Sociology Mind
2012. Vol.2, No.4, 447-457
Published Online October 2012 in SciRes (http://www.SciRP.org/journal/sm) http://dx.doi.org/10.4236/sm.2012.24058
Copyright © 2012 SciRes. 447
Does Pay Disparity Really Hamstring Team Performance?
A Study of Professional Ice Hockey Players
Noah Stefanec
Claremont Graduate University, Claremont, USA
Email: noahstefanec@hotmail.com
Received May 3rd, 2012; revised June 8th, 2012; accepted June 19th, 2012
Here, I employ an unbalanced panel of data from the National Hockey League (NHL) to examine the im-
pact of pay disparity on team-cohesiveness. I find evidence to suggest the existence of a negative rela-
tionship between higher degrees of within-position pay disparity and team performance; the evidence re-
ported here shows a simple monotonic elasticity of team performance with respect to pay disparity to be
roughly 19%.
Keywords: Relative Compensation; Pay Compression; Industrial Politics
Introduction
Insights into the general nature of relative compensation
schemes reveal that enhanced cooperation amongst workers in a
firm can be achieved via compression of the wage structure.
Proponents of this theoretical concept, such as Milgrom and
Roberts (1988), Akerlof and Yellen (1988, 1990), Lazear
(1989), and Levine (1991), offer convincing, well-motivated,
and detailed theoretical justifications for the effectiveness of
pay compression on improved team-cohesiveness. Conceptually,
the notion is quite simple: If a relatively large degree of earn-
ings inequality was to exist in a relative-based reward system,
then workers in the same firm are incentivized to compete
against each and thus team-cohesiveness breaks down. Ac-
cordingly, an elevated degree of earnings equality disincentive-
izes anticooperative behavior amongst employees. Theoreti-
cally speaking, however, an efficient level of pay dispersion
may be able to persist within a firm without motivating subvert-
sive behavior.
Ramaswamy and Rowthorn (1991), for instance, also pro-
pose a convincing theoretical argument which disputes the ef-
fectiveness of pay compression. Their dissent mainly centers on
the behavioral tendencies of the workers within a particular
group (firm). When a group of individuals strive for a common
goal, the personality composition of the group is of great im-
portance: Individuals with so-called “damage potential” may
need to be paid efficiency wages in an effort to mitigate their
desire to harm the team’s productivity. In this way, a certain
extent of pay disparity can exist within the group yet not be a
causal mechanism directly related to collaborative behavior.
Both parties offer lucid, rational arguments possessing their
own particular merits, and the debate has attracted serious
mainstream and academic attention.
Unfortunately, firm-level data is notoriously difficult to ac-
quire, making empirical evaluations of these theories difficult.
This has forced many empirical researchers to employ more
creative means to explore this topic. Recently, many have re-
sorted to utilizing the accurate and readily-available salary and
performance data regarding professional athletes in an attempt
to empirically document the effects of changes in reward struc-
tures on collaborative behavior (Depken, 2000; Berri & Jewell,
2004; Garcicano & Palacios-Huerta, 2006). The results of these
studies have thus far been mixed, leaving the subject open to
debate.
The purpose of this paper is to empirically study the effects
of increased degrees of pay disparity on the behavior of profes-
sional hockey players. Although I make no claim that a hockey
club is representative of every single type of private-sector firm,
the results may still be able to offer significant insights into the
behavioral response of workers to changes to within-group
earnings equality. The main question addressed by this paper is:
Does a higher echelon of pay inequality really disincentivize
teamwork?
Section 2 discusses the past and current literature related to
the topic of pay compression. In lieu to the model found in
Ramaswamy and Rowthorn (1991), Lazear’s (1989) more clas-
sical model of industrial politics was adapted to better mirror
the world of professional hockey. This model, found in Section
3, predicts higher degrees of (within-position) pay inequality
result in less team-oriented behavior, although certain altera-
tions to key assumptions can relax this result. Section 4 dis-
cusses the empirical methodology utilized to test the theory;
team winning percentage is employed as the dependent measure
of team performance while a modified intraposition version of
the Herfindahl-Hirschman Index (HHI) reflects pay disparity.
Section 5 reports the findings obtained from the employment
of a panel-based empirical approach. The evidence presented
here demonstrates a statistically and economically significant
negative relationship between higher degrees of pay disparity
and team performance. Particularly, I find the elasticity of team
performance with respect to pay disparity to be roughly 19%.
Section 6 addresses possible complications in the study while
Section 7 concludes.
The Literature
The existing sports economics literature regarding pro-
fessional hockey is chiefly empirical and has long been
dominated by the debate over the potential discrimination of
French-Canadian skaters playing for teams in English-speaking
N. STEFANEC
Canada (Lavoie et al., 1987; Jones & Walsh, 1988; Mclean &
Veall, 1992; Longley, 1995; Krashinsky & Krashinsky, 1997;
Curme & Daugherty, 2004)1. In this literature, the standard
procedure for explaining the variation in pay across hockey
players has been to assume parsimonious marginal revenue
product-based earnings equations following Mincer (1974), but
theoretically speaking, little work has been done to model the
compensation structure of players in the National Hockey
League (NHL). This paper abstracts from the marginal revenue
product-based explanation of wages for professional hockey
players in an attempt to study the effects of increased pay
dispersion on team performance.
Hockey players are generally thought to be cooperating with
their teammates against a common opponent, but in a more
abstract sense, each player is also competing against members
of their own team who occupy the same on-ice position (i.e.
center, right wing, etc.) in hopes of being awarded a higher
salary upon the basis of their ordinal rank. From this perspec-
tive, hockey as a profession can be viewed as a rank-order
promotional tournament (Lazear & Rosen, 1981). Moreover,
incremental increases in pay based upon ordinal rank become
larger as players become recognized as highly talented, not
unlike the so-called “superstar effect” usually reserved for the
discussion of top-executive compensation packages (Rosen,
1981). Even in the world of professional hockey, the hierarchal
structure within any given position can be as important an in-
centive mechanism to a player as their total compensation
package.
Relative-based pay is appropriate when transaction costs
render payment based upon absolute performance ineffective
(Lazear, 1986, 2000). In professional hockey, this is fairly close
to what is observed. Performance bonuses notwithstanding,
players are not paid solely/explicitly by the piece per se (i.e. by
goals, assists, hits, etc.) because an attempt to do so could result
in a dysfunctional incentive. Recalling Kerr (1975) and Baker
(1992), a payment scheme such as
12 3
goals assists hitsyab bb 
'bs
bbb
(where y is gross compensation, a is some base-salary, and
are the piece-rates associated with each respective performance
measure) will ensure multi-tasking by players; for instance,
players will place too much emphasis on hits and pay less at-
tention to passing and scoring attempts if .
321
In a similar vein, the theory of relative compensation gener-
ates a transparent lens through which the interaction of workers
within a firm can be viewed. As with any compensation scheme,
relative pay can also be dysfunctional to a degree. Pay com-
pression proponents argue that a higher level of intrafirm pay
disparity can be inefficient as compensation based upon ordinal
rank can incentivize uncooperative behavior and internal dis-
sonance (Milgrom & Roberts, 1988; Akerlof & Yellen, 1988,
1990; Lazear, 1989; Levine, 1991). This theory thus illustrates
a classic economic trade-off between productive incentives and
cooperation: Higher wage inequality between winners and los-
ers of a promotional tournament generates both the incentive to
supply effort and the disincentive to work in concert with fel-
low employees, leading to blatant sabotage. Strangely enough,
this idea is put most eloquently by comedic actor Leslie Nielsen
who once wrote: “You dont win golf matches by trying to take
strokes off your own score; you win golf matches by doing eve-
rything within your power to see to it that your opponent adds
strokes to his score.”2 Accordingly, some degree of pay com-
pression can be (relatively) efficient as it detracts attention
away from subversive behavior and encourages cooperation,
although a tighter wage distribution may hamstring the firm by
lowering the equilibrium level of individual effort.
Various predications of pay compression theory have been
subjected to empirical testing. Particularly, the application of
sports data to this particular problem has helped lend pay com-
pression proponents marginal support. Sports data is recently
becoming more widely-utilized by labor economists due to its
accuracy, its availability, and the ease to which economic the-
ory explained through the lens of professional sports can be
more relatable to students in the classroom. For example, Dep-
ken (2000) employs a panel-data approach using observations
from Major League Baseball (MLB) and finds that teams with
less earnings disparity experienced improved group perform-
ance (as measured by team winning percentage).
More recently, Garcicano and Palacios-Huerta (2006) find
professional soccer players responded to a change in their in-
centive structure designed to encourage scoring (an increased
number of points for winning the match) by increasing both
their level of play and their level of sabotage, such as tackling
opponents (again, a dysfunctional incentive can produce physi-
cal danger) or “freezing the game” when ahead late in the
match. In line with the predictions of industrial politics, the
authors find that a decompression of the reward structure for
soccer players resulted in both higher equilibrium levels of
individual effort and sabotage, yet this study offers no direct
link between pay disparities and team performance. Most of
these above findings tend to side with the proponents of pay
compression, yet other theories and their subsequent empirical
testing has ignited a debate in the literature about the topic.
On the opposing side of the pay compression theory, some
contend that group productivity and the level of earnings dis-
persion within a firm are unrelated. Most notably, Ramaswamy
and Rowthorn (1991) argue that firms should pay workers with
so-called “damage potential” efficiency wages to lessen their
tendencies towards shirking, negligence, or disruptive conduct.
In this way, wage rates are an increasing function of “damage
potential” and thus earnings dispersion (while still efficient) can
persist yet be completely unrelated to team performance. There
is empirical evidence to support this theory as well; for example,
Berri and Jewell (2004) employ data from the National Basket-
ball Association (NBA) and find a non-negative relationship
between wage disparity and team productivity. These findings
would tend to refute the arguments made by pay compression
proponents3.
Because empirical support for pay compression theory re-
mains rather mixed, the subject is still very much open to de-
bate. One sport as yet unexamined by empirical researchers is
professional hockey; a behavioral analysis of hockey players is
important and innovative in that the frame of reference regard-
ing pay disparity can be narrowed from an aggregate firm-level
down to a more realistic, intrapositional level. The evidence
presented here suggests the existence of a negative relationship
1Changes to the incentive structure prior to the 2000-2001 season regarding
overtime victories have also been investigated in the past (Easton & Rock-
erbie, 2005; Shmanske & Lowenthal, 2007).
2Adapted from Leslie Nielsen’s Stupid Little Golf Book, Doubleday Pub-
lishing (1995: p. 69).
3Other studies suggest that race (rather than pay disparity) does not influ-
ence the level of cooperation within the workplace, especially in a highly
visible setting (Lefgren et al., 2009).
Copyright © 2012 SciRes.
448
N. STEFANEC
between higher degrees of within-position pay disparity and
team performance; I find the elasticity of team performance
with respect to pay disparity to be roughly 19%.
The Model
A simple, classical model of a relative compensation scheme
similar to that found in Lazear (1989) is adapted here to more
adequately reflect the environment of a professional hockey
player. The main prediction of this model is that compression
of the intraposition salary structure should increase the degree
to which players work in concert with their intrapositional
counterparts. Accordingly, decompression of the salary struc-
ture results in position-wise disunity and anticooperative be-
havior.
i) Basic setup of the model.
As an abstract alternative to the marginal revenue prod-
uct-based explanation of wages for professional athletes, as-
sume relative compensation is appropriate. Regard a hockey
club as a single firm consisting of two ex-ante identical players
j and k who are competing for larger salaries based upon their
within-group ordinal rank (mutually exclusively defined by
center, right winger, left winger, defensemen, or goalie). As
opposed to the entire league or single team (which is represent-
tative of a single firm), the position a player occupies is as-
sumed to be the reference group; for example, it is unlikely that
a defensemen would be seeking to compete for a position as a
center within any given team. Superior rewards are also as-
sumed to be tied to job titles such as captain or alternate captain.
There are a fixed, limited number of players who can earn these
titles and in this way wages are tied to the “job” rather than to
the individual as emphasized by Lazear and Rosen (1981)4.
Two possible outcomes exist for the competing players. The
winning player earns a job title and an accompanying wage of
1 while the losing player earns a wage of 2. Of course, it is
the case that 12
. Define the wage “tilt” as 12
.
The wage tilt can be thought of as the level of earnings disper-
sion or the degree of wage (in) equality between the winner and
loser of the tournament. Also define .
w w
wwww 
Ww w
12
The productivity of professional athletes is generally thought
to exist across two dimensions: Individual duties and informal
obligations to teammates. Accordingly, every risk-neutral pro-
fessional hockey player exercises the production function:
12
θ,θf
θ
0, 0ff θ
θ
θ
0f
θ
0
θ
θ
θ
θ
θ
0f
(1)
where 1 is a player’s average level of individualistic on-ice
productivity (which can also be extended to include many of
the intangible aspects of athletic aptitude such as coachability,
persistence, and drive, all of which produce level-effects on
individual performance in any a respective position) where
111
while 2 can be generally be thought of as
intrapositional team-oriented behavior both on and off-the-ice.
For example, higher chosen equilibrium values of the latter
argument can include increased camaraderie, mentorship, and
knowledge-sharing regarding behavioral tendencies of oppos-
ing players. Put more colloquially, the first argument of the
production function 1 measures the degree to which a player
“plays for the name on the back of the jersey” while the second
argument of the production function 2 captures the degree to
which a player “plays for the logo on the front of the jersey.” It
is commonly believed that collaboration is mutually beneficial;
thus, it is assumed that .
2
While 1 is assumed to be strictly positive (a zero value of
individual effort would result in termination in all likelihood),
there is no assumption here which restricts 2
θ; the
possibility of a zero value of 2 exists. Negative values of
2 may exist on the ice only for defensemen (since this is the
only time where two players occupying the same position are
on the ice simultaneously) but negative values of 2 probably
do not exist in the locker room (e.g. sabotaging equipment, etc.)
due to the high degree of visibility on that margin. Thus,
negative values of 2
θ are assumed away but allowing for
them would not change the results of the model in any signi-
ficant manner. Basically, low positive values of 2
θ below
some threshold are a general indication of “damaging” antics
such as missing or complaining during practice, reputational
assaults on positional counterparts in the media, refusing to
mentor a younger player aspiring to play the same position, or
the withholding of knowledge. Small equilibrium values of 2
may hurt teammates in the short-run or may eventually cause
teammates to ignore the player’s behavior in the long-run.
Exceedingly large values of 2 may even result in the firing
of a disruptive player due to peer-pressure by co-workers5. For
simplicity in modeling, the higher-order derivative regarding
the second argument of the production function is assumed to
be monotonic such that 22 .
Certainly both workers in firms and players on sports teams
exert zero, small or even large values of 2, and the main aim
of this paper is to address and empirically test the two compet-
ing hypotheses regarding this phenomenon: Is this behavior in
fact (at least to some degree) motivated by the degree of pay
inequality? A definitive answer to this question can benefit
many human resource managers seeking both enhanced internal
harmony from their employees as well as isolating and healing
possible sources of internal friction amongst their employees.
In a sports context, these results may alert team owners to the
amount of in-fighting they are causing amongst their own team
via pay inequalities which exist within them their chosen rela-
tive pay scale.
θ
4Captains are the only players allowed to converse with referees on the ice
over ruling disputes. When the captain is not present, the alternate captain
fills this role. The assumption that higher wages are tied to these jobs is
abstract; players in these roles usually have larger marginal revenue prod-
ucts, more leadership ability, and longer experience as well.
5An appropriate example here is a recent incident involving Sean Avery, a
known agitator reputed to have ill-relations with many of the players and
coaches in the league. In fact, 66.4% of his peers ranked him the
“most-hated player in the league” according to a 2007 poll of 283 NHLers
(The Hockey News, 2007). While playing for the Dallas Stars at the start o
f
the 2008-2009 season, he made inappropriate and anti-social comments
off-the-ice, causing (initially) a six-game suspension (CBC Sports, 2008)
which was then extended indefinitely until a mandatory anger management
treatment program could be completed. During this period of rehabilitation,
the entire Dallas Stars organization (front-office, coaches, and players)
collectively decided Avery would not be welcomed back into the locker
room (Duthie, 2008). He was placed on waivers (i.e. fired), yet subse-
quently (re)hired by the New York Rangers.
Following Lazear (1989), the individual output of players j
and k is given by:
12
θ,θε
j
jk j
qf (2a)
and
12
θ,θε
kkjk
qf (2b)
θ0
respectively, where 2k (take 2
θk, for example) is the
amount of cooperative effort player j exerts which favorably
Copyright © 2012 SciRes. 449
N. STEFANEC
affects the output of teammate k. is traditionally thought of
as stochastic productive luck or as measurement error in deter-
mining the final ordinal ranking where
ε
ε0E. The prob-
ability that player j defeats player k is then given as:
12
θ,
j
Gf21
θθ,θ
kj
f


Pr k
pqq
jk (3)
where
G is the cumulative distribution function. Finally,
team output is given by:
,
j
k
QQqq. (4)
To ensure that this is not a zero-sum game for the principal,
allow total output to be tied directly to fan attendance (A) such
that
,
jk
qEQq
W
 
. Profit is then given by

where the price of a ticket is essentially normalized to unity.
Total team output is thus defined as having a dollar-to-dollar
relationship with fan attendance, implying that winning teams
(i.e. those consisting mainly of players with higher net yield)
sell more tickets. An individual’s net yield is the difference
between their (expected) output and their cost of effort, the
latter function given by
12
θ,θCwhere
for all players, positions, teams, and seasons.
111 222
,,, 0C C

CC
The remainder of the theoretical section is designed to pre-
dict the response of players to an increased degree of pay
equality. The behavior of a professional hockey player is mod-
eled as a two-stage principal-agent game. In the first stage of
the problem, symmetric players competing for jobs at the same
position solve for equilibrium levels of individual effort and
team-oriented effort taking the wage tilt as exogenous. Given
the players’ labor supply behavior, a single non-monopsonist
team owner then chooses the wage tilt to maximize rent-per-
player subject to a zero-profit constraint.
ii) A player’s problem.
Although both players solve the same labor supply problem,
arbitrarily consider the maximization problem of defenseman j.
Recall each player is ex-ante identical in ability and that players
are assumed to occupy the same position (so player k is also a
defenseman). Taking the wage tilt as exogenous, player j
maximizes his expected utility by choosing both his individu-
ally-motivated and cooperative levels of effort, respectively.
Following Lazear (1989), the problem is given as:
12
12112
θ,θ
max w1wwθ,θ
jj
j
j
pC

where the necessary first-order conditions for a maximum are
given by:
1112
0θ,θ
j
k
gCf
(5a)
2212
(0) θ,θ
kj
gCf
(5b).
g
The probability density function
εε
is evaluated at zero
because the equilibrium is Cournot-Nash, which is conven-
tional in the tournament literature. Assuming players adopt a
winning strategy (i.e. there is a large enough spread between
kj
), the second order-conditions sufficient for an interior
solution are given by:
11 11
00gfC

22 0C
(6a)
(6b).
Thus, the equilibrium level of individual effort is given by
*
θθ
11jj
and the equilibrium level of team-oriented effort
is given by
*
θθ
22jj
.
From Equation (5a), it is seen that larger wage tilts generate
higher equilibrium levels of individual effort. Comparative
statics show that holding cooperative behavior constant and
differentiating (5a) with respect to individual effort, the partial
derivative of individual effort with respect to pay disparity is
positive and given by:

11
11 11
θ00
0
jgf
Cgf
(7a).
 
Ceteris paribus, a decompression of the salary structure
within the frame of reference motivates players to produce a
higher level of individual effort (Lazear & Rosen, 1981)6. Ac-
cordingly, compression of the pay structure discourages com-
petitive spirit. A decompression of the pay structure, however,
implies a lower equilibrium level of cooperative effort and
illustrates the essence of this classical economic tradeoff:
Higher pay disparity is reflected in less harmonious attitudes
towards others competing for the same position, ceteris paribus.
This can be seen from Equation (5b), where holding effort con-
stant and differentiating with respect to team-oriented behavior,
the partial derivative of cooperation with respect to pay dispar-
ity is negative and given by:
6There exists a large body of empirical work to support this predication; see
(for example) Ehrenberg and Bognanno (1990a and 1990b) and Freeman
and Bell (1999).
7As a theoretical aside, the assumption made with respect to the
higher-order derivative of the second argument of the production function is
crucial to this result. First, a more canonical assumption regarding the
second-order derivative of a production function is to assume that the ar-
gument exhibits diminishing returns such that f22 < 0. In other words, a
player who moves further away from choosing a corner solution of zero in
θ2 may only drive his teammate to respond increasingly positive up to some
relevant range. Alternatively, increasing returns such that f22 > 0 is also a
possibility. Thus, for equation (7b) to hold negative under these possibilities
it then must be the case that . Therefore, although
sensitive to changes in assumptions, this classical model leaves open the
possibility that pay disparity and cooperation may have a non-negative
relationship as suggested by Ramaswamy and Rowthorn (1991).
22
22
θ00
jgf
C

 (7b).
The goal of the forthcoming empirical analysis is to test the
prediction of Equation (7b): Does a decompression of the re-
ward structure really result in lower equilibrium levels of col-
laborative behavior?7 These results also imply that, all else
equal, a higher echelon of intra-position wage equality will
benefit NHL team owners by improving group performance,
attendance, and net profit. Before proceeding to the empirical
analysis, the impact of improved cooperation on profit is briefly
discussed in the next section.

1
0g


iii) A team owner’s problem.
A single team owner acting as principal seeks to maximize
the expected profit-per-position (net rent) subject to a zero
profit constraint8. Team owners are assumed to possess no mo-
22 22
fC
8It is relevant to note that an entirely separate debate about this issue exists
in the sports economics literature. Kesenne (1996, 2006), for instance,
suggests win percentage maximization or even talent maximization as other
viable possibilities. Here, it is simply assumed that greater cooperation
generates a more successful and profitable team. Thus, the team owner need
not maximize win percentage directly because a profit-maximizing selec-
tion of the wage tilt should (in theory) accomplish the same goal. This does,
however, suggest a simple negative relationship between pay disparity and
cooperation which may not be the case (this will be discussed later).
Copyright © 2012 SciRes.
450
N. STEFANEC
nopsonistic bargaining power over the players. By strict defini-
tion, a monopsony is a single buyer in the market for a good (in
this case, a hockey player). Recall each team is analogous to a
single firm; because the NHL is comprised of thirty teams (two
conferences, each with three divisions and five teams per divi-
sion), the NHL does not appear to operate under imperfect
competition in so as far as it has been emphasized in most of
the prior literature regarding the sport9. Again following Lazear
(1989), an owner’s problem is given as:

max μ,


θμ,θ
j
jkk
C
WC
st WA
where the necessary first-order condition for a maximum is
given by:
12112
μθ μθ0Eff QCC
 
 

(8).
From Equation (8), it can easily be seen that net output is
higher when positional teammates are more prone to work to-
gether. Fundamentally, this is because the marginal cost of
effort is higher on a dysfunctional team. This result can be de-
rived more formally by solving for the marginal cost of effort in
Equation (8) and comparing a game in which the possibility of
cooperation is zero and a game in which the possibility of co-
operation is greater than zero. Respectively, these are given by:
1
CE11
Qf (8a)
and
122
111
θθ
θθ
Qf C
CEQf 





(
8b).
Each additional unit of effort costs more on the margin in
Equation (8a) than in Equation (8b) because the inequality
12 12
θ,θ0θ,θ0CC 
holds for all players. Thus, any team owner who incentivizes
teamwork realizes greater net profits because
12 12
2θ,θ0)2 θ,θ0QC QC  
w%
θ
HHI
.
Data and Empirical Approach
The empirical testing of economic theories derived from a
within-firm frame of reference is largely contingent upon the
availability of such data. Although some have managed to
obtain and utilize performance date from within a firm (e.g.
Lazear, 2000), firm-level data is notoriously difficult to obtain.
In response, many researchers have turned attention to data
gathered with regards to professional athletes. The attractiveness
of sports data mainly centers on its large degree of availability,
its low degree measurement error due to higher levels of
observability, and the ease to which economic concepts
explained via phenomenon observed in professional sports can
be more relatable to students in the classroom.
i) The data.
The unbalanced panel describing professional hockey players
assembled and employed for use in this study includes
observations from the 2000-2001, 2001-2002, 2002-2003, and
2003-2004 seasons. These seasons were chosen because a
change in the incentive structure regarding overtime/shootout
victories was put in place in 2000 (affecting all entities equally)
and the labor dispute between team owners and the National
Hockey League Players’ Association (NHLPA) did not occur
until 2005. Thus, this choice of seasons avoids both major
changes to the overtime incentive structure and changes to both
the overall league compensation structure and regulatory
modifications which occurred as a result of the eventual
collective bargaining agreement (CBA) reached between team
owners and the players’ union. Salary information is given in
domestic (US) currency thus any issues involving exchange
rates (e.g. Canadian vs. US dollars) can be ignored. As a point
of fact, all salaries paid to players are mandated by the league
to be remunerated in US currency. General demographic
statistics regarding time-variant traits were also easily obtained.
Furthermore, the main attractive feature of hockey data is the
ability to narrow the frame of reference regarding pay disparity
from an aggregate firm-level to a more realistic intraposition
level; all positions are included in the sample, differentiated by
centers, right-wings, left-wings, defensemen, and goalies.
Certain criteria regarding inclusion into the sample is worthy
of a brief discussion at this point. First, because the sample is
rather small, it is not restricted by the number of games played
in any given season; thus, both “full-time” and “part-time”
players are included in the interest of obtaining more variation
in the independent variables. Second, players who were traded
from their initial team in a given season are not excluded from
the sample in an effort to minimize selection bias. For example,
players who are more prone to leave their team when the
chances of making the post-season are slim (“hired guns”), may
be considered more individualistic by their very nature. Thus,
excluding “job-movers” may result in a sample consisting
solely of players with low marginal costs of team loyalty,
saintly effort, and positional-collaboration. A sample such as
this would in all likelihood be less affected by pay disparity.
ii) Empirical approach.
A panel-data based approach is employed to test the predica-
tion that an increased degree of pay disparity results in lower
intrapositional cooperation. The traditional measure selected to
reflect cooperation is team winning percentage (). This is
the dependent variable of interest in the forthcoming empirical
specification and is representative of 2 in the theoretical
portion of the paper. Note that while team revenue or team
profits may also be an adequate measure of group performance,
these figures are only as reliable as the accounting practices a
particular team employs, the veracity of which has been ques-
tioned in the past. For instance, independent studies of revenues
and expenses conducted internally by NHL owners estimated
league losses at a 10% greater margin than the independent
study conducted by Forbes Magazine (Staudohar, 2005)10.
The main independent variable of interest, pay disparity, is
measured here by an intraposition adaptation of the Herfin-
dahl-Hirschman Index (), which is calculated by:
9In a similar vein, a raiding issue has recently surfaced in the world o
f
professional hockey. The Kontinental Hockey League (KHL), formed in the
spring of 2007 to replace the disbanded Russian Superleague, has been
luring contractually-obligated NHL players overseas (Wawrow, 2008).
Thus, as the market for hockey players becomes more globally competitive,
any degree of monopsonistic bargaining power enjoyed by NHL team
owners is diminishing over time.
10In a more innovative attempt to broaden the spectrum of variables repre-
senting team performance, I also employed assists per game, which should
be a good proxy of how well a team is working together. However, the
employment of this measure produced insignificant results. Note also that
the correlation coefficient between assists per game and win percentage was
also rather small
(
.0534
)
.
Copyright © 2012 SciRes. 451
N. STEFANEC

2
1
share
n
pts
i
1815n
HHI (9)
where n is the number of players l in the sample (
)
and share
p
ts is position p’s share of his respective team t’s
total payroll in season s. Payroll is defined as the sum of the
team’s total salary expenditures allocated to a specific position.
Conventionally, it is the case that
0,HHI
HHI
10000

ε
pts ipts
HHI
w%
α
ε
ε
δ
ˆ
δ0
0
Ho
ˆ
:δ0
Ha
. From the
point of view of the theoretical model, is expected to
proxy . Note that other researchers have also employed
variations of this measure as a proxy for pay disparity (e.g.
Depken 2000, Berri & Jewell, 2004).
The following empirical specification is employed to test the
prediction of Equation (7b). A fixed-effects model which more
directly exploits the panel nature of the data is estimated. As
opposed to a pooled cross-sectional model which assumes
variation is simply across individual players, the fixed-effects
model employed here assumes variation is within-teams and
across individuals, positions, and time (seasons). Employing
win percentage as the dependent metric of teamwork and fol-
lowing Depken (2000), the specification is given by:

ln w%αβδln
iptsiipts
X
  (10)
where ipts is player l at position p on team t’s winning
percentage in season s, individual fixed-effects measuring un-
observed individual heterogeneity is given by i, X is a vector
of consisting of time-variant controls including player l at posi-
tion p’s share of his respective team t’s payroll in season s, and
player l on team t’s collective points per game, age, experience,
weight, height, number of fights, and total penalty minutes at
position p in season s ( this vector also includes squared terms
of players’ physical demographics and violent tendencies as
well as both season and team-specific fixed-effects)11. β’s are
the estimated parameters which are consistent under general
conditions and efficient under normality, δ is the coefficient of
interest, and is a stochastic term which varies across indi-
viduals, positions, teams, and seasons. is assumed to have
the standard properties of being uncorrelated with itself, uncor-
related with the independent variables, has mean zero, and is
homoskedastic.
The estimated coefficient of interest is interpreted here
as the elasticity of team performance with respect to pay dis-
parity (defined as the percentage change in team performance
with respect to each additional unity percentage change in pay
disparity) and it is expected that this elasticity will be negative
such that . Elasticities are employed here for simplifi-
cation of the analysis because they possess the beneficial qual-
ity of being “unitless” (i.e. being independent of units). Thus,
the null hypothesis is being tested against the al-
ternate hypothesis
ˆ
:δ
(two-tailed t-test). Given that
theory clearly predicts a negative relationship, a one-tailed
t-test is also performed where the null hypothesis ˆ
:δ0
Ho
is
tested against the alternate hypothesis .
ˆ
:δ0
Ha
HHI
Some general summary statistics regarding the dependent
and independent variables (as well as payroll information) can
be found in Table 1. First, information regarding pay disparity
across time as well as by position is presented; recall pay dis-
parity is the independent variable of interest. Second, statistics
on win percentage and are given across time and by position,
which is the dependent variable of interest. Third, payroll in-
formation (by position) is also presented. The statistics show
that the variance of pay disparity peaked during the 2000-2001
season. It is interesting to note that the correlation between
earnings disparity and payroll is rather high (.416). In all like-
lihood, this suggests that varies because of the market
size of each team; put differently, some teams are poor and can
only afford a collection of younger, inexperienced, yet more
equally paid players (with maybe an additional higher paid,
experienced yet out-his-prime player) while larger market
teams can afford better players in their prime who can com-
mand higher salaries. It is also a possible that teams may sim-
ply just employ different payment strategies. In addition, sum-
mary statistics regarding the time-variant traits can be found in
Table 2.
Results
When workers’ rewards are based upon a relative compare-
son of performance, many argue that pay compression can be
(relatively) efficient because a tighter wage distribution miti-
gates anticooperative behavior and encourages team collabora-
tion (Milgrom & Roberts 1988; Akerlof & Yellen 1988, 1990;
Lazear 1989; Levine 1991). Others argue that pay compression
can persist yet be unrelated to team performance (Ramaswamy
& Rowthorn, 1991). Neither theory has received definitive
empirical support, leaving the matter open to debate. The em-
pirical portion of this paper attempts to directly address this
puzzle. Here, I estimate a fixed-effects model which more di-
rectly exploits the nature of the panel data to investigate the
effects of an increased degree of pay disparity on team per-
formance12. These results can be found in Table 3 (column 1),
which presents an estimate of equation 10; this model explains
roughly 22% of the variation in the log of winning percentage
(adjusted).
The estimated coefficient on payroll is statistically insignifi-
cant (suggesting that an owner may not be able to simply “buy
a winning team”). Unsurprisingly, marginal increases in the
level of points per game result in higher win percentage. With
respect to age and experience, the results cannot be interpreted
inearly. Interestingly, they suggest that younger teams have l
11A player receives one point for a goal and one point for an assist; this is
employed as a general performance measure. Indicators of violence are
included because prior work has shown that fighting ability helps teams
move through successive rounds of the playoff (Haisken-DeNew & Vorell,
2008). Although fighting and aggrieves offenses carry with it a zero-toler-
ance policy when it comes to enforcement by the NHL, it is interesting that
p
layers (particularly fighters) adhere to an informal etiquette system among
themselves which is largely based upon trust, respect, and reputation. This
includes an invitation and verbal agreement before a fight begins, the
p
romise not to engage another player when he is injured or near the end o
f
his shift, and not wearing equipment or using dangerous objects such as
sticks or helmets to injure opposing players (Bernstein, 2006). Players (such
as Chris Simon) who break these informal rules or who engage in blatant
attempts to injure other players often lose the respect of their peers.
12In addition to “hired guns,” the so-called “agitators” and “goons” also
tend to have high (assumed) time-invariant marginal costs of cooperation.
Although personality is certainly liable to influence team chemistry as
suggested by Ramaswamy and Rowthorn (1991), fixed-effects models
should absorb the behavior of these types of players. Only 2.3% of the
sample is composed of agitators while 4% are enforcers (identification o
f
these players was accomplished via www.wikipedia.org.) As an aside, the
data suggests that these players are paid significantly less on average than
their dovish counterparts (roughly 15% - 30%, all else equal), suggesting a
negative wage profile associated with those considered to have increasing
“damage potential.” This may be expected though, because the performance
of NHL players is monitored quite thoroughly whereas efficiency wages are
usually paid in the absence of monitoring.
Copyright © 2012 SciRes.
452
N. STEFANEC
Copyright © 2012 SciRes. 453
Table 1.
Summary statistics.
Variables (n = 1815) Mean Std. Dev. Minimum Maximum
HHI
2000-2001 (n = 376) 487.19 199.05 1 735.19
2001-2002 (n = 445) 483.46 197.47 2 735.45
2002-2003 (n = 491) 479.20 198.53 3 735.67
2003-2004 (n = 503) 482.32 197.90 4 735.80
Centers (n = 528) 499.29 194.94 8 735.80
Right-wings (n = 261) 475.19 215.84 5 732.50
Left-wings (n = 341) 453.17 197.06 1 729.75
Defensemen (n = 594) 494.66 188.95 29 733.32
Goalies (n = 91) 441.79 209.50 12 735.13
Win Percentage
2000-2001 .453 .111 .256 .634
2001-2002 .437 .085 .231 .585
2002-2003 .437 .097 .268 .634
2003-2004 .436 .093 .244 .707
Centers .434 .097 .231 .634
Right-wings .436 .096 .231 .634
Left-wings .446 .094 .231 .707
Defensemen .441 .097 .231 .641
Goalies .456 .010 .244 .634
Payroll
Centers $5,105,887 $4,541,306 $300,000 $26,000,000
Right-wings $3,980,050 $4,072,505 $300,000 $20,600,000
Left-wings $3,609,063 $3,333,912 $300,000 $17,800,000
Defensemen $4,913,326 $4,051,023 $300,000 $20,100,000
Goalies $2,865,426 $2,614,549 $350,000 $12,000,000
Notes: Following convention, 0,10000HHI
.989p
δ
. Payroll is defined as the sum of the team’s total salary expenditures allocated to a specific position. Data sources:
http://content.usatoday.com/ sports/hockey/nhl/salaries, www.hockeydb.com, www.nhl.com, http://thehockeynews.com/salaries.
lower win percentages, but at an increasing rate and that more
experience teams have higher win percentages, but at a de-
creasing rate. Height and weight do not seem to statistically
contribute to explaining the overall variation in win percentage.
Violence, however, seems to explain some of the variation in
team winning percentage: Fighting increases winning percent-
age at a decreasing rate whereas penalty minutes decrease win-
ning percentage at a constant rate.
I then find statistically and economically significant evidence
to suggest the existence of a negative relationship between
higher degrees of within-position pay disparity and team
performance; the findings reported here suggest the elasticity of
team performance with respect to pay disparity is roughly 19%
(ceteris paribus, each additional percentage increase in pay
disparity for player l at position p on team t in season s results
in roughly a 19% reduction in team win percentage). This result
is statistically significant at the 5% level and sides with the
proponents of pay compression (Milgrom and Roberts 1988,
Akerlof and Yellen 1988, 1990, Lazear 1989, Levine 1991).
This result is economically significant as well. A one-tailed
t-test finds this coefficient to be definitively negative at the 5%
level of statistical significance (). The model also
appears sensitive to extreme values of pay disparity; the result
is not robust when excluding both the upper and lower 10% of
the distribution, suggesting outliers may be driving these results
as clearly seen in Figure 1. Note that the competing theory of
Ramaswamy and Rowthorn (1991) posits the line in this figure
should be horizontal. Table 4 presents a more “tiered”
approach to estimating equation (10); this shows that the model
produces a robust estimate of which ranges from 18% -
22% depending upon the various controls included in the
regression13.
13A Hausman (1978) test favored a random-effects model over a
fixed-effects model. Model (10) does produce a robust result significant at
the 5% level for non-traded players (“job-stayers”) such that δ.229
.
The result is not robust to exclusion of “part-time” players (games played <
40) or models run segregating by position, possibly because these restric-
tions simply lessen the overall variation in the independent variable. Due to
a concern over omitted variable bias, a model was run which included an
interaction term between pay disparity and payroll; while δ
remained
robust, the interaction term was insignificant, suggesting that pay disparity
is of greater concern for teams with lower payrolls. All of these results are
available from the author upon request.
Discussion
Although I find pay inequality to have simple negative causal
relationship with group performance, there exist certain
N. STEFANEC
Table 2.
Summary statistics (individual time-variant traits).
Variables (n = 1815) Mean Std. Dev. Minimum Maximum
Points per game
Centers 1.69 1.02 .080 5.26
Right-wings 1.15 .778 .035 4.20
Left-wings 1.26 .848 .068 4.67
Defensemen 1.12 .763 .057 4.30
Goalies .043 .028 .014 .160
Age (years)
Centers 25.61 3.78 18 36
Right-wings 25.70 3.68 19 37
Left-wings 25.41 3.72 18 37
Defensemen 25.73 3.50 19 41
Goalies 26.82 4.28 19 38
Experience (years)
Centers 6.34 3.79 1 18
Right-wings 5.67 4.01 0 19
Left-wings 5.94 3.96 1 18
Defensemen 5.82 3.72 1 21
Goalies 5.82 4.20 1 17
Weight (pounds)
Centers 196.07 14.33 155 232
Right-wings 198.82 14.41 161 240
Left-wings 201.38 14.69 169 235
Defensemen 205.58 15.83 170 260
Goalies 188.27 14.55 155 221
Height (inches)
Centers 72.64 2.20 67 78
Right-wings 72.62 1.83 69 78
Left-wings 73.04 1.68 69 77
Defensemen 73.66 2.00 69 81
Goalies 72.73 1.86 69 78
Fights
Centers 2.39 3.70 0 21
Right-wings 4.98 6.93 0 31
Left-wings 5.92 7.99 0 33
Defensemen 4.38 5.33 0 30
Goalies .101 .407 0 3
Penalty minutes
Centers 141.34 92.54 4 515
Right-wings 142.68 115.33 0 614
Left-wings 151.15 126.39 0 664
Defensemen 205.18 133.22 2 717
Goalies 11.69 13.92 0 91
Data sources: www.hockeydb.com, www.nhl.com, www.hockeyfights.com. With regards to points per game, a player is awarded a single point for a goal and a single point
for an assist; this is then divided by the number of games played. Fights are defined as one or more of the players involved being penalized five minutes for fighting.
Copyright © 2012 SciRes.
454
N. STEFANEC
Table 3.
Estimated coefficients (fixed-effects models).
Dependent variable: Log of win percentage
Variables (n = 1815) (1) Equation 10
Payroll (in millions) .002 (.004)
Point per game .051*** (.015)
Age –.004*** (.001)
Age squared .00002*** (4.04e–06)
Experience .013*** (.003)
Experience squared –.0002*** (.00005)
Weight –.0004 (.001)
Weight squared 2.60e–07 (3.31e–07)
Height .001 (.002)
Height squared –1.70e–06 (2.59e–06)
Fights .015*** (.003)
Fights squared –.0004*** (.0001)
Penalty minutes –.0004*** (.0001)
Penalty minutes squared 1.02e–06 (1.05e–06)
2000-2001 .036** (.018)
2001-2002 .031 (.016)
2002-2003 .006 (.012)
LogHHI –.191** (.084)
Player and team fixed-effects included in the model? yes
R2 .258
2
R
ˆ
δ0ˆ
:δ0Ha
.217
Overall F-statistic F(47,526) = 25.30, Pr > F = .000
p-value for one-tailed test (, )
:Ho.988
Notes: *(**, ***) significant at .10(.05, .01) level, two-tailed test. Heteroskedastic-consistent standard errors (adjusted for 528 clusters in id) in parenthesis. Clus-
tering by position produced very similar results, most likely because position is (for the most part) nested in id.
complications which may compromise the integrity of this
finding. First, the unavailability of data regarding explicit
pecuniary bonuses linked to individual and group performance
is one problem: Observably, standard pay-for-performance
would be a more parsimonious incentive to act as a team.
Unfortunately, data regarding monetary bonuses explicitly
linked to individual performance (e.g. reaching certain thre-
shold levels of goals or assists, receiving an award, being
elected an All-Star by the fans, etc.) or group performance (e.g.
if a bonus were offered and divided amongst the team for
reaching successive rounds of the playoffs and/or earning a trip
to the Stanley Cup championship) could not be identified for
empirical purposes. The absence of this information may cause
an omitted variable bias problem if these bonuses constitute a
significant portion of a player’s overall gross compensation,
overestimating the effects of pay disparity on teamwork and
providing only upper-bound estimates of this effect. However,
if the proportion of performance bonuses to overall gross
compensation is negligible, then this problem may not severely
overstate the effects pay disparity on teamwork.
Another problematic issue rests on the assumption that win-
ning percentage captures only cooperative behavior. Although
it has been employed in the literature before and has been ac-
cepted as a relatively decent proxy for cooperation (e.g. Depken
2000, Berri & Jewell 2004), more realistically, it measures
overall production, which is influenced by both individual and
cooperative effort. This can clearly produce a biased estimator
of . δ
It may also be the case that the relationship between pay dis-
parity and winning percentage may be non-monotonic. For
instance, small degrees of pay disparity offer little in the way of
incentives for individual effort and teams will perform poorly.
At some point, however, pay disparity may become so large
that cooperative effort deteriorates so quickly that winning
percentage decreases, suggesting that winning percentage is a
concave function of pay disparity. In other words, if this intuit-
tion is correct, then a simple negative relationship between pay
disparity and cooperation may not be expected and Equation
(10) may not be correctly specified. To address this concern,
quadratic forms of
were employed in Equation (10) to test
this theory, but the higher-order estimated coefficients of
were statistically insignificant.
δ
The frame of reference (within-position), while offering a
unique extension to the literature, may also present flaws. The
intuition here is simple: A key assumption is that each player is
assigned a unique position, which is true for goalies and
Copyright © 2012 SciRes. 455
N. STEFANEC
Table 4.
Tiered econometric approach (fixed-effects models).
Variables (n = 1815) Dependent variable: Log of win percentage
(1) (2) (3) (4) (5)
LogHHI –.216*** (.78) –.205*** (.003) –.182** (.079) –.183** (.080) –.191** (.084)
Payroll (in millions) - .003 (.003) .002 (.003) .001 (.004) .001 (.004)
Point per game - - .017** (.007) .039*** (.015) .051*** (.015)
Age - - - –.004*** (.001) –.004*** (.001)
Age Squared - - - –.00002*** (4.04e–06) -.00002*** (4.07e–06)
Experience - - - .013*** (.003) .012*** (.003)
Experience Squared - - - –.0003*** (–.00018) –.0002*** (–.00018)
Weight - - - –.0003 (.0008) –.0003 (.0007)
Weight Squared - - - 2.14e–07 (3.37e–07) 2.60e–07 (3.31e–07)
Height - - - .0005 (.0004) .0007 (.0021)
Height Squared - - - –1.52e–06 (2.64e–06) –1.70e–06
(2.59e–06)
Fights - - - - .015*** (.003)
Fights Squared - - - - –.0004*** (.0001)
Penalty Minutes - - - - –.0004*** (.0001)
Penalty Minutes Squared - - - - 1.02e–06 (1.05e–06)
Player, season, and team
fixed-effects included in the
model?
yes yes yes yes yes
R2 .220 .240 .265 .264 .258
2
R
ˆ
δ0ˆ
:δ0Ha
.189 .190 .193 .202 .217
Overall F-Statistic F(22,526) = 28.433,
Pr > F = .00
F(34,526) = 28.23,
Pr > F = .00
F(35,526) = 28.65,
Pr > F= .00
F(43,526) = 23.05,
Pr > F = 0.00
F(47,526) = 25.30,
Pr > F = 0.00
p-value for one-tailed test
( , )
:Ho.997 .995 .989 .989 .989
Notes: Notes: *(**, ***) significant at .10(.05, .01) level, two-tailed test. Heteroskedastic-consistent standard errors (adjusted for 528 clusters in id) in parenthesis.
Clustering by position produced very similar results, most likely because position is (for the most part) nested in id.
defensemen but not necessarily for forwards. Do hockey clubs,
when choosing their twelve forwards really choose the best four
players at each position and maintain strict segregation, or does
some adjustment occur on these lines? Clearly, some of both
occur. To employ a recent example, Sidney Crosby and Evgeni
Malkin of Pittsburgh and Mike Richards and Jeff Carter of Los
Angeles are all centers but often play on the same line. How-
ever, the data sources simply classify the players by their pri-
mary position thus this margin was unable to be adequately
addressed, but clearly, this observation can compromise both
the theoretical assumptions and the efficiency of the empirical
models. Also, while it is true that line combinations and posi-
tion assignments are much more fluid than they once were, the
data employed here is before recent rule changes which allows
for the best offensive players to be on the ice at the same time
(specifically during a power play) due to different dimensions
of the field of play (i.e. a 2005 rule change contracted the neu-
tral-zone, making the offensive zones larger than they once
were).
Furthermore, the role of a first-line center (scoring) is gener-
ally different than that of a fourth-line center (perhaps veteran
leadership), allowing for more complications to arise. For in-
stance, the frame of reference may logically be a player’s line
combination rather than their position. Again, unfortunately, the
lack of data along these lines simply makes it impossible to
improve upon the intrapositional assumption although it clearly
improves upon prior work and offers a unique empirical exten-
sion to the existing literature. Perhaps future data will become
available such that these concerns can be adequately addressed.
Conclusion
Does an elevated stratum of intrafirm pay equality incentive-
ize harmony within a firm and encourage employees to act in
concert with each other? Accordingly, does a subordinate
echelon of pay equality incentivize uncooperative behavior
amongst employees, particularly when rewards are based upon
a relative comparison of performance? Many theoretical re-
searchers agree with this hypothesis (Milgrom & Roberts, 1988;
Akerlof & Yellen, 1988, 1990; Lazear, 1989; Levine, 1991).
In contrast, others such as Ramaswamy and Rowthorn (1991),
oppose the link between pay equality and cooperation, arguing
that pay disparity can exist when it prevents workers from ex-
ercising damaging behaviors to the group via paying them effi-
ciency wages. Thus, a non-negative relationship between team
performance and pay equality may therefore also exist. Because
empirical evidence in support of either theory is rather mixed,
the debate rages on: Which theory is correct?
Copyright © 2012 SciRes.
456
N. STEFANEC
This paper seeks to adjoin to the debate by employing sports
data, particularly regarding that of professional hockey players.
Hockey data is somewhat unique in that the frame of reference
regarding pay disparity can be narrowed from the aggregate
firm-level down to an intrapositional level. Here, I employ an
unbalanced panel of data from the National Hockey League
(NHL) encompassing observations over four seasons and utilize
a panel-data based empirical approach to examine the impact of
pay disparity on cooperation. I find evidence to suggest the
existence of a negative relationship between higher degrees of
within-position pay disparity and team performance; the evi-
dence reported here shows the elasticity of team performance
with respect to pay disparity to be roughly 19%.
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