Study on the Contribution of Sport
to Economic Growth and
Employment in the EU
Study commissioned by the European Commission,
Directorate-General Education and Culture
Final Report
November 2012
SportsEconAustria (SpEA, Project lead)
Sport Industry Research Centre (SIRC) at Sheffield Hallam University
Statistical Service of the Republic of Cyprus
Meerwaarde Sport en Economie
Federation of the European Sporting Goods Industry (FESI)
Ministry of Sport and Tourism of the Republic of Poland
Contents
1 Executive Summary 1
2 Introduction 7
3 Developing Sport Satellite Account Systems in Europe 9
3.1 Satellite systems in the National Accounts ..................................................................... 9
3.2 An Input-Output Table: Sport ........................................................................................ 10
3.3 Analysis of the Economic Effects of Sport .................................................................... 10
3.3.1 Calculation of the Value-Added Effects of Sport ................................................. 10
3.3.2 Calculation of the Purchasing Power Effects of Sports ....................................... 10
3.3.3 Calculation of the Employment Effects of Sport .................................................. 11
3.3.4 Calculation of Multiplier Effects ........................................................................... 11
4 Definition of Sport in the Economic Sense 13
5 Set up of a Multiregional Input-Output Table: Sport 17
5.1 National Input-Output Tables ........................................................................................ 18
5.1.1 Calculation of Input-Output Tables ...................................................................... 23
5.1.2 The Input-Output Table of Malta .......................................................................... 29
5.2 Collection of National Sports Data ................................................................................ 31
5.3 Imports and Exports ..................................................................................................... 32
5.4 Enlarging national Input-Output Tables ........................................................................ 32
5.5 Multiregional Input-Output Table according to Chenery and Moses ............................. 34
5.6 Finalisation of the Multiregional Input-Output Table ..................................................... 37
6 European and International Data Sources 40
6.1 Production .................................................................................................................... 40
6.2 Sport-related Public Administration and Social Security, CPA 75 ................................. 41
6.3 Sport-related Education, CPA 80 .................................................................................. 41
6.4 Sport-Related Health, CPA 85 ...................................................................................... 42
6.5 The European Market for Sport Articles ....................................................................... 42
6.6 Import and Export Data ................................................................................................ 44
6.7 Additional Service and Goods Data .............................................................................. 48
6.8 Further Calculations ..................................................................................................... 49
7 Remarkable Matters 51
7.1 Prior Publications .......................................................................................................... 51
7.2 German Data ................................................................................................................ 51
7.3 Input-Output Table: Sport of France ............................................................................. 52
7.4 Issues related to Input-Output Tables ........................................................................... 55
7.5 International Trade Data ............................................................................................... 56
8 Employment 57
9 Strength/Weakness Analysis in a Country Comparison 62
9.1 Relative Strength and Weakness in the Goods and Services Sectors ......................... 63
9.2 Conclusion of Strengths and Weaknesses ................................................................... 65
10 Analysis of Growth Potentials 66
10.1 Common Growth Potentials .......................................................................................... 66
10.1.1 Sports Nutrition ................................................................................................ 66
10.1.2 Sports Insurance ............................................................................................. 67
10.1.3 Economic and Legal Consultancy ................................................................... 69
10.2 Country Growth Potentials ............................................................................................ 70
11 Identification of Key Sectors 72
12 Range of products 75
13 Macroeconomic Effects of Sport - European Union 77
13.1 Gross value added ....................................................................................................... 77
13.2 Employment .................................................................................................................. 78
13.3 Sector-specific multipliers ............................................................................................. 79
14 Macroeconomic Effects of Sport - National Results 83
14.1 Austria .......................................................................................................................... 84
14.1.1 Gross value added .......................................................................................... 84
14.1.2 Employment .................................................................................................... 85
14.1.3 Sector-specific multipliers ................................................................................ 85
14.2 Belgium ......................................................................................................................... 87
14.2.1 Gross value added .......................................................................................... 87
14.2.2 Employment .................................................................................................... 88
14.2.3 Sector-specific multipliers ................................................................................ 88
14.3 Bulgaria ........................................................................................................................ 90
14.3.1 Gross value added .......................................................................................... 90
14.3.2 Employment .................................................................................................... 91
14.3.3 Sector-specific multipliers ................................................................................ 91
14.4 Cyprus .......................................................................................................................... 93
14.4.1 Gross value added .......................................................................................... 93
14.4.2 Employment .................................................................................................... 94
14.4.3 Sector-specific multipliers ................................................................................ 94
14.5 Czech Republic ............................................................................................................ 96
14.5.1 Gross value added .......................................................................................... 96
14.5.2 Employment .................................................................................................... 97
14.5.3 Sector-specific multipliers ................................................................................ 97
14.6 Denmark ....................................................................................................................... 99
14.6.1 Gross value added .......................................................................................... 99
14.6.2 Employment .................................................................................................. 100
14.6.3 Sector-specific multipliers .............................................................................. 100
14.7 Estonia ........................................................................................................................ 102
14.7.1 Gross value added ........................................................................................ 102
14.7.2 Employment .................................................................................................. 103
14.7.3 Sector-specific multipliers .............................................................................. 103
14.8 Finland ........................................................................................................................ 105
14.8.1 Gross value added ........................................................................................ 105
14.8.2 Employment .................................................................................................. 106
14.8.3 Sector-specific multipliers .............................................................................. 106
14.9 France ........................................................................................................................ 108
14.9.1 Gross value added ........................................................................................ 108
14.9.2 Employment .................................................................................................. 109
14.9.3 Sector-specific multipliers .............................................................................. 109
14.10 Germany .................................................................................................................... 111
14.10.1 Gross value added ......................................................................................... 111
14.10.2 Employment .................................................................................................. 112
14.10.3 Sector-specific multipliers .............................................................................. 112
14.11 Greece ...................................................................................................................... 114
14.11.1 Gross value added ........................................................................................ 114
14.11.2 Employment .................................................................................................. 115
14.11.3 Sector-specific multipliers .............................................................................. 115
14.12 Hungary .................................................................................................................... 117
14.12.1 Gross value added ........................................................................................ 117
14.12.2 Employment .................................................................................................. 118
14.12.3 Sector-specific multipliers .............................................................................. 118
14.13 Ireland ....................................................................................................................... 120
14.13.1 Gross value added ........................................................................................ 120
14.13.2 Employment .................................................................................................. 121
14.13.3 Sector-specific multipliers .............................................................................. 121
14.14 Italy ........................................................................................................................... 123
14.14.1 Gross value added ........................................................................................ 123
14.14.2 Employment .................................................................................................. 124
14.14.3 Sector-specific multipliers .............................................................................. 124
14.15 Latvia ........................................................................................................................ 126
14.15.1 Gross value added ........................................................................................ 126
14.15.2 Employment .................................................................................................. 127
14.15.3 Sector-specific multipliers .............................................................................. 127
14.16 Lithuania ................................................................................................................... 129
14.16.1 Gross value added ........................................................................................ 129
14.16.2 Employment .................................................................................................. 130
14.16.3 Sector-specific multipliers .............................................................................. 130
14.17 Luxemburg ................................................................................................................ 132
14.17.1 Gross value added ........................................................................................ 132
14.17.2 Employment .................................................................................................. 133
14.17.3 Sector-specific multipliers .............................................................................. 133
14.18 Malta ......................................................................................................................... 135
14.18.1 Gross value added ........................................................................................ 135
14.18.2 Employment .................................................................................................. 136
14.18.3 Sector-specific multipliers .............................................................................. 136
14.19 The Netherlands ....................................................................................................... 138
14.19.1 Gross value added ........................................................................................ 138
14.19.2 Employment .................................................................................................. 139
14.19.3 Sector-specific multipliers .............................................................................. 139
14.20 Poland....................................................................................................................... 141
14.20.1 Gross value added ........................................................................................ 141
14.20.2 Employment .................................................................................................. 142
14.20.3 Sector-specific multipliers .............................................................................. 142
14.21 Portugal .................................................................................................................... 144
14.21.1 Gross value added ........................................................................................ 144
14.21.2 Employment .................................................................................................. 145
14.21.3 Sector-specific multipliers .............................................................................. 145
14.22 Romania ................................................................................................................... 147
14.22.1 Gross value added ........................................................................................ 147
14.22.2 Employment .................................................................................................. 148
14.22.3 Sector-specific multipliers .............................................................................. 148
14.23 Slovakia .................................................................................................................... 150
14.23.1 Gross value added ........................................................................................ 150
14.23.2 Employment .................................................................................................. 151
14.23.3 Sector-specific multipliers .............................................................................. 151
14.24 Slovenia .................................................................................................................... 153
14.24.1 Gross value added ........................................................................................ 153
14.24.2 Employment .................................................................................................. 154
14.24.3 Sector-specific multipliers .............................................................................. 154
14.25 Spain......................................................................................................................... 156
14.25.1 Gross value added ........................................................................................ 156
14.25.2 Employment .................................................................................................. 157
14.25.3 Sector-specific multipliers .............................................................................. 157
14.26 Sweden ..................................................................................................................... 159
14.26.1 Gross value added ........................................................................................ 159
14.26.2 Employment .................................................................................................. 160
14.26.3 Sector-specific multipliers .............................................................................. 160
14.27 United Kingdom ........................................................................................................ 162
14.27.1 Gross value added ........................................................................................ 162
14.27.2 Employment .................................................................................................. 163
14.27.3 Sector-specific multipliers .............................................................................. 163
15 List of Figures 165
16 List of Tables 169
17 Bibliography 171
17.1 Methods and Data: ..................................................................................................... 171
17.2 Satellite Accounts and Sport Economics .................................................................... 174
17.3 Sources of Statistic: .................................................................................................... 175
Annex: National Data Sheets 176
Study on the Contribution of Sport to Economic Growth and Employment - 1 -
1 Executive Summary
The Study on the Contribution of Sport to Economic Growth and Employment in the
European Union was carried out in 2011-2012, based on data collection in all 27 EU Member
States focussing on sport as an economic activity. The methodology utilised a specific
adaptation of the National Accounts of the Member States, using these accounts to make a
Multiregional Input-Output Table: Sport (MRIOT:S) which is based on 27 national Input-
Output Tables: Sport. This means that the chosen approach is consistent with the National
Accounts on the one hand and intra-EU trade on the other.
National Accounts are the main reference point for economic policy making on the national
macro level and are normally maintained by the statistical office of a country. A satellite
account is an extension of the standard national account system. A Sport Satellite Account
(SSA) – being the core of an Input-Output Table: Sport – filters the National Accounts for
sport-relevant activities to extract all sport-related figures while maintaining the structure of
the National Accounts. The instrument of SSAs permits all sport-related economic activities
to show up explicitly, rather than keeping them concealed, in deeply disaggregated (low-
level) classifications of the National Accounts.
1
Hence one of the results of the study is an Input-Output Table: Sport for each Member State.
Most of these Input-Output Tables: Sport are proxy tables and should therefore be used with
caution. They were designed for EU-wide analysis and cannot replace Input-Output Tables:
Sport produced at national level. Noticeably, such national SSAs and Input-Output Tables:
Sport, of direct relevance for this study, have already been developed in several EU Member
States based on the statistical definition of sport agreed by the EU Working Group on Sport
and Economics in 2007 ("Vilnius Definition of sport"). To further improve the data quality, all
Member States are strongly encouraged to produce a fully-fledged national Input-Output
Table: Sport. Once this is done by a country, it should then replace the remaining proxy Input-
Output Table: Sport in the MRIOT:S.
The importance of such a fully-fledged national Input-Output Table: Sport, however,
surpasses the mere use within the MRIOT:S. The latter was designed and created in such a
way that it serves EU-wide policy analyses while the national results are secondary. A
country that has a fully-fledged national Input-Output Table: Sport, in contrast, can evaluate
national policies in much more detail. Distinctive features can be incorporated quickly which
are not so easily reflected in the EU-wide MRIOT:S with its need for a common standard. The
already existing fully-fledged national Input-Output Table: Sport can serve as examples as
they are in widespread and intense use by the respective policy makers.
Two central goals of this study are to establish a consistent data base to serve as a
reference point for subsequent analyses, and to generate a comprehensive estimate of the
magnitude of sport-related value added and employment in Europe. As such, the work will
1
The name Sport Satellite Account is derived from the tabular presentation of the account (i.e. as a matrix). In this format, the
sport-related rows and columns wrap around the non-sport part, circling around it like a satellite.
Study on the Contribution of Sport to Economic Growth and Employment - 2 -
contribute to EU policy and its strategic goals in the Europe 2020 context. It was found that
sport overall is labour-intensive. Growing the sport-related economy thus leads to a more
than proportional growth of employment. In addition, a number of promising sectors were
identified which are currently comparatively small while showing strong connections to the
rest of the economy. Their below-average size indicates growth potential while at the same
time they send out strong impulses to many other sectors.
The main study findings can be summarised as follows:
Sport's share in total gross value added
The Vilnius Definition of sport distinguishes between a statistical, a narrow and a broad
definition of sport as follows:
Statistical Definition: comprised of NACE 92.6 Rev. 1.1 ("Sporting activities", the only
part of the sport sector having its own NACE category).
Narrow Definition: all activities which are inputs to sport (i.e. all goods and services
which are necessary for doing sport) plus the Statistical Definition.
Broad Definition: all activities which require sport as an input (i.e. all goods and
services which are related to a sport activity but without being necessary for doing
sport) plus the Narrow Definition.
The results of the study show that the share of sport-related gross value added of total EU
gross value added is 1.13% for the narrow definition and 1.76% for the broad definition of
sport. The share of what is generally known as the organised sport sector (sport clubs, public
sport venues, sport event organisers) is reflected in the statistical definition. The share of
gross value added according to the statistical definition is 0.28%. Therefore the real share of
sport in terms of production and income is about six times as high as reported in official
statistics.
In 2005, sport-related gross value added (direct effects) amounted to 112.18 bn Euro
according to the narrow definition and 173.86 bn Euro with respect to the broad definition.
For the statistical definition of sport it was 28.16 bn Euro.
The direct effects of sport, combined with its multiplier (indirect and induced) effects, added
up to 2.98% (294.36 bn Euro) of overall gross value added in the EU.
The highest sport-related value added was found in the sector Recreational, cultural and
sporting services, followed by Education services (second), and Hotel and restaurant
services (third).
The average gross value added of the statistical definition shows a broad division between
high income Western European Member States and lower income Eastern states. In
absolute terms, the gross value added per capita in the Eastern Member States is around
5 Euro to 10 Euro per capita for this part of the sport industry, while in the higher income
Study on the Contribution of Sport to Economic Growth and Employment - 3 -
states, this amount is around 50 Euro to 100 Euro per capita. Of course it could be expected
that richer countries spend more on sport than poorer countries, but this is true not only in an
absolute sense but also in a relative sense: the share of gross value added of sport is lower
in low income EU Member States compared to high income states. On a cross-section basis,
the national income elasticity of sports is 1.14, which means that if national income rises by
1%, the gross value added related to sport rises by 1.14%.
From an analysis of specific sectors that are important in enhancing the size of the sport
industry, three sectors stand out:
Tourism
Fitness and the media
Education
- Tourism: for some countries, a substantial contribution to the sport industry share is made
by the hotel and restaurant sector. This is especially true for Austria, Germany, Italy, and
Sweden, which are important destinations for active sports holidays. In Germany and
Sweden a large part is probably generated by domestic tourism, but for the other countries
international tourism is a major source of income. As these countries have a specific supply
advantage and the elasticity of income for sports consumption is above 1, their sports
economic base is likely to be strengthened when European economies grow.
- Fitness and the media: in some North-Western European countries a large part of the total
demand for sport activities is satisfied by commercial sports suppliers such as fitness clubs.
This is true in Sweden and the Netherlands. Another demand-related issue is the strength of
professional football and the role of the media in the UK, where pay television for football
matches has grown into a significant economic activity.
- Education: in almost all countries sport education is an important part of the total sport
economy. However, there are a few exceptional countries. These are Denmark, Estonia and
Latvia which have exceptionally high shares of sport education in sport-related gross value
added. These Member States seem to attach a high value to sport in an educational context.
Employment effects
For the EU as a whole, the contribution of sport-related employment to total employment is
2.12%. In absolute terms this is equal to 4.46 m employees. This is above the sport-related
share in gross value added (1.76%), which indicates that sport is labour-intensive.
The largest number of sport-related jobs can be found in Germany, which has 1.15 m sport-
related jobs or nearly 27% of all sport-related jobs in the EU. The runner-up is the UK, with
more than 610,000, followed by France with more than 410,000 jobs in sport.
Study on the Contribution of Sport to Economic Growth and Employment - 4 -
Sectoral interrelatedness
Multipliers are measures of the degree to which the sectors in an economy are interrelated.
Sectoral multipliers measure the impact in total economic activity generated by a one-unit
change in one sector. The value of a sectoral multiplier is determined by the links on the one
hand and the leakages on the other hand within an economic system. Sectors with strong
relations to the rest of the domestic economy and few imports report high multipliers. If an
impulse to a sector is hardly transferred to other branches or leaves the country (imports of
intermediate goods), the multiplier barely exceeds its minimum value of 1. The study shows
that smaller Member States have significantly lower mean sectoral multipliers than larger
Member States.
The highest multipliers are found in the construction branch and in sectors related to tourism
(hotels, air transport). Education has a relatively low multiplier as it requires only a few
intermediate goods compared to its wages, but it is an important sector in the whole network
of value creation in sports, especially in the Nordic and Baltic countries.
Sectoral growth potentials
The study analyses several sectors for their growth potential and differences between
countries are discussed. A general pattern of sport production can be observed in the sense
that sport services are predominantly produced for the domestic market while sportswear is
predominantly imported. For sports durables internal EU specialisation can be found.
There are three sectors that play a special role in almost all countries: food products and
beverages; construction; and supporting and auxiliary transport services including travel
agency services. These sectors have strong linkages to the rest of the economy and are
therefore strategically important.
The most important policy implications to be drawn from the outcomes of this study are listed
hereafter.
Policy Implication 1: Sport is an important economic sector
The study shows that sport is an important economic sector in the EU, with a share in the
national economies which is comparable to agriculture, forestry and fishing combined.
Moreover, its share is expected to rise in the future.
Policy Implication 2: Sport represents a labour-intensive growth industry
Sport is a relatively labour-intensive industry. This means that the expected growth in the
sport industry is likely to lead to additional employment, with sport's share of total
employment being higher than its share of value added. The sport sector can thus contribute
to fulfilling the Europe 2020 goals.
Policy Implication 3: Sport can foster convergence across EU Member States
Study on the Contribution of Sport to Economic Growth and Employment - 5 -
Sport has the economic characteristics of a luxury good, with an income elasticity above 1.
This implies that sport production and services will grow faster in lower income countries
than in higher income countries. It thus contributes to the economic convergence of Member
States and can help reduce economic imbalances.
Policy Implications 4: Sport has growth-enhancing specialisation advantages
Sport products and services can be found in many other sectors, e.g. in tourism, insurance,
legal consultancy, and many more. This means that sport can help specific niche sectors to
develop, depending on the characteristics of sport demand and supply in a specific country.
Examples of such specialisation patterns can be observed in the UK (professional sports and
betting), in Austria (tourism) and in Northern Europe (education). Further study and
identification of these patterns may help to enhance the sector’s contribution to the Europe
2020 Strategy.
Study on the Contribution of Sport to Economic Growth and Employment - 6 -
Annex: Key indicators per Member State
As explained above, the figures in this table should be seen as proxies produced for the sake
of EU-wide analysis unless stated otherwise. While they represent a first set of indicative
figures produced for all EU Member States according to a single methodology, they should
be used with caution. Figures for Austria, Cyprus, Poland and the UK reflect those countries'
Sport Satellite Accounts, not necessarily based on 2005 as the other values do.
Table 1: Sport related gross value added and employment. All values correspond to
the Broad Definition and contain direct effects only
Value added
Employment
in million Euro
in heads
10,730
242,968
3,043
71,416
223
55,843
310
7,600
1,062
89,119
3,719
69,287
162
15,686
2,654
74,209
21,607
416,537
46,677
1,146,234
2,518
70,878
778
55,577
2,377
40,532
15,599
329,860
136
17,077
161
16,178
697
19,331
93
3,070
5,828
141,896
5,300
225,500
1,534
72,101
790
161,248
472
49,910
521
28,576
10,407
336,177
2,360
73,266
39,860
632,400
Source: SportsEconAustria, Sport Industry Research Centre at Sheffield Hallam University, Statistical
Service of the Republic of Cyprus, Meerwaarde Sport en Economie, Ministry of Sport and Tourism of
the Republic of Poland.
2
According to the national Input-Output-Table Sport of 2005.
3
According to the national Input-Output-Table Sport of 2004. Data of 2005 were used in the calculations.
4
According to the national Input-Output-Table Sport of 2006. Data of 2005 were used in the calculations.
Study on the Contribution of Sport to Economic Growth and Employment - 7 -
2 Introduction
This study assesses the macroeconomic importance of sport in the EU-27, in particular its
growth and employment potential, thereby making a contribution to assess the sector’s role
with respect to the Europe 2020 strategy.
The European Commission has formulated the Europe 2020 strategy to meet future
challenges. It is the “EU’s growth strategy for the coming decade”.
5
Part of this strategy is to
identify specific economic risks and opportunities within the EU. As a result of the Lisbon
Treaty “The Union shall have competence to carry out actions to support, coordinate or
supplement the actions of the Member States. The areas of such action shall, at European
level, be: […] (e) education, vocational training, youth and sport”
6
. To illustrate the role of
sport with regard to “Europe 2020”, knowledge about the specific characteristics of sport
economics and its impact on Europe’s economy is necessary. Although there is some data
available on this, the Commission’s 2007 White Paper on Sport noted the lack of
comprehensive and comparable EU-wide information in order to develop evidence-based
policies.
From its inception in 2006, the EU Working Group "Sport & Economics" has developed a
harmonised definition of sport (“the Vilnius Definition of sport”) and a common methodology
to measure the economic importance of sport (the “Sport Satellite Account” – SSA). A
complete picture of the economic importance of sport for the EU as a whole through the
aggregation of 27 national sport satellite accounts can only be expected in the longer term,
since this approach is a complex and time-consuming task and therefore faces national
budgetary and human resource constraints.
Meanwhile, a macro-economic approach was developed alongside national efforts to
implement sport satellite accounts to get methodologically sound data based on the Vilnius
Definition of sport. This can enhance the overview of the total EU sport economy and
overcome the partial scope of national satellite accounts. It can also stimulate
methodological discussion among Member States, which help to raise the quality and the
comparability of national estimates of SSAs. For these reasons, this study was undertaken.
The study focused on the following research questions:
What is the economic importance of sport in terms of gross value added?
What is the economic importance of sport in terms of employment?
What similarities and differences can be observed between Member States for these
variables and how can these be explained?
What are national strengths and weaknesses?
Where are the growth potentials?
5
Source: http://ec.europa.eu/europe2020/index_en.htm, found on 5 March 2012.
6
Treaty of Lisbon, Article 2 E.
Study on the Contribution of Sport to Economic Growth and Employment - 8 -
Noticeably, four members of the EU Working Group “Sport & Economics” and the Expert
Group “Sport Statistics” – Austria, Cyprus, Poland and the United Kingdom – have already
finished their work on national SSAs which formed a valuable basis for this study.
The report is divided into four large parts:
The introductory chapters:
o Input-Output Analysis in general as well as Satellite Accounts are discussed
in Chapter 3.
o The economic definition of sport is explained in Chapter 4
Descriptions of background theory and practical implementation of the model
and the surrounding calculations:
o At first, Multiregional Input-Output Analysis is discussed (Chapter 5), with the
focus on how to connect stand-alone regional Input-Output Tables.
o The different data sources are described in Chapter 6.
o Several topics worth mentioning are covered in Chapter 7.
Interpretation of the results: EU-wide analyses of the sport-related economy are
discussed first, such as
o employment (Chapter 8),
o strengths and weaknesses (Chapter 9),
o growth potentials (Chapter 10),
o key sectors (Chapter 11), and
o the range of products (Chapter 12).
This is followed by the description of macroeconomic effects on
o the European Union in total (Chapter 13) as well as on
o all single Member States (Chapter 14).
An annex containing national data sheets forms the end of the report.
Study on the Contribution of Sport to Economic Growth and Employment - 9 -
3 Developing Sport Satellite Account Systems in Europe
3.1 Satellite systems in the National Accounts
For several economic and societal questions or problems it is necessary to modify the clarity
and presentation of the existing statistical data in order to enable better data analysis and
facilitate further calculations.
Specialized tables (more detailed Input-Output Tables) have been developed to cover certain
areas of the economy. These extensions of the national accounts thematically “orbit” around
the basic tables – that is why they are called “satellite systems” or “satellite accounts”.
Haslinger
7
provides a general definition of a satellite account system: "A Satellite Account
System is a consistent system of monetary and non-monetary measurement categories
made at regular intervals. These should verify conditions and procedures – correlated with
important societal requests – in detail."
Stahmer
8
introduces a different definition by stating that satellite systems are specific data
systems, which are designed to answer specific economic questions but have a close
connection to the national accounts and hence enable detailed economic analysis.
A “sport satellite account system” includes all economic effects (gross domestic production,
value-added and employment) due to any sport-related activity generated by the various
economic sectors and shows them consistent with the terms of the national accounts.
Accordingly a “sport satellite account system” provides all the economic effects linked to
sport-related activities (which are not included in a proper and detailed form in the national
accounts) in a consistent form.
A complete economic analysis of sport also includes the sport-related indirect and induced
effects caused by the direct sport-related activities. These indirect effects can be sub-divided
into:
- Multiplier effects, which were generated by the demand for intermediate inputs of the
sport-related sectors, for example showers for swimming pools or leather for saddles,
- changes in the capital stock by investments into the sport sectors, for example
special cutting machinery to produce sporting boat hulls, and
- income effects, that arise because sport-related earnings enable higher consumer
expenditures by those working in the sport industry.
7
Haslinger (1988), S. 66
8
Stahmer (1991) S. 45
Study on the Contribution of Sport to Economic Growth and Employment - 10 -
These indirect economic effects again lead to multiplier effects and higher earnings. The
process thus repeats itself. To quantify the total economic impact of sport it is necessary to
sum up the direct effects and the multiplier effects.
Due to the complete compatibility of the satellite account with the national accounts, a
comparison of important macroeconomic aggregates of the sport sector (e.g. gross value-
added, employment) with macroeconomic aggregates of other economic sectors is made
possible.
3.2 An Input-Output Table: Sport
To establish a sports satellite account in the EU-27 countries and to use them in order to
analyse the effects of sport on national economies, it is useful to combine them with the
particular national Input-Output Tables, leading to an “Input-Output Table: Sport”.
Input-Output analysis is one of the most known and used tools of economic analysis. Input-
Output models are systems of linear equations, where each of them describes a different
product allocation of the economy. An Input-Output Table describes the structure of the
economy, and the various relations between the different sectors of an economy, and helps
to quantify the multiplier effects for the national economy.
Implementation of a sport satellite account and combination with the national Input-Output
Table results in a methodological tool that shows the sport-related activities and their various
links with the economy. Hence a sport satellite account is a means to answer important
(sport-related) economic questions within European society in a scientific way.
3.3 Analysis of the Economic Effects of Sport
On the basis of the Input-Output Table: Sport, the sport-related impact on the national
economy can be determined. These further calculations result in sport-related gross National
Product and sport-related employment – as well as the direct and indirect sport-related
effects (multiplier effects) on the value-added, the purchasing power and the labour market.
3.3.1 Calculation of the Value-Added Effects of Sport
The value-added of a sector is the difference between total production and the inputs needed
to generate this production. To quantify these direct value-added effects, information on
income and expenditure in sport, as well as investment, is necessary. By subtracting the
payments for the inputs from the expenditures, the direct value-added effect is obtained. By
applying the appropriate multipliers, the direct and indirect value-added effects are obtained.
3.3.2 Calculation of the Purchasing Power Effects of Sports
For the quantification of the direct effects on purchasing power, the expenditures for
investments and material expenditures as well as effective net incomes are needed. The
effective net income is derived according to the following scheme:
Study on the Contribution of Sport to Economic Growth and Employment - 11 -
Table 2: Calculation Scheme for Effective Income
Staff costs
-
Expenditures (taxes, insurance)
Total net income
-
Savings
-
Spending abroad
Effective net income
Source: SpEA, 2006.
From total staff costs, all expenditures which do not reach the employee (e.g. income tax) are
subtracted to give total net income. Savings are also subtracted from the total. Finally all
spending abroad is subtracted to give effective net income.
3.3.3 Calculation of the Employment Effects of Sport
Three different methods can be used in order to calculate the direct employment effects:
Method 1 uses the average personnel expenditure per year and per person to
calculate the effects.
Method 2 uses a common “employment structure” of the sector proportional to the
value-added.
Method 3 is based on labour productivity. The marginal labour productivity is defined
as the ratio of the change of productivity to the change of labour input (either number
of employees or working hours). The marginal labour productivity indicates the
change of productivity per additional employee. The inverse ratio, the so-called work-
coefficient, is a measure for the number of persons employed in the production
process.
For an extensive evaluation of the employment effects, further factors have to be considered.
For example, the occupation structure is an important issue. The occupation elasticity is
usually larger for workers than for employees, so that an expansion of the construction
activities will lead to a significant increase in the number of workers. A significant increase in
the number of employees is however not to be expected. Another important factor is the
extent of capacity utilization in the appropriate sectors. The full employment effect is only
realised at 100 per cent capacity utilization and an appropriate increase in the capacities due
to the projected extra demand. Beyond that, the tendency exists to compensate a non-
permanent demand by overtime and extra shifts rather than by an additional employment of
workers.
3.3.4 Calculation of Multiplier Effects
For each final expenditure multiplier effects are assumed, since each business needs
unfinished-goods as well as raw materials and supplies of other sectors for the production of
Study on the Contribution of Sport to Economic Growth and Employment - 12 -
its products and/or services. Multipliers show how much of the production of other sectors is
needed to produce a certain good. For example, production of a sports car requires seats,
which come from a different sector. These seats again need textiles, thus affecting a third
sector and so on. The size of the multipliers primarily depends on the structure of the
“economic linkage” of the source sector to the remaining sectors. That means it depends on
how much is received from and delivered to all sectors directly as well as indirectly. The more
the sectors are interlinked, the higher are the multipliers, usually ranging from 1.0 to a little
more than 2.0. Applying multipliers on the direct effects generates the indirect effects. If for
example a football stadium costs 30 m Euro (direct effect) and construction sector reports a
multiplier of 1.8, the indirect effect will be (1.8 - 1.0) x 30, that is 24 m Euro.
It has to be considered that national businesses as well as foreign countries are involved in
the supply chain, but primary effects for a country depend only on import-adjusted values.
Study on the Contribution of Sport to Economic Growth and Employment - 13 -
4 Definition of Sport in the Economic Sense
The sport economy as a whole is not a separate statistically measured sector, but is part of
various other industries and economic sectors. National statistical offices measure sport
explicitly only by the category “operation of sports facilities” in NACE 92.6 where NACE
stands for “Nomenclature statistique des activités économiques dans la Communauté
européenne” and is a classification of industries according to their economic activity. Other
categories such as the production of sport articles, sport retail, and sport tourism are ignored
in the statistical definition.
From an economic point of view, sport is an activity which has repercussions in many
different areas of the economy. In Table 3 some important categories are listed as examples.
Table 3: Overview of some sport-related activities and products with economic impact
Consumer Expenditure
Goods and Services Conditional on Doing Sport
Veterinarian
Dietary Supplements
Sport Bets
Health
Services
Hotels, Restaurants
(sport tourism)
TV
Broadcasts
Doing Sport (According to the Statistical Definition)
Stadiums
Swimming Pools
Professional
sports
Goods and Services Necessary to Do Sport
Racing
Horses
Sport Shoes and
Clothes
Sport
Weapons
School
Education
Sport Cars,
Motorbikes
Fitness
Centres
Watches,
Clocks
Sailing Equipment
Dancing
Schools
Source: "Sport Satellite Accounts – A European Project: New Results" leaflet published by
the European Commission (April 2011).
The question arises as to how the economic importance of these sport-related activities can
be measured. For this purpose the EU Working Group "Sport & Economics" developed and
agreed upon the Vilnius Definition of sport.
Study on the Contribution of Sport to Economic Growth and Employment - 14 -
Economic
activities
Products Goods
World
level
ISIC CPC HS SITC
EU level NACE CPA PRODCOM CN
National
level
National
versions
of NACE
National
versions
of CPA
National
versions of
PRODCOM
Is the reference classification. Classifications are linked by the structure.
Is the reference classification. Classifications are linked by conversion tables.
Classifications are linked by conversion tables.
The Vilnius Definition of sport relates sport activities to specific industries, as they are
registered within the framework of the national accounts.
9
For most of our purposes the NACE categories are still too broad, because NACE refers to
specific companies (or production units); a better targeted measure is products instead of
production units called CPA. CPA is the abbreviation for “Classification of Products by
Activity” and is a classification of products. NACE and CPA are part of an international
classification system of industries and products. The relationship of these classifications is
clarified below.
10
Table 4: Scheme of Classifications
Source: replicated from circa.europa.eu: NACE revision 2.
The sport sector as such is not a NACE category, but NACE category 92.6 "Sporting
Activities" refers to a small part of the sport sector. This category includes sport facilities such
as stadiums, swimming pools, sport clubs and professional sport organisations. The EU
Working Group "Sport & Economics" has labelled this category "the statistical definition of
sport”. In Table 3 this is labelled ‘Doing Sport’. This can be considered to be the sport sector
from a traditional point of view. For example, in this statistical definition neither fitness
centres nor sport education are included.
9
The following text is derived from Meerwaarde Sports and Economics/Spea (2008).
10
The meaning of the other abbreviations fall outside the scope of this report, see:
http://circa.europa.eu/irc/dsis/nacecpacon/info/data/en/2007%20introduction.htm
Study on the Contribution of Sport to Economic Growth and Employment - 15 -
Limiting sport to this NACE category is therefore quite arbitrary from an economic point of
view. Another, conceptually better, definition of the economic sport sector enlarges the
statistical definition of sport by all industries which produce goods that are necessary to
perform sport. Besides sport facilities, this classification includes, for example, manufacturing
of sport shoes and tennis rackets. The latter definition is referred to as the “narrow definition
of sport”. This definition is depicted in the lower part of Table 3.
In addition, the so-called “broad definition of sport” includes not only the statistical definition
and the narrow definition, but also those industries for which sport is an important input for
their production processes, e.g. television broadcasting or hotels accommodating guests
doing sport (sailors, skiers, hikers, etc.), as depicted in the upper part of Table 3.
Besides a list of all products which are considered to be sport-related, the Vilnius Definition of
sport includes several rules, which guide the classification and interpretation of sport
products.
Table 5: Vilnius Definition Set of Rules
1
Goods and services which are part of the statistical and narrow definitions of sport are
also part of the broader definition of sport. The broader definition of sport will be the
focus of the EU Working Group "Sport & Economics".
2
Multipurpose infrastructure and multipurpose durable goods which are not part of the
statistical definition of sport (NACE 92.6) will be excluded, e.g. roads, cars, TV sets,
play stations. Dedicated infrastructure (e.g. NACE 45.23.21/45.23.22) will be included.
3
To avoid double counting and to ensure comprehensiveness, correspondence will be
established between the manufacturing sections and the trade/retailing sections
(categories 51-52) of the table. Sections 51 and 52 are only relevant in terms of trade
margins.
4
Data will be collected on the basis of a common agreement on which NACE and CPA
categories to include. However, to take account of the country-specific sport landscape,
additional CPA categories may exceptionally be included over and above the basic list
agreed in the EU Working Group "Sport & Economics".
5
In general, only final expenditure (incl. capital expenditure) will be taken into account,
and not intermediate expenditure. Reference will be made to intermediate demand only
if it constitutes sizeable input for professional sport. In a similar way, industrial services,
where they are not sport-specific, will not be considered.
Source: Vilnius Definition of sport.
Study on the Contribution of Sport to Economic Growth and Employment - 16 -
The Vilnius Definition of sport is thus an overview of all product groups which are included in
the sport satellite account. It is not so much a definition of sport itself but a classification of
relevant product groups.
Study on the Contribution of Sport to Economic Growth and Employment - 17 -
5 Set up of a Multiregional Input-Output Table: Sport
The basic approach to calculating EU-wide economic effects of sport is to first enlarge the
national Input-Output Tables (IOT) by sport-related sectors. For this, all sport-content will be
extracted from the original sectors and form additional sectors. For example, sector 01,
agriculture, will be divided into “non-sport 01” (wheat, apples…) and “sport-related 01”
(racing horses, football lawn…). The sum of these new sectors must equal the original sector
01. Figure 1 and Figure 2 visualise this enlargement process.
These enlarged national IOTs will be called Input-Output Tables: Sport (IOTs:S). As these 27
IOTs:S are connected by intra-EU foreign trade, they can be linked together in a Multiregional
Input-Output Table: Sport (MRIOT:S) as depicted in Figure 7.
Calculating the links between the regions is a complex economic task for which several
methods were proposed. The three most important ones are:
The Interregional Input-Output Model (IRIO) by Isard (Isard (1953));
the Multiregional Input-Output Model (MRIO) by Chenery and Moses (Moses,1955);
the Balanced Regional Model by Leontief (Leontief,1963).
The major advantage of Isard’s model is that it is able to cover the whole variety of effects of
each sector and each region. This benefit however leads to the big disadvantage of the
model: the enormous effort of data collection. The number of input-output flows is determined
by (m×n)
2
with "m" being the number of regions and "n" the number of sectors. Even in a
small model with five regions and ten sectors, 2,500 data have to be determined. For Europe
an interregional Input-Output model would (as a minimum) cover 27 regions and 17 sectors,
that is (27×17)
2
or more than 210,000 data. As intended the study should not be based on
sectors but on the more detailed categories so that the amount of data necessarily increases
to (27×59)
2
or more than 2,500,000 data. With the sport-relevant extensions (sport satellite
account) of the national Input-Output Tables the interregional Input-Output Model would grow
to a (27×94)
2
matrix or around 6,400,000 data.
For this reason efforts have been made to develop multiregional models with less complexity,
like the one developed by Chenery and Moses. The MRIO, which has been steadily
improved and refined in the last 15 years, covers in its most detailed version for the United
States 51 regions and 79 sectors. Formally the MRIO resembles the model of Isard, but with
regard to the content it differs in that it implies a stability hypothesis. The table itself is set up
in two steps: as a first step the intraregional tables are created (one table for each region), in
a second step the import and export flows are collected.
The model is extendable to any number of regions and the big advantage is that the
complexity of the table stays much lower than in Isard’s model. The amount of data
necessary to fill the table is determined by n×m
2
+m×n
2
(n intermediate goods matrices being
m x m large plus import/export data for all m goods between the n x n countries). Thus the
example above (27 regions and 94 subsections) requires a little more than 300,000 data.
That is less than 5% of the data necessary in Isard’s model. Because of this simplification it
Study on the Contribution of Sport to Economic Growth and Employment - 18 -
was decided to use the MRIO model of Chenery and Moses in the context of this study.
However it is not meant to be used for country comparison.
The structure of the Leontief model corresponds to the Isard model but the interpretation is
completely different and is more complicated, using different definitions of markets. Because
empirical tests showed that this model is only useable for a limited number of regions and
sectors and should not be used for longer periods (not longer than 3 or 5 years) it is not
applicable for this study and therefore will not be discussed in more detail.
5.1 National Input-Output Tables
The starting point for calculating the MRIOT:S is the collection of the 27 national IOTs which
serve as a basis for the 27 IOTs:S. Four of them were already available (Austria, Cyprus,
Poland, and UK) and after adapting they could be used in this study. For the remaining 23
countries, proxy-IOTs:S had to be computed. Technically speaking, these proxy-IOTs:S are
perfectly comparable to the four fully-fledged IOTs:S. The difference is in the economic
research performed to calculate them. National researchers focusing on their country alone
are supposed to have more time and better connections to key national data experts which
are particularly important for this type work. In contrast to this, computing proxy-IOTs:S is
comparable to running a remote analysis of a country’s economy. The result is good enough
for running EU-wide analyses, but should not be used on a single country basis. It is
therefore recommended that whenever a fully-fledged national IOT:S is finished by the
country’s experts, it should replace the proxy-IOT:S in the MRIOT:S.
Almost all EU-27 countries have an Input-Output Table or at least supply and use tables (see
below for the conversion process). The national IOTs correspond to Figure 1. The rows
correspond to the use of goods. Therefore one can read off the first row how much of Good 1
is used to produce Good 1, Good 2, and Good 3. This is the “intermediated use” of the good,
as it is used within the supply chains of the economy. Consumption of final goods are
reported the upper right quadrant. The table shows how much of Good 1 (and the other
goods below) is consumed by private households, the state, and how much is invested (or
put in stock etc.). The last possible use is exports. The sum of intermediate use, consumption
and exports equals total demand of a good. This is reported in the far right-hand column.
Study on the Contribution of Sport to Economic Growth and Employment - 19 -
Output Intermed. Goods
Consumption
Good 1
Good 2
Good 3
Private Consumption
Public Consumption
Investments
Exports
Good 1
Good 2
Good 3
Total
Taxes less subsidies
Total Interm. Consumpt.
Cons. fixed Cap.
Taxes
Wages
Profits
Gross Value Added
Production Value
Imports
Total Supply
Total Demand
Figure 1: Basic Input-Output Table for the EU-27
Source: SpEA, 2012.
The columns in the left part of the IOT refer to the production of the goods. Thus in the upper
part of the first column one can see how much of each good is necessary to produce Good 1.
After taxes are added and subsidies subtracted, total intermediate consumption can be read
off the table. These were the inputs to production. To transform these inputs into output,
capital is required. Gross value added (GVA) is the sum of all capital costs (machinery,
wages, profits, plus taxes). The sum of gross value added plus total intermediate
consumption equals domestic production (“production value”, PV) of Good 1. To find out how
much of each good is supplied and thus available in a country, add imports to domestic
production.
As each good which is produced has to be used in one way or another the entries in total
demand (right-most column) must be equal to those in total supply (lowest row).
For example, the Austrian Input-Output Table for 2005 shows that goods and services of CPA
01, “Products of agriculture, hunting and related services”, worth 6.395 bn Euro were
supplied and demanded. On the supply side,
domestic inputs worth 2.754 bn Euro were used (column-wise sum of the
intermediate goods matrix),
58 bn Euro taxes less subsidies were paid,
a gross value added of 1.927 bn Euro was achieved, and
further goods and services worth 1.657 bn Euro were imported.
The sum of the above values equals 6.395 bn Euro
Study on the Contribution of Sport to Economic Growth and Employment - 20 -
Demand is split as follows:
4.171 bn Euro were used as inputs,
private consumption equalled 1.430 bn Euro,
other consumption (including public) 332 bn Euro, and
goods worth 462 bn Euro were exported.
The sum of these items also equals 6.395 bn Euro
In the next step, these IOTs have to be transformed into IOTs:S by splitting those sectors
which contain sport-related data into two parts. Therefore these sectors have to be identified.
Figure 2 shows the scheme of such an IOT:S. The shaded parts are sport-related, with the
dark shape of the intermediate goods matrix surrounding the non-sport part. Some see it as
“circling around” the non-sport part, thus calling it the “satellite account”.
According to the Vilnius Definition of sport the national Input-Output Tables are going to be
extended by the 35 sport-specific subsections. Therefore each good with sport-related
content is going to be split into a sport-related part (e.g. “15 S“ with “S“ being the sport
reference) and into a non-sport-related part (subsection total minus sport-related part). The
goods with sport-related content are: 01, 15, 17, 18, 19, 22, 23, 24, 25, 28, 29, 33, 34, 35,
36, 45, 50, 51, 52, 55, 60, 61, 62, 63, 64, 65, 66, 71, 73, 74, 75, 80, 85, 92, and 93. Some
CPA categories (e.g. CPA 02) do not contain sport and are left untouched. Thus there are in
principle three different types of categories: those which contain sport-related elements in the
original IOT, but appear in the IOT:S without these sport-related elements; those which never
contained sport-related elements; and the purely sport-related categories.
Study on the Contribution of Sport to Economic Growth and Employment - 21 -
Output Intermed. Goods Consumption
Good 1 N
Good 2 N
Good 3
Good 1 S
Good 2 S
Private Consumption
Public Consumption
Investments
Exports
Good 1 N
Good 2 N
Good 3
Good 1 S
Good 2 S
Total
Taxes less subsidies
Total Interm. Consumpt.
Cons. fixed Cap.
Taxes
Wages
Profits
Gross Value Added
Production Value
Imports
Total Supply
Total Demand
This IOT:S looks as follows (shadowed part of the table refers to the sport satellite account):
Figure 2: Extended Input-Output Table for the EU-27
Source: SpEA, 2011.
Table 6 shows the availability of Input-Output Tables at Eurostat for the purpose of the study
in the third column-triplet. As can be seen, most of the 27 EU Member States report Input-
Output Tables as well as import tables for the year 2005. Therefore this year was chosen as
the basis for our calculations. However, there are a few missing countries and Latvia has
Input-Output Tables for 1998 only. These earlier data can be updated using economic data of
2005. Adjustment took place through growth of gross production and gross value added by
leaving technical coefficients constant, which is a valid approach as these coefficients’
stability is empirically grounded and a centre piece of Leontief’s theory. Technology changes
occur much slower than changes in demand, thus the structure of the intermediate goods
matrix remains stable even over a time span of ten or more years. It is therefore possible to
update the last available Input-Output Table into a 2005 Input-Output Table.
Study on the Contribution of Sport to Economic Growth and Employment - 22 -
2005 2006 2007 2005 2006 2007 2005 2006 2007 2005 2006 2007
Austria √ √ √ √ √ √ √ √
Belgium √ √ √ √ √ √ √ √
Bulgaria √ √
Cyprus √ √ √ √ √ √
Czech Republic √ √ √ √ √ √ √ √ √
Denmark √ √ √ √ √ √ √ √ √ √ √ √
Estonia √ √ √ √ √ √ √ √
Finland √ √ √ √ √ √ √ √ √ √ √ √
France √ √ √ √ √ √ √ √ √ √ √ √
Germany √ √ √ √ √ √ √ √ √ √ √ √
Greece √ √ √ √ √ √ √ √
Hungary √ √ √ √ √ √ √ √
Ireland √ √ √ √ √ √ √ √
Italy √ √ √ √ √ √ √ √
Latvia √ √
Lithuania √ √ √ √ √ √ √ √
Luxembourg √ √ √ √ √ √ √ √ √
Malta
Netherlands √ √ √ √ √ √ √ √ √ √ √ √
Poland √ √ √ √ √ √ √ √
Portugal √ √ √ √ √ √
Romania √ √ √ √ √ √ √ √ √ √
Slovakia √ √ √ √ √ √ √ √
Slovenia √ √ √ √ √ √ √ √
Spain √ √ √ √ √ √ √ √
Sweden √ √ √ √ √ √ √ √
United Kingdom √ √ √ √ √ √ √ √
Use table
Supply table
Input-Output table
Table Imports
Country
1998
1998
2000/2001
2000/2001
Table 6: Availability of Input-Output and Supply and Use Tables
Source: Eurostat,
http://epp.eurostat.ec.europa.eu/portal/page/portal/esa95_supply_use_input_tables/data/workbooks .
Retrieved: March 2012.
For Bulgaria, Cyprus, and Malta no Input-Output Tables are reported for any year. Although
database updates are frequent: between February 2011 and March 2012 several Input-
Output Tables for 2005 were added. However, the Input-Output Tables for Malta (see section
5.1.2), Cyprus, and Bulgaria had to be estimated for the purpose of the study.
11
These
estimated Input-Output Tables meet all methodological requirements of official ones.
However, national statistical institutions can collect more data, e.g. by interviewing
companies about their production technologies, and apply extensive plausibility checks with
their national experts, therefore differences certainly can occur if official IOTs are available for
comparison in the future.
11
Contacting the national statistic institutions resulted in additional useful information, but no IOTs were sent.
Study on the Contribution of Sport to Economic Growth and Employment - 23 -
x
x
x
x x x
x x
x
x x x
x x
x
x x
x x
x
S
Total supply at purchasers' prices
Domestic Supply
Valuation
Industries (NACE)
Products (CPA)
Imports
Margins
Taxes
S
Total supply at basic prices
Therefore estimated tables are used as substitutes only when no official national Input-
Output Table is available.
The IOTs of Denmark, the Netherlands, and Finland turned out to be a special problem as
they were only available as NACE x NACE tables. No CPA x CPA table could be obtained.
Since these were otherwise perfectly properly calculated IOTs, they were kept as they were,
since attempting to translate them to CPA x CPA tables (see chapter 5.1.1 below) would
probably destroy more information than it would create. Replacing them in future versions will
enhance the model’s precision for these countries.
5.1.1 Calculation of Input-Output Tables
As a few countries only reported supply and use tables (SUT) for 2005, the corresponding
Input-Output tables had to be derived from them. This section deals with this conversion.
5.1.1.1 Supply and Use Tables
Several of the following depictions and descriptions closely follow those in UK Office for
National Statistics (2002), Statistik Austria (2010), and Eurostat (2008).
Figure 3: Schematic Supply Table
Source: SpEA, 2011.
Supply Tables show the origin of goods and services in an economy. Figure 3 shows a
scheme of such a table which is composed of two separate parts. The matrix of domestic
supply can be found on the left side. It has product categories (e.g. CPA) in its rows and
industry categories (e.g. NACE) in its columns. In a row, call it i, one can thus read off all
industries which produce product i. For example, real estate services are CPA 70. They are
mainly supplied by real estate agents (industry NACE 70). However, there are also
construction companies (NACE 45) which sell the flats, offices, or swimming pools they
constructed. Product 70 is therefore produced by industry 70 and industry 45. Thus there can
be several entries in each row.
Study on the Contribution of Sport to Economic Growth and Employment - 24 -
x x
x x x x x
x x x
x x x
x x x x x
x x x
x x x x
x x x
x x x x x x
x x x x
x x x x x
x x x x x
Gross Value
added
Compensation of employees
Products (CPA)
Public consumption
S
Total Demand at purchasers' prices
Private consumption
Exports
Final Demand
Taxes less subsidies on production
Industries (NACE)
Gross operating surplus
S Production value at purchasers' prices
On the other hand, column j shows the goods and services produced by industry j. Using the
construction company in NACE 45 again, we see that it not only constructs swimming pools
but also sells them. Industry NACE 45 therefore produces goods of CPA 45 and CPA 70.
Therefore there can also be several entries in each column.
As there exists a close relationship between products and industries (construction companies
mainly construct buildings, selling them is only a side-business), the biggest values are
usually found in the diagonal. For Example, CPA 01 refers to “Products of agriculture, hunting
and related services” which are mainly produced in NACE 01 “Agriculture, hunting and
related service activities”. These are called “characteristic goods”, as it is an industry’s major
effort to produce them. However, there are many industries producing secondary or by-
products. One can imagine a farmer (NACE 01) who not only harvests grapes (CPA 01), but
also transforms them into wine (CPA 15), or a construction company (NACE 45) selling its
own buildings (CPA 70, real estate services). These are non-characteristic goods and
services and are depicted as the off-diagonal entries.
In addition to domestic supply of goods and services, imports are available too. The value of
each imported type of good is reported in a column-vector to the right of the Domestic Supply
or Make Matrix.
The sum (along row i) of domestic production and imports equals the total supply of product i
at basic prices. These are the prices which arise to the producer. To know the purchasers’
prices, one has to add margins and taxes.
Figure 4: Schematic Use Table
Source: SpEA, 2011.
Study on the Contribution of Sport to Economic Growth and Employment - 25 -
Use Tables, as depicted in Figure 4, again can be read row- and column-wise. Row i reports
the different usages of product i. If it is used for producing another good or service (an input
being transformed into another output), it is called an “intermediate good”. This “Use Matrix”
in the upper left corner of the Use Table again has products in rows and industries in its
columns. High values appear in the main diagonal, but inter-industry relations usually are
very pronounced leading to numerous large off-diagonal values too. For example, the 2005
UK Use Table reports products of CPA 01 worth 2.5 bn Euro flowing into NACE 01. However,
goods and services of CPA 01 worth 12.9 bn Euro are used in NACE 15 (Manufacture of
food products and beverages) as inputs.
On the right hand side the values of goods and services which are not used in the domestic
production process are displayed. These are in principal private consumption, public
consumption, and exports. These three categories (plus a number of others) are called “Final
Demand”. The sum of intermediate demand and final demand equals total demand for a
good, which is reported at purchasers’ prices.
Columns of Use Tables reveal the costs of inputs being used in an industry when producing
according to the Supply Table (thus including non-characteristic goods and services).
Intermediate goods and services needed in industry j are shown in the j-th column of the Use
Matrix. Taxes less subsidies can be interpreted as costs of public administration, providing all
the services of a modern state (roads, a legal framework, social security, education etc.).
Compensation of employees (wages), gross operating surplus (i.e. profits), and consumption
of fixed capital (depreciation) are three very important accounts as they specify the return on
capital. Their sum is known as “gross value added”, which is a key economic indicator.
These four different usage-types of resources in an industry (inputs, taxes less subsidies,
compensation of employees, and operating surplus) sum up to the production value at
purchasers’ prices, the last row of the Use Table.
A number of identities hold within the system of Supply and Use Tables. The most obvious
apart from those already depicted in the figures, is that for each type of goods and services
the sum of production value plus imports must equal intermediate demand plus final demand:
all goods and services which are brought into an economy (by production or imports) have to
be used in some way.
GDP can be derived from Supply and Use Tables in three different ways:
By origin: production at basic prices minus intermediate demand equals value added
at basic prices. This plus taxes less subsidies equals GDP.
By use: compensation of employees plus operating surplus plus taxes less subsidies
equals GDP.
By distribution: final demand plus public demand plus exports minus imports equals
GDP.
Study on the Contribution of Sport to Economic Growth and Employment - 26 -
x x x x x
x x x x x x
x x x x x
x x x x x
x x x x x x
x x x x x x x x
x x x x
x x x x x x
x x x x x
x x x x x x x
x x x x x x
x x x x
S Supply at basic prices
Compensation of employees
Gross operating surplus
S Production value at basic prices
Imports
S
Total Demand at basic prices
Final Demand
Products (CPA)
Gross Value
added
Products (CPA)
Private consumption
Public consumption
Exports
Taxes less subsidies on production
Taxes less subsidies on products
5.1.1.2 Calculation of Input-Output Tables in Theory
At first glance, Supply Tables look very much like Input-Output Tables. There is however a
substantial difference: the Use Matrix has products in rows while it has industries in columns.
This is why it is called “asymmetric”. Input-Output Tables, as shown in Figure 5, have
products in both dimensions and are thus called “symmetric”. As a consequence industries
and their sectors no longer show up. In the columns of the Use Table one can see what an
industry requires. In the columns of the Input-Output Table, however, one can see what a
good requires to be produced. As an instance, the Use Table shows what the construction
company in NACE 45 needs to build and sell a swimming pool. Product CPA 45 in the Input-
Output Table reports what is needed to build the swimming pool. The service of selling it is
moved to CPA 70, real estate services. The Input-Output Table thus shows the inputs
necessary to produce a good, no matter by what industry it is produced.
Figure 5: Schematic Input-Output Table
Source: SpEA, 2011.
Input-Output Tables are mainly constructed for analytical purposes. As there is just one single
table rather than two some information is lost, e.g. the origin (in terms of economic sectors)
of goods and services. Total production of a good or service, characteristic and non-
characteristic, is combined and cannot be differentiated any more. This allows replacing
industries in the columns by products. One can imagine this as a Supply Table having its
entries exclusively in the diagonal from the upper left to the lower right. But then there is no
need for such a Supply Matrix as all other cells are zero and all information can be stored in
the Use-Matrix which is now called Input-Output Matrix.
Study on the Contribution of Sport to Economic Growth and Employment - 27 -
5.1.1.3 Conversion of SUTs to IOTs
To convert Supply and Use Tables into an Input-Output Table all off-diagonal entries in the
Supply Table into have to be moved to its row diagonal element. Non-characteristic
production is thus removed from its original industry and added to the one industry where it is
the principal output. Total supply of the good thus remains unchanged, but it is produced by
only one industry.
As output is moved, its inputs have to be moved accordingly. This happens in the Use Table
and requires a technology assumption. For instance, one could imagine the construction of a
barn (CPA 45) by a farmer (NACE 01). He would use the inputs necessary (wood, nails,
labour, etc.) to erect this building. The barn is moved from column 01 to column 45 in the
Supply Table and its inputs accordingly in the Use Table. However, the exact inputs are not
known, only that some construction is moved from 01 to 45. Which input and how much of it
should be moved? Depending on the underlying assumption, there are two principal
answers:
Product technology: it is assumed that a product requires the same inputs no matter
by which industry it is produced. The appropriately sized destination industry’s input
mix is subtracted from the source industry and added to the destination industry.
Although this seems very intuitive for many products, negative values can occur. For
example, if the construction industry uses a lot of concrete, while farmers use wood
for their barns, more concrete would be subtracted from the farming industry than it
actually uses.
Industry technology: it is assumed that an industry uses the same inputs for all its
outputs. This is particularly useful for side-products of a production process. In
addition, no negative values can occur, as only a share of what is used in the source
industry is removed from it and added to the destination industry. For example, in
1995, if 1.4% of NACE 01, agriculture and hunting, in the UK were CPA 45,
construction works, then 1.4% of all inputs of agriculture and hunting would be
removed and added to column 45.
Study on the Contribution of Sport to Economic Growth and Employment - 28 -
Ind A Ind B Ind C Total Ind A Ind B Ind C Total
Prod A 10 5 15 Prod A 2 2 6 10
Prod B 8 8 Prod B 4 4 8
Prod C 5 5 Prod C 2 2
Value added 4 2 2 8
Total 10 8 10 28 Total 10 8 10 28
Ind A Ind B Ind C Total Ind A Ind B Ind C Total
Prod A +5 -5 0 Prod A +1 -1 0
Prod B 0 Prod B +2 -2 0
Prod C 0 Prod C 0
Value added +2 -2 0
Total +5 0 -5 0 Total +5 0 -5 0
Ind A Ind B Ind C Total Ind A Ind B Ind C Total
Prod A 15 15 Prod A 3 2 5 10
Prod B 8 8 Prod B 6 4 -2 8
Prod C 5 5 Prod C 2 2
Value added 6 2 8
Total 15 8 5 28 Total 15 8 5 28
Original
Results
Supply
Use
Supply
Use
Supply
Use
Adjustments
Ind A Ind B Ind C Total Ind A Ind B Ind C Total
Prod A 10 5 15 Prod A 2 2 6 10
Prod B 8 8 Prod B 4 4 8
Prod C 5 5 Prod C 2 2
Value added 4 2 2 8
Total 10 8 10 28 Total 10 8 10 28
Ind A Ind B Ind C Total Ind A Ind B Ind C Total
Prod A +5 -5 0 Prod A +3 -3 0
Prod B 0 Prod B 0
Prod C 0 Prod C +1 -1 0
Value added +1 -1 0
Total +5 0 -5 0 Total +5 0 -5 0
Ind A Ind B Ind C Total Ind A Ind B Ind C Total
Prod A 15 15 Prod A 5 2 3 10
Prod B 8 8 Prod B 4 4 8
Prod C 5 5 Prod C 1 1 2
Value added 5 2 1 8
Total 15 8 5 28 Total 15 8 5 28
Adjustments
Supply
Use
Results
Supply
Use
Original
Supply
Use
Table 7: Moving production under the assumption of product technology
Source: reproduced from UK Office for National Statistics (2002), page 14.
Table 8: Moving production under the assumption of industry technology
Source: reproduced from UK Office for National Statistics (2002), page 15.
Study on the Contribution of Sport to Economic Growth and Employment - 29 -
Table 7 and Table 8 show examples how such movements are done. When using product
technology, a vector of '+/-(1 2 0 2)’ is moved within the Use Table, which corresponds to the
input structure of industry A, '(2 4 0 4)’. Thus a negative value appears in the resulting Use
Table.
This problem does not occur when industry technology is applied. The shifted inputs are
given by '+/-(3 0 1 1)’, which is a fraction of industry C’s inputs '(6 0 2 2)’. This is why
negative values cannot appear as long as some positive production remains in the source
industry.
In reality, the following hybrid algorithm
12
is used: an expert studies each moved product in
detail and decides which of the above technology assumptions to use. This method can still
result in negative entries and requires a lot of technical expert knowledge. Due to this, such
transformations cannot be traced by a third party unless the decision for each entry is
recorded and made available. However, it is the most appropriate way of treating this
problem and widely used by national statistics offices.
The problem of negative values still remains for such entries, however, where product
technology is appropriate. Statistik Austria (2010) and Eurostat (2008) suggest the Almon-
Algorithm which was introduced in Almon (2000): “a slight adjustment in the product-
technology assumption leads to an algorithm that is certain to avoid negative flows yet keeps
close to the spirit of the product-technology idea”. Statistik Austria (2010) advises to be
careful with entries being calculated as zero, as real zeroes hardly ever occur in an Input-
Output Table. In most cases, these entries are strictly positive in the Use Table. They only
became negative and thus subject to the Almon-Algorithm in the process of moving
production. Another useful reminder by Statistik Austria (2010) is that it is only a
mathematical procedure meant to solve the remaining problems after careful inspection and
manual movements.
As a last step, RAS has to balance the matrix, as the column-wise sums are altered by the
Almon-Algorithm.
5.1.2 The Input-Output Table of Malta
Malta was the first country for which an Input-Output Table had to be calculated from Supply
and Use Tables. Although the procedure in general followed the steps described in section
5.1.1, several specific issues arose. One example is that Supply and Use Tables were only
available for 2000, 2001, and 2004. The latter was used to estimate an Input-Output Table for
this year, which was then updated to 2005.
12
Mix of the tow above methods.
Study on the Contribution of Sport to Economic Growth and Employment - 30 -
Table 9: Stylised Supply and Use Tables of Malta
Source: Eurostat,
http://epp.eurostat.ec.europa.eu/portal/page/portal/esa95_supply_use_input_tables/data/workbooks .
Retrieved: February 2012.
A stylised overview of Malta’s Supply and Use Tables is given in Table 9 showing some of the
details. Normal industries and products are subsumed as “Other” in the first rows and
columns.
1. 'Forestry and logging' does not exist as an industry (Supply and Use, column) nor are
such products produced by another industry (Supply, row). There is some import;
therefore supply is positive and used as inputs (Use Matrix, row) as well as final
demand.
2. The same holds true for mining for coal, lignite, and peat as well as for metal ores.
3. Uranium and Thorium ores are neither supplied nor demanded.
Study on the Contribution of Sport to Economic Growth and Employment - 31 -
4. Wholesale exists as a specific industry (Supply and Use, column) with the service
being supplied by other industries (Supply, “Other” column) and imports (Supply, third
column from the right with value “Y”) too. However, valuation is exactly as high in
negative terms as the service is supplied by domestic industries (Supply, Valuation of
wholesale), leading to total supply (Supply, rightmost column) equalling the imports.
In the Use table one can read that these imports are used for exports only (Use,
second column from the right with value “Y”) with no domestic use.
Most sectors were treated by moving production in a straight forward way using the product
technology assumption.
Taxes less subsidies also show up in final demand. Those taxes, which are paid by the final
consumer, such as taxes on tobacco, are included. National statistical organisations
calculate these from consumption surveys, but such information is not available in the
context of the study. Hence the average share of the UK and Austria is used once more,
which are, again, quite similar (27.6% and 24.1% of the taxes remain in intermediate
production respectively).
The vectors below and to the right of the intermediate goods matrix of the Input-Output Table
were calculated including the row- and column-wise sums of the matrix. The Almon algorithm
was applied to get rid of negative entries and RAS balanced the matrix.
Updating from 2004 to 2005 was done using Malta ONS (2011), reporting GDP values from
2004 to 2010, including several details like gross value added of industries down to a level of
30 categories (AA to PP).
Similar procedures were applied to Cyprus. In this case, the provisional Supply and Use
Table are reported by Eurostat and were used to calculate an Input-Output Table.
5.2 Collection of National Sports Data
In order to proceed, sport satellite account data (data for the extension of the original Input-
Output Table) had to be collected for every EU Member State.
The most efficient way was a top-down approach starting with international databases and
ending with national expert knowledge. First of all, existing data was analysed. Our study
uses data sources on a European level (e.g. Eurostat, see Chapter 6), on a national level
(e.g. national statistic offices) or from other sources, such as supra-national organisations
(e.g. European Observatoire of Sport and Employment Secretariat (EOSE)
13
or the
Federation of the European Sporting Goods Industry (FESI)) or already existing studies.
These data sources provide a wide range of standardised high-quality data.
13
E.g. Data collection from the EOSE led and EU funded VOCASPORT project (2004), EOSE Fact Sheets and sectoral studies
on the sport labour market undertaken by EOSE at EU level.
Study on the Contribution of Sport to Economic Growth and Employment - 32 -
Although all these data were collected, there were still gaps in the tables. National data
sources were used in such cases (see below). For those nations and categories where these
secondary data for sport-related subsections were not available or not detailed enough
estimates were used (from expert interviews or other studies). High correlations (e.g.
between Production value/Value added and the employees) and other economic stylised
facts (e.g. financial intermediation services are one category and proportionally require
auxiliary services which form another category) were utilised also.
Searching for secondary national data is a very time-consuming task where fully-fledged
national IOTs:S have a big advantage as they can concentrate on just one country. However,
such searches had to be performed as there are data gaps which cannot be closed
otherwise. During this process it once again turned out that there are key persons in several
countries who can easily provide a wide range of data. Such expert input can bring a proxy-
IOT:S very close to a fully-fledged one. In the context of this study, Italy and France are
examples where national experts provided particularly valuable data.
Specific data on sport-related national production and consumption were available for
Austria, Cyprus, France, Germany, Greece, Italy, Ireland, the Netherlands, and the UK.
These countries represented 77.6% of the EU’s total GDP. Aggregates of private and public
spending were reported for Slovenia.
For all remaining countries we used production data from Eurostat as well as health,
education, and public administration from international data bases. Private consumption
numbers of sports articles were made available by FESI. Remaining gaps were either filled
by calculating the remaining fourth value in the equation production + imports = consumption
+ exports (foreign trade see chapter 5.3) or by assuming similar ratios in similar countries.
5.3 Imports and Exports
The next step was the collection of data for imports and exports within the EU-27. Because
each export from one region is an import to another region, imports were not collected
directly. Exports have the additional advantage of being counted as fob (free on board) while
imports are cif (cost, insurance, freight). Thus export values reflect the real volume much
closer, since imports are increased by an unknown amount of freight and insurance costs.
5.4 Enlarging national Input-Output Tables
There are several algorithms for the problem of filling in matrix-values when only row and
column sums are available. Probably the best known is the RAS, simply named after its three
most important variables R (row wise sum), A (the matrix), and S (the column-wise sum),
method which iteratively updates row and column contents in a proportional way with the
remaining differences converging towards zero.
The TRAS algorithm (“Three-stage RAS”) is a valuable extension, allowing fixed cell entries.
If one knows the value for some reason – e.g. from primary data or because a subsection
having no sport content must remain unchanged – this method only changes the cells around
Study on the Contribution of Sport to Economic Growth and Employment - 33 -
the fixed ones. Minimizing errors over both dimensions while respecting fixed values is an
optimal combination of properties.
Instead of iteratively switching between row and column adjustments, the MODOP-algorithm
(“Modell der doppelten Proportionalität“ or “Model of double proportionality”) updates them in
a parallel fashion. However, the method seems to be prone to estimation errors
14
.
Table 10: Adjustment Algorithms
ADJUSTMENT ALGORITHM
Method
Necessary Data
Brief Description
Source
RAS
Basis IOT
Bi-proportional adjustment of
cell contents through row- and
column sums
Stone, Bates,
Bacharach (1963)
Current boundary values of the IOT
TRAS
Basis IOT
RAS-Algorithm taking known
partial matrices into account
Gilchrist, St. Louis
(1999)
Current boundary values of the IOT
Partial Matrices
MODOP
Basis IOT
Bi-proportional, simultaneous
adjustment of cell contents
through row- and column sums
Stäglin (1972)
Current boundary values of the IOT
PKK
Basis IOT
Row-wise proportional
adjustment of cell element of
the matrix
Matusewski, Pitts,
Sawyer (1963)
Current boundary values of the IOT
SKK
Basis IOT
Bi-proportional update of cells
using weights
Ehret (1970)
Current boundary values of the IOT
Sectoral growth rates
MVR
Basis IOT
Experts create tables which are
then weighted to minimise
differences
Gerking (1976)
Current boundary values of the IOT
KQM
Basis IOT
Minimisation of differences by
Lagrange-method
Jaksch, Conrad
(1971)
Current boundary values of the IOT
Source: SpEA, 2011.
The basic assumption of the PKK method (“Proportionale Koeffizientenkorrektur” or
“Proportional Correction of Coefficients”) is that substitution of inputs is constant over
sectors. Thus it works in a row-wise fashion, ignoring column sums. Another correction would
14
see Koch, Spehl, Osterbach, Benson (1999): „Evaluierung regionalwirtschaftlicher Wirkungsanalysen Anhang II: Gutachten
und externe Evaluierung“, page 199, Taurus.
Study on the Contribution of Sport to Economic Growth and Employment - 34 -
be necessary to reduce the differences in the column sums to zero, making this algorithm
unsuitable for the needs of this study.
SKK (“Streuende Koeffizienten” or “Varying Coefficients”) is an extension of PKK able to work
on both dimensions by applying weights. As it needs sectoral growth rates and shows
substantial errors when tested with real data it cannot be used for this study too.
Applying weighted expert opinion is used by the MVR algorithm (“Minimum Variance
Reconciliation”). The sheer number of cells to fill is a prohibitive obstacle as well as
subjective opinion.
An interesting approach is KQM (“Kleinstquadratemethode” or “Least Squares”) which
minimises the error by a least squares method assuming normally distributed “shocks”
pushing the empirically found values away from the underlying values. Although this sounds
very promising first, it has the disadvantage of leaving behind a residual error which is not
explained.
For the computations in this model, TRAS was used. This allowed shipments between those
CPA divisions which are not marked as sport-related to be kept fixed.
Experimenting showed that using proper starting values is crucial for getting plausible
results. Using a constant (e.g. 1.00) in all unknown cells leads to rows and columns with very
similar entries in each respective cell reporting around 1/94
th
of the sum. It can be assumed
that the required inputs of a sport-related building is the same as that of a non-sport building,
so the original values of the aggregated CPA-divisions were chosen as starting values. TRAS
was run until the sum of all absolute deviations in all the rows and columns was less than
100,000 Euro. This proved to be a rather lengthy task, requiring several thousand iterations,
while other IOTs:S converged well below the threshold within 500 iterations. This procedure
worked in almost all countries. However, the intermediate goods matrix of Luxembourg did
not enhance beyond a certain point. From there on, RAS was used to finalise the last entries
with all cells being allowed to change. Typical deviations from the values reported in the
national IOT are smaller than 10,000 Euro.
The 27 national (proxy) Input-Output Tables: Sport were thus completed. From this step
onwards, sport and non-sport categories are on a par with each other. Whether a category
had no sport-related component, did contain sports but had the sport-related component
subtracted, or was a sports-only category is irrelevant. They are treated in the same manner.
In the next step, they were combined into one large Multiregional Input-Output Table: Sport.
5.5 Multiregional Input-Output Table according to Chenery and Moses
With the 27 expanded and harmonised national Input-Output Tables the Multiregional Input-
Output Table can be set up. It is a 27-regions and 94-sectors (59 standard CPA divisions +
34 CPA divisions with sport content) model. Below a very simplified version (for a 3 region
and 3 sector model, no discrimination between sport and non-sport) is presented.
Study on the Contribution of Sport to Economic Growth and Employment - 35 -
1 2 3 1 2 3 1 2 3
1
2
3
1
2
3
1
2
3
Gross Value
Added
Gross
Production
Final
Demand
Gross
Production
Subsection
Subsection
Subsection
Region 1
Region 2
Region 3
Subsection
Subsection
Subsection
Region 1
Region 2
Region 3
Figure 6: Set up of a Multiregional Input-Output Table
Source: SpEA, 2011.
The shadowed parts of this Multiregional Input-Output Model are the domestic national Input-
Output Tables; white cells represent the imports (column-wise) and exports (row-wise)
between the regions for each subsection. In principle, domestic IOTs can be used to fill the
Region 1
Subsection
Final
Demand
Gross
Production
1
2
3
∑
Subsection
1
2
3
∑
Gross Value Added
Gross Production
Region 2
Subsection
Final
Demand
Gross
Production
1
2
3
∑
Subsection
1
2
3
∑
Gross Value Added
Gross Production
Region 3
Subsection
Final
Demand
Gross
Production
1
2
3
∑
Subsection
1
2
3
∑
Gross Value Added
Gross Production
Study on the Contribution of Sport to Economic Growth and Employment - 36 -
orange cells. However, the Chenery and Moses procedure calculates all values of the
intermediate goods matrix, so it is easier to use these results.
In principal, all data in each cell of the intermediate goods matrix could be gathered from
primary, secondary, or tertiary data sources. This corresponds to the main idea of Isard’s
model. However, the number of data required increases quadratically with the number of
sectors and regions (see Figure 6). Doubling the number of regions increases the search
effort four times. Although data bases today are better than ever, searching all (94
x27)
2
=2535
2
=6441444 export-values within the EU is an unfeasible task.
Chenery and Moses thus came up with the idea of using less data while imposing restrictions
or assumptions to calculate the rest. What is needed apart from the standard IOTs are data
on exports of good G from sector S1 in region R1 to region R2. It is not necessary to know
the sector in the receiving region. For example, it is enough to know that Belgium exports
non-sport textiles worth 34.98 m Euro to the Czech Republic. It is not necessary to know how
that will be used.
The first restriction is that “[i]t is assumed that the amount of each good absorbed by every
industry in a region is strictly proportional to its output” (Moses (1955), p. 805). This is very
similar to the standard assumption of the Leontief production function, stating that there is a
linear relation between inputs and outputs: if one wants to double the output, the inputs have
to be doubled too.
The second restriction characterises Chenery and Moses type models and states “that each
region purchases its requirements of every good according to a fixed regional supply pattern”
(Moses (1955), p. 807) and that the “model applies to all economic units in the area, an
import pattern which is an average for the region as a whole” (Moses (1955), p. 810). That
implies that one and the same import structure is used for all sectors of a region. For
example, if sector S1 in region R1 imports good G1 in the ratio 90 : 6 : 4 from regions R1
(itself), R2, and R3, then all other sectors of region R1 will do so too.
The third restriction is that not only production patterns remain constant as in the first
restriction, but also trading patterns. If one observes that 10% of the necessary inputs of a
certain product are imported from a specific region, it is assumed that this is also true in
future. This too is consistent with the standard ideas of Input-Output Analysis.
These restrictions deserve closer inspection. Stability of input ratios while output is varied
bases on the idea that every company or every production process can be copied. Although
there are certainly limitations in the form of human capital, space for factories, or availability
of natural resources, this assumption is rather mild within the usual scope of prognoses of
I/O analyses.
Stability of trading patterns has a deeper theoretical background. At first sight there is no
reason why Swedish timber should be different from Polish timber. Thus one could easily
replace one type of timber by the other. But the existing and observable trading structures
emerged for good reasons. As Moses pointed out: “In an immediate sense, trading patterns
Study on the Contribution of Sport to Economic Growth and Employment - 37 -
reflect regional cost-price relationships and regional capacities for production and
distribution. …These are patterns which would automatically be achieved under conditions of
pure competition. They are optimal in the sense that they involve lowest possible over-all
expenditure on production and distribution for satisfying final demand,” (Moses (1955), p. 810
and 811). Thus it does make sense to use exactly this mix of goods and services from
different regions which can be observed and it seems reasonable to assume that this mix is
stable over some time. This is even more justified as prices do not vary frequently. Usually
prices are determined at most every three months, wages once a year. Reactions to such
changes are again delayed by several months. The stability of production prices, transport
costs, and wages are three requirements for the validity of Chenery and Moses models
(Moses (1955), p. 811).
Three further necessities derived from the three original restrictions are “(1) There is excess
capacity in the transport network between every pair of regions. (2) Each industry in each
region has excess capacity. (3) There is a pool of unemployed labor in each region” (Moses
(1955), p. 811). While single companies can often be found at 100% of their capacity, a
whole sector usually has some free capacity. The assumption of free transport paths is also
very mild. The existence of a substantial number of unemployed is a fact, but whether they
can be hired for expanding production in a specialised sector seems questionable.
Chenery and Moses go one step further and claim that if a special import mix for a good or
service is optimal for one sector, it is also the case for all other sectors. “Their interpretation
is that all producers in each region consider the imports from a specific region as
homogenous and thus all producers import from a specific region in proportion to their total
needs rather than importing in different proportion from different regions” (Hartwick (1970).
Although this assumption sounds rather strong, given that there are 94 different goods and
services used in the model, each product is described adequately.
Using these restrictions one is able to reduce data requirements from millions of data, where
many are not even available (e.g. there is no sector-to-sector foreign trade data) to
manageable amount of thousands of data which can be stored in accessible data bases.
5.6 Finalisation of the Multiregional Input-Output Table
The result of the Chenery–Moses procedure is a matrix similar to the one in Figure 6. The
orange entries correspond to the domestic IOT, with the white parts of the intermediate
goods matrix above of each region being a disaggregated intra-model (from within the EU in
this case) imported IOT. The white entries to the left and right of each region are the region’s
intra-model exports.
Extra-regional foreign trade is left untouched by the algorithm. From a numerical point of
view, it is irrelevant whether a good is consumed by private households or exported to a
region outside of the model: in both cases the value is “taken out of the economy”. The same
holds true for extra-model imports and value added. Both numbers “appear” in the domestic
economy. Thus for the sake of proper calculation, extra-EU foreign trade was added to the
Study on the Contribution of Sport to Economic Growth and Employment - 38 -
final demand and value added during the purely numerical procedure. Afterwards the values
were separated again according to their ratios previous to the calculations.
15
What is not shown in the figure, but was of course computed, was intra-model foreign trade
of final demand. The Chenery–Moses procedure allows for calculating the share of domestic
consumption in total consumption. Thus each good or service used by anyone can be
statistically traced back to its origin.
The final result is not just a Multiregional Input-Output Table according to Chenery - Moses. It
is a Multiregional Input-Output Table: Sport. The difference is that it is a MRIOT assembled
from IOTs expanded to IOTs:S. Figure 7 shows the basic structure of this model. There are,
in this example, three national IOTs which were transformed into IOTs:S, containing the dark
green sport part (in the real model this part consists of 34 rows and columns, not just of one).
Therefore in contrast to Figure 6 sport-relevant goods and services can be identified in
Figure 7. The national IOTs:S are dis-assembled into
the intermediate goods matrix,
the demand quadrant, and
the supply quadrant.
The domestic intermediate goods matrices including the sport parts form the dark shaded
parts along the main diagonal in the MRIOT:S. The demand quadrant moves to the right of
the MRIOT:S and, in principal, remains as it was in the national IOT:S. The lower quadrant
including value added, imports, and total supply is put into the lower part of the MRIOT:S,
also without major changes.
The imported IOTs:S can thus be calculated by summing the pale sub-matrices above and
below each regional domestic intermediate goods matrix. The same holds true for the
exports of each good or service which can be found to the left and to the right of the dark
sub-matrices. In fact, even final demand is computed in the same way by the Chenery-
Moses procedure. This information does not affect the study analyses and would only make
the graph much bigger by splitting final demand.
Computing sport-related value added for all regions in the model is done by summing the
values in the green cells of the last but two rows. Final sport-related demand is reported in
the green cells of the corresponding column in the demand quadrant.
15
The same actually took place for all numbers within final demand, like, public demand, NPISH-demand, changes of
inventories, gross capital formation and so on as well as within the different numbers in value added.
Study on the Contribution of Sport to Economic Growth and Employment - 39 -
1 2 3 Sport S
1
2
3
Sport
S
Import
Supply
Gross Value Added
Good
Final
Demand
Export
Total
Demand
Good
1 2 3 Sport S
1
2
3
Sport
S
Import
Supply
Gross Value Added
Good
Final
Demand
Export
Total
Demand
Good
1 2 3 Sport S
1
2
3
Sport
S
Import
Supply
Gross Value Added
Good
Final
Demand
Export
Total
Demand
Good
1 2 3 Sport 1 2 3 Sport 1 2 3 Sport
1
2
3
Sport
1
2
3
Sport
1
2
3
Sport
S
Region 2
Good
Region 3
Good
Good
Region 1
Gross Value Added
Supply
Final
Demand
Export
Total
Demand
Import
Region 3
Good
Region 1
Region 2
Good
Good
Figure 7: Set up of a Multiregional Input-Output Table: Sport
Source: SpEA, 2012.
To compute sectoral multipliers, the Leontief Inverse had to be calculated. This is the inverse
of the identity matrix minus the normalised intermediate goods matrix of the MRIOT:S.
Marking of the sectors as non-sport, and sport according to the broad, narrow, or statistical
definition paved the way for further calculations.
Study on the Contribution of Sport to Economic Growth and Employment - 40 -
6 European and International Data Sources
There are many data sources which might be useful for building the EU-SSA. To keep track
of these different sources and the parts for which they were used, the project group is
working on a meta-database, i.e. a database which describes which data sources were used
during the project, their characteristics and the areas to which they were applied.
As discussed before, when reliable data on a European level for specific countries are
available, these sources should be preferred to national (secondary) data sources.
There a several data sources which might be considered to be useful for specific parts of the
SSAs. These sources are listed in Table 11.
Table 11: Different European Data Bases
EU SILC
Statistics of Income and Living Conditions
EU AES
Cultural participation
EU EHIS
Physical activity
EU TUS
Time Use Survey
ISES
Sports & Events Study
Source: Own research at the data bases themselves.
6.1 Production
Sport-related goods and services can either be imported or produced domestically. Domestic
production is preferable in economic terms since this creates more value added, and
therefore more employment, wages, profits and earnings, as well as taxes and other
contributions.
However, as there is no NACE-entry apart from 92.6 which is directly sport-designated, self-
categorisation of companies as producers of sports goods and services is very rare. Reliable
data on sport-related production therefore is not always available.
This problem is solved as Eurostat publishes production data ranging from CPA 13 to
CPA 36 on the Prodcom 8-digit level. As the first six digits of Prodcom correspond to CPA,
this data base provides extremely detailed information. These data are then matched with
the Vilnius Definition of sport to identify the Prodcom entries with sport content. To calculate
the volume of sport production the sport-related share of each entry has to be calculated.
These shares were calculated in such a way that they fit with the values of those IOTs:S
where production is known.
The absolute volume of a country’s sport-related production in one sector was thus
calculated as (production value of that sector) x (sport-related share of that sector). The
production value is well known from the national IOT. The first of the two multiplicative factors
Study on the Contribution of Sport to Economic Growth and Employment - 41 -
is thus accurately measured for each country, capturing the biggest part of variations in sport-
related production. The second factor is constant for all countries estimated in this way. Since
this share is derived from countries where this value is well known, the differences to reality
can be assumed to be white noise: there is no systematic error. However, fully-fledged
national IOTs:S can paint a clearer picture of a country by replacing the average on the right
hand side of the multiplication. For EU-wide calculations, average values are sufficient.
6.2 Sport-related Public Administration and Social Security, CPA 75
The Eurostat database on national accounts contains gross value added in the sector of
public administration, defence and compulsory social security for the Member States in 2005.
The Eurostat database on government statistics comprises government expenditure by
function (COFOG) for the Member States in 2005 accounting for social security
expenditures. The share of social security expenditures in total government expenditures
was used to estimate gross value added in social security.
On the basis of the European Union Labour Force Survey, LFS, (see European Communities
(2003)) the percentage of professional athletes of all employees in each member state was
calculated in order to estimate sport-related gross value added in social security. The
COFOG database of Eurostat was also used to estimate the sport-related share of public
administration.
6.3 Sport-related Education, CPA 80
Sport as part of the education system typically spans from the first year of school towards
university studies. Thus most states offer approximately 20 years of sport-related education
to some persons. It is therefore not surprising that this activity is economically important in
many countries and an important part of this study.
Gross value added in education for the Member States in 2005 is available from the Eurostat
database on national accounts. Using the online UNESCO/OECD/EUROSTAT (UOE)
database on education statistics, which is compiled on the basis of national administrative
sources (OECD (2007)) together with UNESCO Statistics (UNESCO (2009)) the shares of
primary, secondary and tertiary education (according to ISCD 97) in total expenditure for
each country were computed. These shares were used to differentiate total gross value
added and hence estimated gross value added in the NACE Categories 80.1 (Elementary
Schools), 80.2 (Secondary Education) and 80.3 (Higher Education).
Data on physical education in elementary schools in the Member States of the European
Union were reported in a study of Brettschneider et al. (2004) (see p. 141 et seq.) and used
to estimate sport-related gross value added in elementary schools in each country. The
estimations for gross value added in secondary education per country were based on the
OECD “Teaching and Learning International Survey” (TALIS) (see OECD (2010)), collected
from 4,000 schools in 23 countries from March to May 2008. It contains data on teacher’s
subjects, including physical education, and teacher’s working hours. By assessing the share
of physical education in all subjects taught, the sport-related share of value added in
secondary education was estimated.
Study on the Contribution of Sport to Economic Growth and Employment - 42 -
Assuming that sport teacher training in higher education represents nearly all sport-related
expenditure in this sector, the share of sport teachers of all teachers for each country was
estimated on the basis of the TALIS. The OECD online statistics on education contain
graduates by field of education in tertiary education for OECD countries. These shares were
used to estimate the share of graduates in sport of all graduates on a country basis.
Estimation of sport-related gross value added in higher education was performed by
assigning the sport graduates’ share.
6.4 Sport-Related Health, CPA 85
Sport-related gross value added in the health sector is divided into four subsectors: hospital
activities caused by injuries during sport activities, outpatient care caused by injuries during
sport activities, hospital activities as medical care for professional athletes, and outpatient
activities as medical care for professional athletes.
The Eurostat database on national accounts contains gross value added in the health sector
for the Member States in 2005. Data on health expenditure, differentiated by supplier and
country, are available for 2005 in OECD Health Statistics. Shares of inpatient and outpatient
care in expenditure were estimated on this basis and transferred to gross value added in the
health sector. The Eurostat database on health statistics contains data on hospital
discharges by causes following ICD10. The Injury Database (IDB) (see Bauer (2009)) of the
European Union, a representative survey compiled from hospitals of the Member States,
contains detailed data on injuries (e.g. on the activity during which the injury occurred),
accounting also for sport, and on the treatment in the hospital, whether admitted, treated as
an outpatient or sent to a practitioner. Combining these data sources, the share of inpatient
care after sport injuries in gross value added of the health sector was estimated.
16
The Eurostat database on health statistics contains data on outpatient care by diagnoses
(ISHMT), accounting also for injuries. In conjunction with the IDB, the share of sport-related
injuries in outpatient care could be estimated and hence the sport-related gross value added
in outpatient care could be estimated.
On the basis of the European Union Labour Force Survey (European Communities (2003))
the percentage of professional athletes in of all employees in each member state was
calculated and used to estimate the share of gross value added in inpatient and outpatient
care for professional athletes for each country.
6.5 The European Market for Sport Articles
As the retail market for sport articles is a substantial element of the sport economy, an
overview is given in this section.
Table 11 exhibits the data on purchases of sport articles per capita and in total for all EU
Member States provided by FESI. Numbers vary widely, but were described by FESI as
16
Average costs for treatment of injuries in hospitals were estimated to be around 75% of total average costs for treatment of all
causes on the bases of German health data, see www.gbe-bund.de.
Study on the Contribution of Sport to Economic Growth and Employment - 43 -
trustworthy, turned out to fit well into the national IOTs:S, and harmonised with most of the
other data sources.
The largest markets are UK, France, Italy, Germany, and Spain. These five markets together
represent almost 73% of EU-total purchases. The largest per-capita purchases are observed
in Luxembourg, Malta, Austria, Sweden, and Ireland. As there are many people working in
Luxembourg who do not have a residence there, many purchases in Luxembourg originate
from consumers of neighbouring countries. Austria is also special since many skiing tourists
buy their equipment, at least the skis, at their holiday destination and take them back home.
So there are also many purchases registered in Austria made by non-residents.
Table 12: Purchases of sport articles incl. VAT
Purchases per capita per
year in €
Market volume of sports
articles per year in million €
Austria
199
1649
Belgium
137
1441
Bulgaria
12
95
Cyprus
35
28
Czech Republic
66
677
Denmark
146
789
Estonia
32
41
Finland
134
709
France
143
8709
Germany
86 (205)
7129 (16638)
Greece
111
1235
Hungary
30
307
Ireland
166
696
Italy
130
7638
Latvia
23
52
Lithuania
26
89
Luxembourg
307
154
Malta
206
82
Netherland
157
2557
Poland
18
682
Portugal
62
653
Romania
14
292
Slovakia
30
161
Slovenia
102
203
Spain
121
5313
Sweden
166
1492
UK
149
9000
Source: FESI, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 44 -
German data seem implausible. The value of 86 Euro per person per year is rather low and
conflicts with other studies. Meyer and Ahlert (2000) reported sport article purchases of
14.7 billion Euro for the year 1998 and recently published results of the sport-consumption
survey (Preuß and Alfs (2012)) report expenditures of 19 billion Euro per year for 2009 to
2011. Consequently, the value of 16.6 billion Euro or 205 Euro per person per year was used
in calculations for Germany in 2005.
6.6 Import and Export Data
This section discusses the importance of international trade in sport in the EU economies
and the problems negotiated in defining its size. Both trade in sports goods and services has
been estimated. Although it is possible to consider separately national trade data, a decision
was taken early on to investigate all trade primarily through UN data. This guarantees a
consistency in the presentation and definition. There are two UN datasets under
consideration, one for commodities and one for services.
The steps we used are as follows:
1. Construction of a matrix for international trade data.
2. Data collection on commodity trade.
3. Data collection on service trade.
4. Modelling sport related commodity trade.
5. Modelling sport related service trade.
The definitions of exports and imports, as reported by the UN are not equivalent to each
other. Imports are generally reported on the Cost, Insurance and Freight (CIF) basis, while
exports are reported on the Free on Board basis (FOB). Thus export values represent the
good’s price only (plus transport to the ship/truck) while import values include substantial
additional costs. To negotiate this problem, we collected export figures, which correspond to
the National Accounts, and then we applied the Chenery/Moses procedure to distribute
imports within each country. There is the theoretical drawback that countries have a bigger
incentive for registering imported goods as they might be subject to customs duty while
exports might leave the country unnoticed. This, however, is unlikely to be a problem for the
EU.
The UN international commodity trade data are included within the 'UN Comtrade' database.
The dataset contains annual bilateral merchandise trade (imports/exports) for all available
countries for up to 5 digit SITC (Standard International Trade Classification), and up to 6 digit
HS (Harmonised Commodity Description and Coding Systems) and BEC (Broad Economic
Categories).
Study on the Contribution of Sport to Economic Growth and Employment - 45 -
The SITC system classifies the production of materials, the processing stage, uses of
products, the importance of goods in world trade, and technological changes. The aggregate
categories of commodities examined are: food, drinks and tobacco (sections 0, 1), energy
products (section 3), raw materials (sections: 2, 4), chemicals (section 5), machinery and
transport equipment (section 7) and other manufactured goods (section 8). The eighth
category includes both sports footwear and sporting goods. Although many categories are
explicitly identified, in some cases further breakdown of information is required to arrive to
the sport-related part.
Quantities are available when reported by the home country, and can be converted into UN
standard units. The UN Statistical Office does not supply data directly; all data downloads are
done on line by users. In the case of commodities, there is sufficient data availability.
Because of its direct connection with NACE (“Nomenclature générale des Activités
économiques dans les Communautés Européennes” - Statistical classification of economic
activities in the European Communities) categories, the SITC system is used. All trade up to
five digit SITC is available and consistent with the National Accounts. The way to derive the
NACE codes is as follows:
For the purpose of the study, the SITC rev.3 classification was translated into ISIC
(International Standard Industrial Classification) rev 3 classification. Then the latter is
transformed into NACE rev 1.1, which is equivalent to the National Accounts and the data
used in the Satellite Account.
NACE based statistical classifications are comparable at European and world level. The use
of NACE is mandatory within the European Statistical system. NACE is derived from ISIC, in
the sense that it is more detailed than ISIC. NACE and ISIC have exactly the same items at
the highest levels, whilst NACE is more detailed at lower levels. In this way there is an
alignment of NACE with the international standards. In terms of the format of reporting of
data, following the Eurostat Input-Output Tables convention, we use the two digit level.
However, the UN data occasionally report trade distribution in much greater detail. For
example, in the case of sport goods, Table 13 below shows the UN data detail in this
category.
Finally, the exports we considered can be divided into exports of domestic goods and exports
of foreign goods. The latter is generally referred to as re-exports and implies exporting goods
in the same state as previously imported. This most often happens in relationship to the
country of origin for reasons such as: an exported good might be defective, the importer
might have defaulted on payments or cancelled the order, the authorities might have
imposed an import barrier, and finally demand or prices in the country of origin might have
made it worthwhile to bring the goods back. We have collected more data than required for
the reporting stage, so that modelling of sport-related trade can be meaningful and accurate.
SITC ISIC NACE
Study on the Contribution of Sport to Economic Growth and Employment - 46 -
Based on what we have collected we know that in the case of commodities the sport element
can be meaningfully identified.
Table 13: UN definition of Sports Goods
894.71
Fishing rods, fish-hooks and other line tackle; fish landing nets, butterfly
nets and similar nets; decoy 'birds' (other than those of heading 896.5 or
898.29) and similar hunting or shooting requisites, n.e.s.
894.72
Ice skates and roller skates (including skating boots with skates attached)
894.73
Snow-skis and other snow-ski equipment
894.74
Water-skis, surf-boards, sailboards and other water sport equipment
894.75
Golf equipment
894.76
Tennis, badminton or similar rackets, whether or not strung
894.77
Gloves, mittens and mitts, specially designed for use in sports
894.78
Articles and equipment for general physical exercise, gymnastics or
athletics
894.79
Sports goods, n.e.s.
Source: SIRC, UN.
In the case of international trade in services the 'UN Servicetrade' dataset was used. One
issue was the compatibility of the satellite accounts of individual states with the international
data generated through this exercise. It was expected that equivalent figures would be
generated through both processes. However, unlike the UN Comtrade dataset, the UN
Servicetrade does not have a one to one correspondence to the National Accounts
categories. In other words in the case of services we do not have an alignment of NACE with
the international standards. However, this situation is under review as the UN endeavours to
bridge this gap. An international alignment of NACE in services will improve the existing
statistics. Hence, on the outset, as it stands the exercise becomes much more complex.
Additionally, some information of international service trade is not reported to the UN, and it
has to be derived or modelled using directly the National Accounts or other sources. The
classification used by UN is the Extended Balance of Payments Services Classification
(EBOPS 2002). There is no way to navigate with certainty from the EBOPS classification to
the NACE one (as we go from SITC to NACE in the case of commodities). However
comparing the EBOPS classification directly to the National Input Output tables can bring
much insight about the distribution of trade in sports services. Hence, our methodology is
based on a ‘triangulation’ of EBOPS, NACE and the National Input-Output Accounts. The
methodology must be revised when the UN produces a system of linking EBOPS to NACE.
Table 14 illustrates the international trade in one of the examined categories: ski and ski
equipment. A similar matrix is constructed for each category in the Account. For the sake of
simplicity we restrict our attention to this category and left out most countries in the
illustration. In total we get a 27 by 27 matrix (for the 27 EU countries). By reading
Study on the Contribution of Sport to Economic Growth and Employment - 47 -
AT BE BG CY CZ DK UK EU Rest Total % EU
AT D 3.04 3.54 0.02 18.99 1.24 3.48 241.55 154.68 396.24 61%
BE 0.58 D 0.00 0.00 0.15 0.10 0.16 5.47 1.04 6.51 84%
BG 5.21 0.00 D 0.00 0.15 0.00 0.02 7.20 1.05 8.25 87%
CY 0.00 0.00 0.00 D 0.00 0.00 0.00 0.00 0.00 0.00 0%
CZ 35.61 0.04 0.00 0.00 D 0.05 0.07 70.11 6.26 76.37 92%
DK 0.02 0.00 0.00 0.00 0.00 D 0.00 0.12 0.70 0.81 14%
UK 0.00 0.28 0.01 0.03 0.01 0.27 D 2.15 1.85 4.00 54%
IMPORTS 100.75 11.00 4.54 0.06 35.65 4.93 11.67
TOTALS 740.27 419.28 1,159.56 64%
horizontally, we see the exports of Austria (AT) to the rest EU countries. Hence, Austria
exports 3.04 m Euro and 3.54 Euro worth of skiing goods to Belgium (BE) and Bulgaria (BG)
correspondingly. In the same manner, reading vertically we can identify the imports. Thus the
Czech Republic imports 18.99 m Euro and 0.15 m Euro worth of skiing goods from Austria
(AT) and Belgium (BE) correspondingly. Finally, by adding up horizontally and vertically, we
find the total exports and imports for each country within the European international trade.
The total of imports and the total of exports are obviously the same within the EU. In the
trade of snow skis in the EU, the most important relationship is between Austria and
Germany, the former exporting 81 m Euro of goods to the latter, accounting for 11% of intra-
EU exports. In terms of total world exports, the most important exporters are Austria and
France accounting for 396 m Euro and 296 m Euro of snow ski exports. However, although a
big proportion of the Austrian exports (61%) stays within the EU, France's trade is more
evenly divided with only 51% going towards EU countries. The total exports of all the EU
countries equal 1160 m Euro. From this, 740 m Euro, or 64% of the total is directed towards
other EU countries, with the remaining 36% going towards non-EU destinations.
Table 14: Foreign trade in ski and ski equipment in m Euro. D stands for domestic. Red
bars indicate hidden countries
Source: SIRC, UN.
Finally, Table 15 summarises the percentages of worldwide exports directed towards intra-
European trade. It is apparent that there is very high export integration within the EU. Overall
64% of snow skis, 71% of sport equipment and 66% of overall sport commodities exports
occur within the EU; in other words, two thirds of the Member States’ sport exports are intra-
EU-exports.
Study on the Contribution of Sport to Economic Growth and Employment - 48 -
snow ski
sport
equipment
(36.4)
sport
commodities
AT 61% 65% 64%
BE 84% 97% 92%
BG 87% 81% 89%
CY 0% 88% 38%
CZ 92% 90% 86%
DK 14% 75% 71%
EE 100% 35% 64%
FI 62% 59% 58%
FR 51% 62% 66%
GE 66% 70% 67%
GR 82% 51% 48%
HU 93% 72% 82%
IE 18% 49% 79%
IT 68% 65% 56%
LA 90% 38% 64%
LT 94% 62% 79%
LU 89% 99% 86%
MT 0% 22% 93%
NL 57% 85% 64%
PL 65% 72% 81%
PT 0% 76% 87%
RO 100% 96% 96%
SK 84% 83% 93%
SL 65% 61% 57%
ES 90% 83% 52%
SE 15% 50% 55%
UK 54% 75% 56%
TOTAL 64% 71% 66%
Table 15: Shares of exports staying within the EU
Source: SIRC, UN.
6.7 Additional Service and Goods Data
In addition to UN-service data, OECD service data (OECD (2012a)) was used. This turned
out to be useful as for some reason these two data sets are not equally loaded with
information. As an example, exports of CPA 45, Construction, was not reported in UN data,
but is available in the OECD data base. To stay as consistent as possible, UN data was used
preferably.
Foreign Trade of goods is not reported in the UN data base. Therefore we used the OECD
Structural Analysis Statistics (STAN) data base (OECD (2012b)). Thus foreign trade of all
CPA divisions from 01 to 95 were covered for both sport relevant and total numbers.
Study on the Contribution of Sport to Economic Growth and Employment - 49 -
6.8 Further Calculations
Export data is used in the model since they are valued as fob (free on board) while imports
are cif (cost of insurance and freight). Thus export values represent the good’s price only
(plus transport to the ship/truck) while import values include substantial additional costs.
There is the theoretical drawback to this in that countries have an incentive to register
imported goods as they might be subject to customs duty while exports might leave the
country unnoticed. This objection, however, is unjustified for the EU.
Exports of goods originate from OECD STAN (OECD (2012b)) and are generally complete
and fully available for all 27 EU countries. There is a problem, however, as several CPA
divisions are aggregated. These are 15 and 16, 17 to 19, 21 and 22, and 36 and 37. The
easiest and most intuitive solution was the distribution of these aggregated values according
to the ratios of the respective divisions in the IOT. For example, Germany exports CPA 15,
Food and Beverages, worth 24.5 billion Euro and CPA 16, Tobacco Products, worth 1.7
billion Euro to other EU-members. Therefore all aggregated exports of CPA 15 and 16 to
other EU-members were disaggregated using shares of 24.5/26.2 = 93.5% for 15 and the
remaining 6.5% to 16.
Another characteristic of the STAN database is that there is no entry for Belgium, but only
Belgium plus Luxembourg and Luxembourg alone. This issue was solved by simply
subtracting the values for Luxembourg from the combined totals for Belgium and
Luxembourg.
The biggest problem of obtaining data for foreign trade in services was its incompleteness. If
neither UN nor OECD data were provided, they had to be approximated. Depending to the
type of service, different strategies were followed here:
Total IOT-exports of CPA 63: Supporting and auxiliary transport services: travel
agency services, was distributed according to the mean of CPA 55, 60, 61, and 62,
being hotels and restaurants, land, water, and air traffic.
For CPA 67: Services auxiliary to financial intermediation: the total exports reported in
the national IOT were distributed in the same way as CPA 65, Financial
intermediation services as they should be closely related.
For CPA 90: Sewage and refuse disposal services: the available data of other
countries showed that they are almost exclusively distributed to large neighbouring
countries.
For exports of CPA 92: Recreational, cultural and sporting services: these were
distributed according to the exports of CPA 55, Hotel and restaurant services.
For exports of CPA 95: Other Services: these were distributed according to the mean
of all services.
In some cases an assumption was made that the unknown export structure of a
country, A, is the same as that of another country, B. If such a closely related country
existed, it was often the case that most of country B’s exports actually go to country
A. For instance, there were no data available for the structure of UK’s export of CPA
50, Trade, maintenance and repair services of motor vehicles and motorcycles. Data
for Ireland showed that around 50% of its CPA 50 exports go to the UK.
Study on the Contribution of Sport to Economic Growth and Employment - 50 -
After this stage, two export tables between all EU-members on CPA-2 digit basis were
available: one containing all goods and services, one just the sport-related ones. The sport-
related values were then subtracted from the values in the corresponding original categories
to avoid double counting. For example, France exports 6452 m Euro of CPA 01: Products of
agriculture, to EU members. Out of these, 48 m Euro are sport-related. Thus 6404 m Euro
remain in the non-sport part of CPA 01, while 48 m Euro are reported as sport-related exports
of CPA 01. Linking these two tables together created the complete foreign-trade matrix with
separate sport and non-sport entries.
This matrix had to be adjusted to the values in the national IOTs for two reasons:
1. The IOT reports different imports/exports to/from EU members to the numbers in the
above derived foreign-trade matrix.
2. The IOT reports aggregated imports/exports only, with no reference to intra-EU
foreign trade. France, for example, reports imports from within the EU plus all
imports, but in the case of exports, only the total numbers are given.
The values reported in the IOT were changed as little as possible as such changes can have
far-reaching consequences.
Study on the Contribution of Sport to Economic Growth and Employment - 51 -
7 Remarkable Matters
7.1 Prior Publications
A leaflet (EU-Commission (2011)) with results on the four already available national IOTs:S
was published. The results reported there were partly different to those in the MRIOT:S.
There are several explanations for this.
The MRIOT:S uses a common methodology for 27 Member States. This includes the
UN data base as unique source for foreign trade data. Otherwise the 3 dimensional
data cube for foreign trade (27 sending countries by 27 receiving countries by 94
goods) would be impossible to handle. Therefore in the equation Import + Production
= Export + Consumption features two variables which are different in the MRIOT:S
compared to the national IOTs:S. Production and consumption data thus had to be
adapted in some occasions.
Cyprus reported for 2004, Poland and the UK for 2006 in the above publication while
the MRIOT:S is based on 2005. Some of the differences originate from these
deviations.
The main difference between the UK-figures in the leaflet in this study is that sport-
related trade was not used in the former.
The biggest variations are reported for Austria. The specific issue here was that until
2011 there were several definitions of a “sport tourist” used in Austria. To interpret the
institutions’ calculations properly, one always had to bear in mind the relevant
definition. In autumn 2011 it was decided to harmonise all definitions and use just a
single one. Although this new definition is close to the one used in the previous
calculations here, there is an important difference. This can be best illustrated with an
example. If a German family decides to go on a skiing holiday in Austria, under the
new definition only the members of the family that ski will count as sport-related. If
only one parent skis while the other one takes care of two young children, there is
only one sport-related tourist out of a family of four that will count as sport-related.
Economically it would still make sense to integrate the three other guests too as they
would not be in Austria without the skiing person, but the responsible institutions
decided against it. Thus there are two versions of Austria’s 2005 sport-related
economy with the one used for the MRIOT:S using the more restrictive definition. This
will also be used in future calculations.
7.2 German Data
For the EU-wide MRIOT:S of this study the four complete national IOTs:S of Austria, Cyprus,
Poland, and the UK were available and could be used. In all other cases it makes use of
proxy IOTs:S, which approximate national IOTs:S as closely as possible. These proxy IOTs:S
serve one purpose only: the calculation of the MRIOT:S. They are not meant to substitute
fully-fledged national IOTs:S in their function as stand-alone tools for single countries. It is
also planned that future national IOTs:S will replace these approximations to improve the
quality of the MRIOT:S.
In this respect data on the German sport economy deserve special attention. Even though
there are relatively recent data available (see e.g. Meyer, B. / Ahlert (2000) or Weber,
Study on the Contribution of Sport to Economic Growth and Employment - 52 -
Schnieder, Kortlüke, and Horak (1995)) it was decided to conduct a survey on consumer
expenditure on sport. This will be used to calculate a German IOT:S in the near future.
Since some aggregated national results were already published (Preuß and Alfs (2012)),
these data were used for calculating the German proxy-IOT:S for this study. Therefore the
survey data is the basis for the proxy. Without that survey data there would be no German
IOT:S as the proxy cannot serve this purpose.
However the survey data had to be adapted to the needs of the MRIOT:S. The three most
important issues were:
The MRIOT:S is based on the year 2005 while the survey took place from 2009 to
2011.
The published survey data are highly aggregated.
Sport-related tourism (“Fahrten (ohne Urlaub)” and “Sportreisen” meaning “Trips (no
vacation)” and “Sport-related travel”) was too high to fit into the German IOT.
After dealing with these matters the dataset proved to be very useful.
7.3 Input-Output Table: Sport of France
A short summary of the calculation of the French IOT:S will be provided here, as this case is
rather different from most other countries. France provides very detailed official information
about the economics of sport in Le Haut Commissaire à la Jeunesse, Ministère de la Santé
et des Sports (2009). This data, however, requires some additional work as it was not
prepared in such a way that it would readily fit into an IOT:S.
Table 16: Sport related expenditures in France in 2005
Private households
15.2 bn Euro
Public households
12.1 bn Euro
Companies, media rights
1.4 bn Euro
Source: Le Haut Commissaire à la Jeunesse, Ministère de la Santé et des Sports (2009,
page 2.
Sponsorship, as always, had to be excluded as this money is spent by sport clubs again and
would thus be double counted. Expenditures of private households are reported in more
detail, but still rather aggregated.
Study on the Contribution of Sport to Economic Growth and Employment - 53 -
Table 17: Expenditures of French private households in 2005 in more detail
Clothes and shoes
3.8 bn Euro
Consumer goods
2.2 bn Euro
Other goods
2.8 bn Euro
Services
6.4 bn Euro
Source: Le Haut Commissaire à la Jeunesse, Ministère de la Santé et des Sports (2009,
page 2).
Employment figures in heads are reported in item 6 of the publication. NACE 2.0 codes are
given below the table in the publication and could be converted back to NACE 1.1 used in
this study (see Table 18). The statistical definition of sport is outstanding as there are more
persons employed than in all other categories together. Retail trade, the second largest
category, also employs more persons than all smaller categories together.
Speaking in terms of the three principal sectors, production appears only as NACE 35 and 36
while services comprise the rest of the table. Therefore nearly 90% of sport-related
employment in France is generated in services (see section 9 for a country comparison). This
imbalance can be explained in a number of ways. One possibility is that the vast majority of
sport-related goods are imported and only the services are provided in France. Although
sport-related imports are reported to be higher (see below), the difference is not large
enough to explain the distribution in employment. Another explanation relates to the fact that
employment is measured in heads, not full-time equivalents. Part-time employment in trade
is common. Sport clubs account for 74,296 employees in NACE 92.6. It can be assumed that
there many part-time jobs, thus leading to many more heads employed than full-time
equivalents. However, the discrepancy between production and services is too large to be
explained by this alone. It is possible that many French products are not counted as sport-
related officially, i.e. the official French definition of sport is narrower in the production sectors
than in services. To clarify these issues, a fully-fledged national IOT:S is recommended.
These employment data were then used to estimate sport-related gross value added and
production value by applying the ratio of the original (sport plus non-sport) sectors.
Study on the Contribution of Sport to Economic Growth and Employment - 54 -
Table 18: Employees in heads, estimated gross value added, and estimated production
value in the French sport industry 2005
NACE 1.1
Employees
in heads
Gross value
added, bn €
Production
value, bn €
35 Prod. of other transport equipment
12,058
0.767
4.403
36 Prod. of furniture; other manufactured goods n.e.c.
7,032
0,270
0.803
52 Retail trade services
50,234
1,817
2.974
71 Renting services of machinery and equipment
1,502
0,216
0.415
92.6 Statistical Definition of Sport
91,773
6,344
12.902
93 Other services
9,650
0,317
0.447
Source: Employees: Le Haut Commissaire à la Jeunesse, Ministère de la Santé et des
Sports (2009), page 4. Gross value added and production value: SpEA 2012, own
calculations
A summary of foreign trade as reported in item 4 of the French publication transformed into
NACE 1.1 is given in Table 19. NACE categories unfortunately are not exactly the same as
for employment. This, however, shows that there is sport-related production in other
categories than in 35 and 36 – otherwise all exports of category 18, 19, and 29 must have
been imported first. There is demand for clothes and shoes amounting to 3.8 bn Euro (see
Table 17) which cannot be covered by imports. Thus there has to be a considerable sport-
related production in categories 18 and 19 which does not show up in the data of Table 18.
Table 19: Foreign trade of sport-related goods in France in 2005
NACE 1.1
Exports
Imports
18 Wearing apparel; furs
138.5
260.5
19 Leather and leather products
213.1
480.6
29 Machinery and equipment n.e.c.
53.9
88.1
35 Prod. of other transport equipment
1519.9
1221.4
36 Prod. of furniture; other manufactured goods n.e.c.
246.2
232.7
Others
584.1
894.9
Total
2755.7
3178.2
Source: Employees: Le Haut Commissaire à la Jeunesse, Ministère de la Santé et des
Sports (2009), page 3.
All other data in the above tables were treated similarly:
Values were entered in the appropriate cells of the IOT:S,
Differences were calculated:
o import + production = export + consumption (+ capital formation)
o total supply = total use
Study on the Contribution of Sport to Economic Growth and Employment - 55 -
o total intermediate consumption + gross value added = production value
o production Value + import = total supply
o intermediate consumption + export + consumption (+ capital formation) = total
use
Missing values were calculated by suitable methods (e.g. ratios of gross value added
to production value in original categories were applied etc.).
Thus values for categories 18 (Wearing apparel; furs), 19 (Leather and leather products), 29
(Machinery and equipment n.e.c.), 35 (Prod. of other transport equipment), 36 (Prod. of
furniture; other manufactured goods n.e.c.), 52 (Retail trade services), 64 (Media Rights), 71
(Renting services of machinery and equipment), 92.6 (Statistical Definition of Sport), and 93
(Other services) could be calculated such that they fulfil all requirements of an Input-Output
Table. For 75 (Public Administration), 80 (Education), and Health (85), international data
bases (see section 6) were used. The remaining services plus category 45, Construction,
were approximated by the according shares of the UK-economy.
The result was an IOT:S of France with all publicly available data inserted. Although some
more production-side values could be calculated during the process, the vast majority of
gross value added and production value remain in the services leading to the results in the
strength-weakness analysis in section 9. A fully-fledged IOT:S is required to overcome these
issues.
7.4 Issues related to Input-Output Tables
Although the availability and standardisation of national IOTs has improved substantially
even during the lifetime of this project, there are some problems which should be mentioned.
One of them was the already noted NACE x NACE IOTs of Denmark, the Netherlands, and
Finland. Even though they are useful in many cases, they are not a perfect match with the
standard CPA x CPA IOTs of the remaining EU-members.
Exports of services are sometimes not reported: most remarkably this is the case for
France’s in CPA 55, Hotels and restaurant services. These services report a total use of
more than 76 bn Euro, but there are no exports listed in the French IOT. This could arise from
the interpretation that the service was provided in France and thus it is not considered an
export. In most other countries however (e.g. in Germany), it is considered to be one, if it is
demanded by a foreign guest. Also in the UN-foreign trade data base (see chapter 5.3) every
country’s CPA 55 reports exports to almost all other countries. So there was the dilemma of
which data to use. As an IOT is a tightly woven web, changes in one entry can affect many
others, in the worst case leading to a chain reaction rearranging the whole IOT. Thus the
IOTs were retained as they were whenever possible.
Reporting of CPA 75, Public administration: In Spain and Romania CPA 75 is exclusively
demanded by the government. There is no intermediate or private demand of any kind
reported. In most other countries however, one can find positive entries in these categories,
often reaching several billion Euro, or up to 6% of total consumption. In Austria, the Czech
Republic, Finland, and Italy the share of private consumption in total consumption is clearly
Study on the Contribution of Sport to Economic Growth and Employment - 56 -
less than 1%. It seems as if there can be a margin of discretion what can be reported as
privately demanded public administration.
This situation is not so harsh but still observable in the case of CPA 80, Education, and CPA
85, Health, where the share of private consumption in total consumption can vary between
4% and 36% and 8% to 53% respectively. It is questionable whether these differences can
be explained by differences in the public systems alone.
Inappropriate negative entries in the IOT are frequently reported. For example, Romania’s
CPA 60, Land transport, lists imports of -252 m Euro.
The IOT of Luxembourg contains some confidential data. They were estimated by using
information from Belgium.
The sum of intermediate goods plus taxes less subsidies does not equal total intermediary
consumption in many of Lithuania’s CPA categories from 64 to 92.
No values are reported for CPA categories 90 to 95 in Romania.
Finnish land and water-transport (CPA 60 and 61) report negative values.
Private consumption of basic metals (CPA 27) and exports of insurances (CPA 66) are
negative in Denmark.
7.5 International Trade Data
In the case of International Trade data, the greatest difficulty so far was the creation of a
matrix that can process the UN data content. This difficulty has been negotiated. The most
challenging task in the immediate future remains the collection of appropriate detail in service
data, so that a sport element can be derived.
Although all countries have problems reporting service-related foreign trade data, Spain,
Sweden, and the UK have to be mentioned as particularly problematic in the UN data.
Improvement of foreign-trade data availability for these three countries would increase the
quality of the model as one could rely on one data source only without having to merge UN
with OECD service data.
Study on the Contribution of Sport to Economic Growth and Employment - 57 -
8 Employment
Employment effects were computed in heads since data of full-time equivalents are
incomplete. Basic data came from Eurostat Structural Business Statistics (retrieved in March
2012) where NACE activities 10 to 74 are covered. The separation between sport and non-
sport was done by “structure transfer” a standard method used by the national statistical
offices. This simply means that the ratio of value added to employment of a classification is
used for its sub-classifications too. Thus we assumed that the value added per employee
within one 2-digit category is the same for sport and for non-sport goods; whether a building
is sport- related or not does not make a difference for value added. As the correlation
coefficient was found to take on values clearly above 90% for the sub-sets in the SBS, this
method seems to be very appropriate for the sport- and non-sport sub-sets too. Employment
of the remaining goods and services was calculated as the difference between total
employment (from Eurostat, Labour Force Survey) minus the aggregated SBS-employment
(of NACE 10 to 74) split according to value added. It is however possible that SBS and LFS
employment data differ since. For the case of Austria, Statistics Austria is only required to
include companies with a yearly turnover of more than 10,000 Euro in their SBS. Whether
this rule is valid for other EU-countries could not be clarified.
Employment data for Poland and the UK were delivered by the research teams who
calculated the respective national Sport Satellite Accounts. This data is likely to be modelled
according to the special characteristics of those countries.
In this chapter, nationwide aggregate sport-related employment is discussed. For sectoral
data see chapter 14 and the Annex.
The definition of 92.6 (in the Vilnius Definition known as “Statistical Definition of Sport”)
contains everything named in the CPA classification of national accounting as “Sport”.
Study on the Contribution of Sport to Economic Growth and Employment - 58 -
Figure 8: Statistical Definition: share of national employment, in % of heads
Source: SpEA, 2012.
According to this categorisation UK, Cyprus, and Malta achieve the highest values within the
EU-27 (see Figure 8). Greece, Germany, Slovenia, Ireland, France, Austria, Italy,
Luxembourg, and Poland are also above the EU average of 0.31%. It seems notable that
these are mainly countries with high GDP or classical holiday destinations. The Nordic
countries as well as many eastern countries are found below the average together with a few
others. However, data is not always perfectly comparable. More national SSAs would
certainly bring clarity here.
The Narrow Definition of Sport comprises everything of 92.6 (Statistical Definition of Sport)
plus all goods and services that are needed to do sport, thus all inputs to sport. Values
therefore must be higher (see Figure 9). The shares of national employment within this
definition are more evenly distributed. There is a group of small countries, Luxembourg
(3.70%), Austria (3.21%) and Slovenia (2.43%) which rank first, being a result of sport
tourism and other sport-related services. Employment in the narrow definition is also in well
above the average in Finland, Estonia, and Cyprus. Most other countries achieve an
employment share near the EU mean value of 1.49%. Whether Greece, Sweden, and Italy
really drop so far back compared to the Statistical Definition of Sport discussed in the above
paragraph can only be answered when national IOTs:S are available for them.
Study on the Contribution of Sport to Economic Growth and Employment - 59 -
Figure 9: Narrow Definition: share of national employment, in % of heads
Source: SpEA, 2012.
The Broad Definition of Sport includes the Narrow Definition of Sport and in addition all
goods and services that need sport as an input. This includes the hotel industry, sports
medicine, sport journalism, and so on. Its employment effect is shown in Figure 10.
Luxembourg’s result (5.63%) has to be interpreted with care. As a centre for financial
services, there are many consumers from Belgium, France, and Germany who work and buy
goods and services there but live abroad. So there is a substantial effect from foreign
residents which is then assigned to residents of Luxembourg only. A national IOT:S would
certainly shed some new light on that topic.
The other outstanding result, Austria (5.38%), is caused by its exposure to winter tourism and
the related employment in hotels and restaurants which are only part of the broad definition.
The importance of winter tourism for Austria (of which a large part is sport-related) is
reflected in the fact that in the winter months of 2005 (November, December, January,
February, and March) 9.1% of all overnight stays in the EU were reported by hotels in Austria
(Eurostat Tourist data base). Only much larger countries like Spain, Germany, the UK and
Italy show higher numbers. While Austria produces these 9.1% of overnight stays in winter, it
represents only a share of1.8% of employees in the EU (Eurostat, Labour Force Survey).
Therefore winter tourism contributes disproportionally high to Austrian employment in hotels
and restaurant services compared to the rest of the EU.
Germany, Finland and Slovenia have sport-related employment according to the broad
definition representing more than 3% of total employment. Estonia, Cyprus, Denmark,
Slovakia, UK, Ireland, and Malta have values slightly higher than the EU average of 2.12%.
Most other countries reach values just below the EU average.
Study on the Contribution of Sport to Economic Growth and Employment - 60 -
Figure 10: Broad Definition: Share of national employment, in % of heads
Source: SpEA, 2012.
Positions of EU countries do not change substantially when looking at the Narrow or the
Broad Definition of Sport as indicated by a correlation coefficient of 0.93 between the ranks
of the countries in each definition. In the Statistical Definition, though, several countries are in
a partially quite different position (correlation coefficient between the broad and the narrow
definition is only 0.31). UK, Malta, and Greece, for instance, change from having the highest
sport-related percentages on the narrow definition to positions close to the EU average on
the broad definition.
The scatter-plot shows the employment effects of the three categories (Statistical, Narrow
and Broad Definition of Sport). The x-axis illustrates the (log of the) GDP per person of the
EU countries while the y-axis indicates the share of employment in sport. Hence a 1%
increase of GDP per capita in a country is expected to increase the share of sport-related
employees by a 0.0061 per cent in the broad definition.
17
That is, if a country’s GDP per
capita is twice that of another country the increase equals 100%. The expected difference in
share of employment in sport is thus 100 x 0.0061 = 0.61 per cent. However, Luxembourg
and Austria, having more than 5% of employment shares, pull the regression line upward. A
detailed regression analysis would be necessary to deal with these outliers
18
, but that would
be out of the scope of the study.
The same regression results hold true for the narrow and the statistical definition with values
of 0.0027 and 0.0009 per cent per 1% increase in GDP.
17
Due to this triangular shape of the point-clouds, the variance of y is not constant along x. Thus p-values cannot be interpreted
meaningfully and were accordingly not computed. Although the regression line has no explanatory power, it still serves as the
best description of the point cloud according to the method of least squares.
18
“Outliers” here means that the data points are very different from the rest. It does not indicate wrong measurements!
Study on the Contribution of Sport to Economic Growth and Employment - 61 -
Figure 11: Employment shares in sport and GDP per capita
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 62 -
9 Strength/Weakness Analysis in a Country Comparison
Strength and Weakness Analysis is an instrument originating in business economics which
helps an organisation to identify both internal strengths and weaknesses that it faces in the
competition with others. An organisation as the unit of analysis can be replaced by a country
for our purposes. Results and findings on the grounds of economic studies are brought into a
structured and communicable form. Strength and Weakness Analysis is thus a form of
expression of results gained with any appropriate methods and is not a method of analysis
by itself. In outlining the strengths and weaknesses, approaches for developing strategies
can be found (see Fischer, Pfeffel (2010), p. 92 et seq.).
Strength and Weakness Analysis therefore is a situation assessment of internal factors that
provides insight into a country’s resources and capabilities within its competitive
environment. In a broader concept, the analysis of strengths, weaknesses, opportunities and
threats (SWOT Analysis) information is grouped into two main categories: internal factors and
external factors. The external factors are the opportunities and threats presented by the
external environment. These may include global macroeconomic matters, technological
change, and socio-cultural changes. Analysing these external factors goes beyond the scope
of this study.
The internal factors can be viewed as strengths and weaknesses depending upon their
impact on the country’s objectives. What may represent strengths with respect to one
objective may be a weakness for another. Strengths describe the positive attributes, tangible
and intangible, which are internal to the country and add value or offer the country a
competitive advantage. These are all within the country’s control. What does it do well, what
resources does it have? What advantages does it have over its competition?
Weaknesses are factors that are within the country’s control that detract from its ability to
obtain or maintain a competitive edge. Weaknesses can include limited resources, lack of
access to skills or technology, inferior service offerings, or poor location. These are factors
that are under the country’s control, but, for a variety of reasons, are in need of improvement
to effectively accomplish an objective (see Chelst, Canbolat (2012), p. 520 et seq.).
Strength and Weakness Analysis can be applied in the form of comparing countries that
compete with each other in a market, as the Member States of the European Union. A
ranking in certain areas illustrates relative strengths and weaknesses of a country compared
to the other countries considered.
The concept applied below for the Strength and Weakness Analysis of the sports market of
the EU Member States is a relative one in a twofold sense. First, strengths and weaknesses
are attributes out of a ranking of the Member States. Second, the factors considered are the
share of sport-related products in the value added of a product category of the single country.
The ranking position of a country therefore does not reflect economic strength, not even in a
per capita sense. A relatively less rich country has the same chances to get a high rank as a
relatively rich country, as long as the share of sport-related products in a product category is
Study on the Contribution of Sport to Economic Growth and Employment - 63 -
relatively large nationally. Strength and weakness thus means strength and weakness of
sport in a product market compared to other countries of the European Union. This is an
adequate concept for looking at the impact of sport on the economy within the country's
capabilities. The absolute size of a product market inside a country or within the single
market is not considered in this context as the economic importance of sport in a product-
differentiated national market is examined.
9.1 Relative Strength and Weakness in the Goods and Services Sectors
In what follows, low numbers mean a high ranking ranging from 1 to 27. The countries of the
European Union were ranked according to their share of sport-related production in the
corresponding product markets. A ranking of one, for example in sports nutrition, means that
the share of sports nutrition in the sector of production of foods and beverages of this country
is higher than in any of the other countries. A ranking of 27 means, that a country has the
lowest share of sports nutrition in the sector of production of foods and beverages, both in
terms of gross value added.
In a first assessment, the rankings in the single product markets were averaged for each
country over the two groups, goods and services. Trade, research and development, public
administration, education and health services are not considered within the two groups.
19
Germany has a very strong position in both the goods and services sectors. With slightly
greater relative strength in the goods sectors, Germany has high rankings for example for its
sports nutrition market and its manufacture of sport suits (outwear, ski suits, gloves, etc.).
High rankings in the service sectors come from sport tourism and sports insurance sectors.
The United Kingdom, Ireland, Austria and Poland have a high ranking in the services sectors
and, except for the United Kingdom, are somewhat lower ranked in the goods sectors. The
four countries have above average rankings in most of the good sectors, middle rankings for
example in the sports nutrition and sport suits sectors and some low rankings in the
manufacture of transport equipment, such as sailboats. All three countries have relative
strengths in the service sectors.
Figure 12 shows averages of the rankings in the respective sectors, so that extreme values
do not appear, as a country with a value of 27 would have the worst ranking in all goods or
service sectors. Being close to the 45 degree line means an equal relative
strength/weakness of the goods and service sectors. Being left/above of the 45 degree line
means a higher ranking in the goods sectors than in the service sectors and vice versa.
19
The goods sector includes CPA categories 1, 15, 17-19, 22-25, 28, 29, 33-36, and 45; the services sector includes CPA
categories 55, 60-66, 71, 74, 92, and 93.
Study on the Contribution of Sport to Economic Growth and Employment - 64 -
Figure 12: Ranking in the goods vs. the service sector of the EU Member States
Source: SpEA, 2012.
Slovenia and Estonia compare to Germany in the goods sectors but have a slightly lower
ranking in the services sectors. For both countries, nearly all rankings in the manufacturing
industry are above average. High rankings come for example from manufacture of sporting
equipment (e.g. sporting boats and surfboards). In the service sectors, both countries have a
number of good rankings.
Above average in both, the goods in the service sectors are the rankings for Cyprus and
Belgium. Printing of sport periodicals is a relative strength too. Also, Cypriot sporting
services, the core of sport-related economic activity, have a relative good ranking.
The group of countries with a medium range of rankings, equally in the services and goods
sectors, consists of Finland, Sweden and Latvia. Finland and Sweden have strength in sport
tourism in terms of spending of sport tourists on hotels and restaurants. Latvia has relatively
good rankings throughout the service sector. Another, closely related, group, but with better
rankings in the service sectors, is formed by Lithuania, the Netherlands, Malta and the
Slovak Republic.
On the other side of the 45°-line, there are those mid-range countries, which perform
(slightly) better when it comes to the production of sport-related goods.
Study on the Contribution of Sport to Economic Growth and Employment - 65 -
Below the line, where countries with good service-performance are placed, a majority of
small countries, with the exception of the UK and Poland, can be found. It seems that for
these small countries it is easier to provide sport-related services. If one assumes that the
production of goods provides substantial economies of scale, large, economically powerful
countries are certainly more favoured in producing goods. A second cause is that it is hard to
transport most services and none of them can be stored. So one has to produce them
regionally, no matter how small the economy is. Thus there is always a certain amount of
services produced per inhabitant (e.g. sport education), while production of goods is often left
to larger economies. Services thus have a heavier weight in smaller regions.
France and Luxembourg have an extreme position in this figure, as they have a very strong
position in the services sectors, comparable to Germany, but below average rankings in the
goods sectors. The reason for Luxembourg is its small size which leads to an absence of
production facilities. In the case of France, data availability is very much focused on services
(e.g. more than one half of the reported employees are listed in the various sport services of
the Statistical Definition of sport and more than half of the rest is listed in retail trade
services.) More details are given in section 7.3. Both countries underline the necessity of
fully-fledged national IOTs:S as only they can deal with such kinds of problems properly.
9.2 Conclusion of Strengths and Weaknesses
In order to set up a Strength and Weakness Analysis of the sport-related shares of the
product markets of the European countries, they were ranked according to their relative
shares of sport products in each sector, measured in terms of gross value added.
There are countries with a relative strength in both goods and services, above all Germany,
followed by the United Kingdom, Ireland, Poland and Austria, which are slightly better ranked
in the service sectors, and Slovenia and Estonia, which are slightly better ranked in the
goods sectors. Cyprus and Belgium have a balanced ranking when the goods and service
sectors are compared. Lithuania has its strength in the service sectors, whereas Bulgaria has
very good rankings on average in the goods sector, but average rankings in the service
sectors. The other countries have average rankings in both, the goods and the service
sectors. Sweden, Finland, Latvia, the Slovak Republic, Malta and the Netherlands have
better rankings in the service sectors than in the goods sectors and the other countries are
relatively stronger in the goods sectors.
It is noteworthy that almost all countries which perform better with sport-related services are
rather small. There are at least two plausible explanations: firstly, it is much easier to
transport and store goods than services, so the latter have to be produced locally, no matter
how small an economy is. Secondly, production of goods yields substantial economies of
scale, favouring large countries.
Study on the Contribution of Sport to Economic Growth and Employment - 66 -
10 Analysis of Growth Potentials
Sport represents a large and fast-growing sector of the economy and makes an important
contribution to growth and jobs, with value added and employment effects exceeding
average growth rates (see White Paper on Sport (2007), p. 10). A Sport Satellite Account
constitutes an important database to analyse the contribution of sport to economic and
productivity growth and the growth rates of the sport-relevant parts of the sectors
themselves. As growth and growth rates are dynamic approaches, this kind of analysis has to
be based on Sport Satellite Accounts in two different points in time in order to determine the
relative change in sport-related and overall output.
At the current state of setting up the first Sport Satellite Account for the European Union,
these calculations are not achievable. Alternatively the output multipliers that capture the
direct and indirect effects of an increase in final demand of the sport-related product markets
can be used as an indicator for the growth potentials of sport as they measure the economic
impact in terms of output growth, where output constitutes final demand and intermediate
consumption.
We will focus on relatively small (compared to other) sport-related business sectors that also
have a relatively high national multiplier effect. As they are small, their own growth potential
will in general be higher than in fully developed sport-related areas. The relatively high
multiplier effect additionally indicates a large share of the rest of the economy to benefit from
this growth through a considerable interdependence with other sectors of the economy.
Sectors that show a significantly lower share of sport-related services or production
compared to the European average will also be considered if the corresponding multiplier is
relatively high, as this indicates growth potential too.
10.1 Common Growth Potentials
10.1.1 Sports Nutrition
Sports Nutrition markets, for example protein-based bars, powders and beverages, exhibit
high growth rates worldwide. As shown in Table 20, Germany has a considerable sports
nutrition share in the foods and beverages markets, accounting for more than 1 % of German
food production. For the other EU Member States, however, the share of sports nutrition in
food production is much smaller. The indirect effects on the domestic industries are at the
same time relatively high. The multipliers are 2.0 or even larger for Finland, France, Hungary,
Italy, Poland and Spain. They are above 1.5 for almost all other countries. Since France does
not report production of sport-related food and beverages, its multiplier is neither shown in
the table nor used to calculate the average multiplier. As a market exhibiting high growth
rates itself, the sports nutrition market may represent an important growth potential in
European countries.
Study on the Contribution of Sport to Economic Growth and Employment - 67 -
Market
Prices, Mio €
% of total
Sector
AT 14.6 0.33% 1.65
BE 5.4 0.09% 1.63
BG 0.5 0.08% 1.96
CY 1.2 0.42% 1.91
CZ 2.0 0.09% 1.96
DK 1.9 0.05% 1.80
EE 0.4 0.19% 1.63
FI 3.0 0.13% 2.08
FR 25.6 0.00%
DE 326.6 1.02% 1.84
GR 15.3 0.34% 1.79
HU 0.8 0.05% 2.13
IR 16.4 0.39% 1.78
IT 1.8 0.01% 2.00
LA 0.3 0.04% 1.83
LI 0.3 0.05% 1.76
LU 0.7 0.12% 1.33
MT 0.6 0.65% 1.44
NL 2.3 0.02% 1.85
PL 14.9 0.24% 2.26
PO 0.5 0.02% 1.85
RO 1.1 0.02% 1.84
SK 0.7 0.08% 1.74
SL 0.5 0.11% 1.74
ES 1.6 0.01% 2.21
SE 7.0 0.19% 1.73
UK 147.7 0.51% 1.72
EU 593.6 0.30% * 1.83 **
* GVA-wei ghted EU-wi de average
** Unwei ghted a verage, excluding France.
Country
Gross Value Added
Domestic
Multipliers
CPA 15: Sport related Food and Beverages
Table 20: Sports Nutrition, Gross Value Added and Multipliers
Source: SpEA, 2012.
10.1.2 Sports Insurance
There are a number of sport insurances already existing on the insurance market, for
example winter sports insurance, risk sports insurance, or infrastructure insurance for sport
events. Together with pension funding services for professional athletes, this insurance
branch may further expand, as can be seen in Table 21. While sports insurance and pension
funding has a share of 1% and higher in Austria, Cyprus, Finland, Germany, Ireland and
Malta, this share is much lower in most of the other countries. Given the high risks
Study on the Contribution of Sport to Economic Growth and Employment - 68 -
Market
Prices, Mio €
% of total
Sector
AT 34.6 1.16% 1.66
BE 4.8 0.17% 1.83
BG 0.6 0.57% 1.89
CY 2.8 3.17% 1.62
CZ 0.9 0.33% 2.22
DK 4.1 0.18% 1.57
EE 0.3 0.79% 1.72
FI 7.7 1.37% 1.71
FR 88.2 0.26% 1.86
DE 239.2 2.10% 2.23
GR 1.9 0.25% 1.47
HU 3.1 0.63% 1.85
IR 97.4 2.78% 1.73
IT 4.0 0.05% 1.91
LA 0.1 0.25% 1.75
LI 0.0 0.00%
LU 3.0 0.49% 2.07
MT 1.8 3.38% 1.38
NL 8.1 0.08% 1.60
PL 5.5 0.26% 1.66
PO 8.7 0.63% 1.49
RO 0.5 0.22% 1.59
SK 1.1 0.23% 1.55
SL 1.3 0.56% 1.79
ES 40.2 0.78% 1.86
SE 24.4 0.91% 1.37
UK 45.3 0.26% 2.11
EU 629.5 0.68% * 1.75 **
* GVA-wei ghted EU-wi de a verage
** Unwei ghted a verage, excluding Li thua nia.
CPA 66: Sport related Insurance and Pension
Funding Services
Country
Gross Value Added
Domestic
Multipliers
embedded in many sport activities, insurance companies could seek new growth potential in
insuring sport risks.
Table 21: Sports Insurance and Pension Funding, Gross Value Added and Multipliers
Source: SpEA, 2012.
The indirect effects on domestic industries of an increased demand in sports insurance is
expected to be high too, as indicated by domestic multipliers around 2.0 for countries such
Study on the Contribution of Sport to Economic Growth and Employment - 69 -
as the Czech Republic, Germany, Luxembourg and the UK and above 1.5 for most other
countries.
10.1.3 Economic and Legal Consultancy
Activities such as legal advice, finance and accounting, consultancy and public relations
have still very low shares for sports people, sport clubs or professional athletes, except in the
United Kingdom.
Although a lot of the activities, of for example sport clubs, are at a semi-professional or
voluntary level and are not supported by consulting activities, the overall trend on increased
need for economic and legal consultancy
20
could also affect sport-related businesses.
Potential growth in this sector related to sport would have an important economic impact on
output of other products, as can be seen in Table 22. Domestic multipliers are below the
multipliers discussed in the previous two sections on average, but are still around or above
1.5 for most countries and are around 1.8 to 1.9 for Bulgaria, the Czech Republic and
Portugal.
20
The average annual growth rate of gross value added of legal and economic consultancy (M69 and M70, Nace Rev.2) was
three times higher than the average annual growth rate of gross value added of all Nace activities. See Eurostat, National
Accounts by 64 categories.
Study on the Contribution of Sport to Economic Growth and Employment - 70 -
Market
Prices, Mio €
% of total
Sector
AT 24.8 0.16% 1.62
BE 68.8 0.24% 1.72
BG 1.4 0.23% 1.85
CY 7.8 1.27% 1.22
CZ 1.2 0.02% 1.89
DK 6.1 0.05% 1.54
EE 1.6 0.28% 1.49
FI 2.8 0.04% 1.49
FR 6.5 0.82% 1.67
DE 41.8 0.02% 1.48
GR 1.2 0.03% 1.65
HU 4.8 0.08% 1.52
IR 216.2 2.43% 1.27
IT 5.8 0.01% 1.73
LA 0.6 0.13% 1.48
LI 1.4 0.21% 1.53
LU 4.0 0.19% 1.20
MT 2.5 0.87% 1.46
NL 8.2 0.02% 1.55
PL 190.4 1.49% 1.74
PO 1.0 0.01% 1.76
RO 3.6 0.83% 1.55
SK 2.1 0.09% 1.58
SL 2.3 0.13% 1.55
ES 0.0 0.00%
SE 0.0 0.00%
UK 1406.2 0.83% 1.59
EU 2013.1 0.25% * 1.56 **
* GVA-weighted EU-wi de average
** Unweighted average, excludi ng Spa i n a nd Sweden.
CPA 74: Legal, Financing, Accounting, Services, PR
activities for Sport Clubs and professional
Athletes
Gross Value Added
Country
Domestic
Multipliers
Table 22: Economic and Legal Consultancy for Sport Clubs and Professional Athletes
Source: SpEA, 2012.
10.2 Country Growth Potentials
In the discussion of growth potentials for selected sport-related products in the Member
States of the European Union we focused on industries that add to the previously considered
sectors in which sport-related products have a relatively small share in the corresponding
Study on the Contribution of Sport to Economic Growth and Employment - 71 -
sector, while indirect effects of an increased demand on the rest of the economy, as indicated
by the domestic multiplier, are relatively high.
The formal criterion for selecting sport-related products for potential economic growth was
that the products were chosen by the ranking of their domestic multiplier effects. First of all
they had to show a large difference between domestic and EU values in their share of gross
value added in their respective sector of the economy. Secondly, they also had to represent
relatively small markets. Sectors heavily depending on other sectors – such as land
transport, air transport or post and telecommunication services depending on growth of sport
tourism – were not chosen.
Common trends of the countries of the European Union can be found in the sports nutrition
market, which could face high growth rates for the majority of the countries, as the share of
gross value added of the production of sports nutrition is relatively small. The multiplier
effects on the intermediate consumption of other sectors of the national economies are at the
same time rather high. A similar constellation exists for insurance of sport activities and sport
events which indicates growth potentials of this sector as small shares in gross value added
contrast with the high risks in sport so that it could get more attractive to demand sport
insurances. The domestic multiplier effects in this sector are also relatively high with indirect
effects on the economies therefore considerable. The sectors legal advice, finance and
accounting, consultancy and public relations also have very low shares for sports amateurs,
sports clubs or professional athletes, which could indicate above average growth rates, with
indirect effects on the national economies comparably high.
Sport tourism, measured as the share of spending of sport tourists for hotels and restaurants
in total spending on hotels and restaurants bears potential growth for most of the
Mediterranean countries, as well as the Czech Republic, Denmark, Hungary, Latvia and
Lithuania. At the same time the respective domestic multipliers indicate considerable indirect
effects. A gap between the EU average and national shares in gross value added can also be
found in the activities of travel agencies in Austria, Belgium, Finland, France, Ireland, Latvia,
the Netherlands and Spain. Again, this sector has relatively high domestic multiplier effects.
As its absolute size is likely to be highly correlated with sport tourism, its ability to grow as a
single service is limited.
The majority of EU countries have relatively low shares of sport media in the media sector,
while increased demand for sport periodicals would induce sizeable intermediate
consumption in the rest of the economy, as indicated by domestic multipliers.
Study on the Contribution of Sport to Economic Growth and Employment - 72 -
11 Identification of Key Sectors
Following the theory of growth poles several sectors in an economy can play a key role as
drivers of regional growth. In this sector-oriented explanation of regional growth so-called key
sectors are responsible for uneven spatial development.
A key sector is mainly characterised as causing more stimuli to related sectors than it
receives from them. Growth stimuli are caused by backward (demand of inputs from other
industries) and forward (supply of inputs to other industries) connections with other sectors.
To identify key sectors different approaches have been developed. One of these approaches
comes from Rasmussen (see Hewings and Jensen (1986), Hübler (1979), or Miller and Blair
(1985)) who relates the production stimuli of one sector (to all the other sectors) to the
national average of production stimuli.
The results for the sport-related categories of the EU-27 are shown in Table 23. The green-
shaded fields, especially the dark ones, indicate key sectors in each country, i.e., CPA-
categories which spread more stimuli than they receive.
The table shows that there are three categories that play a vital role in many countries.
These are CPA categories 15 (Food products and beverages), 45 (Construction work), and
CPA 63 (Supporting and auxiliary transport services; travel agency services). This means
that those three categories have large forward and backward linkages and are therefore
strategically important to the countries.
The Rasmussen Index also shows that key sectors are also quite concentrated in CPA 50 to
66 (trade, hotels and restaurant services, transport sectors, financial intermediation and
insurance) in many countries. CPA 22 (Printed matter and recorded media) is also a key
product for 25 countries, although often not very much above the average. For all the other
categories national characteristics in the production chain and import linkages are
responsible as to whether a category plays a key role or not.
Study on the Contribution of Sport to Economic Growth and Employment - 73 -
AT BE BG CY CZ DK EE FI FR DE GR HU IE IT
1
Products of agriculture, hunting
and related services
1.04 0.95 1.04 1.31 0.96 0.69 1.05 1.19 0.66 1.00 1.03 1.19 1.20 0.86
15
Food products and beverages
1.14 1.11 1.18 1.40 1.17 1.24 1.10 1.31 0.66 1.18 1.28 1.40 1.23 1.13
17
Textiles
0.87 0.98 1.03 0.74 0.87 0.87 0.90 0.83 0.66 0.88 0.96 0.85 0.82 1.11
18
Wearing apparel; furs
0.76 0.81 1.02 0.79 0.73 0.77 0.94 0.74 1.18 0.80 0.99 0.93 0.73 1.11
19
Leather and leather products
0.87 0.74 0.89 0.73 0.71 0.73 0.77 0.77 1.00 0.76 0.88 0.87 0.71 1.17
22
Printed matter and recorded media
1.11 1.13 1.10 1.05 1.05 1.18 1.16 1.20 0.66 1.11 1.09 1.18 1.18 1.15
23
Coke, refined petroleum products
and nuclear fuels
0.94 1.02 0.99 0.73 1.03 0.98 0.75 1.02 0.66 1.04 1.23 1.08 0.94 1.07
24
Chemicals, chemical products and
man-made fibres
0.87 0.95 0.90 1.01 0.82 0.96 0.80 0.91 0.66 0.99 0.88 0.93 1.09 0.97
25
Rubber and plastic products
0.92 0.89 0.94 1.01 0.88 0.94 0.85 0.97 0.66 1.02 0.98 0.92 0.88 1.10
28
Fabricated metal products, except
machinery and equipment
0.99 1.02 1.03 0.79 0.98 1.00 0.94 1.09 0.66 1.07 1.20 0.93 0.89 1.14
29
Machinery and equipment n.e.c.
0.96 0.87 0.86 0.86 0.86 0.96 0.78 1.06 0.85 1.07 0.84 0.89 0.81 1.12
33
Medical, precision and optical
instruments, watches and clocks
0.84 0.79 0.85 0.75 0.79 0.91 0.84 0.92 0.66 0.93 0.77 0.82 0.96 0.93
34
Motor vehicles, trailers and semi-
trailers
0.91 0.84 0.61 0.73 0.97 0.75 0.73 0.74 0.66 1.19 0.74 0.87 0.75 0.94
35
Other transport equipment
0.89 0.87 0.97 0.88 0.86 0.89 1.03 1.05 1.23 0.94 0.88 0.97 0.74 1.10
36
Furniture; other manufactured
goods n.e.c.
0.97 0.81 1.02 0.74 0.92 1.00 1.11 1.03 1.13 0.99 0.95 0.94 0.69 1.17
45
Construction work
1.13 1.42 1.29 1.14 1.37 1.21 1.16 1.23 0.66 1.14 1.19 1.15 1.29 1.15
50
Trade, maintenance and repair
services of motor vehicles and
motorcycles; retail sale of
automotive fuel
1.07 1.16 1.03 1.01 1.10 1.04 1.03 1.06 0.66 0.92 0.97 1.13 0.95 1.14
51
Wholesale trade and commission
trade services, except of motor
vehicles and motorcycles
1.07 1.15 1.25 0.73 1.05 1.13 1.11 1.12 0.66 1.04 1.03 1.19 0.78 1.08
52
Retail trade services, except of
motor vehicles and motorcycles;
repair services of personal and
household goods
1.07 1.13 0.90 2.77 1.00 1.03 1.10 1.04 1.05 1.04 0.98 1.09 0.98 1.08
55
Hotel and restaurant services
0.99 1.07 1.03 1.01 1.06 1.15 1.14 1.13 1.19 1.03 1.09 1.27 1.16 1.04
60
Land transport; transport via
pipeline services
1.08 1.13 1.23 0.97 1.06 1.13 1.20 1.03 1.09 1.07 1.17 1.03 0.99 1.08
61
Water transport services
0.76 1.44 1.09 0.73 0.95 1.26 1.30 1.03 1.42 1.18 1.11 0.91 1.21 1.29
62
Air transport services
1.23 1.22 1.20 1.20 1.02 1.22 1.33 1.14 1.10 1.27 1.00 1.10 1.08 1.09
63
Supporting and auxiliary transport
services; travel agency services
1.28 1.20 1.25 0.94 1.25 0.84 1.41 1.16 1.13 1.17 0.87 0.99 1.42 1.15
64
Post and telecommunication
services
1.18 1.05 0.96 0.88 1.02 1.17 1.17 1.22 1.15 1.11 0.86 0.96 1.16 0.99
65
Financial intermediation services,
except insurance and pension
funding services
1.07 1.04 0.82 1.09 1.11 1.01 1.01 0.92 1.18 1.05 0.93 1.04 1.02 0.89
66
Insurance and pension funding
services, except compulsory social
security services
1.14 1.24 1.14 1.19 1.33 1.08 1.16 1.08 1.22 1.43 1.05 1.21 1.19 1.08
71
Renting services of machinery and
equipment without operator and of
personal and household goods
0.95 1.09 0.83 0.94 1.07 1.28 0.98 0.97 1.16 0.80 1.10 0.80 0.97 1.07
73
Research and development
services
1.05 0.97 0.83 0.73 0.75 1.03 0.94 0.77 1.22 1.01 1.13 0.92 0.80 0.99
74
Other business services
1.11 1.17 1.12 0.90 1.13 1.06 1.00 0.94 1.10 0.95 1.18 0.99 0.87 0.98
75
Public administration and defence
services; compulsory social
security services
0.96 0.87 0.96 0.89 0.95 0.97 1.00 1.00 0.94 0.90 0.96 0.85 1.04 0.57
80
Education services
0.82 0.76 0.81 0.81 0.82 0.91 0.92 0.88 0.84 0.82 0.81 0.84 0.91 0.57
85
Health and social work services
0.95 0.98 0.98 0.95 0.88 0.92 0.93 0.89 0.89 0.88 0.95 0.93 1.01 0.85
92
Recreational, cultural and sporting
services
1.04 1.17 1.11 1.01 1.12 1.12 1.10 1.07 1.17 0.99 1.12 1.19 0.97 1.04
93
Other services
0.97 1.10 0.90 0.92 0.91 0.82 1.05 1.03 0.97 0.64 0.91 0.96 1.07 0.89
Table 23: Rasmussen indices of the EU-27 countries
Study on the Contribution of Sport to Economic Growth and Employment - 74 -
LA LI LU MT NL PL PO RO SK SL ES SE UK
1
Products of agriculture, hunting
and related services
1.46 1.13 0.97 1.00 1.06 1.13 1.00 1.14 1.10 1.03 0.99 1.11 1.04
15
Food products and beverages
1.28 1.25 1.03 1.01 1.28 1.43 1.19 1.22 1.15 1.18 1.34 1.16 1.09
17
Textiles
0.99 0.93 1.04 0.76 0.89 0.86 1.00 0.82 0.81 1.01 1.02 0.85 0.89
18
Wearing apparel; furs
1.07 1.01 0.77 0.84 0.73 0.98 1.08 0.94 0.88 1.00 0.91 0.73 0.76
19
Leather and leather products
0.86 0.87 0.77 0.70 0.74 0.88 1.00 0.88 0.95 0.91 1.02 0.76 0.71
22
Printed matter and recorded media
1.11 1.10 0.77 1.06 1.12 1.19 1.06 1.09 1.13 1.22 1.12 1.31 1.09
23
Coke, refined petroleum products
and nuclear fuels
0.74 0.71 0.77 0.71 1.09 1.15 1.09 1.25 1.09 0.69 1.07 0.95 1.07
24
Chemicals, chemical products and
man-made fibres
0.80 1.15 0.82 0.81 1.00 0.92 0.89 0.97 0.89 0.89 0.96 0.94 0.97
25
Rubber and plastic products
0.80 0.99 0.97 0.90 0.96 1.02 0.96 0.90 0.96 1.00 1.05 0.96 1.03
28
Fabricated metal products, except
machinery and equipment
0.96 0.88 0.77 0.94 1.03 1.03 1.02 0.98 0.94 1.00 1.14 1.09 1.02
29
Machinery and equipment n.e.c.
0.81 0.78 1.00 0.77 0.96 0.91 0.85 0.86 0.91 0.95 0.92 1.07 0.96
33
Medical, precision and optical
instruments, watches and clocks
0.77 0.85 1.07 0.92 0.79 0.86 0.78 0.82 0.80 0.84 0.78 0.98 0.87
34
Motor vehicles, trailers and semi-
trailers
0.72 0.73 0.77 0.70 0.84 1.01 0.79 0.90 0.96 0.86 0.94 1.15 0.95
35
Other transport equipment
0.99 0.93 0.77 0.91 0.99 1.00 0.93 1.05 1.03 0.97 0.96 1.02 0.96
36
Furniture; other manufactured
goods n.e.c.
1.01 1.07 0.78 0.86 0.88 1.17 1.05 1.03 1.02 0.97 1.05 1.02 0.93
45
Construction work
1.19 1.16 1.18 1.15 0.69 1.24 1.34 1.17 1.34 1.36 1.40 1.13 1.31
50
Trade, maintenance and repair
services of motor vehicles and
motorcycles; retail sale of
automotive fuel
1.06 0.96 1.09 1.06 1.12 0.94 0.99 1.25 1.09 1.10 1.09 1.08 1.07
51
Wholesale trade and commission
trade services, except of motor
vehicles and motorcycles
1.23 1.03 1.17 0.70 1.05 1.14 1.11 0.95 1.10 1.15 1.02 0.67 1.19
52
Retail trade services, except of
motor vehicles and motorcycles;
repair services of personal and
household goods
1.15 0.94 1.18 1.05 1.07 1.01 1.06 1.02 1.04 1.01 0.95 0.67 1.03
55
Hotel and restaurant services
1.18 1.12 1.26 1.20 1.05 1.16 1.11 1.11 0.91 1.08 1.03 1.19 1.04
60
Land transport; transport via
pipeline services
1.06 0.98 1.01 0.98 1.04 1.12 1.11 1.09 1.08 1.08 1.10 1.09 1.14
61
Water transport services
1.12 0.92 0.93 0.70 1.23 0.63 1.28 0.99 0.76 0.97 1.27 1.17 1.05
62
Air transport services
1.07 1.32 1.19 1.29 1.26 1.13 1.20 1.01 1.07 1.08 1.05 1.15 0.99
63
Supporting and auxiliary transport
services; travel agency services
1.21 1.02 0.92 1.03 1.14 1.35 1.02 1.11 1.32 1.24 1.22 1.31 1.31
64
Post and telecommunication
services
0.98 1.02 0.97 1.12 1.11 0.63 1.10 0.90 1.02 1.14 1.09 1.25 1.01
65
Financial intermediation services,
except insurance and pension
funding services
0.95 1.05 1.54 1.72 0.99 0.99 0.92 0.76 0.92 0.96 0.80 0.94 0.94
66
Insurance and pension funding
services, except compulsory social
security services
1.22 0.71 1.60 0.97 1.10 0.63 0.96 1.06 1.03 1.21 1.13 0.92 1.34
71
Renting services of machinery and
equipment without operator and of
personal and household goods
0.95 1.00 0.92 1.18 1.04 0.98 1.00 1.20 1.13 1.02 1.02 1.06 1.04
73
Research and development
services
0.92 1.15 1.00 0.70 0.90 0.97 0.87 1.22 0.95 0.93 0.92 1.07 0.97
74
Other business services
1.03 1.08 0.93 1.02 1.07 1.10 1.13 1.03 1.04 1.04 0.61 0.67 1.01
75
Public administration and defence
services; compulsory social
security services
1.02 1.06 1.02 1.01 1.08 0.85 0.85 0.89 0.97 0.98 0.87 1.07 1.05
80
Education services
0.93 0.93 0.87 0.81 0.89 0.80 0.76 0.92 0.85 0.84 0.73 0.97 0.89
85
Health and social work services
0.98 1.08 0.97 0.87 0.91 0.91 0.96 1.04 0.98 0.92 0.88 0.90 1.04
92
Recreational, cultural and sporting
services
1.02 1.13 1.06 1.25 1.27 1.07 1.06 0.66 1.18 1.05 0.99 1.20 1.03
93
Other services
1.13 1.25 1.01 0.98 1.13 0.86 0.94 0.66 0.87 0.94 0.99 1.00 1.09
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 75 -
12 Range of products
In terms of economic stability and independency of a country special attention has to be
placed on the range of products offered in the country: the smaller the range of products
offered the more susceptible to risk and dependence on imports the country will be.
One method to quantify the range of products is to consider the number of zeroes in the
intermediate goods matrix of each country. The lower the number of zeroes, the more
autonomous and the more independent the country is.
Taking into account all 94 categories of the European MRIOT Sport (sport-relevant and not
sport-relevant categories) for the EU-27 countries the number of zeroes ranges from 1439
(United Kingdom) to 4859 (Romania), which corresponds to an amount of 16% to 55%.
Therefore Romania has to import lots of its intermediate goods necessary in the production
chain while the UK presents itself as the most autonomous country inside the EU.
Looking only at the sport-relevant parts of the table increases the dependency on imports for
all countries except the UK where 510 cells or 16% (of the 94 x 35 sport-related matrix) show
a value of zero. The most dependent country is again Romania with 2233 zeroes in its sport-
related intermediate matrix which corresponds to an amount of 68%.
Table 24 shows the number of zeroes for each country in absolute and relative terms for the
whole economy (94 sectors) as well as only the sport-relevant part of the economy (35
sectors). Grey fields indicate countries that are above the EU-27-average (31.3% for all
categories and 39.4% for the sport-relevant categories) which can be interpreted as an
above-average dependency or below-average autonomy.
Study on the Contribution of Sport to Economic Growth and Employment - 76 -
Zeros Share Zeros Share
Austria 1910 0.22 809 0.25
Belgium 2320 0.26 969 0.29
Bulgaria 2738 0.31 1678 0.51
Cyprus 4789 0.54 1920 0.58
Czech Republic 2653 0.30 1193 0.36
Denmark 1892 0.21 1104 0.34
Estonia 2602 0.29 1290 0.39
Finland 1856 0.21 1006 0.31
France 3606 0.41 1860 0.57
Germany 2830 0.32 1170 0.36
Greece 2845 0.32 1301 0.40
Hungary 1636 0.19 847 0.26
Ireland 2376 0.27 1130 0.34
Italy 1881 0.21 957 0.29
Latvia 2697 0.31 1368 0.42
Lithuania 3140 0.36 1476 0.45
Luxembourg 4310 0.49 1893 0.58
Malta 2007 0.23 1156 0.35
Netherlands 2756 0.31 1218 0.37
Poland 1855 0.21 837 0.25
Portugal 2606 0.29 1107 0.34
Romania 4859 0.55 2233 0.68
Slovakia 4675 0.53 2186 0.66
Slovenia 2716 0.31 1224 0.37
Spain 2431 0.28 1049 0.32
Sweden 3311 0.37 1461 0.44
UK 1439 0.16 510 0.16
Sport Goods
All Goods
Table 24: Product range of the EU-27 countries
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 77 -
13 Macroeconomic Effects of Sport - European Union
13.1 Gross value added
The share of sport-related value added for the European Union is 1.13% for the narrow
definition and 1.76% for the broad definition of sport. The share of what is generally known
as the organised sports sector (sports clubs, public sports venues, sports event organizers)
is reflected in the statistical definition. The share of value added according to the statistical
definition is 0.28%. Therefore the real share of sport in terms of production and income is
about six times as high as reported in the official statistics.
Sport-related value added (direct effects) amounts to 112.18 bn Euro according to the narrow
definition and 173.86 bn Euro with respect to the broad definition. For the statistical definition
of sport it is 28.16 bn Euro.
The direct effects of sport, combined with its multiplier (indirect and induced) effects, add up
to 2.98% (294.36 bn Euro) of overall gross value added in the European Union.
Figure 13: European Union - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 78 -
Statistical Narrow Broad
Direct 28,160 112,179 173,855
Direct + Indirect 48,774 186,206 294,359
Direct 0.28% 1.13% 1.76%
Direct + Indirect 0.49% 1.88% 2.98%
Multiplier 1.73 1.66 1.69
Figure 13 above highlights the top ten value added sectors in the European Union according
to the broad definition of sport. The highest sport-related value added is in the sector
Recreational, cultural and sporting services, followed by Education services second, and
Hotel and restaurant services ranking third.
The share of sport in European value added is comparable to the share of agriculture,
forestry, and fishing combined and almost two and a half times as large as mining and
quarrying, and represents at least more than one fifth of financial service activities, including
insurance and pension funds. Every sixtieth Euro generated and earned in the European
Union is sport-related.
Table 25: Sport-related GVA of the EU-27 countries, in million Euro and shares in EU
GVA
Source: SpEA, 2012.
Table 25 summarises the GVA effects. Multipliers in this case refer to the indirect GVA-
effects. For example, for each Euro GVA generated directly by increasing sport-related
production in the narrow definition, another 66 Cent of GVA is indirectly generated by the
supply chain.
13.2 Employment
The share of sport-related employment for the European Union is 1.49% for the narrow
definition and 2.12% for the broad definition of sport. The share of what is generally known
as the organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.31%.
Sport-related employment (direct effects) amounts to 3,138,350 persons according to the
narrow definition and 4,460,888 persons with respect to the broad definition. For the
statistical definition sport-related employment is 659,770.
Summing direct and indirect effects, sport leads to an employment of 5,085,137 persons
(2.42% of EU employment) in the narrow definition. For the broad definition, values of
7,378,671 persons (3.51%) can be reported, while it is 1,154,389 persons (0.55%) for the
statistical definition of sport.
Study on the Contribution of Sport to Economic Growth and Employment - 79 -
Statistical Narrow Broad
Direct 659,770 3,138,350 4,460,888
Direct + Indirect 1,154,389 5,085,137 7,378,671
Direct 0.31% 1.49% 2.12%
Direct + Indirect 0.55% 2.42% 3.51%
Multiplier 1.75 1.62 1.65
Table 26: Sport-related employment of the EU-27 countries, in persons and shares in
EU employment
Source: SpEA, 2012.
Table 26 reports the employment effects. As for GVA, the definition of sport is very important.
The multipliers are interpreted in a similar fashion too. For example, if sport-related
production is increased such that employment in the directly producing companies in the
narrow definition increases by 100 persons, another 62 persons will be employed in the
respective supply chain.
The shares sport-related employment (direct: 0.31%, 1.49%, and 2.12%) exceed those of
sport-related GVA (direct: 0.28%, 1.13%, and 1.76%). Sport-related business is thus more
employment intensive than average businesses as more employees are required to generate
the same amount of GVA. Growth in the sport-related economy thus leads to above average
employment growth.
13.3 Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The larger the value of
the multiplier, the more the rest of the economy benefits from an expansion of the sector.
For this project, two types of sector specific multipliers were calculated:
1. a national sector specific multiplier
2. an EU wide sector specific multiplier
The first multiplier takes the economic effects from a national point of view into account. The
effects of an economic stimulus are taken into account as long as they influence the national
economy. Effects on other EU Member States are ignored.
The second multiplier takes EU wide effects into account. Economic effects spilling over to
other EU Member States are thus reflected in the second multiplier. Parts of these effects are
beneficial to the country of origin of the initial stimulus. Regarding the European Union as a
single entity this second multiplier is the one of real importance.
Study on the Contribution of Sport to Economic Growth and Employment - 80 -
The highest sport-related multiplier in the European Union (see Figure 15) can be found in
the sector Construction work, followed by Food products and beverages and Water transport
services.
Education services, Medical, precision and optical instruments, watches, clocks, and Leather
and leather products have the lowest sport-related multipliers.
Figure 14 shows each country’s GDP (scaled in logs) against its average sectoral multiplier.
We observe that on average smaller countries have lower sectoral multipliers, especially if
the data point in the lower right (depicting France) would be “thought away”. The slope
(including France) is significant at 90% confidence level, so the probability that GDP does not
affect the multipliers is around 10%. No weights were applied on the averages of sectoral
multipliers. Small sectors thus count as much as large ones.
Figure 14: GDP (scaled in logs) against average sectoral multipliers
Source: SpEA, 2012.
National data sheets in section 0 report the national and the EU wide multipliers for each
sport-related sector of each country. The difference between these two multipliers tells us
something about the additional effects within the EU, which are ignored when sports demand
is considered from a national perspective only If the national multiplier is relatively low
compared to the EU wide multiplier the effects of an initial economic stimulus in the EU wide
context is considerably higher than in the national context. This is especially the case for
products where there is a relatively high trade pattern within the EU, or in other words, where
intra EU specialization has taken place.
From the tables in the appendix we learn that the intra EU specialization for sport services is
relatively low. This is reflected in the relatively low difference between the national and the
EU wide multipliers for categories 64-93 (so including the ‘traditional sport sector’). On the
other hand the difference between the two multipliers is relatively high for the sectors
Study on the Contribution of Sport to Economic Growth and Employment - 81 -
fabricated metals and motor vehicles and trailers. These are sectors where sports durables
are produced. So this may lead to the hypothesis that sports services are predominantly
produced for the domestic market, that sportswear is predominantly imported, while for sport
durables there is some internal EU specialization.
Education, which is an important sector in the whole network of value creation in sport,
especially in the Nordic and Baltic states, has a relatively low multiplier as it requires only few
intermediate goods compared to the GVA-dominated production value. The highest
multipliers are found in construction, and in the sectors related to tourism (hotel, air
transport). Nevertheless it is important to note that the multiplier merely indicates the impact
per Euro of change, not the total amount of impact that takes place. For instance, education
is one of the most important sectors for economic growth in the long run. Those sectors with
high multipliers are therefore not necessarily those which have the greatest long-term
economic impact on a country.
Study on the Contribution of Sport to Economic Growth and Employment - 82 -
Figure 15: European Union - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 83 -
14 Macroeconomic Effects of Sport - National Results
On the following pages, a closer look at the most important sport-related economic results of
each country is given. Note that multipliers having a value of 1.0 identify goods and services
which are not reported to be produced in this country.
Sector multipliers show how much an economy’s production has to increase if the sector’s
production is increased by 1 unit. In the following sections, EU-wide multipliers are reported.
If thus a value of 1.75 is given for a sector, increasing this sector’s production by 1 unit
increases the EU-wide production (of any product) by another 0.75 units to supply the
production with the necessary intermediate goods.
In addition, the EU-wide average of all these multipliers is stated. If thus an EU-average of
1.60 can be found for the same sector, it is more interconnected with the rest of the economy
than the same sector in the other 26 Member States on average.
Study on the Contribution of Sport to Economic Growth and Employment - 84 -
14.1 Austria
14.1.1 Gross value added
The share of sport-related value added for Austria is 2.12% for the narrow definition and
4.03% for the broad definition of sport. This is above the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.25%.
Sport-related value added (direct effects) amounts to 4.65 bn Euro according to the narrow
definition and 8.84 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.55 bn Euro.
Figure 16: Austria - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 85 -
Figure 16 above highlights the Austrian top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Hotel and restaurant
services, followed by Education services second, and Recreational, cultural and sporting
services third.
14.1.2 Employment
The share of sport-related employment for Austria is 3.21% for the narrow definition and
5.38% for the broad definition of sport. This is above the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.36%.
Sport-related employment (direct effects) amounts to 122,833 persons according to the
narrow definition and 205,863 persons with respect to the broad definition. For the statistical
definition sport-related employment is 13,850.
14.1.3 Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Austria can be found in the sector Air transport
services, followed by Supporting and auxiliary transport services and travel agencies. The
sector Food products and beverages is ranked third.
Water transport services, Wearing apparel, furs and Education services have the lowest
sport-related multipliers.
Figure 17 shows the size of these multipliers for Austria and compares them with the average
value of the EU. The biggest negative difference between Austria and the EU average is in
Water transport services where the Austrian value is 1.13 and EU average is 2.05 (a negative
difference of 0.92). The biggest positive difference between Austria and the EU average is Air
transport services where the Austrian value is 2.06 and the EU average 1.93 (a positive
difference of 0.13).
Study on the Contribution of Sport to Economic Growth and Employment - 86 -
Figure 17: Austria - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 87 -
14.2 Belgium
14.2.1 Gross value added
The share of sport-related value added for Belgium is 0.84% for the narrow definition and
1.13% for the broad definition of sport. This is below the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.14%.
Sport-related value added (direct effects) amounts to 2.27 bn Euro according to the narrow
definition and 3.04 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.38 bn Euro.
Figure 18: Belgium - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 88 -
Figure 18 above highlights the Belgian top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Recreational,
cultural and sporting services, followed by Education services second, and Wholesale trade
and commission trade services third.
14.2.2 Employment
The share of sport-related employment for Belgium is 1.33% for the narrow definition and
1.69% for the broad definition of sport. This is below the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.24%.
Sport-related employment (direct effects) amounts to 56,153 persons according to the narrow
definition and 71,416 persons with respect to the broad definition. For the statistical definition
sport-related employment is 10,336.
14.2.3 Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Belgium can be found in the sector Construction work,
followed by Water transport services. The sector Air transport services is ranked third.
Education services, Leather and leather products and Medical, precision and optical
instruments, watches, clocks have the lowest sport-related multipliers.
Figure 19 shows the size of these multipliers for Belgium and compares them with the
average value of the EU. The biggest negative difference between Belgium and the EU
average is in Furniture; other manufactured goods n.e.c. where the Belgian value is 1.34 and
EU average is 1.81 (a negative difference of 0.47). The biggest positive difference between
Belgium and the EU average is Water transport services where the Belgian value is 2.39 and
the EU average is 2.05 (a positive difference of 0.34).
Study on the Contribution of Sport to Economic Growth and Employment - 89 -
Figure 19: Belgium - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 90 -
14.3 Bulgaria
14.3.1 Gross value added
The share of sport-related value added for Bulgaria is 0.93% for the narrow definition and
1.13% for the broad definition of sport. This is below the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.06%.
Sport-related value added (direct effects) amounts to 0.18 bn Euro according to the narrow
definition and 0.22 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.01 bn Euro.
Figure 20: Bulgaria - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 91 -
Figure 20 above highlights the Bulgarian top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Education services,
followed by Recreational, cultural and sporting services second, and Furniture; other
manufactured goods n.e.c. third.
14.3.2 Employment
The share of sport-related employment for Bulgaria is 1.65% for the narrow definition and
1.87% for the broad definition of sport. This is above the EU average for the narrow definition
(1.49%) respectively below the EU average for the broad definition (2.12%). The share of
what is generally known as the organised sports sector is reflected in the statistical definition.
The employment rate according to the statistical definition is 0.11%.
Sport-related employment (direct effects) amounts to 49,168 persons according to the narrow
definition and 55,843 persons with respect to the broad definition. For the statistical definition
sport-related employment is 3,344.
14.3.3 Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Bulgaria can be found in the sector Construction work,
followed by Supporting and auxiliary transport services; travel agency. The sector Land
transport; transport via pipeline services is ranked third.
Motor vehicles, trailers and semi-trailers, Education services and Financial intermediation
services have the lowest sport-related multipliers.
Figure 21 shows the size of these multipliers for Bulgaria and compares them with the
average value of the EU. The biggest negative difference between Bulgaria and the EU
average is in Motor vehicles, trailers and semi-trailers where the Bulgarian value is 1.01 and
EU average is 1.82 (a negative difference of 0.81). The biggest positive difference between
Bulgaria and the EU average is Wholesale trade and commission trade services where the
Bulgarian value is 2.28 and the EU average is 1.82 (a positive difference of 0.46).
Study on the Contribution of Sport to Economic Growth and Employment - 92 -
Figure 21: Bulgaria - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 93 -
14.4 Cyprus
14.4.1 Gross value added
The share of sport-related value added for Cyprus is 1.79% for the narrow definition and
2.34% for the broad definition of sport. This is above the EU average for the narrow definition
(1.07%) respectively equals the EU average for the broad definition (1.63%). The share of
what is generally known as the organised sports sector (sports clubs, public sports venues,
sports event organizers) is reflected in the statistical definition. The share of value added
according to the statistical definition is 0.65%.
Sport-related value added (direct effects) amounts to 0.19 bn Euro according to the narrow
definition and 0.25 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.07 bn Euro.
Figure 22: Cyprus - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 94 -
Figure 22 above highlights the Cyprian top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Recreational,
cultural and sporting services, followed by Education services second, and Construction work
third.
14.4.2 Employment
The share of sport-related employment for Cyprus is 2.09% for the narrow definition and
2.57% for the broad definition of sport. This is below the EU average for the narrow definition
(1.49%) respectively above the EU average for the broad definition (2.12%). The share of
what is generally known as the organised sports sector is reflected in the statistical definition.
The employment rate according to the statistical definition is 0.56%.
Sport-related employment (direct effects) amounts to 6.356 persons according to the narrow
definition and 7.822 persons with respect to the broad definition. For the statistical definition
sport-related employment is 1,706.
14.4.3 Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Cyprus can be found in the sector Food products and
beverages, followed by Products of agriculture, hunting and related services. The sector Air
transport services is ranked third.
Leather and leather products, Motor vehicles, trailers and semi-trailers and Wholesale trade
and commission trade services, Water transport services, Research and development
service, as well as Coke and refined petroleum are not produced. Furniture and other
manufactured goods n.e.c, Textiles, and Education services have the lowest sport-related
multipliers.
Figure 23 shows the size of these multipliers for Cyprus and compares them with the
average value of the EU. The biggest negative difference between produced goods in Cyprus
and the EU average is in Furniture; other manufactured goods n.e.c. where the Cyprian
value is 1.03 and EU average is 1.81 (a negative difference of 0.78). The biggest positive
difference between Cyprus and the EU average is Products of agriculture, hunting and
related services where the Cyprian value is 2.04 and the EU average is 1.72 (a positive
difference of 0.32).
Study on the Contribution of Sport to Economic Growth and Employment - 95 -
Figure 23: Cyprus - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 96 -
14.5 Czech Republic
14.5.1 Gross value added
The share of sport-related value added for the Czech Republic is 0.80% for the narrow
definition and 1.18% for the broad definition of sport. This is below the EU average (1.13%
narrow definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.07%.
Sport-related value added (direct effects) amounts to 0.71 bn Euro according to the narrow
definition and 1.06 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.07 bn Euro.
Figure 24: Czech Republic - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 97 -
Figure 24 above highlights the Czech top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Health and social
work services, followed by Education services second, and Recreational, cultural and
sporting services third.
14.5.2 Employment
The share of sport-related employment for the Czech Republic is 1.38% for the narrow
definition and 1.87% for the broad definition of sport. This is below the EU average (1.49%
narrow definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.15%.
Sport-related employment (direct effects) amounts to 65,769 persons according to the narrow
definition and 89,119 persons with respect to the broad definition. For the statistical definition
sport-related employment is 6,949.
14.5.3 Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in the Czech Republic can be found in the sector
Construction work, followed by Insurance and pension funding services. The sector
Supporting and auxiliary transport services; travel agency is ranked third.
Research and development services, Leather and leather products and Education services
have the lowest sport-related multipliers.
Figure 25 shows the size of these multipliers for the Czech Republic and compares them
with the average value of the EU. The biggest negative difference between the Czech
Republic and the EU average is in Research and development services where the Czech
value is 1.34 and EU average is 1.70 (a negative difference of 0.36). The biggest positive
difference between the Czech Republic and the EU average is Construction work where the
Czech value is 2.58 and the EU average is 2.14 (a positive difference of 0.44).
Study on the Contribution of Sport to Economic Growth and Employment - 98 -
Figure 25: Czech Republic - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 99 -
14.6 Denmark
14.6.1 Gross value added
The share of sport-related value added for Denmark is 1.82% for the narrow definition and
2.12% for the broad definition of sport. This is above the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.13%.
Sport-related value added (direct effects) amounts to 3.20 bn Euro according to the narrow
definition and 3.72 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.22 bn Euro.
Figure 26: Denmark - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 100 -
Figure 26 above highlights the Danish top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Education services,
followed by Recreational, cultural and sporting services second, and Health and social work
services third.
14.6.2 Employment
The share of sport-related employment for Denmark is 2.12% for the narrow definition and
2.52% for the broad definition of sport. This is above the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.16%.
Sport-related employment (direct effects) amounts to 58,362 persons according to the narrow
definition and 69,287 persons with respect to the broad definition. For the statistical definition
sport-related employment is 4,330.
14.6.3 Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Denmark can be found in the sector Construction work,
followed by Food products and beverages. The sector Water transport services is ranked
third.
Leather and leather products, Motor vehicles, trailers and semi-trailers, and Wearing apparel;
furs report the lowest sport-related multipliers of produced goods.
Figure 27 shows the size of these multipliers for Denmark and compares them with the
average value of the EU. The biggest negative difference between produced goods in
Denmark and the EU average is in Supporting and auxiliary transport services; travel agency
where the Danish value is 1.28 and EU average is 1.99 (a negative difference of 0.72). The
biggest positive difference between Denmark and the EU average is Renting services of
machinery and equipment where the Danish value is 2.01 and the EU average is 1.67 (a
positive difference of 0.34).
Study on the Contribution of Sport to Economic Growth and Employment - 101 -
Figure 27: Denmark - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 102 -
14.7 Estonia
14.7.1 Gross value added
The share of sport-related value added for Estonia is 1.35% for the narrow definition and
1.64% for the broad definition of sport. This is above the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.1%.
Sport-related value added (direct effects) amounts to 0.13 bn Euro according to the narrow
definition and 0.16 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.01 bn Euro.
Figure 28: Estonia - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 103 -
Figure 28 above highlights the Estonian top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Education services,
followed by Recreational, cultural and sporting services second, and Furniture, other
manufactured goods n.e.c. third.
14.7.2 Employment
The share of sport-related employment for Estonia is 2.25% for the narrow definition and
2.58% for the broad definition of sport. This is above the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.18%.
Sport-related employment (direct effects) amounts to 13,662 persons according to the narrow
definition and 15,686 persons with respect to the broad definition. For the statistical definition
sport-related employment is 1,121.
14.7.3 Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Estonia can be found in the sector Supporting and
auxiliary transport services; travel agency, followed by Air transport services. The sector
Construction work is ranked third.
Coke, refined petroleum products and nuclear fuels, Motor vehicles, trailers and semi-trailers
and Machinery and equipment n.e.c. have the lowest sport-related multipliers.
Figure 29 shows the size of these multipliers for Estonia and compares them with the
average value of the EU. The biggest negative difference between Estonia and the EU
average is in Motor vehicles, trailers and semi-trailers where the Estonian value is 1.19 and
EU average is 1.82 (a negative difference of 0.63). The biggest positive difference between
Estonia and the EU average is Supporting and auxiliary transport services; travel agency
where the Estonian value is 2.32 and the EU average is 1.99 (a positive difference of 0.33).
Study on the Contribution of Sport to Economic Growth and Employment - 104 -
Figure 29: Estonia - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 105 -
14.8 Finland
14.8.1 Gross value added
The share of sport-related value added for Finland is 1.39% for the narrow definition and
1.94% for the broad definition of sport. This is above the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.11%.
Sport-related value added (direct effects) amounts to 1.9 bn Euro according to the narrow
definition and 2.65 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.16 bn Euro.
Figure 30: Finland - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 106 -
Figure 30 above highlights the Finnish top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Education services,
followed by Health and social work services second, and Hotel and restaurant services third.
14.8.2 Employment
The share of sport-related employment for Finland is 2.27% for the narrow definition and
3.09% for the broad definition of sport. This is above the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.2%.
Sport-related employment (direct effects) amounts to 54,501 persons according to the narrow
definition and 74,209 persons with respect to the broad definition. For the statistical definition
sport-related employment is 4,856.
14.8.3 Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Finland can be found in the sector Food products and
beverages, followed by Construction work. The sector Products of agriculture, hunting and
related services is ranked third.
Research and development services, Wearing apparel; furs and Leather and leather
products have the lowest sport-related multipliers.
Figure 31 shows the size of these multipliers for Finland and compares them with the
average value of the EU. The biggest negative difference between Finland and the EU
average is in Motor vehicles, trailers and semi-trailers where the Finnish value is 1.36 and
EU average is 1.82 (a negative difference of 0.46). The biggest positive difference between
Finland and the EU average is Products of agriculture, hunting and related services where
the Finnish value is 2.09 and the EU average is 1.72 (a positive difference of 0.37).
Study on the Contribution of Sport to Economic Growth and Employment - 107 -
Figure 31: Finland - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 108 -
14.9 France
14.9.1 Gross value added
The share of sport-related value added for France is 0.95% for the narrow definition and
1.40% for the broad definition of sport. This is below the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.20%.
Sport-related value added (direct effects) amounts to 14.71 bn Euro according to the narrow
definition and 21.61 bn Euro with respect to the broad definition. For the statistical definition
of sport it is 3.17 bn Euro.
Figure 32: France - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 109 -
Figure 32 above highlights the French top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Recreational,
cultural and sporting services second, followed by Education services and Public
administration third.
14.9.2 Employment
The share of sport-related employment for France is 1.30% for the narrow definition and
1.67% for the broad definition of sport. This is below the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.37%.
Sport-related employment (direct effects) amounts to 323,381 persons according to the
narrow definition and 416,537 persons with respect to the broad definition. For the statistical
definition sport-related employment is 91,773.
14.9.3 Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in France can be found in the sector Water transport
services, followed by Other transport services. The sector Wearing apparel; furs is ranked
third.
For many sport-related goods, no production is reported. Education services, Machinery and
equipment n.e.c., and Health and social work services report the lowest sport-related
multipliers of produced goods.
Figure 33 shows the size of these multipliers for France and compares them with the
average value of the EU. The biggest negative difference between France and the EU
average of produced goods is in Machinery and equipment n.e.c. where the French value is
1.39 and EU average is 1.71 (a negative difference of 0.32). The biggest positive difference
between France and the EU average is Wearing apparel; furs where the French value is 2.05
and the EU average is 1.58 (a positive difference of 0.48).
Study on the Contribution of Sport to Economic Growth and Employment - 110 -
Figure 33: France - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 111 -
14.10 Germany
14.10.1Gross value added
The share of sport-related value added for Germany is 1.34% for the narrow definition and
2.31% for the broad definition of sport. This is above the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.28%.
Sport-related value added (direct effects) amounts to 27.11 bn Euro according to the narrow
definition and 46.68 bn Euro with respect to the broad definition. For the statistical definition
of sport it is 5.69 bn Euro.
Figure 34: Germany - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 112 -
Figure 34 above highlights the German top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Recreational,
cultural and sporting services, followed by Hotel and restaurant services second, and
Education services third.
14.10.2Employment
The share of sport-related employment for Germany is 1.84% for the narrow definition and
3.15% for the broad definition of sport. This is above the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.39%.
Sport-related employment (direct effects) amounts to 669,892 persons according to the
narrow definition and 1,146,234 persons with respect to the broad definition. For the
statistical definition sport-related employment is 143,267.
14.10.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Germany can be found in the sector Insurance and
pension funding services, followed by Air transport services. The sector Motor vehicles,
trailers and semi-trailers is ranked third.
Renting services of machinery and equipment, Education services, and Leather and leather
products are either not produced or have the lowest sport-related multipliers.
Figure 35 shows the size of these multipliers for Germany and compares them with the
average value of the EU. The biggest negative difference between Germany and the EU
average is in Renting services of machinery and equipment where the German value is 1.25
and EU average is 1.67 (a negative difference of 0.42). The biggest positive difference
between Germany and the EU average is Motor vehicles, trailers and semi-trailers where the
German value is 2.15 and the EU average is 1.82 (a positive difference of 0.33).
Study on the Contribution of Sport to Economic Growth and Employment - 113 -
Figure 35: Germany - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 114 -
14.11 Greece
14.11.1Gross value added
The share of sport-related value added for Greece is 1% for the narrow definition and 1.44%
for the broad definition of sport. This is below the EU average (1.13% narrow definition and
1.76% broad definition). The share of what is generally known as the organised sports sector
(sports clubs, public sports venues, sports event organizers) is reflected in the statistical
definition. The share of value added according to the statistical definition is 0.36%.
Sport-related value added (direct effects) amounts to 1.74 bn Euro according to the narrow
definition and 2.52 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.63 bn Euro.
Figure 36: Greece - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 115 -
Figure 36 above highlights the Greek top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Recreational,
cultural and sporting services, followed by Post and telecommunication services second, and
Hotel and restaurant services third.
14.11.2Employment
The share of sport-related employment for Greece is 1.29% for the narrow definition and
1.63% for the broad definition of sport. This is below the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.45%.
Sport-related employment (direct effects) amounts to 56,226 persons according to the narrow
definition and 70,878 persons with respect to the broad definition. For the statistical definition
sport-related employment is 19,594.
14.11.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Greece can be found in the sector Food products and
beverages, followed by Fabricated metal products, exc. machinery and equipment. The
sector Construction work is ranked third.
Motor vehicles, trailers and semi-trailers, Medical, precision and optical instruments,
watches, clocks and Education services have the lowest sport-related multipliers.
Figure 37 shows the size of these multipliers for Greece and compares them with the
average value of the EU. The biggest negative difference between Greece and the EU
average is in Motor vehicles, trailers and semi-trailers where the Greek value is 1.06 and EU
average is 1.82 (a negative difference of 0.76). The biggest positive difference between
Greece and the EU average is Other business services where the Greek value is 1.72 and
the EU average is 1.67 (a positive difference of 0.05).
Study on the Contribution of Sport to Economic Growth and Employment - 116 -
Figure 37: Greece - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 117 -
14.12 Hungary
14.12.1Gross value added
The share of sport-related value added for Hungary is 0.79% for the narrow definition and
1.02% for the broad definition of sport. This is below the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.07%.
Sport-related value added (direct effects) amounts to 0.6 bn Euro according to the narrow
definition and 0.78 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.05 bn Euro.
Figure 38: Hungary - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 118 -
Figure 38 above highlights the Hungarian top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Education services,
followed by Recreational, cultural and sporting services second, and Supporting and auxiliary
transport services; travel agency third.
14.12.2Employment
The share of sport-related employment for Hungary is 1.16% for the narrow definition and
1.43% for the broad definition of sport. This is below the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.11%.
Sport-related employment (direct effects) amounts to 45,409 persons according to the narrow
definition and 55,577 persons with respect to the broad definition. For the statistical definition
sport-related employment is 4,205.
14.12.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Hungary can be found in the sector Food products and
beverages, followed by Hotel and restaurant services. The sector Construction work is
ranked third.
Renting services of machinery and equipment, Education services and Public administration
and defence services have the lowest sport-related multipliers.
Figure 39 shows the size of these multipliers for Hungary and compares them with the
average value of the EU. The biggest negative difference between Hungary and the EU
average is in Water transport services where the Hungarian value is 1.52 and EU average is
2.05 (a negative difference of 0.53). The biggest positive difference between Hungary and
the EU average is Hotel and restaurant services where the Hungarian value is 2.13 and the
EU average is 1.82 (a positive difference of 0.31).
Study on the Contribution of Sport to Economic Growth and Employment - 119 -
Figure 39: Hungary - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 120 -
14.13 Ireland
14.13.1Gross value added
The share of sport-related value added for Ireland is 0.96% for the narrow definition and
1.66% for the broad definition of sport. This is below the EU average for the narrow definition
(1.07%) respectively above the EU average for the broad definition (1.63%). The share of
what is generally known as the organised sports sector (sports clubs, public sports venues,
sports event organizers) is reflected in the statistical definition. The share of value added
according to the statistical definition is 0.3%.
Sport-related value added (direct effects) amounts to 1.37 bn Euro according to the narrow
definition and 2.38 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.44 bn Euro.
Figure 40: Ireland - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 121 -
Figure 40 above highlights the Irish top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Recreational,
cultural and sporting services, followed by Production of agriculture, hunting and related
services second, and Financial intermediation services third.
14.13.2Employment
The share of sport-related employment for Ireland is 1.39% for the narrow definition and
2.08% for the broad definition of sport. This is below the EU average for the narrow definition
(1.49%) respectively above the EU average for the broad definition (2.12%). The share of
what is generally known as the organised sports sector is reflected in the statistical definition.
The employment rate according to the statistical definition is 0.37%.
Sport-related employment (direct effects) amounts to 26,995 persons according to the narrow
definition and 40,532 persons with respect to the broad definition. For the statistical definition
sport-related employment is 7,161.
14.13.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Ireland can be found in the sector Supporting and
auxiliary transport services; travel agency, followed by Construction work. The sector Food
products and beverages is ranked third.
Leather and leather products, Wearing apparel; furs, and Other transport equipment report
the lowest sport-related multipliers of produced goods.
Figure 41 shows the size of these multipliers for Ireland and compares them with the average
value of the EU. The biggest negative difference between produced goods in Ireland and the
EU average is in Other transport equipment where the Irish value is 1.12 and EU average is
1.79 (a negative difference of 0.67). The biggest positive difference between Ireland and the
EU average is Supporting and auxiliary transport services; travel agency where the Irish
value is 2.31 and the EU average is 1.99 (a positive difference of 0.32).
Study on the Contribution of Sport to Economic Growth and Employment - 122 -
Figure 41: Ireland - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 123 -
14.14 Italy
14.14.1Gross value added
The share of sport-related value added for Italy is 0.76% for the narrow definition and 1.21%
for the broad definition of sport. This is below the EU average (1.13% narrow definition and
1.76% broad definition). The share of what is generally known as the organised sports sector
(sports clubs, public sports venues, sports event organizers) is reflected in the statistical
definition. The share of value added according to the statistical definition is 0.23%.
Sport-related value added (direct effects) amounts to 9.75 bn Euro according to the narrow
definition and 15.6 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 2.91 bn Euro.
Figure 42: Italy - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 124 -
Figure 42 above highlights the Italian top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Recreational,
cultural and sporting services, followed by Hotel and restaurant services second, and Land
transport; transport via pipeline services third.
14.14.2Employment
The share of sport-related employment for Italy is 1.07% for the narrow definition and 1.47%
for the broad definition of sport. This is below the EU average (1.49% narrow definition and
2.12% broad definition). The share of what is generally known as the organised sports sector
is reflected in the statistical definition. The employment rate according to the statistical
definition is 0.34%.
Sport-related employment (direct effects) amounts to 239,881 persons according to the
narrow definition and 329,860 persons with respect to the broad definition. For the statistical
definition sport-related employment is 75,641.
14.14.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Italy can be found in the sector Water transport
services, followed by Furniture; other manufactured goods n.e.c.. The sector Fabricated
metal products, exc. machinery and equipment is ranked third.
Products of agriculture, hunting and related, Health and social work services, and Financial
intermediation services report the lowest sport-related multipliers of produced goods.
Figure 43 shows the size of these multipliers for Italy and compares them with the average
value of the EU. The biggest negative difference between produced goods in Italy and the
EU average is in Products of agriculture, hunting and related services where the Italian value
is 1.56 and EU average is 1.72 (a negative difference of 0.16). The biggest positive
difference between Italy and the EU average is Leather and leather products where the
Italian value is 2.20 and the EU average is 1.52 (a positive difference of 0.68).
Study on the Contribution of Sport to Economic Growth and Employment - 125 -
Figure 43: Italy - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 126 -
14.15 Latvia
14.15.1Gross value added
The share of sport-related value added for Latvia is 0.91% for the narrow definition and
1.11% for the broad definition of sport. This is below the EU average (1.13% narrow definition
and 1.76% broad definition). The share of what is generally known as the organised sports
sector (sports clubs, public sports venues, sports event organizers) is reflected in the
statistical definition. The share of value added according to the statistical definition is 0.07%.
Sport-related value added (direct effects) amounts to 0.11 bn Euro according to the narrow
definition and 0.14 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.01 bn Euro.
Figure 44: Latvia - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 127 -
Figure 44 above highlights the Latvian top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Education services,
followed by Recreational, cultural and sporting services second, and Furniture, other
manufactured goods n.e.c. third.
14.15.2Employment
The share of sport-related employment for Latvia is 1.44% for the narrow definition and
1.65% for the broad definition of sport. This is below the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.12%.
Sport-related employment (direct effects) amounts to 14,933 persons according to the narrow
definition and 17,077 persons with respect to the broad definition. For the statistical definition
sport-related employment is 1,204.
14.15.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Latvia can be found in the sector Products of
agriculture, hunting and related services, followed by Construction work. The sector Food
products and beverages is ranked third.
Motor vehicles, trailers and semi-trailers, Coke, refined petroleum products and nuclear fuels
and Medical, precision and optical instruments, watches, clocks have the lowest sport-related
multipliers.
Figure 45 shows the size of these multipliers for Latvia and compares them with the average
value of the EU. The biggest negative difference between Latvia and the EU average is in
Motor vehicles, trailers and semi-trailers where the Latvian value is 1.06 and EU average is
1.82 (a negative difference of 0.76). The biggest positive difference between Latvia and the
EU average is Products of agriculture, hunting and related services where the Latvian value
is 2.33 and the EU average is 1.72 (a positive difference of 0.59).
Study on the Contribution of Sport to Economic Growth and Employment - 128 -
Figure 45: Latvia - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 129 -
14.16 Lithuania
14.16.1Gross value added
The share of sport-related value added for Lithuania is 0.65% for the narrow definition and
0.88% for the broad definition of sport. This is below the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.06%.
Sport-related value added (direct effects) amounts to 0.12 bn Euro according to the narrow
definition and 0.16 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.01 bn Euro.
Figure 46: Lithuania - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 130 -
Figure 46 above highlights the Lithuanian top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Furniture; other
manufactured goods n.e.c. followed by Recreational, cultural and sporting services second
and Wholesale trade and commission trade services third.
14.16.2Employment
The share of sport-related employment for Lithuania is 0.87% for the narrow definition and
1.10% for the broad definition of sport. This is below the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.12%.
Sport-related employment (direct effects) amounts to 12,762 persons according to the narrow
definition and 16,178 persons with respect to the broad definition. For the statistical definition
sport-related employment is 1,740.
14.16.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Lithuania can be found in the sector Air transport
services, followed by Food products and beverages. The sector Other services is ranked
third.
Motor vehicles, trailers and semi-trailers, Machinery and equipment n.e.c., and Medical,
precision and optical instruments, watches, clocks are either not produced or have the lowest
sport-related multipliers.
Figure 47 shows the size of these multipliers for Lithuania and compares them with the
average value of the EU. The biggest negative difference between produced goods in
Lithuania and the EU average is in Motor vehicles, trailers and semi-trailers where the
Lithuanian value is 1.05 and EU average is 1.82 (a negative difference of 0.77). The biggest
positive difference between Lithuania and the EU average is Other services where the
Lithuanian value is 1.90 and the EU average is 1.66 (a positive difference of 0.24).
Study on the Contribution of Sport to Economic Growth and Employment - 131 -
Figure 47: Lithuania - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 132 -
14.17 Luxemburg
14.17.1Gross value added
The share of sport-related value added for Luxembourg is 1.32% for the narrow definition
and 2.37% for the broad definition of sport. This is above the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.3%.
Sport-related value added (direct effects) amounts to 0.39 bn Euro according to the narrow
definition and 0.7 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.09 bn Euro.
Figure 48: Luxembourg - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 133 -
Figure 48 above highlights the Luxembourgian top ten value added sectors according to the
broad definition of sport. The highest sport-related value added is in the sector Health and
social work services, followed by Recreational, cultural and sporting services second, and
Hotel and restaurant services third.
14.17.2Employment
The share of sport-related employment for Luxembourg is 3.7% for the narrow definition and
5.63% for the broad definition of sport. This is above the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.32%.
Sport-related employment (direct effects) amounts to 12,708 persons according to the narrow
definition and 19,331 persons with respect to the broad definition. For the statistical definition
sport-related employment is 1,113.
14.17.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Luxembourg can be found in the sector Insurance and
pension funding services, followed by Financial intermediation services. The sector Air
transport services is ranked third.
The lowest sport-related multipliers of produced goods are reported in Furniture; other
manufactured goods n.e.c., Education services, and Chemicals, chemical products and man-
made fibres.
Figure 49 shows the size of these multipliers for Luxembourg and compares them with the
average value of the EU. The biggest negative difference between Luxembourg and the EU
average is in Furniture; other manufactured goods n.e.c. where the Luxembourgian value is
1.02 and EU average is 1.81 (a negative difference of 0.79). The biggest positive difference
between Luxembourg and the EU average is Insurance and pension funding services where
the Luxembourgian value is 2.24 and the EU average is 2.00 (a positive difference of 0.24).
Study on the Contribution of Sport to Economic Growth and Employment - 134 -
Figure 49: Luxembourg - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 135 -
14.18 Malta
14.18.1Gross value added
The share of sport-related value added for Malta is 1.75% for the narrow definition and
2.24% for the broad definition of sport. This is above the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.49%.
Sport-related value added (direct effects) amounts to 0.07 bn Euro according to the narrow
definition and 0.09 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.02 bn Euro.
Figure 50: Malta - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 136 -
Figure 50 above highlights the top ten value added sectors in Malta according to the broad
definition of sport. The highest sport-related value added is in the sector Recreational,
cultural and sporting services, followed by Education services second, and Retail trade
services third.
14.18.2Employment
The share of sport-related employment for Malta is 1.51% for the narrow definition and
2.07% for the broad definition of sport. This is above the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.49%.
Sport-related employment (direct effects) amounts to 2,235 persons according to the narrow
definition and 3,070 persons with respect to the broad definition. For the statistical definition
sport-related employment is 723.
14.18.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Malta can be found in the sector Financial
intermediation services, followed by Air transport services. The sector Recreational, cultural
and sporting services is ranked third.
The lowest sport-related multipliers of produced goods are reported in Coke, refined
petroleum products and nuclear fuels, Machinery and equipment n.e.c., and Textiles.
Figure 51 shows the size of these multipliers for Malta and compares them with the average
value of the EU. The biggest negative difference between Malta and the EU average is in
Coke, refined petroleum products and nuclear fuels where the Maltese value is 1.03 and EU
average is 1.78 (a negative difference of 0.75). The biggest positive difference between
Malta and the EU average is Financial intermediation services where the Maltese value is
2.46 and the EU average is 1.61 (a positive difference of 0.85).
Study on the Contribution of Sport to Economic Growth and Employment - 137 -
Figure 51: Malta - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 138 -
14.19 The Netherlands
14.19.1Gross value added
The share of sport-related value added for the Netherlands is 0.93% for the narrow definition
and 1.28% for the broad definition of sport. This is below the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.23%.
Sport-related value added (direct effects) amounts to 4.25 bn Euro according to the narrow
definition and 5.83 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 1.04 bn Euro.
Figure 52: Netherlands - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 139 -
Figure 52 above highlights the Dutch top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Recreational,
cultural and sporting services, followed by Education services second, and Other services
third.
14.19.2Employment
The share of sport-related employment for the Netherlands is 1.32% for the narrow definition
and 1.75% for the broad definition of sport. This is below the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.27%.
Sport-related employment (direct effects) amounts to 107,024 persons according to the
narrow definition and 141,896 persons with respect to the broad definition. For the statistical
definition sport-related employment is 22,243.
14.19.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in the Netherlands can be found in the sector Air
transport services, followed by Water transport services. The sector Recreational, cultural
and sporting services is ranked third.
Leather and leather products, Wearing apparel; furs, and Medical, precision and optical
instrum., watches, clocks have the lowest sport-related multipliers of produced goods.
Figure 53 shows the size of these multipliers for the Netherlands and compares them with
the average value of the EU. The biggest negative difference between the Netherlands and
the EU average is in Wearing apparel; furs where the Dutch value is 1.15 and EU average is
1.58 (a negative difference of 0.43). The biggest positive difference between the Netherlands
and the EU average is Air transport services where the Dutch value is 2.19 and the EU
average is 1.93 (a positive difference of 0.26).
Study on the Contribution of Sport to Economic Growth and Employment - 140 -
Figure 53: Netherlands - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 141 -
14.20 Poland
14.20.1Gross value added
The share of sport-related value added for Poland is 1.17% for the narrow definition and
1.56% for the broad definition of sport. This is above the EU average for the narrow definition
(1.07%) respectively below the EU average for the broad definition (1.63%). The share of
what is generally known as the organised sports sector (sports clubs, public sports venues,
sports event organizers) is reflected in the statistical definition. The share of value added
according to the statistical definition is 0.22%.
Sport-related value added (direct effects) amounts to 2.53 bn Euro according to the narrow
definition and 3.36 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.48 bn Euro.
Figure 54: Poland - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 142 -
Figure 54 above highlights the Polish top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Recreational,
cultural and sporting services, followed by Education services second, and Other business
services third.
14.20.2Employment
The share of sport-related employment for Poland is 1.57% for the narrow definition and
1.94% for the broad definition of sport. This is above the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.32%.
Sport-related employment (direct effects) amounts to 221,652 persons according to the
narrow definition and 274,423 persons with respect to the broad definition. For the statistical
definition sport-related employment is 44,461.
14.20.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Poland can be found in the sector Food products and
beverages, followed by Supporting and auxiliary transport services; travel agency. The sector
Construction work is ranked third.
Education services, Other services, and Public administration and defence services have the
lowest sport-related multipliers of produced goods.
Figure 55 shows the size of these multipliers for Poland and compares them with the
average value of the EU. The biggest negative difference between Poland and the EU
average is in Insurance and pension funding services where the Polish value is 1.66 and EU
average is 2.00 (a negative difference of 0.36). The biggest positive difference between
Poland and the EU average is Food products and beverages where the Polish value is 2.47
and the EU average is 2.06 (a positive difference of 0.41).
Study on the Contribution of Sport to Economic Growth and Employment - 143 -
Figure 55: Poland - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 144 -
14.21 Portugal
14.21.1Gross value added
The share of sport-related value added for Portugal is 0.96% for the narrow definition and
1.19% for the broad definition of sport. This is below the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.02%.
Sport-related value added (direct effects) amounts to 1.23 bn Euro according to the narrow
definition and 1.53 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.03 bn Euro.
Figure 56: Portugal - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 145 -
Figure 56 above highlights the Portuguese top ten value added sectors according to the
broad definition of sport. The highest sport-related value added is in the sector Education
services, followed by Other services second, and Health and social work services third.
14.21.2Employment
The share of sport-related employment for Portugal is 1.15% for the narrow definition and
1.41% for the broad definition of sport. This is below the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.03%.
Sport-related employment (direct effects) amounts to 59,086 persons according to the narrow
definition and 72,101 persons with respect to the broad definition. For the statistical definition
sport-related employment is 1,452.
14.21.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Portugal can be found in the sector Construction work,
followed by Water transport services. The sector Food products and beverages is ranked
third.
Education services, Medical, precision and optical instruments, watches, clocks and Public
administration and defence services have the lowest sport-related multipliers.
Figure 57 shows the size of these multipliers for Portugal and compares them with the
average value of the EU. The biggest negative difference between Portugal and the EU
average is in Insurance and pension funding services where the Portuguese value is 1.56
and EU average is 2.00 (a negative difference of 0.44). The biggest positive difference
between Portugal and the EU average is Wearing apparel; furs where the Portuguese value
is 2.00 and the EU average is 1.58 (a positive difference of 0.42).
Study on the Contribution of Sport to Economic Growth and Employment - 146 -
Figure 57: Portugal - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 147 -
14.22 Romania
14.22.1Gross value added
The share of sport-related value added for Romania is 0.91% for the narrow definition and
1.12% for the broad definition of sport. This is below the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0%.
Sport-related value added (direct effects) amounts to 0.64 bn Euro according to the narrow
definition and 0.79 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0 bn Euro.
Figure 58: Romania - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 148 -
Figure 58 above highlights the Romanian top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Education services,
followed by Wearing apparel; furs second, and Furniture; other manufactured goods n.e.c.
third.
14.22.2Employment
The share of sport-related employment for Romania is 1.57% for the narrow definition and
1.77% for the broad definition of sport. This is above the EU average for the narrow definition
(1.49%) respectively below the EU average for the broad definition (2.12%). The share of
what is generally known as the organised sports sector is reflected in the statistical definition.
The employment rate according to the statistical definition is 0%.
Sport-related employment (direct effects) amounts to 142,935 persons according to the
narrow definition and 161,248 persons with respect to the broad definition. For the statistical
definition sport-related employment is 0.
14.22.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Romania can be found in the sector Trade,
maintenance and repair services of motor vehicles, followed by Research and development
services. The sector Food products and beverages is ranked third.
Financial intermediation services, Textiles, and Medical, precision and optical instruments,
watches, clocks have the lowest sport-related multipliers of produced goods.
Figure 59 shows the size of these multipliers for Romania and compares them with the
average value of the EU. The biggest negative difference of produced goods between
Romania and the EU average is in Financial intermediation services where the Romanian
value is 1.16 and EU average is 1.61 (a negative difference of 0.45). The biggest positive
difference between Romania and the EU average is Trade, maintenance and repair services
of motor vehicles where the Romanian value is 2.18 and the EU average is 1.83 (a positive
difference of 0.35).
Study on the Contribution of Sport to Economic Growth and Employment - 149 -
Figure 59: Romania - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 150 -
14.23 Slovakia
14.23.1Gross value added
The share of sport-related value added for Slovakia is 0.73% for the narrow definition and
1.08% for the broad definition of sport. This is below the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.09%.
Sport-related value added (direct effects) amounts to 0.32 bn Euro according to the narrow
definition and 0.47 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.04 bn Euro.
Figure 60: Slovakia - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 151 -
Figure 60 above highlights the Slovakian top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Health and social
work services, followed by Recreational, cultural and sporting services second, and
Education services third.
14.23.2Employment
The share of sport-related employment for Slovakia is 1.6% for the narrow definition and
2.25% for the broad definition of sport. This is above the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.25%.
Sport-related employment (direct effects) amounts to 35,444 persons according to the narrow
definition and 49,910 persons with respect to the broad definition. For the statistical definition
sport-related employment is 5,643.
14.23.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Slovakia can be found in the sector Construction work,
followed by Supporting and auxiliary transport services; travel agency. The sector Printed
matter and recorded media is ranked third.
Water transport services, Medical, precision and optical instruments, watches, clocks and
Education services have the lowest sport-related multipliers.
Figure 61 shows the size of these multipliers for Slovakia and compares them with the
average value of the EU. The biggest negative difference between Slovakia and the EU
average is in Water transport services where the Slovakian value is 1.19 and EU average is
2.05 (a negative difference of 0.86). The biggest positive difference between Slovakia and
the EU average is Supporting and auxiliary transport services; travel agency where the
Slovakian value is 2.21 and the EU average is 1.99 (a positive difference of 0.22).
Study on the Contribution of Sport to Economic Growth and Employment - 152 -
Figure 61: Slovakia - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 153 -
14.24 Slovenia
14.24.1Gross value added
The share of sport-related value added for Slovenia is 1.66% for the narrow definition and
2.1% for the broad definition of sport. This is above the EU average (1.13% narrow definition
and 1.76% broad definition). The share of what is generally known as the organised sports
sector (sports clubs, public sports venues, sports event organizers) is reflected in the
statistical definition. The share of value added according to the statistical definition is 0.23%.
Sport-related value added (direct effects) amounts to 0.41 bn Euro according to the narrow
definition and 0.52 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.06 bn Euro.
Figure 62: Slovenia - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 154 -
Figure 62 above highlights the Slovenian top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Recreational,
cultural and sporting services, followed by Education services second, and Health and social
work services third.
14.24.2Employment
The share of sport-related employment for Slovenia is 2.43% for the narrow definition and
3.01% for the broad definition of sport. This is above the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.38%.
Sport-related employment (direct effects) amounts to 23,011 persons according to the narrow
definition and 28,576 persons with respect to the broad definition. For the statistical definition
sport-related employment is 3,600.
14.24.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Slovenia can be found in the sector Construction work,
followed by Printed matter and recorded media. The sector Supporting and auxiliary
transport services; travel agency is ranked third.
Coke, refined petroleum products and nuclear fuels, Education services and Medical,
precision and optical instrum., watches, clocks have the lowest sport-related multipliers.
Figure 63 shows the size of these multipliers for Slovenia and compares them with the
average value of the EU. The biggest negative difference between Slovenia and the EU
average is in Coke, refined petroleum products and nuclear fuels where the Slovenian value
is 1.04 and EU average is 1.78 (a negative difference of 0.74). The biggest positive
difference between Slovenia and the EU average is Construction work where the Slovenian
value is 2.39 and the EU average is 2.14 (a positive difference of 0.25).
Study on the Contribution of Sport to Economic Growth and Employment - 155 -
Figure 63: Slovenia - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 156 -
14.25 Spain
14.25.1Gross value added
The share of sport-related value added for Spain is 0.9% for the narrow definition and 1.28%
for the broad definition of sport. This is below the EU average (1.13% narrow definition and
1.76% broad definition). The share of what is generally known as the organised sports sector
(sports clubs, public sports venues, sports event organizers) is reflected in the statistical
definition. The share of value added according to the statistical definition is 0.02%.
Sport-related value added (direct effects) amounts to 7.33 bn Euro according to the narrow
definition and 10.41 bn Euro with respect to the broad definition. For the statistical definition
of sport it is 0.14 bn Euro.
Figure 64: Spain - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 157 -
Figure 64 above highlights the Spanish top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Health and social
work services, followed by Education services second, and Construction work third.
14.25.2Employment
The share of sport-related employment for Spain is 1.33% for the narrow definition and
1.77% for the broad definition of sport. This is below the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.03%.
Sport-related employment (direct effects) amounts to 252,183 persons according to the
narrow definition and 336,177 persons with respect to the broad definition. For the statistical
definition sport-related employment is 5,774.
14.25.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Spain can be found in the sector Construction work,
followed by Food products and beverages. The sector Water transport services is ranked
third.
Education services, Financial intermediation services, and Medical, precision and optical
instruments, watches, clocks are have the lowest sport-related multipliers of produced goods.
Figure 65 shows the size of these multipliers for Spain and compares them with the average
value of the EU. The biggest negative difference between Spain and the EU average is in
Financial intermediation services where the Spanish value is 1.34 and EU average is 1.61 (a
negative difference of 0.27). The biggest positive difference between Spain and the EU
average is Leather and leather products where the Spanish value is 1.93 and the EU
average is 1.52 (a positive difference of 0.41).
Study on the Contribution of Sport to Economic Growth and Employment - 158 -
Figure 65: Spain - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 159 -
14.26 Sweden
14.26.1Gross value added
The share of sport-related value added for Sweden is 0.54% for the narrow definition and
0.92% for the broad definition of sport. This is below the EU average (1.13% narrow
definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.09%.
Sport-related value added (direct effects) amounts to 1.39 bn Euro according to the narrow
definition and 2.36 bn Euro with respect to the broad definition. For the statistical definition of
sport it is 0.23 bn Euro.
Figure 66: Sweden - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 160 -
Figure 66 above highlights the Swedish top ten value added sectors according to the broad
definition of sport. The highest sport-related value added is in the sector Hotel and restaurant
services, followed by Education services second, and Recreational, cultural and sporting
services third.
14.26.2Employment
The share of sport-related employment for Sweden is 1.12% for the narrow definition and
1.69% for the broad definition of sport. This is below the EU average (1.49% narrow
definition and 2.12% broad definition). The share of what is generally known as the
organised sports sector is reflected in the statistical definition. The employment rate
according to the statistical definition is 0.19%.
Sport-related employment (direct effects) amounts to 48,717 persons according to the narrow
definition and 73,266 persons with respect to the broad definition. For the statistical definition
sport-related employment is 8,358.
14.26.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in Sweden can be found in the sector Supporting and
auxiliary transport services; travel agency, followed by Printed matter and recorded media.
The sector Motor vehicles, trailers and semi-trailers is ranked third.
Wearing apparel; furs, Leather and leather products, and Textiles report the smallest
multipliers of produced sport-related goods.
Figure 67 shows the size of these multipliers for Sweden and compares them with the
average value of the EU. The biggest negative difference between Sweden and the EU
average is in Insurance and pension funding services where the Swedish value is 1.40 and
EU average is 2.00 (a negative difference of 0.60). The biggest positive difference between
Sweden and the EU average is Motor vehicles, trailers and semi-trailers where the Swedish
value is 2.03 and the EU average is 1.82 (a positive difference of 0.21).
Study on the Contribution of Sport to Economic Growth and Employment - 161 -
Figure 67: Sweden - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 162 -
14.27 United Kingdom
14.27.1Gross value added
The share of sport-related value added for the United Kingdom is 1.52% for the narrow
definition and 2.33% for the broad definition of sport. This is above the EU average (1.13%
narrow definition and 1.76% broad definition). The share of what is generally known as the
organised sports sector (sports clubs, public sports venues, sports event organizers) is
reflected in the statistical definition. The share of value added according to the statistical
definition is 0.71%.
Sport-related value added (direct effects) amounts to 24.84 bn Euro according to the narrow
definition and 37.99 bn Euro with respect to the broad definition. For the statistical definition
of sport it is 11.66 bn Euro.
Figure 68: United Kingdom - gross value added at market prices, broad definition
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 163 -
Figure 68 above highlights the top ten value added sectors in the United Kingdom according
to the broad definition of sport. The highest sport-related value added is in the sector
Recreational, cultural and sporting services, followed by Post and telecommunication
services second, and Education services third.
14.27.2Employment
The share of sport-related employment for the United Kingdom is 1.46% for the narrow
definition and 2.16% for the broad definition of sport. This is below the EU average for the
narrow definition (1.49%) respectively above the EU average for the broad definition (2.12%).
The share of what is generally known as the organised sports sector is reflected in the
statistical definition. The employment rate according to the statistical definition is 0.61%.
Sport-related employment (direct effects) amounts to 417,072 persons according to the
narrow definition and 618,770 persons with respect to the broad definition. For the statistical
definition sport-related employment is 175,325.
14.27.3Sector-specific multipliers
Multipliers describe the inter-connectedness of a sector with the rest of the economy. If the
multiplier equals 1.0 the sector is not connected to any other sector. The higher the multiplier,
the more the rest of the economy benefits from an expansion of the sector.
The highest sport-related multiplier in the United Kingdom can be found in the sector
Insurance and pension funding services, followed by Construction work. The sector
Supporting and auxiliary transport services; travel agency is ranked third.
Leather and leather products, Wearing apparel; furs and Education services have the lowest
sport-related multipliers.
Figure 69 shows the size of these multipliers for the United Kingdom and compares them
with the average value of the EU. The biggest negative difference between the United
Kingdom and the EU average is in Leather and leather products where the national value is
1.17 and EU average is 1.52 (a negative difference of 0.35). The biggest positive difference
between the United Kingdom and the EU average is Insurance and pension funding services
where the national value is 2.22 and the EU average is 2.00 (a positive difference of 0.20).
Study on the Contribution of Sport to Economic Growth and Employment - 164 -
Figure 69: United Kingdom - sector-specific multipliers and EU-averages
Source: SpEA, 2012.
Study on the Contribution of Sport to Economic Growth and Employment - 165 -
15 List of Figures
Figure 1: Basic Input-Output Table for the EU-27 .................................................................. 19
Figure 2: Extended Input-Output Table for the EU-27 ............................................................ 21
Figure 3: Schematic Supply Table .......................................................................................... 23
Figure 4: Schematic Use Table .............................................................................................. 24
Figure 5: Schematic Input-Output Table ................................................................................. 26
Figure 6: Set up of a Multiregional Input-Output Table ........................................................... 35
Figure 7: Set up of a Multiregional Input-Output Table: Sport ................................................ 39
Figure 8: Statistical Definition: share of national employment, in % of heads ........................ 58
Figure 9: Narrow Definition: share of national employment, in % of heads ............................ 59
Figure 10: Broad Definition: Share of national employment, in % of heads ........................... 60
Figure 11: Employment shares in sport and GDP per capita ................................................. 61
Figure 12: Ranking in the goods vs. the service sector of the EU Member States ................ 64
Figure 13: European Union - gross value added at market prices, broad definition .............. 77
Figure 14: GDP (scaled in logs) against average sectoral multipliers .................................... 80
Figure 15: European Union - sector-specific multipliers and EU-averages ............................ 82
Figure 16: Austria - gross value added at market prices, broad definition ............................. 84
Figure 17: Austria - sector-specific multipliers and EU-averages ........................................... 86
Figure 18: Belgium - gross value added at market prices, broad definition ........................... 87
Figure 19: Belgium - sector-specific multipliers and EU-averages ......................................... 89
Figure 20: Bulgaria - gross value added at market prices, broad definition ........................... 90
Figure 21: Bulgaria - sector-specific multipliers and EU-averages ......................................... 92
Figure 22: Cyprus - gross value added at market prices, broad definition ............................. 93
Study on the Contribution of Sport to Economic Growth and Employment - 166 -
Figure 23: Cyprus - sector-specific multipliers and EU-averages .......................................... 95
Figure 24: Czech Republic - gross value added at market prices, broad definition ............... 96
Figure 25: Czech Republic - sector-specific multipliers and EU-averages ............................. 98
Figure 26: Denmark - gross value added at market prices, broad definition .......................... 99
Figure 27: Denmark - sector-specific multipliers and EU-averages ..................................... 101
Figure 28: Estonia - gross value added at market prices, broad definition .......................... 102
Figure 29: Estonia - sector-specific multipliers and EU-averages ........................................ 104
Figure 30: Finland - gross value added at market prices, broad definition ........................... 105
Figure 31: Finland - sector-specific multipliers and EU-averages ........................................ 107
Figure 32: France - gross value added at market prices, broad definition ........................... 108
Figure 33: France - sector-specific multipliers and EU-averages ......................................... 110
Figure 34: Germany - gross value added at market prices, broad definition ........................ 111
Figure 35: Germany - sector-specific multipliers and EU-averages ..................................... 113
Figure 36: Greece - gross value added at market prices, broad definition ........................... 114
Figure 37: Greece - sector-specific multipliers and EU-averages ........................................ 116
Figure 38: Hungary - gross value added at market prices, broad definition ......................... 117
Figure 39: Hungary - sector-specific multipliers and EU-averages ...................................... 119
Figure 40: Ireland - gross value added at market prices, broad definition ........................... 120
Figure 41: Ireland - sector-specific multipliers and EU-averages ......................................... 122
Figure 42: Italy - gross value added at market prices, broad definition ................................ 123
Figure 43: Italy - sector-specific multipliers and EU-averages ............................................. 125
Figure 44: Latvia - gross value added at market prices, broad definition ............................. 126
Figure 45: Latvia - sector-specific multipliers and EU-averages .......................................... 128
Study on the Contribution of Sport to Economic Growth and Employment - 167 -
Figure 46: Lithuania - gross value added at market prices, broad definition ........................ 129
Figure 47: Lithuania - sector-specific multipliers and EU-averages ..................................... 131
Figure 48: Luxembourg - gross value added at market prices, broad definition .................. 132
Figure 49: Luxembourg - sector-specific multipliers and EU-averages ................................ 134
Figure 50: Malta - gross value added at market prices, broad definition .............................. 135
Figure 51: Malta - sector-specific multipliers and EU-averages ........................................... 137
Figure 52: Netherlands - gross value added at market prices, broad definition ................... 138
Figure 53: Netherlands - sector-specific multipliers and EU-averages ................................ 140
Figure 54: Poland - gross value added at market prices, broad definition ........................... 141
Figure 55: Poland - sector-specific multipliers and EU-averages ......................................... 143
Figure 56: Portugal - gross value added at market prices, broad definition ......................... 144
Figure 57: Portugal - sector-specific multipliers and EU-averages ...................................... 146
Figure 58: Romania - gross value added at market prices, broad definition ........................ 147
Figure 59: Romania - sector-specific multipliers and EU-averages ..................................... 149
Figure 60: Slovakia - gross value added at market prices, broad definition ......................... 150
Figure 61: Slovakia - sector-specific multipliers and EU-averages ...................................... 152
Figure 62: Slovenia - gross value added at market prices, broad definition ......................... 153
Figure 63: Slovenia - sector-specific multipliers and EU-averages ...................................... 155
Figure 64: Spain - gross value added at market prices, broad definition ............................. 156
Figure 65: Spain - sector-specific multipliers and EU-averages ........................................... 158
Figure 66: Sweden - gross value added at market prices, broad definition ......................... 159
Figure 67: Sweden - sector-specific multipliers and EU-averages ....................................... 161
Figure 68: United Kingdom - gross value added at market prices, broad definition ............. 162
Study on the Contribution of Sport to Economic Growth and Employment - 168 -
Figure 69: United Kingdom - sector-specific multipliers and EU-averages .......................... 164
Study on the Contribution of Sport to Economic Growth and Employment - 169 -
16 List of Tables
Table 1: Sport related gross value added and employment. All values correspond to the
Broad Definition and contain direct effects only ................................................................. 6
Table 2: Calculation Scheme for Effective Income ................................................................. 11
Table 3: Overview of some sport-related activities and products with economic impact ........ 13
Table 4: Scheme of Classifications ......................................................................................... 14
Table 5: Vilnius Definition Set of Rules ................................................................................... 15
Table 6: Availability of Input-Output and Supply and Use Tables ........................................... 22
Table 7: Moving production under the assumption of product technology ............................. 28
Table 8: Moving production under the assumption of industry technology ............................ 28
Table 9: Stylised Supply and Use Tables of Malta .................................................................. 30
Table 10: Adjustment Algorithms ............................................................................................ 33
Table 11: Different European Data Bases .............................................................................. 40
Table 12: Purchases of sport articles incl. VAT ....................................................................... 43
Table 13: UN definition of Sports Goods ................................................................................ 46
Table 14: Foreign trade in ski and ski equipment in m Euro. D stands for domestic. Red bars
indicate hidden countries ................................................................................................. 47
Table 15: Shares of exports staying within the EU ................................................................. 48
Table 16: Sport related expenditures in France in 2005 ......................................................... 52
Table 17: Expenditures of French private households in 2005 in more detail ........................ 53
Table 18: Employees in heads, estimated gross value added, and estimated production value
in the French sport industry 2005 .................................................................................... 54
Table 19: Foreign trade of sport-related goods in France in 2005 .......................................... 54
Table 20: Sports Nutrition, Gross Value Added and Multipliers .............................................. 67
Study on the Contribution of Sport to Economic Growth and Employment - 170 -
Table 21: Sports Insurance and Pension Funding, Gross Value Added and Multipliers ......... 68
Table 22: Economic and Legal Consultancy for Sport Clubs and Professional Athletes ........ 70
Table 23: Rasmussen indices of the EU-27 countries ........................................................... 73
Table 24: Product range of the EU-27 countries .................................................................... 76
Table 25: Sport-related GVA of the EU-27 countries, in million Euro and shares in EU GVA . 78
Table 26: Sport-related employment of the EU-27 countries, in persons and shares in EU
employment ..................................................................................................................... 79
Study on the Contribution of Sport to Economic Growth and Employment - 171 -
17 Bibliography
17.1 Methods and Data:
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Cartwright J.V. / Beemiller R.M. / Gustely R.D. (1981) Regional Input-Output Modelling
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Information, with an Application to Canadian Data, in: Economic Systems Research 11(2), S.
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Output-Model, in: International Regional Science Review 1(1), S. 30 – 46
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American Economic Review 43 (1), S. 167 - 180
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Isard W. (1998) Gravity and spatial interaction models, in: Isard W. et al (Hrsg) Methods of
Interregional and Regional Analysis, S. 41 – 133, Aldershot
Kurz H.D. / Dietzenbacher E./Lager C. (1998) Input-Output Analysis, Volume I – III, Edward
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Leontief W. (1966) Input-Output-Economics, Oxford University Press
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Sixth International Conference on Input-Output Techniques, Vienna, 22. – 26. 4. 1974,
Ballinger Publishing Company, Cambridge
Study on the Contribution of Sport to Economic Growth and Employment - 174 -
Polenske K.R. (1980) The U.S. Multiregional Input-Output Accounts and Model, Lexington
Books, USA
Preuß H. / Alfs Ch. (2012) Wirtschaftliche Bedeutung des Sportkonsums für Deutschland,
Johannes Gutenberg-Universität Mainz, Presentation, downloaded in March 2012.
Richardson H.W. (1985) Input-Output and Economic Base Multiplier Looking Backward and
Forward, in: Journal of Regional Science 25 (4), S. 605 – 661
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(Hrsg.) Applications for Input-Output-Analysis, Amsterdam
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17.2 Satellite Accounts and Sport Economics
Ahlert, G. (2005): Sportsatellitensysteme, Vergleich der konzeptionellen Grundlagen in
Deutschland und Frankreich, Studie der Gesellschaft für wirtschaftliche Strukturforschung im
Auftrag des Bundesinstituts für Sportwissenschaft, Osnabrück.
Commission of The European Communities (2007) White Paper on Sport, COM(2007)
391 final, Brussels 11 July.
Dimitrov C. / Felderer B. / Kleissner A. / Moser B. / Schnabl A. / Weissteiner T. (2006) A
Sports Satellite Account for Austria, Study financed by the OeNB Jubiläumsfonds, Vienna.
Grohall G. / Helmenstein C. / Kleissner A. (2010) Sport Satellite Accounts, Non-Technical
Methodology Paper, Vienna.
Helmenstein C. / Kleissner A. / Moser B. (2006) Sports in Austria. The Economic Impact of
Sports in Austria, Study ordered by the Austrian Federal Economic Chamber, Vienna.
Study on the Contribution of Sport to Economic Growth and Employment - 175 -
Madsen B. / Jensen B. C. (1998) Commodity Balance and Interregional Trade: Make and
Use Approaches to Interregional Modelling, Paper presented at the 12th International
Conference on Input-Output Techniques, New York 18-22 May.
Meerwaarde / SpEA (2007) The Use of sport satellite accounts for policy purposes,
Discussion paper for the EU sports directors, Amsterdam: Meerwaarde.
Meyer, B. / Ahlert G. (2000) Die ökonomischen Perspektiven des Sports, Schriftenreihe des
Bundesinstituts für Sportwissenschaft Band 100, Köln.
Piispala, J. (2000) On Regionalising Input/Output Tables - Experiences from Compiling
Regional supply and Use Tables in Finland, Paper presented at the XIII Conference on Input-
Output Techniques at University of Macareta, Italy, August 21-25th.
Piispala, J. (1999) Constructing Regional Supply and Use Tables in Finland, Paper
Presented at the European Regional Science Association (ERSA) 39th European Congress
in Dublin, Ireland, August 23-27.
EU-Commission (2010) Sport Satellite Accounts – A European Project: First Results, Leaflet
prepared for the meeting of Sports Director Generals in Barcelona/Spain, Brussels 25-26
February 2010.
EU-Commission (2011) Sport Satellite Accounts - A European Project: New Results, Leaflet,
Spring 2011, Brussels.
Vilnius Definition of Sport, official manual, retrieved from http://www.spea.at Vienna and
Vilnius.
Weber, W. / Schnieder, C. / Kortlüke, N. / Horak, B. (1995) Die wirtschaftliche Bedeutung
des Sports, Schriftenreihe des Bundesinstituts für Sportwissenschaft Band 81, Köln.
17.3 Sources of Statistic:
Eurostat: Eurostat, Statistical office of the European Union,
Bâtiment Joseph Bech, 5, rue Alphonse Weicker
2721 Luxembourg
http://epp.eurostat.ec.europa.eu/
Source-OECD: OECD
2, rue André Pascal
75775 Paris 16
http:// www.sourceoecd.org/
Study on the Contribution of Sport to Economic Growth and Employment - 176 -
Annex: National Data Sheets
The following tables give an overview of each of the 27 Member States. The most basic
national results are given. Sport-related GVA and employment data are stated in absolute
terms as well as in relation to the nation’s total values. For each sport-related sector the GVA
is reported in absolute terms and as the share of the sector’s total GVA. For example,
Austria’s sector 1, Products of agriculture, reports 2.35 million Euro GVA which is 0.12% of
sector 1’s total value. Thus 1,924.26 million Euros are the remaining 98.88% non-sport
agriculture GVA.
Sector multipliers show how much an economy’s production has to increase if the sector’s
production is increased by 1 unit. Austria’s sport-related sector 1, Products of agriculture, has
a domestic multiplier of 1.51. If this sector’s production is therefore increased by 1 unit (e.g.
100,000 Euro), Austria’s total production value has to increase by 1.51 units to supply
sector 1 with the necessary intermediate goods and services.
Some intermediate goods, however, are imported rather than produced domestically. It is
likely that at least some of these imports originate from another EU Member State. If this is
the case, increasing the production of Austria’s sport-related sector 1 also increases the
production in other Member States. In the example, these are 0.26 units as the EU-wide
increase of production equals 1.77 units.
The difference between the domestic and the EU-wide multipliers can thus be interpreted as
the contribution of domestic production of one sector to the production of the other EU-
member states through the sector’s supply chain.
Study on the Contribution of Sport to Economic Growth and Employment - 177 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 2.35 0.12% 1.51 1.77
15 Food products and beverages 14.56 0.33% 1.65 1.93
17 Textiles 16.13 2.37% 1.27 1.53
18 Wearing apparel; furs 38.46 13.07% 1.11 1.22
19 Leather and leather products 21.82 10.20% 1.27 1.46
22 Printed matter and recorded media 35.87 1.79% 1.62 1.88
23 Coke, refined petroleum products and nuclear fuels 2.87 2.00% 1.37 1.46
24 Chemicals, chemical products and man-made fibres 12.27 0.47% 1.27 1.46
25 Rubber and plastic products 0.38 0.02% 1.34 1.60
28
Fabricated metal products,exc. machinery and equipment
11.58 0.32% 1.45 1.75
29 Machinery and equipment n.e.c. 0.77 0.01% 1.39 1.68
33 Medical, precision and optical instrum., watches, clocks 18.87 1.58% 1.23 1.36
34 Motor vehicles, trailers and semi-trailers 3.44 0.12% 1.33 1.76
35 Other transport equipment 24.50 2.84% 1.29 1.47
36 Furniture; other manufactured goods n.e.c. 238.22 12.26% 1.41 1.67
45 Construction work 136.91
0.87%
1.64 1.90
50
Trade, maintenance and repair services of motor vehicles
173.34 4.75% 1.55 1.84
51 Wholesale trade and commission trade services 338.82 2.21% 1.55 1.71
52 Retail trade services 553.38 5.68% 1.55 1.65
55 Hotel and restaurant services 3121.52 29.69% 1.44 1.58
60 Land transport; transport via pipeline services 13.41 0.24% 1.56 1.74
61 Water transport services 0.14 0.50% 1.10 1.13
62 Air transport services 12.65 2.05% 1.79 2.06
63 Supporting and auxiliary transport services;travel agency 7.65 0.28% 1.86 2.04
64 Post and telecommunication services 8.00 0.18% 1.71 1.90
65 Financial intermediation services 31.60 0.43% 1.56 1.63
66 Insurance and pension funding services 34.56 1.16% 1.66 1.74
71 Renting services of machinery and equipment 101.56 2.68% 1.38 1.44
73 Research and development services 15.90 2.00% 1.52 1.66
74 Other business services 24.79 0.16% 1.62 1.73
75 Public administration and defence services 124.08 1.01% 1.39 1.47
80 Education services 1531.66 13.25% 1.19 1.24
85 Health and social work services 1029.03 8.20% 1.38 1.54
92 Recreational, cultural and sporting services 1101.79 30.32% 1.52 1.61
93 Other services 35.15 2.07% 1.41 1.52
Sector-specific Multiplier
0.25 %
2.12 %
4.03 %
0.36 %
3.21 %
% of total
0.55 bn €
4.65 bn €
8.84 bn €
13,850
Direct Effects
National Data Sheet
Austria
GROSS VALUE ADDED
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Description
Statistical Definition
EMPLOYMENT
CPA
122,833
205,863
DETAILED INFORMATION on SECTORAL LEVEL
GROSS VALUE ADDED
(Market Prices, Mio. €)
Narrow Definition
Broad Definition
Narrow Definition
Broad Definition
5.38 %
Statistical Definition
Study on the Contribution of Sport to Economic Growth and Employment - 178 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 73.15 3.56% 1.40 1.64
15 Food products and beverages 5.43 0.09% 1.63 2.01
17 Textiles 16.27 1.16% 1.44 1.82
18 Wearing apparel; furs 59.60 19.48% 1.19 1.34
19 Leather and leather products 1.53 2.30% 1.09 1.18
22 Printed matter and recorded media 133.92 5.88% 1.67 1.97
23 Coke, refined petroleum products and nuclear fuels 6.72 0.56% 1.50 1.81
24 Chemicals, chemical products and man-made fibres 21.55 0.24% 1.40 1.77
25 Rubber and plastic products 13.58 0.72% 1.30 1.58
28
Fabricated metal products,exc. machinery and equipment
1.00 0.03% 1.50 1.85
29 Machinery and equipment n.e.c. 1.62 0.05% 1.28 1.53
33 Medical, precision and optical instrum., watches, clocks 2.90 0.45% 1.17 1.29
34 Motor vehicles, trailers and semi-trailers 12.12 0.45% 1.24 1.68
35 Other transport equipment 73.79 11.66% 1.28 1.47
36 Furniture; other manufactured goods n.e.c. 29.48 3.15% 1.20 1.34
45 Construction work 0.29
0.00%
2.09 2.45
50
Trade, maintenance and repair services of motor vehicles
108.87 2.67% 1.71 2.04
51 Wholesale trade and commission trade services 334.92 1.46% 1.70 1.91
52 Retail trade services 134.26 1.38% 1.66 1.82
55 Hotel and restaurant services 192.52 4.32% 1.58 1.87
60 Land transport; transport via pipeline services 56.71 0.95% 1.66 1.87
61 Water transport services 4.00 0.48% 2.12 2.39
62 Air transport services 8.85 1.87% 1.80 2.10
63 Supporting and auxiliary transport services;travel agency 17.38 0.21% 1.76 1.97
64 Post and telecommunication services 0.54 0.01% 1.55 1.71
65 Financial intermediation services 28.03 0.44% 1.54 1.62
66 Insurance and pension funding services 4.84 0.17% 1.83 1.94
71 Renting services of machinery and equipment 4.67 0.17% 1.61 1.78
73 Research and development services 7.94 0.43% 1.43 1.57
74 Other business services 68.84 0.24% 1.72 1.85
75 Public administration and defence services 15.16 0.08% 1.28 1.36
80 Education services 604.79 3.63% 1.12 1.15
85 Health and social work services 79.51 0.42% 1.44 1.62
92 Recreational, cultural and sporting services 764.51 21.29% 1.72 1.86
93 Other services 153.57 14.09% 1.62 1.93
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Belgium
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.38 bn €
0.14 %
Narrow Definition
2.27 bn €
0.84 %
Broad Definition
3.04 bn €
1.13 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
10,336
0.24 %
Narrow Definition
56,153
1.33 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
71,416
1.69 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 179 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 2.51 0.15% 1.72 1.88
15 Food products and beverages 0.47 0.08% 1.96 2.15
17 Textiles 1.07 0.76% 1.70 1.92
18 Wearing apparel; furs 16.42 4.97% 1.69 1.91
19 Leather and leather products 3.23 7.98% 1.48 1.61
22 Printed matter and recorded media 2.83 2.45% 1.81 2.06
23 Coke, refined petroleum products and nuclear fuels 0.33 0.14% 1.64 1.72
24 Chemicals, chemical products and man-made fibres 0.84 0.30% 1.49 1.65
25 Rubber and plastic products 0.83 1.05% 1.55 1.78
28
Fabricated metal products,exc. machinery and equipment
1.96 1.13% 1.70 1.92
29 Machinery and equipment n.e.c. 0.28 0.08% 1.43 1.57
33 Medical, precision and optical instrum., watches, clocks 0.40 0.88% 1.41 1.53
34 Motor vehicles, trailers and semi-trailers 0.49 2.23% 1.01 1.01
35 Other transport equipment 11.38 20.46% 1.61 1.78
36 Furniture; other manufactured goods n.e.c. 19.85 17.35% 1.68 1.88
45 Construction work 4.99
0.46%
2.13 2.47
50
Trade, maintenance and repair services of motor vehicles
0.48 0.14% 1.70 1.90
51 Wholesale trade and commission trade services 1.02 0.13% 2.08 2.28
52 Retail trade services 3.30 0.32% 1.49 1.62
55 Hotel and restaurant services 4.58 1.01% 1.71 1.89
60 Land transport; transport via pipeline services 2.60 0.39% 2.04 2.28
61 Water transport services 1.12 1.34% 1.80 2.00
62 Air transport services 0.12 0.44% 1.98 2.22
63 Supporting and auxiliary transport services;travel agency 6.53 1.89% 2.06 2.32
64 Post and telecommunication services 0.54 0.06% 1.59 1.73
65 Financial intermediation services 2.23 0.21% 1.35 1.43
66 Insurance and pension funding services 0.60 0.57% 1.89 2.10
71 Renting services of machinery and equipment 0.55 1.01% 1.37 1.47
73 Research and development services 0.70 1.39% 1.37 1.47
74 Other business services 1.41 0.23% 1.85 2.03
75 Public administration and defence services 1.12 0.09% 1.59 1.76
80 Education services 85.24 9.95% 1.34 1.42
85 Health and social work services 16.67 2.48% 1.62 1.81
92 Recreational, cultural and sporting services 25.54 9.96% 1.84 2.06
93 Other services 0.58 1.13% 1.48 1.62
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Bulgaria
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.01 bn €
0.06 %
Narrow Definition
0.18 bn €
0.93 %
Broad Definition
0.22 bn €
1.13 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
3,344
0.11 %
Narrow Definition
49,168
1.65 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
55,843
1.87 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 180 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 0.75 0.22% 1.78 2.04
15 Food products and beverages 1.17 0.42% 1.91 2.18
17 Textiles 0.03 0.21% 1.01 1.03
18 Wearing apparel; furs 0.91 10.21% 1.08 1.30
19 Leather and leather products 0.00 0.00% 1.00 1.00
22 Printed matter and recorded media 2.87 4.47% 1.43 1.91
23 Coke, refined petroleum products and nuclear fuels 0.14 4.59% 1.00 1.00
24 Chemicals, chemical products and man-made fibres 2.34 3.85% 1.38 1.84
25 Rubber and plastic products 0.28 0.79% 1.38 1.84
28
Fabricated metal products,exc. machinery and equipment
0.03 0.07% 1.08 1.17
29 Machinery and equipment n.e.c. 0.35 2.49% 1.17 1.43
33 Medical, precision and optical instrum., watches, clocks -0.01 0.09% 1.03 1.18
34 Motor vehicles, trailers and semi-trailers 0.00 0.00% 1.00 1.00
35 Other transport equipment 2.79 62.76% 1.20 1.40
36 Furniture; other manufactured goods n.e.c. 0.06 0.26% 1.01 1.03
45 Construction work 8.30
0.85%
1.55 1.91
50
Trade, maintenance and repair services of motor vehicles
0.79 0.36% 1.38 1.65
51 Wholesale trade and commission trade services 0.00 0.00% 1.00 1.00
52 Retail trade services 0.00 0.00% 1.00 1.00
55 Hotel and restaurant services 3.95 0.51% 1.37 1.54
60 Land transport; transport via pipeline services 0.77 0.68% 1.32 1.53
61 Water transport services 0.00 0.00% 1.00 1.00
62 Air transport services 0.79 0.55% 1.63 2.02
63 Supporting and auxiliary transport services;travel agency 0.70 0.18% 1.28 1.38
64 Post and telecommunication services 2.33 0.54% 1.20 1.30
65 Financial intermediation services 1.06 0.52% 1.49 1.72
66 Insurance and pension funding services 2.80 3.17% 1.62 1.84
71 Renting services of machinery and equipment 0.38 0.68% 1.29 1.40
73 Research and development services 0.00 0.00% 1.00 1.00
74 Other business services 7.83 1.27% 1.22 1.32
75 Public administration and defence services 1.03 0.08% 1.22 1.36
80 Education services 52.02 7.07% 1.10 1.14
85 Health and social work services 7.70 1.57% 1.29 1.54
92 Recreational, cultural and sporting services 137.61 47.92% 1.38 1.51
93 Other services 6.95 5.31% 1.25 1.39
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Cyprus
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.07 bn €
0.65 %
Narrow Definition
0.19 bn €
1.79 %
Broad Definition
0.25 bn €
2.34 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
1,706
0.56 %
Narrow Definition
6,356
2.09 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
7,822
2.57 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 181 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 3.05 0.16% 1.60 1.83
15 Food products and beverages 2.03 0.09% 1.96 2.25
17 Textiles 5.59 0.92% 1.46 1.76
18 Wearing apparel; furs 31.98 11.52% 1.21 1.52
19 Leather and leather products 4.09 5.24% 1.19 1.42
22 Printed matter and recorded media 5.10 0.67% 1.75 2.10
23 Coke, refined petroleum products and nuclear fuels 1.04 0.50% 1.72 1.83
24 Chemicals, chemical products and man-made fibres 8.25 0.67% 1.36 1.57
25 Rubber and plastic products 12.23 0.82% 1.47 1.89
28
Fabricated metal products,exc. machinery and equipment
15.35 0.61% 1.63 2.02
29 Machinery and equipment n.e.c. 1.35 0.06% 1.43 1.78
33 Medical, precision and optical instrum., watches, clocks 2.32 0.48% 1.32 1.62
34 Motor vehicles, trailers and semi-trailers 0.56 0.02% 1.61 2.12
35 Other transport equipment 24.75 8.37% 1.43 1.74
36 Furniture; other manufactured goods n.e.c. 118.36 13.36% 1.53 1.88
45 Construction work 18.93
0.32%
2.29 2.58
50
Trade, maintenance and repair services of motor vehicles
16.04 1.12% 1.84 2.16
51 Wholesale trade and commission trade services 11.59 0.18% 1.75 1.88
52 Retail trade services 14.75 0.39% 1.67 1.77
55 Hotel and restaurant services 55.13 2.98% 1.76 1.91
60 Land transport; transport via pipeline services 17.15 0.51% 1.76 1.95
61 Water transport services 0.02 0.35% 1.58 1.71
62 Air transport services 1.01 0.61% 1.69 1.91
63 Supporting and auxiliary transport services;travel agency 91.71 3.10% 2.09 2.26
64 Post and telecommunication services 0.27 0.01% 1.70 1.80
65 Financial intermediation services 5.87 0.28% 1.84 1.94
66 Insurance and pension funding services 0.85 0.33% 2.22 2.38
71 Renting services of machinery and equipment 3.17 0.78% 1.78 1.93
73 Research and development services 1.04 0.32% 1.25 1.34
74 Other business services 1.24 0.02% 1.89 2.02
75 Public administration and defence services 9.64 0.19% 1.58 1.67
80 Education services 192.09 4.97% 1.37 1.47
85 Health and social work services 254.51 7.16% 1.46 1.64
92 Recreational, cultural and sporting services 130.73 8.61% 1.87 1.99
93 Other services 0.62 0.12% 1.52 1.65
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Czech Republic
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.07 bn €
0.07 %
Narrow Definition
0.71 bn €
0.80 %
Broad Definition
1.06 bn €
1.18 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
6,949
0.15 %
Narrow Definition
65,769
1.38 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
89,119
1.87 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 182 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 0.00 0.00% 1.00 1.00
15 Food products and beverages 1.89 0.05% 1.80 2.06
17 Textiles 5.94 1.80% 1.26 1.47
18 Wearing apparel; furs 13.58 18.20% 1.13 1.22
19 Leather and leather products 2.25 12.63% 1.06 1.09
22 Printed matter and recorded media 72.42 3.89% 1.71 1.97
23 Coke, refined petroleum products and nuclear fuels 0.01 0.02% 1.42 1.46
24 Chemicals, chemical products and man-made fibres 5.17 0.15% 1.40 1.59
25 Rubber and plastic products 14.33 1.13% 1.37 1.60
28
Fabricated metal products,exc. machinery and equipment
0.81 0.04% 1.45 1.79
29 Machinery and equipment n.e.c. 38.11 1.08% 1.40 1.67
33 Medical, precision and optical instrum., watches, clocks 4.07 0.31% 1.33 1.50
34 Motor vehicles, trailers and semi-trailers 19.68 5.55% 1.09 1.18
35 Other transport equipment 26.25 7.78% 1.29 1.54
36 Furniture; other manufactured goods n.e.c. 135.51 9.89% 1.45 1.70
45 Construction work 2.28
0.02%
1.75 2.06
50
Trade, maintenance and repair services of motor vehicles
32.36 1.21% 1.52 1.78
51 Wholesale trade and commission trade services 177.18 1.49% 1.64 1.78
52 Retail trade services 78.53 1.21% 1.49 1.58
55 Hotel and restaurant services 74.24 2.93% 1.67 1.86
60 Land transport; transport via pipeline services 17.94 0.43% 1.64 1.79
61 Water transport services 8.02 0.20% 1.83 2.01
62 Air transport services 2.27 1.01% 1.78 1.99
63 Supporting and auxiliary transport services;travel agency 2.31 0.09% 1.22 1.28
64 Post and telecommunication services 31.57 0.79% 1.70 1.85
65 Financial intermediation services 11.99 0.18% 1.47 1.54
66 Insurance and pension funding services 4.07 0.18% 1.57 1.63
71 Renting services of machinery and equipment 0.99 0.13% 1.86 2.01
73 Research and development services 0.90 0.16% 1.50 1.63
74 Other business services 6.10 0.05% 1.54 1.64
75 Public administration and defence services 61.53 0.56% 1.41 1.51
80 Education services 2126.69 21.51% 1.33 1.38
85 Health and social work services 285.19 1.51% 1.33 1.41
92 Recreational, cultural and sporting services 448.56 13.28% 1.62 1.72
93 Other services 5.81 0.69% 1.19 1.24
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Denmark
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.22 bn €
0.13 %
Narrow Definition
3.20 bn €
1.82 %
Broad Definition
3.72 bn €
2.12 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
4,330
0.16 %
Narrow Definition
58,362
2.12 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
69,287
2.52 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 183 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 1.25 0.61% 1.55 1.83
15 Food products and beverages 0.39 0.19% 1.63 1.94
17 Textiles 1.17 1.42% 1.33 1.60
18 Wearing apparel; furs 2.82 4.16% 1.39 1.72
19 Leather and leather products 0.77 7.61% 1.14 1.37
22 Printed matter and recorded media 4.10 4.20% 1.71 2.06
23 Coke, refined petroleum products and nuclear fuels 0.36 1.34% 1.11 1.14
24 Chemicals, chemical products and man-made fibres 0.23 0.32% 1.18 1.40
25 Rubber and plastic products 0.47 0.78% 1.25 1.58
28
Fabricated metal products,exc. machinery and equipment
0.64 0.60% 1.38 1.85
29 Machinery and equipment n.e.c. 0.33 0.34% 1.15 1.31
33 Medical, precision and optical instrum., watches, clocks 0.12 0.46% 1.25 1.51
34 Motor vehicles, trailers and semi-trailers 0.03 0.08% 1.08 1.19
35 Other transport equipment 4.38 12.80% 1.52 1.77
36 Furniture; other manufactured goods n.e.c. 13.31 11.42% 1.65 1.97
45 Construction work 4.65
0.68%
1.72 2.11
50
Trade, maintenance and repair services of motor vehicles
0.52 0.24% 1.52 1.79
51 Wholesale trade and commission trade services 2.19 0.26% 1.64 1.80
52 Retail trade services 1.63 0.38% 1.63 1.76
55 Hotel and restaurant services 3.87 2.18% 1.69 2.06
60 Land transport; transport via pipeline services 2.13 0.56% 1.78 1.97
61 Water transport services 0.64 1.64% 1.92 2.07
62 Air transport services 0.34 1.45% 1.98 2.15
63 Supporting and auxiliary transport services;travel agency 2.12 0.57% 2.09 2.32
64 Post and telecommunication services 0.09 0.03% 1.73 1.84
65 Financial intermediation services 3.40 1.57% 1.49 1.57
66 Insurance and pension funding services 0.33 0.79% 1.72 1.80
71 Renting services of machinery and equipment 1.37 0.91% 1.45 1.60
73 Research and development services 0.31 0.79% 1.40 1.57
74 Other business services 1.62 0.28% 1.49 1.62
75 Public administration and defence services 1.79 0.35% 1.48 1.62
80 Education services 77.17 17.32% 1.36 1.48
85 Health and social work services 7.17 2.43% 1.37 1.62
92 Recreational, cultural and sporting services 20.03 10.09% 1.62 1.79
93 Other services 0.05 0.11% 1.55 1.79
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Estonia
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.01 bn €
0.10 %
Narrow Definition
0.13 bn €
1.35 %
Broad Definition
0.16 bn €
1.64 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
1,121
0.18 %
Narrow Definition
13,662
2.25 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
15,686
2.58 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 184 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 0.36 0.02% 1.89 2.09
15 Food products and beverages 3.00 0.13% 2.08 2.32
17 Textiles 3.29 1.20% 1.32 1.49
18 Wearing apparel; furs 21.64 12.44% 1.18 1.27
19 Leather and leather products 5.63 7.04% 1.23 1.36
22 Printed matter and recorded media 7.61 0.40% 1.91 2.04
23 Coke, refined petroleum products and nuclear fuels 2.57 0.37% 1.62 1.75
24 Chemicals, chemical products and man-made fibres 0.93 0.05% 1.45 1.63
25 Rubber and plastic products 3.05 0.29% 1.54 1.77
28
Fabricated metal products,exc. machinery and equipment
2.40 0.10% 1.73 1.95
29 Machinery and equipment n.e.c. 0.93 0.02% 1.69 1.94
33 Medical, precision and optical instrum., watches, clocks 1.28 0.16% 1.46 1.61
34 Motor vehicles, trailers and semi-trailers 1.83 0.51% 1.17 1.36
35 Other transport equipment 67.56 9.72% 1.67 1.90
36 Furniture; other manufactured goods n.e.c. 102.07 15.97% 1.64 1.82
45 Construction work 21.94
0.24%
1.96 2.16
50
Trade, maintenance and repair services of motor vehicles
39.72 1.51% 1.69 1.79
51 Wholesale trade and commission trade services 35.94 0.55% 1.78 1.92
52 Retail trade services 198.40 3.98% 1.65 1.75
55 Hotel and restaurant services 354.00 15.59% 1.80 1.95
60 Land transport; transport via pipeline services 2.10 0.05% 1.64 1.74
61 Water transport services 2.05 0.23% 1.64 1.78
62 Air transport services 4.54 0.61% 1.82 1.97
63 Supporting and auxiliary transport services;travel agency 8.93 0.28% 1.85 1.98
64 Post and telecommunication services 1.13 0.04% 1.94 2.08
65 Financial intermediation services 4.92 0.20% 1.46 1.54
66 Insurance and pension funding services 7.68 1.37% 1.71 1.83
71 Renting services of machinery and equipment 5.93 1.24% 1.54 1.65
73 Research and development services 2.37 0.32% 1.22 1.26
74 Other business services 2.82 0.04% 1.49 1.58
75 Public administration and defence services 8.13 0.12% 1.59 1.70
80 Education services 855.71 12.67% 1.40 1.46
85 Health and social work services 551.06 4.64% 1.41 1.49
92 Recreational, cultural and sporting services 310.75 12.80% 1.71 1.79
93 Other services 11.36 1.98% 1.64 1.75
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Finland
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.16 bn €
0.11 %
Narrow Definition
1.90 bn €
1.39 %
Broad Definition
2.65 bn €
1.94 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
4,856
0.20 %
Narrow Definition
54,501
2.27 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
74,209
3.09 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 185 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 0.00 0.00% 1.00 1.00
15 Food products and beverages 0.00 0.00% 1.00 1.00
17 Textiles 0.00 0.00% 1.00 1.00
18 Wearing apparel; furs 1224.54 37.36% 1.79 2.05
19 Leather and leather products 349.49 28.69% 1.53 1.70
22 Printed matter and recorded media 0.00 0.00% 1.00 1.00
23 Coke, refined petroleum products and nuclear fuels 0.00 0.00% 1.00 1.00
24 Chemicals, chemical products and man-made fibres 0.00 0.00% 1.00 1.00
25 Rubber and plastic products 0.00 0.00% 1.00 1.00
28
Fabricated metal products,exc. machinery and equipment
0.00 0.00% 1.00 1.00
29 Machinery and equipment n.e.c. 13.47 0.07% 1.30 1.39
33 Medical, precision and optical instrum., watches, clocks 0.00 0.00% 1.00 1.00
34 Motor vehicles, trailers and semi-trailers 0.00 0.00% 1.00 1.00
35 Other transport equipment 767.20 8.69% 1.87 2.21
36 Furniture; other manufactured goods n.e.c. 269.98 4.27% 1.72 1.94
45 Construction work 0.00
0.00%
1.00 1.00
50
Trade, maintenance and repair services of motor vehicles
0.00 0.00% 1.00 1.00
51 Wholesale trade and commission trade services 0.00 0.00% 1.00 1.00
52 Retail trade services 1817.30 2.74% 1.59 1.65
55 Hotel and restaurant services 509.89 1.35% 1.81 1.94
60 Land transport; transport via pipeline services 163.31 0.47% 1.65 1.73
61 Water transport services 13.37 0.62% 2.17 2.32
62 Air transport services 49.37 0.83% 1.67 1.81
63 Supporting and auxiliary transport services;travel agency 945.96 3.91% 1.72 1.82
64 Post and telecommunication services 707.98 2.16% 1.74 1.83
65 Financial intermediation services 447.01 1.01% 1.79 1.85
66 Insurance and pension funding services 47.65 0.26% 1.86 1.90
71 Renting services of machinery and equipment 215.94 1.73% 1.77 1.82
73 Research and development services 71.23 0.53% 1.85 2.00
74 Other business services 1273.33 0.82% 1.67 1.73
75 Public administration and defence services 2131.10 2.00% 1.43 1.49
80 Education services 3473.95 4.20% 1.28 1.32
85 Health and social work services 454.12 0.35% 1.36 1.42
92 Recreational, cultural and sporting services 6343.95 21.09% 1.78 1.87
93 Other services 316.81 3.46% 1.48 1.54
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
France
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
3.17 bn €
0.20 %
Narrow Definition
14.71 bn €
0.95 %
Broad Definition
21.61 bn €
1.40 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
91,773
0.37 %
Narrow Definition
323,381
1.30 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
416,537
1.67 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 186 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 12.20 0.08% 1.56 1.69
15 Food products and beverages 326.57 1.02% 1.84 2.05
17 Textiles 55.86 1.22% 1.37 1.53
18 Wearing apparel; furs 718.20 31.93% 1.25 1.40
19 Leather and leather products 220.62 26.39% 1.19 1.34
22 Printed matter and recorded media 1747.41 8.23% 1.74 1.85
23 Coke, refined petroleum products and nuclear fuels 27.83 0.59% 1.63 1.78
24 Chemicals, chemical products and man-made fibres 868.32 2.23% 1.55 1.72
25 Rubber and plastic products 633.52 3.03% 1.59 1.80
28
Fabricated metal products,exc. machinery and equipment
872.46 2.18% 1.68 1.87
29 Machinery and equipment n.e.c. 705.28 1.03% 1.67 1.86
33 Medical, precision and optical instrum., watches, clocks 44.82 0.21% 1.45 1.56
34 Motor vehicles, trailers and semi-trailers 886.50 1.59% 1.85 2.15
35 Other transport equipment 223.26 2.29% 1.46 1.60
36 Furniture; other manufactured goods n.e.c. 395.55 3.76% 1.55 1.72
45 Construction work 43.43
0.05%
1.78 1.95
50
Trade, maintenance and repair services of motor vehicles
963.08 2.30% 1.44 1.52
51 Wholesale trade and commission trade services 1722.77 1.77% 1.62 1.70
52 Retail trade services 3630.42 4.24% 1.62 1.68
55 Hotel and restaurant services 8899.11 26.38% 1.61 1.72
60 Land transport; transport via pipeline services 2696.42 9.05% 1.66 1.76
61 Water transport services 372.10 5.69% 1.84 1.96
62 Air transport services 457.57 8.64% 1.97 2.19
63 Supporting and auxiliary transport services;travel agency 551.96 1.69% 1.83 1.95
64 Post and telecommunication services 23.57 0.06% 1.73 1.81
65 Financial intermediation services 83.03 0.12% 1.63 1.68
66 Insurance and pension funding services 239.15 2.10% 2.23 2.31
71 Renting services of machinery and equipment 203.66 0.47% 1.25 1.25
73 Research and development services 7.42 0.08% 1.58 1.65
74 Other business services 41.84 0.02% 1.48 1.52
75 Public administration and defence services 85.14 0.07% 1.41 1.47
80 Education services 5450.84 5.89% 1.28 1.31
85 Health and social work services 2079.99 1.42% 1.37 1.43
92 Recreational, cultural and sporting services 11387.53 30.33% 1.55 1.60
93 Other services 0.00 0.00% 1.00 1.00
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Germany
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
5.69 bn €
0.28 %
Narrow Definition
27.11 bn €
1.34 %
Broad Definition
46.68 bn €
2.31 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
143,267
0.39 %
Narrow Definition
669,892
1.84 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
1,146,234
3.15 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 187 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 147.44 1.99% 1.45 1.52
15 Food products and beverages 15.32 0.34% 1.79 1.92
17 Textiles 41.21 6.05% 1.35 1.45
18 Wearing apparel; furs 65.16 6.75% 1.39 1.49
19 Leather and leather products 12.35 7.02% 1.23 1.33
22 Printed matter and recorded media 87.19 9.11% 1.52 1.69
23 Coke, refined petroleum products and nuclear fuels 7.75 0.76% 1.72 1.75
24 Chemicals, chemical products and man-made fibres 6.69 0.64% 1.23 1.33
25 Rubber and plastic products 0.24 0.04% 1.38 1.56
28
Fabricated metal products,exc. machinery and equipment
0.11 0.01% 1.68 1.89
29 Machinery and equipment n.e.c. 0.74 0.11% 1.18 1.25
33 Medical, precision and optical instrum., watches, clocks 0.62 0.40% 1.08 1.11
34 Motor vehicles, trailers and semi-trailers 0.33 0.31% 1.04 1.06
35 Other transport equipment 29.13 5.09% 1.24 1.28
36 Furniture; other manufactured goods n.e.c. 42.87 7.35% 1.33 1.43
45 Construction work 20.45
0.18%
1.67 1.84
50
Trade, maintenance and repair services of motor vehicles
8.91 0.21% 1.36 1.41
51 Wholesale trade and commission trade services 107.34 0.78% 1.44 1.52
52 Retail trade services 142.42 1.26% 1.37 1.42
55 Hotel and restaurant services 148.83 1.24% 1.52 1.64
60 Land transport; transport via pipeline services 4.61 0.22% 1.64 1.71
61 Water transport services 17.03 0.23% 1.56 1.62
62 Air transport services 6.18 0.90% 1.41 1.45
63 Supporting and auxiliary transport services;travel agency 8.10 0.43% 1.21 1.24
64 Post and telecommunication services 164.24 3.68% 1.21 1.24
65 Financial intermediation services 36.85 0.51% 1.30 1.33
66 Insurance and pension funding services 1.91 0.25% 1.47 1.50
71 Renting services of machinery and equipment 1.76 0.41% 1.55 1.62
73 Research and development services 0.91 0.42% 1.59 1.67
74 Other business services 1.17 0.03% 1.65 1.72
75 Public administration and defence services 9.96 0.07% 1.35 1.45
80 Education services 97.96 0.97% 1.13 1.16
85 Health and social work services 3.96 0.06% 1.34 1.55
92 Recreational, cultural and sporting services 1261.95 47.71% 1.57 1.64
93 Other services 16.54 0.59% 1.28 1.31
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Greece
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.63 bn €
0.36 %
Narrow Definition
1.74 bn €
1.00 %
Broad Definition
2.52 bn €
1.44 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
19,594
0.45 %
Narrow Definition
56,226
1.29 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
70,878
1.63 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 188 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 17.47 0.61% 1.82 1.99
15 Food products and beverages 0.85 0.05% 2.13 2.32
17 Textiles 1.02 0.54% 1.30 1.52
18 Wearing apparel; furs 18.52 7.57% 1.43 1.82
19 Leather and leather products 4.53 4.10% 1.33 1.62
22 Printed matter and recorded media 15.03 2.66% 1.80 2.09
23 Coke, refined petroleum products and nuclear fuels 3.98 0.52% 1.64 1.74
24 Chemicals, chemical products and man-made fibres 7.24 0.46% 1.42 1.59
25 Rubber and plastic products 4.00 0.60% 1.41 1.70
28
Fabricated metal products,exc. machinery and equipment
5.70 0.64% 1.42 1.77
29 Machinery and equipment n.e.c. 0.27 0.02% 1.36 1.65
33 Medical, precision and optical instrum., watches, clocks 0.74 0.18% 1.25 1.40
34 Motor vehicles, trailers and semi-trailers 6.46 0.36% 1.32 1.89
35 Other transport equipment 16.87 10.74% 1.48 1.75
36 Furniture; other manufactured goods n.e.c. 44.26 13.29% 1.43 1.70
45 Construction work 46.88
1.18%
1.75 2.11
50
Trade, maintenance and repair services of motor vehicles
3.17 0.31% 1.73 2.01
51 Wholesale trade and commission trade services 26.95 0.78% 1.82 2.00
52 Retail trade services 6.82 0.21% 1.67 1.80
55 Hotel and restaurant services 26.83 2.16% 1.93 2.13
60 Land transport; transport via pipeline services 19.58 0.85% 1.58 1.76
61 Water transport services 0.04 0.28% 1.39 1.52
62 Air transport services 0.34 0.86% 1.69 1.89
63 Supporting and auxiliary transport services;travel agency 49.56 5.08% 1.51 1.63
64 Post and telecommunication services 0.32 0.01% 1.46 1.54
65 Financial intermediation services 1.13 0.05% 1.59 1.65
66 Insurance and pension funding services 3.05 0.63% 1.85 1.91
71 Renting services of machinery and equipment 6.24 0.90% 1.22 1.29
73 Research and development services 1.69 0.46% 1.40 1.52
74 Other business services 4.83 0.08% 1.52 1.62
75 Public administration and defence services 4.54 0.07% 1.30 1.36
80 Education services 269.02 6.23% 1.29 1.35
85 Health and social work services 48.00 1.33% 1.43 1.58
92 Recreational, cultural and sporting services 109.46 8.92% 1.82 1.95
93 Other services 2.52 0.17% 1.47 1.57
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Hungary
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.05 bn €
0.07 %
Narrow Definition
0.60 bn €
0.79 %
Broad Definition
0.78 bn €
1.02 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
4,205
0.11 %
Narrow Definition
45,409
1.16 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
55,577
1.43 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 189 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 245.14 10.18% 1.75 2.04
15 Food products and beverages 16.38 0.39% 1.78 2.05
17 Textiles 6.50 4.05% 1.19 1.34
18 Wearing apparel; furs 7.39 10.36% 1.06 1.11
19 Leather and leather products 4.82 49.50% 1.04 1.06
22 Printed matter and recorded media 39.99 1.17% 1.71 1.99
23 Coke, refined petroleum products and nuclear fuels 5.19 1.08% 1.37 1.51
24 Chemicals, chemical products and man-made fibres 32.42 0.29% 1.58 1.75
25 Rubber and plastic products 0.24 0.04% 1.28 1.48
28
Fabricated metal products,exc. machinery and equipment
0.07 0.01% 1.29 1.58
29 Machinery and equipment n.e.c. 0.90 0.10% 1.17 1.34
33 Medical, precision and optical instrum., watches, clocks 11.34 0.46% 1.40 1.59
34 Motor vehicles, trailers and semi-trailers 0.60 0.33% 1.09 1.15
35 Other transport equipment 6.57 2.70% 1.07 1.12
36 Furniture; other manufactured goods n.e.c. 0.00 0.00% 1.00 1.00
45 Construction work 14.20
0.10%
1.87 2.17
50
Trade, maintenance and repair services of motor vehicles
3.15 0.21% 1.38 1.51
51 Wholesale trade and commission trade services 68.22 0.60% 1.13 1.16
52 Retail trade services 75.24 1.38% 1.43 1.52
55 Hotel and restaurant services 43.43 1.30% 1.69 1.94
60 Land transport; transport via pipeline services 4.51 0.20% 1.44 1.59
61 Water transport services 0.16 0.10% 1.76 1.95
62 Air transport services 9.62 1.03% 1.57 1.77
63 Supporting and auxiliary transport services;travel agency 6.67 0.52% 2.06 2.31
64 Post and telecommunication services 28.42 0.99% 1.69 1.90
65 Financial intermediation services 233.44 2.96% 1.48 1.57
66 Insurance and pension funding services 97.39 2.78% 1.73 1.83
71 Renting services of machinery and equipment 78.28 2.17% 1.42 1.52
73 Research and development services 4.02 1.06% 1.16 1.20
74 Other business services 216.24 2.43% 1.27 1.33
75 Public administration and defence services 174.49 2.80% 1.52 1.63
80 Education services 59.96 1.02% 1.32 1.39
85 Health and social work services 5.81 0.06% 1.47 1.60
92 Recreational, cultural and sporting services 870.37 49.28% 1.42 1.51
93 Other services 5.57 0.89% 1.56 1.69
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Ireland
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.44 bn €
0.30 %
Narrow Definition
1.37 bn €
0.96 %
Broad Definition
2.38 bn €
1.66 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
7,161
0.37 %
Narrow Definition
26,995
1.39 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
40,532
2.08 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 190 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 1308.66 5.00% 1.52 1.56
15 Food products and beverages 1.75 0.01% 2.00 2.09
17 Textiles 777.98 6.96% 1.96 2.08
18 Wearing apparel; furs 96.94 0.89% 1.96 2.08
19 Leather and leather products 358.53 4.76% 2.07 2.20
22 Printed matter and recorded media 237.38 2.31% 2.04 2.17
23 Coke, refined petroleum products and nuclear fuels 3.46 0.07% 1.89 1.99
24 Chemicals, chemical products and man-made fibres 17.75 0.11% 1.71 1.89
25 Rubber and plastic products 41.63 0.43% 1.95 2.16
28
Fabricated metal products,exc. machinery and equipment
42.60 0.16% 2.02 2.21
29 Machinery and equipment n.e.c. 52.55 0.15% 1.98 2.15
33 Medical, precision and optical instrum., watches, clocks 66.11 1.12% 1.64 1.76
34 Motor vehicles, trailers and semi-trailers 162.38 2.14% 1.67 1.84
35 Other transport equipment 482.50 11.78% 1.95 2.14
36 Furniture; other manufactured goods n.e.c. 224.25 1.82% 2.07 2.26
45 Construction work 1272.83
1.70%
2.04 2.16
50
Trade, maintenance and repair services of motor vehicles
14.43 0.06% 2.02 2.20
51 Wholesale trade and commission trade services 93.55 0.15% 1.91 2.00
52 Retail trade services 25.74 0.05% 1.91 2.00
55 Hotel and restaurant services 2383.45 5.08% 1.83 1.93
60 Land transport; transport via pipeline services 1550.39 3.59% 1.91 2.02
61 Water transport services 43.96 2.89% 2.28 2.42
62 Air transport services 90.55 5.41% 1.93 2.03
63 Supporting and auxiliary transport services;travel agency 195.69 1.02% 2.04 2.13
64 Post and telecommunication services 2.67 0.01% 1.76 1.83
65 Financial intermediation services 15.34 0.04% 1.57 1.60
66 Insurance and pension funding services 3.96 0.05% 1.91 1.95
71 Renting services of machinery and equipment 10.11 0.08% 1.88 1.99
73 Research and development services 2.07 0.02% 1.75 1.87
74 Other business services 5.77 0.01% 1.73 1.79
75 Public administration and defence services 0.00 0.00% 1.00 1.00
80 Education services 0.00 0.00% 1.00 1.00
85 Health and social work services 195.16 0.26% 1.50 1.57
92 Recreational, cultural and sporting services 5817.37 36.13% 1.83 1.89
93 Other services 1.26 0.01% 1.57 1.63
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Italy
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
2.91 bn €
0.23 %
Narrow Definition
9.75 bn €
0.76 %
Broad Definition
15.60 bn €
1.21 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
75,641
0.34 %
Narrow Definition
239,881
1.07 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
329,860
1.47 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 191 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 0.26 0.07% 2.10 2.33
15 Food products and beverages 0.28 0.04% 1.83 2.07
17 Textiles 0.66 0.47% 1.42 1.64
18 Wearing apparel; furs 2.59 1.86% 1.53 1.77
19 Leather and leather products 0.08 0.80% 1.24 1.40
22 Printed matter and recorded media 3.18 2.29% 1.59 1.89
23 Coke, refined petroleum products and nuclear fuels 0.02 0.37% 1.06 1.08
24 Chemicals, chemical products and man-made fibres 0.21 0.28% 1.15 1.29
25 Rubber and plastic products 0.25 0.93% 1.15 1.33
28
Fabricated metal products,exc. machinery and equipment
0.88 1.02% 1.38 1.62
29 Machinery and equipment n.e.c. 0.03 0.04% 1.16 1.28
33 Medical, precision and optical instrum., watches, clocks 0.06 0.37% 1.11 1.18
34 Motor vehicles, trailers and semi-trailers 0.01 0.31% 1.03 1.06
35 Other transport equipment 6.07 8.47% 1.42 1.68
36 Furniture; other manufactured goods n.e.c. 8.96 12.58% 1.45 1.67
45 Construction work 2.96
0.36%
1.70 2.06
50
Trade, maintenance and repair services of motor vehicles
0.92 0.39% 1.53 1.83
51 Wholesale trade and commission trade services 1.35 0.14% 1.76 1.94
52 Retail trade services 1.07 0.13% 1.65 1.82
55 Hotel and restaurant services 3.26 2.16% 1.69 1.92
60 Land transport; transport via pipeline services 2.34 0.37% 1.53 1.73
61 Water transport services 0.53 1.14% 1.61 1.75
62 Air transport services 0.53 1.43% 1.54 1.68
63 Supporting and auxiliary transport services;travel agency 4.99 0.64% 1.74 1.92
64 Post and telecommunication services 0.06 0.01% 1.41 1.51
65 Financial intermediation services 1.77 0.32% 1.36 1.43
66 Insurance and pension funding services 0.13 0.25% 1.75 1.83
71 Renting services of machinery and equipment 0.32 0.68% 1.37 1.49
73 Research and development services 0.13 0.40% 1.32 1.43
74 Other business services 0.56 0.13% 1.48 1.64
75 Public administration and defence services 0.57 0.07% 1.47 1.60
80 Education services 68.88 10.40% 1.33 1.43
85 Health and social work services 4.68 1.09% 1.41 1.64
92 Recreational, cultural and sporting services 16.82 5.95% 1.47 1.57
93 Other services 0.22 0.28% 1.62 1.86
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Latvia
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.01 bn €
0.07 %
Narrow Definition
0.11 bn €
0.91 %
Broad Definition
0.14 bn €
1.11 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
1,204
0.12 %
Narrow Definition
14,933
1.44 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
17,077
1.65 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 192 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 2.55 0.30% 1.59 1.76
15 Food products and beverages 0.26 0.05% 1.76 2.01
17 Textiles 1.01 0.76% 1.31 1.45
18 Wearing apparel; furs 10.31 4.52% 1.43 1.63
19 Leather and leather products 0.06 0.58% 1.22 1.31
22 Printed matter and recorded media 0.68 0.55% 1.55 1.82
23 Coke, refined petroleum products and nuclear fuels 0.00 0.00% 1.00 1.00
24 Chemicals, chemical products and man-made fibres 1.65 0.21% 1.62 1.68
25 Rubber and plastic products 1.35 0.71% 1.39 1.57
28
Fabricated metal products,exc. machinery and equipment
2.65 1.89% 1.24 1.52
29 Machinery and equipment n.e.c. 0.04 0.04% 1.10 1.18
33 Medical, precision and optical instrum., watches, clocks 0.13 0.35% 1.19 1.29
34 Motor vehicles, trailers and semi-trailers 0.04 0.16% 1.03 1.05
35 Other transport equipment 15.02 11.97% 1.30 1.45
36 Furniture; other manufactured goods n.e.c. 25.54 9.01% 1.51 1.75
45 Construction work 3.93
0.29%
1.64 1.85
50
Trade, maintenance and repair services of motor vehicles
2.04 0.39% 1.35 1.47
51 Wholesale trade and commission trade services 15.04 0.91% 1.45 1.56
52 Retail trade services 2.97 0.18% 1.32 1.40
55 Hotel and restaurant services 4.08 1.52% 1.57 1.70
60 Land transport; transport via pipeline services 7.05 0.56% 1.38 1.53
61 Water transport services 0.56 0.59% 1.29 1.38
62 Air transport services 0.84 2.40% 1.86 2.07
63 Supporting and auxiliary transport services;travel agency 7.93 1.54% 1.43 1.55
64 Post and telecommunication services 0.61 0.13% 1.43 1.58
65 Financial intermediation services 3.14 0.98% 1.48 1.57
66 Insurance and pension funding services 0.00 0.00% 1.00 1.00
71 Renting services of machinery and equipment 0.95 1.11% 1.41 1.50
73 Research and development services 0.27 3.25% 1.62 1.72
74 Other business services 1.43 0.21% 1.53 1.64
75 Public administration and defence services 1.82 0.19% 1.49 1.61
80 Education services 9.46 1.02% 1.31 1.37
85 Health and social work services 14.06 2.50% 1.52 1.65
92 Recreational, cultural and sporting services 22.47 10.61% 1.58 1.72
93 Other services 0.87 0.66% 1.75 1.90
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Lithuania
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.01 bn €
0.06 %
Narrow Definition
0.12 bn €
0.65 %
Broad Definition
0.16 bn €
0.88 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
1,740
0.12 %
Narrow Definition
12,762
0.87 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
16,178
1.10 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 193 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 0.11 0.13% 1.26 1.35
15 Food products and beverages 0.70 0.12% 1.33 1.47
17 Textiles 1.64 1.06% 1.34 1.95
18 Wearing apparel; furs 0.00 0.00% 1.00 1.00
19 Leather and leather products 0.00 0.00% 1.00 1.00
22 Printed matter and recorded media 0.00 0.00% 1.00 1.00
23 Coke, refined petroleum products and nuclear fuels 0.00 0.00% 1.00 1.00
24 Chemicals, chemical products and man-made fibres 0.19 0.27% 1.06 1.22
25 Rubber and plastic products 1.08 0.44% 1.25 1.76
28
Fabricated metal products,exc. machinery and equipment
0.00 0.00% 1.00 1.00
29 Machinery and equipment n.e.c. 0.06 0.03% 1.30 1.47
33 Medical, precision and optical instrum., watches, clocks 0.59 0.55% 1.38 1.65
34 Motor vehicles, trailers and semi-trailers 0.00 0.00% 1.00 1.00
35 Other transport equipment 0.00 0.00% 1.00 1.00
36 Furniture; other manufactured goods n.e.c. 0.72 6.06% 1.01 1.02
45 Construction work 2.60
0.16%
1.53 1.86
50
Trade, maintenance and repair services of motor vehicles
15.81 4.49% 1.41 1.57
51 Wholesale trade and commission trade services 13.47 1.16% 1.51 1.83
52 Retail trade services 43.04 5.92% 1.52 1.81
55 Hotel and restaurant services 98.27 20.35% 1.63 1.81
60 Land transport; transport via pipeline services 1.58 0.23% 1.31 1.56
61 Water transport services 0.31 4.53% 1.21 1.43
62 Air transport services 3.54 1.13% 1.54 2.00
63 Supporting and auxiliary transport services;travel agency 2.19 0.77% 1.19 1.28
64 Post and telecommunication services 0.78 0.08% 1.25 1.40
65 Financial intermediation services 44.57 0.85% 1.99 2.14
66 Insurance and pension funding services 3.00 0.49% 2.07 2.24
71 Renting services of machinery and equipment 3.34 0.90% 1.18 1.30
73 Research and development services 1.16 0.67% 1.29 1.51
74 Other business services 4.02 0.19% 1.20 1.27
75 Public administration and defence services 3.14 0.23% 1.32 1.43
80 Education services 56.43 5.66% 1.12 1.16
85 Health and social work services 214.47 17.26% 1.25 1.42
92 Recreational, cultural and sporting services 176.81 65.13% 1.36 1.58
93 Other services 3.08 3.21% 1.31 1.45
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Luxembourg
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.09 bn €
0.30 %
Narrow Definition
0.39 bn €
1.32 %
Broad Definition
0.70 bn €
2.37 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
1,113
0.32 %
Narrow Definition
12,708
3.70 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
19,331
5.63 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 194 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 0.36 0.42% 1.43 1.56
15 Food products and beverages 0.57 0.65% 1.44 1.56
17 Textiles 0.01 0.09% 1.08 1.15
18 Wearing apparel; furs 0.81 2.17% 1.19 1.34
19 Leather and leather products 0.00 0.00% 1.00 1.00
22 Printed matter and recorded media 1.10 2.18% 1.51 1.87
23 Coke, refined petroleum products and nuclear fuels 0.02 1.08% 1.02 1.03
24 Chemicals, chemical products and man-made fibres 1.14 2.26% 1.15 1.32
25 Rubber and plastic products 0.12 0.30% 1.28 1.52
28
Fabricated metal products,exc. machinery and equipment
0.02 0.10% 1.34 1.61
29 Machinery and equipment n.e.c. 0.26 1.79% 1.09 1.12
33 Medical, precision and optical instrum., watches, clocks 0.00 0.00% 1.32 1.44
34 Motor vehicles, trailers and semi-trailers 0.00 0.00% 1.00 1.00
35 Other transport equipment 0.80 2.85% 1.29 1.45
36 Furniture; other manufactured goods n.e.c. 0.06 0.07% 1.22 1.44
45 Construction work 3.13
1.79%
1.65 1.89
50
Trade, maintenance and repair services of motor vehicles
0.38 0.30% 1.52 1.65
51 Wholesale trade and commission trade services 0.00 0.00% 1.00 1.00
52 Retail trade services 5.67 2.85% 1.49 1.62
55 Hotel and restaurant services 1.42 0.62% 1.71 1.92
60 Land transport; transport via pipeline services 0.41 0.76% 1.40 1.51
61 Water transport services 0.00 0.00% 1.00 1.00
62 Air transport services 0.25 0.36% 1.84 2.26
63 Supporting and auxiliary transport services;travel agency 0.23 0.19% 1.48 1.56
64 Post and telecommunication services 0.76 0.57% 1.59 1.68
65 Financial intermediation services 0.37 0.27% 2.45 2.46
66 Insurance and pension funding services 1.80 3.38% 1.38 1.39
71 Renting services of machinery and equipment 0.10 0.15% 1.68 1.84
73 Research and development services 0.00 0.00% 1.00 1.00
74 Other business services 2.52 0.87% 1.46 1.57
75 Public administration and defence services 0.42 0.14% 1.45 1.53
80 Education services 22.86 8.82% 1.15 1.20
85 Health and social work services 3.88 1.54% 1.24 1.37
92 Recreational, cultural and sporting services 40.50 26.89% 1.78 1.92
93 Other services 2.94 7.53% 1.39 1.48
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Malta
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.02 bn €
0.49 %
Narrow Definition
0.07 bn €
1.75 %
Broad Definition
0.09 bn €
2.24 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
723
0.49 %
Narrow Definition
2,235
1.51 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
3,070
2.07 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 195 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 325.13 3.50% 1.54 1.71
15 Food products and beverages 2.26 0.02% 1.85 1.97
17 Textiles 5.28 0.66% 1.28 1.50
18 Wearing apparel; furs 13.80 8.36% 1.06 1.15
19 Leather and leather products 8.04 6.04% 1.07 1.12
22 Printed matter and recorded media 176.32 3.08% 1.62 1.87
23 Coke, refined petroleum products and nuclear fuels 4.36 0.12% 1.58 1.75
24 Chemicals, chemical products and man-made fibres 10.06 0.10% 1.45 1.74
25 Rubber and plastic products 15.50 0.80% 1.38 1.61
28
Fabricated metal products,exc. machinery and equipment
1.00 0.02% 1.49 1.88
29 Machinery and equipment n.e.c. 0.07 0.00% 1.38 1.67
33 Medical, precision and optical instrum., watches, clocks 8.18 0.46% 1.15 1.26
34 Motor vehicles, trailers and semi-trailers 8.86 0.47% 1.22 1.53
35 Other transport equipment 32.94 2.16% 1.43 1.70
36 Furniture; other manufactured goods n.e.c. 132.53 2.96% 1.28 1.45
45 Construction work 0.00
0.00%
1.00 1.00
50
Trade, maintenance and repair services of motor vehicles
207.07 2.83% 1.62 1.89
51 Wholesale trade and commission trade services 14.70 0.04% 1.52 1.65
52 Retail trade services 241.06 1.49% 1.55 1.64
55 Hotel and restaurant services 458.25 5.41% 1.52 1.64
60 Land transport; transport via pipeline services 305.56 3.06% 1.50 1.65
61 Water transport services 12.68 0.64% 1.79 2.03
62 Air transport services 18.10 0.96% 1.83 2.19
63 Supporting and auxiliary transport services;travel agency 27.88 0.40% 1.65 1.80
64 Post and telecommunication services 0.51 0.00% 1.61 1.74
65 Financial intermediation services 21.26 0.11% 1.43 1.48
66 Insurance and pension funding services 8.15 0.08% 1.60 1.66
71 Renting services of machinery and equipment 5.59 0.13% 1.51 1.64
73 Research and development services 3.65 0.18% 1.31 1.39
74 Other business services 8.24 0.02% 1.55 1.65
75 Public administration and defence services 14.70 0.05% 1.56 1.67
80 Education services 983.69 4.92% 1.28 1.34
85 Health and social work services 160.60 0.40% 1.32 1.41
92 Recreational, cultural and sporting services 2079.69 33.05% 1.84 1.97
93 Other services 512.00 14.46% 1.63 1.76
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Netherlands
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
1.04 bn €
0.23 %
Narrow Definition
4.25 bn €
0.93 %
Broad Definition
5.83 bn €
1.28 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
22,243
0.27 %
Narrow Definition
107,024
1.32 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
141,896
1.75 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 196 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 15.49 0.17% 1.78 1.94
15 Food products and beverages 14.89 0.24% 2.26 2.47
17 Textiles 8.55 1.08% 1.36 1.51
18 Wearing apparel; furs 46.41 4.39% 1.55 1.75
19 Leather and leather products 3.16 1.20% 1.39 1.55
22 Printed matter and recorded media 42.16 2.13% 1.89 2.11
23 Coke, refined petroleum products and nuclear fuels 9.67 1.56% 1.82 1.88
24 Chemicals, chemical products and man-made fibres 25.55 1.09% 1.46 1.64
25 Rubber and plastic products 18.20 0.74% 1.61 1.89
28
Fabricated metal products,exc. machinery and equipment
119.46 3.24% 1.63 1.96
29 Machinery and equipment n.e.c. 10.12 0.30% 1.44 1.67
33 Medical, precision and optical instrum., watches, clocks 1.07 0.14% 1.36 1.50
34 Motor vehicles, trailers and semi-trailers 4.18 0.16% 1.60 2.00
35 Other transport equipment 70.72 8.51% 1.58 1.81
36 Furniture; other manufactured goods n.e.c. 61.92 3.04% 1.85 2.14
45 Construction work 177.45
1.30%
1.97 2.23
50
Trade, maintenance and repair services of motor vehicles
74.97 0.91% 1.48 1.58
51 Wholesale trade and commission trade services 175.79 1.32% 1.81 1.95
52 Retail trade services 122.84 0.70% 1.59 1.69
55 Hotel and restaurant services 51.23 1.81% 1.83 1.97
60 Land transport; transport via pipeline services 86.80 1.14% 1.77 1.94
61 Water transport services 0.00 0.00% 1.00 1.00
62 Air transport services 5.92 2.46% 1.78 1.89
63 Supporting and auxiliary transport services;travel agency 135.62 6.15% 2.13 2.28
64 Post and telecommunication services 0.00 0.00% 1.00 1.00
65 Financial intermediation services 50.16 1.06% 1.57 1.63
66 Insurance and pension funding services 5.47 0.26% 1.59 1.66
71 Renting services of machinery and equipment 15.51 0.90% 1.54 1.65
73 Research and development services 8.18 0.88% 1.53 1.66
74 Other business services 190.38 1.49% 1.74 1.87
75 Public administration and defence services 21.53 0.16% 1.35 1.42
80 Education services 816.93 7.00% 1.27 1.30
85 Health and social work services 5.05 0.06% 1.44 1.54
92 Recreational, cultural and sporting services 953.07 32.74% 1.68 1.82
93 Other services 12.58 0.89% 1.36 1.42
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Poland
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.48 bn €
0.22 %
Narrow Definition
2.53 bn €
1.17 %
Broad Definition
3.36 bn €
1.56 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
44,461
0.32 %
Narrow Definition
221,652
1.57 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
274,423
1.94 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 197 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 62.85 2.57% 1.57 1.71
15 Food products and beverages 0.48 0.02% 1.85 2.12
17 Textiles 12.56 0.86% 1.56 1.82
18 Wearing apparel; furs 15.88 1.28% 1.69 2.00
19 Leather and leather products 80.31 10.70% 1.56 1.90
22 Printed matter and recorded media 20.04 1.64% 1.65 1.89
23 Coke, refined petroleum products and nuclear fuels 0.19 0.29% 1.71 1.80
24 Chemicals, chemical products and man-made fibres 0.50 0.04% 1.39 1.62
25 Rubber and plastic products 7.64 1.10% 1.50 1.85
28
Fabricated metal products,exc. machinery and equipment
11.58 0.82% 1.60 2.01
29 Machinery and equipment n.e.c. 1.66 0.16% 1.32 1.57
33 Medical, precision and optical instrum., watches, clocks 13.73 6.85% 1.22 1.37
34 Motor vehicles, trailers and semi-trailers 0.47 0.07% 1.24 1.66
35 Other transport equipment 76.98 19.95% 1.45 1.71
36 Furniture; other manufactured goods n.e.c. 20.43 2.36% 1.64 1.95
45 Construction work 3.22
0.04%
2.09 2.36
50
Trade, maintenance and repair services of motor vehicles
1.17 0.03% 1.54 1.73
51 Wholesale trade and commission trade services 17.37 0.26% 1.73 1.86
52 Retail trade services 8.59 0.16% 1.66 1.75
55 Hotel and restaurant services 53.06 0.95% 1.74 1.95
60 Land transport; transport via pipeline services 50.86 2.50% 1.74 1.89
61 Water transport services 1.58 1.21% 2.00 2.17
62 Air transport services 2.64 0.64% 1.87 2.06
63 Supporting and auxiliary transport services;travel agency 3.50 0.17% 1.59 1.68
64 Post and telecommunication services 1.50 0.04% 1.71 1.85
65 Financial intermediation services 28.06 0.50% 1.43 1.48
66 Insurance and pension funding services 8.67 0.63% 1.49 1.56
71 Renting services of machinery and equipment 3.45 0.40% 1.55 1.64
73 Research and development services 1.44 0.31% 1.36 1.42
74 Other business services 0.97 0.01% 1.76 1.87
75 Public administration and defence services 27.74 0.27% 1.33 1.39
80 Education services 545.77 5.96% 1.18 1.21
85 Health and social work services 192.23 2.25% 1.50 1.65
92 Recreational, cultural and sporting services 52.91 2.95% 1.65 1.75
93 Other services 203.80 30.49% 1.46 1.58
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Portugal
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.03 bn €
0.02 %
Narrow Definition
1.23 bn €
0.96 %
Broad Definition
1.53 bn €
1.19 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
1,452
0.03 %
Narrow Definition
59,086
1.15 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
72,101
1.41 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 198 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 4.37 0.07% 1.71 1.83
15 Food products and beverages 1.14 0.02% 1.84 1.96
17 Textiles 1.29 0.25% 1.23 1.33
18 Wearing apparel; furs 86.96 9.49% 1.41 1.63
19 Leather and leather products 21.53 5.98% 1.33 1.45
22 Printed matter and recorded media 4.14 0.92% 1.65 1.84
23 Coke, refined petroleum products and nuclear fuels 2.54 0.26% 1.87 1.95
24 Chemicals, chemical products and man-made fibres 1.58 0.23% 1.45 1.57
25 Rubber and plastic products 6.46 1.18% 1.36 1.58
28
Fabricated metal products,exc. machinery and equipment
7.71 0.88% 1.47 1.66
29 Machinery and equipment n.e.c. 0.19 0.02% 1.29 1.42
33 Medical, precision and optical instrum., watches, clocks 1.51 1.11% 1.23 1.35
34 Motor vehicles, trailers and semi-trailers 3.60 0.28% 1.35 1.47
35 Other transport equipment 16.73 4.40% 1.59 1.82
36 Furniture; other manufactured goods n.e.c. 85.75 10.70% 1.56 1.72
45 Construction work 71.57
1.37%
1.76 1.94
50
Trade, maintenance and repair services of motor vehicles
0.33 0.14% 1.89 2.18
51 Wholesale trade and commission trade services 9.63 0.22% 1.42 1.51
52 Retail trade services 18.28 0.58% 1.53 1.61
55 Hotel and restaurant services 19.36 1.38% 1.67 1.76
60 Land transport; transport via pipeline services 30.94 0.71% 1.64 1.79
61 Water transport services 0.58 1.01% 1.49 1.61
62 Air transport services 1.15 0.84% 1.52 1.71
63 Supporting and auxiliary transport services;travel agency 43.53 3.54% 1.66 1.72
64 Post and telecommunication services 0.19 0.01% 1.35 1.40
65 Financial intermediation services 0.06 0.01% 1.15 1.16
66 Insurance and pension funding services 0.53 0.22% 1.59 1.68
71 Renting services of machinery and equipment 0.37 0.02% 1.80 1.92
73 Research and development services 0.69 0.42% 1.83 2.00
74 Other business services 3.55 0.83% 1.55 1.68
75 Public administration and defence services 1.52 0.04% 1.33 1.41
80 Education services 274.86 10.21% 1.38 1.48
85 Health and social work services 67.35 3.17% 1.56 1.82
92 Recreational, cultural and sporting services 0.00 0.00% 1.00 1.00
93 Other services 0.00 0.00% 1.00 1.00
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Romania
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.00 bn €
0.00 %
Narrow Definition
0.64 bn €
0.91 %
Broad Definition
0.79 bn €
1.12 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
0
0.00 %
Narrow Definition
142,935
1.57 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
161,248
1.77 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 199 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 0.83 0.07% 1.66 1.84
15 Food products and beverages 0.72 0.08% 1.74 1.94
17 Textiles 1.44 0.79% 1.22 1.35
18 Wearing apparel; furs 13.36 4.92% 1.32 1.54
19 Leather and leather products 4.07 2.60% 1.44 1.65
22 Printed matter and recorded media 2.51 0.91% 1.70 1.97
23 Coke, refined petroleum products and nuclear fuels 1.01 0.20% 1.64 1.72
24 Chemicals, chemical products and man-made fibres 2.26 0.42% 1.34 1.48
25 Rubber and plastic products 2.74 0.65% 1.44 1.72
28
Fabricated metal products,exc. machinery and equipment
5.35 0.52% 1.42 1.63
29 Machinery and equipment n.e.c. 0.28 0.03% 1.38 1.60
33 Medical, precision and optical instrum., watches, clocks 0.39 0.17% 1.20 1.31
34 Motor vehicles, trailers and semi-trailers 5.03 0.65% 1.45 1.91
35 Other transport equipment 5.59 5.55% 1.56 1.83
36 Furniture; other manufactured goods n.e.c. 24.56 7.26% 1.54 1.88
45 Construction work 15.57
0.46%
2.02 2.28
50
Trade, maintenance and repair services of motor vehicles
2.69 0.57% 1.64 1.91
51 Wholesale trade and commission trade services 11.05 0.41% 1.66 1.80
52 Retail trade services 10.65 0.52% 1.58 1.69
55 Hotel and restaurant services 14.43 2.27% 1.37 1.47
60 Land transport; transport via pipeline services 12.52 0.57% 1.63 1.79
61 Water transport services 0.52 2.82% 1.15 1.19
62 Air transport services -0.03 0.32% 1.61 1.81
63 Supporting and auxiliary transport services;travel agency 17.24 3.70% 2.00 2.21
64 Post and telecommunication services 0.59 0.04% 1.53 1.61
65 Financial intermediation services 1.33 0.09% 1.39 1.45
66 Insurance and pension funding services 1.06 0.23% 1.55 1.63
71 Renting services of machinery and equipment 2.88 0.91% 1.70 1.81
73 Research and development services 0.27 0.30% 1.44 1.56
74 Other business services 2.05 0.09% 1.58 1.71
75 Public administration and defence services 3.31 0.11% 1.46 1.55
80 Education services 71.79 4.73% 1.28 1.33
85 Health and social work services 150.65 11.82% 1.48 1.64
92 Recreational, cultural and sporting services 82.70 13.41% 1.78 1.90
93 Other services 0.76 0.25% 1.31 1.37
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Slowakia
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.04 bn €
0.09 %
Narrow Definition
0.32 bn €
0.73 %
Broad Definition
0.47 bn €
1.08 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
5,643
0.25 %
Narrow Definition
35,444
1.60 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
49,910
2.25 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 200 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 3.94 0.71% 1.53 1.65
15 Food products and beverages 0.52 0.11% 1.74 1.95
17 Textiles 1.35 0.86% 1.50 1.81
18 Wearing apparel; furs 8.61 8.41% 1.47 1.77
19 Leather and leather products 1.27 2.62% 1.34 1.50
22 Printed matter and recorded media 7.86 3.71% 1.81 2.05
23 Coke, refined petroleum products and nuclear fuels -0.01 0.64% 1.03 1.04
24 Chemicals, chemical products and man-made fibres 5.64 0.77% 1.32 1.50
25 Rubber and plastic products 5.37 1.75% 1.49 1.82
28
Fabricated metal products,exc. machinery and equipment
5.58 0.92% 1.49 1.88
29 Machinery and equipment n.e.c. 0.44 0.06% 1.41 1.74
33 Medical, precision and optical instrum., watches, clocks 0.80 0.64% 1.24 1.45
34 Motor vehicles, trailers and semi-trailers 0.12 0.05% 1.28 1.76
35 Other transport equipment 15.80 28.25% 1.44 1.69
36 Furniture; other manufactured goods n.e.c. 57.61 16.18% 1.44 1.69
45 Construction work 7.63
0.49%
2.02 2.39
50
Trade, maintenance and repair services of motor vehicles
36.28 7.01% 1.63 1.87
51 Wholesale trade and commission trade services 35.42 2.60% 1.71 1.87
52 Retail trade services 6.33 0.48% 1.50 1.59
55 Hotel and restaurant services 7.46 1.20% 1.60 1.75
60 Land transport; transport via pipeline services 7.84 1.06% 1.60 1.85
61 Water transport services 0.41 0.69% 1.43 1.71
62 Air transport services 0.26 0.68% 1.60 1.82
63 Supporting and auxiliary transport services;travel agency 9.39 3.46% 1.83 2.03
64 Post and telecommunication services 0.52 0.08% 1.69 1.75
65 Financial intermediation services 7.99 1.07% 1.42 1.47
66 Insurance and pension funding services 1.27 0.56% 1.79 1.87
71 Renting services of machinery and equipment 2.34 3.11% 1.51 1.61
73 Research and development services 0.63 0.39% 1.38 1.50
74 Other business services 2.28 0.13% 1.55 1.66
75 Public administration and defence services 3.19 0.22% 1.44 1.54
80 Education services 96.04 7.03% 1.24 1.30
85 Health and social work services 65.53 5.29% 1.36 1.51
92 Recreational, cultural and sporting services 114.21 21.95% 1.56 1.63
93 Other services 0.69 0.38% 1.39 1.47
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Slovenia
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.06 bn €
0.23 %
Narrow Definition
0.41 bn €
1.66 %
Broad Definition
0.52 bn €
2.10 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
3,600
0.38 %
Narrow Definition
23,011
2.43 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
28,576
3.01 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 201 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 31.94 0.15% 1.63 1.76
15 Food products and beverages 1.64 0.01% 2.21 2.42
17 Textiles 16.40 0.65% 1.69 1.91
18 Wearing apparel; furs 28.64 1.26% 1.50 1.67
19 Leather and leather products 448.41 30.46% 1.68 1.94
22 Printed matter and recorded media 198.41 2.73% 1.85 2.05
23 Coke, refined petroleum products and nuclear fuels 17.69 0.46% 1.76 1.83
24 Chemicals, chemical products and man-made fibres 10.60 0.10% 1.58 1.78
25 Rubber and plastic products 12.28 0.25% 1.74 2.01
28
Fabricated metal products,exc. machinery and equipment
114.44 0.90% 1.88 2.14
29 Machinery and equipment n.e.c. 16.42 0.18% 1.52 1.70
33 Medical, precision and optical instrum., watches, clocks 142.55 11.63% 1.29 1.43
34 Motor vehicles, trailers and semi-trailers 36.50 0.38% 1.55 1.95
35 Other transport equipment 409.73 14.44% 1.57 1.81
36 Furniture; other manufactured goods n.e.c. 243.46 4.46% 1.73 1.94
45 Construction work 1114.30
1.22%
2.31 2.48
50
Trade, maintenance and repair services of motor vehicles
2.02 0.02% 1.79 2.10
51 Wholesale trade and commission trade services 25.76 0.06% 1.68 1.75
52 Retail trade services 90.48 0.24% 1.56 1.60
55 Hotel and restaurant services 415.47 0.70% 1.69 1.80
60 Land transport; transport via pipeline services 477.56 2.51% 1.80 1.93
61 Water transport services 17.96 1.96% 2.08 2.24
62 Air transport services 2.06 0.08% 1.74 1.87
63 Supporting and auxiliary transport services;travel agency 18.06 0.13% 2.00 2.14
64 Post and telecommunication services 9.34 0.05% 1.79 1.92
65 Financial intermediation services 276.50 1.10% 1.31 1.34
66 Insurance and pension funding services 40.25 0.78% 1.86 1.93
71 Renting services of machinery and equipment 20.41 0.39% 1.67 1.77
73 Research and development services 6.89 0.22% 1.52 1.63
74 Other business services 0.00 0.00% 1.00 1.00
75 Public administration and defence services 91.43 0.21% 1.43 1.50
80 Education services 2767.07 7.12% 1.21 1.23
85 Health and social work services 2821.94 6.33% 1.45 1.57
92 Recreational, cultural and sporting services 280.69 1.32% 1.63 1.71
93 Other services 199.82 4.33% 1.62 1.73
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Spain
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.14 bn €
0.02 %
Narrow Definition
7.33 bn €
0.90 %
Broad Definition
10.41 bn €
1.28 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
5,774
0.03 %
Narrow Definition
252,183
1.33 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
336,177
1.77 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 202 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 1.28 0.10% 1.65 1.80
15 Food products and beverages 7.02 0.19% 1.73 1.97
17 Textiles 5.70 1.70% 1.27 1.40
18 Wearing apparel; furs 16.80 18.21% 1.09 1.14
19 Leather and leather products 6.60 10.90% 1.13 1.20
22 Printed matter and recorded media 8.03 0.31% 1.95 2.13
23 Coke, refined petroleum products and nuclear fuels 3.33 0.78% 1.42 1.63
24 Chemicals, chemical products and man-made fibres 9.98 0.19% 1.40 1.56
25 Rubber and plastic products 1.75 0.13% 1.42 1.64
28
Fabricated metal products,exc. machinery and equipment
1.63 0.04% 1.63 1.87
29 Machinery and equipment n.e.c. 0.32 0.01% 1.60 1.83
33 Medical, precision and optical instrum., watches, clocks 5.13 0.26% 1.46 1.61
34 Motor vehicles, trailers and semi-trailers 1.17 0.03% 1.71 2.03
35 Other transport equipment 44.61 3.31% 1.52 1.70
36 Furniture; other manufactured goods n.e.c. 166.60 15.93% 1.51 1.75
45 Construction work 10.34
0.09%
1.69 1.89
50
Trade, maintenance and repair services of motor vehicles
81.16 0.28% 1.61 1.73
51 Wholesale trade and commission trade services 0.00 0.00% 1.00 1.00
52 Retail trade services 0.00 0.00% 1.00 1.00
55 Hotel and restaurant services 709.48 17.36% 1.77 1.95
60 Land transport; transport via pipeline services 5.47 0.08% 1.62 1.74
61 Water transport services 2.84 0.29% 1.73 1.97
62 Air transport services 4.84 0.92% 1.72 1.87
63 Supporting and auxiliary transport services;travel agency 11.79 0.20% 1.95 2.16
64 Post and telecommunication services 2.05 0.04% 1.85 1.96
65 Financial intermediation services 19.20 0.25% 1.39 1.43
66 Insurance and pension funding services 24.43 0.91% 1.37 1.40
71 Renting services of machinery and equipment 13.65 0.50% 1.58 1.69
73 Research and development services 3.07 0.01% 1.60 1.69
74 Other business services 0.00 0.00% 1.00 1.00
75 Public administration and defence services 13.44 0.13% 1.60 1.69
80 Education services 580.41 4.05% 1.44 1.49
85 Health and social work services 116.46 0.42% 1.34 1.41
92 Recreational, cultural and sporting services 458.11 11.13% 1.79 1.88
93 Other services 23.20 1.66% 1.49 1.58
GROSS VALUE ADDED
Sector-specific Multiplier
National Data Sheet
Sweden
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)
Direct Effects
% of total
Statistical Definition
0.23 bn €
0.09 %
Narrow Definition
1.39 bn €
0.54 %
Broad Definition
2.36 bn €
0.92 %
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
8,358
0.19 %
Narrow Definition
48,717
1.12 %
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
Broad Definition
73,266
1.69 %
DETAILED INFORMATION on SECTORAL LEVEL
Study on the Contribution of Sport to Economic Growth and Employment - 203 -
Sport-related
% of total domestic EU-wide
1 Products of agriculture, hunting and related services 406.50 4.41% 1.64 1.78
15 Food products and beverages 147.70 0.51% 1.72 1.89
17 Textiles 166.70 4.59% 1.40 1.51
18 Wearing apparel; furs 152.10 8.65% 1.19 1.25
19 Leather and leather products 13.20 2.38% 1.12 1.17
22 Printed matter and recorded media 514.70 2.98% 1.71 1.88
23 Coke, refined petroleum products and nuclear fuels 48.30 1.42% 1.68 1.74
24 Chemicals, chemical products and man-made fibres 74.60 0.35% 1.53 1.70
25 Rubber and plastic products 30.80 0.29% 1.63 1.83
28
Fabricated metal products,exc. machinery and equipment
7.50 0.04% 1.61 1.78
29 Machinery and equipment n.e.c. 35.10 0.20% 1.51 1.66
33 Medical, precision and optical instrum., watches, clocks 47.20 0.64% 1.37 1.48
34 Motor vehicles, trailers and semi-trailers 58.50 0.48% 1.50 1.70
35 Other transport equipment 831.70 8.65% 1.51 1.66
36 Furniture; other manufactured goods n.e.c. 459.10 5.42% 1.47 1.63
45 Construction work 235.00
0.23%
2.06 2.19
50
Trade, maintenance and repair services of motor vehicles
90.70 0.25% 1.68 1.82
51 Wholesale trade and commission trade services 543.90 0.77% 1.87 1.99
52 Retail trade services 1087.90 1.31% 1.62 1.69
55 Hotel and restaurant services 769.10 1.34% 1.64 1.76
60 Land transport; transport via pipeline services 152.10 0.47% 1.80 1.91
61 Water transport services 34.50 0.62% 1.66 1.77
62 Air transport services 71.90 0.83% 1.56 1.64
63 Supporting and auxiliary transport services;travel agency 1014.80 3.91% 2.06 2.16
64 Post and telecommunication services 3285.60 7.95% 1.59 1.71
65 Financial intermediation services 734.00 1.01% 1.48 1.54
66 Insurance and pension funding services 45.30 0.26% 2.11 2.22
71 Renting services of machinery and equipment 146.10 0.70% 1.63 1.74
73 Research and development services 43.00 0.58% 1.53 1.62
74 Other business services 1406.20 0.83% 1.59 1.66
75 Public administration and defence services 47.20 0.05% 1.66 1.77
80 Education services 1754.70 1.82% 1.40 1.45
85 Health and social work services 103.80 0.09% 1.63 1.74
92 Recreational, cultural and sporting services 23312.10 58.74% 1.62 1.71
93 Other services 121.90 1.32% 1.72 1.82
Sector-specific Multiplier
Narrow Definition
417,072
1.46 %
Broad Definition
618,770
2.16 %
DETAILED INFORMATION on SECTORAL LEVEL
CPA
Description
GROSS VALUE ADDED
(Market Prices, Mio. €)
EMPLOYMENT
Direct Effects
% of total
Statistical Definition
175,325
0.61 %
Narrow Definition
24.84 bn €
1.52 %
Broad Definition
37.99 bn €
2.33 %
Direct Effects
% of total
Statistical Definition
11.66 bn €
0.71 %
GROSS VALUE ADDED
National Data Sheet
United Kingdom
ECONOMIC IMPACT OF SPORT (according to the Vilnius Definition)