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Bachelor Thesis in Economics
The development of player transfer fees in the
English Premier League
Author:
Patrik Pettersson
Mälardalen University
Västerås
721 23, SWEDEN
Division of Business and Social Sciences
________________________________________________________
Bachelor Thesis in Economics
Date:
June 2017
Thesis name:
The development of player transfer fees in the English Premier League
Author:
Patrik Pettersson
Student id:
ppn14001
Supervisor:
Johan Lindén
Address:
Mälardalen University
Västerås
721 23, SWEDEN
Abstract
Directly changing the circumstances in English Premier League by introducing a new
broadcasting rights deal which generates more revenue to all soccer clubs contending in the
competition should affect the consumption and investment behavior, by increasing the total
turnover with £0.7 billion for a competition only a couple of year earlier reported to have a
turnover at £3.4 billion. With homogeneous information about new financial status leads to
expectations of a reaction from the whole industry. This paper will focus on the price
development in transfer fees and prove a relationship with increasing the revenue from
broadcasting rights deals.
The thesis will be based on microdata about transfer fees from English Premier League during
the five latest seasons, a period between 2012/2013 to 2016/2017, collected from the English
version of the website Transfermarkt.
The conclusion consists of two diverse types of investigation, a regression estimation with
significant values on the variables this thesis clamming to have an impact on the transfer fees.
Together with a figure illustrating how the average transfer fee has almost doubled during this
period, with at least on distinct increase related to the time of increased revenues.
Table of Contents
1. Introduction ......................................................................................................................................... 1
1.1 Background ................................................................................................................................... 1
1.2 Aim ................................................................................................................................................ 2
1.3 Limitations..................................................................................................................................... 2
1.4 Literature ....................................................................................................................................... 4
1.5 Structure ........................................................................................................................................ 6
2. Soccer industry .................................................................................................................................... 7
2.1 Sports ideology .............................................................................................................................. 7
2.2 English Premier League ................................................................................................................ 8
2.3 Regulation ..................................................................................................................................... 9
2.4 Transfer system ........................................................................................................................... 10
2.5 Player pricing .............................................................................................................................. 10
2.6 Revenue ....................................................................................................................................... 11
2.7 Broadcasting ................................................................................................................................ 12
2.8 Production ................................................................................................................................... 13
3. Economics theory .............................................................................................................................. 15
3.1 Budget constraints ....................................................................................................................... 15
3.2 Consumption over two periods .................................................................................................... 16
3.3 Money and Inflation .................................................................................................................... 17
3.4 Market equilibriums .................................................................................................................... 18
4. Methodology ..................................................................................................................................... 19
4.1 Data ............................................................................................................................................. 19
4.2 Price development ....................................................................................................................... 19
4.3 Regression ................................................................................................................................... 21
4.3.1 Process .................................................................................................................................. 21
4.3.2 Variables ............................................................................................................................... 21
4.3.3 Estimation ............................................................................................................................. 23
5. Results ............................................................................................................................................... 25
5.1 Price development ....................................................................................................................... 25
5.2 Regression 1: Optimal ................................................................................................................. 28
6. Conclusions ....................................................................................................................................... 30
References ............................................................................................................................................. 31
Appendix ............................................................................................................................................... 34
TABELS
Table 1: Consumption development………………………………………………………….20
Table 2: Regression variables………………………………………………………………...22
Table 3: Compilation of transfers…………………………………………………………….26
FIGURES
Figure 1: Broadcasting revenue development………………………………………………….1
Figure 2: Budget constrains…………………………………………………………………..15
Figure 3: Transfer fee development…………………………………………………………..25
Figure 4: Box plot…………………………………………………………………………….27
Figure 5: Regression estimation………………………………………………………………28
ABBREVIATIONS
1. EPL – English Premier League
2. UEFA – Union of European Football Associations
3. FIFA – Fédération Internationale de Football Association
4. FA – (English) Football Association
1
1. Introduction
1.1 Background In August each year, is the first kick-off for a new season of soccer in the English top division
Premier League with 20 clubs from England and Wales competing over the title as English
champions. A sport that has existed in competitive structure in over 100 years only in England,
often referred as the home of soccer. Nowadays the league has the biggest brand according to
the general public, together with the most money in circulation.
The entertainment from soccer has evolved to a way of life and an industry, with roots all over
the world. The base of soccer is the players on the pitch, but together with supporters, club staff,
media and sponsors made soccer and sports in general to a phenomenon with in the community.
Not following the same principals of behavior in society and exists in all of its’ sectors,
sometimes hard to explain with words.
Today professional players are contracted to clubs, allowing them to only represent one club at
the time. They could be described as employees producing entertainment for everyone with an
interest to watch. Compared to a normal employment, soccer players do not have the possibility
to change workplace by themselves, with three diverse ways to change employer in the shape
of expired contract, loan or a transfer. Expired contract refers to a position where the player
could be descried as unemployed, no binding document between the player and any club. A
loan is when a club borrows a player from another club, either with or without compensation.
While a transfer is when one club compensates another in form of a payment for them to acquire
one player on permanent bases, such payment is called a transfer fee.
The Guardian (2016) reported that the competing clubs in the Premier League during the season
2014/2015 had a total turnover at £3.4 billion, where revenues mainly coming from: match day
income, merchandise, commercial, player trading and TV/broadcasting rights.
BBC (2015) reported that till the season 2016/2017 a new renegotiated deal regarding the
broadcasting replaced the expired one. The new deal covers the next three upcoming seasons
of the competition and generates a total of £5.136 billion split evenly between the 20 clubs over
the seasons. The previous deal generated £3.018 billion, which gives an increase of £2.118
billion or a seasonal increase of £0.7 billion which is equivalent to 20% of the turnover from
2014/2015.
2
Figure 1: Broadcasting revenue development (Source: BBC)
With homogeneous information about an increased revenue coming from improved
broadcasting deal in an industry where all actors are both buyers and sellers expects a reaction,
change in consumption habits and clubs’ valuation of the labor force should be reconsidered.
1.2 Aim
This paper will examine the relationship between increased transfer fees within the English
Premier League with the renegotiated broadcasting rights during the last five seasons, as well
prove a significant change in the transfer fee.
1.3 Limitations
With a limited time schedule, sacrifices have to be made. The problem has to be decomposed
to a thesis affecting only a fraction of possible research field. The soccer clubs’ income increase
could influence many sectors of their business in consumption and investments, it could be
everything from upgrade the facilities to increase the number of youth teams. This paper will
only focus on the price development in players transfers fees, study how the extra income from
the broadcasting rights has increased the value of the heterogenous labor force. This also
implies that the only type of employer change will be the permeant based that consists of a
payment between two parties, omitting the changes with income increase for loans and free
transfers.
Soccer agent Alex Cowdy (Sanghera, 2007) states in an interview with BBC that two diverse
types of transfers can occur. Dependent on if the buying or selling club takes the initiative, if a
player is looking for club or if a club is looking for player. The two different circumstances
3
regarding the transfers will be overlooked due to the interesting information in the transfer is
the transfer fee negotiated between the clubs.
The new broadcasting deal directly increases revenue for clubs participating in the English
Premier League, indirectly other leagues outside of England and divisions under the EPL within
England since the money will be spent implies other actors will benefit on the increased deal.
Other competitions broadcasting rights will be renegotiated with various gaps creating a
comparable situation with income increases and effects of those. This paper will only focus on
actors within EPL as these clubs are directly benefiting of the broadcasting deal and limiting
the number of actors to 20.
The study will be limited to the latest five seasons of EPL (starts in August and ends in May
each year), the interval will be between seasons 2012/2013 and 2016/2017. During this period,
there has been three different broadcasting deals which all generating different amounts of
broadcasting revenue to the clubs. The time spam should be enough to illustrate if there are any
connection between the drastic increased income and transfer fees, and it is reasonable about of
data compared to this thesis time schedule.
Players that had not turn eighteen before the transfer will be excluded from the data based on
ethnical aspect of buying and selling underaged persons with purpose of labor, although FIFA
and UEFA has established regulations and criteria to fulfill for these types of transfers. One
other major factor is that the EPL is a senior level completion, but without age regulations.
Implying that most transfers of underage players will be treated as investments and not effecting
the outcome, but those who effects the outcome is just a fraction of the transfers.
Data and other information that lying as base for the empirical part of the paper will not be
double checked to save time, since it exceeds 500 separate transfers as well the original source
is reliable. Some information could be wrong but it will only be a fraction and should have a
low impact on results and findings.
4
1.4 Literature
The field of sports economics is relatively new, since the second part of the 20th century has the
attention and research increased in context with increasing financial state of the sector. The
material today could not be described as limited but all aspects of economics is not explored
and the sector lacks established theories. The published material contains recurring researchers
which often has focused on one research area or sport. Stefan Szymanski is involved in large
parts of literature with focus on soccer and sports in general, both as a researcher and author,
even in this paper.
Wladimir Andreff and Stefan Szymanski published “Handbook on the Economics of Sport” in
2009, which is a collection of individual research papers within sports by the editors of the book
together with 63 other researchers. The book contains material covering extreme sports,
audience, the Olympics and everything in-between. This paper will use material directly linked
to soccer, broadcasting and general sport economics, to find theories and studies connected to
the thesis.
Simon Kuper and co-author Stefan Szymanski published “Soccernomics”, a book containing
own research together with stories about development and behavior within soccer. The
literature includes both interesting and useful material connected to the thesis with information
about clubs reasoning and financials within the sport.
Stefan Szymanski continued on the same track and published “Money and Soccer”, focusing
on a deeper level of soccer financials, psychology and decision making. Containing two chapter
about revenues and debts, material used in the paper since the revenue has a big impact on the
thesis.
“Perspektiv på Sport Management” is a collection of a numerus amount of Swedish authors
work including Ingela Broberg, P-G Fahlström and Tomas Peterson published by a Swedish
educational association (SISU), containing information about sports management in general.
With a focus on Tomas Peterson part, about behavior and ideologies within sports.
The two articles “What determines the transfer fee of a soccer player? (Evidence from the Dutch
Eredivisie)” by Leon Haverkamp and “Valuation of Football Players” by Anders Munkhaugen
Gulbrandsen, Christian Munkhaugen Gulbrandsen contains findings regarding what establish
the valuation of players, and has a direct connection to the papers’ aim. Both researches will be
a part of section “3. Soccer industry”.
5
KEA European affairs and CDES (the Centre for the Law and Economics of Sports) published
2013 a report of “The Economic and Legal Aspects of Transfers of Players”, which contains
for instance the circumstances of the labor market, rights and sports logic of a transfer.
Material published from UEFA and FIFA, the European soccer association and the world soccer
association, will be a part of this paper. The two actors determine what is allowed both on the
pitch and in the office together with ensuring all actors within soccer follows the law and the
regulation.
Articles published within the British news sector could complement the information gathered
from previous mentioned sources, publishers as BBC, Sky and The Guardian. Those is used to
spread homogenous information to the larger audience.
Hal R. Varian book “Intermediate Microeconomic” contains theory about firms and consumers’
behavior as well maximizing both utility and profits. With a focus on the effect of an income
increase, price changes and market equilibrium.
George J. Borjas book “Labor economics” contains all kind of information about the labor
market. This paper will be using sections of the literature about human capital, demand and
supply.
Since this study examine how all individual actors within the market, the English Premier
League, which could be compared to an economy and macro behavior, not stating that it’s the
case. “Macroeconomics” by Nils Gottfries illustrates how nation’s economy is affected by
various changes but some parts could be applied to this situation, as an increase of money
supply.
A.H Studenmunds book “Using econometrics” will be used in the purpose with creation of the
regression estimation. The book will not be referred to in theoretical part but will be used under
the following section “methodology” and “theoretical models”. “Using econometrics” contains
information of creation of the regression and various problems that could occur.
6
1.5 Structure
This paper will consist of four different sections until the conclusion, dividing up the
information into section will help to clarify the content. The first part will consist of theoretical
information about the soccer industry to give the reader an understanding of behavior and
structure. The second part contains economical models and theories relevant to the thesis and
applies under the circumstances.
The third section contains the methodology used for the empirical parts and to obtain the
findings. The origin of the data will be presented together with structure of the approach to the
theoretical models, which contains the collected data.
The last section of this paper will consist of two diverse findings from investigation of the
thesis, price development and one regression. Using separate results method will illustrate the
effect of an increased broadcasting revenue in diverse ways, but with the findings it will either
strengthen the thesis or reject it.
7
2. Soccer industry
2.1 Sports ideology
Peterson (2004) describes how the Swedish sport movement has developed since the
government abolished the regulations limiting to amateurism, this lead an introduction of today
two important processes professionalization and commercialization. Complementing the old
system of non-profits and amateurism which was regard as a welfare project, to occupy people
from unhealthy living.
Sports organizations option to decide what kind of operation they want to have is not limited to
Sweden, it implies within most parts on Earth but with different conditions and circumstances
between various sports and nations.
According to Kuper and co-writer Szymanski (2014) there have been numerus times a
businessman overtakes a top-level soccer club with target to develop both the competitive
outcome and the profit. Given the facts around Alan Sugar 10 years in Tottenham in north
London, during that period the club became the definition of a mid-table team and each season
the local rival Arsenal finished above. The fans weren’t happy with the performance and during
the first six seasons Sugar only made £12 million in profits, which is considered low.
Kuper and Szymanski presents a study of how profits and losses both have gone towards zero
from 1993 to 2012 amongst Premier League clubs, with barely any consistent connection
between a good placement and profits. Surely there are some suggestions of top teams making
bigger profits but as well top teams losing more. In 45% of the cases there is a negative relation
between change in league finishing and profits, a better finishing leads to decreasing profit or
a worse placement leads to increasing profits. The remaining 55% has a positive relation
between placement and financial results, better placement generates higher profits and worse
gives lower profits.
Journalist Francisco Perez Cutino noted: “It’s not that winning matches can help a club make
profits; rather, the effect works the other way around: if a club finds new revenues, that can
help it win matches” (Kuper & Szymanski 2014, p. 76).
Szymanski together with the Spanish economist Garcia del Barrio presented the findings based
on English and Spanish clubs, that if a club want to make profits they must decrease
expenditures in form of wages. Clubs that paid their players less in wages suffered on the pitch,
since the relation between higher wages and winning games are strong. The conclusion is in
8
form of a tradeoff: to acquire trophies clubs must omit maximized profits and vice versa
maximized profits omits trophies. For the recurring Spanish league challenger Barcelona to
maximize its profits the estimated optimal league finishing would be at 15th place.
2.2 English Premier League
Worldsoccertalk (2017) presents basic information about the English Premier League (EPL),
also called Barclays Premier League. The league quickly became one of the world’s most
popular competition after its reconstruction and launch in 1992. Today EPL consists of 20 clubs
where all of them plays one home and away game against each opponent, generating a total 38
games each season. The first kick-off is in August and the final whistle in May without any
breaks except international competitive games arranged by either FIFA or UEFA, the World
and European association of football, that only occurs a few times each season.
Buzzacchi, Szymanski and Valletti (2003) defines the league format as “open”, which means
that each season there are a small rotation of teams. Annual promotion and relegation is the
process where the three clubs in the EPL with the lowest amount of point gets swapped with
the top three clubs from the second division. North American sport leagues and with its
franchise system uses the other format “closed”, where there is team rotation except when a
franchise decides to relocate. It is also common in Europe that clubs compete in more than one
national competition, consisting of both the league and knock-out cups.
An article by Skysports (2016) explains how the qualifications for the two European
competitions Champions League and Europa League depends on clubs’ performances, where
the Champions league has a higher status. The winner of the EPL together with the second and
third placer qualifies directly for the main event of Champions League, while the fourth placer
must go through a play-off round. Winning either one of the two English national knock-out
cups, FA cup or League cup, will guarantee a spot in the Europa league. The winners of
Champions League and Europa league will both be given a place in the Champions League, for
one of them a chance to defend the title.
Premier League (2017) itself goes through the internal structure where the league is treated as
a company and where each one of the 20 member clubs are shareholder, each season the
relegated clubs’ losses it shares and the promoted clubs is appointed as new owner. All members
work independent form each other following the rules of the league itself, the English soccer
association the FA, UEFA, FIFA and as well following the law. The Premier League rulebook
9
is treated as a contract between the league and clubs, breaking it could lead to sports-related
punishments, financial or even exclusion. The clubs have the opportunity to affect the rules and
propose ones at a yearly shareholder meeting requiring that 14 of 20 clubs has to support the
proposal.
2.3 Regulation
UEFA (2017) published information about the purpose and restrictions when introducing
Financial Fair Play regulations, the reason for establishing FFP is to improve the financial
health within European soccer industry. Limiting clubs to only have negative balance at €5
million over a period of three years to prevent them from creating unstainable debt, revenues
minus expenditure. At the moment, it is allowed to exceed if the clubs’ owner directly cover
this but there are regulations, and at the summer of 2018 and forward this extra input from
owners will be considered illegal.
UFEA will investigate sponsorship deals between clubs and companies where there exists direct
links between the clubs’ owner and the sponsoring company. Representatives from UEFA will
determine if the sponsor revenues are according to market price and considered fair valued.
Breaking the FFP will generate consequences risking a warning and reprimand followed up by
financial or sports related punishments, even exclusion from competitions.
In Kuper and Szymanski (2014) work they share the story about when the “Sugar Daddy”
Roman Abramovich in 2003 bought London based soccer club Chelsea, he went from unknown
billionaire to world celebrity. The objective was to have fun and it was clear from the beginning
that it was not a financial investment, during his first eight years as owner the club had losses
at a total exceeding £630 million. Since Abramovichs arrival, several more “Sugar Daddies”
has bought clubs and became a part of the industry with the same objective. The effect has been
increasing wages and transfer fees for players while the clubs’ profits shrinks.
FIFA (2017) has presented regulations regarding players’ status and transfers where it is clear
that a player can only be registered at one club at a time. During a season, the same player could
be registered for three different clubs but being enable to represent two of them in official
matches. At two separate times during the season is the player able to register for a new club,
first opportunity is between two seasons and secondly in the middle of the season.
Transfers of minors has different regulations, no international transfers of players under 18 is
allowed. But there are three different exceptions, firstly if the parents move to the country of
10
the interested club on bases without connection to soccer. Secondly if the player lives 50km to
the border of the nation of the interesting club which is also located 50km to the same border,
creating a maximum distance of 100km but the player still lives at home. Last is that it takes
place within the European Union but the player has to be 16 or older, with the conditions that
the club is directly responsible for the players’ education, health and living situation.
2.4 Transfer system
Carmichael (Andreff & Szymanski, 2009) indicates that three reasonings is behind all transfers;
either it is to increase the financial state of mostly the selling club, improve performance of the
buying club or satisficing players desire.
The most common process start by the interesting club approaches the club the player is
contracted to, but there are situations where selling clubs offers the player to other clubs for
certain price. After the clubs has agreed upon a transfer fee the buying club is allowed to contact
the player and start to construct a contract containing personal terms, but the player is neither
obligated or forced to sign the contract and that leads to a cancelling of the transaction.
The payment of the transfer could be in various forms, most common is that all or the majority
of the payment is a one-time transaction in connection with the player physically moves and it
is not uncommon that the payment consists of numerical payments over a period of time. The
transfer fee could even consist of “bonuses” triggered by either the players’ performances or
team performances by the buying club, even other players could be included as a part of the
payment or regarded as the whole payment.
2.5 Player pricing
Haverkamps (2010) paper researched factors determining prices of players in Netherlands top
division Eredivisie. Accordingly there are three main factors affecting: players characteristics,
buying and selling clubs characteristics. Clubs actions are based on economical reasoning and
both buying and selling club is methodical.
According to Kuper and Szymanski (2014) the French soccer club Lyon booked valuations of
their own players, with the philosophy to sell when a bid exceeded the valuation. Lyon used
media to push up the bid by publicly go out with that the player was not for sale as well that the
player was untradeable for them, although Lyon already had a replacement incoming.
11
Further Kuper and Szymanski introduce how nationalities has become fashion, the trend today
has left Dutch players and now Belgian players are the most popular. Following the traditional
economic model with supply and demand, the demand has increased while supply has remained
the same leading to an overvaluation of these players.
In Gulbrandsen and Gulbrandsen (2011) thesis they include one more price determined aspect
in fan appeal and noon performance related revenues, in form of commercial compensation and
publicity. No two players or clubs are identical and the result from combining player with club
will always be unique in performance and financial value.
2.6 Revenue
The Guardian (2017) published all involved clubs in the 2014/2015 edition of the Premier
Leagues’ financial figures. All clubs combined had a turnover at £3.4 billion, with Manchester
United at the top with £395 million and Burnley at 20th place with £79 million. The sum of the
six largest and lately performance wise most successful clubs’ turnover was equivalent to 55%
of all Premier League clubs.
Szymanski (2015) claims that the main four income sources for soccer clubs could be divided
in to; broadcasting rights, matchday revenues, merchandise and sponsorships. In 1958 the
average annual revenue for teams competing in the earlier version of Premier League hade a
turnover at £127 000, which was equal to Wayne Rooney’s salary for two and a half days work
in 2014. Excluding the inflation, the top division in English soccer has had an average annual
compounded growth rate at 7.3%.
Soccer industry revenues has a limited correlation with the growth of the general economy, the
correlation coefficient at +0.12. During the financial crises in 2008 the Premier Leagues
revenue grow by 20% since the introduction of a new broadcasting rights deal and 9% in 2009
while the national economy shank with 6% during the same period. But in 2005 the soccer
industry had it harder financial mostly base on a worse broadcasting deal then previous one
while the national economy had a positive trend.
12
2.7 Broadcasting
Parlasca (Andreff & Szymanski, 2009) describes the collective selling of broadcasting rights
until 1990s as a deal between two monopolies, the English football association (the FA) and
governmental public service channels. The FA is treated as the producer and owns the rights
for the competition and sold the national rights to the BBC, since it was the only existing TV
company in England.
Nowadays the circumstances regarding selling broadcasting rights are describe as a cartel
business, there are still only one seller (the FA) but the broadcasting sector has expanded and
consists of many potential customers. The negotiation of whom to broadcast is an auction where
broadcasting companies bids but the seller still sets the conditions for the final product.
According to the BBC (2015) during the current deal the broadcasters are allowed to have live
coverage on TV at 46.67% of all Premier League games, 168 of 380 games each season.
Parlasca (Andreff & Szymanski, 2009) claims that both the quantity and the quality of
broadcasting the EPL would increase if clubs themselves would negotiate the broadcasting
rights either by game-by-game or seasonal package instead of the monopoly selling collective.
The willingness to pay by broadcasting companies is affected by two major factors; the quality
of the TV-rights and that the contribution of the contract would increase the broadcastings
overall revenue and not only the sport sectors.
The collective selling of the rights reduces the consumer choice, since there is a negotiation in
the broadcasting rights of how many games will be sent live and each weak will consists of
mostly different teams. There is no evidence about a relation between increased overall
coverage and the attending audience, but the general interest has increased.
Buraimo (Andreff & Szymanski, 2009) presents three major factors affecting potential viewers
demand, firstly cost and availability, quality in talent referred as star players attending and the
composition of which teams that are on the pitch.
An expression of a demand function has been published by Buraimo (2007) focusing on the
audience to the broadcasting in England. With the assumption of no limitations of availability,
compared to at the stadium where the home crowd often outnumbers the visitors crowd.
𝐴𝑈𝐷𝑖𝑗𝑡 = 𝑔(𝐵𝐴𝑅𝐵, 𝑃𝑅𝑂𝑀𝑣𝑠𝑃𝑅𝑂𝑀, 𝑃𝑅𝑂𝑀𝑣𝑠𝑀𝐼𝐷, 𝑃𝑅𝑂𝑀𝑣𝑠𝑅𝐸𝐿, 𝑀𝐼𝐷𝑣𝑠𝑅𝐸𝐿,
𝑅𝐸𝐿𝑣𝑠𝑅𝐸𝐿, 𝐶𝑊𝐴𝐺𝐸/ 𝐷𝑊𝐴𝐺𝐸, 𝑈𝑁𝐶𝐸𝑅𝑇𝐴𝐼𝑁𝑇𝑌, 𝑂𝑇𝐻𝐸𝑅 𝐷𝑈𝑀𝑀𝐼𝐸𝑆, �̅�𝑖𝑗𝑡)
(1)
13
AUD is described as the logarithm of broadcasting audience between the two teams i and j in
season t. Barb is a company in England that measures viewers ratings and what they watch,
BARB is a dummy variable upfield if the viewer is a part of Barbs measurements. PROM
represents teams in top 6 in the ongoing season, MID teams ranked between 7th and 16th while
REL are teams risking being relegated from the league. CWAGE is both teams total wage bill
for the season divided by the whole leagues seasonal wages. Alternative use DWAGE, the
difference between the teams’ seasonal wage divided by the average wage in the league.
UNCERTAINTY is analyzed evaluation of the outcome. Āijt captures the at atmosphere
produce by the attending fans at the stadium.
2.8 Production
Accordingly to Borland (Andreff & Szymanski, 2009) there are five major components, divided
into producers and consumers, that affects the production of team sports. Only one major
component belongs among consumers and it is the audience of the competitions, including
minor components in from of media and business seeking advertising (sponsors) in connection
to the event are the only actor is threated to consume the product.
The producer category consists of players, clubs, the competition and stadiums, with the
government as an outsider contributor. The players are regarded as labor in the production in
any form of competitions, as professionals, amateur and junior players. Clubs are the company,
structuring the internal processes, employ labor and stands for the production. Stadium are the
place of production and the competition are both defining the industry and threated as input.
Changes in production acquire when the expectations of the consumers deviate from what is
produced, what the players among themselves, club and the competition sets for guidelines and
objectives. Similar to most other industries behavior, but the abnormal vision between the
producers and consumers leads an evolution of the production within the team sport.
Borland (Andreff & Szymanski, 2009) has developed a general production function for one
team but it is presented as how it could be specified since it doesn’t exist one version that is
agreed on:
𝑃𝑖𝑡 = 𝛾(𝑄1𝑖𝑡, … , 𝑄𝐽𝑖𝑡, 𝑀𝑖𝑡, 𝑇1𝑖𝑡, … , 𝑇𝑁𝑖𝑡); 𝑖 = 1, … , 𝑖; 𝑡 = 1, … , 𝑇 (2)
14
The denotation P represents either the performance or the output produced of team i at time t.
The independent factors consist of quality (Q) of the J player in the club, the manager (M) and
other N team quality(T).
The disagreement of the correct version of production function is based on what output to
measure, which inputs to include and the functional form. The result and the formulation of the
production function will differentiate between sport and researcher. Most common way to
present production is by season winning percentage, but many sports consist of three outcomes
win, lose or draw and a winning percentage would generate to a misleading finding since
percentage doesn’t give the whole picture.
Given Scully research from 1974 “Pay and performance in Major League Baseball” with the
seasons 1968 and 1969 as data, Scully presented a production function with teams winning
percentage as output:
𝑃𝐶𝑇𝑊𝐼𝑁𝑖𝑡 = 𝛼 + 𝛽𝑇𝑆𝐴𝑖𝑡 + 𝑥𝑇𝑆𝑊𝑖𝑡 + 𝛿𝑁𝐿𝑖𝑡 + 𝜑𝐶𝑂𝑁𝑇𝑖𝑡 + 𝜔𝑂𝑈𝑇𝑖𝑡 + 휀𝑖𝑡 (3)
The variables themselves has no interest but baseball as a sport could be analyzed with statistics
in percentage; the batters hit percentage, average bases reached and percentage to reach first
base. Compared to other sports baseball is easy to present numbers on performances.
15
3. Economics theory
3.1 Budget constraints
Varian (2014) interpolates the budget constraint as all combinations of goods consumers can
afford with its income. Mostly it’s enough to use two goods in the instruction of the theory and
makes it easier to understand with help of graphs. In the economy there are two goods, apples
and pears, the combination of apples and pears are denoted (xa, xp) and indicates the consumers’
consumption bundle. Pa and pp represents the prices of apples and pears, while the income is
denoted by m. Everything below and up to the income is affordable and therefore the budget
constraint is the following:
𝑝𝑎𝑥𝑎 + 𝑝𝑝𝑥𝑝 ≤ 𝑚 (4)
The budget line is when exactly all income is spent on consumption and presented in the
following:
𝑝𝑎𝑥𝑎 + 𝑝𝑝𝑥𝑝 = 𝑚 (5)
Figure 2: Budget constraint
With an income of 10 and prices of both apples and pears are 1, the consumer has the option to
spend all income on 10 apples, 10 pears or anything in between. There is a negative relationship
between apples and pears with a tradeoff 1 to 1, giving up one apple gives one pear.
Changes in m is denoted either income increase or decrease depending on if the value is higher
or lower than the original m. Graphically with an income increase will the budget line do a
0
2
4
6
8
10
12
0 2 4 6 8 10 12
Pea
r
Apple
16
parallel shift outwards, if m equals 12 instead the budget constraint will go between 12 on the
vertical and horizontal axis.
Price changes also affects the budget line but differently, increasing prices in apples will lead
to a lower amount in consumption. If the price of apples increased to 2 while income and pears
are unchanged at 10 and 1, the maximum consumption of apples are 5 while pears are 10. Giving
them a trade with 1 apple for 2 pears, a negative relation with double slope from first case. The
budget line goes from the 10 on the vertical axis to 5 on the horizontal axis.
3.2 Consumption over two periods
Gottfries (2013) explains how a consumer could plan their consumption over two periods, with
income and consumption in each period. The income is denoted Y1l and Y2
l, the real income in
period 1 and 2 exposed as units of consumption and the consumer will spend all income over
both periods. C1 and C2 denotes consumption in the two periods and i is the interest rate from
period 1 to period 2. The net savings, income minus the consumption in period 1 will be transfer
to period 2 and is explained by following:
𝑃1𝑌1𝑙 − 𝑃1𝐶1 (6)
In period 2 the consumer will receive new income and continuous to consume but it will be
affected by the net saving balance from period 1, giving the following equation:
𝑃2𝐶2 = 𝑃2𝑌2𝑙 + (1 + 𝑖)(𝑃1𝑌1
𝑙 − 𝑃1𝐶1) (7)
Reworking the equation and introducing the real interest rate: 1+ r = (1+ i) / (P2/P1) (see
Appendix 3 for mathematics), result in the following:
𝐶1 +
𝐶2
1 + 𝑟= 𝑌1
𝑙 +𝑌2
𝑙
1 + 𝑟
(8)
The right side of the equation is the present value of income during the two periods and since
there are no savings outside this periods income equals the present value of consumption. If the
consumer only lives within two periods this formulation is called lifetime budget constraint.
17
3.3 Money and Inflation
Gottfries (2013) claims that there is a simple theory in the long run between money and inflation
in the whole economy, by assuming that the money supply has a fixed exogenous velocity –
describe as the number of times a single bill is used within the economy. Denoting the velocity
with V, money quantity with M, prices by P and Y as production gives the following equation:
𝑀 ∗ 𝑉 = 𝑃 ∗ 𝑌 (9)
The right side, P*Y is the notation for the nominal value of production or expressed as GDP.
Giving that the money quantity times velocity equals the GDP.
In the long run the economy will have a natural level of production, affecting the Y variable to
fluctuate around one production level and changing the definition of Y to Yn (natural level of
production). Assuming that the money supply is determined by the central bank and velocity is
an exogenous value makes P an expression of given values:
𝑃 =
𝑀 ∗ 𝑉
𝑌𝑛
(10)
With a decision from the central bank to increase the money supply by 15% will increase prices
by the same percentage, since there are given values of velocity and production, concluding
price levels follow the money quantity.
Inflation is described as the change in price levels over periods. Measures with the consumer
price index illustrates the cost changes in consumption of the same good over two periods of
time, where inflation is denoted by π:
𝜋 =
𝑃𝑡+1 − 𝑃𝑡
𝑃𝑡
(11)
18
3.4 Market equilibriums
According to Varian (2014) total demand is describe as the sum of all individual consumers’
demand, which is the consumers’ willingness to purchase goods based on the price. Giving the
equation that demand is a function of price, D(p). The tendency is that the cheaper the good
becomes more will be consumed, a negative relation and a negative slope in graphs.
Supply determined how much procurers will supply the market with, that is dependent on the
possible selling price of the good. Since the price of the good determents the supply, it gives
the function S(p). A positive relation between price and quantity, the slope is positively sloped
indicating that higher price leads to more goods on the market.
The market equilibrium in a noon regulated competitive market is described as where the supply
function and the demand function are equivalent, it indicated both the quantity and the price of
goods on the market for individual goods or baskets of goods. The equilibrium price is denoted
P* and has the same value in both functions, according to the equation:
𝐷(𝑝∗) = 𝑆(𝑝∗) (12)
Borjas (2016) claims it’s a comparable situation within labor economics, but with different
variables and circumstances. Wages is the independent factor instead of prices and employment
instead of quantity. Supply is described as the labor force willingness to work at a given wage,
generating the formula S(w). With a positive relation, it indicates that increased wage will
increase work force willingness to work.
Demand in labor economics is firms’ willingness to employ dependent on wages, a function
formulated as D(w). A negative relation between wages and employment, high wages to few or
low wages to many.
The equilibrium in the labor market behaves as in a competitive goods market, where the supply
function equals the demand function. Both wage and employment will be given by the collusion
of labor force looking for work and firms looking for employment. In equilibrium wage is
denoted w* and employment is denoted E*.
19
4. Methodology
4.1 Data
The hearth of this thesis will consist of microdata about soccer players’ transaction between
two clubs, information regarding the transfer fees. This information will be collected from the
website Transfermarkt, which is a database of statistics, valuations and other information
relevant to soccer players as well as the industry. The website is regarded as reliable since its
function is to collect information to one database, the website has it on staff and the business is
owned by Alex-Springer Verlag that also own the German newspaper “Bild”.
The microdata is complemented by information about the changes in income, which is collected
from the BBC article “Premier League TV rights: Sky and BT pay £5.1bn for live games”
published February 10th, 2015. The information used from the article is when the increase of
broadcasting revenues occurs together with the numbers of the changes.
Information about the clubs’ performance and placement in the league from previous season is
data collected from both Premier Leagues’ official website and Wikipedia. The data used from
these sites are the finishes in the table from the previous seasons, which gives the clubs that are
promoted and relegated together with which clubs qualified for European tournaments.
The information will be handled separately and each transaction will be an observation, and all
data will be collected in Excel (see Appendix 1). The data consists of what could be described
as player data and club data. Each observation will contain what player the transfer regards
together with both involved clubs, the transfer fee and information to satisfy all variables
presented in section 4.3.2 related to the regression. It is a total of 847 player transfers collected
where 585 is included in the regression, the remaining 262 represents players sold from the
league which is not include in the regression.
4.2 Price development
The short description of this section is the actual changes in transfer fees and behavior from
involved actors in Premier League during the period of interest.
KEA European Affairs & CDES (2013) report about the soccer industry, presents how both the
value of the transfers and the amount of transfers has increased from the seasons 1994/1995 to
2010/2011 in the whole industry. The information is separated into four seasons with five years
in-between, given 1994/1995, 1999/2000, 2005/2006 and 2010/2011. The first observation had
20
5 735 transfers to a value of €402 869 000, given an average transfer fee of €70 247. In the
season of 2010/2011 18 307 transfers occurred at the total value of € 3 002 198 000, the average
transfer fee at € 163 992. It’s estimated that 55% of the value of the transactions comes from
the “big 5” leagues including English Premier League.
Table 1: Consumption development (Source: KEA European Affairs & CDES)
An increase of income leads to expectations of a counter reaction for the clubs increased
financial state. Not clamming that the soccer industry is a national economy or behaves like
one, but it has similarities to Gottfries (2013) theory intercepted as money supply equals the
value of production presented with equation (9).
Since the introduction of UEFA Financial Fair Play the access to introduce legal money into
the soccer industry has be reduced heavily, now only allowing revenue related to the business.
Together with Szymanskis’ (2015) claims that profits have gone towards zero, indicates that
the money clubs earn equals or almost equals the expenditures.
Gottfries (2013) claims when one of the four variables included in equation (9) changes it
requires a reaction by one of the remaining three. In the situation with increased revenues the
focus will be on the reaction of transfer fees and price development, similar to an inflation but
only for on section of the national economy therefor denoted price development.
The development of the transfer fee will be illustrated by calculating the average payment for
each season during the period of interest using the collection of data. Average transfer fee will
generate neutral findings if any trend could be allocated related to the increased revenues. The
finding will be divided into four categories, separating the information will help avoid double
couniting transfers since sold from one club will be bought by another:
• Bought to EPL – players purchased from clubs in other competitions than EPL.
• Bought within EPL – players purchased from clubs in EPL.
• All bought by EPL club – combined findings from bought to EPL and bought within
EPL.
• Sold from EPL – players sold to club outside EPL.
21
The category “Sold from EPL” is not expected to have the same result as the other three, but
should follow the same trend. Since club within the Premier League is not the buyer and other
parts of the soccer industry does not have the same development with its resources leads to
lower transfer fees. At the same time the clubs should acquire a higher transfer fee to maximize
the return of their investment. Another possible outcome is that EPL clubs sell of unnecessary
labor to a sales price while it still has a value.
Presenting the information in a box plot consistent of three periods, one for each broadcasting
deal active during the period of the thesis, will illustrate changes in clubs’ consumption
behavior using all transfer fees from the investigated five seasons. The box plot will clarify Q1
(first quartile), median, Q3 (third quartile) and establish qualifications for outliners, which is
1.5(Q3-Q1) from either Q1 or Q3.
4.3 Regression
4.3.1 Process
The thesis will consist of a “try and error” system while establishing a regression representing
the determination of transfer fees, since there is no regression model established with what
variables to include and not. The process will consist of several regressions, trying to find a
general expression of which variables to include and having a significant impact on the
outcome. Variables with strong indications of no insignificant impact will be removed leading
to a new regression, this process will be repeated until all unnecessary variables are omitted.
The inclusion of the variables that the findings are based on (TV1 and TV2) will occur when
there are an establish version, to avoid arguments and conflicts of controlling the result.
This way of approach conflicts with what Studenmund (2014) presents under “Specification
Searches” in context of fixing the findings, but as recommended all tested regressions is reveled
in the Appendix.
4.3.2 Variables
The table on the following page consists of all used variables in the process of establish on
regression, but long from all is included in the regression used for investigating the thesis.
22
VARIABLE DESCRIPTION Age Age of player at transfer Age-D Dummy variable: 1 if player is older than 26 when transfer occur Ars Dummy variable: 1 if buying club is Arsenal Ast Dummy variable: 1 if buying club is Aston Villa Bou Dummy variable: 1 if buying club is Bournemouth Bur Dummy variable: 1 if buying club is Burnley Car Dummy variable: 1 if buying club is Cardiff Che Dummy variable: 1 if buying club is Chelsea Cry Dummy variable: 1 if buying club is Crystal Palace Eng Dummy variable: 1 if the player has English nationality Eve Dummy variable: 1 if buying club is Everton Ful Dummy variable: 1 if buying club is Fulham G Dummy variable: 1 if player plays as goalkeeper GPL Nr of games played in the league previous season for owning club GPT Nr of games played in European tournament previous season for owning club. Hull Dummy variable: 1 if buying club is Hull Imp Dummy variable: 1 if player is bought form club outside EPL Jan Dummy variable: 1 if player is purchased during January Lei Dummy variable: 1 if buying club is Leicester Liv Dummy variable: 1 if buying club is Liverpool M Dummy variable: 1 if player plays as midfielder ManC Dummy variable: 1 if buying club is Manchester City ManU Dummy variable: 1 if buying club is Manchester United Mid Dummy variable: 1 if buying club is Middlesbrough New Dummy variable: 1 if buying club is Newcastle N.EU Dummy variable: 1 if player doesn’t have EU nationality Nor Dummy variable: 1 if buying club is Norwich nrS Number of seasons player has represented previous club since 18th birthday PT Dummy variable: 1 if purchasing team is promoted to EPL QEU Dummy variable: 1 if purchasing team is qualified for European tournament
upcoming season
QPR Dummy variable: 1 if buying club is QPR Rea Dummy variable: 1 if buying club is Reading S Dummy variable: 1 if player plays as striker Sou Dummy variable: 1 if buying club is Southampton Sun Dummy variable: 1 if buying club is Sunderland Swa Dummy variable: 1 if buying club is Swansea Tot Dummy variable: 1 if buying club is Tottenham TF Transfer fee, payment between two clubs in exchange for player TV1 Dummy variable: 1 if purchase occur during broadcasting deal between
2013/2014 and 2015/2016
TV2 Dummy variable: 1 if purchase occur during broadcasting deal between 2016/2017 and 2018/2019
TVTR Broadcasting rights deal generation of revenue to clubs Wat Dummy variable: 1 if buying club is Watford WestB Dummy variable: 1 if buying club is West Brom WestH Dummy variable: 1 if buying club is West Ham Wig Dummy variable: 1 if buying club is Wigan Year Season after 2012/2013 that transfer occur
Table 2: Regression variables
23
The table consist of numerus dummy variables indicating which the buying clubs is but one
club is missing, namely Stoke. If all dummy variables that includes a club has the value 0, Stoke
is active. Chosen for this roll since during the investigated period Stoke has continuously
finished in the middle of the table with the following placements 13th, 9th, 9th, 9th and 9th, no
other club has been more stable in the middle region.
Similar with the dummy variables indicating the players positions, defender has no own dummy
variable and is active if the variables G, M, and S has the value 0. If it is not a goalkeeper,
midfielder or striker it must be a defender.
4.3.3 Estimation
Haverkamps (2010) work determine that both player characteristics and club characteristics
affects the transfer fee. There are no indications of what is included in either player or club
characteristics. This regression could be explained by Haverkamps (2010) work but also
introducing the characteristics of the financial state of the league and especially the revenue
from the broadcasting rights
Often in situations regarding transfers and valuations of soccer players the terms current and
potential ability are common. Determination of how good a player is and could be has
significant impact on the transfer fee, but it is almost impossible to estimate in numbers since
soccer is a game with more than one aspect. Clubs set their own valuations of players they
possess and players matching attributes the club seeks, leading to a non-existing general way
of determining valuation.
The regression will consist of numerus independent variables to give a better description of
what factors determining the transfer fee. These variables will contain both information about
clubs’ active in the transaction, performance and information about the player. The regression
estimation is the following:
𝑇𝐹 = 𝛽0 + 𝛽1"𝐴𝐺𝐸 − 𝐷" + 𝛽2𝐺𝑃𝐿 + 𝛽3𝐺𝑃𝑇 + 𝛽4𝐼𝑀𝑃 + 𝛽5𝑇𝑉1 + 𝛽6𝑇𝑉2 + 𝛽7𝐺 + 𝛽8𝑀
+ 𝛽9𝑆 + 𝛽10𝐴𝑅𝑆 + 𝛽11𝐶𝐻𝐸 + 𝛽12𝐿𝐼𝑉 + 𝛽13𝑀𝐴𝑁𝐶 + 𝛽14𝑀𝐴𝑁𝑈 + 𝛽15𝑇𝑂𝑇
Ruijg and van Ophem (2014) states that age has a significant impact on the transfer fee, with a
positive effect up to the age of 26. AGE-D is a dummy variable, active if the player has passed
the age 26 at the time of the transfer.
24
Both GPL and GPT implies how important the player has been during the previous season, with
how many games in the national league and in European club tournament the player has
appeared in.
IMP stands for import, a dummy variable active if the player comes from another league than
English Premier League. The variable does not specify if the transfer occur from a team within
the English division system or from another nation.
The variables with most importance for the aim of the thesis is TV1 and TV2, both dummy
variables indicate an income increase as an effect of new broadcasting rights deals at two
separate occasions. TV1 is active between the seasons 2013/2014 and 2015/2016, while TV2
is active during the season 2016/2017. Both variables are expected to indicate a drastic jump of
the transfer fees, generating a higher demand of money in exchange for players than previous.
Leading to the establishment of the following hypotheses testing:
𝐻0 = 𝑛𝑜 𝑖𝑚𝑝𝑎𝑐𝑡 𝑜𝑓 𝑏𝑟𝑜𝑎𝑑𝑐𝑎𝑠𝑡𝑖𝑛𝑔 𝑟𝑖𝑔ℎ𝑡𝑠 𝑟𝑒𝑣𝑒𝑛𝑢𝑒𝑠
𝐻𝐴 = 𝑆𝑖𝑔𝑛𝑖𝑓𝑖𝑐𝑎𝑛𝑡 𝑣𝑎𝑙𝑢𝑒𝑠 𝑜𝑛 𝑇𝑉1 𝑎𝑛𝑑 𝑇𝑉2
One of the three dummy variables G, M and S is fulfilled it the player is either a goalkeeper, a
midfielder or a striker. If no of the variables has the value 1, then the player is a defender.
The regression estimation contains six dummy variables that represents the buying clubs. These
clubs have the best financial state seen to the whole league, and they are regularly qualified for
the European club tournaments; Champions League or Europa League. If neither of the included
clubs’ variable are active indicates one other actor in the league is the buying club, implying
the assumption that the remaining clubs has similar behavior related to consumption.
As Studenmund (2014) points out correlation between variable affects the outcome, two or
more variables generates an explanation of similar affects and relevant variables get
insignificant estimations. The variable YEAR has been omitted since a strong connection with
the variables TV1 and TV2 could give a misleading result. YEAR could include other impacts
on the transfer fees that is not explained by any other included variable, some other effects that
has happened over time.
25
5. Results
5.1 Price development
The findings in the diagram follows the expectations that an increase of revenues directly affects
the transfer fees and valuations of soccer players purchased by clubs in EPL, where the average
transfer fee has almost doubled over the period of five years or expressed as a period of three
different broadcasting deals.
Figure 3: Transfer fee development
“Bought within EPL” has the average transfer fee € 8 738 636 at the season 2012/2013, there
is an insignificant increase by the following season with an average of € 9 369 474. The increase
of the first broadcasting revenue has a minimal impact and the increase could be a change by
other factors as well. During the epoch of the new broadcasting deal the increase is almost
steady over the two seasons at almost € 2 000 000, with an average of € 11 203 333 respectively
€ 13 162 000. The second revenue increase from broadcasting rights decrement in the payments
between two clubs compared to the previous year, giving an average transfer fee at €
14 160 606.
The trend of “Bought to EPL” has another development, at the first studied season 2012/2013
the average transfer fee is € 6 193 817. The following season has a significant increase with an
average payment at € 8 667 193, this drastic change could be allocated by the increased
revenues. The development for the season 2014/2015 could on the other hand not be explained,
since the transfer fees increase is similar to the one from 2012/2013 to 2013/2014 given an
average at € 10 264 375. During the season 2015/2016 the average is follows the valuations
from previous year with € 10 102 615. The gap created unto the season 2016/2017 is distinct
0
5000000
10000000
15000000
2012/2013 2013/2014 2014/2015 2015/2016 2016/2017
Average transfer fee in €
Bought to EPL Bought within EPL
Sold from EPL All bought by EPL club
26
and could be referred to an income increase given that the average transfer fee for the season is
€ 13 219 148, an increase of lite over € 3 000 000.
“All bought by EPL club” is a combination of “Bought within EPL” and “Bought to EPL”,
where the amount of transfers is heavily more in “Bought to EPL” which makes this trend
follow the development of “Bought to EPL”. At the season 2012/2013 the average transfer fee
was € 6 680 652, followed by an average payment of € 8 798 010 during the season 2013/2014.
The two seasons 2014/2015 and 2015/2016 has similar averages at € 10 538 584 respectively €
10 673 396, a resembling to the development from “Bought to EPL” for those seasons. The
increase of the season 2016/2017 could be argued to be evident an effect of the new
broadcasting rights since the average transfer fee is € 13 475 909.
By establishing the facts from the development, the change in transfer fees are significant from
the second income increase between the seasons 2015/2016 and 2016/2017. The same could be
argued for the first income increase but since a similar development on the following season
some other factor could influence the findings.
The development from “Sold from EPL” doesn’t follow the same theory about the transfer fee
development but is expected to have a similar growth. The increase between 2012/2013 and
2013/2014 is significant, from 2013/2014 the average transfer fee could be described as
stabilized with a slight decrease under the following seasons. The selling of Gareth Bale
2013/2014 and Luis Suarez 2014/2015 has affected the results since the two transfers together
was € 182 720 000 which is equivalent to 36.9% of the total sales under these two seasons,
which leads to a boost in the average transfer fees during these seasons.
Studding the amount of transfers and the total value of all transfers similar to KEA European
Affairs & CDES (2013), it could be established that there is a strong indication of increasing
total values on transfer fees, appearing both in “Transfers fees from EPL” and “All transfer fees
payed.
Table 3: Compilation of transfers
27
Regarding the amount of transfers the same statement can’t be establish, surly the variation of
the number of players bought and sold is clear but there is no general trend. The season
2013/2014 has the lowest amount of total transfers, and since the amount of players sold has
increased but it cannot be argued to be significant.
The amount of players bought peaks during the season 2015/2016 at 134 transfers, these
transfers could be an pre-consumption with knowledge of an income increase similar to Nils
Gottfries (2013) explanation of consumption in two periods but an extended version of X
periods. BBC went public with the information about the revenue from the new broadcasting
rights in February 2015 but since all clubs contesting in EPL are stakeholders and shareholders
the information about the deal and negotiations could have been internal knowledge before
2015 and explain the increase in transfer fees in 2014/2015.
The box plot contains three time periods, representing the different incomes generated from the
broadcasting deals active in the five seasons studied. TV0 is the first deal, active during the
season 2012/2013. TV1 and TV2 follows the same description as the regression variables,
catching the time periods of the seasons 2013/2014 to 2015/2016 respectively season
2016/2017.
Figure 4: Box plot
The diagram gives a clear indication of increasing Q1, medians and Q3, illustrated with the
boxes moves upwards. The distance between Q1 and Q3 tend to increase, with that an
increase of the limit which indicates from where observations are marked as outlines. TV1 has
the most outlines but the period is also three times longer than the other two, which could
explain the difference in outliners. TV2 contains one observation above € 100 000 000 which
is the transfer fee for Paul Pogba when Manchester United bought him from Juventus in the
summer of 2016.
28
5.2 Regression 1: Optimal
The result from the regression estimation will determinate how several factors, consisting of
player and club characteristics together with broadcasting rights revenues affects the transfer
fee of a player. The regression will also establish if the broadcasting rights revenue has a direct
connection with increasing transfer fees.
Figure 5: Regression estimation
Almost all included variables in the regression estimation are significant different from zero, G
has a low t-score while AGE-D is on the boarder to significant, and indicates factors affecting
changes in the transfer fee which is the dependent variable. The adjusted R2 describes the fit of
the regression compared to each observation. This value is not near 1, but the value should be
perceived as good and the regression has produce a fully acceptable estimation.
One important notice it the INTERCEPTION of the y-axis, in the regression the estimation has
a strong negative value while this paper investigates the effects on transfer fees payed by one
club in exchange of a player form another club. No data used in this regression has a negative
29
value, the lowest data used is a transfer fee at € 100 000. These findings suggest a possibility
of both receiving a player and a payment, that scenario will be excluded in any type of
reasoning.
AGE-D has an insignificant value, just under the limit for significant. The variable tends om
imply that older players has lower transfer fees then younger, this offspring seems reasonable
but the determination at what age the tendency shifts at is undefined.
The variables GPL and GPT has both significant values, which implies that the more a player
plays the higher the transfer fee is expected to be. Appearances in European club tournaments
gives a higher valuation but the amount of games is much fewer compared to the league.
The regression applies that players imported to the Premier League is cheaper than equivalent
player at a direct competitor. The variable IMP has a strong negative impact with significant
values.
The variables TV1 and TV2 are indicates a transfer fee increase when the broadcasting deals
has generated higher revenues, since both TV1 and TV2 has t-scores significant different from
zero. Both variables reinforce the papers thesis with a relationship between income increase for
the clubs and increased transfer fees, and rejects the null hypothesis.
As briefly mentioned above, the variable G has an insignificant value on the t-score. The other
two position related variables, M and S, has t-score with significant impact on the dependent
variable. The conclusion is that defender and goalkeeper has similar transfer fees, while
midfielder and strikers is valued higher.
All the included clubs have significant values, indicating that their transfers have a higher
payment than the remaining actors in the league. The findings consist of different values on
each clubs’ dummy variable, with a span between € 5 025 022 to € 21 185 769.
30
6. Conclusions
The section “Price development” contains a strong indication of a relation between increased
broadcasting rights revenue and increased transfer fees at the summer of 2016, where the
average transfer fee rose from € 10 673 396 to € 13 475 909. There is also indication of the
same effect at the summer of 2013 where a new broadcasting rights deal applied, but the effect
continuous over the summer of 2014 which could not be explained. Over the studied period the
average transfer fee has more than double from € 6 193 817 to € 13 475 909, which could be a
direct reaction from the new deals.
The boxplot strengthens the thesis with its results, all transfer fees have increased. The
difference between the Q1 and Q3 has grown, but Q1 has increased during the three different
broadcasting revenue periods.
The regression presented contains two significant values on the two variables proving the thesis
and a relation between increased transfer fees with broadcasting rights, rejecting the null
hypothesis. Both TV1 and TV2 has a t-score almost exceeding 4 which is clearly significant
from zero, TV1 had an impact on the transfer fee excessing € 3 600 000 while TV2 exceeded €
7 300 000.
Together the diverse methods find a relation. Adding the increase from the regression during
the season 2016/2017 to the average transfer fee from 2012/2013 gives € 13 518 109, which is
close to the actual average transfer fee in 2016/2017 at € 13 475 909. Stating that the regression
estimation has equivalent outcome with the average transfer fee calculations.
Gottfries (2013) theory “Money and inflation” illustrates how a national economy reacts when
one of the included variables alter. Not claiming that the soccer industry follows this theory
from Gottfries, but the soccer industry has a similar behavior. Altering one factor that affects
the balance in the industry will lead to a reaction somewhere else.
Haverkamps (2010) conclusion from “What determined the transfer fee of a soccer player?
Evidence from the Dutch Eredivisie” is that the characteristics of the player and both involved
clubs determines the transfer fee. Adding to the theory is the financial state of the competition
and drastic changes in revenue for the clubs involved, as a change in income for all actors in a
sector where they are both buyers and sellers will increase the requested compensation for the
labor in form of a soccer player.
31
References
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WEBB BASED SOURCES
BBC (2015, February 10) Premier League TV rights: Sky and BT pay £5.1bn for live games.
Retrieve from: http://www.bbc.com/sport/football/31357409 (2017, April 7)
BBC, Sanghera Mandeep (2007) Transfer deadline day. Retrieve from:
http://news.bbc.co.uk/sport2/hi/football/6314369.stm (2017, April 7)
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nd_transfer_of_players_en_33410.pdf (2017, May 3)
Haverkamp Leon (2010) What determined the transfer fee of a soccer player? Evidence from
the Dutch Eredivisie. Retrieved from: http://dare.uva.nl/cgi/arno/show.cgi?fid=169049 (2017,
May 3)
KEA European Affairs & CDES (2013) The Economic and Legal Aspects of Transfers of
Players. Retrieved from: http://ec.europa.eu/assets/eac/sport/library/documents/cons-study-
transfers-final-rpt.pdf (2017, May 4)
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of Football Players, A Complete Pricing Framework. Retrieved from:
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ndsen%202011.pdf?sequence=1&isAllowed=y (2017, May 3)
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https://ideas.repec.org/p/ame/wpaper/1401.html (2017, June 6)
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Premier League teams explained. Retrieved from:
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33
DATA SOURCES
Transfermarkt.com (2017, April 21), Wikipedia.com (2017, April 19), Premierleague.com
(2017, April 19)
BBC (2015, February 10) Premier League TV rights: Sky and BT pay £5.1bn for live games.
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FIGURES
Figure 1: Broadcasting revenue development
BBC (2015, February 10) Premier League TV rights: Sky and BT pay £5.1bn for live games.
Retrieve from: http://www.bbc.com/sport/football/31357409 (2017, April 7)
Table 1: Development
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Players. Retrieved from: http://ec.europa.eu/assets/eac/sport/library/documents/cons-study-
transfers-final-rpt.pdf (2017, May 4)
34
Appendix
Appendix 1: Data collection
All data used in this paper will be in an attached Windows Excel document
35
Appendix 2: Regression schedule
X – Indicates insignificant variable
S – Indicates significant variable
“.” – Indicates almost significant variable
36
Appendix 3: Mathematics
Section 4.2, Consumption over two periods;
𝑃2𝐶2 = 𝑃2𝑌2𝑙 + (1 + 𝑖)(𝑃1𝑌1
𝑙 − 𝑃1𝐶1)
↔ 𝐶1 +𝐶2
1 + 𝑟= 𝑌1
𝑙 +𝑌2
𝑙
1 + 𝑟
𝑤ℎ𝑒𝑟𝑒 1 + 𝑟 =1 + 𝑖
𝑃2
𝑃1
=(1 + 𝑖)𝑃1
𝑃2
Proof:
𝑃2𝐶2 = 𝑃2𝑌2𝑙 + (1 + 𝑖)(𝑃1𝑌1
𝑙 − 𝑃1𝐶1)
𝑃2𝐶2 = 𝑃2𝑌2𝑙 + (1 + 𝑖)𝑃1𝑌1
𝑙 − (1 + 𝑖)𝑃1𝐶1
(1 + 𝑖)𝑃1𝐶1 + 𝑃2𝐶2 = (1 + 𝑖)𝑃1𝑌1𝑙 + 𝑃2𝑌2
𝑙
(1 + 𝑖)𝑃1𝐶1
𝑃2+ 𝐶2 =
(1 + 𝑖)𝑃1𝑌1𝑙
𝑃2+ 𝑌2
𝑙
(1 + 𝑟)𝐶1 + 𝐶2 = (1 + 𝑟)𝑌1𝑙 + 𝑌2
𝑙
𝐶1 +𝐶2
1 + 𝑟= 𝑌1
𝑙 +𝑌2
𝑙
1 + 𝑟