1

CHAPTER II

LITERATURE REVIEW

The purpose of this chapter is to review the literature on attendance at

professional sporting events. In addition, rational addiction models and theories will

be surveyed. There is an abundant literature on both of these topics, and each will be

discussed based on its relevance to the present research on rational addiction among

fans of the National Football League (NFL). First, the chapter will begin by

discussing literature on attendance at all types of sporting events. Studies of

attendance for both collegiate and professional American football1 will be examined

at the end of the attendance section. Second, this chapter will explore the body of

literature on rational addiction, examining current research in the area and discussing

how it may be applied to habit-forming goods such as alcohol and cigarettes. The

majority of empirical studies that test rational addiction have studied either cigarettes,

alcohol, or illicit drugs. The final section of this chapter will discuss an unpublished

working paper that applies a rational addiction model to explore attendance and ticket

pricing at professional baseball games. FIGURE 2.1 is a visual representation of the

available literature pertaining to rational addiction and NFL attendance.

1 American football as opposed to soccer, known as football elsewhere. In this paper references to football can be assumed to be American football unless otherwise noted.

2

FIGURE 2.1

Attendance and Rational Addiction Literature

A

Collegiate

Football

Fan Motivation

Rational Addiction Models

There have been a numbe

that influence the consumption of

attendance at sporting events. Ec

analyze the factors that determine

applied to various sports.

Attendance in Major Leag

Kahane and Schmanske test the p

MLB attendance. They hypothes

Sports ttendance

Other Sports

NFL

ContinuousModels

Attendance

r of studies in the economics liter

sports, which is generally repres

onomic demand models have bee

spectator attendance, and this me

ue Baseball (MLB) has been stud

roposition that roster turnover has

ize that fans prefer some consiste

Discrete Models

ature on factors

ented by spectator

n widely used to

thod has been

ied frequently.

an impact on

ncy in the

3

composition of the team and that when turnover is high, fans will lose interest in the

team. Using data from the 1990 through 1992 MLB seasons, they control for factors

such as price, income, population, team quality, league, year, and stadium effects.

They use an ordinary least squares estimator and find that turnover does indeed have

a significant and negative impact on attendance in MLB.2

In another study on Major League Baseball attendance, McDonald and

Rascher explore the effects that special promotions have on game day attendance.

They study the overall effect that a promotion has on attendance and also the

marginal impact of increasing the number of promotion days on attendance. They use

data from the 1996 season for 19 teams. Using ordinary least squares regression, they

find that promotions increase game-day attendance by about 14%. There is evidence

of diminishing marginal returns with promotions, since increasing the number of

promotions has a negative impact on the marginal effect of the promotion. However,

the gain of having an extra promotion day is greater than the effect of diminishing

returns.3

There have also been some studies on attendance at basketball games.

Burdekin and Idson examine the effect that customer discrimination has on

attendance for the National Basketball Association (NBA). They use data from the

1980-81 through 1985-86 NBA seasons to test their hypothesis that fans prefer to see

players of their own race. They find that attendance is significantly affected by the

2 Leo Kahane and Stephen Schmanske, “Team roster turnover and attendance in major league

baseball,” Applied Economics, Volume 29, 1997: 425-431. 3 Mark McDonald and Daniel Rascher, “Does Bat Day Make Cents? The Effect of

Promotions on the Demand for Major League Baseball,” Journal Of Sport Management, Volume 14, 2000: 8-27.

4

racial composition of the team relative to the racial composition of the market area.

Teams whose racial composition more closely matches that of the location in which

they play have games that are attended more than teams made up of players that do

not represent the racial composition of the local area.4

Zhang, Pease, Hui, and Michaud explore the variables that determine whether

or not spectators will attend NBA games by developing the Spectator Decision

Making Inventory. The inventory includes 20 variables that are believed to have an

impact on the decision to attend an NBA game. They survey a random sample of 861

NBA spectators and employ factor and regression analyses to test the validity of the

survey results. The factors that they find to be significantly related to game

attendance are game promotion, home team, opposing team, and schedule

convenience.5

Soccer is another sport that has been relatively well studied. Peel and Thomas

investigate the determinants of attendance for professional soccer in England,

hypothesizing that games that are not predicable attract bigger crowds. They attempt

to isolate the effect of the uncertainty of outcome by using betting odds as a means of

measuring the uncertainty and employing ordinary least squares regression. Using

data from the 1981-82 season of the English Football League, they find that

economic, geographic, and demographic variables play a part in determining

attendance at soccer matches. Also, variables related to the quality of the teams and

4 Richard Burdekin and Todd Idson, “Customer preferences, attendance, and the racial

structure of professional basketball teams,” Applied Economics, Volume 23, 1991: 179-186. 5 Zhang, Pease, Hui, and Michaud, “Variables affecting spectator decisions to attend NBA

games,” Sport Marketing Quarterly, Volume 4, Number 4, 1995: 29-39

5

other exogenous variables, such as weather, are found to influence the demand for

attendance.6

Dobson and Goddard provide further research on the demand for soccer.

They use data from the 1925 to 1992 seasons of the English Football League to test

their hypotheses that ticket prices, age of team, fan loyalty, and demographics all play

important roles in the demand for professional soccer. They employ two-stage

regression analysis, where attendance and loyalty are endogenous variables. They

find that team success, price, and loyalty are significant factors that determine

attendance in the English Football League.7

Baimbridge examines soccer match attendance at the European Championship

that was held in England in 1996. He uses data from the tournament and explores the

effects that economic, demographic, and match-specific variables have on attendance

at such an event. He uses ordinary least squares regression and finds that the distance

between the team’s home city and the tournament site and the quality of the teams are

the most important factors that affect tournament attendance.8

There has also been considerable research done on hockey attendance.

Studies have examined attendance at the major and minor league levels. Hansen and

Gauthier explore the National Hockey League (NHL) and compare and contrast

factors that affect attendance in the NHL with the other major professional sports

6 Peel and Thomas, “Outcome uncertainty and the demand for football: An analysis of match

attendances in the English Football League,” Scottish Journal of Political Economy,Volume 35, Number 3, 1988: 242-249.

7 Dobson and Goddard, “The demand for professional league football in England and Wales,

1925-1992,” The Statistician, Volume 44, Number 2, 1995: 259-277. 8 Mark Baimbridge, “Match attendance at Euro 96: Was the crowd waving or drowning?”

Applied Economics Letters,Volume 4, 1997: 555-558.

6

(NBA, MLB, NFL, Canadian Football League, Major Indoor Soccer League),

hypothesizing that there would not be any significant differences in factors affecting

attendance at these sporting events. They develop a questionnaire using a Likert 5-

point scale regarding attendance based on 40 factors believed to impact attendance

and apply it to a sample of 117 teams from the various sports leagues. Using factor

analysis and Varimax rotation, they examine the questionnaires. They use ANOVA

and Tukey tests to determine significant differences, finding that there are indeed

significant differences amongst leagues in the factors that determine attendance. The

results of the analysis indicate that scheduling, team roster quality, price, forms of

entertainment competition, and convenience for fans are the significant factors that

affect attendance for the NHL. Similar factors are found to affect attendance at NFL

games, but to varying extents.9

Zhang, Pease, and Smith examine the determinants of minor league hockey

attendance. They focus on the role that the broadcast media plays in determining

attendance. Using a survey of a random sample of 2,225 minor league hockey game

spectators, the authors use regression analysis to determine the factors that affect

attendance. They conduct the survey during 6 games of an International Hockey

League team during the 1994-95 season. The analysis suggests that broadcasting

plays a large part in increasing attendance, with television and radio broadcasting of

away games being significant factors in determining the attendance at home games.

9 Hansen and Gauthier, “Factors affecting attendance at professional sporting events,” Journal

of Sport Management, Volume 15, Number 1, 1989: 15-32.

7

The authors conclude that a good broadcasting relationship creates and increases

spectator interest.10

As for football, there have been studies done in recent years on the demand

for attendance at collegiate as well as professional football games. In their study of

NCAA Division II football, DeSchriver and Jensen examine the relationship between

attendance at college football games and various economic and game variables. Data

is collected for three college football seasons (1994, 1996, and 1999) for all NCAA

Division II teams. They use ordinary least squares and fixed-effect regression models

to estimate demand equations for Division II college football. Results of the analysis

suggest that both the past season and current season winning percentages have an

affect on attendance, with the past season’s performance becoming relatively less

important than the current season’s performance as the season progresses.

Promotional activities, size of the college, and competition within the market were

also found to be significant factors in determining attendance at college football

games.11

Welki and Zlatoper examine NFL attendance and the factors that affect it.

They use data from the 1991 NFL season and employ Tobit analysis. The

explanatory variables include economic and demographic factors as well as game-

specific variables. The regression analysis indicates that the home team’s winning

percentage is an important factor in determining attendance. They also suggest that

10 James Zhang, Dale Pease, and Dennis Smith, “Relationship Between Broadcasting Media

and Minor League Hockey Game Attendance,” Journal of Sport Management, Volume 12, 1998: 103-122.

11 Timothy DeSchriver and Paul Jensen, “Determinants of Spectator Attendance at NCAA

Division II Football Contests,” Journal of Sport Management, Volume 16, 2002: 311-330.

8

higher ticket prices depress attendance and that the demand for professional football

appears to be inelastic.12

There are also some studies that attempt to explain fan motivation in their

football attendance studies. For example, Kahle, Kambara, and Rose study college

football to determine what it is that draws fans to the games. The study uses

functional theory of attitudinal motivation to construct and test a model of fan

attendance at college football games, based on survey data from 112 students at a

large public university in the Pacific Northwest region of the United States. They

find that that collegiate football fans were motivated by overall attachment to and

love for the team, to achieve some degree of freedom from the stress and anxieties of

daily life, and by camaraderie, or a desire for group affiliation.13

These studies provide a solid foundation for research on NFL attendance, but

there is at least one factor that seems to be missing from each of these attempts to

explain the demand for various sporting events. None of the studies attempt to

account for habit-formation in their models. This could prove to be an important

omission.

There are some studies in the psychology literature that address addiction to

sports, but they mostly discuss the athletes’ dependency on participation in sports and

exercise14 rather than addressing the issue of fans’ possible habits in the consumption

12 Andrew Welki and Thomas Zlatoper, “US Professional Football: The Demand for Game-

Day Attendance in 1991,” Managerial and Decision Economics, Volume 15, 1994: 489-495. 13 L.R. Kahle, K.M. Kambara, and G.M. Rose, “A functional model of fan attendance

motivations for college football,” Sport Marketing Quarterly, Volume 5, number 4, 1996: 51-60. 14 D. Bamber, I.M. Cockerill, S. Rodgers, and D. Carroll, “It's exercise or nothing: a

qualitative analysis of exercise dependence,” British Journal of Sports Medicine, Volume 34, Number 6, 2000: 423-430.

9

of sporting events. However, some authors have acknowledged that sports fans may

follow sports at least partly because it becomes a habit. Gerdy describes sports as the

“all-American addiction,” but supplies only anecdotal evidence to support this

claim.15 Another body of literature on rational addiction explores how habits can be a

factor in determining consumption and how this can be tested empirically. The

following section will briefly explore the current studies on rational addiction.

Rational Addiction

Economic theory regarding the role that habits play in the demand for goods is

a relatively new subject. Alfred Marshall initially mentioned the idea in his 1920

textbook. Marshall notes:

“…whether a commodity conforms to the law of diminishing or increasing return, the increase in consumption resulting from a fall in price is gradual; and, further, habits which have once grown up around the use of a commodity while its price is low are not quickly abandoned when its price rises again.”16

This was the beginning of the economic study of the effects that tastes and

preferences have on demand. However, many economists, including Milton

Friedman, have been skeptical at best when it comes to accounting for tastes.

Friedman expresses this sentiment in his 1962 book Price Theory.

“…The economist has little to say about the formation of wants; this is the province of the psychologist.”17

15 John R. Gerdy, Sports: The All-American Addiction, Jackson, Mississippi: University Press

of Mississippi, 2002. 16Alfred Marshall, Principles of Economics, Eighth Edition, London: The Macmillan

Company, 1920: 807. 17 Milton Friedman, Price Theory: A Provisional Text, Chicago: The University of Chicago

Press, 1962: 13.

10

Nonetheless, attitudes have begun to change in recent decades, and the literature

regarding economic research on addiction has expanded tremendously.

Literature on addiction is both abundant and diverse. There are two main

subcategories of addiction research that break the literature into the myopic and

rational branches. The main difference between the two is that the myopic models

only consider the effect of past consumption on present consumption, while ignoring

the expected future consumption. The rational school considers both past and future

consumption when estimating present consumption. Traditionally, the two are

classified separately, although the myopic studies can really be thought of as a special

case of the rational model when the effect of expected future consumption is zero.

This study will focus on the subset of addiction research that deals with models of

rational addiction, since that is the model that will be used in this paper. For a review

of addiction literature that includes myopic models see Fenn18 and Chaloupka. 19

Rational addiction, according to Becker and Murphy, implies that people

make choices according to their consistent utility maximization plan.20 Rational

addiction models, as applied to cigarette demand, examine the notion that past

consumption, price, and estimated future consumption have an effect on present

18 Aju Fenn, “The impact of addiction information on cigarette consumption,” Ph.D.

Dissertation, Iowa State University, 1998.

19 Frank Chaloupka, “An economic analysis of addictive behavior: The case of cigarette smoking,” Ph.D. Dissertation, City University of New York, 1988.

20 Gary S. Becker and Kevin M. Murphy, “A Theory of Rational Addiction,” Journal Of

Political Economy, Volume 6, Number 4, 1988: 675-700.

11

consumption. There have been a few studies done regarding alcohol21 and some

illicit drugs such as cocaine.22

In the body of literature on rational addiction, two main classifications can be

made. There are rational addiction models that are discrete and those that are

continuous.23 The difference between the two lies in the fact that research using a

continuous model uses dependent variables that can assume continuous values while

discrete models refer to dependent variables that have specific zero-one values.

Discrete models have mainly been used to explore starting and quitting rates for

smokers24 while continuous models have attempted to model present consumption of

an addictive good as a function of past, present and future prices, income, and

addictive stock of the good.25 In either case, the key to the models is that present

consumption depends on price, past consumption, and expected future consumption.

Stigler and Becker lays the foundation for rational addiction analysis.26 This

early research on rational addiction is theoretical in nature and gives no empirical

evidence. It sets up the theory upon which later papers with rational addiction models

are built. It is in these papers that the idea of habit formation based on utility

21 Teresa Waters and Frank Sloan, “Why do people drink? Tests of the rational addiction

model,” Applied Economics, Volume 27, 1995: 727-736. 22 Michael Grossman and Frank Chaloupka, “The demand for cocaine by young adults: A

rational addiction approach,” Journal of Health Economics, Volume 17, Issue 4, 1998: 427-475. 23 A. Myrick Freeman, The Measurement of Environmental and Resource Values: Theory and

Methods, Washington, D.C.: Resources for the Future, 1993. 24 Theodore Keeler and Martin Marciniak, “Rational addiction and smoking cessation: An

empirical study,” Journal of Socio-Economics, Volume 28, Issue 5, 1999: 633-644. 25 Frank Chaloupka, “Rational Addictive Behavior and Cigarette Smoking,” Journal of

Political Economy, Volume 99, Number 4, 1991: 722-742. 26 George Stigler and Gary Becker, “De Gustibus Non Est Disputandum,” The American

Economic Review, Volume 67, Number 2, 1977: 76-90.

12

maximization is first introduced. Stigler and Becker set up their argument based on

an idea of household production. They make a claim that rather than consuming

goods, people consume commodities that they themselves produce by using market

goods and their own human capital.27 The commodity itself does not even have to be

a tangible good. Stigler and Becker use an example of music appreciation, first

employed by Marshall,28 in their paper. When discussing the idea of diminishing

marginal utility, Marshall states:

“…it is therefore no exception to the law that the more good music a man hears, the stronger is his taste for it likely to become.”29

The total bundle of commodities that a household consumes is broken down

into music appreciation and a vector of all other commodities. The consumer

“produces” music appreciation by allocating time to music and human capital

contributing to music appreciation. The human capital contributing to music

appreciation can be further broken down into inputs of educational attainment and the

amount of accumulated music appreciation carried over from the previous period.30

Using this approach, Stigler and Becker are able to show that present consumption

does indeed depend upon past and expected future consumption for addictive goods.

Spinnewyn extends this theoretical model and further considers the interaction

27 Ibid. 28 Alfred Marshall, Principles of Economics, Eighth Edition, London: The Macmillan

Company, 1920: 94. 29 Ibid: 94. 30 George Stigler and Gary Becker, “De Gustibus Non Est Disputandum,” The American

Economic Review, Volume 67, Number 2, 1977: 80.

13

between past and current consumption among utility maximizing consumers.31

Iannaccone adapts the Stigler and Becker model of demand for habit-forming goods

and applies it to his own model of religious participation that depends on a “stock of

religious experience.” 32

The most widely cited work on rational addiction is that of Becker and

Murphy. In this purely theoretical and fairly complicated work, Becker and Murphy

set up the model of rational utility maximization with stable preferences. They lay

out the framework that is widely accepted for rational addiction, which claims that the

utility function that consumers are maximizing depends on the addictive good, all

other non-addictive goods, and the “addictive stock” of the addictive good. The

model explores things such as elasticity of demand for addicts versus non-addicts,

phenomena such as binges and cold turkey, and the relationship that temporarily

stressful events have on permanent addictions.33 One of the major contributions of

this article is the way in which it defeats the common misconception that cigarette

demand is insensitive to price due to the habit-forming properties of cigarettes. The

Becker-Murphy model shows that price does indeed play an important role in the

quantity consumed of an addictive good. Moreover, a drop in price for an addictive

good may have larger effects on long run demand than it would for a non-addictive

31 Frans Spinnewyn, “Rational Habit Formation,” European Economic Review, Volume 15,

1981: 91-109. 32 Lawrence Iannaccone, “Consumption Capital and Habit Formation with an Application to

Religious Participation,” Ph.D. Dissertation, University of Chicago, 1984: 2. 33 Gary S. Becker and Kevin M. Murphy, “A Theory of Rational Addiction,” Journal Of

Political Economy, Volume 6, Number 4, 1988: 675-700.

14

good, since the drop in price affects not only the current period’s consumption but

also the future period’s consumption through the addictive stock of the good.34

This theory of rational addiction has now been tested in numerous empirical

studies. Chaloupka provides a simplified and empirically tested version of the

Becker-Murphy model. He uses cigarette consumption data from 1976 through 1980,

which was obtained from the Second National Health and Nutrition Examination

Survey on 28,000 people from 6 months to 74 years of age. Data was also collected

by county of residence for prices, taxes, and demographic variables such as age,

gender, income, education, race, and, marital status. He separated the groups

according to age and education and estimated demand equations separately for each

group in order to isolate the effect of time preference on demand. In accordance with

rational addiction theory, he finds evidence that, prices and past and future

consumption do indeed affect current consumption in his models of cigarette

demand.35

Grossman provides the first published effort that applies the rational addiction

model to alcohol consumption. He collected data on per capita consumption of

alcohol from National Health and Nutrition Examination Surveys, which also

included demographic information. However, the results of his empirical analysis

provide little evidence to support the notion of rational addiction for alcohol

consumption.36 Waters and Sloan also apply the rational addiction model to alcohol

34 Ibid: 687. 35 Frank Chaloupka, “Rational Addictive Behavior and Cigarette Smoking,” Journal of

Political Economy, Volume 99, Number 4, 1991: 722-742. 36 Michael Grossman, “The economic analysis of addictive behavior,” The Economics and

Prevention of Alcohol Related Problems, Maryland: The Department of Health and Human Services, 1993.

15

consumption and did indeed find evidence of rational addiction in their study. They

use data from the 1983 US Health Interview Survey and found that past and future

consumption have strong positive relationships with current consumption. They also

found price to be negative and significant in their empirical rational addiction

model.37

Becker, Grossman, and Murphy find that past and future prices do indeed

influence the present consumption of cigarettes, which concurs with the model in

previous theoretical work on rational addiction.38 They use annual U.S. data that is

broken down by state for the 1955 through 1985 period. They estimate an equation

for cigarette demand and employ two-stage least squares regression to estimate a

simultaneous model of current, past, and future consumption. Their findings suggest

that estimated past and future consumption do indeed have significant, positive

relationships with current consumption while the current cigarette prices impact

current consumption negatively.39 This empirical evidence provides direct support

for the earlier theoretical work by Becker and Murphy.40

In a more recent study, Fenn, Antonovitz, and Schroeter test the hypothesis

that the 1979 U.S. Surgeon General’s report had a significant impact on cigarette

37 Teresa Waters and Frank Sloan, “Why do people drink? Tests of the rational addiction

model,” Applied Economics, Volume 27, 1995: 727-736. 38 Gary Becker, Michael Grossman, and Kevin Murphy, “An Empirical Analysis of Cigarette

Addiction,” The American Economic Review, Volume 84, Number 3, 1994: 396-418. 39 Ibid. 40 Gary S. Becker and Kevin M. Murphy, “A Theory of Rational Addiction,” Journal Of

Political Economy, Volume 6, Number 4, 1988: 675-700.

16

demand.41 The 1979 report provided conclusive evidence about the addictive nature

of nicotine in cigarettes. They hypothesized that demand may have been myopic

before the warning and rational afterward. They used annual data for the U.S., again

broken down by state, from 1955 to 1994. To account for the new information that

was published about the cigarettes in 1979, they add a dummy variable to their

regression equation that takes on a value of one for every year after 1979. Following

earlier studies on rational addiction, the model is tested using fixed effects two-stage

least squares. The results suggest that characteristics of rational addiction were

evident even before the Surgeon General’s published warning in 1979, further

supporting the notion that that rational model is indeed superior to its myopic

counterpart. However, they also found that there was indeed a structural shift in

1979, which supports their original hypothesis.42

Rational Addiction and Attendance

Ahn and Lee attempt to apply elements of the rational addiction model to

sports consumption in their examination of baseball attendance.43 They use the

possibility of habit-formation as an explanation for the fact that Major League

Baseball teams appear to price their tickets below the profit-maximizing price. The

41 Aju Fenn, Frances Antonovitz, and John Schroeter, “Cigarettes and addiction information:

new evidence in support of the rational addiction model,” Economics Letters, 2001: 39-45. 42 Ibid. 43 Seung Ahn and Young Lee, “Life-Cycle Demand for Major League Baseball,” Working

Paper, 2003.

17

authors posit that this may be due to the fact that the franchises recognize that the

consumption of baseball games may indeed be habit-forming. Thus, they price their

tickets slightly lower than they normally would in order to attract a larger fan base,

knowing that increasing their fan base in any given time period will increase their

attendance and gate receipts in subsequent seasons. This study focuses on a life-cycle

profit maximization model for teams and examines their pricing strategies. Using

pooled data from the 1969 through 2000 MLB seasons and the Generalized Method

of Moments as well as Ordinary Least Squares to estimate the demand equation, Ahn

and Lee test for habit formation in consumption of professional baseball games. The

results of the regression analysis indicate that baseball consumption is indeed

habitual, but not necessarily rational.44

Byers, Peel, and Thomas analyze the possibility of rational habit-formation

among professional soccer fans in England.45 Using data from the English Football

League and an Autoregressive Fully Integrated Moving-Average (ARFIMA)

regression technique, the study examines whether or not habit-formation plays a role

in the demand for attendance at soccer games. The results indicate support for the

rational habit-formation model, suggesting that habit may be an important factor that

influences spectators at professional sporting events. These two working papers

provide preliminary evidence for habit-formation. Further research into rational

addiction and consumption of professional sports games is warranted.

44 Ibid. 45 Byers, Peel, and Thomas, “Habit and Long Memory in Attendance Demand: The Case of

Football Support,” Working Paper, 2000.

18

Conclusion

The present study will fuse elements from the body of literature on attendance

at sporting events with the current research on rational addiction. The previous

research on attendance for sports has not addressed the possibility of rational

addictive behavior, with the exception of the working paper on MLB attendance by

Anh and Lee.46 There has yet to be a paper published that examines the possibility of

rational addiction in the demand for sports attendance, and this will be the first to

apply the model to the National Football League. Following the earlier work done on

attendance, this study will examine the traditional variables used in predicting

spectatorship at sporting events to see how they impact NFL attendance. Estimated

past and future consumption are added to the model, according to rational addiction

theory. The result will be a model that accounts for habit formation in the demand for

attendance at NFL games.

46 Seung Ahn and Young Lee, “Life-Cycle Demand for Major League Baseball,” Working

Paper, 2003.

19

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