953-2003)
Big 7 Conference (1948-1959):
Colorado, Iowa State, Kansas, Kansas State, Missouri, Nebraska,
Oklahoma
Big 8 Conference (1960-1994):
Colorado, Nebraska, Missouri, Iowa State, Kansas, Kansas State,
Oklahoma, Oklahoma State
Big XII Conference (1995-2003):
Baylor, Colorado, Iowa State, Kansas, Kansas State, Missouri,
Nebraska, Oklahoma, Oklahoma State, Texas, Texas A&M, Texas Tech
Conference USA (1995-2003)
Alabama-Birmingham (1999-2003), Army (1997-2003), Cincinnati, East
Carolina, Houston, Louisville, Memphis, Southern Mississippi, Texas
Christian (2001-2003), Tulane
Mid-American Athletic Conference (1962-2003)
Akron (1992-2003), Ball State (1975-2003), Bowling Green, Buffalo
(1999-2003), Central Florida (2002-2003), Central Michigan (1975-2003),
Eastern Michigan (1977-2003), Kent. Marshall, Miami (Ohio), Northern
Illinois (1975-2003), Ohio, Toledo, Western Michigan
Mountain West Conference (1999-2003)
Air Force, Brigham Young, Colorado State, Nevada-Las Vegas, New
Mexico, San Diego State, Utah, Wyoming
Pacific Coast-AAWU-Pacific 8-Pacific Ten Conference (1953-2003)
Pacific Coast (1916-1958):
California, Idaho, Oregon, Oregon State, Southern California,
Stanford, UCLA, Washington, Washington State
AAWU (1959-1967):
California, Oregon (1964-1967), Oregon State (1964-1967), Southern
California, Stanford, UCLA, Washington, Washington State (1962-1967)
Pacific 8 (1968-1977):
California, Oregon, Oregon Stale (1964-1977), Southern California,
Stanford, UCLA, Washington, Washington State
Pacific Ten (1978-2003):
Arizona, Arizona State, California, Oregon, Oregon State, Southern
California, Stanford, UCLA, Washington, Washington State
Southeastern Conference (1953-2003)
Alabama, Arkansas (1992-2003), Auburn, Florida, Georgia, Georgia
Tech (1953-1963L Kentucky, Louisiana State, Mississippi, Mississippi
State, South Carolina (1992-2003), Tennessee, Tulane (1953-1980),
Vanderbilt
Southwest Conference (1953-1994)
Arkansas (1953-1991), Baylor, Houston (1976-1994), Rice, Southern
Methodist, Texas, Texas A&M, Texas Christian, Texas Tech (1960-1994)
Western Athletic Conference (1962-2003)
Air Force (1980-1998), Arizona (1962-1977), Arizona State (1962
1977), Boise State (2001-2003), Brigham Young (1962-1998), Colorado
State (1968-1998), Fresno State (1992-2003), Hawaii (1979-2003),
Louisiana Tech (2001-2003), Nevada-Las Vegas (1995-1998), New Mexico
(1962-1998), Rice (1995-2003). San Diego State (1978-1998), San Jose State (1995-2003), Southern Methodist (1995-2003), Texas Christian
(1995-2001), Texas El Paso (1968-2003), Tulsa (1995-2003), Utah
(1962-1998), Wyoming (1962-1998)
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(1) The other organizations are the National Association of
Intercollegiate Athletics (NAIA), the National Christian College
Athletic Association (NCCAA) and the National Junior College Athletic
Association (NJCAA).
(2) The history of the NCAA has been well documented by other
authors, (e.g., Fleisher, Goff, and Tollison [1992], Eckard [1998],
Depken and Wilson [2004], and the NCAA itself).
(3) In 1950, the Council of the NCAA and the Executive Committee
attempted to terminate the NCAA memberships of Boston College, the
Citadel, the University of Maryland, the University of Virginia,
Villanova University, Virginia Military Institute, and Virginia Tech for
violation of the Sanity Code. However, a membership vote overturned the
recommended termination.
(4) NCAA rules hold for all intercollegiate sports. While this
article focuses on college football, the majority of NCAA infractions
occur in other sports.
(5) In 2003, there were 28 post-season bowl games, eight more than were
played in 1997. The following table presents select College Bowl Game
Payouts in 1997 and 2003:
2003 Payout 1997 Payout
Bowl Game Site per Team per Team
Fiesta Tempe, Arizona $14-17 M $9.45 M
Rose Pasadena, California $14-17 M $11.60 M
Sugar New Orleans, Louisiana $14-17 M $9.45 M
Orange Miami, Florida $14-17 M $9.78 M
Florida Citrus Orlando, Florida $5.1 M $3.98 M
Outback Tampa, Florida $2.65 M $1.93 M
Holiday San Diego, California $2 M $1.61 M
1997 payouts are measured in 2003 dollars. In 2003, the Florida Citrus
Bowl was renamed the Capital One Bowl.
Teams participating in bowl games retain a percentage of the per-team
bowl payout, the remainder shared with the other schools in the
participant's conference.
(6) The number of high profile whistle-blowers has increased over
the past 20 years. Notable examples include Jan Kemp at the University
of Georgia in 1986 (academic fraud); teachers and tutors at the
University of Tennessee in 1998 (academic fraud); academic tutors at the
University of Minnesota in 1999 (academic fraud); high school football
coaches affiliated with the University of Alabama and the University of
Kentucky in 2001 (bribery); and disgruntled players at the University of
Georgia in 2003 (academic fraud and bribery). These instances indicate
the willingness for people to report significant violations of NCAA
regulations, even if they lack passionate interest in the success of a
particular team or sport.
(7) Our normalization is only one possibility. Eckard (1998) awards
one point lbr a win and half a point for a tie. The impact our
normalization is to scale the parameter estimates: statistical inference is lint affected.
(8) Alternative measures of competitive balance focus on changes in
the relative standings of a conlerence's teams. Eckard (1998) and
Humphreys (2002) use the intertemporal variation in team position as a
measure of competitive balance, wherein greater variance indicates
better competitive balance.
(9) The two measures of enforcement are not used in the same
estimation because their correlation is approximately 0.75.
(10) The season champion of each BCS Conference earns an automatic
berth to one of the four BCS bowl games, from which the national
championship is determined. The BCS Conferences are the Southeastern,
Big East, Big Ten, Big XII, Atlantic Coast, and Pacific Ten, along with
Notre Dame.
(11) The data were gathered from the schools themselves,
newspapers, media guides, and the NCAA. They are available online at
http://www.cae.wisc.edu/~dwilson, last accessed December 2003.
(12) The Big 6 existed from 1928 through 1947 and included Iowa
State, Kansas. Kansas State, Missouri, Nebraska and Oklahoma. The Big 7
existed from 1948 through 1959 and included the same teams as the Big 6
with the addition of Colorado. The Big 8, which began in 1960 and lasted
through 1994, included the same teams as the Big 7 with the addition of
Oklahoma State. These eight teams joined four teams from the defunct
Southwest Conference to form the Big XII in 1995.
(13) Data were also gathered on new football investigations and the
different types of punishments imposed on football programs including
loss of scholarships, loss of postseason play, and loss of television
appearances. However, models including various types of penalties were
not statistically different from the results presented here.
(14) Schools often self-report and self-punish secondary
infractions, which are generally trivial violations such as a player
borrowing change from a coach to use a pay phone (which violates NCAA
bylaw 16.12.2.2).
(15) In this case, the number of wins includes non-conference wins.
Craig A. Depken II * and Dennis P. Wilson ([dagger])
* Department of Economics, University of Texas-Arlington,
Arlington, TX 76019, USA; E-mail depken@uta.edu.
([dagger]) Department of Economics, University of Texas-Arlington,
Arlington, TX 76019, USA; E-mail dpwilson@uta.edu; corresponding author.
We appreciate the helpful comments of two anonymous referees on a
previous version of the manuscript. Any remaining errors are the sole
responsibility of the authors.
Received October 2004; accepted July 2005.
Table 1. Descriptive Statistics of the Data
Standard
Variable Mean Deviation Minimum Maximum
Performance points
Herfindahl (HHI) 1488.34 318.65 755.03 3000.00
Log of HHI 7.28 0.20 6.62 8.01
Number of investigations (a) 0.54 0.79 0.00 4.00
Number of investigations (b) 1.39 0.66 0.00 4.00
Total number of probations 0.56 0.82 0.00 5.00
(a)
Total number of probations
pending (b) 1.08 0.94 1.00 5.00
Average length of probations
(a) 0.98 1.40 0.00 5.00
Average length of probations
pending (b) 1.68 1.39 0.00 5.00
Number of teams in 9.13 1.72 5.00 16.00
conference
Atlantic Coast Conference 0.123 0.33 0.00 1.00
Big East Conference 0.03 0.17 0.00 1.00
Big 10 Conference 0.12 0.33 0.00 1.00
Big 7-Big 8-Big XII 0.13 0.33 0.00 1.00
Conference
Conference USA 0.02 0.14 0.00 1.00
Mid-American Athletic
Conference 0.10 0.31 0.00 1.00
Mountain West Conference 0.01 0.10 0.00 1.00
Pacific Coast-AAWU-Pacific
8-Pacific 10 Conference 0.13 0.33 0.00 1.00
Southeastern Conference 0.13 0.34 0.00 1.00
Southwest Conference 0.10 0.31 0.00 1.00
Western Athletic Conference 0.10 0.30 0.00 1.00
Sample includes 401 observations describing 16 major Division IA
football conferences from 1953 to 2003; see Appendix for details.
(a) Based on entire sample.
(b) Based on 156 conference-year observations in which at least one
football-related investigation took place. The means of conference
dummy variables do not sum to 1 because of rounding.
Table 2. Instrumental Variables Panel Estimation Results
Dependent Variable: PPHI
Independent Variable IV-2SLS IV-GMM DPD
Lagged dependent 0.219 * 0.215 * 0.255 *
variable (0.06) (0.06) (0.04)
Teams in conference -120.709 * -120.722 * -113.219 *
(11.66) (11.58) (10.73)
Number of -155.051 * -156.109 * -113.466 *
Investigations (59.27) (58.54) (45.92)
Average length of 35.220 * 35.041 * 27.345 *
probation (12.37) (12.19) (10.79)
R-squared 0.761 0.76 --
First-stage F-stat on
excluded instruments 2.19 * 2.19 * --
Hansen J-statistic
of overidentifying
restrictions 0.84 0.84 3.25
F-test: zero slopes 85.08 * 85.50 * 265.98 *
H1: Net effect of -157.44 * -159.216 -112.57 *
average enforcement [0.02] [0.01] [0.04]
efforts on
competitive balance
measure (conferences
with at least one
investigation) (a)
H2: Net effect of -49.62 * -50.37 * -34.76 *
average enforcement [0.03] [0.02] [0.07]
efforts on competitive
balance measure
(entire sample) (b)
Lagged dependent 0.240 * 0.243 * 0.274 *
variable (0.05) (0.05) (0.05)
Teams in conference -123.217 * -121.949 * -113.686 *
(12.10) (11.79) (12.31)
Number of -182.536 * -178.446 * -161.455 *
probations (63.86) (62.81) (68.64)
Average length of 80.922 * 79.082 * 67.461 *
probation (27.00) (26.39) (27.93)
R-squared 0.773 0.778 --
First-stage F-stat
on excluded
instruments 2.89 * 2.89 * --
Hansen J-statistic
of overidentifying
restrictions 0.65 0.65 3.06
F-test: zero slopes 84.27 * 86.09 * 75.12 *
H1: Net effect of -61.63 * -60.30 * -61.44 *
average enforcement [0.03] [0.03 ] [0.08]
efforts on competitive
balance measure
(conferences
with at least one
investigation) (a)
H2: Net effect of -21.85 ** -21.39 ** -23.38
average enforcement [0.08] [0.08] [0.13]
efforts on
competitive balance
measure
(entire sample) (b)
Dependent Variable: Log PPHI
Independent Variable IV-2SLS IV-GMM DPD
Lagged dependent 0.183 * 0.179 * 0.231 *
variable (0.09) (0.02) (0.04)
Teams in conference -0.087 * -0.087 * -0.081 *
(0.006) (0.006) (0.01)
Number of -0.081 * -0.085 * -0.058 *
Investigations (0.03) (0.03) (0.02)
Average length of 0.019 * 0.019 * 0.015 *
probation (0.01) (0.01) (0.01)
R-squared 0.821 0.806 --
First-stage F-stat on
excluded instruments 2.36 * 2.36 * --
Hansen J-statistic
of overidentifying
restrictions 1.04 1.04 3.86
F-test: zero slopes 139.03 * 139.39 * 530.21 *
H1: Net effect of -0.081 * -0.085 * -0.056 *
average enforcement [0.03] [0.02] [0.05]
efforts on
competitive balance
measure (conferences
with at least one
investigation) (a)
H2: Net effect of -0.025 * -0.027 * -0.017 **
average enforcement [0.05] [0.04] [0.09]
efforts on competitive
balance measure
(entire sample) (b)
Lagged dependent 0.204 * 0.204 * 0.247 *
variable (0.05) (0.05) (0.05)
Teams in conference -0.088 * -0.088 * -0.081 *
(0.01) (0.01) (0.01)
Number of -0.103 * -0.102 * -0.090 *
probations (0.04) (0.04) (0.04)
Average length of 0.046 * 0.046 * 0.039 *
probation (0.02) (0.02) (0.02)
R-squared 0.815 0.816 --
First-stage F-stat
on excluded
instruments 2.94 * 2.94 * --
Hansen J-statistic
of overidentifying
restrictions 0.94 0.94 3.78
F-test: zero slopes 120.67 * 122.47 * 799.54 *
H1: Net effect of -0.034 * -0.033 * -0.032 **
average enforcement [0.04] [0.04] [0.08]
efforts on competitive
balance measure
(conferences
with at least one
investigation) (a)
H2: Net effect of -0.012 ** -0.012 ** -0.012
average enforcement [0.10] [0.091 [0.13]
efforts on
competitive balance
measure
(entire sample) (b)
All specifications include conference fixed effects and a dummy
variable to control for four outliers, determined using the method
proposed by Hadi (1992, 1994). Number of investigations and number of
probations instrumented with major regulatory changes in the NCAA
membership agreement and whether a conference is a BCS Conference; see
text for details. IV-2SLS and IV-GMM are
heteroscedastic-autocorrelation (HAC) consistent estimates. DPD are
Blundell and Bond (1998) Dynamic Panel Data estimates.
(a) Net benefits calculated using average number of investigations or
probations and average length of probations among sample conferences in
which at least one investigation took place (see Table 1).
(b) Net benefits calculated using the average number of investigations
or probations and average length of probations for the entire sample
(see Table 1).
* Indicates significance at the 5% and ** 10% level in a two-tailed
test. Robust standard errors reported in parentheses; two-tailed p
values reported in brackets.
Table 3a. Sample Conferences with One-Year Decline in Herfindahl, More
than 150 Points, and at Least One Football-Related Investigation
Conference Year HHI [DELTA]HHI
Atlantic Coast 1955 1759.003 -231.737
Atlantic Coast 1961 1331.361 -244.083
Atlantic Coast 1983 1632.373 -385.767
Atlantic Coast 1992 1435.185 -191.090
Big 8 1972 1511.480 -248.724
Big 8 1981 1549.745 -165.816
Big 8 1992 1485.969 -274.234
Big Ten 1969 1248.980 -163.265
Big Ten 1984 1207.407 -182.716
Conference USA 1998 1666.667 -399.491
Mid-American 1969 1791.383 -260.771
Mid-American 1980 1145.125 -244.224
Pacific 10 (AAWU) 1964 1675.900 -546.322
Southeastern 1992 1064.140 -282.798
Southwest 1957 1780.045 -283.446
Southwest 1974 1575.255 -153.061
Southwest 1976 1469.907 -239.276
Southwest 1989 1435.185 -325.018
Western Athletic 1969 1712.000 -197.262
Averages 1498.795 -264.163
Change in
Conference %[DELTA]HHI Six-Win Teams
Atlantic Coast -11.64 0
Atlantic Coast -15.49 -2
Atlantic Coast -19.11 -1
Atlantic Coast -11.75 0
Big 8 -14.13 +1
Big 8 -9.66 +1
Big 8 -15.57 -2
Big Ten -11.56 -2
Big Ten -13.14 +2
Conference USA -19.33 +1
Mid-American -12.71 0
Mid-American -17.57 0
Pacific 10 (AAWU) -24.58 +2
Southeastern -20.99 +1
Southwest -13.73 0
Southwest -8.85 +3
Southwest -13.99 0
Southwest -18.46 0
Western Athletic -10.33 +1
Averages -14.87 +0.26
Four other observations, not reported here, corresponded
with conferences that experienced an annual drop in the HHI of
between 140 and 150 points. The change in six-win teams
reflects total victories, including nonconference and non-Division
1A opponents. During the sample period, teams played either 10 or
11 games (not including conference championship and postseason
bowl games). Therefore, six wins would correspond to an above-average
team.
Table 3b. Sample Conferences with One-Year Decline in Herfindahl
Greater than 60 Points and at Least One New Football-Related Probation
Conference Year HHI [DELTA]HHI
Atlantic Coast 1955 1759.003 -231.738
Atlantic Coast 2003 1327.161 -123.45
Big East 1994 1639.031 -146.687
Big East 2003 1658.163 -76.530
Big 8 1970 1607.143 -76.530
Big 8 1972 1511.480 -249.725
Big 8 1981 1549.745 -165.816
Big Ten 1974 1296.875 -87.50
Big Ten 1999 1146.694 -92.975
Mid-American 1969 1791.383 -260.771
Mid-American 2002 969.5291 -110.71
Pacific Ten 2002 1237.500 -87.500
Southeastern 1981 1378.772 -109.261
Southeastern 1990 1269.388 -77.551
Southwest 1957 1780.045 -283.446
Southwest 1958 1700.680 -79.365
Southwest 1966 1530.612 -102.041
Southwest 1974 1575.255 -153.061
Southwest 1976 1469.907 -239.276
Southwest 1989 1435.185 -325.019
Western
Athletic 1997 755.0296 -108.14
Averages 1447.075 -151.766
Change in
Conference %[DELTA]HHI Six-Win Teams
Atlantic Coast -11.64 0
Atlantic Coast -8.51 -1
Big East -8.21 0
Big East -4.41 +2
Big 8 -4.54 0
Big 8 -14.13 +2
Big 8 9.66 +1
Big Ten -6.32 +2
Big Ten -7.50 +2
Mid-American -12.71 0
Mid-American -10.25 +1
Pacific Ten -6.60 +2
Southeastern -7.34 0
Southeastern -5.75 -2
Southwest -13.73 0
Southwest -4.45 -1
Southwest -6.25 -1
Southwest -8.85 +3
Southwest -13.99 0
Southwest 18.46 0
Western
Athletic -12.52 +1
Averages -6.64 +0.52
The change in six-win teams reflects total victories, including
nonconference and non-Division IA opponents. During the sample
period teams played either 10 or 11 games (not including conference
championship and postseason bowl games). Therefore, six wins would
correspond to an above-average team.