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EU industrial
structure
2011
Trends and Performance
European Commission
Enterprise and Industry
ISSN 1831-3043

EU industrial
structure
2011
Trends
and Performance
European Commission
Enterprise and Industry

ENTERPRISE & INDUSTRY MAGAZINE
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Luxembourg: Publications Office of the European Union, 2011.
ISBN 978-92-79-20733-4
ISSN 1831-3043
doi:10.2769/28487
© European Union, 2011
Reproduction is authorised provided the source is acknowledged.
Printed in Luxembourg

Table of Contents
ExEcutivE summary 8
OvErviEw 12
Chapter I
thE aFtErmath OF thE crisis — a lOng and unEvEn rEcOvEry(?) 15
I.1 Recession and recovery(?) ....................................................................................................................................................................15
I.1.1 Manufacturing recession and recovery(?)..........................................................................................................................16
I.1.2 Services recession and recovery(?) ...................................................................................................................................... 23
I.2 Sector developments: the current recovery(?) ..............................................................................................................................24
I.2.1 Recent developments in manufacturing industries ....................................................................................................... 24
I.2.2 Recent developments in services industries ..................................................................................................................... 30
I.3 Annex Figures ............................................................................................................................................................................................32
Chapter II
changEs in Eu industrial structurE 35
II.1 The shares of industries and sectoral specialisation in the EU ................................................................................................35
II.1.1 Structural change in the EU .................................................................................................................................................. 35
II.1.2 Member states’ sectoral specialisation .............................................................................................................................. 39
II.2 Skill and technology specialization .................................................................................................................................................. 45
II.2.1 Changes in skills’ specialization .......................................................................................................................................... 45
II.2.2 Changes in technology specialization ............................................................................................................................... 48
II.3 Size distribution of enterprises .......................................................................................................................................................... 50
II.4 Services output of manufacturing .....................................................................................................................................................51
II.5 Inter‑sectoral spillovers — a case study ...........................................................................................................................................52
Appendix figure ...................................................................................................................................................................................................55
Chapter III
drivErs OF sEctOr grOwth and cOmpEtitivEnEss 57
III.1 Output growth across sectors .............................................................................................................................................................57
III.2 Sectoral competitiveness indicators ................................................................................................................................................ 60
III.2.1 Labour productivity ............................................................................................................................................................... 63
III.2.2 Unit labour costs ..................................................................................................................................................................... 67
III.3 Factors of production ............................................................................................................................................................................ 69
III.3.1 Labour ....................................................................................................................................................................................... 69
III.3.2 Human capital ........................................................................................................................................................................ 71
III.3.3 Gross fixed capital formation ...............................................................................................................................................74
III.3.4 Energy intensity ....................................................................................................................................................................... 77
III.3.5 Technology ............................................................................................................................................................................... 78
III.3.5.1 R&D .......................................................................................................................................................................... 80
III.3.5.2 Patents ......................................................................................................................................................................81
III.3.5.3 Innovation .............................................................................................................................................................. 84
III.4 Demand‑side drivers: a sectoral picture ........................................................................................................................................ 86
III.4.1 Private Consumption ............................................................................................................................................................. 86
III.4.2 Investment demand ................................................................................................................................................................91
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EU industrial structure 2011 — Trends and Performance
Chapter IV
intErnatiOnal cOmpEtitivEnEss OF Eu industry 95
IV.1 EU importance in world trade .............................................................................................................................................................95
IV.1.1 Goods .........................................................................................................................................................................................95
IV.1.2 Services ..................................................................................................................................................................................... 98
IV.2 EU manufacturing and services competitiveness by sector.................................................................................................. 100
IV.2.1 EU trade in manufactures by destination ...................................................................................................................... 100
IV.2.2 Export Market Shares ...........................................................................................................................................................103
IV.2.3 Sectoral trade balance ........................................................................................................................................................ 105
IV.2.4 Revealed comparative advantage ................................................................................................................................... 106
IV.2.4.1 RCA in manufactures ......................................................................................................................................... 106
IV.2.4.2 RCA in Services .................................................................................................................................................... 106
IV.3 Intra‑industry trade ...............................................................................................................................................................................119
IV.4 The role of technology in EU sectoral trade .................................................................................................................................123
IV.5 Trade in intermediate goods ..............................................................................................................................................................124
IV.6 International movement of factors of production .....................................................................................................................129
IV.6.1 FDI .............................................................................................................................................................................................129
IV.6.2 Internationalisation of R&D ................................................................................................................................................133
Annexes
annExEs 137
A.1 Statistical nomenclature ......................................................................................................................................................................137
A.2 List of abbreviations .............................................................................................................................................................................145
rEFErEncEs 146
4

List of Figures
Figure I.1: Growth rates (T/T‑12) in manufacturing in the EU, Japan and the US from 1990
Table of Contents
to June 2011 (monthly data). .....................................................................................................................................................................16
Figure I.2: Downturns and recoveries in EU‑27 industrial production since 1990 ......................................................................................17
Figure I.3: EU Manufacturing growth rates (T/T‑12) from 1991 to 2010 (monthly data) ...........................................................................18
Figure I.4: EU‑27 recessions and recoveries in the last two decades. Percentage deviations
from peak and months of recovery for EU‑27 manufacturing production .............................................................................19
Figure I.5: Capital, Durable and Intermediate goods were most heavily hit during the latest recession ..........................................19
Figure I.6: Decline in output from Peak to Trough (%) and number of months of falling output for EU‑27
industries during the latest crisis11 .........................................................................................................................................................20
Figure I.7: Percentage of manufacturing industries with very low growth rates in 1991‑ 2011 ............................................................21
Figure I.8: Growth in EU services industries 1996‑2011 (%) .................................................................................................................................23
Figure I.9: Growth rates in EU services industries compared to the whole EU economy 1996‑2010 (%) ..........................................24
Figure I.10: EU manufacturing diffusion index from January 1991 to June 2011 (monthly data) ...........................................................25
Figure I.11: Increase in output from the trough to June 2011 (%) and number of months of increasing
output for EU‑27 industries since the latest crisis ..............................................................................................................................26
Figure I.12: EU‑27 manufacturing growth rates of production and new orders (T/T‑12) for manufacturing goods
from January 2001 to June 2011 ..............................................................................................................................................................28
Figure I.13: EU‑27 manufacturing order‑books levels, stocks of finished products and production expectations
from January 1985 to February 2011 (monthly data) ........................................................................................................................28
Figure I.14: Increasing probabilities of contraction in the end of 2011 .............................................................................................................29
Figure I.15: Production and demand expectations: EU services and manufacturing industries
between 1996 and 2011 (monthly data) ................................................................................................................................................31
Figure I.16: Decline by country in manufacturing output from peak to trough (%) and number of months
of falling output in EU‑27 during the latest crisis ...............................................................................................................................32
Figure I.17: Recovery by country in manufacturing output from the trough to March 2011 (%)
and number of months of increasing output in EU‑27 since the latest crisis ..........................................................................32
Figure II.1: EU Structural change 1997 ‑2009 (% of GDP) .......................................................................................................................................36
Figure II.2: Distribution of EU countries by GDP shares of manufacturing and market services in 2009 ...........................................36
Figure II.3: EU industry shares in GDP in 1997 and 2007 % ..................................................................................................................................38
Figure II.4: Change in the share of sectors in the EU in 1997‑2009 (percentage points) ...........................................................................39
Figure II.5: Ranking of countries by degree of specialisation ..............................................................................................................................41
Figure II.6: Large economies are less dependent on a few sectors ...................................................................................................................42
Figure II.7: Distribution of value added by enterprise size in 2007 (%) ............................................................................................................51
Figure II.8: Services as shares of manufacturing output in 1995 and 2005 (%) .............................................................................................52
Figure II.9: A technology shock in the motor vehicle industry has permanent effects on employment
and productivity in rubber and plastics ...............................................................................................................................................53
Figure II.10: A non‑technology shock has permanent effects on employment only ..................................................................................54
Figure II.11: Sector share in EU‑27 GDP in 2009 (%) ...................................................................................................................................................55
Figure III.1: Value added — average annual growth rate in the EU in 1995 – 2009 (%) ..............................................................................58
Figure III.2: EU average annual production growth rate in 1995‑2010 (%).......................................................................................................59
Figure III.3: EU average annual production growth rate in 1995‑2010 (%).......................................................................................................60
Figure III.4: EU value added in 1995‑2010 (1995 = 100) ...........................................................................................................................................61
Figure III.5: EU labour productivity per person employed in 1995‑2009 (1995 = 100) ................................................................................61
Figure III.6: EU ULC (index, 1995 = 100) .........................................................................................................................................................................62
Figure III.7: EU relative prices (Industry = 100) ...........................................................................................................................................................62
Figure III.8: Labour productivity growth vs changes in relative prices in 1995‑2009 ..................................................................................63
Figure III.9: Annual growth in EU labour productivity per person employed 1995‑2009 (%) ..................................................................64
Figure III.10: Average annual growth in labour productivity 2000‑2010 (%). Production per hours worked .......................................66
Figure III.11: Average annual growth in labour productivity 1997‑2010 (%). Production per employed ...............................................67
Figure III.12: Recent ULC fluctuations are driven mainly by productivity developments ............................................................................68
5

EU industrial structure 2011 — Trends and Performance
Figure III.13: Average annual growth in unit labour costs in EU manufacturing by industry 2001‑10 (%) .............................................69
Figure III.14: Average annual growth of persons employed in the EU 1995‑2009 (%) ...................................................................................70
Figure III.15: Employment by educational attainment in the EU‑27 in 2009 .....................................................................................................73
Figure III.16: EU GFCF growth rates based on selected countries in 1995‑2009 ..............................................................................................75
Figure III.17: Annual growth rates of GFCF in manufacture of transport equipment in France, Germany, Italy
6
and Spain 1995‑2009 ....................................................................................................................................................................................76
Figure III.18: EU and US R&D expenditure as shares of value added in sectors in 2006 (%) ........................................................................80
Figure III.19: EU R&D expenditure as shares of value added in sectors in 1997 and 2006 (%) ....................................................................81
Figure III.20: EU‑27 sectors by patent intensity (averages in 2005‑06 and 2006‑07) ....................................................................................83
Figure III.21: EU sectors by patent performance relative to the rest of the world in 2004‑06 ....................................................................84
Figure III.22: Innovative enterprises as a percentage of all enterprises in the EU‑27 in 2008 (%) ..............................................................85
Figure III.23: Enterprises which introduced new or improved products to the market as a share
of all enterprises engaged in innovation activity in the EU‑27 in 2008 (%) ..............................................................................86
Figure III.24: Shares of goods and services in private consumption in constant and current prices
in seven EU countries from 1980 to 2009 ..............................................................................................................................................87
Figure III.25: Private consumption shares (current prices) in seven EU countries in 1980 and 2008 ........................................................88
Figure III.26: EU‑27 sectoral shares of private consumption in 2008 % of total consumption ...................................................................89
Figure III.27: Private consumption in EU‑15 and in EU‑27 in 1996 and 2008 (average annual percentage growth
rates in constant prices) ...............................................................................................................................................................................90
Figure III.28: EU‑27 investment breakdown in 2010 (% of total current price) .................................................................................................91
Figure III.29: Investment average annual growth rate in the EU‑27 and EU‑15: 1997‑2010 (%) ...................................................................92
Figure IV.1: EU accounts for almost half of world exports of services (%) ........................................................................................................99
Figure IV.2: EU accounts for most of world imports of services (%) ...................................................................................................................99
Figure IV.3: EU‑27 RCA index in 2009 ...........................................................................................................................................................................107
Figure IV.4: EU‑27 trade in manufactured products — RCA index in 2009 .................................................................................................. 109
Figure IV.5: US trade in manufactured products — RCA index in 2009 ......................................................................................................... 109
Figure IV.6: Japan trade in manufactured products — RCA index in 2009 ...................................................................................................110
Figure IV.7: Brazil trade in manufactured products — RCA index in 2009 ....................................................................................................110
Figure IV.8: China trade in manufactured products — RCA index in 2009 ................................................................................................... 111
Figure IV.9: India trade in manufactured products — RCA index in 2009 ..................................................................................................... 111
Figure IV.10: Russia trade in manufactured products — RCA index in 2009...................................................................................................112
Figure IV.11: EU‑27 trade in services — RCA index in 2009 ....................................................................................................................................116
Figure IV.12: US trade in services — RCA index in 2009 ..........................................................................................................................................116
Figure IV.13: Japan trade in services — RCA index in 2009 ...................................................................................................................................117
Figure IV.14: Brazil trade in services — RCA index in 2009 ....................................................................................................................................117
Figure IV.15: China trade in services — RCA index in 2009 ....................................................................................................................................118
Figure IV.16: India trade in services — RCA index in 2009 .....................................................................................................................................118
Figure IV.17: Russia trade in services — RCA index in 2009 ...................................................................................................................................119
Figure IV.18: Grubel‑Lloyd index by income level of EU‑27 trade partner in 2009 .......................................................................................122
Figure IV.19: Vertical specialisation of exports by country in 1995 and 2005 (%) ..........................................................................................125
Figure IV.20: Import content of exports for 15 EU countries in 1995 and 2005 (%) .......................................................................................126
Figure IV.21: Outward EU foreign direct investment stock in 2007 ....................................................................................................................129
Figure IV.22: Inward EU Foreign direct investment stock in 2007 .......................................................................................................................130
Figure IV.23: Share of the inward EU FDI stock owned by EU firms in 2007 .....................................................................................................130
Figure IV.24: EU‑27 outward FDI stock to the rest of the world/EU‑27 inward FDI stock from the rest
of the world in 2007 (ratio) ......................................................................................................................................................................131
Figure IV.25: Sectoral share in FDI stock relative to share in value added EU‑27 in 2007 ..........................................................................132
Figure IV.26: Share of foreign‑owned patents in EU‑27 patent applications 1990‑2007 (%) .....................................................................133
Figure IV.27: Share of foreign‑owned patents in EU manufacturing industries 2003‑07 (%) ....................................................................134
Figure IV.28: Share of overseas patents of total patents applications 1991‑95 and 2003‑07 (%) .............................................................134
Figure IV.29: Location of overseas patents applied by the EU‑27 at EPO 1990‑2006 (%) ............................................................................135

List of Tables
Table of Contents
Table I.1: Descriptive statistics of the growth rates of EU, US and Japanese manufacturing industry production .....................16
Table I.2: Growth and volatility in EU‑27 manufacturing industries 1990‑2011(%)...................................................................................22
Table I.3: Recent developments in EU manufacturing, mining, electricity and construction .............................................................26
Table I.4: EU services production, recent developments. Growth in services turnover in constant
prices relative to the same month of the previous year ..................................................................................................................30
Table II.1: Share in GDP in 2009 and change in shares of GDP between 1997 and 2009 ........................................................................37
Table II.2: Sectoral specialisation indices 1997 and 2009 ....................................................................................................................................43
Table II.3: Share of industry by labour skill in 1997 and 2007 (%) .....................................................................................................................46
Table II.4: Country specialisation by labour skill in 1997 and 2007..................................................................................................................47
Table II.5: Share of industry by technology categories in 1997 and 2007 (%) .............................................................................................49
Table II.6: Country specialisation by technology categories in 1997 and 2007 ..........................................................................................49
Table II.7: Percentage responses of employment and productivity in four manufacturing industries
to shocks in the motor vehicles industry ..............................................................................................................................................54
Table III.1: EU labour productivity growth 2000‑2009 (%). Production per hours worked .....................................................................65
Table III.2: EU ULC annual growth in mining and manufacturing industries in 2000‑2010(%)...............................................................68
Table III.3: EU manufacturing employment and hours worked — average annual growth
from 2000 to 2010 .........................................................................................................................................................................................71
Table III.4: EU‑22 investment ratios in 2005‑2009 ...................................................................................................................................................74
Table III.5: EU investment intensity. Average 2005‑07 ...........................................................................................................................................76
Table III.6: EU energy intensity. Average 2005‑07 ...................................................................................................................................................77
Table III.7: Growth in investment levels, average annual growth rates: 1997‑2009 (%) ............................................................................92
Table IV.1: Manufactured products — export world trade matrix in 2009. Shares of total world exports (%) ................................96
Table IV.2: Manufactured products — world trade matrix, export destination in 2009 (%) ...................................................................97
Table IV.3: Manufactured products — world import structures by origin of imports in 2009 (%) .......................................................98
Table IV.4: EU exports of manufactured goods in 2009 by destination (%) ................................................................................................101
Table IV.5: EU imports of manufactured goods by origin (2009 in%) ............................................................................................................102
Table IV.6: Share of EU and main trade partners in world markets by sectors in 2009 .......................................................................... 104
Table IV.7: EU RTB indicators in manufacturing sectors from 2007 to 2009 ............................................................................................... 105
Table IV.8: RCA in manufacturing in 2009: EU countries, US, Japan and Brazil, China and Russia ..................................................... 108
Table IV.9: RCA in services activities in 2009: EU countries, US, Japan and Brazil, China and Russia .................................................115
Table IV.10: Manufactured products ‑ World trade matrix, income level: exports in 2009 (%) ..............................................................120
Table IV.11: Manufactured products ‑ World trade matrix income level: destination of exports in 2009 (%) ..................................120
Table IV.12: Manufactured products ‑ World trade matrix — income level: import destination in 2009 (%) ...................................121
Table IV.13: RCA by technology category in 2009: EU countries, US, Japan and Brazil, China, India and Russia .............................123
Table IV.14: Indicators of RCA for manufactured goods in 2000 and 2009 ....................................................................................................127
Table IV.15: Indicators of RCA for intermediate goods according to technological intensity in 2009.................................................128
Table IV.16: Export and import unit values of intermediates according to technological intensity in 2009 ....................................128
Table A.1.1: Sectoral nomenclature for economic activities — NACE rev 1.1 ................................................................................................137
Table A.1.2: Sectoral nomenclature for economic activities — NACE rev 2 ...................................................................................................139
Table A.1.3: Sectoral nomenclature for consumption activities (COICOP) .....................................................................................................141
Table A.1.4: Sectoral nomenclature for trade in services activities. ..................................................................................................................142
Table A.1.5: Classification of products by activities (CPA) .....................................................................................................................................143
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EU industrial structure 2011 — Trends and Performance
Executive summary
The impact of the latest crisis on EU sectors was much
stronger than previous ones since 1990.
The sectoral impact of the latest financial crisis is more
significant because of the larger size and scope of the
downturn. The latest recession lasted 17 months before
industrial production began to pick up. In comparison,
the 1992‑93 recession lasted 19 months before
production recovered from the trough; the millennium
recession 13 months. Nonetheless, growth rates fell much
more drastically in the recent crisis than in the 1992‑93 and
millennium downturns.
It is still too early to determine how long it will take to
reach pre‑crisis production levels. But it is clear that the
latest recession was much deeper than the previous ones.
Manufacturing production in the EU‑27 took some two and
a half years to regain its pre‑recession production level after
the 1992‑93 crisis. The millennium recession was milder
but the recovery process lasted longer, about four and
a half years. Judging from the latest available data, it may
take more than four years before the pre‑recession peak is
regained.
Looking more closely at the sectoral impact of the crisis,
the total number of affected industries is unprecedented
in comparison with previous downturns since 1990.
The impact has been uneven across sectors. Capital
goods, durable goods and intermediate goods were
hit harder than non‑durable consumer goods. The fall
in production for total industry was significantly larger
than for services. Services sectors have been generally
less sensitive to the crisis, displaying higher growth rates
and lower volatility.
In early 2011, production levels for non‑durable consumer
goods’ industries were close to the pre‑recession peak
while durables and intermediates still were well below
the pre‑recession levels. At a more disaggregated level,
the industries producing motor vehicles, basic metals and
8
machinery n.e.c. experienced larger declines in production
than other manufacturing industries.
The trough of the crisis can be identified as early 2009 in
most industries in the EU, the US and Japan. The first signs
of recovery seemed to have appeared in the beginning
of 2011. Early 2011 business survey data (order book levels,
stocks of finished products), indicated increasing growth
across manufacturing. Nonetheless, growth in some EU
sectors still seemed more fragile in early 2011, namely
furniture, mining and quarrying and tobacco.
The latest developments during the summer of 2011 have
increased the uncertainty of how sustainable the recovery
process is. Increasing uncertainty about the sustainability
of public finances which deteriorated during the recession
may give rise to wealth effects and reduce consumption and
investments. Measures to tackle public debt problems in
the US and several Member States risk affecting directly and
negatively consumption and investment as well. The latest
available data (June and July 2011) on short‑term statistics
shows a decrease in EU‑27 industrial production. Business
surveys on production expectations, orders and inventories
point in the same direction. It is still too early to judge
whether the latest developments indicate a slowdown or if
the economic activity will pick up again.
The developing services economy
Services sectors occupy increasingly larger shares in the
EU Member states. Market services have grown to 50 % of
the EU economy in 2009, from 46 % in 1997; non‑market
services have risen to 24 % from 22 %. Over the same time
period, the share of EU manufacturing dropped from 20 %
to 15 %. A shrinking EU agricultural sector went down to as
little as 2 % of the EU value added in 2009 from 3 % in 1997.
With the exception of Malta, all EU countries have seen the
share of market services activities increase since 1997. But
these EU‑wide developments hide large differences among

countries. Luxembourg stands out with a very large services
sector along with Cyprus, Latvia and the UK. Conversely,
Czech Republic, Hungary, Ireland and Romania still have
relatively large manufacturing sectors. In Romania, Slovakia
and Spain, the share of the construction sector exceeds by
far the EU average of 6 %.
Changes do not only take place between industries.
Technological development, increased globalisation and
more competition force firms and industries to adapt
their business models. Some of these changes within
industries increasingly blur the distinction between
manufacturing and services activities. An increasing
number of manufacturing firms offer services along with
their traditional physical goods. This ‘convergence process’
between manufacturing and services takes place on
a global scale. Services as shares of total manufacturing
output have increased in almost all EU economies.
Larger countries tend to have more potential for
diversification as their larger markets can harbour more
industries than small ones. The most diversified are,
naturally, France, Germany, Italy, Spain, and the UK. But
smaller countries like Austria, Belgium, the Netherlands, and
Sweden also exhibit diversified industrial structures. Natural
resources, relative factor endowments of labour, human
capital, and physical capital largely explain specialisation
patterns. Baltic countries, for instance, are very highly
specialised in wood. Cyprus, Ireland, Luxembourg and the
UK and have focused most on financial intermediation.
The industrial structure of an economy, i.e. the shares of the
various sectors, is the result of long term changes. Changes
tend to be slow. A country dominated by low technology
and low skills will not, overnight, move to purely high
technology and high skill industries. Nonetheless, it is
found that the transition is quite remarkable in certain
cases. Finland, for instance, became the country with the
highest EU specialisation in high technology industries
in only a decade (1997‑2007); this is to a high extent
explained by the increasing predominance of Nokia. Latvia,
from 1997 to 2007 made a remarkable shift, compared to
other EU countries, towards a higher specialisation in higher
skilled industries.
The role and importance of the EU
manufacturing sector
The crisis has impacted on the growth potential of EU
manufacturing sectors. Nonetheless, large drops in
shares of value added and employment in manufacturing
Executive summary
sectors does not mean that manufacturing industries have
become less important. From a long‑term perspective,
manufacturing sectors have remained among the most
productive in the EU economy. Labour productivity
growth per person employed in industrial sectors,
from 1995 to 2010, was higher than in the most productive
services activities, such as wholesale, retail and financial
intermediation.
R&D intensity is one of the factors driving higher
labour productivity growth in manufacturing. Among
all sectors in the economy, the most R&D intensive
in 2006 were manufacturing: radio, TV and communication
equipment, followed by pharmaceuticals, other transport
equipment and motor vehicles. As a result, patenting in
manufacturing sectors is also higher, with industries such
as office machinery, telecommunication equipment and
pharmaceuticals surpassing all others. According to the
community innovation survey, these sectors also exhibited
relatively high shares of innovative enterprises of all
enterprises in 2008.
Manufacturing sectors also have the highest multiplier
effects; inter‑linkages can generate positive, but also
negative, changes in terms of production or employment
in other sectors. A case study on the German automotive
sector illustrates this phenomenon. It analyses how
the demand for motor vehicles had an impact on other
industries and whether this impact is sustained.
Firms, sectors or economies try to increase their
competitiveness by lowering costs, increasing productivity
and innovation. In the aftermath of the latest crisis, EU
manufacturing has managed to reduce labour costs and
increase productivity.
The EU plays a central role in trade
of high value added goods and
services
The EU, Asia and North America account for about 84 %
of total world export flows in 2009. Trade among EU
countries (i.e. single market trade) represented more than
a quarter of world trade of manufactured goods in 2009. In
comparison, intra‑regional trade in Asia and North America
accounted for 15% and 4% respectively of world trade with
manufactured goods.
World trade flows mostly take place among developed
countries. Most high income countries’ trade takes place
with other high income countries. In all manufacturing
9

EU industrial structure 2011 — Trends and Performance
sectors except textiles, paper, machinery n.e.c, electrical
equipment and basic metals, half or more of EU‑27 exports
are destined for high income countries.
Part of international trade consists of cross‑border flows
of products of different industries (inter‑industry trade)
reflecting relative different factor (labour and capital)
endowments and technology. Countries which are relatively
endowed with capital tend to trade capital intensive goods
in exchange for labour intensive goods from countries
which are relatively well endowed with labour: for example,
pharmaceuticals for textiles or motor cars for food.
However, there is a high share of exchange of similar goods
between countries, with comparable levels of income. High
income countries tend for example to trade different brands
of cars with each other and low income countries different
types of clothes for each other. This intra‑industry trade
(IIT) is explained by factors such as economies of scale and
demand for differentiated products, rather than by relative
factor endowments. As demand for differentiated products,
and varieties of different qualities, tend to rise with income,
per capita incomes of countries play an important role in
determining trade patterns.
Almost 54 % of world trade occurs between countries in
the groups composed of the EU‑27 and other high‑income
countries. If upper‑medium countries are included, this
share rises to 70 %.
China stands out in the group of BRIC countries (Brazil,
Russia, India, China). More than 40 % of EU imports
in furniture, leather and footwear, clothing, electrical
equipment, non‑metallic mineral products, and metal
products come from China. Brazil captures 14 % and 12 % of
EU imports of paper and food products.
Competitiveness on world markets is measured by indices
of revealed comparative advantages. The measurements
of revealed comparative advantages for manufacturing
in 2009 show that the EU‑27 had comparative advantages
in industries such as printing, beverages, tobacco products,
motor vehicles and pharmaceuticals. In contrast, the
EU‑27 did not have any comparative advantages in
the production of computers, electronic and optical
products, textiles, other manufacturing, clothing and
refined petroleum. The measure of revealed comparative
advantages has some weaknesses which should be
taken into account. It is sensitive for the level of sectoral
aggregation, which may mask differing performance in
various categories of goods within the same group of
products. This is particularly relevant for industries which
10
have a large variety of brands and quality levels for the
same type of goods. Another consideration is country
heterogeneity within the EU, as the performance of the EU
as a whole is explained in some cases by the performance
of a few EU countries. Finally, the weight of each sector and
country in the export structure of the EU should be borne
in mind to get to a balanced assessment of the EU’s sectoral
performance in external trade.
Analysing comparative advantages for individual Member
States reveals that many EU countries, in 2009, have
comparative advantages in the production of wood and
wood products. The high revealed comparative advantages
for Austria, Estonia, Finland, Latvia and Portugal are in line
with the specialisation patterns that could be observed in
the analyses of industrial structure. Belgium, Cyprus and
Ireland appear to have comparative advantages in basic
pharmaceutical products. Bulgaria, Greece, Portugal and
Romania have comparative advantages in clothing and
Italy, Portugal and Romania have comparative advantages
in leather and footwear.
US manufacturing industries have comparative advantages
in chemicals, pharmaceuticals, machinery and other
manufacturing goods. Japanese manufacturing industries
have comparative advantages in motor vehicles, other
transport equipment, machinery, computers, electronic
and optical products. Analyses of the BRIC countries show
that the Brazilian, Indian and Russian manufacturing
industries have comparative advantages in the production
of labour intensive goods or products which are based on
endowments of natural resources. Chinese manufacturing
industries display a different pattern. It may seem as if China
has become one of the most important trade partners
in high technology goods but the high comparative
advantage of China in this type of trade should be
taken with a pinch of salt. China exports proportionally
more technology‑intensive goods, but a large share of
the content is imported from developed countries. As
confirmed by data on trade in intermediate goods, China is
still more an ‘assembler’ than a producer of high technology
goods. While the Chinese import of intermediate goods
consists of high quality goods, their exports seem to be of
a lower quality.
The analyses of trade in service show that the EU,
in 2009, has comparative advantages in almost all sectors
except personal, cultural and recreational, construction
services and travel. 1 Cyprus, Luxembourg and the
UK has comparative advantages in financial services.
1 See Chapter IV for a definition of these types of services.

Ireland also has a high RCA in computer and information
services, together with Finland. US service industries
have comparative advantage in financial services and in
trade with personal, cultural and recreational services.
Japanese service industries have comparative advantages
in construction services, as do China and Russia. India is
highly specialised in computer and information services.
China differs from India in this respect. While China has
strong comparative advantages in manufacturing radios,
televisions and telecommunication equipment, it does
not have any advantage in the services related to those
manufacturing goods. Brazil has comparative advantages
in other business services.
Increased internationalisation of EU
industries
The globalisation of economic activity shows itself not
only in increased trade but also in increased foreign direct
investment (FDI) which has displayed higher growth
than trade for at least the last 15 years. The stocks of
both inward and outward EU FDI are concentrated in the
financial and real estate sectors. In absolute terms, financial
Executive summary
intermediation, real estate and business activities represent
almost two thirds of the overall outward EU FDI stock and
more than two thirds of the inward EU stock of foreign
direct investment
Globalisation also has an impact on corporate research,
development and innovation (R&D&I). Internationalisation
of R&D has increased considerably in the EU. The share of
foreign owned patent applications in the EU increased from
some 10 % in 1990 to 17 % in 2007. The largest increase
has been recorded by intra‑EU patent applications. The
most internationalised manufacturing industries in terms
of foreign‑owned patents in the EU‑27 are manufacture of
radio, TV and communication equipment, food and drink,
office machinery and chemicals. Outward patenting and
R&D outside the own country is still relatively modest.
On average, only 10 % of all EU‑27 patents were granted
abroad between 2003 and 2007 at the same level as US
patents while BRIC countries had a larger share of outward
patenting. The US is the most important location for EU
outward R&D. The US accounts for 60 % of overseas patents
applied by EU entities at the EPO. The BRIC share is still small
but rising fast and is now larger than the Japanese share of
EU outward patenting.
11

EU industrial structure 2011 — Trends and Performance
Overview
12
This publication aims to satisfy the increasing
need for analysis of the competitiveness of the EU
economy from a sectoral perspective. Analyses of
this kind provide evidence of the industrial structure
in the different Member States, differences in
performance of different sectors within the EU, and
differences in sector performance across Member
States. They yield insight into the competitiveness
of different sectors and how they are affected by
business fluctuations. The EU industrial structure is
one of the few publications that present this view.
Together with the publications of Eurostat, 2 it is
unique in this respect. Throughout the publication,
the term ‘sectors’ is used interchangeably with
‘industries’ unless otherwise specified.
This publication can be used by economists and
policy makers in the EU and Member States or
anyone outside the EU interested in the structure
and performance of EU industries. Academics,
journalists, organisations and citizens who are
interested in different aspects of the EU economy
from a sectoral perspective may also find useful
information in this publication.
Chapter I contain analyses of short run fluctuations
impacting on EU sectors. The impacts of the latest
recession are compared across sectors. The latest
recession is compared to the previous two, since 1990, in
terms of size, duration and diffusion of the crisis. As most
industries seem to have moved out from the trough of the
recession, the recovery process is also compared across
sectors. It should be noted that since the analyses in the
chapter are based on short term indicators; the results
2 See for example ‘Eurostatistics. Data for short term economic
analysis.’ and ‘European Business: Facts and figures.’
are based on data that were available at the time of the
drafting of the report. Chapter II analyses the industrial
structure of the EU. The focus is on the sectoral structure
and specialisation. Some of the analyses use sectoral
taxonomies to aid comparison between sectors and
countries with respect to, for example, the technology
intensity of sectors. The chapter also provides a breakdown
of enterprises in size categories in terms of value added.
The last section of the chapter consists of case studies
analysing sectoral inter‑relations over time. Chapter III
aims to analyse industrial growth and competitiveness
within the EU from different perspectives. Assessments
of competitiveness are made from labour productivity
and unit labour costs developments in the EU. The use of
growth factors — labour, human capital, investments, and
technology — in the sectors is analysed using indicators.
Also, some results in terms of innovation are presented.
The last section of chapter III analyses developments
on the demand side, with special attention to product
composition and developments in private consumption
and investments. The analyses in chapter IV are devoted
to the external competitiveness of EU industry. A set of
indicators are presented aiming to show the performances
of EU manufacturing and services. Along with indicators
of export shares in world markets, relative trade balance,
revealed comparative advantage (RCA) and intra‑industry
trade (IIT), foreign direct investments is presented as an
indicator of the international movement of factors, and
patent data as indicators of the internationalisation of R&D.
The chapter also contains a section presenting indicators
showing the importance of trade in intermediate products
in different respects. These indicators aim to offer insight
into the significance of global value chains for EU sectors.
Finally, Annex A1 presents the statistical nomenclatures
used in the report and includes the abridged names of the
categories used in throughout.
The analyses of industrial structure and economic
developments are based on a set of indicators. The use of

indicators for sectors varies depending on the availability
of data for different sectors and countries; data availability
determines the level of aggregation on which sectors
are analysed. Availability also restricts some sectors and
indicators to being analysed only on a quarterly basis, while
others can be analysed monthly. This mainly affects services
sectors which, to a lesser extent than manufacturing,
can be analysed with the aid of monthly indicators. The
update of the statistical classification to NACE Rev. 2 has
had consequences for this publication. The introduction
of NACE 2 has brought about changes in the way data are
collected, grouped and reported. Not all data has been
revised backwards in time, which affects the possibility to
Overview
analyse developments over time for sectors according to
NACE 2. This has placed some limitations on the analyses.
The focus of the analyses and descriptions in this
publication is market economy sectors: all sectors from
mining to market services are included. When considered
necessary, the whole economy, including primary services
and non‑market services, are analysed. The data do not
always allow for comparison of the same set of indicators
for sectors at the same level of aggregation. This is
a consequence of variation in detail between different
sectors such as manufacturing and services and also
between different topics such as trade and R&D.
13

Chapter I
The aftermath of the crisis —
a long and uneven recovery(?)
The purpose of this chapter is to describe and analyse
short‑term developments in EU industries. 3 The analyses
in the other chapters are more focused on long‑term
developments and refer to conditions of a more structural
nature. The structure of EU manufacturing and services
industries changes slowly over time and the analyses in the
following chapters only partly reflect recent fluctuations
caused by the financial crisis. 4 This chapter focuses on the
most recent developments in 2009 and 2010, which are
analysed with the aid of monthly indicators of production
and turnover to measure growth in manufacturing and
services industries. Also, information on new orders
and business surveys results are used to assess future
developments. Indicators for services measuring
developments in real terms are however only available on
a quarterly basis.
A few words on the statistical nomenclatures for sectors
which are used in this chapter are in order here. The
presentation of monthly indicators of production and new
orders is based on the nomenclature NACE Rev. 2. The
information provided by the business surveys is based on
NACE Rev. 1. Data on services activities are not available
to the same extent as data on manufacturing activities.
3 DG Enterprise and Industry is regularly updating a monthly
note, which quantifies and analyses the economic recovery in
manufacturing, construction and services industries. http://
ec.europa.eu/enterprise/policies/industrial-competitiveness/
documents/index_en.htm#monthly_notes
4 This is also a consequence of a lag in the collection of annual
data, which is mostly used in those chapters. Annual data on
value-added and employment are available with a time lag of
several months Most of the annual data available when drafting
this report referred to 2008 when the effect of the financial crisis
had not manifested itself in the statistics.
Analyses of services industries, therefore, require data of
a different kind and from different sources. Box I.1. discusses
data issues concerning the service industry analyses.
I.1 Recession and recovery(?)
This section examines the impacts of the last recession in
terms of its effects on growth rates and cyclical fluctuations.
Even though the focus is on short‑term developments, the
dramatic falls in production that occurred during a relatively
short period of time may have had adverse effects on the
EU economy’s growth and level of output in the long‑term.
The last crisis can affect long‑term growth and output in at
least three ways: through employment, investments and
technology. 5 Analyses of short‑term developments can
provide insights for future long‑term growth.
The effects of the recession were felt on a global scale.
The next section begins with a comparison of EU‑27
manufacturing growth rates and cyclical fluctuations with
US and Japanese manufacturing growth rates and cyclical
fluctuations.
The latest recession was the most severe recession for a long
period of time. Its effects on industrial production and
employment were much harder than previous recessions
during since 1990. The latest recession is compared with the
two previous since 1990. The comparisons are made in terms
of sizes and durations of the recessions. The analyses thereafter
5 For a more detailed discussion see Directorate General for
Economic Affairs (2009. ECFIN Economic Brief, Issue 3 2009.
15

EU industrial structure 2011 — Trends and Performance
focus on how the recession has affected EU‑27 manufacturing
and services industries. The latest recession did not affect all
industries in the same way: some industries are more sensitive
to cyclical fluctuations and were therefore hit harder. The
impact of the recession on different EU industries will be
analysed in terms of size, duration and diffusion.
i11 manufacturing recession and
recovery(?)
Manufacturing growth rates in the EU, Japan and the
US are presented below. The Japanese growth rate is
16
considerably more variable than those of the EU and
US. The greater volatility of Japanese growth rates is
probably due to a high specialisation in capital goods
which are more sensitive to business fluctuations. The fall
in Japanese manufacturing production was significantly
larger than for the EU and the US. Following the trough
in early 2009, Japanese manufacturing went through
an impressive recovery in 2010. The sharp decline in the
first half of 2011 can to a large extent be explained by
the impacts of the earthquake. 6 Judging from the latest
available data, growth rates seem to return to average
levels, cf. Figure I.1.
FIgURE I.1: growth rates (T/T-12) in manufacturing in the EU, Japan and the US from 1990
to June 2011 (monthly data)
40
30
20
10
0
-10
-20
-30
-40
1991
1992
1993
1994
1995
1996
Source: own calculations using Eurostat data.
1997
1998
1999
2000
Japanese industrial production fluctuates much more
than the EU and US industrial production: peaks are higher
2001
2002
2003
2004
2005
2006
EU growth
Japan growth
US growth
TAbLE I.1: Descriptive statistics of the growth rates of EU, US and Japanese manufacturing industry
production
2007
2008
2009
mean standard deviation max min
Eu growth 1.26 5.11 9.23 ‑19.75
Japan growth 0.01 8.50 33.38 ‑35.24
us growth 2.19 5.24 10.27 ‑17.64
Source: own calculations using Eurostat data.
2010
2011
and troughs are lower. US industrial production grows on
average faster than in the EU and Japan, cf. Table I.1.
6 The full extent of the impact of the earthquake in Japan on
Japanese manufacturing is not known at the time of drafting.

The impact of the last downturn in the EU was unprecedented
in size but did not last longer when compared to two
other large recessions since 1990. 7 The 1992‑93 recession
7 It did not last longer in the sense that the number of months
with falling industrial production relative to the previous
month was not greater than for the 1992-93 recession. Another
measure of the duration would be the number of months with
decreasing 12-month growth rates. Measuring the duration of the
recession this way yields 18 months of falling 12-month growth
rates for both the 1992-93 and the latest recession.
Chapter I — The aftermath of the crisis — a long and uneven recovery(?)
lasted 19 months and the millennium recession
only 13 months. The latest recession lasted 17 months before
industrial production began to pick up again, cf. Figure I.2.
FIgURE I.2: Downturns and recoveries in EU-27 industrial production since 1990
120
115
110
105
100
95
90
85
80
75
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Source: own calculations using Eurostat data.
The size of the effects of the financial crisis for
EU‑27 manufacturing was larger than the previous
recessions since 1990. This is illustrated below where EU
manufacturing growth between 1991 and June 2011 has
been plotted with the mean of growth and the mean plus
and minus the standard deviation of the growth. While
EU Manufacturing
2010 2011
the downturns in 1992‑93 and in the beginning of the
millennium caused growth rates below the mean minus one
standard deviation, the financial crisis caused growth rates
to fall significantly below the mean minus two standard
deviations, cf. Figure I.3.
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
17

EU industrial structure 2011 — Trends and Performance
FIgURE I.3: EU Manufacturing growth rates (T/T-12) from 1991 to 2010 (monthly data)
Figure I.2 showed that the latest recession was not
significantly longer than previous recessions since the 1990.
This conclusion was made on the basis of the number of
months with negative growth rates. Below, the analysis
will focus on the duration of recovery, i.e, the number of
months it takes manufacturing production to reach the
pre‑recession peak. The latest recession is compared with
the two previous since 1990. The size of the recession is
measured as percentage deviations from the peak preceding
the recession. While it is still too early to determine how
long it will take to regain the peak of January 2008, it is
clear that the latest recession was much deeper than the
previous ones since 1990. Following the 1992‑93 recession
it took some two and a half years for EU‑27 manufacturing
industrial production to regain its pre‑recession production
level. The trough of industrial production was seven percent
lower than the peak in February 1992. The recession during
the millennium was milder but the recovery lasted longer:
the pre‑recession level of industrial production was not
reached again for four and a half years. Judging from the
latest available data, it may take four years before the
pre‑recession peak is regained
18
15
10
5
0
-5
-10
-15
-20
Mean - 2stdev
Mean + 2stdev
Mean - stdev
Mean + stdev
Mean
Growth
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Source: own calculations using Eurostat data.
Comparing the growth rates during the recoveries of
the last three recessions it seems that they are higher
the deeper the trough during recessions. The trough in
the 1992‑93 recession was lower than in the millennium
recession. Growth after the trough was significantly
higher following the 1992‑93 recession compared to the
millennium recession. This seems to be the case also for
the latest recession as the pace of recovery after it is higher
than after the two previous. Nonetheless, the current
recovery is likely to last longer than the previous since 1990,
cf. Figure I.4. 8
8 The choice of number of months for the comparison of
post-trough growth rates is determined by the number of
months it took manufacturing production to regain pre-peak
recession level after the trough during the1992-93 recession.

The impacts of the latest recession varied across
manufacturing industries. The different manufacturing
aggregates are compared below with respect to the size
and duration of the latest recession. The mildest effect
was felt in the industries producing non‑durable consumer
goods while industries producing durable consumer goods
were hit much harder. Capital goods and intermediate
Chapter I — The aftermath of the crisis — a long and uneven recovery(?)
FIgURE I.4: EU-27 recessions and recoveries in the last two decades. Percentage deviations from peak
and months of recovery for EU-27 manufacturing production
Percent
5
0
-5
-10
-15
-20
-25
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54
Source: own calculations using Eurostat data.
Months
The nancial crisis
The millenium recession
The 1992-1993 recession
goods suffered most, with production losses of 26 % relative
to the pre‑recession peak levels, while the total consumer
goods and non‑durable consumer goods faired relatively
well with production losses amounting to between 65%
and 7 % at the troughs. Production levels for industries
producing non‑durable consumer goods are close to the
pre‑recession peak cf. Figure I.5. 9
FIgURE I.5: Capital, Durable and Intermediate goods were most heavily hit during the latest recession
Percent
5
0
-5
-10
-15
-20
-25
-30
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40
Source: own calculations using Eurostat data.
Months
Non-durables
Intermediates
Durables
Consumer
Capital
9 In order to facilitate comparison of the duration of the recession
for the different manufacturing aggregates, the peak levels for
all sub-sectors in figure II.3 have been set to the peak level for
capital and intermediate goods which occurred in January 2008.
In reality, the decline for durable consumer goods began in
August 2007 while the peak for non-durable consumer goods
and total consumer goods occurred in October 2007.
19

EU industrial structure 2011 — Trends and Performance
The largest decline occurred in the motor vehicle industries,
where output fell by 45 % from peak to trough during the
crisis. The industry recovered relatively fast and the trough
was reached after only 10 months. Other industries also hit
relatively hard, and which recovered relatively fast, were
basic metals and machinery n.e.c. industries. Industries
producing non‑durable consumer goods were not hit as
hard, even though the decline in output in some cases
20
lasted quite some time. Some industries, such as tobacco,
textiles and clothing, have been in decline for quite some
time and experience a downward trend. Production in the
pharmaceuticals industry was hardly affected. Production
only fell by 2% from February to March 2008. Production of
pharmaceuticals thereafter continued to increase and the
pre‑recession peak was surpassed in August the same year,
cf. Figure I.6. 10
FIgURE I.6: Decline in output from Peak to Trough (%) and number of months of falling output for
EU-27 industries during the latest crisis 11
50
40
30
20
10
0
Motor vehicles
Basic metals
Machinery n.e.c.
Fabricated metal
Textiles
Tobacco
Electrical equipment
Non-metallic minerals
Intermediate goods
Capital goods
Wood
Furniture
Rubber and plastics
Leather
Chemicals
Durables
Manufacturing
Construction
Computers
Mining and quarrying
Clothing
Paper
Other transport
Repair and installation
Coke and rened petroleum
Printing and publishing
Beverages
Other manufacturing
Consumer goods
P-T
Months
Note: Decline in output and number of months are both measured on the left axis. The calculations have been made for data between
January 2008 and December 2010. Some industries have been in decline for a long time and the calculation of decline between peak and
trough has not taken this into account.
Source: own calculations using Eurostat data.
The analyses so far concern the size and duration of the
crisis. The analyses below focus on the diffusion of the
crisis and recovery across EU manufacturing industries. 12
The diffusion of the financial crisis is illustrated by the
percentage of manufacturing industries which, each
month, exhibit very low growth rates. Very low growth
rates are defined as growth rates lower than average
growth rates minus two standard deviations before the
latest financial crisis. 13 75% of manufacturing industries
displayed very low growth rates in March 2009. More
than half of the manufacturing industries experienced
very low growth rates between November 2008 and
September 2009. 14 The recovery can be seen by the rapid
decline of manufacturing industries with very low growth
rates at the end of 2009 and the beginning of 2010. In
June 2011, no manufacturing industries had had growth
rates below the average minus two standard deviations
since January 2010, cf. Figure I.7.
10 The choice of selecting the first and last months is somewhat arbitrary and affects the appearance of the figure. Also production in the food,
computers and other manufacturing industries has surpassed prerecession peaks.
11 See the annex to chapter II for a graph illustrating the development of manufacturing output from peaks to troughs in the individual Member
States. See also European Commission (2009). Statistics in focus — 97/2009. Eurostat.
12 The analysis is performed for two-digit manufacturing industries.
13 See also European Commission (2009). Product Market Review 2009. Microeconomic consequences of the crisis and implications for the
recovery. European Economy 11. Directorate Economic and Financial Affairs.
14 The mean and standard deviations used correspond to the period prior to the 2008-2009 crisis. For more discussion, see European
Commission (2009).
Non-durables
Food
Pharmaceuticals

The previous figures imply that there is a great deal of variety
in growth and cyclical behaviour across the manufacturing
industries. The industries are therefore compared using
measures of the cyclical fluctuation and monthly growth
rates in constant prices between 1990 and January 2011. The
effect of the financial crisis in terms of production loss is also
compared across manufacturing industries in the table below.
The columns below the heading ‘cycle’ present the
maximum, minimum and the cyclical intensity of the
cycle components for each industry. Cyclical fluctuations
are measured as deviations of actual output from
trend output. 15 The cycle fluctuation for each industry
is compared to the total manufacturing industry by
dividing the standard deviation for each industry’s
cyclical component with the standard deviation for the
total manufacturing industry’s cyclical component. 16
A cyclical intensity around 1.0 indicates that an industry
faces the same cyclical fluctuations as the aggregate
manufacturing.
15 The gaps and trend output are estimated with the
Christiano-Fitzgerald band-pass filter, see Christiano, L. J. and
Fitzgerald, T. J. (1996).
16 It should be noted that the calculations of the cyclical fluctuations
are subject to uncertainty. The uncertainty stems from the fact
that trend (or potential) output is not observable and has to be
estimated by some method. Thus, cyclical fluctuations, which are
measured as deviations of trend output from actual output, are
also uncertain.
Chapter I — The aftermath of the crisis — a long and uneven recovery(?)
FIgURE I.7: Percentage of manufacturing industries with very low growth rates in 1991-2011
80
70
60
50
40
30
20
10
0
1991
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Source: own calculations using Eurostat data.
Industries producing repair of machinery, motor vehicles,
electrical equipment, machinery n.e.c. and computers,
electronic and optical products are subject to larger cyclical
fluctuations than other industries. On the lower range of
the scale are industries which produce goods which are
less sensitive to fluctuations in income, and hence are less
sensitive to fluctuations in demand. These industries consist
of enterprises producing necessity goods such as the food
and beverage industries and also pharmaceutical industries.
The columns below the heading ‘growth’ present the
maximum, minimum and average twelve month growth
rates. The growth rates are calculated as the monthly
growth rates relative to the same month of the previous
years. The pharmaceutical industry displays average growth
rates which are significantly higher than any other. Also,
the industry producing electronic and optical products has
relatively high average growth rates. The lowest average
growth rates are found in industries producing textiles,
leather and footwear, tobacco and clothing.
21

EU industrial structure 2011 — Trends and Performance
The last column presents production loss during the crises.
Production loss is calculated as production during the
trough relative to production during the peak before the
crisis. The largest production losses during the latest crisis
22
were experienced by industries producing motor vehicles
and basic metals. These industries are also subject to large
fluctuations as indicated by the high cyclical intensities for
these industries, cf. Table I.2.
TAbLE I.2: growth and volatility in EU-27 manufacturing industries 1990-2011 (%)
nacE rev 2
codes
industry max min
cycle growth crisis
cyclical
intensity
max min average
production
loss
Capital 12.5 ‑15.9 1.3 16.2 ‑25.3 1.5 ‑25.3
Consumer 3.1 ‑4.2 0.4 5.1 ‑6.7 0.6 ‑6.7
Consumer dur 8.7 ‑11.1 1.1 9.8 ‑20.3 0.0 ‑20.3
Consumer non dur 2.4 ‑3.1 0.3 4.7 ‑4.4 0.7 ‑4.4
Intermediate 10.5 ‑14.6 1.2 13.8 ‑25.7 1.1 ‑25.7
B Mining and quarrying 6.2 ‑5.6 0.7 17.2 ‑16.5 ‑1.1 ‑16.5
c Manufacturing 8.8 ‑11.8 1.0 9.2 ‑19.8 1.2 ‑19.8
c10 Food 1.7 ‑1.9 0.2 5.9 ‑3.4 1.3 ‑3.4
c11 Beverages 3.8 ‑3.3 0.5 15.2 ‑9.4 0.8 ‑7.3
c12 Tobacco 8.7 ‑6.9 0.9 18.5 ‑22.9 ‑3.5 ‑22.9
c13 Textiles 6.7 ‑12.0 1.0 14.5 ‑25.3 ‑2.7 ‑25.3
c14 Clothing 5.8 ‑7.6 1.0 11.4 ‑17.7 ‑4.5 ‑17.7
c15 Leather and footwear 6.3 ‑9.7 1.2 8.3 ‑22.5 ‑4.0 ‑22.5
c16
Wood and wood
products
8.0 ‑9.8 1.1 13.6 ‑22.1 0.3 ‑22.1
c17 Paper 5.7 ‑8.1 0.7 10.8 ‑15.1 1.2 ‑15.1
c18 Printing 3.3 ‑5.0 0.6 13.5 ‑8.2 0.3 ‑8.2
c19 Refined petroleum 4.2 ‑3.9 0.5 14.3 ‑11.2 0.2 ‑11.2
c20 Chemicals 7.4 ‑12.1 0.9 17.1 ‑22.2 1.7 ‑22.2
c21 Pharmaceuticals 2.1 ‑4.2 0.4 16.8 ‑8.7 5.1 ‑2.7
c22 Rubber & plastics 9.4 ‑12.3 1.1 17.7 ‑22.0 1.4 ‑22.0
c23
Non‑metallic mineral
products
8.6 ‑11.8 1.1 13.4 ‑24.0 ‑0.2 ‑24.0
c24 Basic metals 13.7 ‑21.8 1.6 36.2 ‑40.3 0.5 ‑40.3
c25 Metal products 12.6 ‑15.8 1.4 13.3 ‑27.9 0.7 ‑27.9
c26
Computers, electronic
& optical
14.5 ‑16.0 1.6 23.2 ‑19.6 3.4 ‑19.6
c27 Electrical equipment 12.7 ‑17.3 1.5 16.5 ‑27.5 1.2 ‑27.5
c28 Machinery n.e.c. 16.0 ‑21.3 1.8 20.4 ‑30.6 1.0 ‑30.6
c29 Motor vehicles 17.1 ‑22.9 1.8 34.9 ‑44.6 2.8 ‑44.6
c30 Other transport eq. 5.2 ‑4.8 0.7 16.7 ‑14.4 0.5 ‑14.4
c31 Furniture 6.1 ‑6.9 0.8 12.1 ‑23.3 0.7 ‑9.3
c32 Other manufacturing 8.8 ‑9.5 1.0 10.7 ‑21.5 ‑0.8 ‑21.5
c33 Repair of machinery 20.9 ‑19.3 2.0 20.0 ‑31.8 ‑1.1 ‑15.3
d Electricity & gas 3.4 ‑3.6 0.4 15.4 ‑13.1 1.4 ‑13.1
F Construction 5.1 ‑4.2 0.7 10.7 ‑13.7 0.5 ‑10.7
F41 Buildings 5.6 ‑5.6 0.8 12.2 ‑13.0 0.8 ‑13.0
F42 Civil engineering 3.8 ‑5.0 0.6 12.5 ‑20.2 ‑0.4 ‑18.3
Source: own calculations using Eurostat data.

i12 services recession and recovery(?)
Service industries have grown faster and have been
exposed to fewer cyclical fluctuations than total industry
since 1996. Inspection of quarterly data on value added
in constant prices over the period confirms that the
service sector generally shows higher growth rates and
less volatility than total industry. 17 Due to limited data
availability, the latest crisis can only be compared to the
recession at the turn of the millennium. Developments in
FIgURE I.8: growth in EU services industries 1996-2011 (%)
10
5
0
-5
-10
-15
-20
1996
1996Q4
1997Q3
1998Q2
1999
17 Since there is no data on production in constant prices, value
added is used to calculate growth rates for services.
1999Q4
2000Q3
2001Q2
2001Q2
Chapter I — The aftermath of the crisis — a long and uneven recovery(?)
2002
2002Q4
both recessions, however, show that the fall in production
for total industry was significantly larger than for services. 18
In fact, negative growth rates for the service industries did
not appear before the latest recession. Data availability
only allows for comparison of large aggregates of services
industries. Fluctuations for trade, hotels and restaurants are
relatively larger than for the other aggregates of service
industries. Non‑market services show considerably less
volatility, cf. Figure I.8.
Non-market services
Financial intermediation and business services
Trade, hotels and restaurants
Total industry (excluding construction)
Note: Growth rates in EU services industries and total industry value added in constant prices relative to the same quarter of the previous
year in 1996:1‑2011:1 (%).
Source: own calculations using Eurostat data.
Below, two groups of market services are compared to GDP.
The relatively large sensitivity to fluctuations for the group
‘trade, hotels and restaurants is obvious and fluctuations in
production for these service industries are larger than for
GDP as a whole. Also the growth in value added for this
group of service industries exceeds that of GDP for the
period 1996‑2009.
2003Q3
2004Q2
2005
2005Q4
2006Q3
2007Q2
Growth rates for ‘Financial intermediation and business
services’ are higher and fluctuate less than growth rates for
‘trade, hotels and restaurants. The fall in production was
also less than half of that for GDP. The figure indicates that
developments in the sector lag behind that of GDP. The
decline begins later, the trough appears later and finally the
recovery begins a quarter later than the recovery of GDP,
cf. Figure I.9.
18 Total industry consists of mining and quarrying, manufacturing
and industries producing electricity, gas and water.
2008
2008Q4
2009Q3
2010Q2
2011
23

EU industrial structure 2011 — Trends and Performance
FIgURE I.9: growth rates in EU services industries compared to the whole EU economy 1996-2010 (%)
8
6
4
2
0
-2
-4
-6
-8
I.2 Sector developments: the
current recovery(?)
The previous section has shown the size, duration and
diffusion of the latest crisis according to the information
that was available at the time of drafting this text. It is
not yet possible to have a full assessment of the duration
of the recovery since available data show that production
has yet to reach pre‑crisis levels. The focus of this section
is on more recent developments and the objective is to
assess the pace of the recovery, to what extent it has spread
across manufacturing and service industries, and also what
it implies for future developments. The section begins with
an overview of the manufacturing industries, followed
by a state of play in services sectors. The two parts are
structured in a similar way. Monthly indicators of production
are used for analyses of the most recent developments and
an indicator is constructed to assess the intensity of the
recovery and the speed of diffusion across industries. Data
availability only allows construction of this indicator for
manufacturing industries. Developments in the near future
are assessed with the aid of information on expectations
of future demand. The indicators for manufacturing and
services activities are not always similar and comparisons
should be made with caution.
24
1996
1996Q4
1997Q3
1998Q2
1999
1999Q4
2000Q3
2001Q2
2001Q2
2002
Financial intermediation and business services
Trade, hotels and restaurants
All branches - Total
2002Q4
Note: Growth rates in EU services industries and total industry value added in constant prices relative to the same quarter of the previous
year in 1996:1‑2011:1 (%).
Source: own calculations using Eurostat data.
2003Q3
2004Q2
2005
2005Q4
2006Q3
2007Q2
i21 recent developments in
manufacturing industries
An indicator which measures how fluctuations spread
across manufacturing industries is used to illustrate
diffusion. The diffusion index is defined as the difference
between the percentage of manufacturing industries that
are expanding and of those that are declining. The index
ranges from ‑100 to 100. ‘Expanding’ and ‘declining’ mean
positive and negative growth rates respectively. The total
number of industries used in the calculations is 93 (defined
in terms of the 3‑digit level of NACE Rev. 2). ‘Expansion’ is
defined as no negative or zero growth. The lowest value of
the index, ‑90.5, corresponds to January 2009 when only
four manufacturing industries displayed positive growth
rates. The latest available data show that the recovery
process that was on the way in the beginning of 2011 is
fragile. The diffusion index of 14 in June 2011 means
that 57 % of manufacturing industries display positive
growth rates. It remains to be seen whether this fall of the
diffusion index is temporary, cf. Figure I.10.
2008
2008Q4
2009Q3
2010Q2
2011

Chapter I — The aftermath of the crisis — a long and uneven recovery(?)
FIgURE I.10: EU manufacturing diffusion index from January 1991 to June 2011 (monthly data)
100
80
60
40
20
0
-20
-40
-60
-80
-100
1991
1992
1993
1994
1995
1996
Source: own calculations using Eurostat data.
1997
1998
1999
As noted in Figure I.7 above, the recovery process, although
fragile, seems to be underway in the EU‑27 manufacturing
2000
industries. There are even three manufacturing industries
which have reached their pre‑crisis levels; food,
pharmaceuticals and other manufacturing. The three
manufacturing industries which were hit hardest, motor
vehicles, basic metals and machinery n.e.c., have also
recorded the largest percentage increases since their
troughs. the recovery seems to be fragile in furniture,
mining and quarrying and tobacco where very modest
increases are recorded only lasting recent months,
cf. Figure I.11. 19
19 See the annex to chapter II for a graph illustrating the
development of manufacturing output since the troughs in the
individual Member States.
2001
2002
2003
2004
2005
2006
2007
2008
Diusion index
2009
2010
2011
The most recent development for the EU‑27 manufacturing
industries together with mining, electricity & water and
construction, are summarised in the table below. The
first four columns present annual average growth rates
in 2009 and 2010, the growth rate in 2010 compared
with 2009, and the last six months (January to June 2011). The
fifth column presents, for each industry, the growth since
the trough at the crisis; the last column, ‘spread’, presents
the growth difference in percentage points for each industry
relative manufacturing for the last six months. 20
20 The spread is the difference between growth of industry
i and manufacturing the last six months minus the difference
between the average growth difference between industry i and
manufacturing for the whole period.
25

EU industrial structure 2011 — Trends and Performance
FIgURE I.11: Increase in output from the trough to June 2011 (%) and number of months of increasing
output for EU-27 industries since the latest crisis
80
70
60
50
40
30
20
10
0
Starting with aggregates, consumer goods were not hit as
hard by the crisis as capital and intermediate goods. Among
consumer goods, non‑durable consumer goods such as
food and pharmaceuticals have also fared better, confirmed
by their lower cyclical intensity shown in Table II.2 above.
The lowest growth rates in 2009 were recorded by capital
26
Motor vehicles
Basic metals
Machinery n.e.c.
Computers
Electrical equipment
Chemicals
Capital goods
Intermediate goods
Fabricated metal
Rubber and plastics
Pharmaceuticals
Leather
Manufacturing
Textiles
Other manufacturing
Paper
Note: Increase in output and number of months are both measured on the left axis. The calculations have been made for data between
January 2008 and March 2011. N in ‘T‑N’ stands for ‘now’ which in this case means latest available data.
Source: own calculations using Eurostat data.
Repair and installation
Coke and rened petroleum
Non-metallic minerals
Other transport
Wood
Durables
Food
Consumer goods
Non-durables
and intermediate goods, produced in, for example,
industries producing machinery n.e.c. and basic metals.
Growth rates in industries producing motor vehicles,
computers and machinery n.e.c. are particularly high during
the last six months, cf. Table I.3.
TAbLE I.3: Recent developments in EU manufacturing, mining, electricity and construction
nacE
rev 2
growth
2009
growth
2010
2010/2009
last six
months
Construction
Beverages
Printing and publishing
post trough
growth
Clothing
Furniture
Mining and quarrying
Tobacco
spread last
six months
Capital ‑19.4 9.3 28.7 11.2 18.7 4.3
Consumer ‑4.3 3.3 7.6 1.8 5.3 ‑4.1
Durable consumer ‑15.0 4.5 19.5 0.4 5.3 ‑4.9
Nondurable consumer ‑2.6 3.0 5.6 2.0 5.0 ‑4.0
Intermediate ‑17.6 9.6 27.2 6.5 18.3 0.2
B Mining & quarrying ‑10.9 ‑0.7 10.2 ‑7.4 ‑5.6 ‑11.4
c Manufacturing ‑14.5 7.5 22.0 6.5 13.3 ‑
c10 Food ‑1.0 2.2 3.2 1.9 5.3 ‑4.7
c11 Beverages ‑2.6 ‑1.3 1.3 2.3 2.1 ‑3.9
>>>

nacE
rev 2
growth
2009
Chapter I — The aftermath of the crisis — a long and uneven recovery(?)
growth
2010
2010/2009
last six
months
post trough
growth
spread last
six months
c12 Tobacco ‑2.8 ‑6.2 ‑3.4 ‑8.3 ‑7.5 ‑10.0
c13 Textiles ‑16.6 8.4 25.0 1.3 11.0 ‑1.3
c14 Clothing ‑10.8 0.6 11.3 ‑2.4 3.9 ‑3.2
c15 Leather and footwear ‑12.5 3.3 15.8 7.3 14.1 5.8
c16 Wood ‑13.7 3.8 17.5 1.7 5.0 ‑3.9
c17 Paper ‑8.9 6.1 15.0 0.8 8.5 ‑5.6
c18 Printing ‑7.2 1.6 8.9 1.4 3.8 ‑4.3
c19 Refined petroleum ‑7.8 0.1 7.9 1.5 6.3 ‑3.9
c20 Chemicals ‑10.4 10.1 20.5 3.4 19.9 ‑3.6
c21 Pharmaceuticals 3.3 5.8 2.5 3.6 14.2 ‑6.8
c22 Rubber & plastics ‑12.8 7.9 20.7 6.5 15.9 ‑0.2
c23 Non metallic mineral products ‑18.5 2.6 21.1 5.9 6.6 0.7
c24 Basic metals ‑25.6 19.6 45.1 8.5 46.2 2.7
c25 Metal products ‑21.8 7.4 29.1 9.1 16.0 3.0
c26 Computers, electronic & optical ‑15.2 11.3 26.5 9.4 23.7 0.7
c27 Electrical eq. ‑20.3 11.2 31.5 8.6 20.7 2.1
c28 Machinery n.e.c. ‑26.1 10.5 36.5 14.9 26.3 8.5
c29 Motor vehicles ‑21.9 21.8 43.7 16.6 62.1 8.4
c30 Other transport eq. ‑6.1 ‑2.7 3.4 2.6 5.8 ‑3.2
c31 Furniture ‑16.3 ‑0.9 15.4 2.6 2.8 ‑1.9
c32 Other manufacturing ‑5.9 7.9 13.7 2.9 9.6 ‑3.1
c33 Repair of machinery ‑8.7 3.4 12.1 3.0 8.7 ‑1.2
d Electricity & gas ‑4.9 4.2 9.1 ‑3.7 3.4 ‑10.2
F Construction ‑8.6 ‑3.9 4.7 ‑1.3 4.0 ‑7.1
F41 Buildings ‑10.8 ‑3.2 7.6 ‑1.7 3.5 ‑7.7
F42 Civil engineering 2.2 ‑7.0 ‑9.3 0.9 3.5 ‑4.0
Source: own calculations using Eurostat data.
The remainder of this section aims to assess future
developments for the manufacturing industries. The
analyses below are undertaken using information on new
orders and other leading indicators: order‑book levels,
stocks of finished products and production expectations.
The discussion will shed light on expectations for the near
future and on the extent to which the recovery will be felt
across the manufacturing industries in the months to come.
Monthly real21 growth rates, relative to the same month of
the previous year, of production and new orders for total
21 New orders have been deflated with the corresponding producer
price indices for the aggregates.
manufacturing are used in the first step of the assessment
of future developments. New orders recorded its lowest
level in February 2009. The decline, although modest
in the beginning, started in early 2007. The recovery of
new orders, during the recent recession, preceded the
recovery of production with one month. Production
growth hit bottom in March 2009. Positive growth rates
of new orders occurred again in November 2009, two
months before production growth rates became positive.
Twelve‑month growth rates of new orders and production
increased steadily until the second quarter of 2010. After
having levelled out during the last quarter of 2010 and the
first two months of 2011, growth rates are declining again,
cf. Figure I.12.
27

EU industrial structure 2011 — Trends and Performance
FIgURE I.12: EU-27 manufacturing growth rates of production and new orders (T/T-12) for
manufacturing goods from January 2001 to June 2011
20
15
10
5
0
-5
-10
-15
-20
-25
-30
-35
The main aggregates of manufactured goods show similar
developments Declines in new orders were particularly
dramatic for capital goods, intermediate goods and, to
a lesser extent, consumer durable goods.
The second step in the analyses is carried out with indicators
from EU business surveys. 22 Three indicators, assessment
of order‑book levels, of stocks of finished products, and
expectations of future demand, confirm the picture of
recovery and its fragility that has taken place during recent
28
months. Order‑book levels and production expectation
reached their lowest levels in the middle of 2009. These
two indicators provide information on developments in
production in the near future. Stocks of finished products act
as a buffer and allow production to continue at a higher than
actual demand during recessions. Stocks of finished products
started to increase in mid‑2007 and reached its highest level
in April 2009. The stocks kept declining until April 2011 but
began to rise in May 2011. The rise since May mirrors the
declines of the other two indicators, cf. Figure I.13.
FIgURE I.13: EU-27 manufacturing order-books levels, stocks of finished products and production
expectations from January 1985 to February 2011 (monthly data)
30
20
10
0
-10
-20
-30
-40
-50
-60
-70
Jan-85
Manufacturing production
Manufacturing new orders
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Source: own calculations using Eurostat data.
Jan-86
Jan-87
Jan-88
Jan-89
Jan-90
Jan-91
Jan-92
Jan-93
Jan-94
Jan-95
Jan-96
Jan-97
Jan-98
Production expectations for the months ahead
Assessment of stocks of nished products
Assessment of order-book levels
Note: There is a break in the time series due to a change in the classification of economic activities. Data until April 2010 are collected
according to NACE Rev. 1.1. Data from May 2010 according to NACE Rev. 2. 23
Source: Directorate General for Economic and Financial Affairs.
22 Directorate General for Economic and Financial Affairs business surveys.
23 The change of classification to NACE Rev. 2 entails a change in the identification and grouping of similar economic activities in the business
surveys. This gave rise to a break in the time series. Analyses of consequences of the change indicate that the changeover has affected the
level but did not, on the whole, affect the direction of the change, only its magnitude. See DG ECFIN, http://ec.europa.eu/economy_finance/
db_indicators/surveys/nace2/index_en.htm for further discussion. 23
Jan-99
Jan-00
Jan-01
Jan-02
Jan-03
Jan-04
Jan-05
Jan-06
Jan-07
Jan-08
Jan-09
Jan-10
Jan-11

The third step in assessing future developments
involves an attempt to predict future developments of
EU manufacturing production. The development of EU
manufacturing production displays significant changes
over time, with some marked breaks in the series. One
way to characterise such a series is to think of it in terms
of being in different regimes or states. Two such states can
be expansion and contraction. Provided that the economy
is in expansion, there is a probability that it will be in
contraction the next period. 24 The assessment of future
developments is performed by an econometric analysis
of the probability of contraction of EU manufacturing
production between 1990 and June 2011. 25 The three large
recessions during the time period were associated with
large probabilities of contraction. In the latest recession,
FIgURE I.14: Increasing probabilities of contraction in the end of 2011
115
110
105
100
95
90
85
80
75
Chapter I — The aftermath of the crisis — a long and uneven recovery(?)
probabilities fell significantly during the end of 2009. The
probabilities of contraction remain low as manufacturing
picks up again after the trough.
The assessment also includes a forecast of manufacturing
production between July 2011 and June 2012, with the
associated probabilities for a contraction during this period
of time. The vertical blue line at the right of the figure divides
the sample into actual and predicted production. The forecast
is based on the latest available data for manufacturing
production and manufacturing new orders. 26 According to
the forecast, manufacturing production growth slows down
in the end of 2011 but picks up slowly again in the beginning
of 2012. The probabilities of contraction during the forecast
period are rising but still below 0.2, cf. Figure I.14.
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Source: own calculations using Eurostat data.
Manufacturing production
Probability of contraction
Forecast
There is a high degree of uncertainty associated with the
analysis above. The forecast of EU27 industrial production
and predicted probabilities should therefore not be taken
literally. It is very difficult to assess how the developments in
the financial markets that occur at the drafting of this report
will impact on industrial production. Also other forecasts
24 If the economy is expanding in the current time period, the
probability that the economy will be expanding also in the next
time period is p. The probability that the economy instead will be
contracting in the next period is then 1-p.
25 See Hamilton, J. D. (1989) for a discussion of the method.
and business cycle indicators indicate that economic
activity will slow down in the EU. DG ECFIN’s Economic
Sentiment Indicator declined in July 2011 both for the EU and
the Euro area. Also, the Flash Consumer Confidence Indicator
declined in July. 27
26 A bivariate VAR model including three lags of growth rates
of manufacturing production and new orders is used for the
forecast. New orders is deflated by manufacturing producer
prices.
27 http://ec.europa.eu/economy_finance/db_indicators/surveys/
index_en.htm
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
29

EU industrial structure 2011 — Trends and Performance
i22 recent developments in services
industries
The quarterly data presented in section I.1.2 presented
highly aggregated service sectors; the analyses below offer
more detail on developments in various service sectors
for the last months for which data are available. From the
last month for which data are available for all sectors, one
30
can see that only four service industries; water transport,
warehousing and support services for transportation,
computer services and R&D and technical activities still
display negative growth. Wholesale trade have recovered
remarkable well and display very high growth rates. Looking
at aggregates, total services display positive growth rates
for the whole period, cf. Table I.4.
TAbLE I.4: EU services production, recent developments. growth in services turnover in constant
prices relative to the same month of the previous year
nacE 2
codes
2010:08 2010:09 2010:10 2010:11 2010:12 2011:01 2011:02 2011:03
g45 Motor vehicles trade 2.1 0.6 0.5 3.9 2.3 4.6 5.2 1.8
g46 Wholesale trade 7.9 7.2 7.3 6.9 5.7 4.8 9.9 7.1
g47 Retail trade 1.5 1.6 1.6 2.8 3.2 4.7 5.1 5.4
i Accommodation & Food 5.0 4.6 3.1 4.3 4.8 4.1 3.5 4.0
h49 Land transport 4.6 3.7 2.9 3.6 3.5 4.1 3.2 2.3
h50 Water transport ‑2.1 2.6 3.5 6.9 0.6 ‑1.3 2.1 ‑1.7
h51 Air transport 13.3 15.8 13.9 15.5 10.1 14.5 8.9 6.5
h52
Warehousing and support
activities for transportation
0.2 0.6 0.3 ‑1.1 ‑1.1 0.4 ‑1.5 ‑1.7
h53 Postal and courier 13.2 10.4 8.3 9.1 7.3 6.7 5.5 4.5
J61 Tele‑ communications 3.3 2.7 2.5 2.1 2.5 2.1 2.1 1.9
J62 Computer services ‑0.4 ‑1.7 ‑1.6 ‑1.8 ‑2.2 ‑1.9 ‑2.0 ‑2.3
m72 R&D and technical activities 5.5 4.2 5.2 0.9 1.1 ‑1.9 ‑1.1 ‑1.8
n
Administrative and support
activities
1.3 0.4 0.0 ‑0.4 0.3 3.7 6.4 5.3
g‑n Total services 4.6 4.0 3.6 4.2 3.0 3.9 6.1 4.0
c Manufacturing 9.2 7.2 8.3 8.4 9.2 8.4 9.1 6.2
Source: own calculations using Eurostat data.
box I.1: Data issues in measuring services activities
The closest item in the consumer prices index has been used for each service industry. When such an item is
unavailable, the index for all services has been used to deflate the turnover series, as follows. Retail trade is presented
in constant prices in the original series. For hotels and restaurants, postal activities, and transport services, the
corresponding consumer price indices for these industries have been used. Supporting activities for transportation
are deflated by the price index for all transport services. Information and communication and telecommunications
are deflated by the price index for communications. All other services industries are deflated by the consumer price
index for all services.

The business survey indicator used for services industries
is calculated as the difference between the percentages
of total answers to the survey that consider that demand
(turnover) for the firm’s services will increase in the next
quarter and the percentage that consider that it will
decrease. The indicator is compared with an indicator
for manufacturing. The indicator for manufacturing is
defined in the same way, although it applies to production
expectations for the next quarter. The results for all
Chapter I — The aftermath of the crisis — a long and uneven recovery(?)
services relative to manufacturing between April 1996 and
July 2011 are presented below. The balance for services is in
general more positive than the balance for manufacturing
until November 2009. Demand expectations declined
sharply in the second half of 2008. The decline continues
until March 2009 where the opinion balance became less
negative and in October 2009, the balances are positive
again and rose sharply until the first quarter of 2011 after
which they have decreased, cf. Figure I.15.
FIgURE I.15: Production and demand expectations: EU services and manufacturing industries
between 1996 and 2011 (monthly data)
50
40
30
20
10
0
-10
-20
-30
-40
Apr-96
Apr-97
Apr-98
Apr-99
Apr-00
Apr-01
Apr-02
Apr-03
Apr-04
Apr-05
Apr-06
Apr-07
Apr-08
Services
Manufacturing
Apr-09
Apr-10
Note: There is a break in the time series due to a change in the classification of economic activities. Data until April 2010 are collected
according to NACE Rev. 1.1. Data from May 2010 according to NACE Rev. 2. 28
Source: Directorate General for Economic and Financial Affairs business surveys.
28 See footnote 14 for how the change of classification from NACE Rev. 1.1 to NACE Rev. 2 has affected the time series for the variables.
Apr-11
31

EU industrial structure 2011 — Trends and Performance
I.3 Annex Figures
FIgURE I.16: Decline by country in manufacturing output from peak to trough (%) and number of
months of falling output in EU-27 during the latest crisis
40
35
30
25
20
15
10
32
5
0
EE
BG
SK
LU
FI
LV
SI
HU
IT
DK
ES
LT
SE
DE
EL
CZ
MT
IE
BE EU27 EU15
FR
PT
AT
PL
CY
Months
P-T
Note: Decline in output and number of months are both measured on the left axis. The calculations have been made for data between
January 2008 and December 2010.
Source: own calculations using Eurostat data.
FIgURE I.17: Recovery by country in manufacturing output from the trough to March 2011 (%) and
number of months of increasing output in EU-27 since the latest crisis
60
50
40
30
20
10
0
EE
SK
LV
BE
LT
DE
BG
CZ
LU
PL
FI
IE
HU
SE
AT
SI
RO
DK EU27 EU15
IT
NL
MT
FR
PT
UK
RO
ES
NL
Months
T-N
Note: Increase in output and number of months are both measured on the left axis. The calculations have been made for data between
January 2008 and March 2011. N in ‘T‑N’ stands for ‘now’ which in this case means latest available data.
Source: own calculations using Eurostat data.
CY
UK
EL

Chapter II
Changes in EU Industrial
structure
The objective of this chapter is to describe the industry
structure in the EU as a whole and also in individual EU member
states. The description is made in terms of value added and
employment for the different sectors. It includes descriptive
statistics covering the breakdown of the economies by sectors
in Section II.1. Section II.2 then introduces two different
taxonomies based on skills and technology. In Section II.3,
descriptive statistics on the size distribution of firms, in terms
of employees, in the various sectors are introduced. Section
II.4 contains a brief discussion of the increased tendency of
manufacturing firms also to supply services. The chapter ends
with an analysis of how developments in one sector spill over
to other sectors in the economy, Section II.5.
II.1 The shares of industries and
sectoral specialisation in the EU
The industrial structure of the economy is the result of
long‑term trends in sectoral growth where each sector’s share
of employment and value added is determined by productivity
growth, the structure of demand and international trade.
Chapter III analyses the growth of sectors from a long‑term
perspective and Chapter I focuses on the most recent
developments. This section outlines the distribution across
sectors of total value added in the EU. This approach reflects
the relative importance of the industries and provides a basis
for analysing the specialisation of Member States.
The sectors analysed in this report are determined by the
statistical nomenclatures used, by the different levels of
aggregation chosen for the analysis, and by the availability
of data. Analyses of industrial structure at a certain level of
aggregation imply that some sectors will be only partially,
or not at all, recognisable in this report, either because no
data are available at detailed level or because the statistical
classification does not reflect the reality of the sector. One
example is manufacture of computers, electronic and
optical products, for which some data are not available for
manufacturing of optical products and manufacturing of
computers separately. Other cases are economic activities
which encompass manufacturing and repair activities under
the same heading. Examples of these are building and
repairing of ships and boats and manufacturing of aircraft
and spacecraft. While NACE Rev. 2 brought a higher level of
disaggregation in certain sectors compared to NACE Rev. 1,
many economic activities cannot be split into detail. This
means that different trends and performances of sub‑sectors
are hidden behind larger aggregates.
ii11 structural change in the Eu
The EU industrial structure develops according to the
long‑term trend of an increased services sector at the expense
of the manufacturing sector. Market services have grown to
represent 50 % of the EU economy in 2009 from 46 % of EU
GDP in 1997. The share of non‑market services also increased
from 22 % in 1996 to reach 24 % in 2009. Construction, as
well as mining and quarrying, roughly remained stable
at 6 % and 1 % respectively. The shares of manufacturing
decreased from 20 % to 15 % between 1997 and 2009 while
the shares of agriculture dropped more moderately from
and 3 % to 2 %. Market services and manufacturing generally
evolved in opposite directions: the former increased its
overall share by 4 percentage points while the latter lost
symmetrically 5 percentage points, cf. Figure II.1.
35

EU industrial structure 2011 — Trends and Performance
FIgURE II.1: EU Structural change 1997-2009 (% of gDP)
60
50
40
30
20
10
0
36
Agriculture
forestry
and shing
Mining and
quarrying
Source: own calculation using Eurostat data.
Manufacturing
The overall EU trends observed in Figure II.1 hide large
variations among member states, with very different
patterns of industry structure. Luxembourg stands out as the
country with a very large market services sector and a very
small manufacturing sector. Cyprus, Latvia and the UK also
have large market services sectors. Conversely, the Czech
Republic, Hungary, Ireland and Romania have small market
services sectors but relatively large manufacturing sectors.
Electricity,
gas and
water supply
Construction
Market
services
2009
1997
Non-market
services
FIgURE II.2: Distribution of EU countries by gDP shares of manufacturing and market services in 2009
75
70
65
60
55
50
45
40
LU
CY
LV
GR
FR
UK
BE
EE
NL MT
ES
DK
EU27
PT SE
LT
PL
BG SI
AT
FI SK
HU
35
5 10 15 20 25
Source: own calculation using Eurostat data.
The latter are examples of countries that have received
considerable foreign direct investment in manufacturing in
the period under consideration. Hence, it is not necessarily
the case that there is any catch‑up pending in services in the
short‑term. In terms of future growth, it is likely that services
will increase in weight and presumably lower growth rates
because of the lower productivity growth of services relative
to manufacturing, cf. Figure II.2.
IT
RO
DE
IE
CZ

While there is some variety in the overall industrial
structure, common trends emerge. market services
shares have grown by an average of 38 percentage
points from 1997 to 2009 while manufacturing
and agricultural activities shares are diminishing
in almost all countries With the exception of Malta,
all countries have seen their share of market services
activities increase since 1997. The countries where
the gains in shares over time of market services were
the most spectacular were Bulgaria, Latvia, Lithuania,
and Luxembourg, where market services increased
by between 8.5 percentage points and 10 percentage
Chapter II — Changes in EU Industrial structure
points. In Latvia and Luxembourg, these gains were
coupled with large drops in shares of manufacturing
by between 7 and 10 percentage points. The countries
that have the lowest shares of market services in the
EU are catching up and have all seen robust expansion
in market services shares since 1997; increases
between 3 and 5.5 percentage points were recorded in
Czech Republic, Finland, Hungary and Romania. A few
countries, Romania, Slovakia and Spain, stand out as far as
the construction sector is concerned. In these countries,
the share of the construction sector is around 10 %, much
higher than the EU average of 6.3 %, cf. Table II.1.
TAbLE II.1: Share in gDP in 2009 and change in shares of gDP between 1997 and 2009 29
sectors
country
(y1‑y2)
agriculture,
fishing and
mining
manufacturing
Electricity,
gas and water
supply
construction market services
non‑market
services 29
change share change share change share change share change share change share
at (97‑07) ‑0.5 2.2 0.2 20.1 0.2 2.9 ‑0.9 7.1 2.3 47.3 ‑1.4 20.4
BE (97‑09) ‑1.0 0.8 ‑6.3 14.0 ‑0.8 2.2 0.5 5.4 4.5 52.2 3.1 25.4
Bg (97‑06) ‑16.8 11.5 0.2 18.6 ‑0.4 4.0 3.1 5.9 8.9 44.9 6.7 15.1
cy (97‑09) ‑1.7 2.6 ‑4.2 6.8 0.0 2.0 0.3 8.2 2.3 54.7 3.4 25.6
cZ (97‑09) ‑2.7 3.4 ‑3.7 23.6 1.8 5.7 ‑0.2 7.4 3.0 42.5 1.8 17.6
dE (97‑08) ‑0.4 1.2 0.2 22.7 0.3 2.7 ‑1.9 4.0 2.2 47.3 ‑0.4 22.2
dK (97‑09) ‑1.1 3.5 ‑3.8 13.2 ‑0.6 1.9 0.2 4.9 2.4 46.8 3.0 29.8
EE (97‑09) ‑3.0 3.9 ‑5.7 14.3 0.8 3.9 0.9 7.0 3.1 50.2 3.9 20.8
Es (97‑09) ‑2.6 2.8 ‑6.4 12.7 ‑0.3 2.5 3.7 10.8 3.5 48.2 2.1 23.0
Fi (97‑09) ‑1.3 3.1 ‑6.6 18.2 0.3 2.7 1.6 7.0 4.0 44.3 2.1 24.7
Fr (99‑09) ‑1.3 1.9 ‑5.5 10.6 ‑0.1 1.6 1.4 6.4 4.0 52.7 1.5 26.7
gr (00‑09) ‑3.6 3.5 ‑0.8 10.3 0.4 2.6 ‑2.6 4.5 2.1 52.8 4.6 26.3
hu (97‑09) ‑3.8 3.6 ‑1.5 21.3 ‑0.3 3.4 0.0 4.4 4.4 44.5 1.3 22.7
iE (97‑09) ‑4.5 1.5 ‑6.6 24.2 0.2 1.6 0.0 5.6 7.1 44.4 3.8 22.8
it (97‑09) ‑1.6 2.2 ‑5.6 16.1 0.1 2.3 1.2 6.3 4.3 51.0 1.5 22.1
lt (97‑09) ‑7.5 3.7 ‑2.2 16.4 ‑0.3 3.9 ‑1.1 6.4 10.3 48.6 0.8 21.1
lu (97‑09) ‑0.6 0.4 ‑6.7 6.5 ‑0.2 1.2 ‑0.9 5.3 9.0 69.9 ‑0.6 16.7
lv (97‑09) ‑1.5 3.8 ‑10.3 9.9 ‑1.3 3.6 2.4 6.6 8.6 54.1 2.1 22.0
mt (97‑09) ‑0.7 2.4 ‑6.6 13.3 0.0 2.1 ‑0.5 3.9 ‑1.5 47.5 9.4 30.9
nl (97‑09) ‑1.5 4.7 ‑3.7 12.6 0.7 2.3 0.7 6.0 0.2 48.5 3.5 25.9
pl (97‑05) ‑2.7 7.1 ‑1.3 18.5 0.5 3.6 ‑1.2 6.0 3.7 45.5 1.0 19.2
pt (97‑07) ‑2.1 3.0 ‑4.3 14.6 0.3 3.0 ‑0.2 6.8 4.6 48.4 1.8 24.2
rO (97‑08) ‑13.0 8.6 ‑3.4 22.4 ‑1.4 2.3 6.1 11.9 5.4 40.0 6.3 14.8
sE (97‑09) ‑0.6 2.4 ‑6.1 15.5 0.3 3.3 1.0 5.2 2.5 46.7 2.8 26.9
si (97‑09) ‑2.1 2.9 ‑6.3 19.6 0.8 3.2 1.2 7.9 4.8 45.3 1.7 21.2
sK (97‑09) ‑1.7 4.5 ‑3.4 19.6 1.5 5.5 2.2 9.5 0.2 43.5 1.2 17.4
uK (97‑05) ‑0.7 3.1 ‑7.3 13.0 0.1 2.2 0.7 5.8 5.8 53.3 1.3 22.6
Eu‑27 (97‑09) ‑1.3 2.4 ‑4.9 14.9 ‑0.2 2.4 0.7 6.3 3.8 49.9 1.9 24.1
Note: the time period covered varies with countries (as indicated in parentheses).
Source: own calculation using Eurostat data.
29 Non-market services are those supplied predominantly by the public sector: codes L to O of NACE Rev. 1.1 (public administration and
defence, education; health, social services) and household activities.
37

EU industrial structure 2011 — Trends and Performance
A narrower breakdown is provided below. 30 The
sectors are represented at the 2‑digit level of the NACE
classification. real estate, renting and business
activities stand out as the largest activity, reaching
about 23 % of the total EU economy in 2009 compared
to 20 % in 1997, cf. Figure II.3.
FIgURE II.3: EU industry shares in gDP in 1997 and 2007 %
25
20
15
10
5
0
Real estate, renting and business activities is not only
the largest sector, it is also the one that increased most,
by 3.4 %. In comparison, while manufacturing had a share
higher than ‘Real estate, renting and business activities’
in 1996, it is also the sector that was most affected by the
financial crisis. The manufacturing sector witnessed the
largest decline of 4.9 percentage points from 1996 to 2009.
These figures, however, have to be interpreted with care.
The period 1997‑2007 is also the period that witnessed
the accumulation of imbalances that caused the recession
30 A more detailed picture is provided by Table II.8 in the Appendix,
which presents the share of sectors in 1997 and 2009.
38
Agriculture, hunting and forestry
Fishing
Mining and quarrying
Manufacturing
Food products; beverages and tobacco
Textiles and textile products
Leather and leather products
Wood and wood products
Paper products; publishing and printing
Source: own calculation using Eurostat data.
Rened petroleum products
Chemicals, chemical products
Rubber and plastic products
Other non-metallic mineral products
Basic metals and fabricated metal products
Machinery and equipment n.e.c.
of 2008‑2010. Among these imbalances, the housing bubble
stands out as one of the main distortions recorded in that
period. Hence, the remarkable increase of the real estate
services and construction sectors can be directly attributed
to mispriced assets. 31 The inflation of these sectors was later
partially reversed during the recession; by mid‑2011 the
Electrical and optical equipment
Transport equipment
Manufacturing n.e.c.
Electricity, gas and water supply
Construction
Wholesale and retail trade
Hotels and restaurants
Transport, storage and communication
2009
1997
correction was still ongoing with the construction sector
still contracting. While the raise of the housing‑related
sectors can be attributed to growing imbalances, the
drop in the share of manufacturing is probably reflecting
a well‑understood long‑term trend explained by its
high productivity growth relative to services in general.
This is interesting because it means that we can rule
out trade specialization as the driving force behind the
31 This has been discussed in detail in chapter 1 in the European
Competitiveness Report 2010. Although anecdotical, figure 1.4 in
European Competitiveness Report 2011 is quite compelling about
the size of the distortions: it shows how the construction sector
in Spain ended up employing more workers than in Germany in
absolute terms.
Financial intermediation
Real estate, renting and business activities
Public administration and defence
Education
Health and social work
Other social & personal services
Activities of households

developments. This is confirmed by the poor relation
between the bubble (and growth of the construction
sector) and the behaviour of international market shares
of manufacturing. 32 In short, the developments reflect the
typical landscape of an economy with fast productivity
32 See section 1.3 in the European Competitiveness Report 2010.
Chapter II — Changes in EU Industrial structure
growth in manufacturing and increasing weight of services
with one or two anomalies like the real estate services and
construction due to the imbalances accumulated over the
period under consideration cf. Figure II.4. 33
FIgURE II.4: Change in the share of sectors in the EU in 1997-2009 (percentage points)
Real estate, renting and business activities
Health and social work
Construction
Financial intermediation
Education
Other social & personal services
Hotels and restaurants
Activities of households
Transport, storage and communication
Fishing
Leather and leather products
Rened petroleum products
Wood and wood products
Mining and quarrying
Manufacturing n.e.c.
Electricity, gas and water supply
Rubber and plastic products
Other non-metallic mineral products
Chemicals, chemical products
Machinery and equipment n.e.c.
Public administration and defence
Food products; beverages and tobacco
Textiles and textile products
Transport equipment
Basic metals and fabricated metal products
Paper products; publishing and printing
Wholesale and retail trade
Electrical and optical equipment
Agriculture, hunting and forestry
Manufacturing
-5 -4 -3 -2 -1 0 1 2 3 4
Source: own calculations using Eurostat data.
ii12 member states’ sectoral
specialisation
Sectoral specialisation is a concept which adds
a comparative dimension to the breakdown by shares that
was presented in the previous section. The breakdown
of industries by shares in each country is compared to
the average share in the EU and used as an indicator of
specialisation. The two indicators, shares and specialisation,
complement each other: a country can be specialised
in sectors that represent only a small share of the overall
economy, cf. Box II.1.
33 Figure II.11 in the Appendix breaks down manufacturing and
market services into further sectors.
39

EU industrial structure 2011 — Trends and Performance
40
box II.1: Indicator of a country’s sectoral specialisation
The indicator of a country’s sectoral specialisation compares the share of a given sector in one country with the
share of the same sector in the EU as a whole. A value of 1 for a sector indicates the same share for that sector in the
country and in the EU. Values above (below) 1 indicate specialisation (lack of specialisation) of the country in that
sector and, the higher the value of the indicator, the higher the country’s specialisation compared to the EU average.
The index is calculated, for country ‘i’ and industry ‘j’, as follows:
where VA is value added and EU refers to EU‑27.
When interpreting the coefficient there are at least three caveats.
1) Large countries mostly determine the sectoral profile of the EU, in which they are included. It is, therefore, less likely to
find significant differences between large countries and the EU as a whole. For the same reason it is more likely to find
a substantially different profile in small countries from that of the EU. This arithmetic property of the indicator affects the
value of the index but not the specialisation profile of the country. However, the 2009 edition of EU industrial structure
(See Figure II.7 p. 61) showed that the results are not substantially affected by the method of calculation since changing
the area of reference by excluding the country under analysis does not substantially alter those indicators. Nevertheless,
other factors, as well as the way the indicator is calculated, explain the fact that small countries tend to show a sectoral
profile different from the average. Large countries are in a naturally favourable position to initiate a larger number of
activities successfully. Conversely, the obvious constraints that prevent small countries from developing a large range
of economic activities lead these countries to specialise on the basis of, among other things, their own comparative
advantages, their degree of development, the availability of specific resources, historical reasons, geographical and
location advantages, and technical characteristics of the sectors (e.g. economies of scale).
2) The level of sectoral aggregation also affects the results, as aggregation may mask the level of specialisation or lack
of specialisation of a country in a given sector. This applies to the results presented in Section II.2, as the taxonomies
for which the indicator is calculated are the result of aggregating sectors as defined in the NACE Rev. 1 nomenclature.
3) Specialisation and size of the sector are not necessarily related. The fact that a country is specialised in a sector
does not necessarily imply that the share of this sector in the economy of the country is large.
degree of specialisation in a country
While the indicator of sectoral specialisation provides a value for each sector in a given country, the degree of
specialisation in a country is measured as the Euclidean distance between the country’s vector of specialisation and
the vector corresponding to the non‑specialisation hypothetical case of non‑specialisation in which the coefficient
of specialisation would take the value 1 for each sector. For country ‘i’ and ‘n’ sectors the coefficient that measures
the degree of specialisation is calculated as follows.

Looking at the overall specialisation of a country, the
countries with the most specialised industrial structures are,
FIgURE II.5: Ranking of countries by degree of specialisation
HU
BG
EE
BG
RO
LV
GR
PT
LU
LT
MT
SK
CZ
CY
IT
DK
NL
PL
DE
FI
ES
SI
BE
UK
SE
AT
FR
Chapter II — Changes in EU Industrial structure
presented in decreasing order, Hungary, Bulgaria, Estonia,
Ireland, Romania, Latvia and Greece, cf. Figure II.5.
0 2 4 6 8 10
Source: own calculations using Eurostat data.
The larger the country is, the higher is its potential for
diversification. The sectors that drive this high specialisation
can be deduced from Table II.2. The five countries most
diversified in the EU are Germany, France, the UK, Italy and
Spain. Interestingly, smaller countries like the Netherlands,
Belgium, Austria and Sweden also have diversified industrial
structures, cf. Figure II.6.
41

EU industrial structure 2011 — Trends and Performance
FIgURE II.6: Large economies are less dependent on a few sectors
8
7
6
5
4
3
2
1
0
0 500 1 000 1 500 2 000 2 500
42
LU
BG
GR
RO
LV
PT
EE HU
LT
MT IE
DK
CY
SK CZ
SI
FI
SE
AT
BE
NL
PL
Source: own calculations using Eurostat data.
As explained in Box II.1, being highly specialised in a sector
does not mean that the sector in question represents
a large share in the economy. A sector in which a country
is specialised represents, in proportion, more than in other
countries. In certain countries, sectoral indexes reach
very high values. The indices should be interpreted with
caution. As indicated in the headings below every country
abbreviation, data availability for the countries differs
substantially in some cases. The latest data available for
UK and Poland refer to 2005 and 2006 for Bulgaria. For the
countries where data is available for 2009, the recent crisis
may have affected the specialisation indices significantly
compared to 2008: manufacturing of refined petroleum
products illustrates this. The industry only accounted for 1.7 %
and 1.9 % of Hungarian GDP in 2008 and 2009 respectively.
The corresponding EU‑27 shares were 0.3 % and 0.2 %. Even
though the industry declined in absolute terms in Hungary,
the specialisation index increased from 5.5 to 8.5 since it
declined less than the whole economy while the opposite
occurred for the whole EU‑27.
ES
IT
UK
FR
The highest sectoral level of specialisation is in Hungary,
with a specialisation of 8.5 in refined petroleum products.
Another high level of sectoral specialisation is found in
Ireland with a specialisation of 6.0 in chemicals. Bulgaria
and Romania show high specialisation in agriculture. These
findings reflect the trend according to which the more
developed a country is, the less important the primary
sector becomes. For mining and quarrying, Bulgaria,
Denmark and the Netherlands are the most specialised.
The lowest specialisation in manufacturing can be found in
Cyprus, Greece, Latvia and Luxembourg, with specialisation
indices between 0.4 and 0.7. Luxembourg stands out as
highly specialised in financial intermediation. Looking
more closely at manufacturing sectors, a few facts are
worth highlighting. The Baltic countries Estonia, Latvia and
Lithuania are highly specialised in the wood industry with
specialisation indices between 3 and 6. Italy still has a very
high specialisation in leather, cf. Table II.2.
DE

TAbLE II.2: Sectoral specialisation indices 1997 and 2009
Chapter II — Changes in EU Industrial structure
at BE Bg cy cZ dE dK EE Es Fi Fr El hu
code sector 1997 2007 1997 2009 1998 2006 1997 2009 1997 2009 1997 2009 1997 2009 1997 2009 1997 2009 1997 2009 1999 2009 2000 2009 1997 2009
a agriculture, hunting and forestry 0.86 1.01 0.57 0.41 7.35 4.99 1.40 1.30 1.54 1.42 0.48 0.56 1.08 0.50 1.72 1.46 1.74 1.55 1.48 1.66 1.22 1.05 2.66 1.79 2.57 2.06
B Fishing 0.04 0.06 0.31 0.26 0.46 0.54 2.57 3.13 0.45 0.11 0.11 0.17 2.54 1.92 5.73 4.19 3.21 2.79 1.08 1.01 1.18 1.05 5.75 4.73 0.19 0.25
c mining and quarrying 0.43 0.53 0.19 0.15 2.38 3.30 0.28 0.46 2.08 1.52 0.34 0.39 1.55 3.46 1.83 1.76 0.44 0.25 0.35 0.51 0.21 0.20 0.60 0.54 0.48 0.34
d manufacturing 1.01 1.17 1.03 0.94 0.97 1.08 0.56 0.46 1.38 1.59 1.13 1.53 0.86 0.89 1.01 0.96 0.96 0.85 1.25 1.22 0.82 0.71 0.57 0.69 1.16 1.44
da Food products; beverages and 0.91 0.98 1.11 1.06 2.25 1.45 1.59 1.06 1.67 1.49 0.84 0.84 1.24 1.23 1.95 1.15 1.21 1.11 0.95 0.92 0.91 0.77 1.22 1.82 1.42 1.14
tobacco
dB textiles and textile products 0.84 0.78 1.14 1.05 2.59 4.81 1.14 0.33 1.45 1.24 0.53 0.63 0.47 0.32 2.28 1.94 1.16 0.79 0.56 0.46 0.75 0.61 1.62 1.76 1.48 0.72
dc leather and leather products 0.64 0.53 0.25 0.23 3.08 1.72 1.26 0.21 1.05 0.60 0.32 0.36 0.24 0.03 1.47 0.68 1.73 1.00 0.47 0.40 0.69 0.65 0.63 0.61 1.61 1.03
dd wood and wood products 2.17 2.37 0.64 0.70 0.89 0.96 1.54 1.61 1.86 2.62 1.05 0.95 1.10 0.88 4.61 5.56 1.01 0.76 3.21 2.08 0.64 0.56 0.67 0.46 1.08 0.85
dE paper products; publishing and 0.96 1.07 0.89 0.89 0.63 0.57 0.49 0.55 0.84 1.07 1.00 1.19 1.04 0.83 0.86 0.99 0.88 0.97 2.99 2.36 0.74 0.70 0.42 0.65 0.75 0.84
printing
dF refined petroleum products 1.24 0.80 1.90 2.69 5.52 3.41 0.41 0.02 1.38 0.21 0.53 0.54 0.13 0.62 0.09 2.23 1.53 1.01 0.83 1.77 1.13 0.66 2.07 3.41 6.58 8.45
dg chemicals, chemical products 0.58 0.87 1.98 1.72 0.67 0.68 0.26 0.27 0.98 0.69 1.15 1.49 0.90 1.17 0.71 0.46 0.87 0.87 0.77 0.96 0.81 0.73 0.39 0.37 1.17 1.26
dh rubber and plastic products 0.89 1.07 0.82 0.81 0.43 0.69 0.40 0.39 1.09 2.51 1.22 1.58 0.91 0.90 0.49 0.65 0.93 0.84 0.89 0.96 0.91 0.78 0.42 0.50 0.93 1.64
di Other non‑metallic mineral 1.47 1.47 1.16 1.29 0.59 1.87 1.23 1.59 2.21 2.04 1.02 1.03 0.88 0.73 1.17 1.22 1.51 1.36 0.81 0.93 0.72 0.76 1.06 0.82 1.09 1.19
products
dJ Basic metals and fabricated 1.24 1.47 1.12 1.02 0.79 1.32 0.33 0.41 1.99 1.62 1.11 1.58 0.70 0.64 0.54 0.74 0.96 0.99 1.07 1.13 0.90 0.78 0.43 0.57 0.78 0.91
metal products
dK machinery and equipment nec 1.05 1.45 0.58 0.54 0.74 0.78 0.13 0.11 1.38 1.57 1.53 2.21 1.23 1.10 0.35 0.41 0.58 0.54 1.44 1.57 0.68 0.61 0.19 0.18 0.79 0.94
dl Electrical and optical equipment 1.07 1.18 0.76 0.61 0.30 0.57 0.07 0.10 1.10 1.81 1.35 2.07 0.72 1.50 0.63 1.16 0.59 0.44 1.81 2.01 0.82 0.57 0.17 0.19 1.46 2.87
dm transport equipment 0.59 0.87 0.88 0.60 0.31 0.23 0.05 0.06 1.13 2.36 1.58 2.31 0.29 0.12 0.55 0.34 1.13 0.77 0.52 0.39 0.94 0.88 0.23 0.25 0.96 1.93
dn manufacturing nec 1.61 1.36 0.74 0.63 0.18 1.12 1.02 0.63 1.33 1.64 0.87 1.03 1.30 1.05 2.01 1.49 1.06 0.99 0.77 0.69 0.74 0.70 0.79 0.76 0.64 0.69
E Electricity, gas and water supply 1.01 1.32 1.15 0.91 2.19 1.84 0.76 0.83 1.47 2.35 0.88 1.10 0.95 0.78 1.18 1.61 1.03 1.02 0.91 1.11 0.82 0.68 1.16 1.09 1.39 1.41
F construction 1.42 1.11 0.88 0.86 0.87 0.94 1.42 1.30 1.34 1.17 1.06 0.64 0.85 0.78 1.09 1.10 1.27 1.71 0.97 1.11 0.91 1.02 1.25 0.71 0.79 0.70
g wholesale and retail trade 1.13 1.09 1.02 1.08 0.54 0.81 1.10 1.10 0.98 1.06 0.92 0.94 1.10 1.03 1.09 1.16 0.97 0.93 0.87 0.89 0.90 0.90 1.26 1.47 0.92 1.04
h hotels and restaurants 1.48 1.52 0.58 0.56 0.78 0.86 3.28 2.00 1.01 0.63 0.54 0.55 0.59 0.51 0.56 0.48 2.71 2.50 0.51 0.55 0.81 0.80 2.60 2.39 0.76 0.52
i transport, storage and
1.10 0.92 1.16 1.16 1.23 1.79 1.20 1.09 1.54 1.54 0.81 0.85 1.17 0.92 1.80 1.62 1.14 0.99 1.34 1.17 0.91 0.97 1.13 1.39 1.23 1.16
communication
J Financial intermediation 1.11 0.97 1.20 1.04 0.51 0.92 1.23 1.41 0.58 0.67 0.97 0.62 0.98 1.17 0.54 0.59 0.96 1.14 0.70 0.52 0.94 0.87 1.13 0.93 0.76 0.78
K real estate, renting and 0.74 0.83 1.02 1.06 0.84 0.70 0.82 0.90 0.60 0.62 1.13 1.12 0.85 0.89 0.90 0.92 0.68 0.73 0.81 0.94 1.20 1.24 0.72 0.62 0.76 0.82
business activities
l public administration and 0.97 0.92 0.99 1.16 0.87 1.10 1.30 1.56 0.76 0.87 0.94 0.86 0.98 1.02 0.77 1.17 1.92 1.00 0.76 0.81 1.16 1.18 1.31 1.46 1.13 1.35
defence
m Education 1.15 1.03 1.37 1.32 0.69 0.73 1.07 1.19 0.82 0.83 0.92 0.82 1.13 1.17 1.09 1.03 0.30 0.98 1.05 1.00 1.18 1.03 1.01 1.30 0.99 0.93
n health and social work 0.86 0.83 1.00 1.03 0.40 0.34 0.58 0.54 0.57 0.56 1.06 0.95 1.65 1.59 0.52 0.55 0.35 0.85 1.36 1.31 1.25 1.21 0.58 0.60 0.70 0.56
O Other social & personal services 1.11 1.00 0.63 0.67 0.38 0.55 1.06 0.94 0.80 0.78 1.27 1.13 1.14 1.14 0.79 0.83 0.76 0.97 1.02 1.00 0.84 0.91 1.03 1.07 1.20 1.15
p activities of households 0.08 0.07 0.48 0.32 0.00 0.00 0.96 2.02 0.03 0.04 0.65 0.61 0.28 0.31 0.10 0.06 2.14 1.52 0.10 0.19 1.06 1.12 1.30 1.68 0.00 0.00
Note: Specialisation index for refined petroleum products in Denmark are based on 2008 data.
Source: own calculations using Eurostat data.
43

EU industrial structure 2011 — Trends and Performance
TAbLE II.2 (continued): Sectoral specialisation indices 1997 and 2009
44
iE it lt lu lv mt nl pl pt rO sE si sK uK
code sector 1997 2009 1997 2009 1997 2009 1997 2009 2000 2009 1997 2009 1997 2009 1997 2005 1997 2007 1997 2008 1997 2009 1997 2009 1997 2009 1997 2005
a agriculture, hunting and forestry 1.77 0.56 1.13 1.09 3.96 2.06 0.31 0.19 1.84 2.00 0.96 1.14 1.25 1.06 2.43 2.50 1.58 1.24 6.95 4.30 0.95 1.09 1.54 1.53 1.96 2.46 0.49 0.48
B Fishing 3.87 1.34 1.31 1.48 0.47 1.25 0.00 0.00 4.37 1.77 2.24 3.86 0.84 0.45 0.35 0.29 3.63 4.11 0.08 0.16 0.33 0.39 0.13 0.21 0.04 0.11 0.56 0.43
c mining and quarrying 0.92 0.68 0.62 0.48 0.48 0.42 0.16 0.12 0.13 0.65 0.32 0.45 3.09 4.06 3.56 3.17 0.53 0.63 3.11 1.22 0.36 0.81 0.94 0.61 1.04 0.78 2.70 2.79
d manufacturing 1.56 1.63 1.10 1.09 0.94 1.10 0.66 0.43 0.70 0.67 1.01 0.90 0.82 0.85 1.00 1.07 0.95 0.85 1.31 1.36 1.09 1.05 1.31 1.32 1.16 1.32 1.03 0.75
da Food products; beverages and 2.23 2.16 0.92 0.98 2.24 2.06 0.51 0.35 1.67 1.22 1.21 0.97 1.23 1.51 1.55 1.60 1.02 0.95 3.41 3.03 0.78 0.71 1.27 0.86 1.13 0.92 1.14 0.94
tobacco
dB textiles and textile products 0.65 0.29 2.30 2.68 3.08 2.32 1.15 0.59 1.78 1.00 2.44 1.01 0.36 0.35 1.58 1.32 3.23 3.18 2.64 2.81 0.23 0.28 2.29 1.33 1.32 1.27 1.02 0.53
dc leather and leather products 0.28 0.24 3.38 3.96 1.73 0.31 0.00 0.00 0.17 0.13 1.71 0.08 0.20 0.18 1.43 0.86 4.82 3.70 2.29 2.82 0.16 0.00 2.78 1.80 1.45 1.71 0.55 0.22
dd wood and wood products 0.81 0.59 1.19 1.08 1.86 3.73 0.42 0.32 5.98 5.91 0.18 0.20 0.52 0.66 1.71 1.82 1.49 1.83 1.95 2.37 1.86 1.96 2.20 2.02 1.82 3.92 0.65 0.69
dE paper products; publishing and 2.60 2.46 0.72 0.81 0.69 0.86 0.47 0.40 0.64 0.74 0.75 1.18 1.16 1.14 0.73 0.95 0.93 0.93 0.44 0.81 1.70 1.59 1.30 1.19 1.08 1.01 1.36 1.15
printing
dF refined petroleum products 0.13 0.10 1.45 0.52 0.00 0.00 0.00 0.00 0.01 0.00 0.05 0.01 0.81 1.27 1.45 1.88 0.25 1.23 2.54 3.25 0.68 1.04 0.23 0.03 5.08 1.40 0.96 0.66
dg chemicals, chemical products 4.47 6.03 0.85 0.76 0.66 1.06 0.50 0.16 0.21 0.39 0.47 1.09 1.35 1.09 0.76 0.73 0.64 0.49 0.66 0.54 1.10 1.38 1.45 1.85 0.91 0.46 1.02 0.82
dh rubber and plastic products 0.67 0.58 1.05 0.89 0.28 1.20 2.23 1.09 0.25 0.43 1.25 0.90 0.60 0.63 1.02 1.44 0.65 0.77 0.58 1.22 0.74 0.69 1.56 2.00 0.94 1.66 1.16 0.91
di Other non‑metallic mineral 1.24 0.70 1.26 1.19 0.86 0.83 1.21 0.79 0.45 0.73 0.86 0.87 0.66 0.72 1.37 1.50 2.12 1.55 1.44 1.63 0.47 0.62 1.33 1.18 1.47 1.70 0.77 0.66
products
dJ Basic metals and fabricated 0.40 0.32 1.32 1.27 0.18 0.36 1.44 1.13 0.52 0.47 0.35 0.23 0.74 0.71 0.94 0.95 0.67 0.63 1.14 0.91 1.21 0.99 1.33 1.58 1.67 1.88 0.89 0.59
metal products
dK machinery and equipment nec 0.50 0.28 1.22 1.30 0.37 0.29 0.51 0.29 0.25 0.16 0.23 0.10 0.63 0.68 0.78 0.76 0.41 0.45 0.78 0.53 1.29 1.11 1.09 1.29 1.07 0.76 0.84 0.59
dl Electrical and optical equipment 2.55 2.56 0.89 0.96 0.51 0.50 0.23 0.23 0.21 0.39 2.02 1.96 0.56 0.45 0.66 0.71 0.61 0.62 0.63 0.81 1.31 1.42 1.30 1.27 0.82 1.64 1.13 0.64
dm transport equipment 0.27 0.23 0.65 0.62 0.25 0.58 0.04 0.06 0.23 0.25 0.59 0.70 0.40 0.34 0.62 0.90 0.59 0.45 0.75 1.63 1.32 0.91 0.43 0.86 0.55 1.58 1.05 0.76
dn manufacturing nec 0.77 0.58 1.37 1.46 0.98 2.62 0.33 0.15 0.94 0.94 3.39 2.47 1.46 1.62 1.45 1.48 1.04 1.08 1.82 1.46 0.73 0.70 1.88 1.45 0.92 1.40 1.01 0.85
E Electricity, gas and water supply 0.53 0.66 0.81 0.95 1.58 1.60 0.54 0.51 1.85 1.50 0.79 0.85 0.59 0.95 1.19 1.71 1.02 1.35 1.38 0.98 1.13 1.38 0.90 1.32 1.51 2.29 0.81 1.03
F construction 0.99 0.89 0.91 1.00 1.34 1.02 1.11 0.85 1.10 1.05 0.77 0.61 0.94 0.96 1.29 1.00 1.26 1.06 1.04 1.85 0.76 0.83 1.19 1.25 1.30 1.50 0.90 0.96
g wholesale and retail trade 0.89 0.85 1.14 0.98 1.37 1.52 0.91 1.02 1.42 1.36 1.26 0.97 1.13 1.10 1.63 1.65 1.18 1.20 0.81 1.05 0.89 1.03 1.04 1.12 1.20 1.43 0.98 1.01
h hotels and restaurants 0.87 0.75 1.32 1.32 0.64 0.47 0.92 0.50 0.40 0.46 2.54 1.46 0.71 0.58 0.38 0.42 1.41 1.65 1.04 0.65 0.49 0.50 0.89 0.78 0.60 0.46 1.01 0.98
i transport, storage and 0.86 0.80 1.03 1.07 1.39 2.02 1.47 1.28 2.03 1.67 1.47 1.21 1.04 0.93 0.91 1.03 0.96 1.02 1.25 1.63 1.17 1.07 1.04 1.06 1.55 1.04 1.12 1.02
communication
J Financial intermediation 1.29 1.70 0.81 0.93 0.28 0.39 3.93 4.49 1.00 1.06 1.00 0.95 1.22 1.29 0.76 0.78 1.22 1.39 0.64 0.46 1.11 0.77 0.89 0.87 0.73 0.70 1.20 1.48
K real estate, renting and business 0.61 0.75 0.94 1.01 0.49 0.62 0.90 0.96 0.67 0.86 0.62 0.80 1.00 0.89 0.58 0.63 0.68 0.68 0.53 0.55 0.95 0.94 0.72 0.79 0.67 0.65 0.98 1.07
activities
l public administration and 0.73 0.84 0.87 1.03 1.27 1.13 0.85 0.79 1.30 1.26 1.04 1.05 1.05 1.12 0.91 0.98 1.17 1.40 0.41 0.78 0.80 0.75 0.81 0.96 0.78 1.08 0.76 0.76
defence
m Education 0.96 1.11 1.07 0.94 1.03 1.20 0.85 0.75 1.04 1.04 1.13 1.10 0.90 0.95 0.93 0.99 1.33 1.30 0.40 0.76 1.10 1.09 1.09 1.07 0.68 0.64 1.09 1.06
n health and social work 0.96 1.08 0.85 0.81 0.57 0.54 0.72 0.66 0.52 0.44 0.73 0.88 1.18 1.30 0.54 0.52 0.80 0.86 0.23 0.43 1.55 1.54 0.80 0.75 0.72 0.44 1.00 1.01
O Other social & personal services 0.85 0.73 0.86 0.76 0.78 0.75 0.62 0.50 1.06 1.20 1.12 2.76 0.81 0.78 0.91 0.95 0.57 0.62 0.63 0.82 0.97 1.09 0.96 0.84 0.81 0.87 1.10 1.20
p activities of households 0.26 0.20 1.91 2.08 0.09 0.18 1.03 0.74 0.00 0.00 0.38 0.59 0.82 0.82 1.26 1.16 1.63 1.80 0.00 0.00 0.03 0.08 0.18 0.15 0.00 0.00 0.94 0.93
Source: own calculations using Eurostat data.

For countries as a whole, it should be noted that, in
principle, specialization is not necessarily a good or
bad thing per se. On one hand, specialization may
reflect a natural focus on what the country does better
relative to trade partners (comparative advantage), and
hence a gain of overall productivity. On the other hand,
diversification will always render a society more resilient
to external shocks; a downturn in a specific sector can be
compensated by other sectors still doing well and feeding
public finances that eventually help cushion the negative
impact of the shock (e.g., paying unemployment insurance).
Nevertheless, diversification can also be seen as reflecting
a society with a wider choice for its citizens; a high degree
of diversification is very likely reflecting a strong and
diverse human capital base that makes it possible to have
from artists to engineers producing from haut couture
to satellites. Given that by nature larger countries tend to
be more diversified, countries below the line in figure II.6
can be seen as reaping the benefits from having a more
diversified economy than the average country given its size.
In that reading, Belgium is a highly diversified country for
its size whereas Italy, despite its large size, is less diversified
and, in principle, more vulnerable to sectoral shocks or
to competition from emerging economies due to high
specialisation in low skill industries such as textiles and
leather products.
box II.2: Labour skills taxonomy
Chapter II — Changes in EU Industrial structure
The taxonomy of labour skills is presented and discussed in Chapter II of O’Mahony and van Ark (2003),
EU productivity and competitiveness — An industry perspective, European Commission. A measure of educational
attainment is the metric that has been used to reflect skill intensity. The sectors from the NACE Rev1. classification
were broken down in the following way:
II.2 Skill and technology
specialization
The sectors analysed are classified according to the statistical
nomenclature (NACE Rev. 2) presenting data on economic
activities. It is sometimes useful to use other ways to classify
sectors according to economic and technological criteria.
Such classification can be used to illustrate similarities
and differences between countries and sectors. Industry
taxonomies are used for this purpose to group industries
that have common characteristics. Once the taxonomies
are applied to EU member states, it is possible to compare
patterns across countries. The focus below is on two different
taxonomies: one on skills and one on technology. It is not
only the quantity of these inputs that matters for sectoral
performance but also their qualities. As in the previous
section, two different types of indicators are available:
a breakdown by value added share and specialisation.
ii21 changes in skills’ specialization
The types of education and training that contribute to
making a sector competitive can be very sector‑specific.
Similarly, different levels of skills are needed across sectors.
The measure of skill intensity, represented by the levels34 of education attainment that dominate in a sector, reflects
this heterogeneity. The sectors in which people reached
a similar level of educational attainment are classified
according to different levels of skills. This led to four
different categories, cf. Box II.2.
low skill: A Agriculture, hunting and forestry, B Fishing, C Mining and quarrying, DA15 Manufacture of food
products and beverages, DA16 Manufacture of tobacco products, DB Manufacture of textiles and textile products,
DC Manufacture of leather and leather products, DH Manufacture of rubber and plastic products, DI Manufacture
of other non‑metallic mineral products, DJ27 Manufacture of basic metals, DM34 Manufacture of motor vehicles,
trailers and semi‑trailers, DN36 Manufacture of furniture; manufacturing n.e.c., DN37 Recycling, H Hotels and
restaurants, O Other community, social, personal service activities.
34 A common measure is the one provided by International
Standard classification ISCED. The classification can be found on:
http://www.uis.unesco.org/Pages/default.aspx
45

EU industrial structure 2011 — Trends and Performance
Belgium, Cyprus, France, Luxembourg and the United
Kingdom have the highest shares of high skilled labour,
above the EU‑25 average of 43 %, in the economy in 2007.
Those countries also display the highest specialisations,
above 1, in high skill sectors in 2007. The Czech Republic,
Greece, Malta, Poland, Slovakia and Spain have the highest
shares of low skilled labour, well above the EU‑25 average
of 21 %, in the economy in 2007. They also display the highest
specialisation indexes in low labour skill sectors. There were
very few significant structural changes from 1997 to 2007.
The most remarkable move towards high skilled labour
46
low intermediate skill: DD Manufacture of wood and wood products, DE Manufacture of pulp, paper and
paper products; publishing and printing, DJ28 Manufacture of fabricated metal products, except machinery and
equipment, DK Manufacture of machinery and equipment n.e.c., DL31 Manufacture of electrical machinery and
apparatus n.e.c., F Construction, G Wholesale and retail trade; repair of motor vehicles, motorcycles and personal
and household goods, I60 Land transport; transport via pipelines, I61 Water transport.
high intermediate skill: DL33 Manufacture of medical, precision and optical instruments, watches and clocks,
DM35 Manufacture of other transport equipment, E Electricity, gas and water supply, I62 Air transport, I63 Supporting
and auxiliary transport activities; activities of travel agencies, I64 Post and telecommunications, K71Renting of
machinery and equipment without operator and of personal and household goods, N Health and social work.
high skill: DF Manufacture of coke, refined petroleum products and nuclear fuel, DG Manufacture of chemicals,
chemical products and man‑made fibres, DL30 Manufacture of office machinery and computers, DL32 Manufacture
of radio, television and communication equipment and apparatus, J Financial intermediation, K70 Real estate
activities, K72 Computer and related activities, K73 Research and development, K74 Other business activities, L Public
administration and defence; compulsory social security, M Education.
To obtain a sufficiently detailed sectoral skill intensity data set, the Eurostat and EU‑KLEMS databases were
combined.
TAbLE II.3: Share of industry by labour skill in 1997 and 2007 (%)
industries can be observed in Latvia: both the shares
of these industries and the specialisation indexes have
significantly increased. The low‑intermediary skill sectors in
Latvia have also seen their shares and specialisation index
improve. The change has taken place at the expense of the
high‑intermediary skill and low skill sectors. Lithuania, the
neighbour country, has not made as impressive progress
towards high skill sectors, but the size of low skill sectors in
the economy has shrunk considerably. Malta and Portugal
both increased their shares and specialisation in high and
intermediary‑high skill sectors, cf. Tables II.3 and II.4.
hs his lis ls
1997 2007 1997 2007 1997 2007 1997 2007
austria 34.6 35.9 13.5 14.4 32.6 31.0 19.3 18.7
Belgium 44.8 46.1 15.5 16.3 24.9 25.5 14.8 12.1
cyprus 36.5 43.2 12.7 12.4 26.4 26.5 24.5 17.9
czech republic 26.8 29.0 14.4 15.0 33.0 33.5 25.7 22.5
denmark 36.1 37.6 18.0 17.9 28.8 28.4 17.1 16.2
Estonia 32.2 34.2 14.6 14.0 31.0 35.0 22.2 16.7
Finland 34.0 36.7 18.2 17.8 31.9 31.1 16.0 14.4
France 44.8 47.3 15.5 14.1 24.0 25.1 15.8 13.5
germany 40.1 41.2 15.4 16.6 27.9 25.4 16.7 16.8
greece 34.8 35.0 11.8 13.2 25.9 29.6 27.4 22.2
hungary 36.3 40.6 13.3 13.2 26.3 26.8 24.2 19.5
>>>

Chapter II — Changes in EU Industrial structure
hs his lis ls
1997 2007 1997 2007 1997 2007 1997 2007
ireland 39.5 42.6 12.8 14.9 26.4 28.2 21.2 14.3
italy 37.0 40.7 11.9 12.7 30.4 29.4 20.7 17.2
latvia 27.2 33.8 17.3 13.1 33.7 37.9 21.8 15.3
lithuania 26.7 28.3 13.4 14.1 32.6 38.6 27.3 19.0
luxembourg n.a. 55.5 n.a 13.3 n.a 21.1 n.a 10.1
malta 32.0 37.6 13.7 16.1 28.7 21.4 25.6 24.9
netherlands 40.1 41.5 14.9 16.8 26.9 25.9 18.1 15.7
poland 28.4 30.8 11.1 13.0 35.6 34.6 24.9 21.7
portugal 35.9 39.3 12.8 15.9 28.9 25.9 22.4 18.9
slovakia 29.2 29.0 14.5 13.8 35.6 36.7 20.6 20.5
slovenia 33.7 37.7 12.5 13.6 31.3 30.7 22.5 18.1
spain 32.6 34.1 13.0 12.7 27.7 31.5 26.8 21.7
sweden 37.5 37.1 19.3 19.9 28.3 28.7 14.9 14.3
united Kingdom 37.8 43.1 15.5 15.6 27.5 25.4 19.3 15.9
Eu‑25 41.2 42.6 14.9 15.2 26.6 26.5 17.2 15.7
Note: Bulgaria and Romania not available for lack of data.
Source: own calculations using EU KLEMS and Eurostat data.
TAbLE II.4: Country specialisation by labour skill in 1997 and 2007
hs his lis ls
1997 2007 1997 2007 1997 2007 1997 2007
austria 0.84 0.84 0.90 0.94 1.23 1.17 1.12 1.19
Belgium 1.09 1.08 1.03 1.07 0.94 0.96 0.86 0.77
cyprus 0.88 1.01 0.85 0.81 0.99 1.00 1.42 1.14
czech republic 0.65 0.68 0.97 0.99 1.24 1.26 1.50 1.44
denmark 0.88 0.88 1.20 1.18 1.08 1.07 1.00 1.03
Estonia 0.78 0.80 0.98 0.92 1.16 1.32 1.29 1.07
Finland 0.82 0.86 1.22 1.17 1.20 1.17 0.93 0.92
France 1.09 1.11 1.04 0.92 0.90 0.95 0.92 0.86
germany 0.97 0.97 1.03 1.09 1.05 0.96 0.97 1.07
greece 0.84 0.82 0.79 0.87 0.97 1.12 1.60 1.41
hungary 0.88 0.95 0.89 0.87 0.99 1.01 1.41 1.24
ireland 0.96 1.00 0.86 0.98 0.99 1.06 1.24 0.91
italy 0.90 0.96 0.80 0.83 1.14 1.11 1.21 1.10
latvia 0.66 0.79 1.16 0.86 1.26 1.43 1.27 0.98
lithuania 0.65 0.66 0.90 0.92 1.22 1.46 1.59 1.21
luxembourg n.a. 1.30 n.a. 0.87 n.a. 0.80 n.a. 0.64
malta 0.78 0.88 0.92 1.06 1.08 0.81 1.49 1.59
netherlands 0.97 0.97 0.99 1.11 1.01 0.98 1.05 1.00
poland 0.69 0.72 0.74 0.85 1.33 1.30 1.45 1.38
portugal 0.87 0.92 0.86 1.05 1.08 0.98 1.30 1.21
slovakia 0.71 0.68 0.97 0.91 1.34 1.38 1.20 1.31
slovenia 0.82 0.88 0.84 0.89 1.17 1.16 1.31 1.15
spain 0.79 0.80 0.87 0.84 1.04 1.19 1.56 1.38
sweden 0.91 0.87 1.29 1.31 1.06 1.08 0.87 0.91
united
Kingdom
0.92 1.01 1.04 1.03 1.03 0.96 1.12 1.01
Note: Bulgaria and Romania not available for lack of data.
Source: own calculations using EU KLEMS and Eurostat data.
47

EU industrial structure 2011 — Trends and Performance
ii22 changes in technology specialization
The technology taxonomy provides insight concerning
the technology shares and specialisation across EU
48
box II.3: Technology taxonomy
manufacturing sectors. The sectors in which the R&D
intensity reached similar levels were regrouped. This led to
four different categories, cf. Box II.3.
The OECD (1997) classification of industries based on technological intensity was used as a reference. According to
this classification, R&D intensity, expenditures on R&D relative to value added, is the main criterion for evaluating
the technological content of an industry. As a result, manufacturing industries (following NACE rev. 1) are broken
down in four groups.
low tech: DA Manufacture of food products, beverages and tobacco, DB Manufacture of textiles and textile
products, DC Manufacture of leather and leather products, DD Manufacture of wood and wood products, DE
Manufacture of pulp, paper and paper products; publishing and printing.
low intermediate tech: DF Manufacture of coke, refined petroleum products and nuclear fuel, DH251 Manufacture
of rubber products, DH252 Manufacture of plastic products, DI Manufacture of other non‑metallic mineral products,
DJ27 Manufacture of basic metals, DJ28 Manufacture of fabricated metal products, except machinery and
equipment, DM351 Building and repairing of ships and boats, DN Manufacturing n.e.c.
high intermediate tech: DG241Manufacture of basic chemicals, DG242 Manufacture of pesticides and other
agro‑chemical products, DG247 Manufacture of man‑made fibres, DG243 Manufacture of paints, varnishes
and similar coatings, printing ink and mastics, DG245 Manufacture of soap and detergents, cleaning and
polishing preparations, perfumes and toilet preparations, DG246 Manufacture of other chemical products,
DK291 Manufacture of machinery for the production and use of mechanical power, except aircraft, vehicle and
cycle engines, DK293 Manufacture of agricultural and forestry machinery, DK294 Manufacture of machine‑tools,
DK295 Manufacture of other special purpose machinery, DK292 Manufacture of other general purpose machinery,
DL31 Manufacture of electrical machinery and apparatus n.e.c., DK297 Manufacture of domestic appliances
n.e.c., DM352 Manufacture of railway and tramway locomotives and rolling stock, DM34 Manufacture of motor
vehicles, trailers and semi‑trailers, DM354 Manufacture of motorcycles and bicycles, DM355 Manufacture of other
transport equipment n.e.c., DL33 Manufacture of medical, precision and optical instruments, watches and clocks,
DK296 Manufacture of weapons and ammunition.
high tech: DG244 Manufacture of pharmaceuticals, medicinal chemicals and botanical products, DL30 Manufacture
of office machinery and computers, DL32 Manufacture of radio, television and communication equipment and
apparatus, DM353 Manufacture of aircraft and spacecraft.
As with all indicators, interpretations should be cautious.
The base of the calculation of the indicators is the
manufacturing aggregates in all countries, so some
countries with a relatively small manufacturing base
can obtain high values in a certain category of skill and
technology. The overall EU‑25 is characterised by high
shares in the medium low technology and medium high
technology sectors. Those represent almost two thirds
of the EU‑25 in 2007. Finland, Hungary, Ireland, Malta,
Sweden, and the United Kingdom have had the highest
shares of high technology sectors, above 13 %, in 2007.
Those are also the countries with the highest specialisation
indices, above 1.3, in high technology sectors in 2007.
Cyprus, Estonia, Greece, Latvia, Lithuania and Portugal
have the highest shares of low technology, above 40 %,
in 2007 and also have the highest specialisation indexes
in low technology sectors, above 1.6. There were very few
significant structural changes from 1997 to 2007. With the
exception of Portugal, all the countries with high shares
and specialisation in low technology are moving up the

technology scale. They are less and less specialised in
low technology industries. Latvia’s low technology sector
share in the economy decreased from 69 % to 54 %, Cyprus
from 58 % to 45 %, Lithuania from 59 % to 44 % and Greece
and Estonia from 55 % to 43 % and 42 % respectively. On
the other side of the spectrum, Finland has reinforced
its high technology specialisation. Finland, which was
still behind Sweden in Ireland in 1997 in terms of overall
share of high technology sectors, has the highest share
TAbLE II.5: Share of industry by technology categories in 1997 and 2007 (%)
Chapter II — Changes in EU Industrial structure
of high technology industries in 2007. High technology
manufacturing industries represented more than 20 %
of Finish manufacturing. The importance of Nokia in
the Finnish economy explains a large part of this. The
relationship between technology and skill intensities is
weak for some countries. Cyprus, which exhibited large
shares and large specialisation in high skill sectors according
to the two previous tables, is specialised in low technology
and medium‑technology sectors, cf. Tables II.5 and II.6.
ht mht mlt lt
1997 2007 1997 2007 1997 2007 1997 2007
austria 8.1 6.0 27.0 33.8 35.1 34.7 29.8 25.5
Belgium 8.9 12.1 33.7 28.6 29.3 33.4 28.1 26.0
cyprus 1.6 3.1 8.5 10.3 32.0 41.4 57.9 45.3
czech republic 6.6 4.9 27.6 37.3 36.6 36.5 29.2 21.4
denmark 9.8 9.3 27.6 32.5 28.2 28.9 34.4 29.4
Estonia 5.2 3.9 17.0 18.4 23.0 35.8 54.8 41.9
Finland 12.5 20.7 24.8 24.6 23.4 26.2 39.3 28.5
France 11.1 10.6 29.2 29.6 30.2 32.7 29.5 27.0
germany 9.8 8.3 40.6 49.7 28.0 25.2 21.6 16.8
greece 3.3 4.9 12.8 11.9 29.2 40.2 54.6 43.0
hungary 9.0 13.0 29.4 39.8 29.5 27.2 32.1 20.0
ireland 18.0 18.8 35.1 37.0 11.1 9.5 35.8 34.7
italy 6.5 5.6 28.4 30.0 32.9 36.3 32.2 28.2
latvia 4.5 3.0 11.0 12.0 16.2 31.2 68.3 53.8
lithuania 6.1 2.2 13.2 18.1 22.4 36.2 58.3 43.5
luxembourg 0.6 1.1 19.7 16.6 54.1 60.6 25.7 21.6
malta 11.0 14.4 24.8 31.1 28.7 26.9 35.4 27.6
netherlands 7.7 4.6 28.8 31.3 28.7 31.0 34.8 33.1
poland 4.2 3.8 24.3 26.9 33.0 35.5 38.5 33.9
portugal 5.6 2.3 18.8 17.1 28.2 33.0 47.4 47.5
slovakia 4.8 6.0 25.4 27.7 39.1 40.6 30.7 25.7
slovenia 9.4 7.7 25.7 34.5 29.5 34.1 35.4 23.7
spain 6.0 4.7 28.0 28.6 33.3 38.3 32.8 28.4
sweden 15.0 14.7 33.6 34.5 23.6 26.2 27.8 24.6
united Kingdom 12.0 13.2 29.3 27.6 26.2 26.6 32.4 32.6
Eu‑25 8.5 9.5 32.2 35.7 30.5 29.6 28.8 25.2
Note: Bulgaria and Romania not available for lack of data.
Source: own calculations using EU KLEMS and Eurostat data.
TAbLE II.6: Country specialisation by technology categories in 1997 and 2007
ht mht mlt lt
1997 2007 1997 2007 1997 2007 1997 2007
austria 1.0 0.6 0.8 0.9 1.1 1.2 1.0 1.0
Belgium 1.0 1.3 1.0 0.8 1.0 1.1 1.0 1.0
cyprus 0.2 0.3 0.3 0.3 1.0 1.4 2.0 1.8
czech republic 0.8 0.5 0.9 1.0 1.2 1.2 1.0 0.8
denmark 1.2 1.0 0.9 0.9 0.9 1.0 1.2 1.2
>>>
49

EU industrial structure 2011 — Trends and Performance
50
ht mht mlt lt
1997 2007 1997 2007 1997 2007 1997 2007
Estonia 0.6 0.4 0.5 0.5 0.8 1.2 1.9 1.7
Finland 1.5 2.2 0.8 0.7 0.8 0.9 1.4 1.1
France 1.3 1.1 0.9 0.8 1.0 1.1 1.0 1.1
germany 1.2 0.9 1.3 1.4 0.9 0.9 0.8 0.7
greece 0.4 0.5 0.4 0.3 1.0 1.4 1.9 1.7
hungary 1.1 1.4 0.9 1.1 1.0 0.9 1.1 0.8
ireland 2.1 2.0 1.1 1.0 0.4 0.3 1.2 1.4
italy 0.8 0.6 0.9 0.8 1.1 1.2 1.1 1.1
latvia 0.5 0.3 0.3 0.3 0.5 1.1 2.4 2.1
lithuania 0.7 0.2 0.4 0.5 0.7 1.2 2.0 1.7
luxembourg 0.1 0.1 0.6 0.5 1.8 2.0 0.9 0.9
malta 1.3 1.5 0.8 0.9 0.9 0.9 1.2 1.1
netherlands 0.9 0.5 0.9 0.9 0.9 1.0 1.2 1.3
poland 0.5 0.4 0.8 0.8 1.1 1.2 1.3 1.3
portugal 0.7 0.2 0.6 0.5 0.9 1.1 1.6 1.9
slovakia 0.6 0.6 0.8 0.8 1.3 1.4 1.1 1.0
slovenia 1.1 0.8 0.8 1.0 1.0 1.2 1.2 0.9
spain 0.7 0.5 0.9 0.8 1.1 1.3 1.1 1.1
sweden 1.8 1.5 1.0 1.0 0.8 0.9 1.0 1.0
united Kingdom 1.4 1.4 0.9 0.8 0.9 0.9 1.1 1.3
Note: Bulgaria and Romania not available for lack of data.
Source: own calculations using EU KLEMS and Eurostat data.
II.3 Size distribution of enterprises
The distribution of economic activity according to the size of the
enterprises provides a measure of the degree of concentration
and of the share of large and small enterprises in the economy.
This is of interest in understanding sectoral performance, in
analysing competitiveness, and for policy. The distribution
reflects certain characteristics of sectors and, simultaneously,
influences performance and competitiveness. Sectoral
technology (e.g. economies of scale) and market size are some
of the factors explaining the enterprise‑size structure of the
sector, which, in turn, determines market power and sectoral
performance and competitiveness. It is clear that the resilience or
vulnerability of sectors and enterprises to certain market shocks
is affected by the size of enterprises, which also plays a crucial
role in innovation and the development of new activities and
products. For these reasons, it is important to bear in mind the
size of enterprises in the sectoral analysis, and to incorporate it
into formulation of industrial policy.
It is often argued that small and medium‑sized enterprises
(SMEs) constitute the backbone of the EU economy. However,
the share of SMEs varies significantly among industries. The
figure below presents, in a decreasing order, the sectors
where large enterprises dominate: large enterprises are those
with 250 or more employees. The units underlying these
distributions are enterprises. The concentration of value added
in large enterprises that characterises some of the sectors does
not necessarily imply economies of scale since enterprises, and
more particularly the largest ones, may own several small plants.
Large enterprises represent more than 80 % of value added
in the industries producing tobacco, the communications
sector, mineral oil refining and nuclear fuel, motor vehicles,
air transport and other transport equipment. The first
impression is that manufacturing sectors are generally formed
by larger enterprises than services sectors. Indeed, 55 %
on average of enterprises of the manufacturing sector are
above 250 employees against 36 % on average in the services
sectors. The sectors with more than 80 % of SMEs are real estate
activities, recycling and construction. But, contrary to common
belief that manufacturing enterprises are supposed to be large,
decomposition of firm size distribution by sector reveals a more
nuanced picture. Many manufacturing sectors are dominated
by small firms, especially the industries producing leather and
footwear, fabricated metal products, wood products, textiles,
clothing, and furniture where between 72 % and 79 % of the
firms have fewer than 250 employees, cf. Figure II.7. 35
35 According to the official EU definition of an SME, the number of
employees is not the only criterion that matters. The definition also
takes into consideration thresholds related to turnovers of balance
sheet totals. Size distribution according to employment bands
rather than turnover or balance sheet total was favoured because
for data availability reasons.

ox II.4: SME definition
FIgURE II.7: Distribution of value added by enterprise size in 2007 (%)
Tobacco
Communications
Mineral oil rening and nuclear fuel
Motor vehicles
Air transport
Other transport equipment
Electricity, gas and water supply
Radio and TV equipment; electronic components
Basic metals
Chemicals
Oce machinery
Electrical machinery
Pulp, paper and paper products
Research and development
Supporting transport activities
Food and drink
Machinery and equipment n.e.c.
Scientic and other instruments
Non-metallic mineral products
Retail trade
Rubber and plastics
Computer and related activities
Inland transport
Printing and publishing
Water transport
Other business activities
Furniture; other manufacturing
Clothing
Textiles
Renting of machinery and equipment
Hotels and restaurants
Wood and wood products
Wholesale trade
Fabricated metal products
Sale and repair of motor vehicles
Leather and footwear
Construction
Recycling
Real estate activities
MANUFACTURING
SERVICES
TOTAL ECONOMY
Source: own calculations using Eurostat data.
II.4 Services output of
manufacturing
An increasing number of manufacturing firms offer services
along with their traditional physical goods. This tendency
is coined ‘convergence process’ in the literature. 36 By
offering complementary services manufacturing, firms
can differentiate their products from the competitors’ and
reduce price elasticities for their goods. Complementary
services may also be a way to increase the qualities of the
36 European Commission, DG Enterprise and Industries (2011)
forthcoming. European Competitiveness Report 2011.
Chapter II — Changes in EU Industrial structure
Enterprises qualify as SMEs if they meet certain employee ceilings (10, 50, and 250 employees) and one of the two
financial ceilings (turnover or balance sheets).
Eurostat currently collects data regarding the three employee ceilings but not data concerning the financial ceilings.
1–9
10–19
20–49
50–249 250 or more
0 10 20 30 40 50 60 70 80 90 100 110
goods and build long term relationship with customers
which also might reduce the price elasticities the firms are
facing. Opening up additional sources of revenue could be
another motive. 37
Services as shares of total manufacturing output increased
in all but three EU countries between 1995 and 2005. Largest
shares are found in the Finnish and Dutch manufacturing
industries where services constitute around 8 % of total
output, cf. Figure II. 8.
37 Ibid.
51

EU industrial structure 2011 — Trends and Performance
FIgURE II.8: Services as shares of manufacturing output in 1995 and 2005 (%)
9
8
7
6
5
4
3
2
1
0
52
2005
1995
FR
PO
CZ
GR
EE
SI
HU
DK
PL
SK
ES
Note: Wholesale and retail trade are excluded. Data for France only includes services products CPA 75 to 92. The values for all service
products include CPA 50 to 95 for EU Member States and NAICS 42 to 92 for the US. The values for services excluding wholesale and retail
trade cover CPA 55 to 95 for EU Member States and NAICS 48 to 92 for the US. Data for France covers only service products CPA 72 to 95.
Source: European Commission, DG Enterprise and Industries (2011), forthcoming European Competitiveness Report 2011. Author’s
calculations using Eurostat data.
II.5 Inter-sectoral spillovers —
a case study
The data presented in the previous chapter showed how the
crisis spread to all sectors of the economy. It also provided
evidence on the extent of the recovery for the sectors. While
some sectors already exhibit strong growth rates at the
beginning of 2010, others lag behind. The fact that some
sectors are affected early in the business cycle and that the
development in some sectors lags behind implies that there
are interlinkages between some sectors which give rise to
joint movement of production and employment. Previous
editions of the EU industrial structure have examined these
interlinkages. 38 By using output multipliers it was shown how
an increase in demand for a sector was translated into that
sector’s demand for intermediate goods from other sectors.
A case study is provided below which provides more
insight into these relationships. The case study provides
analysis of how shocks originating in the German motor
vehicles industry impact on productivity and employment
38 European Commission, DG Enterprise and Industries (2009), EU
Industrial Structure 2009. Performance and competitiveness.
BE
IT
LI
DE
IE
AT
in four other German manufacturing industries: basic
metals, fabricated metal products, rubber and plastics, and
electrical equipment. Some words on the choice of industry
for the analysis are in order. Lack of data did not allow
for analysis of the whole EU‑27 manufacturing industry.
The motor vehicle industry was chosen since it is one of
the most important industries in the EU. The four other
industries were chosen on the basis of German input‑output
tables which indicated that these industries are the most
affected by increase in demand for motor vehicles.
The case study is undertaken with econometric analyses. 39
The relationships between industries are analysed with
vector autoregressive (VAR) models. The analyses are
conducted within an empirical framework inspired by
the works of Blanchard & Quah (1989) and Galí (1999)
who analysed the importance of technology and
non‑technology shocks for aggregate fluctuations in
productivity and employment. There is no consistent
39 The analyses are carried out with monthly data on production,
employment and hours worked for the period January 1990 to
August 2009. All series are indices and collected from Eurostat’s
short term business statistics database. Productivity is calculated
as production per hours worked.
UK
SE
LU
NL
FI

definition of shocks. Shocks, or disturbances, are often
defined as significant changes in variables from underlying
trends. The magnitude of changes is in general determined
using measures of dispersion such as standard deviations.
Shocks could also be defined as unexpected events beyond
the control of industries or the entity in question. See for
example the discussion in Varangis et al. (2004).
Four two‑industry VAR‑models were estimated, consisting
of four variables: labour productivity and employment for
the motor vehicles industry and for one of the other four
industries respectively. 40
Impulse response functions were calculated in order to see
the responses of technology and non‑technology shocks
40 The models are estimated in first differences of the variables since
unit root tests indicated that they were non-stationary. See http://
ec.europa.eu/enterprise/newsroom/cf/_getdocument.cfm?doc_
id=6003 for a detailed description of the methodology and results.
Chapter II — Changes in EU Industrial structure
on employment and productivity growth. The impulse
response functions show how, for example, employment
in the rubber and plastics industries responds to
a one‑percentage technology shock in the motor vehicles
industry. The responses are presented for a time period of
four years (48) months. The responses are shown together
with 90 percent confidence intervals.
The analyses show that a one‑percentage technology shock
originating in the motor vehicles industry has significant
positive and permanent effects on employment in the
rubber and plastics industry, which increases by some 2.5 %.
Productivity in the rubber and plastics industry increases
permanently by some 1.5 % after a technology shock in the
motor vehicles industry, cf. Figure II. 9.
FIgURE II.9: A technology shock in the motor vehicle industry has permanent effects on employment
and productivity in rubber and plastics
Employment productivity
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
-0.5
-1.0
lower
upper
response
1
13
25
Source: own calculations using Eurostat data.
37
48
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
lower
upper
response
1
13
25
37
48
53

EU industrial structure 2011 — Trends and Performance
A non‑technology shock in the motor vehicles industry
has permanent effects on employment in the rubber and
54
plastics industry, with an increase of some 2.5 %. 41 The
responses of productivity are only transitory, cf. Figure II.10.
FIgURE II.10: A non-technology shock has permanent effects on employment only
Employment productivity
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
1
13
25
Source: own calculations using Eurostat data.
37
lower
upper
response
The results for all four industries are summarised below.
The impulse response analyses indicate that a technology
shock in the motor vehicles industry permanently increase
productivity in the four other industries by some 1.5 %
to 4 % and employment in two industries by 2 % to 2.5 %.
48
2.5
2.0
1.5
1.0
0.5
0.0
-0.5
-1.0
-1.5
-2.0
1
13
lower
upper
response
Non‑technology shocks in the motor vehicles industry
have no permanent effects on productivity in the other
industries but increase employment in the four industries
by 2.5 % to 4.5 %, cf. Table II.7.
TAbLE II.7: Percentage responses of employment and productivity in four manufacturing industries
to shocks in the motor vehicles industry
technology shocks non‑technology shocks
Employment productivity Employment productivity
rubber and plastics 2.5 1.5 2.6 0.0
Basic metals 0.0 4.1 3.5 0.0
Fabricated metal products 0.0 3.8 4.5 0.0
Electrical equipment 2.0 4.2 4.0 0.0
Source: own calculations using Eurostat data.
41 Caution is needed when interpreting the results from the shocks,
especially on employment. Since the confidence intervals are
relatively wide, the estimates are not as precise as one might
think by only looking at the curve of the impulse response.
25
37
48

Appendix figure
FIgURE II.11: Sector share in EU-27 gDP in 2009 (%)
Agriculture, hunting and forestry
Fishing
Mining and quarrying
Manufacturing
Food products; beverages and tobacco
Textiles and textile products
Leather and leather products
Wood and wood products
Paper products; publishing and printing
Rened petroleum products
Chemicals, chemical products
Rubber and plastic products
Other non-metallic mineral products
Basic metals and fabricated metal products
Machinery and equipment n.e.c.
Electrical and optical equipment
Transport equipment
Manufacturing n.e.c.
Electricity, gas and water supply
Construction
Wholesale and retail trade
Hotels and restaurants
Transport, storage and communication
Financial intermediation
Real estate, renting and business activities
Public administration and defence
Education
Health and social work
Other social & personal services
Activities of households
Source: own calculations using Eurostat data.
Chapter II — Changes in EU Industrial structure
0 5 10 15 20 25
1997
2009
55

Chapter III
Drivers of Sector Growth
and Competitiveness
This chapter analyses economic growth in the EU from
a sectoral perspective. Section III.1 focuses on growth in output
by sectors. Industrial performance is analysed from a long‑term
perspective aiming at capturing main trends in sectoral
developments. Section III.2 presents indicators of sectoral
competitiveness using: labour productivity and unit labour
costs (ULC). These indicators are used to make comparisons
across sectors in the EU. The focus in Section III.3 shifts to
indicators for various factors of production: labour inputs,
human capital, capital formation, energy and technology.
Finally, Section III.4 examines sectoral growth from the demand
side, by analysing private consumption and investment.
III.1 Output growth across sectors
Growth varies considerably across EU sectors. Value
added in EU sectors grew on average by 2.4 % during
1995‑2009. Services activities were among the fastest
growing, confirming the dynamism of market services
highlighted in Section II.1. Transport, storage and
communication increased on average by 3.9 %, financial
intermediation by 3.6 %, real estate, renting and business
activities by 3.3 % and wholesale and retail trade
by 2.6 %. Nonetheless, the sector that outpaced all others
was a manufacturing sector; manufacture of electrical
and optical equipment which, on average, rose by 6%
during 1995‑2009. While the manufacturing sectors
on average grew slightly less than the EU economy
as a whole, 2.2 % annual growth against 2.4 % annual
growth on average, the manufacturing sectors chemicals,
transport equipment, rubber and plastics, and machinery
and equipment n.e.c. performed better than EU economy
as a whole. Value added declined in the following sectors:
fishing, mining and quarrying sectors, textiles, and
leather, cf. Figure III.1.
57

EU industrial structure 2011 — Trends and Performance
FIgURE III.1: Value added — average annual growth rate in the EU in 1995 – 2009 (%)
58
Electrical and optical equipment
Transport and communication
Health and social work
Financial intermediation
Chemicals
Real estate and business activities
Education
Rubber and plastics
Wholesale and retail trade
Transport equipment
Machinery n.e.c.
Other services
Total
Basic metals and metal products
Manufacturing
Hotels and restaurants
Activities of households
Non-metallic mineral products
Other mining
Pulp, paper and publishing
Construction
Other manufacturing
Agriculture, hunting and forestry
Wood and wood products
Electricity, gas and water supply
Food, drinks and tobacco
Rened petroleum
Fishing
Textiles and clothing
Public administration
Mining and quarrying
Mining of energy products
Leather and footwear
Note: Growth rates refer to value added in constant prices.
Source: own calculations using Eurostat data.
In analyses of growth in terms of production it should
be taken into account that production differs from value
added since intermediate consumption is included.
Production measurements in real terms are only available
for manufacturing sectors in the data sources used in this
publication. EU average annual production growth rates
in 1995‑2010 are very different across sectors. Growth
in the more ‘traditional’ and labour‑intensive sectors
declined more than in other sectors. Declining annual
-4 -3 -2 -1 0 1 2 3 4 5 6 7 8
production growth rates in 1995‑2010 can be witnessed in
leather and footwear, clothing, tobacco and textiles where
growth declined on average by between 2.5 % and 5 %
in 1995‑2009. Conversely, the highest growing sectors
tend to be more capital‑intensive. Average production
growth in 1995‑2010 was the highest in pharmaceuticals,
computer, electronic and optical products and in motor
vehicles where growth increased by between 3 %
and 5.4 %, cf. Figure III.2.

FIgURE III.2: EU average annual production growth rate in 1995-2010 (%)
Pharmaceuticals
Computer, electronic and optical products
Motor vehicles
Other manufacturing
Chemicals
Other transport eqpt.
Food
Machinery and equipment n.e.c.
Rubber and plastic products
Electrical equipment
Paper and paper products
Beverages
Fabricated metals
Repair and installation
Basic metals
Wood and wood products
Coke and rened petroleum
Printing and publishing
Non-metallic mineral products
Furniture
Textiles
Tobacco
Clothing
Leather and footwear
Source: own calculations using Eurostat data.
Chapter III — Drivers of Sector Growth and Competitiveness
-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6
box III.1: Output measurements: Value added v. production
Value added presents the advantage of being available for all types of activities: ranging from agriculture to
non‑business services while production is only available for manufacturing activities. The Eurostat Manual of
Business Statistics identifies two possible meanings for the concept of ‘production’: 1. activity of manufacturing, i.e.
the transforming of goods; or 2. result of this activity, i.e. the output of manufactured goods in a fixed period. In both
definitions of production, Eurostat excludes the services sectors. The other main difference is that value‑added is
a measure of output that subtracts intermediate consumption made by an individual producer, industry or sector
while production includes intermediate consumption.
Source: European System of Accounts (ESA) 1995, and NACE Rev. 1, Introduction, P. 21, OECD.
The developments in individual sub‑sectors in figure III.1 above
are hidden by the level of aggregation. Studying production
growth rates at the 3‑digit NACE level offers a more refined
picture of the various EU sectors in 1995‑2010. Concerning the
highest growing aggregated sector ‘Computer, electronic and
optical products’ in Figure III.1, the underlying sub‑sectors are
irradiation, electromedical and electrotherapeutic equipment,
installation of industrial machinery and equipment, medical
and dental instruments and supplies, optical instruments
and photographic equipment, instruments and appliances
for measuring, testing and navigation, electricity distribution
and control apparatus. Growth rates in these sectors varied
between 2.2 % and 4.5 %. Similarly, the two sub‑sectors of
motor vehicles, ‘parts and accessories for motor vehicles’
and ‘motor vehicles’, grew on average by 2.4 % in 1995‑2010.
Many sub‑sectors of the machinery and equipment industry
also grew considerably, by between 2 % and 4 % in 1995‑
2009: air and spacecraft and related machinery, agricultural
and forestry machinery, general‑purpose machinery, and
other general‑purpose machinery. On the other side of the
spectrum, most of the declining sub‑sectors are associated
with the textile industry, cf. Figure III.3.
59

EU industrial structure 2011 — Trends and Performance
FIgURE III.3: EU average annual production growth rate in 1995-2010 (%)
Optical instruments and photographic eq.
Air and spacecraft and related machinery
Irradiation, electromedical and electrotherapeutic equipment
Medical and dental instruments
Motor vehicles
Forging, pressing, stamping and roll
Installation of industrial machinery and equipment
Parts and accessories for motor vehicles
Instruments and appliances for measuring
General purpose machinery
Processing and preserving of sh
Soap and detergents
Agricultural and forestry machinery
Basic chemicals
Pulp, paper and paperboard
Bakery and farinaceous products
Processing and preserving of meat
Electric motors
Vegetable and animal oils
Grain mill products
Wiring
Other chemical products
Processing and preserving of fruit
Treatment and coating of metals
Other food products
Batteries and accumulators
Sawmilling
Other electrical equipment
Cement, lime and plaster
Concrete, cement and plaster
Refractory products
Wood, cork, straw and plaiting materials
Tanning and dressing of leather
Tanks, reservoirs and containers of metal
Domestic appliances
Ships and boats
Other textiles
Transport equipment n.e.c.
Man-made bres
Clay building materials
Computers and peripheral equipment
Other porcelain and ceramic products
Finishing of textiles
Weaving of textiles
Clothing
Knitted and crocheted clothing
Preparation and spinning of textile
Musical instruments
Footwear
Magnetic and optical media
-10 -8 -6 -4 -2 0 2 4 6
Note: The figure only shows the 25 high and low (negative) growth sextors.
Source: own calculations using Eurostat data.
III.2 Sectoral competitiveness
indicators
Competitiveness is a multidimensional concept, which
is studied from two perspectives in this report. The first
perspective looks at means for industries to improve their
competitiveness by lowering their costs, increasing their
productivity, employing skilled labour, renewing their
capital stock and increasing their spending on R&D and
innovation to upgrade their products. Different indicators
which measure aspects of an industry’s competitiveness,
such as labour productivity and unit labour costs (ULC),
are the subject of the remainder of this chapter. The
second perspective studies how effective industries
have been in improving their competitiveness in the
international markets. This perspective is analysed in
Chapter V.
60
This section presents a set of indicators on EU sectoral
growth, productivity, unit labour costs and relative prices.
The objective is to present stylised facts across the main
sectors of the economy and to show the role of labour
productivity in sectoral competitiveness. More precisely,
market services are sub‑divided into two groups. The
first consists of wholesale and retail trade, repair of
motor vehicles, motorcycles and personal and household
goods, hotels and restaurants, transport, storage and
communication (NACE Rev. 1 categories G to I) and the
second comprises financial intermediation, real estate,
renting and business activities (NACE Rev. 1 categories J
and K). Non‑market services encompass public
administration and defence, compulsory social security;
education; health and social work; other community, social
and personal service activities; private households with
employed persons (NACE Rev. 1 categories L to P). Industry

encompasses mining, manufacturing and electricity, gas
and water supply.
Value added in constant (1995) prices grew steadily,
although at different rates, in all sectors but agriculture
until 2008. All sectors except non‑market services and
FIgURE III.4: EU value added in 1995-2010 (1995 = 100)
160
150
140
130
120
110
100
90
Agriculture, hunting, forestry and shing
Total industry
Financial intermediation and business services Non-market services
Construction
Total
Wholesale and retail trade
Chapter III — Drivers of Sector Growth and Competitiveness
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Source: own calculations using Eurostat data.
But while value added grew substantially in financial
intermediation and wholesale and retail, employment
also rose quickly. Labour productivity growth per person
employed since 1995 was higher in the industrial sectors
than in wholesale, retail and financial intermediation. The
agriculture have seen their value added decrease during
the latest crisis. Financial services and wholesale and trade
displayed higher growth rates than other activities over the
whole time period. The largest declines during the crisis
occurred in total industry and the construction sector,
cf. Figure III.4.
fall in labour productivity during the crisis and the upward
movement during the recovery reflects the pro‑cyclical
pattern due to labour hoarding in industry when demand
and production decreases, cf. Figure III.5.
FIgURE III.5: EU labour productivity per person employed in 1995-2009 (1995 = 100)
150
140
130
120
110
100
90
80
Total industry
Wholesale and retail trade
Financial intermediation and business services
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Source: own calculations using Eurostat data.
61

EU industrial structure 2011 — Trends and Performance
Developments in ULC are caused by changes in labour costs
per employee relative to labour productivity growth. High
labour productivity growth generated more favourable unit
FIgURE III.6: EU ULC (index, 1995 = 100)
160
150
140
130
120
110
100
90
FIgURE III.7: EU relative prices (Industry = 100)
115
110
105
100
95
90
85
62
Industry
Wholesale and retail trade
Financial intermediation and business services
Wholesale and retail trade
Financial intermediation and business services
labour costs in industry. EU ULC grew more in services than
in industry due to lower productivity growth, cf. Figure III.6.
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Source: own calculations using Eurostat data.
Taking the developments in Figure III.5 into account, relative
prices increased more in services sectors and relatively more
in financial intermediation than in wholesale and retail
relative to manufacturing. The relative price is the ratio of
two price indices, the value added deflator (2000 = 100) of
industry divided by the value added deflator (2000 = 100)
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Source: own calculations using Eurostat data.
of market services. Between 1995 and 2007 the relative price
of industrial goods declined relative to the price of market
services. These evolutions may also reflect the higher level
of technical change and higher degree of competition in
industry including openness to trade compared to services
sectors in the EU, cf. Figure III.7.

The relationship between productivity growth and
changes over time in prices is shown below. There is
a negative relationship, implying that relatively high rates
of productivity growth are negatively related to changes
in relative prices. The high rate of labour productivity
growth experienced in the industrial sector has resulted
Chapter III — Drivers of Sector Growth and Competitiveness
in moderate evolution of the relative price of industry
output via, among other channels, its impact on ULC. These
developments suggest that the industry sector has been
able to provide the economy with relatively cheap (and
high quality) inputs, thus contributing to overall economic
growth and competitiveness, cf. Figure III.8.
FIgURE III.8: Labour productivity growth vs changes in relative prices in 1995-2009
Change in relative prices
3.5
3.0
2.5
1.5
1.0
0.5
0.0
Construction
Non-market services
2.0 Financial intermediation and business services
Wholesale and retail trade
Industry
-0.5
Agriculture, forestry
and fishing
-1.0
-0.4 -0.2 -0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8
Note: Annual average percentage changes.
Source: own calculations using Eurostat data.
iii21 labour productivity
Labour productivity is analysed at different levels of
aggregation in this section, beginning with an overall view
of labour productivity growth for the main sectors of the
economy in 1995‑2009. Value added and employment
is used in the calculation of labour productivity growth
for all sectors in the economy. A more detailed sectoral
classification, but limited to manufacturing, is used later to
study labour productivity growth which is calculated using
Labour productivity growth
production. This part will be used as basis for calculating
unit labour costs in the next section.
The effects of the latest crisis show in moderate growth
rates across sectors. EU labour productivity growth in 1995‑
2009 was higher than 3 % in only a few sectors. It grew by
between 3.2 % and 5.2 % in the sectors producing electrical
and optical equipment, chemicals and agriculture, hunting
and forestry, cf. Figure III.9.
63

EU industrial structure 2011 — Trends and Performance
FIgURE III.9: Annual growth in EU labour productivity per person employed 1995-2009 (%)
Electrical and optical equipment
Chemicals
Agriculture, hunting and forestry
Transport and communication
Financial intermediation
Rened petroleum
Manufacturing
Machinery n.e.c.
Pulp, paper and publishing
Health and social work
Education
Wood and wood products
Non-metallic mineral products
Basic metals and metal products
Textiles and clothing
Rubber and plastics
TOTAL
Electricity, gas and water supply
Wholesale and retail trade
Transport equipment
Other mining
Fishing
Mining of energy products
Food, drinks and tobacco
Mining and quarrying
Other services
Other manufacturing
Hotels and restaurants
Construction
Leather and footwear
Real estate and business activities
Public administration
-3 -2 -1 0 1 2 3 4 5 6
Source: own calculations using Eurostat data.
64
box III. 2: The interpretation and measurement of labour productivity
Labour productivity is a measure of the amount of final goods and services produced by a unit of labour input in the
course of a given period of time. Excluding intermediates, labour productivity also measures the ability of workers
to generate income given the state of technology and other inputs.
Even if technology is the key determinant, changes in labour productivity cannot be automatically identified with
technical change because it depends also on other inputs like capital or intermediates. For example, increasing
capital per worker (capital deepening), everything else equal, will increase labour productivity even if technology
is the same. In the longer term, however, technical change in a broad sense will be the only source of labour
productivity growth. In turn, labour productivity growth is the only source of economic growth: the sustained
growth of income per capita that has transformed so deeply our societies since the inception of the industrial
revolution. This is the reason why aggregate labour productivity attracts so much attention.
Inspecting sectoral labour productivity changes will also reveal important trends in our economies. For instance, the
faster productivity growth of manufacturing relative to services explains why workers are increasingly employed in
the services’ sector. Productivity differentials with other countries will also explain comparative advantages and, in
the end, observed specialization patterns.
Labour productivity is measured by the ratio of value added to hours worked. The use of value added (production
minus intermediates) ensures that intermediates are not inputed more than once. When hours are not available, it is
common to use value added per person in employment (employees plus the self‑employed).
At the sectoral level, the estimate of value added is more difficult and takes longer to be published than that of
production. This is the reason why in practice production is often used instead of value added when estimating
productivity; particularly in short‑term assessments of latest developments (before the figure for value added is

42
A more detailed picture based on production and not
on value added brings further evidence concerning the
dynamics of EU labour productivity growth. As explained
in boxes III.1 and III.2, there is a difference in measuring
labour productivity in terms of value added compared to
measuring productivity in terms of production. Overall
productivity growth, measured as production per hours
worked, for total manufacturing was positive for 2000‑
2010 at 2.3 %. It was higher in 2000‑2005 when it grew
by 2.6 % than in 2006‑10 when the growth rate was 1.9 %.
The latest year for which data are available, 2010, shows
42 See J. Durán, ‘A digression on the notions of production and
value added and the measurement of productivity,’ Economic
Note 2011-01, DG Enterprise and Industry, European Commission.
Chapter III — Drivers of Sector Growth and Competitiveness
available). Including intermediates, however, induce serious measurement errors that have to be kept in mind when
interpreting production per unit of labour input (so‑called productivity ‘based on gross output’). 42
a very strong productivity growth improvement. 43
Significant productivity gains 2006‑10 compared to 2000‑05
in only were achieved in five sectors: beverages, clothing,
leather, computer, electronic and optical products and
other transport equipment. Developments for 2010 are
especially strong in industries producing basic metals,
computer, electronic and optical products, motor vehicles
and machinery n.e.c., cf. Table III.1.
TAbLE III.1: EU labour productivity growth 2000-2009 (%). Production per hours worked
code sector 2000‑2010 2000‑2005 2006‑2010 2010
B Mining and quarrying 0.4 1.6 ‑0.8 1.9
c Manufacturing 2.3 2.6 1.9 8.5
c10 Food 2.1 2.9 1.4 2.3
c11 Beverages 3.0 2.9 3.1 2.7
c12 Tobacco ‑0.7 ‑0.7 ‑0.7 ‑4.2
c13 Textiles 0.9 0.9 1.0 8.4
c14 Clothing 1.5 ‑3.4 6.3 10.9
c15 Leather and footwear ‑2.6 ‑5.5 0.4 5.3
c16 Wood and wood products 1.5 2.3 0.7 3.9
c17 Paper 3.0 3.1 2.9 7.3
c18 Printing 1.7 2.8 0.6 5.0
c19 Refined petroleum 2.1 2.6 1.6 3.5
c20 Chemicals 2.9 3.5 2.3 10.8
c21 Pharmaceuticals 5.5 6.0 4.9 8.4
c22 Rubber and plastics 1.1 1.7 0.4 5.8
c23 Non‑metallic mineral products 0.9 2.4 ‑0.6 4.0
c24 Basic metals 2.3 3.3 1.4 18.8
c25 Metal products 0.6 2.0 ‑0.8 7.6
c26
Computer, electronic and
optical
4.7 2.6 6.8 14.3
c27 Electrical equipment 1.8 2.0 1.5 9.7
43 Available at the time of the drafting of the report.
>>>
65

EU industrial structure 2011 — Trends and Performance
The sectors that achieved the highest annual growth
rates 2000‑2010 were pharmaceuticals, computer, electronic
and optical products, pulp and paper and beverages where
66
code sector 2000‑2010 2000‑2005 2006‑2010 2010
c28 Machinery n.e.c. 2.1 2.9 1.4 12.0
c29 Motor vehicles 2.2 2.7 1.7 16.6
c30 Other transport eq. 2.3 1.8 2.8 3.8
c31 Furniture 0.2 0.7 ‑0.3 1.4
c32 Other manufacturing 2.5 2.9 2.1 7.5
c33 Repair of machinery 2.7 3.2 2.3 8.1
Note: Own calculations using Eurostat data.
Source: own calculations using Eurostat data.
labour productivity on average grew by 3 % or more.
Productivity growth in the sectors producing tobacco and
leather was negative, cf. Figure III.10.
FIgURE III.10: Average annual growth in labour productivity 2000-2010 (%). Production per hours worked
Pharmaceuticals
Computer, electronic and optical products
Pulp and paper
Beverages
Chemicals
Repair and installation of mach and equipment
Other manufacturing
Basic metals
Other transport equipment
Manufacturing
Motor vehicles
Machinery and equipment n.e.c.
Food products
Coke and rened petroleum
Electrical equipment
Printing and publishing
Wood and wood products
Clothing
Rubber and plastic products
Textiles
Non-metallic mineral products
Fabricated metals
Mining and quarrying
Furniture
Tobacco
Leather
Source: own calculations using Eurostat data.
The evolution of EU and US average annual growth rates in
labour productivity, in terms of production per employed,
-3 -2 -1 0 1 2 3 4 5 6
varies considerably. Labour productivity drops are distinctly
more marked in the EU than in the US, cf. Figure III.11.

Chapter III — Drivers of Sector Growth and Competitiveness
FIgURE III.11: Average annual growth in labour productivity 1997-2010 (%). Production per employed
15
10
5
0
-5
-10
-15
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Source: own calculations using Eurostat and OECD data.
iii22 unit labour costs
Unit labour costs (ULC) are defined as the ratio of labour
costs per employee to value added per employee. Since
developments in ULC show if nominal wages increase in line
with productivity, it can be regarded as a measure of cost
competitiveness. Cost competitiveness across EU sectors
appears to be very variable. High EU ULC growth rates
during 2009 are explained by production decreasing more
than employment at given labour costs. This occurred in many
manufacturing industries. Box III.3 provides more insight into
the methodology and interpretation of unit labour costs.
The performance of manufacturing industries, together
with mining and quarrying, in terms of ULC growth rates
is compared below. The comparison aims to show which
industries perform particularly well relative to aggregate
manufacturing. The comparison is made for different time
periods since 2000 to facilitate a comparison of ULC growth
rates before and during the latest crisis. The period 2000‑
2005 was clearly influenced by relatively high labour
productivity developments and characterised by low
ULC growth. Manufacturing as a whole witnessed almost
stable ULC at +0.6 %. Almost all sectors, with the particular
exception of leather and footwear, tobacco, clothing
and other transport equipment, were characterised by
increasing ULC. during the period 2005‑10 the situation
deteriorated for mining and aggregate manufacturing,
and for almost all manufacturing subsectors This is the
normal situation during recessions when production falls
rapidly while adjustments of labour are more sluggish
The same developments also explain why labour productivity
growth decreases during recessions. Both ULC and labour
productivity move pro‑cyclical.
Computer, electronic and optical products, pharmaceuticals,
and clothing did not see their ULC increase. A word of
caution is necessary when interpreting the figures. The
results in the table are strongly dependent on the chosen
time period. The recovery during 2010 has increased
productivity growth while, at the same time, wage
increases have been modest. That lowers ULC growth rates
substantially in industries such as basic metals and motor
vehicles. Choosing 2000‑2009 yields higher ULC growth
rates than 2000‑2010 since production, and consequently
productivity growth, fell heavily during 2009, cf. Table III.2.
67

EU industrial structure 2011 — Trends and Performance
TAbLE III.2: EU ULC annual growth in mining and manufacturing industries in 2000-2010 (%)
code sector 2000‑2005 2005‑2010 2000‑2009 2000‑2010 2010
B Mining and quarrying 4.0 7.9 6.2 5.9 3.4
c Manufacturing 0.6 1.4 1.8 1.0 ‑6.5
c10 Food 0.9 1.5 1.4 1.2 ‑0.4
c11 Beverages 0.7 0.5 0.6 0.6 0.2
c12 Tobacco 6.3 5.1 6.1 5.7 2.2
c13 Textiles 1.8 0.8 2.4 1.3 ‑8.5
c14 Clothing 4.0 ‑0.7 2.4 1.6 ‑5.5
c15 Leather and footwear 7.3 4.4 6.7 5.9 ‑1.8
c16 Wood and wood products 0.6 3.5 2.8 2.0 ‑4.7
c17 Paper 0.0 ‑0.3 0.5 ‑0.1 ‑5.4
c18 Printing 0.5 0.4 1.0 0.5 ‑4.4
c19 Refined petroleum 1.0 3.5 2.4 2.3 1.2
c20 Chemicals 0.0 0.3 1.3 0.2 ‑9.5
c21 Pharmaceuticals ‑2.3 ‑1.8 ‑1.6 ‑2.1 ‑6.3
c22 Rubber and plastics 1.1 1.4 2.0 1.3 ‑5.3
c23 Non‑metallic mineral products 1.0 3.8 3.0 2.4 ‑3.7
c24 Basic metals ‑0.1 3.3 3.4 1.6 ‑14.6
c25 Metal products 1.1 3.8 3.4 2.4 ‑6.3
c26 Computer, electronic and optical 0.1 ‑2.3 ‑0.2 ‑1.1 ‑9.3
c27 Electrical eq. 0.5 1.2 1.9 0.9 ‑8.3
c28 Machinery n.e.c. 0.6 3.6 3.3 2.1 ‑8.4
c29 Motor vehicles ‑0.1 1.0 2.2 0.5 ‑15.2
c30 Other transport eq. 2.5 1.8 2.3 2.1 0.9
c31 Furniture 1.8 3.3 3.1 2.6 ‑2.7
c32 Other manufacturing 0.3 0.5 1.0 0.4 ‑5.2
c33 Repair of machinery 1.3 0.5 1.4 0.9 ‑3.3
Note: Labour compensation data for 2009 in national accounts not available yet. The table above is based on quarterly data from
short‑term statistics. Indices of production, gross wages and salaries have been used.
Source: own calculations using Eurostat data.
The different developments in ULC caused by large
swings in labour productivity growth are evident when
comparing 2009 with 2010. since movements in labour
costs per employee are relatively small during the whole
period, movements in labour productivity growth explain
68
the major part of the fluctuations in ulc Decomposing
further, changes in production cause most of the fluctuations
in labour productivity growth. Production fell by some 18 %
between the first quarters of 2008 and 2009 while
employment fell by around 5 %, cf. Figure III.12.
FIgURE III.12: Recent ULC fluctuations are driven mainly by productivity developments
20
15
10
5
0
-5
-10
-15
-20
ULC
Wages per employee
Production per employee
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Note: Average annual growth in unit labour costs, wages per employee and productivity in the EU manufacturing industry in 2001‑2010 (%)
Source: own calculations using Eurostat data.

ox III.3: Unit labour costs
Chapter III — Drivers of Sector Growth and Competitiveness
As presented in Figure III.12., unit labour cost growth is expressed in terms of growth rates of the ratio of labour
compensation (gross wages 44 ) per employee to labour productivity growth (production by employee). Unit labour
costs are to be interpreted cautiously. Unit labour costs are not an exhaustive measure of cost competitiveness, as
only labour costs are taken into account. In sectors where capital expenditure costs play a large role, unit labour
costs levels and changes over time play a lesser role than in industries largely driven by labour costs.
Mining, tobacco and leather and footwear displayed very
high growth rates of ULC for the whole period 2000‑2010. 45
At the other extreme, unit labour costs declined in
44 Total labour compensation usually includes not only gross wages
and salaries of employees, but also other costs of labour that are
paid by employers, including employers’ contributions to social
security and pension schemes. Here only gross wages are taken
into account.
45 An analysis at macroeconomic level, with data for the European
Union, the United States and Japan, is presented regularly in the
series of quarterly reports ‘Price and cost competitiveness’ by the
European Commission, Directorate-General for Economic and
Financial Affairs.
computer, electronic and optical products, pharmaceuticals
and pulp and paper, cf. Figure III.13.
FIgURE III.13: Average annual growth in unit labour costs in EU manufacturing by industry 2001-10 (%)
Mining and quarrying
Leather and footwear
Tobacco
Furniture
Metal products
Non-metallic mineral products
Rened petroleum
Other transport eq.
Machinery n.e.c.
Wood and wood products
Clothing
Basic metals
Textiles
Rubber and plastics
Food
Manufacturing
Repair of machinery
Electrical eq.
Beverages
Printing
Motor vehicles
Other manufacturing
Chemicals
Pulp and paper
Computer, electronic and optical products
Pharmaceuticals
-3 -2 -1 0 1 2 3 4 5 6 7
Source: own calculations using Eurostat data.
III.3 Factors of production
Improving productivity can be achieved through the mix
of different factors of production. The combination of
factors of production with the production technology
can significantly improve the performance of firms and
industries. This section looks at the inputs of labour, human
capital, investment, energy and technology.
iii31 labour
In the manufacturing sectors, increases in outputs have not
been mirrored by equivalent increases in employment. While
this has triggered higher productivity growth, it has also
meant that manufacturing growth was not labour intensive.
Most jobs have come from the services industries, illustrating
the move from primary and secondary sectors to the tertiary
69

EU industrial structure 2011 — Trends and Performance
economy. While the average annual growth in persons
employed in the EU in 1995‑2009 was 2 %, it decreased on
average by 1 % in manufacturing industries. Manufacturing
employment only grew in transport equipment, rubber and
plastics and other manufacturing. Strongest employment
FIgURE III.14: Average annual growth of persons employed in the EU 1995-2009 (%)
Real estate and business activities
Agriculture, hunting and forestry
70
Hotels and restaurants
Other services
TOTAL
Health and social work
Construction
Wholesale and retail trade
Education
Transport and communication
Financial intermediation
Public administration
Rubber and plastics
Transport equipment
Other manufacturing
Other mining
Food, drinks and tobacco
Basic metals and metal products
Electrical and optical equipment
Electricity, gas and water supply
Machines n.e.c.
Manufacturing
Chemicals
Non-metallic mineral products
Pulp, paper and publishing
Wood and wood products
Fishing
Mining and quarrying
Rened petroleum
Mining of energy products
Leather and footwear
Textiles and clothing
Source: own calculations using Eurostat data.
-5 -4 -3 -2 -1 0 1 2 3 4 5
A more detailed and updated picture of the evolution
of labour input in manufacturing can be provided by
studying sectors at the 2‑digit level. 46 Hours worked is
closely correlated with the number of persons employed.
In the 2009 edition of EU Industrial Structure, the data ended
46 Due to the change from NACE Rev. 1 to NACE Rev. 2, Table III.5 and
Table III.6 are not completely comparable with each others.
growth in service industries was seen in real estate and
business activities, hotels and restaurants and other services.
In these sectors employment on average grew more than in
the total EU economy, cf. Figure III.14.
in September 2008 and the slump had not yet materialised
in all manufacturing sectors. This illustrates a lag in how the
crisis has affected the EU labour market. While production
was hurt first, labour hoarding prevented a strong fall in
employment. In a second stage, the fall in demand has hit
employment in sectors. The most impacted manufacturing
industries (until the last quarter of 2010) were clothing,
textiles, leather and tobacco, cf. Table III.3.

Chapter III — Drivers of Sector Growth and Competitiveness
TAbLE III.3: EU manufacturing employment and hours worked — average annual growth
from 2000 to 2010
code
Employment hours worked
sector 2000‑2010 2000‑2010
c Manufacturing ‑1.9 ‑1.9
c10 Food ‑0.9 ‑0.6
c11 Beverages ‑2.3 ‑1.9
c12 Tobacco ‑4.4 ‑4.5
c13 Textiles ‑5.2 ‑6.2
c14 Clothing ‑5.8 ‑6.5
c15 Leather ‑3.7 ‑4.6
c16 Wood and wood products ‑2.6 ‑2.5
c17 Paper ‑2.4 ‑2.5
c18 Printing ‑2.5 ‑2.7
c19 Refined petroleum ‑2.0 ‑2.3
c20 Chemicals ‑2.1 ‑2.2
c21 Pharmaceuticals ‑0.6 ‑0.4
c22 Rubber and plastics ‑0.9 ‑0.7
c23 Non‑metallic mineral products ‑2.6 ‑2.6
c24 Basic metals ‑2.9 ‑2.8
c25 Metal products ‑0.8 ‑0.7
c26 Computer, electronic and optical ‑2.7 ‑2.7
c27 Electrical eq. ‑1.7 ‑1.6
c28 Machinery n.e.c. ‑1.3 ‑1.1
c29 Motor vehicles ‑1.2 ‑1.2
c30 Other transport eq. ‑1.3 ‑1.0
c31 Furniture ‑2.6 ‑2.6
c32 Other manufacturing ‑1.0 ‑0.8
c33 Repair of machinery ‑1.1 ‑0.8
Source: own calculations using Eurostat data.
iii32 human capital
The labour force is not homogenous but consists of
individuals with different types of skills and levels of
educational attainment. This heterogeneity of the labour
force is often not reflected in measures of labour inputs.
Human capital is as an additional factor of production,
which helps to explain differences in economic growth
between countries. The purpose of this section is to present
an indicator of human capital at sectoral level related
to education, which, in modern economies, is a crucial
component of the production process.
To the extent that human capital consists of the stock of
knowledge, skills and experience embodied in the labour
force, a commonly used proxy for accumulated knowledge
71

EU industrial structure 2011 — Trends and Performance
is formal educational attainment. This has the advantage
of being easily available information, although it is a rough
approximation of human capital that does not take
account of the post‑schooling accumulation from training
at the workplace and experience (learning by doing). 47
In this section the indicator used is the distribution of
47 For a discussion of proxies for human capital in empirical studies,
see Greiner, Semmler, and Gong (2005). On different ways of
measuring the stock of human capital, including a discussion on
the limitations of educational attainment as a proxy for human
capital, see OECD (1998).
72
employment in each sector by educational attainment.
The International Standard Classification of Education
(ISCED) classification identifies levels of education
from 0 to 6 and was used to measure, in each sector, the
proportion of low‑skilled, medium‑skilled and high‑skilled
people, cf. Box III.4.
box III.4: Using International Standard Classification of Education to
define skill categories
The International Standard Classification of Education (ISCED) differentiates seven levels of education.
‑ Level 0: pre‑primary
‑ Level 1: primary education
‑ Level 2: lower secondary
‑ Level 3: upper secondary
‑ Level 4: post‑secondary non‑tertiary
‑ Level 5: first stage of tertiary education
‑ Level 6: second stage of tertiary education.
The publication has aggregated the levels in three categories so that total employment in each sector can be broken
down in three skill categories instead of seven:
‑ Low skilled: Level 0, Level 1 and level 2
‑ Medium skilled: Level 3 and level 4
‑ High‑skilled: Level 5 and level 6.
The skill intensity of sectors in the EU‑27, according to NACE
Rev. 2, reveals a contrasting picture as far as manufacturing
sectors are concerned. The pharmaceutical industry is the
manufacturing sector that stands out most in the EU, with
about half the employed having a tertiary level of education
(high skill). The educational sector has the highest proportion
of highly qualified staff. Two thirds of people working in
this sector are highly qualified. This sector is followed by
the professional, scientific and technical activities (60 % of
high skilled) and the information and communication sector
(54 % of high skilled). It is closely followed by certain services
industries: the financial and insurance activities, human health
and social work as well as art and entertainment and creation.
Financial and insurance activities is also the sector where the
proportion of low‑skilled is the smallest compared to any other.
Coke and refined petroleum, computer, electronic and optical
products, other transport equipment, the chemical and the
machinery industry all have at least one quarter highly skilled
employees. At the other end of the scale are the sectors where
low levels of education prevail, defined as more than 30 % of
the workforce: leather, textiles, wood, and wearing apparel.
Other sectors — from other transport equipment to paper
products — are in an intermediate position, with a similar
share of high and low education attainment. In interpreting
these figures the meaningful indicator should be the flow of
services from the human capital stock, which is related to the
utilisation rate of the human capital stock, rather than the
capital stock itself, cf. Figure III.15.

FIgURE III.15: Employment by educational attainment in the EU-27 in 2009
Agriculture and forestry
Leather and footwear
Clothing
Wood and wood products
Furniture
Accomodation & food
Textiles
Food
Metal products
Construction
Transportation & storage
Non-metallic mineral products
Paper
Basic metals
Rubber and plasticss
Wholesale and retail trade
Mining and quarrying
Printing
Administration
Repair of machinery
Other manufacturing
Electrical eq.
Tobacco
Motor vehicles
Beverages
Machinery n.e.c.
Other services activities
Chemicals and chemical products
Other transport eq
Real Estate activities
Electricity and gas
Cmputer, electronic and optical
Rened petroleum
Arts & entertainment
Human health and social work
Financial & insurance activities
Pharmaceuticals
Information
Extraterritorial organisations and bodies
Professional, Scientic and Technical activities
Education
Source: calculated using Eurostat’s labour force survey data.
Apart from the relevance of human capital when analysing
growth and growth‑related issues, the educational level of
the labour force is important for assessing competitiveness,
particularly in an international context. By encouraging the
adoption and development of technology and ideas,
human capital makes enterprises and sectors competitive
labour‑intensive sectors, characterised by low‑education
employment, may be particularly sensitive to competition
from low‑wage developing countries Examples of
manufacturing sectors in this situation are wearing apparel,
textiles, furniture and other manufacturing, and fabricated
Chapter III — Drivers of Sector Growth and Competitiveness
High Medium Low
0 10 20 30 40 50 60 70
metal products, which also exhibit poor performance
in external trade in terms of the revealed comparative
advantage index (see Chapter V). In contrast, chemicals,
the manufacturing sector with the highest component of
high‑education employment (33 %), and also characterised
as capital‑intensive, ranks highly in revealed comparative
advantage. It is worth emphasising that unit labour costs,
and not merely wage differences, is the relevant indicator for
assessing cost competitiveness, and that gains from trade,
for both high‑ and low‑wage countries, are determined by
comparative, rather than absolute, advantages.
73

EU industrial structure 2011 — Trends and Performance
iii33 gross fixed capital formation
Capital formation increases production capacity and can
contribute to the competitiveness of firms and sectors
by increasing labour productivity. Capital goods inject
technology, innovation and intangibles (e.g. software)
into the production process, and facilitate change and
reorganisation. In addition, investment decisions are
forward‑looking and, therefore, closely linked to the
medium‑ and long‑term expectations of the sector. This
section presents three indicators related to investment. The
first is an indicator which relates investment to value added,
the second refers to investment growth, and the third is
a proxy for capital intensity based on investment flows.
TAbLE III.4: EU-22 investment ratios in 2005-2009
74
The investment ratio is defined as the ratio of gross
fixed capital formation (GFCF) to value added. 48 There is
a relationship between the sectors where large companies
dominate (Figure II.7) and the sectors with the largest
investment ratios. Apart from the real estate and business
activities sectors, those with the highest investment
intensities are also the top sectors as far as large companies
are concerned (above 250 employees): electricity, gas and
water supply, transport and communication, mining and
quarrying and refined petroleum. With the exception of
a few sectors, the investment ratios have been quite stable
over time. The crisis is evident as investment ratios drop in
almost all sectors during 2009, cf. Table III.4.
code sector 2005 2006 2007 2008 2009
a Agriculture and forestry 0.33 0.34 0.34 0.40 0.35
B Fishing 0.14 0.15 0.18 0.18 0.17
c Mining and quarrying 0.24 0.31 0.36 0.35 0.31
d Manufacturing 0.16 0.16 0.17 0.16 0.14
da Food, drinks and tobacco 0.17 0.18 0.19 0.19 0.15
dB Textiles and clothing 0.11 0.12 0.13 0.12 0.10
dc Leather and footwear 0.09 0.10 0.10 0.10 0.08
dd Wood and wood products 0.18 0.19 0.20 0.21 0.16
dE Pulp, paper and publishing 0.16 0.16 0.16 0.14 0.12
dF Refined petroleum 0.24 0.27 0.35 0.30 0.39
dg Chemicals 0.15 0.16 0.18 0.18 0.16
dh Rubber and plastics 0.16 0.16 0.18 0.17 0.12
di Non‑metallic mineral products 0.20 0.21 0.22 0.24 0.24
dJ Basic metals and metal products 0.14 0.15 0.16 0.16 0.16
dK Machinery n.e.c. 0.11 0.11 0.11 0.12 0.11
dl Electrical and optical equipment 0.13 0.13 0.14 0.12 0.11
dm Transport equipment 0.22 0.20 0.20 0.19 0.19
dn Other manufacturing 0.12 0.13 0.14 0.12 0.08
E Electricity, gas and water supply 0.32 0.35 0.37 0.36 0.32
F Construction 0.09 0.09 0.09 0.09 0.07
>>>
48 The aggregate consists of BE, CZ, DK, DE, IE, ES, FR, IT, CY, LT, LU,
MT, HU, NL, AT, PL, PT, SI, SK, FI, SE and UK. Netherlands is not
included in the manufacturing sector DC: Textiles and Lithuania
is not included in DF: Refined petroleum.

Chapter III — Drivers of Sector Growth and Competitiveness
code sector 2005 2006 2007 2008 2009
g Wholesale and retail trade 0.13 0.13 0.13 0.12 0.10
h Hotels and restaurants 0.12 0.13 0.12 0.12 0.09
i Transport and communication 0.34 0.35 0.37 0.38 0.34
J Financial intermediation 0.10 0.11 0.10 0.12 0.10
K Real estate and business activities 0.42 0.43 0.44 0.40 0.33
l Public administration 0.27 0.27 0.28 0.27 0.26
m Education 0.09 0.09 0.09 0.09 0.08
n Health and social work 0.10 0.10 0.11 0.10 0.08
O Other services 0.25 0.27 0.28 0.28 0.25
total 023 023 024 024 024
Note: The investment ratio is defined as the ratio of gross fixed capital formation (GFCF) to value added.
Source: own calculations using Eurostat data.
The second investment indicator is growth in gross fixed
capital formation (GFCF). When analysing the development
over time, it should be kept in mind that capital intensive
sectors need to invest more than other sectors to maintain
production and that significant investments are necessary
FIgURE III.16: EU gFCF growth rates based on selected countries in 1995-2009
Mining and quarrying
Rened petroleum
Construction
Real estate and business activities
Transport and communication
Other services
Health and social work
All Branches
Wood and wood products
Wholesale and retail trade
Basic metals and metal products
Public administration
Hotels and restaurants
Education
Agriculture and forestry
Chemicals
Electrical and optical equipment
Machinery n.e.c.
Other manufacturing
Transport equipment
Rubber and plastics
Electricity, gas and water supply
Financial intermediation
Manufacturing
Non-metallic mineral products
Food, drinks and tobacco
Fishing
Pulp, paper and publishing
Leather and footwear
Textiles and clothing
Source: own calculations using Eurostat data.
to replace old buildings, machinery and equipment. The
evolution between 1995 and 2009 shows that services
sectors in general have invested more than manufacturing
sectors, cf. Figure III.16.
-4 -2 0 2 4 6 8
75

EU industrial structure 2011 — Trends and Performance
The ranking of the sectors above may differ considerably
from year to year due to the highly cyclical behaviour of
GFCF. This can be illustrated for the manufacturing sector
transport equipment. Annual growth rates of GFCF in fixed
76
prices are shown for France, Germany, Italy and Spain;
especially volatile is the French series. The effect of the crisis
on the investments is obvious, cf. Figure III.17.
FIgURE III.17: Annual growth rates of gFCF in manufacture of transport equipment in France, germany,
Italy and Spain 1995-2009
40
30
20
10
0
-10
-20
-30
-40
Spain
Germany
Italy
France
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Source: own calculations using Eurostat data.
Capital intensity is an indicator that can be used to characterise
the technology of sectors. It is useful not only for descriptive
purposes, but also as determinant of industry conditions
and behaviour. High levels of investment can operate as
a barrier to entry, imply a higher degree of risk, and influence
cost structures and price strategies of firms. Though capital
intensity should be measured as the stock of capital per
person employed, a proxy is used in this section, namely
the ratio of investment in tangible assets to the number of
persons employed. The calculation of the indicator is based
on 2005, 2006 and 2007 data. The values presented correspond
to the average of these three years. The data refer to EU‑27 and
the coverage by industry, which goes up to three digits of
NACE Rev. 1, encompassing a range of sectors from mining
and quarrying to market services. In a few cases, due to lack of
observations, estimations were needed to complete the table.
This is not a strict indicator of capital stock per person
employed but of the investment flow per person
employed. A drawback is that investment is highly cyclical
and therefore the results must be interpreted as an
approximation, although the cyclical effect is partially offset
by taking average values over three years.
The sectors that operate with relatively high levels of capital
intensity are a mix of utilities, manufacturing and services
sectors. Conversely, apart from wholesale and retail, all
medium investment intensity sectors are in manufacturing.
And, logically, the manufacturing sectors with the lowest
investment intensity (leather, textiles) are labour intensive
and face the strongest competition from low cost countries,
cf. Table III.5.
TAbLE III.5: EU investment intensity. Average 2005-07
code sector million € / 1 000 persons
E Electricity, gas and water supply 49.0
dF Refined petroleum 43.1
c Mining and quarrying 29.1
i Transport and communication 14.3
dg Chemicals 14.2
K Real estate and business activities 13.3
>>>

Chapter III — Drivers of Sector Growth and Competitiveness
code sector million € / 1 000 persons
dm Transport equipment 10.2
di Non‑metallic mineral products 9.5
da Food, drinks and tobacco 7.5
dh Rubber and plastics 7.0
dE Pulp, paper and publishing 6.9
dJ Basic metals and metal products 6.5
dl Electrical and optical equipment 5.7
dd Wood and wood products 5.4
dK Machinery n.e.c. 4.8
g Wholesale and retail trade 4.7
dn Other manufacturing 4.0
F Construction 3.8
h Hotels and restaurants 3.8
dB Textiles and clothing 2.5
dc Leather and footwear 2.1
Source: own calculations using Eurostat data.
iii34 Energy intensity
Energy intensity is defined as the value of the purchases
of energy products used as fuel in the production process
of the sector relative to the value of production and value
added respectively. More precisely, this excludes the energy
products used as intermediate inputs to be transformed
into final products, such as crude oil used to produce
refined oil products in the coke and oil refining sector.
TAbLE III.6: EU energy intensity. Average 2005-07
Quite a few sectors in which the EU has become less
competitive — textiles, leather or clothing — are relatively
energy intensive. But also, some sectors where the EU
is performing well compared to the rest of the world
(Chapter V) are more energy intensive, namely pulp and
paper, non‑metallic mineral products and chemicals,
cf. Table III.6.
code sector Energy/production (%) Energy/va (%)
E Electricity, gas and water supply 12.0 43.8
dJ27 Basic metals 5.6 24.6
dE21 Pulp and paper 5.9 21.7
dF23 Refined petroleum 1.6 19.2
di26 Non‑metallic mineral products 6.1 17.3
dg24 Chemicals 3.1 10.7
dB17 Textiles 3.2 10.5
dn37 Recycling 2.3 9.6
dd20 Wood and wood products 2.4 8.0
dh25 Rubber and plastics 2.5 7.7
da15 Food and drink 1.9 7.6
c Mining and quarrying 2.4 5.8
dc19 Leather and footwear 1.4 5.3
dB18 Clothing 1.4 4.8
dJ28 Metal products 1.6 4.5
F Construction 1.3 3.9
dn36 Furniture; other manufacturing 1.2 3.7
dm34 Motor vehicles 0.7 3.5
dK29 Machinery n.e.c. 0.9 2.8
dl31 Electrical machinery 0.9 2.8
dm35 Other transport eq. 0.7 2.6
dl32 Radio, TV & communic. eq. 0.7 2.5
dE22 Printing and publishing 0.9 2.2
dl33 Scientific and other instruments 0.7 1.7
dl30 Office machinery 0.3 1.6
da16 Tobacco 0.3 1.6
Source: own calculations using Eurostat data.
77

EU industrial structure 2011 — Trends and Performance
iii35 technology
This section presents indicators describing the technology
in EU industries from different aspects. The indicators
R&D expenditures, patenting and developing of new
or improved products represent different stages of the
R&D&I process. While there is a relationship between
these indicators, there is no one‑to‑one correspondence.
78
Expenditures on R&D are indicators on inputs in knowledge
production. Patent statistics are used to calculate output
indicators of knowledge production. Having a patent does
not, however, necessarily mean that the patenting firm
will be able to market a product. Nor does a new product
necessarily mean that there is a patent preceding its
commercialisation. Indicators reflecting the different stages
from R&D to new products are covered in Box III.5 below. 49
box III.5: Using indicators to assess innovation performance across
sectors
In this publication, the approach is specifically sectoral and therefore uses only the indicators linked to EU policies
that will provide a cross‑sector view of innovation inputs and outputs. The indicators chosen are R&D expenditure
and number of patents; they are the most commonly used, but present certain biases that are discussed later in this
box. They tend to estimate manufacturing better than services research activities.
In brief, innovation corresponds to four different categories of progress:
‑ product innovation
‑ process innovation
‑ market innovation
‑ organisational innovation
There are different types of indicators that can be used to capture innovation. Some will typically quantify inputs
while others will measure results of innovation. The various types of indicators are each better suited to measuring
certain types of innovation (product, process, market, and organisation).
input indicators for innovation performance
Research and development (R&D) is one among many activities that may be carried out in an innovation
process. R&D comprises basic research, applied research and experimental development. The indicators are
usually either R&D expenditure spending or number R&D personnel. In a knowledge‑driven economy, R&D
expenditure is not the only sign of innovation. Other types of measure can represent inputs that are supposed
to lead to progress. Expenditures on software, training, organisation, etc. also quantify the innovation effort.
The R&D indicator does not capture innovations in service activities very well. Services innovations often involve software
applications and research in social sciences that are not properly accounted for in R&D expenditure surveys. Such
surveys50 focus more on technological R&D than on social science R&D. 51 As this publication focuses on R&D expenditures,
it reflects the measurement of innovation in manufacturing better than innovation in services. Countries follow different
practices in their national surveys when it comes to allocating R&D expenditures of large, multi‑sector enterprises to the
different economic sectors. Similar R&D expenditure can be categorised in different industries across countries.
Output indicators for innovation performance
There are different ways to mark the outcome of innovation, for example by submitting a patent, creating a new
trademark, publishing an article or delivering new products to the market.
49 See OECD (2007) for a more detailed discussion of different indicators of R&D and innovation.
50 To understand the methodology behind R&D surveys, see OECD (2002).
51 For more information on innovation in services see Miles (2007). For an alternative source of sectoral company-based survey see the
‘2008 EU industrial R&D investment’ European Commission (2008).

Chapter III — Drivers of Sector Growth and Competitiveness
‑ Patent statistics are relevant to the extent that innovations can benefit from patents. The first drawback of
this indicator is that certain types of innovation cannot be patented. For example, the patenting of software
innovations is not the same in the EU and in the US. Therefore industry comparison between EU and extra‑EU
countries is not always straightforward. Second, the quality of patents is not assessed. Many companies
may apply for patents for strategic reasons, without bringing actual innovations onto the market or into
production.
‑ Trademark data, as the results of innovation, are a better proxy for organisational and marketing innovations.
‑ The number of publications in a research domain can be a good proxy to represent ideas creation. Nonetheless,
there are difficulties in comparing this type of output across sectors.
‑ New or significantly improved products on the market
On the whole, there are certain innovations, such as organisational ones, that will be very difficult to assess ex‑post
from a qualitative and quantitative point of view.
the link between input and output
Eventually, research and development efforts will lead to an increase in the stock of knowledge. This knowledge
will turn into new applications and new products. An output to input ratio provides a concrete measure of R&D
performance. The ratio of patents to employment in different sectors is used below. The measure is denoted
by PAT1.
Countries follow different practices in their national surveys when it comes to allocating R&D expenditures of large,
multi‑sector enterprises to the different economic sectors. Similar R&D expenditure can be categorised in different
industries across countries.
Output indicators for innovation performance
There are different ways to mark the outcome of innovation, for example by submitting a patent, creating a new
trademark, publishing an article or delivering new products to the market.
‑ Patent statistics are relevant to the extent that innovations can benefit from patents. The first drawback of
this indicator is that certain types of innovation cannot be patented. For example, the patenting of software
innovations is not the same in the EU and in the US. Therefore industry comparison between EU and extra‑EU
countries is not always straightforward. Second, the quality of patents is not assessed. Many companies
may apply for patents for strategic reasons, without bringing actual innovations onto the market or into
production.
‑ Trademark data, as the results of innovation, are a better proxy for organisational and marketing innovations.
‑ The number of publications in a research domain can be a good proxy to represent ideas creation. Nonetheless,
there are difficulties in comparing this type of output across sectors.
‑ New or significantly improved products on the market
On the whole, there are certain innovations, such as organisational ones, that will be very difficult to assess ex‑post
from a qualitative and quantitative point of view.
the link between input and output
Eventually, research and development efforts will lead to an increase in the stock of knowledge. This knowledge
will turn into new applications and new products. An output to input ratio provides a concrete measure of R&D
performance. The ratio of patents to employment in different sectors is used below. The measure is denoted
by PAT1.
79

EU industrial structure 2011 — Trends and Performance
III.3.5.1 R&D
In 2007, R&D represented 1.85 % of EU GDP in comparison
with 2.67 % in the US, the gap mainly explained by private
investment in R&D. Looking at the sectoral allocation
and not only at the overall amount of R&D injected in the
respective economies brings additional insight into R&D
intensity differences.
To analyse R&D expenditure, an aggregate was formed (an
EU sample of 17 countries) representing more than 80 % of
total R&D expenditure in the EU. The different graphs focus
on the gross domestic expenditure on R&D (GERD) financed
by industry; they do not reflect the sectoral R&D effort by
80
governments. In order to estimate and compare the intensity
of innovation efforts in different sectors, R&D expenditures
were divided by value added generated in the sector. Among
the more R&D intensive sectors, there is only one sector
where the EU significantly outperforms the US: chemicals.
Certain sectors may contribute to a lesser extent to the
overall innovation effort because of their small size.
Nonetheless, they may still be very R&D intensive compared
to the output generated in the sector. One illustration is the
office, accounting and computing machinery sector, which
represents less than 1 % of total value added in the EU
in 2006 but has one of the highest R&D intensities, as high
as 30 % of value added, cf. Figure III.18.
Figure III.18: EU and US R&D expenditure as shares of value added in sectors in 2006 (%)
Radio, TV & communic. eq.
Pharmaceuticals
Other transport eq.
Motor vehicles
Scientic and
other instruments
Oce machinery
Chemicals
Total manufacturing
Machinery nec
Electrical machinery
Rubber and plastics
Rened petroleum
Basic metals
Non-metallic mineral
products
Food, beverages
and tobacco
Textiles, leather
and footwear
Other manufacturing
Metal products
Wood, paper, printing,
publishing
Electricity, gas
and water supply
Total services
Construction
EU US
0 5 10 15 20 25 30 35 40 45 50
Note: The EU is represented by 17 countries: Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary,
Ireland, Italy, Netherlands, Poland, Portugal, Spain, Sweden and the UK. The industries are classified according to ISIC Rev. 3.1.
Source: own calculations using OECD data.

In certain sectors an increase in EU R&D expenditure over time
may be a sign of catch‑up. Some manufacturing sectors that
exhibit above average R&D intensity nonetheless saw their
R&D intensity increase between 1997 and 2007. This is the case
Chapter III — Drivers of Sector Growth and Competitiveness
for Radio, TV and communication equipment, pharmaceuticals
and motor vehicles. Conversely, R&D intensity decreased
during 1997‑2006 in other transport equipment and office,
accounting and computers, cf. Figure III.19.
Figure III.19: EU R&D expenditure as shares of value added in sectors in 1997 and 2006 (%)
Radio, TV & communic. eq.
Pharmaceuticals
Other transport eq.
Motorvehicles
Scientic and other instruments
Oce machinery
Chemicals
Total manufacturing
Machinery nec
Electrical machinery
Rubber and plastics
Rened petroleum
Basic metals
Non-metallic mineral products
Food, beverages and tobacco
Textiles, leather and footwear
Manufacturing n.e.c.
Metal products
Wood, paper, printing, publishing
Electricity, gas and water supply
Total services
Construction
2006 1997
0 5 10 15 20 25 30 35
Note: The EU is represented by 14 countries: Austria, Czech Republic, Denmark, Germany, Greece, Hungary, Ireland, Italy, Netherlands,
Poland, Portugal, Slovak Republic, Slovenia, Spain. The industries are classified according to ISIC Rev. 3.1.
Source: own calculations using OECD data.
III.3.5.2 PATEnTS
Patent statistics are used to calculate indicators for the
output side of knowledge production and, despite the
drawbacks of this indicator, 52 the information is of interest.
Various aspects make patents particularly useful as a proxy
52 Griliches (1990) discusses a number of issues related to patents,
including the advantages and drawbacks. See also Pavitt (1985),
Silverman (2002) and Griliches (1984).
81

EU industrial structure 2011 — Trends and Performance
for technology and technological developments. Patent
statistics refer to the output of the research process
undertaken by firms and sectors. They provide information
on a large number of sectors and technologies and they
permit good coverage of developments over time, which
is particularly interesting. As these data are available for
a large number of countries, it is possible to calculate the
relative performance of the EU, or any other country or
region relative to the world.
Two sectoral indicators based on the number of patents
are used in this section. The first indicator, PAT1, compares
patent intensity across industrial sectors in the EU. It is
computed as the ratio of patents to employment in a sector,
relative to the same ratio for total manufacturing:
where:
PAT : patents filed by EU sector ‘i’
i,EU
PAT : patents filed by EU ‘all sectors’
T,EU
L : employment in EU sector ‘i’
i,EU
L : total employment in the EU
T,EU
Values greater (lower) than 1 indicate that the sector is
more (less) patent‑intensive than the whole economy (and
therefore than all other sectors). The indicator is calculated
82
using data from both the European Patent Office (EPO) and
the US Patent Office (USPO).
The second indicator, PAT2, compares the number of
patents in a given sector in the EU relative to total patents in
the EU with the number of patents in the same sector in the
world relative to total patents in the world. It is therefore,
an indicator of the EU sector’s relative performance in
patenting. It is defined by the following ratio:
where:
PAT : number of patents filed by EU sector ‘i’
i,EU
PAT : number of patents filed by EU ‘all sectors’
T,EU
PAT : number of patents filed by world sector ‘i’
i,W
PAT : number of patents filed by world ‘all sectors’
T,W
Values greater than 1 indicate that the sector has a ‘patent’
specialisation relative to the rest of the world. 53
As PAT1 reflects the number of patents in a sector relative
to employment, it measures patenting intensity across
sectors. 54 As was the case with R&D, this varies substantially
across sectors, from the highest values in two ICT sectors
(office machinery and telecommunications equipment)
to the near‑negligible value for clothing, wood and wood
products, and printing and publishing, cf. Figure III.20.
53 Some studies normalise the specialisation indices such that the
specialisation indices are bounded between -1 and 1. A figure
with normalised indices looks identical as figure III.17 though
re-scaled.
54 The ranking is based on the data from EPO.

Chapter III — Drivers of Sector Growth and Competitiveness
FIgURE III.20: EU-27 sectors by patent intensity (averages in 2005-06 and 2006-07)
Oce machinery
Telecommunication equipment
Watches and clocks
Pharmaceuticals, medicinal chemicals and botanical prod.
Basic chemicals
Radio and TV receivers
Electronic valves and tubes
Optical instruments, photographic equipment
Soap and det., cleaning and pol. prep., perfumes and toilet prep.
Other chemical products
Industrial process control equipment
Rened petroleum
Medical and surgical equipment
Pesticides and other agrochemical products
Lighting equipment and electric lamps
Man-made bres
Domestic appliances n.e.c.
Other special purpose machinery
Motor vehicles
Agricultural and forestry machinery
Other transport eq.
Instruments for measuring, testing and navigating
Machine tools
Accumulators and batteries
Mchinery for the production and use of mech. power
Tobacco
Other general purpose machinery
Electricity distr. and control app., insulated wire and cable
Basic metals
Paints, varn. and similar coat., printing ink and mastics
Weapons and ammunition
Pulp and paper
Rubber and plastics
Non-metallic mineral products
Furniture; other manufacturing
Electric motors, generators and transformers
Metal products
Electrical equipment n.e.c.
Food and drink
Textiles
Leather and footwear
Printing and publishing
Wood and wood products
Clothing
Source: own calculations using Eurostat data.
The second indicator, PAT2 compares the performance
of EU sectors with the same sectors in the world. The
indicator measures specialisation in the patenting process
in the country under analysis. The results for this indicator
show that the EU performs slightly better than the world
USPTO 2005-06 EPO 2005-2006
0 5 10 15 20 25
in a number of sectors. However, the EU specialisation
in patenting is lower than the world average in a range
of R&D‑intensive sectors such as ICT industries and
pharmaceuticals cf. Figure III.21.
83

EU industrial structure 2011 — Trends and Performance
FIgURE III.21: EU sectors by patent performance relative to the rest of the world in 2004-06
84
Agricultural and forestry machinery
Wood and wood products
Metal products
Machine tools
Motor vehicles
Leather and footwear
Machinery for the production and use of mech. power
Rubber and plastics
Other special purpose machinery
Domestic appliances n.e.c.
Clothing
Other general purpose machinery
Furniture; other manufacturing
Weapons and ammunition
Other transport eq.
Tobacco
Industrial process control equipment
Electric motors, generators and transformers
Basic metals
Non-metallic mineral products
Paints, varn. and similar coat., printing ink and mastics
Electricity distr. and control app., insulated wire and cable
Pulp and paper
Textiles
Lighting equipment and electric lamps
Food and drink
Mineral oil rening and nuclear fuel
Other chemical products
Man-made bres
Basic chemicals
Soap and det., cleaning and pol. prep., perfumes and toilet prep.
Instruments for measuring, testing and navigating
Pesticides and other agrochemical products
Printing and publishing
Electrical equipment
Pharmaceuticals, medicinal chemicals and botanical prod.
Optical instruments, photographic equipment
Electronic valves and tubes
Telecommunication equipment
Oce machinery
Medical and surgical equipment
Radio and TV receivers
Watches and clocks
Accumulators and batteries
Source: own calculations using Eurostat data.
III.3.5.3 InnOVATIOn
Innovation activities aim to produce new products. By
engaging in such and activities firms try to commercialise
products bringing something new and/or improved
to customers. Success often provides the firm with an
advantage in that the product is different from other
existing products. This differentiation of the product
reduces the demand elasticity the firm faces and makes it
less reliable on costs and prices to compete.
Manufacturing industries engage relatively more in
innovating activities than services. Firms in industries
USPTO EPO
0.0 0.5 1.0 1.5 2.0 2.5
producing pharmaceuticals, computers and electronic
products, coke and petroleum and chemicals engage
more in innovation than firms in other industries. 55 Services
industries where innovating enterprises are relatively
common are information and communication and financial
and insurance activities, cf. Figure III.22.
55 The figures, calculated as averages for different sectors in the
Member States, should be taken with some caution. The dataset
suffers from lack of observations for a number of countries
and industries. The average for Accommodation is based
on 6 observations, real estate activities and administrative and
support service activities on 7 observations, tobacco is based
on 10 observations, construction on 11 observations coke and
refined petroleum on 13 observations.

Chapter III — Drivers of Sector Growth and Competitiveness
FIgURE III.22: Innovative enterprises as a percentage of all enterprises in the EU-27 in 2008 (%)
Pharmaceuticals
Computer, electronic and optical
Rened petroleum
Chemicals
Tobacco
Machinery n.e.c.
Beverages
Electrical equipment
Information & communication
Basic metals
Rubber and plastics
Financial & insurance activities
Motor vehicles
Other manufacturing
Manufacturing
Other transport eq.
Electricity and gas
Non-metallic mineral products
Metal products
Water supply
Food
Textiles
Paper
Printing
Furniture
Repair of machinery
Professional, Scientic and Technical activities
Leather and footware
Wood and wood products
Clothing
Wholesale and retail trade
Transportation & storage
Real estate activities
Construction
Administration
Accomodation & food
Source: own calculations based on Eurostat data.
Successful outputs of innovating activities are new or
improved products brought to the market. ICT related
manufacturing and services industries seem to be more
successful in developing new and/or improved products
0 10 20 30 40 50 60 70 80
than other industries. On the whole, manufacturing
firms seem more successful than services firms. There are
only two services industries among the top 20 sectors,
cf. Figure III.23. 56
56 The figures should be taken with some caution for the reasons
mentioned in the previous footnote. It should be noted that
there are no observations for the UK.
85

EU industrial structure 2011 — Trends and Performance
FIgURE III.23: Enterprises which introduced new or improved products to the market as a share of all
enterprises engaged in innovation activity in the EU-27 in 2008 (%)
Computer, electronic & optical
Information and communication
Chemicals
Other manufacturing
Motor vehicles
Other transport eq.
Textiles
Electrical equipment
Rened petroleum
Machinery n.e.c.
Pharmaceuticals
Rubber and plastic
Tobacco
Beverages
Professional, scientic and technical activities
Food
Leather and footwear
Manufacturing
Furniture
Repair of machinery
Clothing
Wholesale and retail trade
Non-metallic mineral products
Basic metals
Paper
Metal products
Financial and insurance activities
Wood and wood products
Administration
Water supply
Printing
Construction
Transportation & storage
Accommodation and food
Electricity and gas
Real estate activities
Source: own calculations based on Eurostat data.
III.4 Demand-side drivers:
a sectoral picture
Fluctuations in demand differ among sectors in both size
and timing of fluctuations. Some sectors produce products
which are relatively insensitive to variations in income and
prices while others are more affected by the variations. The
latter were also impacted earlier by both slowdowns and
recoveries. Analyses of fluctuations in consumption and
investment demand can provide useful information about
sectoral performance.
iii41 private consumption
Consumption fluctuates over time for different reasons:
demographic changes, changes in preferences for services
and goods, fluctuations in income and relative prices. While
consumption patterns are extremely stable for certain
goods and services, they appear less so for others.
86
0 10 20 30 40 50 60
Private consumption of services has continued to increase
at the expense of private consumption of goods since 1980.
The share of services consumption was 30 percentage
points larger than the share of goods consumption
in 1980 in constant terms; and the difference in the shares
increased to 48 percentage points in 2009. In spite of
the increase in relative prices in services, this trend can
be explained by changes in preferences and by income
elasticities of demand. Increasing living standards and
incomes lead to higher consumption of products with
high income elasticities at the expense of products whose
income elasticities are lower, cf. Figure III.24. 57
57 The previous publication EU Industrial Structure 2007 — Challenges
and opportunities (‘IV.3 Private consumption’) indicated that
income elasticities of demand are much higher for services
sectors than for goods.

Chapter III — Drivers of Sector Growth and Competitiveness
FIgURE III.24: Shares of goods and services in private consumption in constant and current prices in
seven EU countries from 1980 to 2009
80
70
60
50
40
30
20
10
0
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
Services (Constant)
Services (Current)
Goods (Constant)
Goods (Current)
2002
2003
2004
2005
2006
2007
2008
2009
Note: The seven countries presented are Austria, Denmark, Finland, France, Italy, Netherlands and United Kingdom. Goods sectors include
food and non‑alcoholic beverages, alcoholic beverages, tobacco and narcotics, clothing and footwear, furnishings, household equipment
and routine maintenance of the house. Services sectors include health, transport, communications, recreation and culture, education,
restaurants and hotels, miscellaneous goods and services, housing, water, electricity, gas and other fuels.
Source: calculated using Eurostat data.
A substitution of consumption of goods for services has
taken place between 1980 and 2008. Breaking down
private consumption into large categories in seven
countries shows that food and non‑alcoholic beverages
have fallen to a much lower share of total consumption,
from 19 % to 12 %, while the share of housing and
utilities in total private consumption has risen from 17 %
to 24 % between 1980 and 2009. Changes in the shares of
consumption expenditures across categories may reflect
changes in the level of income (income effects), changes
in relative prices (substitution effects) or government
interventions. First, over long periods of time income
typically increases significantly so that the preference over
different categories changes because households tend to
shift consumption from basic to luxury categories. As an
example, the increase in the share of expenditures in health
services or housing is very likely reflecting an increasing
consumption of services that can be seen as relatively
luxurious; the kind of commodities households tend to
consume more of the richer they are. Second, relative
changes in technology and/or trade patterns can change
relative prices, rendering some commodities cheaper than
others. What will happen with the share in consumption
expenditures will depend on whether the induce changes
in quantities are more or less than proportional to the
price change. For example, the increase in the share
communication services is probably to a large extent
reflecting a drop in the price of communications driving
a more than proportional increase in consumption. In
contrast, large increases in productivity are probably behind
the drop in the relative price of food, and hence the drop
in its share in consumption expenditures compared to, say,
services where productivity grows more slowly. Similarly,
trade probably explains the drop in the relative price of
clothes and its subsequent drop in the share of expenditures
because the eventual increase in consumption does not
compensate for the drop in prices. Finally, cultural changes
due to public awareness campaigns, legal constraints and
taxes may explain other changes like the drop in the share of
alcoholic beverages and tobacco cf. Figure III.25.
87

EU industrial structure 2011 — Trends and Performance
FIgURE III.25: Private consumption shares (current prices) in seven EU countries in 1980 and 2008
88
25
20
15
10
5
0
Alcoholic
beverages,
tobacco and
narcotics
Clothing
and footwear
Communications
Education
Food and
non-alcoholic
beverages
Furnishings, household
equipment and routine
maintenance of the house
Health
Housing, water, electricity,
gas and other fuels
Miscellaneous goods
and services
Recreation and culture
Restaurants and hotels
1980
2008
Transport
Note: The seven countries presented are Austria, Denmark, Finland, France, Italy, Netherlands and United Kingdom. Final consumption
expenditure of households is classified according to consumption purpose (COICOP) for different goods and services.
Source: calculated using Eurostat data.
A detailed overview of the consumption breakdown
in EU‑27 in 2008 offers insight into consumption
patterns. Necessity goods account for the highest
shares of total private consumption, with food, housing,
catering services, clothing and electricity gas and
fuels representing in total more than 50 % of total
consumption. 58 Recreational and cultural services and
financial services only rank eighth and ninth respectively,
cf. Figure III.26.
58 Basic needs are the goods and services that are essential to
achieve a certain minimum standard of living.

Chapter III — Drivers of Sector Growth and Competitiveness
FIgURE III.26: EU-27 sectoral shares of private consumption in 2008 (% of total consumption)
Food
Imputed rentals for housing
Catering services
Operation of personal transport equipment
Clothing
Electricity, gas and other fuels
Actual rentals for housing
Purchase of vehicles
Recreational and cultural services
Financial services n.e.c.
Insurance
Transport services
Telephone and telefax services
Personal care
Furniture and furnishings, carpets and other oor coverings
Tobacco
Other recreational items and equipment, gardens and pets
Audio-visual, photographic and information processing equipment
Water supply and miscellaneous services relating to the dwelling
Goods and services for routine household maintenance
Accommodation services
Alcoholic beverages
Newspapers, books and stationery
Medical products, appliances and equipment
Out-patient services
Maintenance and repair of the dwelling
Non-alcoholic beverages
Other services n.e.c.
Education
Social protection
Footwear including repair
Household appliances
Personal eects n.e.c.
Hospital services
Package holidays
Household textiles
Glassware, tableware and household utensils
Tools and equipment for house and garden
Other major durables for recreation and culture
Telephone and telefax equipment
Postal services
0 2 4 6 8 10 12
Note: Final consumption expenditure of households is classified according to consumption purpose (COICOP) for different goods and
services.
Source: own calculations using Eurostat data.
As EU standards of living are constantly improving,
demand for goods and services with relatively high income
elasticities have been growing faster than demand for
necessity goods. EU average annual growth in constant
prices has increased significantly in communication,
recreation and culture and health. Telephone and telefax
equipment increased by 17.4 % on average, followed by
audio‑visual, photographic and information processing
equipment, telephone and telefax services and financial
services n.e.c. which increased by between 4.5 % and 10 %.
The differences between the EU‑15 and the EU‑27 were
largest in areas where consumption grew much faster in the
EU‑15 than in the rest of the EU. Consumption of package
holidays in the EU‑15 grew by 50 % more than in the EU‑
27 and consumption of alcoholic beverages and electricity,
gas and other fuels grew in the EU‑15 by +0.5 % while it
decreased in the whole of the EU, cf. Figure III.27. 59
59 Figure III.27 includes more categories of goods than Figure III.23.
Some categories are also further broken down in Figure III.24 in
order to provide more information. Figure III.23 shows for
examples that while consumption of alcoholic beverages,
tobacco and narcotics decreased both for EU-15 and EU-27, the
consumption of alcoholic beverages increased in EU-15.
89

EU industrial structure 2011 — Trends and Performance
FIgURE III.27: Private consumption in EU-15 and in EU-27 in 1996 and 2008 (average annual percentage
growth rates in constant prices)
90
Telephone and telefax equipment
Audio-visual, photographic and information processing equipment
Communications
Telephone and telefax services
Financial services n.e.c.
Other major durables for recreation and culture
Recreation and culture
Other recreational items and equipment, gardens and pets
Tools and equipment for house and garden
Package holidays
Medical products, appliances and equipment
Health
Miscellaneous goods and services
Out-patient services
Household appliances
Recreational and cultural services
Imputed rentals for housing
Transport services
Personal care
TOTAL
Hospital services
Goods and services for routine household maintenance
Non-alcoholic beverages
Accommodation services
Housing, water, electricity, gas and other fuels
Restaurants and hotels
Catering services
Education
Other services n.e.c.
Social protection
Maintenance and repair of the dwelling
Water supply and miscellaneous services relating to the dwelling
Furnishings, household equipment and routine maintenance of the house
Actual rentals for housing
Transport
Purchase of vehicles
Clothing
Clothing and footwear
Household textiles
Operation of personal transport equipment
Insurance
Glassware, tableware and household utensils
Footwear including repair
Furniture and furnishings, carpets and other oor coverings
Food and non-alcoholic beverages
Food
Personal eects n.e.c.
Newspapers, books and stationery
Electricity, gas and other fuels
Alcoholic beverages
Alcoholic beverages, tobacco and narcotics
Postal services
Tobacco
EU 27 EU 15
-2 0 2 4 6 8 10 12 14 16 18
Note: Final consumption expenditure of households is classified according to consumption purpose (COICOP) for different goods and
services.
Source: own calculations using Eurostat data.

iii42 investment demand
Gross fixed capital formation (GFCF) is a measure of the
net new investment by enterprises, government and
households in the domestic economy in fixed capital
assets, during an accounting period. GFCF is not a measure
of total investment, as financial assets are not included.
For that reason, this indicator gives a good insight into
investment growth in the real economy. It represents a list
of five product categories: metal products and machinery,
transport equipment, construction work related to housing,
construction work related to construction other than
housing, and other products.
FIgURE III.28: EU-27 investment breakdown in 2010 (% of total current price)
31 %
Construction work:
other constructions
Other products
9 %
Chapter III — Drivers of Sector Growth and Competitiveness
Some assets have an impact on the amount and quality
of production facilities in an economy. This is the case for
metal products and machinery, for construction other than
housing and for transport equipment investments. Others,
such as housing construction work, increase consumer
welfare but do not add substantially to the productive
stock of assets of the private sector. The overall EU picture
in 2010 shows that most of the investments that have taken
place benefit the production facilities of the EU. The three
categories, metal products and machinery, construction
other than housing and transport equipment investments,
represent in total two‑thirds of total investment,
cf. Figure III.28.
25 %
Construction work: housing
Note: The graph intentionally does not include products of agriculture, forestry, fisheries and aquaculture.
Source: own calculations using Eurostat data.
Total investment in the EU grew on average by 1.1 % in the
EU‑27 and 1.6 % in the EU‑15 in 1997‑2010: ‘other products’
was the category with the highest annual growth rate
Metal products
and machinery
26 %
9 %
Transport
equipment
of 4 %. Transport equipment and the metal products and
machinery sector also witnessed substantial growth,
cf. Figure III.29.
91

EU industrial structure 2011 — Trends and Performance
FIgURE III.29: Investment average annual growth rate in the EU-27 and EU-15: 1997-2010 (%)
Construction work: other constructions
92
Other products
Metal products and machinery
Transport equipment
Total
Construction work: housing
EU 27 EU 15
-1% 0% 1% 2% 3% 4%
Note: Calculated from data expressed in constant terms (reference year 2000). The graph intentionally does not include products of
agriculture, forestry, fisheries and aquaculture.
Source: calculated using Eurostat data.
Investment growth in ‘other products’, a heterogeneous
category, displayed the strongest growth. Investment
growth for the other fast growing assets, transport
equipment and metal products and machinery, also show
large variations between Member States. While average
growth in transport equipment is around or above 5 % in
Estonia and Sweden, it is decreasing in the Netherlands and
Portugal. Metals products and machinery investments are
only decreasing in Slovakia while developments in Cyprus
Estonia, and Slovenia were strong. Similarly, investment in
housing construction is very buoyant in Estonia, Lithuania,
Luxembourg, Slovakia and Sweden with growth rates
between 4.5 % and 8 %, cf. Table III.7.
TAbLE III.7: growth in investment levels, average annual growth rates: 1997-2009 (%)
total
metal
products and
machinery
transport
equipment
construction
work: housing
construction
work: other
constructions
Other
products
Belgium 2.0 n.a. n.a. n.a. n.a. n.a.
Bulgaria 12.2 n.a. n.a. n.a. n.a. n.a.
czech republic 1.8 n.a. n.a. n.a. n.a. n.a.
denmark 1.0 1.5 3.5 0.7 ‑2.3 6.2
germany 0.9 n.a. n.a. ‑1.2 ‑1.0 6.4
Estonia 3.6 4.9 5.1 7.0 0.8 19.2
ireland ‑1.5 n.a. n.a. n.a. n.a. n.a.
spain 2.6 2.8 3.2 1.2 3.5 2.8
France 2.6 n.a. n.a. n.a. n.a. n.a.
italy 1.0 1.1 1.9 0.9 0.5 1.3
cyprus 3.7 4.4 4.4 2.6 4.5 n.a.
latvia 5.3 n.a. n.a. n.a. n.a. n.a.
lithuania 3.6 4.3 2.0 4.4 2.2 13.5
luxembourg 3.8 3.8 ‑0.3 4.6 5.2 2.4
hungary 3.2 n.a. n.a. n.a. n.a. n.a.
netherlands 0.8 2.8 ‑1.1 ‑0.5 0.8 1.9
austria 0.7 1.3 1.5 ‑2.2 0.8 7.2
poland 4.2 n.a. n.a. n.a. n.a. n.a.
portugal ‑0.4 3.4 ‑1.9 n.a. ‑4.8 4.4
slovenia 3.2 6.1 3.2 0.3 1.8 5.7
>>>

total
metal
products and
machinery
transport
equipment
Chapter III — Drivers of Sector Growth and Competitiveness
construction
work: housing
construction
work: other
constructions
Other
products
slovakia 0.9 ‑0.2 0.4 8.1 1.1 6.7
Finland 2.1 0.8 1.0 3.2 1.8 5.1
sweden 3.4 3.3 4.8 5.8 1.2 4.9
united Kingdom 2.2 3.5 0.3 ‑0.1 1.8 3.5
Eu‑27 1.7 2.7 2.6 0.2 1.1 3.9
Eu‑25 1.7 2.7 2.5 0.2 1.1 3.9
Eu‑15 1.6 2.7 2.4 0.0 1.0 3.8
Note: Greece, Malta and Romania missing. Calculated from data expressed in volumes (reference year 2000). The table intentionally does
not include products of agriculture, forestry, fisheries and aquaculture.
Source: own calculations using Eurostat data.
93

Chapter IV
International competitiveness
of EU industry
This chapter analyses the international competitiveness of
EU industries. The analyses are performed using trade flows
to calculate indicators of competitiveness and other aspects
of international trade. An analysis of international trade is
important for at least two reasons. First, exports of goods
and services accounted for 13.4 % 60 of EU GDP in 2009;
the figure is substantially higher for some industries,
which shows the importance of international markets for
domestic production. Second, performance in external
trade provides insight into various factors which determine
trade patterns and the competitiveness of EU industries.
This chapter covers trade in both goods and services
and also contains a section on foreign direct investment
(FDI), which is important for understanding the effect of
internationalisation on European industries.
The chapter is organised as follows. Section IV.1 presents an
overall picture of EU relative weight in world trade flows.
Section IV.2 is dedicated to an analysis of competitiveness
from various angles. The competitiveness of EU industries
is analysed using three indicators: share in world markets,
relative trade balance, and revealed comparative advantage.
EU Intra‑industry trade is examined in section IV.3. The
role of technology in international trade is analysed in
section IV.4. Section IV.5 analyses EU trade in intermediate
goods from two perspectives, beginning with, the import
dependence of foreign imports for EU exports. This is
followed by analyses of EU competitiveness in intermediate
goods according to a broad categorisation of goods. Finally,
foreign direct investment by sector is analysed in Section
IV.6 together with indicators of internationalisation of R&D.
IV.1 EU importance in world trade
This section provides a general framework for the analysis
of EU competitiveness in external markets by presenting the
60 Eurostat globalisation indicators.
share of the EU and other regions in cross‑border flows of
goods and services
iv11 goods
The EU‑27 constitutes a large share of world trade in
manufactured goods: exports originating in EU‑27 countries,
including intra‑Eu‑27 trade, accounted for 40.8 % of total
world exports in 2009. The importance of the EU single
market is illustrated by the fact that more than a quarter
of total cross‑border supplies of goods took place within
the EU‑27. Asia and North America are the two other main
trade players and, together with the EU‑27, accounted for
about 84 % of total world export flows, cf. Table IV.1. 61
61 The regions are as follows. Other Western Europe: Iceland,
Norway, Switzerland. Central and Eastern Europe: Albania,
Armenia, Azerbaijan, Belarus, Bosnia Herzegovina, Croatia,
Georgia, Kazakhstan, Montenegro, Rep. of Moldova, Russian
Federation, Serbia, TFYR of Macedonia, Turkey, Ukraine. North
America: Canada, USA. Latin America: Argentina, Bahamas,
Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican
Rep., Ecuador, El Salvador, Guatemala, Haiti, Honduras, Jamaica,
Mexico, Neth. Antilles, Nicaragua, Panama, Paraguay, Peru,
Suriname, Trinidad and Tobago, Uruguay, Venezuela. Middle
East: Bahrain, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Occ.
Palestinian Terr., Oman, Qatar, Saudi Arabia, Syria, United Arab
Emirates, Yemen. Asia: Afghanistan, Bangladesh, Bhutan, Brunei
Darussalam, Cambodia, China, China, Hong Kong SAR, China,
Macao SAR, Dem. People’s Rep. of Korea, India, Indonesia, Japan,
Kyrgyzstan, Lao People’s Dem. Rep., Malaysia, Maldives, Mongolia,
Myanmar, Nepal, Pakistan, Philippines, Rep. of Korea, Singapore,
Sri Lanka, Tajikistan, Thailand, Timor-Leste, Uzbekistan, Viet Nam.
Oceania: Australia, New Zealand. Africa: Algeria, Angola, Benin,
Botswana, Burkina Faso, Burundi, Cameroon, Cape Verde, Central
African Rep., Chad, Comoros, Congo, Côte d’Ivoire, Dem. Rep. of
the Congo, Djibouti, Egypt, Equatorial Guinea, Eritrea, Ethiopia,
Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho,
Liberia Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius,
Morocco, Mozambique, Namibia, Niger, Nigeria, Rwanda, Senegal,
Sierra Leone, Somalia, South Africa, Sudan, Swaziland, Togo,
Tunisia, Uganda, United Rep. of Tanzania, Zambia, Zimbabwe.
95

EU industrial structure 2011 — Trends and Performance
TAbLE IV.1: Manufactured products — export world trade matrix in 2009. Shares of total world
exports (%)
Origin
96
Eu‑27
Other
western
Europe
central
and
Eastern
Europe
north
america
latin
america
middle
East
asia china india Oceania africa world
EU‑27 27.0 1.7 2.1 3.0 0.9 1.2 3.2 1.1 0.4 0.3 1.4 40.8
Other Western
Europe
Central and
Eastern Europe
1.9 0.0 0.1 0.3 0.1 0.1 0.3 0.1 0.0 0.0 0.0 2.8
2.2 0.1 0.6 0.2 0.0 0.3 0.6 0.2 0.1 0.0 0.1 4.2
North America 2.3 0.2 0.1 4.0 2.3 0.5 2.5 0.8 0.2 0.2 0.3 12.4
Latin America 0.7 0.1 0.0 2.4 1.1 0.1 0.8 0.4 0.1 0.0 0.1 5.4
Middle East 0.1 0.0 0.0 0.2 0.0 0.1 0.1 0.0 0.0 0.0 0.0 0.6
Asia 4.9 0.2 0.6 5.0 1.3 1.5 15.2 4.2 0.7 0.8 1.0 30.4
China 2.3 0.1 0.4 2.3 0.5 0.5 4.6 0.0 0.3 0.2 0.5 11.4
India 0.3 0.0 0.0 0.2 0.0 0.4 0.5 0.1 0.0 0.0 0.1 1.6
Oceania 0.1 0.0 0.0 0.1 0.0 0.0 0.9 0.3 0.1 0.1 0.0 1.3
Africa 0.7 0.1 0.0 0.4 0.1 0.1 0.4 0.2 0.1 0.0 0.4 2.1
World 40.0 2.5 3.7 15.5 5.7 3.8 24.0 7.3 1.6 1.5 3.3 100.0
Note: The matrix is calculated from export data. It refers exclusively to manufactured products, so it does not include crude oil and other
products from mining and quarrying. The values in each cell are percentage shares of total world trade. The main diagonal in the matrix
(shaded cells) represents intra‑region trade (e.g. exports from EU countries to EU countries). The matrix shows two countries separately,
China (China and Hong Kong; intra‑China trade set to zero) and India, which are also included in Asia. Each cell shows the share of total
world exports which are exported from an exporter to a certain destination. For example, Asian exports to EU‑27 accounts for 4.9 % of
total world exports and total Asian exports accounts for 30.4 % of total world exports.
Source: own calculations using Comtrade database.
In 2009, the main destination of EU‑27 exports to non‑EU
countries were Asia, North America, and Central and Eastern
Europe, which together amounted to more than 60 % of
total EU‑27 exports. While China was a large destination for
Asian, exports, the Chinese market only accounted for 7.8 %
of EU‑27 exports, cf. Table IV.2. 62
62 The Chinese market is also an important market for exporters
in the Middle East. However, exports from this region only
constitute 1.4 % of total world exports.

Chapter IV — International competitiveness of EU industry
TAbLE IV.2: Manufactured products — world trade matrix, export destination in 2009 (%)
Eu‑27
Other
western
Europe
central
and
Eastern
Europe
north
america
latin
america
middle
East
partner
asia china india Oceania africa world
EU‑27 0.0 12.0 15.2 22.0 6.3 8.9 23.2 7.8 2.6 2.3 10.1 100.0
Other Western
Europe
Central and
Eastern Europe
69.4 0.0 2.2 9.8 1.9 2.9 11.7 2.6 0.9 0.8 1.3 100.0
62.8 4.0 0.0 4.5 1.3 7.4 15.7 6.4 1.7 0.1 4.1 100.0
North America 27.7 2.6 1.8 0.0 27.0 5.4 30.0 9.0 2.0 2.5 3.0 100.0
Latin America 15.9 2.3 0.8 57.0 0.0 1.9 19.1 10.2 1.6 0.5 2.6 100.0
reporter Middle East 22.6 3.5 4.2 33.7 3.2 0.0 26.9 5.1 7.3 1.0 4.8 100.0
Asia 32.0 1.6 4.0 32.5 8.5 10.0 0.0 27.6 4.5 5.0 6.4 100.0
China 20.1 0.5 3.4 20.4 4.8 4.4 40.4 0.0 2.5 1.9 4.1 100.0
India 21.8 0.6 1.7 12.2 3.1 22.5 29.3 6.4 0.0 1.0 8.0 100.0
Oceania 10.8 0.3 0.3 5.2 1.5 2.7 77.8 26.5 9.2 0.0 1.4 100.0
Africa 40.6 4.1 2.3 21.2 4.6 4.9 21.7 8.8 5.5 0.6 0.0 100.0
Note: The matrix is calculated from export data. It refers exclusively to manufactured products, so it does not include crude oil and other
products from mining and quarrying. Exporters are shown in rows and destination markets in columns. Each cell shows the share of total
exports from an exporter to a certain destination. For example, 32% of Asian exports are destined for EU‑27. The main diagonal in the
matrix (shaded cells) shows that intra‑regional trade (e.g. exports from EU countries to EU countries) is excluded in this table. The matrix
shows two countries separately, China (China and Hong Kong) and India, which are also included in Asia.
Source: own calculations using Comtrade database.
When intra‑regional trade is not taken into account,
EU‑27 imports came mainly from Asia (28 %) and North
America (25 %). Along with Asia, the EU‑27 occupy almost
two thirds of North American imports, cf. Table IV.3.
97

EU industrial structure 2011 — Trends and Performance
TAbLE IV.3: Manufactured products — world import structures by origin of imports in 2009 (%)
reporter
98
Eu‑27
Other
western
Europe
central
and
Eastern
Europe
north
america
latin
america
partner
middle
East
asia china india Oceania africa
EU‑27 0.0 65.0 65.4 32.3 17.3 12.9 37.1 23.0 27.9 8.5 43.6
Other Western
Europe
Central and
Eastern Europe
13.3 0.0 1.2 1.9 0.6 0.3 1.4 0.7 0.8 0.3 1.2
13.8 2.5 0.0 2.5 1.2 2.0 4.8 3.2 3.0 0.8 2.2
North America 24.7 9.9 8.4 0.0 55.7 12.4 36.6 24.3 17.7 6.3 21.9
Latin America 6.9 2.1 1.4 23.6 0.0 0.9 8.6 5.4 4.1 1.6 3.7
Middle East 3.3 2.2 1.9 2.0 0.7 0.0 2.1 0.8 3.1 1.5 1.1
Asia 28.3 16.3 17.3 32.8 22.1 66.2 0.0 38.0 34.4 79.4 25.8
China 10.2 3.2 8.2 10.5 12.5 11.0 26.5 0.0 10.5 28.2 13.2
India 3.0 4.0 1.9 2.0 1.6 13.6 4.3 2.1 0.0 8.4 6.3
Oceania 2.8 0.9 0.3 2.6 0.5 0.9 5.2 2.3 1.3 0.0 0.4
Africa 6.9 1.1 4.1 2.2 1.9 4.3 4.1 2.3 7.7 1.7 0.0
World 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Note: The matrix is calculated from import data. It refers exclusively to manufactured products, so it does not include crude oil and other
products from mining and quarrying. Detailed import data from India were not available for 2008 in the chosen trade classification
(HS2007). The first column for instance shows a breakdown of EU imports from the RoW by origin: Asia has the highest share in EU imports
from the RoW (28.3) followed by North America (24.7) The first row show that e.g. 32.3 % of North American imports originate in the EU‑27.
Source: own calculations using Comtrade database.
iv12 services
No data are available on multilateral trade flows for services
and the information presented is limited to exports and
imports by region, shown in graphical format. 63
63 The regions are as follows, based on data availability that differed
from data availability in manufacturing trade. Other Western
Europe: Iceland, Norway, Switzerland. Central and Eastern Europe:
Albania, Armenia, Rep. of Azerbaijan, Belarus, Bosnia & Herzegovina,
Croatia, Georgia, Kazakhstan, Macedonia, Moldova, Montenegro,
Serbia, Turkey, Ukraine. North America: Canada, USA. Latin
America: Argentina, Aruba, Bermuda, Bolivia, Brazil, Chile, Costa
Rica, El Salvador, Guatemala, Honduras, Panama, Paraguay, Peru,
Uruguay. Middle East: Israel, Kuwait, Saudi Arabia. Asia: Bangladesh,
Cambodia, China, Hong Kong, India, Indonesia, Japan, Republic
of Korea, Kyrgyz Republic, Macao, Malaysia, Pakistan, Philippines,
Russian Federation, Singapore, Sri Lanka, Thailand. Oceania:
Australia, New Zealand. Africa: Botswana, Cameroon, Cape Verde,
Côte d’Ivoire, Ethiopia, The Gambia, Guinea, Kenya, Mali, Mauritius,
Morocco, Mozambique, Namibia, Seychelles, South Africa, Sudan,
Tanzania, Togo, Tunisia, Uganda, Zambia.
The EU accounts for about half of world exports of services
when intra‑regional trade is included. When intra‑regional
trade is excluded, Asia’s share of world exports is almost as
large as the EU share, cf. Figure IV.1.

FIgURE IV.1: EU accounts for almost half of world exports of services (%)
EU-27
Other Western Europe
Central and Eastern Europe
North America
Latin America
Middle East
Asia excluding China and India
China
India
Oceania
Africa
Chapter IV — International competitiveness of EU industry
Excluding intra-regional trade
Including intra-regional trade
0 10 20 30 40 50 60
Note: The regions corrected for intra‑regional trade are EU‑27 and North America.
Source: IMF balance of payments statistics (BOPS), UN services trade statistics, Eurostat.
The EU also accounts for the largest share of total world
imports of services when intra‑EU‑27 is included. Asia and
FIgURE IV.2: EU accounts for most of world imports of services (%)
EU-27
Other Western Europe
Central and Eastern Europe
North America
Latin America
Middle East
Asia excluding China and India
China
India
Oceania
Africa
Excluding intra-regional trade
Including intra-regional trade
0 10 20 30 40 50
Note: The regions corrected for intra‑regional trade are EU‑27 and North America.
Source: IMF balance of payments statistics (BOPS), UN services trade statistics, Eurostat.
the EU‑27 are on par when intra‑regional trade for the
EU‑27 and North America is excluded, cf. Figure IV.2.
99

EU industrial structure 2011 — Trends and Performance
IV.2 EU manufacturing and services
competitiveness by sector
While the previous section looked at overall trade flows, this
section looks at EU sectoral performance. It analyses first
the destination and origin of manufacturing exports and
imports. Then it discusses the EU’s trade competitiveness
with the aid of three indicators: the share of the EU in the
world market, the relative trade balance (RTB), and an
index of revealed comparative advantage (RCA). 64 These
indicators are used to describe EU competitiveness in
external trade in goods. 65 Only the revealed comparative
advantage (RCA) is presented for services. The indices are
calculated from trade flows, and are assumed to reveal the
strongest sectors in each of the countries and regions for
which they are calculated, measuring their comparative
advantage. The indices are applied to various sectoral
classifications to clarify the nature of the comparative
advantage in each case. In this section the indicators are
presented for a breakdown of manufacturing into 23 groups
of products. 66 By way of comparison, section IV.4 analyses
trade in manufacturing for products grouped into
technology categories.
iv21 Eu trade in manufactures by
destination
The EU mainly trades with partners of similar level of
development, but there are noticeable variations across
sectors. It is worth underlining that the analyses below only
refer to manufactured goods, so agriculture and mining
(including energy) products are not included. This has
a significant effect on the shares of some trade partners,
as in the case of Russia and the oil‑producing countries.
In 2009, Russia represented more than a third of EU imports
in refined petroleum. The shares of the main trade partners
64 See Balassa (1965) for a discussion of the RCA-index.
65 They were calculated for different time periods (to test for the
sensitivity to the financial crisis) and the crisis appeared to have
no significant impact on the data.
66 The sectors considered are manufacturing industries at the
two-digit level in the Classification of Products by Activity (CPA).
100
in EU manufacturing trade are concentrated in high income
and upper medium income partners. 67
In all manufacturing sectors except textiles, paper,
machinery, electrical equipment and basic metals, about
half or more of EU‑27 exports were destined for high
income countries in 2009, cf. Table IV.4.
The picture differs for imports. The EU imports more
than half of its textiles, clothing, footwear, non metallic
mineral products and furniture from low medium income
countries. Low income countries exports to the EU reach
a level above 10 % only in textiles, clothing and leather
and footwear. US exports to the EU are significant in
other transport equipments and pharmaceuticals,
representing 53 % and 47 % respectively of EU imports. Japan
is a large source of EU imports for motor vehicles (32 %)
and machinery (18 %). Finally, the BRIC group is presented
both as an aggregate and in terms of its separate members,
Brazil, Russia India and China. Overall, Russia, Brazil and India
count much less than China as far as EU trade is concerned.
More than 40 % of EU imports in furniture (54 %), leather
and footwear (52 %), clothing (45 %), electrical equipment
(44 %), non‑metallic mineral products (43 %), metal products
(41 %) come from China. Brazil captures 14 % and 12 % of EU
imports of paper and food, cf. Table IV.5.
67 The classification by income level is the one from the World
Bank. The country groups are as follow: High non‑EU: Australia,
Bahamas, Bahrain, Brunei Darussalam, Canada, Croatia, China
Hong Kong SAR, Iceland, Israel, Japan, Rep. of Korea, Kuwait,
China Macao SAR, Oman, Neth. Antilles, New Zealand, Norway,
Qatar, Saudi Arabia, Singapore, Switzerland, United Arab Emirates,
USA. Upper‑medium: Algeria, Argentina, Bosnia Herzegovina,
Botswana, Brazil, Belarus, Chile, Colombia, Costa Rica, Cuba,
Dominican Rep., Equatorial Guinea, Gabon, Jamaica, Kazakhstan,
Lebanon, Libya, Malaysia, Mauritius, Mexico, Montenegro,
Namibia, Panama, Russian Federation, Serbia, South Africa,
Suriname, Trinidad and Tobago, Turkey, TFYR of Macedonia,
Uruguay, Venezuela. Low‑medium: Albania, Angola, Azerbaijan,
Armenia, Bolivia, Belize, Cameroon, Cape Verde, Sri Lanka, China,
Ecuador, El Salvador, Djibouti, Georgia, Guatemala, Honduras,
Indonesia, Iran, Iraq, Côte d’Ivoire, Jordan, Lesotho, Maldives,
Mongolia, Rep. of Moldova, Morocco, Nicaragua, Nigeria,
Paraguay, Peru, Philippines, Timor-Leste, India, Swaziland, Syria,
Thailand, Tunisia, Ukraine, Egypt. Low: Afghanistan, Bangladesh,
Bhutan, Myanmar, Burundi, Cambodia, Central African Rep.,
Chad, Comoros, Congo, Dem. Rep. of the Congo, Benin, Ethiopia,
Eritrea, Gambia, Ghana, Guinea, Haiti, Kenya, Dem. People’s Rep.
of Korea, Kyrgyzstan, Lao People’s Dem. Rep., Liberia, Madagascar,
Malawi, Mali, Mauritania, Mozambique, Nepal, Niger, Pakistan,
Guinea-Bissau, Rwanda, Senegal, Sierra Leone, Viet Nam, Somalia,
Zimbabwe, Sudan, Tajikistan, Togo, Uganda, United Rep. of
Tanzania, Burkina Faso, Uzbekistan, Yemen, Zambia.

TAbLE IV.4: EU exports of manufactured goods in 2009 by destination (%)
usa Japan Bric Brazil china india russia
low
income
low
medium
upper
medium
high
income
nacE cOdE
income
income
non Eu‑27
c10 Food 50.2 28.6 18.3 5.1 11.0 5.7 17.1 1.3 3.9 0.3 11.7
c11 Beverages 71.7 16.8 9.4 2.7 35.4 6.4 9.0 1.6 3.0 0.3 4.1
c12 Tobacco 55.5 24.0 19.7 3.8 1.2 22.4 3.1 0.2 0.9 0.0 1.9
c13 Textiles 39.6 27.1 33.7 3.6 10.1 2.8 12.4 1.1 5.5 1.1 4.7
c14 Clothing 56.8 30.1 12.4 2.4 8.9 6.2 17.8 0.3 1.9 0.2 15.4
c15 Leather & footwear 65.7 20.3 14.0 1.2 13.4 10.0 14.1 0.2 4.4 1.0 8.5
c16 Wood & wood products 56.7 22.5 20.0 1.6 8.7 8.9 8.8 0.2 2.3 0.6 5.7
c17 Paper 41.6 33.4 23.8 2.4 9.2 2.3 21.4 2.0 5.7 2.7 11.1
c18 Printing 55.9 30.4 13.2 1.2 12.1 6.6 16.3 3.2 3.4 1.0 8.7
c19 Refined petroleum 52.7 22.9 19.9 5.7 27.5 0.5 3.5 0.8 0.5 0.6 1.7
c20 Chemicals 53.8 25.7 19.2 2.0 23.9 4.7 18.8 3.2 7.1 2.4 6.0
c21 Pharmaceuticals 69.2 19.4 9.6 2.3 36.3 5.7 11.4 2.4 3.0 0.6 5.4
c22 Rubber & plastics 50.8 29.6 19.7 1.8 13.9 2.3 18.1 2.2 6.2 1.6 8.2
c23 Non‑metalic mineral products 55.1 25.2 18.6 2.3 16.8 2.5 14.9 1.5 4.1 1.7 7.6
c24 Basic metals 47.2 25.3 26.3 2.0 12.6 1.4 19.1 2.2 9.5 4.5 3.0
c25 Metal products 49.6 27.7 21.0 2.8 13.2 2.2 18.2 2.1 6.2 2.5 7.3
Chapter IV — International competitiveness of EU industry
c26 Computers, electronic & optical 54.4 23.9 19.8 2.7 18.8 3.6 18.5 1.5 7.6 3.0 6.4
c27 Electrical equipment 46.1 25.6 26.2 3.1 13.2 1.8 23.5 2.2 11.4 2.6 7.2
c28 Machinery n.e.c. 43.7 25.7 28.4 2.9 14.3 2.1 26.0 2.8 12.8 3.6 6.8
c29 Motor vehicles 50.2 28.4 20.0 1.9 21.0 4.4 20.2 2.6 10.5 0.8 6.3
c30 Other transport eq. 62.4 18.9 16.9 2.0 27.9 1.4 17.4 2.0 8.5 3.0 3.9
c31 Furniture 64.5 22.1 12.9 1.5 15.2 2.4 16.1 0.5 3.0 0.7 11.9
c32 Other manufacturing 70.3 15.7 13.0 1.5 24.5 5.7 10.8 1.2 3.4 2.2 3.9
Note: Intra‑EU regional trade is excluded. The shares do not add up to 100 since the US, Japan and the BRIC countries are included in the aggregates by income.
Source: own calculations using Comtrade database.
101

EU industrial structure 2011 — Trends and Performance
TAbLE IV.5: EU imports of manufactured goods by origin (2009 in %)
102
usa Japan Bric Brazil china india russia
low
income
low
medium
upper
medium
high
income
nacE cOdE
income
income
non Eu‑27
c10 Food 21.5 41.3 33.0 5.3 4.9 0.2 22.7 12.2 6.7 2.5 1.4
c11 Beverages 51.6 45.4 3.8 0.2 20.1 0.4 3.0 0.3 0.7 0.2 1.7
c12 Tobacco 19.5 58.2 17.4 6.5 7.9 0.2 19.4 10.0 4.6 1.7 3.1
c13 Textiles 14.4 20.2 54.7 11.8 3.7 1.5 47.3 0.3 35.2 11.6 0.3
c14 Clothing 3.5 16.1 67.2 14.8 0.6 0.1 52.6 0.0 45.1 7.5 0.0
c15 Leather & footwear 5.3 8.7 72.0 14.7 1.0 0.1 62.9 3.2 52.2 7.1 0.3
c16 Wood & wood products 20.3 32.3 44.4 3.6 7.3 0.1 46.3 7.4 27.0 0.6 11.4
c17 Paper 52.6 30.1 17.5 0.2 20.0 1.4 31.0 13.7 12.1 0.6 4.5
c18 Printing 71.3 5.5 23.4 0.0 6.4 13.6 23.3 0.9 21.1 0.4 0.9
c19 Refined petroleum 35.7 55.0 9.5 0.1 11.9 1.0 43.1 0.6 0.7 4.4 37.4
c20 Chemicals 66.5 16.5 17.0 0.4 26.8 8.4 19.7 2.3 8.8 3.1 5.5
c21 Pharmaceuticals 91.3 2.0 6.9 0.0 47.3 3.3 7.2 0.6 4.6 1.9 0.0
c22 Rubber & plastics 44.9 15.3 39.1 1.3 15.2 7.8 33.8 0.9 29.7 2.4 0.9
c23 Non‑metalic mineral products 29.0 18.7 52.6 1.7 11.7 4.6 49.5 1.5 42.9 4.1 1.1
c24 Basic metals 41.9 40.9 16.2 3.1 7.1 3.3 24.8 2.3 6.4 2.2 13.9
c25 Metal products 40.0 11.5 48.1 1.1 11.4 5.3 46.1 0.6 41.1 3.7 0.7
c26 Computers, electronic & optical 44.1 7.9 47.7 0.4 12.4 11.0 41.9 0.1 41.1 0.6 0.1
c27 Electrical equipment 37.8 10.9 51.8 0.2 11.1 7.8 46.6 0.6 44.1 1.6 0.3
c28 Machinery n.e.c. 64.9 9.5 25.9 0.3 24.5 18.4 24.6 1.3 21.3 1.6 0.4
c29 Motor vehicles 56.6 27.6 16.3 0.1 11.4 32.2 12.4 1.9 5.3 4.9 0.3
c30 Other transport eq. 83.4 5.7 9.5 1.6 52.9 2.8 10.9 2.0 8.0 0.3 0.6
c31 Furniture 11.6 16.0 66.1 7.2 2.3 0.4 59.0 2.4 53.6 2.1 0.9
c32 Other manufacturing 46.5 5.5 47.0 1.2 23.7 5.2 41.7 0.2 37.3 3.8 0.4
Note: Intra‑EU regional trade is excluded. The shares do not add up to 100 since the US, Japan and the BRIC countries are included in the aggregates by income.
Source: own calculations using Comtrade database

iv22 Export market shares
Export market shares provide insight into the position
relative to international competitors. Gains or loss of
market share indicates whether an EU industry is gaining
competitiveness, or not, on the world market, cf. Box IV.1.
box IV.1: Share in world markets
The share of sector ‘i’in world markets is defined as:
Share of sector ‘i’ = EU exports to world market in sector ‘i’/ Total world exports in sector ‘i’
where, ‘world’ is defined as EU‑27 + US, Japan, and a selected group of countries.
For the EU the share is calculated including and excluding intra‑EU trade.
Largest EU export shares in 2009, when intra‑regional trade
is included) were recorded for printing and reproduction
of recorded media, beverages, tobacco products,
pharmaceuticals, paper and paper products and furniture.
When intra‑regional trade in the EU is excluded, US
industries hold larger shares than the EU of world exports
of computer, electronic and optical products and other
manufacturing. Japanese industries held large shares of
world exports of motor vehicles, trailers and semi‑trailers
and machinery and equipment; however, EU industries
(excluding intra‑regional trade) had even larger shares of
world exports. China, besides having the largest shares of
clothing, leather and footwear and textiles, holds relatively
Chapter IV — International competitiveness of EU industry
large market shares in computer, electronic and optical
products, furniture, and electrical equipment and fabricated
metal products, cf. Table IV.6. 68
68 The market share approach favours large countries; therefore, it is
more relevant to compare the EU as a whole with the US, Japan,
China, India, Brazil and Russia. The initial size of an economy may
matter in its ability to seek foreign markets. Larger countries may
benefit from more resources as far as capital, labour or other factors
of production are concerned. Large countries may also benefit from
economies of scale as they have larger domestic markets.
103

EU industrial structure 2011 — Trends and Performance
TAbLE IV.6: Share of EU and main trade partners in world markets by sectors in 2009
104
Japan usa Bric Brazil china russia india
Eu‑without
intra‑regional trade
commodity description Eu‑27
c10 Food 46.8 14.8 0.5 8.2 12.7 5.5 4.7 0.8 1.7
c11 Beverages 69.0 48.4 0.3 6.0 1.9 0.1 1.2 0.5 0.2
c12 Tobacco 68.3 30.3 0.4 2.6 5.5 0.7 1.9 2.1 0.8
c13 Textiles 29.5 11.4 2.7 4.8 37.2 0.5 32.0 0.1 4.6
c14 Clothing 32.5 10.3 0.1 1.4 39.3 0.1 35.2 0.0 4.0
c15 Leather & footwear 38.6 16.2 0.2 1.9 37.0 2.1 32.5 0.1 2.2
c16 Wood & wood products 50.1 21.4 0.1 5.2 19.4 2.2 12.1 4.8 0.2
c17 Paper 57.2 25.1 1.5 10.7 9.3 3.0 4.7 1.4 0.3
c18 Printing 76.0 49.4 1.1 6.1 4.0 0.3 1.9 0.1 1.7
c19 Refined petroleum 32.8 14.8 2.4 9.4 20.6 0.7 3.3 11.4 5.2
c20 Chemicals 49.5 24.8 5.7 13.1 9.9 1.1 5.6 1.7 1.5
c21 Pharmaceuticals 65.5 41.9 1.0 10.1 4.3 0.3 2.6 0.1 1.4
c22 Rubber & plastics 50.2 19.2 6.1 9.3 13.6 0.8 11.5 0.4 0.9
c23 Non‑metallic mineral products 50.2 24.0 5.3 6.3 20.7 1.2 17.4 0.8 1.3
c24 Basic metals 35.0 14.2 7.1 6.4 14.6 2.1 5.8 4.9 1.8
c25 Metal products 49.3 23.3 3.8 8.2 18.9 0.9 16.2 0.5 1.3
c26 Computers, electronic & optical 24.3 9.7 6.7 9.3 24.5 0.2 23.8 0.1 0.4
c27 Electrical equipment 41.7 21.3 6.4 8.0 19.6 0.6 18.0 0.3 0.7
c28 Machinery n.e.c. 50.3 32.9 9.4 12.3 10.9 0.7 9.1 0.3 0.7
c29 Motor vehicles 55.5 24.8 12.1 8.7 4.5 1.0 2.8 0.2 0.6
c30 Other transport eq. 49.0 34.8 8.6 4.5 13.4 1.5 9.6 0.7 1.6
c31 Furniture 50.9 21.5 0.8 4.2 27.0 0.8 25.5 0.3 0.5
c32 Other manufacturing 32.0 16.3 2.6 14.3 23.9 0.2 14.1 0.1 9.5
Source: own calculations using COMTRADE data.

iv23 sectoral trade balance
The relative trade balance (RTB), measures the trade
balance relative to total trade in the sector. This indicator
box IV.2: Relative trade balance (RTb) indicator
The RTB indicator for product ‘i’ is defined as follows:
where X=value of exports and M=value of imports.
Chapter IV — International competitiveness of EU industry
is calculated for the EU relative to the rest of the world. It is
used to rank EU sectors according to their competitiveness
vis‑à‑vis the rest of the world and to measure gains and
losses in competitiveness over time, cf. Box IV.2.
This indicator is based on EU‑25 trade with the rest of the world. The source of the data is the UN database
COMTRADE.
A negative trade balance is not necessarily a bad sign.
Imports can contribute to the country’s economy and
may stimulate production in other sectors. Also, trade
balances are dependant on domestic and foreign demand.
This means that this indicator does not exclusively reflect
external competitive strength; it also indicates a difference
between domestic and international demand.
TAbLE IV.7: EU RTb indicators in manufacturing sectors from 2007 to 2009
EU industries recorded their highest RTB values in 2009 for
beverages, machinery and equipment, other transport
equipment and fabricated metal products. EU RTBs
increased between 2009 and 2008 in basic metals,
machinery and equipment, paper and chemical products.
EU RTBs were notably negative for wearing apparel and
computer, electronic and optical products, cf. Table IV.7.
nacE code 2007 2008 2009
c10 Manufacture of food products ‑0.03 ‑0.03 ‑0.03
c11 Manufacture of beverages 0.21 0.20 0.20
c12 Manufacture of tobacco products 0.03 0.06 0.06
c13 Manufacture of textiles ‑0.01 ‑0.01 ‑0.02
c14 Manufacture of wearing apparel ‑0.19 ‑0.19 ‑0.21
c15 Manufacture of leather and related products ‑0.07 ‑0.07 ‑0.08
c16
Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles
of straw and plaiting materials
0.00 0.02 0.04
c17 Manufacture of paper and paper products 0.04 0.04 0.06
c18 Printing and reproduction of recorded media 0.08 0.05 0.04
c19 Manufacture of coke and refined petroleum products ‑0.03 ‑0.01 ‑0.05
c20 Manufacture of chemicals and chemical products 0.03 0.03 0.05
c21 Manufacture of basic pharmaceutical products and pharmaceutical preparations 0.07 0.08 0.08
c22 Manufacture of rubber and plastic products 0.04 0.04 0.04
c23 Manufacture of other non‑metallic mineral products 0.08 0.08 0.09
c24 Manufacture of basic metals ‑0.06 ‑0.03 0.01
c25 Manufacture of fabricated metal products, except machinery and equipment 0.09 0.09 0.10
c26 Manufacture of computer, electronic and optical products ‑0.11 ‑0.11 ‑0.11
c27 Manufacture of electrical equipment 0.07 0.08 0.08
c28 Manufacture of machineryand equipment n.e.c. 0.16 0.17 0.20
c29 Manufacture of motor vehicles, trailers and semi‑trailers 0.06 0.08 0.08
c30 Manufacture of other transport equipment 0.13 0.11 0.11
c31 Manufacture of furniture 0.04 0.04 0.03
c32 Other manufacturing ‑0.04 ‑0.04 ‑0.04
Note: Due to the transition from NACE Rev. 1 to NACE Rev. 2, the data are not completely comparable with the previous edition.
Data according to NACE Rev. 2 are only available from 2007.
Source: own calculations using Comtrade data.
105

EU industrial structure 2011 — Trends and Performance
iv24 revealed comparative advantage
The third indicator of competitiveness is the index of
revealed comparative advantage (RCA), which compares
the share of a given sector’s exports in the EU’s total
manufacturing exports with the share of the same sector’s
106
exports in the total manufacturing exports of a group of
reference countries. Values higher (lower) than 1 mean that
a given industry performs better (worse) than the reference
group, and are interpreted as a sign of comparative
advantage. The RCA indicator is thus used to rank EU
products by comparative advantage, cf. Box IV.3.
box IV.3: Revealed comparative advantage (RCA) indicator
The RCA indicator for product ‘i’ is defined as follows:
where: X=value of exports; the reference group (‘W’) is the EU‑27 plus 142 other countries (as listed in Section
IV.1.1 Goods); the source used is the UN COMTRADE database. In the calculation of RCA, XEU stands for exports to
the rest of the world (excluding intra‑EU trade) and XW measures exports to the rest of the world by the countries
in the reference group.
IV.2.4.1 RCA In MAnUFACTURES
In 2009, the EU‑27 recorded RCAs above 1.6 for industries
producing printing, beverages, and tobacco products.
At the bottom of the graph, computer, electronic and
optical products, textiles, other manufacturing, clothing
and refined petroleum have an index lower than 0.8.
When interpreting the results some considerations
should be taken into account: first, the level of sectoral
aggregation may mask differing performance in various
categories of goods within the same group of products.
This is particularly relevant for industries which have
a large variety of brands and quality levels for the same
type of goods. Another consideration concerns country
heterogeneity within the EU, as the performance of the EU
as a whole is explained in some cases by the performance
of a few EU countries. Finally, the weight of each sector and
country in the export structure of the EU should be borne
in mind to get to a balanced assessment of the EU’s sectoral
performance in external trade, cf. Figure IV.3.

FIgURE IV.3: EU-27 RCA index in 2009
Printing
Beverages
Tobacco
Pharmaceuticals
Paper
Motor vehicles
Furniture
Machinery n.e.c.
Rubber & plastics
Non-metallic mineral products
Wood & wood products
Chemicals
Metal products
Other transport eq.
Food
Electrical equipment
Leather & footwear
Basic metals
Rened petroleum
Clothing
Other manufacturing
Textiles
Computers, electronic & optical
Chapter IV — International competitiveness of EU industry
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
Source: own calculations using COMTRADE data.
Cyprus, Greece, Lithuania, Luxembourg, the Netherlands,
Portugal and Romania, all appeared to be highly specialised in
tobacco products in 2009. Wood and wood products is another
category of goods where many EU countries recurrently exhibit
high revealed comparative advantages. The high RCAs in
wood and wood products of Austria, Estonia, Finland, Latvia
and Portugal are in line with the specialisation patterns that
could be observed in Section II.1 (Table II.2). Interestingly, only
Finland and Sweden are the only countries which are highly
specialised in paper and paper products. Cyprus and Ireland,
followed by Belgium appear to be significant players in basic
pharmaceutical products. In Ireland, this is also coupled with
high RCAs in chemical products. Bulgaria and Romania are
the only EU remnants that still had high revealed comparative
advantages in trade of wearing apparel while Portugal,
Italy and Romania have important revealed comparative
advantages in leather and related products.
In reference to Section II.1.2, and as illustrated in Figure II.6,
smaller countries tend to have stronger specialisation
patterns. This also applies to sectoral trade characteristics.
A problem with the RCA measure is that countries with
a relatively small manufacturing industry can turn out to
have high RCAs even though the industry with the high
RCA only consists of a few firms but accounts for a large
share of total manufacturing exports in the country. Natural
examples in the EU are Cyprus, Luxemburg and Malta where
some industries display very high RCAs.
Compared to the EU, the US seemed to have high
revealed comparative advantages in the following groups
of products in 2009: other manufacturing, computer,
electronic and optical products, chemicals, refined
petroleum products and machinery, and equipment.
Japan had high RCAs in capital equipment, particularly
motor vehicles and machinery. In China, the trade
specialisation profile is strongly oriented towards textiles,
clothing, leather and furniture; although China also
has a high RCA in sectors such as office machinery and
computers, cf. Table IV.8.
107

EU industrial structure 2011 — Trends and Performance
TAbLE IV.8: RCA in manufacturing in 2009: EU countries, US, Japan and brazil, China and Russia
108
c10 c11 c12 c13 c14 c15 c16 c17 c18 c19 c20 c21 c22 c23 c24 c25 c26 c27 c28 c29 c30 c31 c32
Non‑
Comput‑ Electri‑
Wood
Refined
Rubber
Metal
Ma‑
Other
Other
Leather &
Chemi‑ Pharma‑ metallic Basic ers, elec‑ cal
Motor
Furni‑
Food Beverages Tobacco Textiles Clothing & wood Paper Printing petro‑
& plas‑
prod‑
chinery
trans‑
manu‑
footwear
cals ceuticals mineral metals tronic & equip‑ vehicles
ture
products
leum
tics
ucts
n.e.c.
port eq. facturing
products
optical ment
Austria 0.92 2.06 0.85 0.71 0.55 0.75 4.45 2.23 1.30 0.26 0.50 1.33 1.36 1.40 1.24 1.98 0.41 1.34 1.47 1.27 0.71 1.42 0.78
Belgium 1.35 1.08 0.98 0.87 0.78 1.02 0.83 0.96 7.21 1.06 2.10 3.40 1.06 1.13 1.04 0.72 0.22 0.43 0.68 1.16 0.24 0.60 1.12
Bulgaria 1.45 0.94 3.10 1.37 3.73 1.31 1.56 0.42 0.29 2.61 0.56 0.69 0.82 2.18 2.83 0.66 0.30 1.11 0.72 0.29 0.34 1.39 0.33
Cyprus 2.06 1.43 34.64 0.11 0.55 0.42 0.24 0.40 0.23 0.00 0.53 4.53 0.37 0.39 0.37 0.63 0.92 0.30 0.55 0.33 1.52 0.80 2.69
Czech Rep. 0.47 0.74 1.54 0.93 0.38 0.39 1.53 1.04 1.32 0.17 0.50 0.28 1.70 1.83 0.67 2.01 0.98 1.51 1.15 2.17 0.51 1.49 0.78
Denmark 3.08 0.77 1.86 0.73 1.53 0.79 1.31 0.69 0.99 0.73 0.62 1.28 1.18 1.50 0.35 1.57 0.49 1.18 1.53 0.33 0.61 2.75 0.86
Estonia 1.23 2.08 0.45 1.49 1.13 0.65 8.16 0.78 0.01 3.48 0.68 0.10 1.31 1.60 0.42 1.90 0.39 1.42 0.65 1.13 0.29 3.00 0.54
Finland 0.33 0.51 0.02 0.23 0.16 0.26 4.79 8.57 0.75 1.49 0.58 0.44 0.86 0.78 1.19 0.97 0.78 1.51 1.57 0.36 1.30 0.29 0.49
France 1.18 3.94 0.59 0.60 0.73 1.05 0.66 1.05 1.15 0.58 1.33 1.69 1.12 0.98 0.76 0.92 0.43 0.92 0.88 1.22 3.23 0.66 0.76
Germany 0.78 0.66 1.80 0.54 0.51 0.38 0.87 1.24 2.43 0.29 1.05 1.33 1.29 1.03 0.77 1.24 0.54 1.17 1.62 1.77 1.35 0.85 0.64
Greece 2.70 1.81 5.69 1.75 2.14 0.71 0.56 0.73 1.47 2.10 0.90 1.65 1.25 2.57 1.96 1.01 0.25 0.78 0.40 0.11 1.18 0.36 0.39
Hungary 0.84 0.40 0.02 0.33 0.31 0.52 0.82 0.87 0.15 0.36 0.52 0.85 1.22 1.17 0.31 0.76 1.75 1.72 0.79 1.87 0.16 0.98 0.26
Ireland 1.25 1.62 0.40 0.08 0.07 0.06 0.35 0.10 0.00 0.15 3.38 6.26 0.28 0.22 0.05 0.20 0.88 0.22 0.29 0.04 0.39 0.09 1.44
Italy 0.93 2.13 0.02 1.37 1.60 3.01 0.53 1.01 1.25 0.72 0.68 0.91 1.36 2.02 0.98 1.73 0.20 1.13 1.90 0.74 0.95 2.55 0.95
Latvia 1.61 4.16 3.35 1.15 1.25 0.37 18.34 0.78 0.65 0.70 0.60 1.12 0.87 1.59 1.43 1.43 0.43 0.59 0.60 0.75 0.50 2.76 0.55
Lithuania 2.02 1.17 5.65 1.14 1.43 0.33 3.36 0.85 1.00 4.93 1.35 0.37 1.18 0.77 0.23 1.00 0.23 0.51 0.52 0.68 0.50 6.01 0.38
Luxembourg 0.92 0.88 6.33 2.05 0.38 0.44 2.13 2.37 0.21 0.02 0.52 0.16 3.72 2.56 4.05 1.10 0.33 0.67 0.84 0.73 1.18 0.11 0.25
Malta 0.63 0.21 1.32 1.19 0.36 0.16 0.05 0.02 1.74 0.09 0.33 2.10 1.46 0.42 0.04 0.40 2.55 1.69 0.39 0.04 0.81 0.35 1.97
Netherlands 2.11 1.44 5.36 0.49 0.57 0.66 0.31 0.92 0.73 2.02 1.63 0.83 0.82 0.48 0.58 0.75 1.14 0.54 1.00 0.36 0.41 0.40 0.83
Poland 1.40 0.47 4.77 0.62 0.73 0.36 2.40 1.55 0.48 0.43 0.65 0.27 1.68 1.54 0.86 1.70 0.66 1.29 0.56 2.03 1.09 4.97 0.30
Portugal 1.17 3.76 5.30 1.98 2.26 3.30 4.51 2.61 0.99 0.63 0.62 0.34 1.83 3.55 0.60 2.02 0.31 0.98 0.52 1.45 0.14 2.62 0.30
Romania 0.33 0.23 5.93 1.13 2.55 2.81 3.98 0.29 0.04 1.29 0.44 0.30 1.38 0.53 0.88 0.96 0.50 1.40 0.76 1.99 1.54 3.90 0.30
Slovakia 0.46 0.51 0.00 0.40 0.49 1.22 1.79 1.33 0.63 0.89 0.39 0.15 1.28 1.15 1.14 1.57 1.40 0.98 0.61 2.35 0.27 1.72 0.29
Slovenia 0.59 0.60 0.00 0.69 0.45 0.64 3.19 1.85 0.19 0.34 0.81 2.04 1.64 1.54 0.90 1.88 0.23 2.05 0.99 1.84 0.33 3.09 0.49
Spain 1.60 2.22 0.33 0.84 1.23 1.35 0.88 1.29 0.46 0.53 1.06 1.21 1.21 2.21 1.02 1.16 0.21 0.89 0.70 2.43 1.04 0.85 0.38
Sweden 0.53 0.91 0.24 0.33 0.32 0.21 3.98 5.68 0.14 1.30 0.73 1.53 0.91 0.64 1.04 1.01 0.76 1.12 1.27 0.97 0.40 1.62 0.54
United
0.70 3.32 0.93 0.53 0.60 0.46 0.19 0.76 1.10 1.30 1.36 2.33 0.92 0.73 0.74 0.79 0.70 0.71 1.08 1.15 1.49 0.38 1.09
Kingdom
EU‑27 1.10 1.62 1.60 0.69 0.76 0.91 1.18 1.34 1.79 0.77 1.16 1.54 1.18 1.18 0.82 1.16 0.57 0.98 1.18 1.30 1.15 1.20 0.75
USA 0.91 0.66 0.29 0.53 0.16 0.21 0.58 1.19 0.67 1.04 1.46 1.13 1.03 0.70 0.71 0.91 1.03 0.89 1.37 0.96 0.50 0.46 1.59
Japan 0.09 0.06 0.08 0.48 0.02 0.03 0.02 0.26 0.20 0.41 1.00 0.18 1.08 0.94 1.25 0.67 1.18 1.12 1.65 2.12 1.51 0.14 0.46
Brazil 5.09 0.12 0.61 0.45 0.05 1.96 2.05 2.77 0.24 0.69 0.97 0.32 0.74 1.10 1.91 0.83 0.14 0.56 0.67 0.95 1.38 0.69 0.19
China 0.37 0.09 0.15 2.52 2.77 2.56 0.96 0.37 0.15 0.26 0.44 0.20 0.91 1.37 0.46 1.27 1.87 1.42 0.72 0.22 0.76 2.01 1.11
India 1.03 0.09 0.50 2.86 2.48 1.36 0.12 0.21 1.05 3.18 0.93 0.84 0.54 0.79 1.10 0.82 0.25 0.42 0.43 0.34 1.00 0.28 5.88
Russia 0.66 0.37 1.69 0.08 0.02 0.11 3.82 1.08 0.09 9.03 1.33 0.06 0.31 0.64 3.89 0.37 0.12 0.24 0.24 0.15 0.52 0.22 0.05
Source: own calculations using COMTRADE data.

RCA‑indices for individual manufacturing industries are
presented in graphs to aid comparison of EU‑27 with
Chapter IV — International competitiveness of EU industry
the US, Japan, China, Russia and Brazil, cf. Figures IV.4
to IV.10.
FIgURE IV.4: EU-27 trade in manufactured products — RCA index in 2009
Other transport eq.
Motor vehicles
Machinery n.e.c.
Electrical equipment
Computers, electronic & optical
Metal products
Other manufacturing
Furniture
Basic metals
Non-metallic mineral products
Food
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
Rubber & plastics Pharmaceuticals
Beverages
Tobacco
Chemicals
Textiles
Clothing
Paper
Printing
Refined petroleum
Leather & footwear
Wood & wood products
Note: The ‘radius 1’ circle is highlighted to aid identification of those sectors with a comparative advantage, which are located outside
the circle.
Source: own calculations using COMTRADE data.
FIgURE IV.5: US trade in manufactured products — RCA index in 2009
Other transport eq.
Motor vehicles
Machinery n.e.c.
Electrical equipment
Computers, electronic & optical
Metal products
Other manufacturing
Furniture
Basic metals
Food
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
Beverages
Tobacco
Non-metallic mineral products
Chemicals
Rubber & plastics Pharmaceuticals
Textiles
Clothing
Paper
Printing
Refined petroleum
Leather & footwear
Wood & wood products
Note: The ‘radius 1’ circle is highlighted to aid identification of those sectors with a comparative advantage, which are located outside
the circle.
Source: own calculations using COMTRADE data.
109

EU industrial structure 2011 — Trends and Performance
FIgURE IV.6: Japan trade in manufactured products — RCA index in 2009
110
Other transport eq.
Motor vehicles
Machinery n.e.c.
Electrical equipment
Computers, electronic & optical
Metal products
Other manufacturing
Furniture
Basic metals
Non-metallic mineral products
Food
2.5
2.0
1.5
1.0
0.5
Beverages
Rubber & plastics Pharmaceuticals
Tobacco
Chemicals
Textiles
Clothing
Printing
Paper
Rened petroleum
Leather & footwear
Wood & wood products
Note: The ‘radius 1’ circle is highlighted to aid identification of those sectors with a comparative advantage, which are located outside
the circle.
Source: own calculations using COMTRADE data.
FIgURE IV.7: brazil trade in manufactured products — RCA index in 2009
Other transport eq.
Motor vehicles
Machinery n.e.c.
Electrical equipment
Computers, electronic & optical
Metal products
Other manufacturing
Furniture
Basic metals
Food
5
Non-metallic mineral products
Chemicals
Rubber & plastics Pharmaceuticals
4
3
2
1
Beverages
Tobacco
Textiles
Clothing
Printing
Paper
Rened petroleum
Leather & footwear
Wood & wood products
Note: The ‘radius 1’ circle is highlighted to aid identification of those sectors with a comparative advantage, which are located outside
the circle.
Source: own calculations using COMTRADE data.

FIgURE IV.8: China trade in manufactured products — RCA index in 2009
Other transport eq.
Motor vehicles
Machinery n.e.c.
Electrical equipment
Computers, electronic & optical
Metal products
Other manufacturing
Furniture
Basic metals
Non-metallic mineral products
Food
3.0
2.5
2.0
1.5
1.0
0.5
Rubber & plastics Pharmaceuticals
Chapter IV — International competitiveness of EU industry
Beverages
Tobacco
Chemicals
Textiles
Clothing
Printing
Paper
Rened petroleum
Leather & footwear
Wood & wood products
Note: The ‘radius 1’ circle is highlighted to aid identification of those sectors with a comparative advantage, which are located outside
the circle.
Source: own calculations using COMTRADE data.
FIgURE IV.9: India trade in manufactured products — RCA index in 2009
Other transport eq.
Motor vehicles
Machinery n.e.c.
Electrical equipment
Computers, electronic & optical
Metal products
Other manufacturing
Furniture
Basic metals
Food
6
Non-metallic mineral products
Chemicals
Rubber & plastics Pharmaceuticals
5
4
3
2
1
Beverages
Tobacco
Textiles
Clothing
Printing
Paper
Rened petroleum
Leather & footwear
Wood & wood products
Note: The ‘radius 1’ circle is highlighted to aid identification of those sectors with a comparative advantage, which are located outside
the circle.
Source: own calculations using COMTRADE data.
111

EU industrial structure 2011 — Trends and Performance
FIgURE IV.10: Russia trade in manufactured products — RCA index in 2009
112
Other transport eq.
Motor vehicles
Machinery n.e.c.
Electrical equipment
Computers, electronic & optical
Metal products
Other manufacturing
Furniture
Basic metals
Non-metallic mineral products
Food
10
Rubber & plastics Pharmaceuticals
9
8
7
6
5
4
3
2
1
Beverages
Tobacco
Chemicals
Textiles
Clothing
Paper
Printing
Rened petroleum
Leather & footwear
Wood & wood products
Note: The ‘radius 1’ circle is highlighted to aid identification of those sectors with a comparative advantage, which are located outside
the circle.
Source: own calculations using COMTRADE data.
IV.2.4.2 RCA In SERVICES
Service industries account for about three quarters of
the EU value added in 2009 but significantly less of their
output is traded compared to manufacturing which
represents 15 % of EU value added. World services exports
represented about 2 300 billion euro in 2009 (WTO, 2011).
In absolute terms, this amounts to slightly more than
a quarter of the 8 200 billion euro in merchandise and
agricultural trade in 2009 (WTO, 2011). The analyses of
trade in services in this section are based on a sample
of 102 countries (see section IV.1.2 Services), accounting
for 99 % of services trade in the world. This sample was
used to estimate total world trade for all services and total
word trade by type of service.
Trade in services differs substantially from manufacturing
trade, for example in transactions of products between
different countries. A definition of trade in services
and presentation of the different services industries
participating in international trade is provided below,
cf. Box IV.4. 69
69 It should also be noted that the service ‘Royalties and licence fees’
is not included in this report as it is not related to a special service
activity.

Chapter IV — International competitiveness of EU industry
box IV.4: trade in services: definition, sectoral breakdown and
measurement 70
International trade in services involves transactions between residents and non‑residents of an economy. Services
are less tradable than goods. As they are immediately consumed, they cannot be resold. For many services, the
consumer and provider of the service have to be located at the same place.
From a sectoral perspective, the main components of services activities are generally broken down into three
categories grouping together 11 types of services sectors:
1. Transportation
2. Travel.
3. Other services, including: communication services, construction services, insurance services, financial services,
computer and information services, royalties and licence fees, other business services, personal, cultural and
recreational services and government services
There are four modes for the supply of services:
‑ Mode 1 is cross‑border supply, where only the service crosses the border. The change of country can, for
example, be via electronic communication (Internet, telephone, facsimile, etc.). The sectors characterised by
cross‑border supply are: most of transportation, communication services, financial and insurance services,
royalties and licence fees. Parts of certain sectors can involve cross‑border supply: part of computer and
information services, part of other business services, and part of personal, cultural and recreational services.
‑ Mode 2 is consumption abroad, when consumers cross the border. This is the case principally for tourism or
business travel, when individuals go to hotels and restaurants. Part of transportation can also be counted as
consumption abroad (supporting and auxiliary services for carriers in foreign ports).
‑ Mode 3 is commercial presence, when suppliers (firms) cross the border to supply services. A foreign
company will, for example, open branches or subsidiaries in the destination country. Some construction services
involve commercial presence.
‑ Mode 4 is the presence of natural persons when suppliers (natural persons) cross the border to supply
services. An individual who is self‑employed (for example a consultant or a health worker) or an employee (for
instance a construction worker) moves temporarily to the country of the consumer to supply services. This form
of trade is found in the following sectors: part of the computer and information services sector, part of ‘other
business services’, part of the personal, cultural and recreational services sector, and part of the construction
services sector.
In this report, there is a gap between the conceptual classification of trade in services and the data that were used
from the balance of payments statistics. Data on trade in services are more deficient than data on trade in goods.
There are practical difficulties that arise when capturing trade in services. It is complicated to separate goods and
services in the balance of payments. As a result, the latter may be under‑recorded. Moreover, certain transactions
falling under the four modes of supply are not accounted for in the balance of payments estimates of services trade.
Cross‑border trade (Mode 1) is the mode of supply best covered by the balance of payments statistics. Mode 2 —
consumption abroad — is generally well covered as it is represented by expenditures in tourism and business travel.
Trade through commercial presence (mode 3) is accounted for through company surveys (foreign affiliates trade in
services surveys), which are a different type of statistics. The balance of payments takes into account residency rather
than nationality: a service is considered as traded if it takes place between residents and non‑residents. In the case
of trade through commercial presence (mode 3), there are only residents of the country who are involved. Mode 4 —
presence of natural persons — is also badly covered.
70 For more background, see European Commission, United Nations, International Monetary Fund, Organisation for Economic Cooperation
and Development, United Nations Conference on Trade and Development, World Trade Organisation (2002) and WTO (2007).
113

EU industrial structure 2011 — Trends and Performance
Before the results of analyses are presented it should be
noted that the RCA measure for services trade cannot be
114
compared directly with the RCA measure for goods trade,
cf. Box IV.5.
box IV.5: differing interpretation of rca in manufacturing and services 71
i Unlike manufacturing goods, services are not only supplied through cross‑border trade. There are other modes of
supply, such as movements of consumers to producers, commercial presence abroad or movement of physical persons.
ii Domestic polices rather than trade policies are more likely to have an impact on trade in services.
iii Services supplied via factor movements are traded between residents and non‑residents in the same country
and not between countries.
As was discussed in section III.2, specialisation in services
industries differs markedly between the Member States.
Cyprus, Luxembourg and the UK have very strong revealed
comparative advantages in financial services. Ireland,
Luxembourg and the UK have high RCAs in insurance
services. Ireland also has a high RCA in computer and
information services together with Finland. As with
manufacturing, the RCA measure is sensitive to the relative
distribution of services industries in a country. In relatively
small economies relatively large service industries which
account for a large share of exports can give rise to high
RCAs. This is the case for Cyprus and Malta with regard to
financial services and personal, cultural and recreational
services respectively, cf. Table IV.9. 72 71 72
TAbLE IV.9: RCA in services activities in 2009: EU countries, US, Japan and brazil, China and Russia
communi‑
cation
computer
and infor‑
mation
construc‑
tion
Finance insurance
Other
business
services
personal,
cultural
and rec‑
reational
transpor‑
tation
Austria 1.17 0.63 0.88 0.26 0.94 1.08 0.45 0.80 1.52
Belgium 2.00 0.91 0.63 0.52 0.68 1.61 0.67 0.97 0.54
Bulgaria 1.30 0.40 2.02 0.07 0.82 0.37 0.70 0.73 2.31
Cyprus 0.40 0.26 0.34 2.79 0.35 0.71 0.40 1.34 0.77
Czech Republic 0.82 0.84 0.58 0.03 0.26 0.86 0.46 1.51 1.07
Denmark 0.47 0.56 0.24 0.16 0.35 0.77 0.73 2.17 0.47
travel
>>>
71 See Langhammer (2004) for a detailed presentation.
72 Personal, cultural and recreational services involve transactions
in (i) audiovisual and related services and (ii) other personal,
cultural and recreational services. Other personal, cultural and
recreational services comprise services such as those associated
with museums, libraries, archives, and other cultural, sporting,
and recreational activities. Also included are fees for services,
including provision of correspondence courses, rendered abroad
by teachers or doctors. Construction services cover work performed
on construction projects and installations by employees of an
enterprise in locations outside the economic territory of the
enterprise. Goods imported by the enterprise for use in the
projects are included in the value of these services rather than
under goods. Projects carried out by foreign subsidiaries or
branches of enterprises (direct investors) and certain site offices
are excluded because such projects are part of the production
of the host economy. See http://stats.oecd.org/OECDStat_
Metadata/ShowMetadata.ashx?Dataset=TIS&Coords=[SER].
[287]&ShowOnWeb=true&Lang=en

communi‑
cation
computer
and infor‑
mation
construc‑
tion
The EU has a relative comparative advantage in almost all the
sectors analysed except personal, cultural and recreational,
construction and travel. 73 The previous edition of EU industrial
structure, which based its findings on 2006 data, showed
that the EU had the highest RCA in financial services of all
countries. 2009 data shows that even though the EU still has
73 As mentioned previously, trade deficits and indications that
country does not have comparative advantages in a sector does
not necessarily mean that it constitutes a problem. The RCA
values below 1.0 for personal, cultural and recreational and travel
services industries indicate that citizens in the EU-27 on average
spend more money in third countries than third country tourists
spend in the EU. The conclusion is that a relatively high standard
of living allows people in the EU-27 to travel to third countries
and spend money.
Finance insurance
Chapter IV — International competitiveness of EU industry
Other
business
services
personal,
cultural
and rec‑
reational
transpor‑
tation
Estonia 1.30 0.51 1.17 0.15 0.08 0.62 0.21 1.93 0.77
Finland 0.57 4.92 1.75 0.21 0.31 1.93 0.03 0.00 0.52
France 1.12 0.16 1.41 0.17 0.20 0.80 1.01 1.37 1.26
Germany 0.73 0.92 1.62 0.59 0.80 1.12 0.41 1.39 0.55
Greece 0.30 0.12 0.23 0.04 0.33 0.14 0.33 2.36 1.10
Hungary 0.91 0.93 0.66 0.12 0.04 0.95 4.49 1.16 1.15
Ireland 0.33 6.54 0.00 1.21 5.15 1.30 0.00 0.00 0.24
Italy 0.61 0.12 0.85 0.87 0.50 1.06 0.93 0.85 1.49
Latvia 1.06 0.55 0.32 0.86 0.30 0.61 0.22 1.81 0.80
Lithuania 1.11 0.18 0.59 0.14 0.00 0.30 0.37 1.97 1.25
Luxembourg 2.22 0.30 0.26 7.86 2.26 0.51 1.60 0.19 0.29
Malta 0.58 0.33 0.00 0.83 0.60 1.11 18.12 0.47 1.14
Netherlands 2.08 1.20 1.14 0.20 0.28 1.48 0.83 1.02 0.61
Poland 0.90 0.52 1.74 0.19 0.04 1.01 0.44 1.07 1.32
Portugal 1.20 0.27 1.05 0.12 0.28 0.79 1.24 0.91 1.83
Romania 3.62 1.73 1.77 0.24 0.22 1.14 0.72 1.07 0.54
Slovak
Republic
1.40 0.78 0.67 0.67 0.50 0.56 0.77 1.08 1.60
Slovenia 1.85 0.44 1.53 0.08 0.63 0.72 0.75 0.88 1.78
Spain 0.69 0.84 1.15 0.50 0.65 0.95 1.24 0.52 1.86
Sweden 1.46 2.11 0.32 0.32 0.81 1.60 0.86 0.63 0.80
United
Kingdom
travel
1.36 0.85 0.36 3.15 2.21 1.26 1.26 0.51 0.57
EU‑27 1.07 1.09 0.90 1.12 1.07 1.07 0.88 0.97 0.90
United States 0.99 0.58 0.58 1.89 1.60 0.91 3.17 0.57 1.32
Japan 0.20 0.11 3.03 0.47 0.27 1.23 0.11 1.65 0.32
Brazil 0.55 0.14 0.02 0.80 0.61 2.11 0.28 0.55 0.87
China,P.R.:
Mainland
0.32 0.72 2.06 0.04 0.44 1.18 0.06 1.10 1.10
India 0.56 7.74 0.27 0.45 0.64 0.53 0.44 0.77 0.47
Russian
Federation
1.32 0.53 2.65 0.34 0.46 1.08 0.76 1.08 0.97
Source: own calculations using IMF bops and OECD.
a comparative advantage in financial services, the US now has
the highest RCA in these services. US RCAs are even higher
compared with the EU in personal, cultural and recreational
services. Both the EU and the US appear to be quite diversified
in their services trade. Japan appears to be highly specialised
in trade of construction services as do China and Russia. India
is highly specialised in computer and information services,
an area where China differs radically. While China has strong
comparative advantages in manufacturing radio, television
and telecommunication equipment, it does not have any
advantage in the services related to those manufacturing
goods. Brazil exhibits high RCA values in other business
services, cf. Figures IV.11 to IV.17.
115

EU industrial structure 2011 — Trends and Performance
FIgURE IV.11: EU-27 trade in services — RCA index in 2009
116
Transportation
Personal, cultural and recreational
Travel
Communication
1.2
1.0
0.8
0.6
0.4
0.2
Other business services Insurance
Computer and information
Finance
Construction
Note: The ‘radius 1’ circle is highlighted to aid identification of those sectors with a comparative advantage, which are located outside
the circle.
Source: own calculations using IMF bops.
FIgURE IV.12: US trade in services — RCA index in 2009
Transportation
Personal, cultural and recreational
Travel
Communication
3.5
3.0
2.5
2.0
1.5
1.0
0.5
Other business services Insurance
Computer and information
Finance
Construction
Note: The ‘radius 1’ circle is highlighted to aid identification of those sectors with a comparative advantage, which are located outside
the circle.
Source: own calculations using IMF bops.

FIgURE IV.13: Japan trade in services — RCA index in 2009
Transportation
Personal, cultural and recreational
Travel
Chapter IV — International competitiveness of EU industry
Communication
3.5
3.0
2.5
2.0
1.5
1.0
0.5
Other business services Insurance
Computer and information
Finance
Construction
Note: The ‘radius 1’ circle is highlighted to aid identification of those sectors with a comparative advantage, which are located outside
the circle.
Source: own calculations using IMF bops.
FIgURE IV.14: brazil trade in services — RCA index in 2009
Transportation
Personal, cultural and recreational
Travel
Communication
2.5
2.0
1.5
1.0
0.5
Other business services Insurance
Computer and information
Finance
Construction
Note: The ‘radius 1’ circle is highlighted to aid identification of those sectors with a comparative advantage, which are located outside
the circle.
Source: own calculations using IMF bops.
117

EU industrial structure 2011 — Trends and Performance
FIgURE IV.15: China trade in services — RCA index in 2009
118
Transportation
Personal, cultural and recreational
Travel
Communication
2.5
2.0
1.5
1.0
0.5
Other business services Insurance
Computer and information
Finance
Construction
Note: The ‘radius 1’ circle is highlighted to aid identification of those sectors with a comparative advantage, which are located outside
the circle.
Source: own calculations using IMF bops.
FIgURE IV.16: India trade in services — RCA index in 2009
Transportation
Personal, cultural and recreational
Travel
Communication
8
Other business services Insurance
6
4
2
Computer and information
Finance
Construction
Note: The ‘radius 1’ circle is highlighted to aid identification of those sectors with a comparative advantage, which are located outside
the circle.
Source: own calculations using IMF bops

FIgURE IV.17: Russia trade in services — RCA index in 2009
Transportation
Personal, cultural and recreational
Travel
Communication
3.0
Chapter IV — International competitiveness of EU industry
2.5
2.0
1.5
1.0
0.5
Other business services Insurance
Computer and information
Finance
Construction
Note: The ‘radius 1’ circle is highlighted to aid identification of those sectors with a comparative advantage, which are located outside
the circle.
Source: own calculations using IMF bops.
IV.3 Intra-industry trade
Trade was analysed for broad categories of products in
the previous section. Part of international trade consists
in countries exchanging products (inter‑industry trade)
reflecting relative different factor (labour and capital)
endowments and technology. Countries which are relatively
endowed with capital tend to trade capital intensive goods
in exchange for labour intensive goods from countries
which are relatively well endowed with labour: for example,
pharmaceuticals for textiles or motor cars for food. In
section IV.1, the international trade network was presented
in terms of trade flows between geographic regions.
However, a large proportion of trade comprises exchange
of similar goods between countries which have comparable
levels of income, such as different brands of cars and clothes.
This type of trade, intra‑industry trade (IIT) is explained
by factors such as economies of scale and demand for
differentiated products, rather than by relative factor
endowments. As demand for differentiated products and
varieties of different qualities tend to rise with income,
per capita incomes of countries play an important role in
determining trade patterns.
About 53 % of world trade occurs between countries in
the groups composed of the EU‑27 and other high‑income
countries. If upper‑medium countries are included, this share
rises to almost 70 %. While trade between different types of
countries (e.g. high and upper‑medium income countries on
the one hand and low and low‑medium income countries
on the other) can be expected to involve goods produced
with differences in factor intensities, the exchange of
goods between high‑income countries suggests a different
pattern of trade. However, IIT also involves trade between
high‑income and lower‑income countries as well as between
the lower‑income countries themselves, cf. Table IV.10. 74
74 The classification by income level that was used is the one from
the World Bank. The country groups are: High non‑EU: Australia,
Bahamas, Bahrain, Brunei Darussalam, Canada, Croatia, China,
Hong Kong SAR, Iceland, Israel, Japan, Rep. of Korea, Kuwait, China,
Macao SAR, Oman, Neth. Antilles, New Zealand, Norway, Qatar,
Saudi Arabia, Singapore, Switzerland, United Arab Emirates, USA.
Upper‑medium: Algeria, Argentina, Bosnia Herzegovina, Botswana,
Brazil, Belarus, Chile, Colombia, Costa Rica, Cuba, Dominican Rep.,
Equatorial Guinea, Gabon, Jamaica, Kazakhstan, Lebanon, Libya,
Malaysia, Mauritius, Mexico, Montenegro, Namibia, Panama, Russian
Federation, Serbia, South Africa, Suriname, Trinidad and Tobago,
Turkey, TFYR of Macedonia, Uruguay, Venezuela. Low‑medium:
Albania, Angola, Azerbaijan, Armenia, Bolivia, Belize, Cameroon,
Cape Verde, Sri Lanka, China, Ecuador, El Salvador, Djibouti,
Georgia, Guatemala, Honduras, Indonesia, Iran, Iraq, Côte d’Ivoire,
Jordan, Lesotho, Maldives, Mongolia, Rep. of Moldova, Morocco,
Nicaragua, Nigeria, Paraguay, Peru, Philippines, Timor-Leste, India,
Swaziland, Syria, Thailand, Tunisia, Ukraine, Egypt. Low: Afghanistan,
Bangladesh, Bhutan, Myanmar, Burundi, Cambodia, Central African
Rep., Chad, Comoros, Congo, Dem. Rep. of the Congo, Benin,
Ethiopia, Eritrea, Gambia, Ghana, Guinea, Haiti, Kenya, Dem.
People’s Rep. of Korea, Kyrgyzstan, Lao People’s Dem. Rep., Liberia,
Madagascar, Malawi, Mali, Mauritania, Mozambique, Nepal, Niger,
Pakistan, Guinea-Bissau, Rwanda, Senegal, Sierra Leone, Viet Nam,
Somalia, Zimbabwe, Sudan, Tajikistan, Togo, Uganda, United Rep. of
Tanzania, Burkina Faso, Uzbekistan, Yemen, Zambia.
119

EU industrial structure 2011 — Trends and Performance
TAbLE IV.10: Manufactured products - World trade matrix, income level: exports in 2009 (%)
Export Eu‑27
120
high
income
non Eu‑27
upper
medium
income
destination
low
medium
income
low
income
Origin EU‑27 26.9 7.3 3.3 2.9 0.4 40.6
High income non EU‑27 6.3 12.8 3.9 7.5 0.6 31.1
Upper medium income 3.4 4.3 1.5 2.1 0.3 11.5
Low medium income 3.3 8.2 1.7 1.9 0.9 16.0
Low income 0.1 0.4 0.1 0.2 0.1 1.0
world
World 39.8 33.1 10.4 14.6 2.2 100.0
Note: Due to rounding, certain columns or rows do not add up to 100 %. The matrix is calculated from export data. It refers exclusively
to manufactured products, so it does not include crude oil and other products from mining and quarrying. The values in each cell are
percentage shares of total world trade. The main diagonal in the matrix (shaded cells) represents intra‑region trade (e.g. exports from EU
countries to EU countries). Each cell shows the share of total world exports which are exported from an exporter to a certain destination.
For example, Upper medium income countries’ exports to EU‑27 accounts for 3.4 % of total world exports and total Upper median income
countries’ exports accounts for 11.5 % of total world exports.
Source: own calculations using COMTRADE data.
When intra‑regional EU trade is excluded from the data,
the largest share of EU‑27 trade (both exports and imports)
takes place with high income countries. Some 53 % of
extra‑EU exports go to other high‑income countries,
and 56 % of imports originate from high‑income countries
towards the EU. However, 21 % of extra‑EU exports go to
low‑medium income countries, and 18% of EU imports also
originate from these countries, cf. Tables IV.11 and IV.12.
TAbLE IV.11: Manufactured products - World trade matrix income level: destination of exports in 2009 (%)
Export Eu‑27
high
income non
Eu‑27
upper
medium
income
destination
low
medium
income
low income world
Origin EU‑27 0.0 52.8 23.9 20.8 2.6 100.0
High income non EU‑27 34.5 0.0 21.1 41.0 3.4 100.0
Upper medium income 33.7 43.0 0.0 20.6 3.1 100.0
Low medium income 23.2 58.5 12.3 0.0 6.1 100.0
Low income 15.8 47.3 8.9 28.0 0.0 100.0
Note: Due to rounding, certain columns or rows do not add up to 100 %. The matrix is calculated from export data. It refers exclusively to
manufactured products, so it does not include crude oil and other products from mining and quarrying. The main diagonal in the matrix
(shaded cells) shows that intra‑regional trade (e.g. exports from EU countries to EU countries) is excluded in this table. Exporters are
shown in rows and destination markets in columns. Each cell shows the share of total exports from an exporter to a certain destination.
For example, 33.7 % of Upper medium income countries’ exports are destined for EU‑27.
Source: own calculations using COMTRADE data.

Chapter IV — International competitiveness of EU industry
TAbLE IV.12: Manufactured products - World trade matrix — income level: import destination in 2009 (%)
import Eu‑27
high income
non Eu‑27
destination
upper medium
income
low medium
income
low
income
Origin EU‑27 0.0 38.0 36.1 27.4 26.8
High income non EU‑27 55.7 0.0 43.7 57.1 39.8
Upper medium income 24.2 21.1 0.0 12.8 9.1
Low medium income 18.3 37.5 18.9 0.0 24.3
Low income 1.8 3.5 1.9 2.8 0.0
World 100.0 100.0 100.0 100.0 100.0
Note: Due to rounding, certain columns or rows do not add up to 100 %. The matrix is calculated from import data. It refers exclusively to
manufactured products, so it does not include crude oil and other products from mining and quarrying. Detailed export data from India
were not available for 2008 in the chosen trade classification (HS2007). Exporters are shown in rows and destination markets in columns.
Each cell shows the share of total imports for a certain country from an exporting country. For example, 36.1 % of Upper medium income
countries’ imports origin in the EU‑27. The last row sums up each exporting country’s share for every importing country.
Source: own calculations using COMTRADE data.
The most widely used measure of intra‑industry trade (IIT)
is the Grubel‑Lloyd (GL) index. The GL index is sensitive
to the level of aggregation of industries or products: the
higher the level of aggregation of industries, the higher
the GL index. 75 The reason for this property of the GL index
is that the absolute value of net trade when the industries
are defined on a higher level of aggregation, e.g. 4‑digit,
box IV.6: Intra-industry trade
75 Put differently, the higher the number of industries (products),
the lower the value of the GL index.
is equal to or less than the sum of the absolute values
of net trade when the industries are defined on a lower
level of aggregation, e.g. 6‑digit. For example, net trade
with different signs on the lower level of aggregation can
cancel out at the higher level of aggregation. The index
ranges from 0 (no IIT) to 1 (all trade is intra‑industry),
cf. Box IV.6.
The GL index for product ‘i’ (where X and M stand for exports and imports, respectively) is defined as follows:
The GL index can be defined across products as follows:
121

EU industrial structure 2011 — Trends and Performance
Applying the GL index for EU‑27 trade in manufactured
products with four groups of countries, classified by
income level, shows that the value of the GL index increases
with the level of income of the trade partner. 76 The GL
index is 0.09 for trade with low‑income countries, 0.26 for
trade with low‑medium income countries, 0.30 for trade
76 The classification by income level that was used is the one from
the World Bank. The country groups are: High non‑EU: Australia,
Bahamas, Bahrain, Brunei Darussalam, Canada, Croatia, China,
Hong Kong SAR, Iceland, Israel, Japan, Rep. of Korea, Kuwait,
China, Macao SAR, Oman, Neth. Antilles, New Zealand, Norway,
Qatar, Saudi Arabia, Singapore, Switzerland, United Arab Emirates,
USA. Upper‑medium: Algeria, Argentina, Bosnia Herzegovina,
Botswana, Brazil, Belarus, Chile, Colombia, Costa Rica, Cuba,
Dominican Rep., Equatorial Guinea, Gabon, Jamaica, Kazakhstan,
Lebanon, Libya, Malaysia, Mauritius, Mexico, Montenegro,
Namibia, Panama, Russian Federation, Serbia, South Africa,
Suriname, Trinidad and Tobago, Turkey, TFYR of Macedonia,
Uruguay, Venezuela. Low‑medium: Albania, Angola, Azerbaijan,
Armenia, Bolivia, Belize, Cameroon, Cape Verde, Sri Lanka, China,
Ecuador, El Salvador, Djibouti, Georgia, Guatemala, Honduras,
Indonesia, Iran, Iraq, Côte d’Ivoire, Jordan, Lesotho, Maldives,
Mongolia, Rep. of Moldova, Morocco, Nicaragua, Nigeria,
Paraguay, Peru, Philippines, Timor-Leste, India, Swaziland, Syria,
Thailand, Tunisia, Ukraine, Egypt. Low: Afghanistan, Bangladesh,
Bhutan, Myanmar, Burundi, Cambodia, Central African Rep.,
Chad, Comoros, Congo, Dem. Rep. of the Congo, Benin, Ethiopia,
Eritrea, Gambia, Ghana, Guinea, Haiti, Kenya, Dem. People’s Rep.
of Korea, Kyrgyzstan, Lao People’s Dem. Rep., Liberia, Madagascar,
Malawi, Mali, Mauritania, Mozambique, Nepal, Niger, Pakistan,
Guinea-Bissau, Rwanda, Senegal, Sierra Leone, Viet Nam, Somalia,
Zimbabwe, Sudan, Tajikistan, Togo, Uganda, United Rep. of
Tanzania, Burkina Faso, Uzbekistan, Yemen, Zambia.
122
with upper‑medium income countries, and 0.61 for
trade with high‑income countries. This shows that trade
with industrialised countries has a large component
of intra‑industry trade, while trade with lower‑income
countries has a large component of inter‑industry trade,
cf. Figure IV.18.
FIgURE IV.18: grubel-Lloyd index by income level of EU-27 trade partner in 2009
Grybel-Lloyd index in 2009
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
Low income
Low medium income
Trade partners country groups
Upper medium income
Note: calculations based on a sample of 5 050 6‑digit products from HS2007 classification.
Source: own calculations using COMTRADE data.
High income non EU-27

IV.4 The role of technology in EU
sectoral trade
Analysing trade performance in the four technology categories
for individual MS shows that Cyprus, Hungary, Ireland and
Malta have the highest revealed comparative advantages
in high technology products. 77 Conversely, Greece, Latvia
and Portugal exhibit high RCA’s in low technology products.
Caution is needed when studying RCA’s for individual countries
as small countries with small manufacturing industries can
have high RCA’s due to a few relatively large firms which export
large shares of their production.
77 The taxonomy used in section III.2.2 was adapted to trade
product categories.
Chapter IV — International competitiveness of EU industry
The RCA’s for different technology categories do not
differ significantly for the EU‑27 which has a slightly
higher RCA in trade with medium‑high technology
products. Notwithstanding the high RCAs of certain
individual EU countries, the US has the highest RCA
index in high and medium‑high technology products in
comparison with the EU as a whole and Japan or the BRIC
countries. Japan’s comparative advantage is particularly
strong in medium‑high technology products. China
has a dual structure, with a high RCA in both high‑ and
low‑technology products while Russia only has a RCA
larger than one in trade with medium‑low technology
products, cf. Table IV.13.
TAbLE IV.13: RCA by technology category in 2009: EU countries, US, Japan and brazil, China, India and
Russia
high tech medium high tech medium low tech low tech
Austria 0.54 1.14 1.02 1.20
Belgium 0.97 1.06 0.92 1.02
Bulgaria 0.36 0.59 1.75 1.65
Cyprus 1.70 0.73 0.51 1.43
Czech Rep. 0.85 1.22 0.95 0.75
Denmark 0.52 0.97 0.93 1.75
Estonia 0.30 0.82 1.48 1.58
Finland 0.69 0.97 1.07 1.35
France 1.07 1.07 0.78 1.08
Germany 0.76 1.39 0.77 0.75
Greece 0.66 0.50 1.45 1.90
Hungary 1.60 1.11 0.56 0.62
Ireland 2.05 1.11 0.14 0.66
Italy 0.38 1.12 1.14 1.28
Latvia 0.60 0.58 1.13 2.22
Lithuania 0.23 0.74 1.67 1.57
Luxembourg 0.41 0.68 1.86 1.23
Malta 2.66 0.50 0.50 0.80
Netherlands 1.08 0.89 0.92 1.27
Poland 0.57 1.03 1.22 1.14
Portugal 0.33 0.84 1.09 2.06
Romania 0.46 1.04 1.22 1.26
Slovakia 1.07 1.03 1.09 0.72
Slovenia 0.62 1.25 1.04 0.86
Spain 0.49 1.18 0.93 1.31
Sweden 0.86 1.01 0.97 1.19
United
Kingdom
1.10 1.10 0.88 0.82
EU‑27 0.84 1.14 0.89 1.03
Japan 0.81 1.49 0.97 0.18
USA 0.93 1.25 0.89 0.68
Brazil 0.39 0.71 0.95 2.45
China 1.49 0.67 0.88 1.30
India 0.41 0.51 2.06 1.33
Russia 0.08 0.46 2.97 0.60
Source: own calculations using Comtrade data.
123

EU industrial structure 2011 — Trends and Performance
IV.5 Trade in intermediate goods
This section aims at providing information about how the
globalisation process and increased trade in intermediate
goods have impacted on the trade performance of EU
industries. This is analysed in two ways. First, the extent
of imported intermediates in exports for countries and
industries is analysed. This is followed by analysis of the
competitiveness of EU manufacturing in intermediate trade.
The EU manufacturing industry is compared with those of
the BRIC countries, Japan and the USA.
A distinct feature of the increased globalisation is the
fragmentation of firms’ value chains and establishment of
cross‑border networks by an increasing number of firms.
This implies that imports and exports move together, since
companies’ production process are increasingly characterised
124
box IV.7: Vertical specialisation
by sequential production in different locations depending on
the comparative advantages of the locations. An increasing
share of firms’ exports is composed of imports: for example,
it is no longer valid to label a product which is exported from
the UK as ‘Made in UK’ since the production of components
and services needed to produce the product has taken place
in many locations across the world. The concept ‘vertical
specialisation’ [Hummels et al. (2001)] which is a measure of
the import content of exports, has been proposed to gauge
this feature of trade with intermediate goods.
The concept of vertical specialisation concerns both imports
and exports of goods between at least three countries.
Intermediates are imported in one country from a source
country and used in the production of further intermediate
goods or final goods which are exported to a destination
country, cf. Box IV.7.
When an industry i in country k uses imported inputs to produce an exported good, vertical specialisation VS is ki
defined as: 78
Vertical specialisation for a country k equals the sum of VS for all i, VS = Σ VS . Relating it to exports yields vertical
k i ki
specialisation share of total exports for a country: 79
VS share of total exports for country k =
where X denotes exports. 80
78 Hummels et. at. (2001) p. 78.
79 The concept ‘import content of exports’ is sometimes used to describe the same phenomena, OECD (2010).
80 See Hummels et. al. (2001) p. 79 for details. It is shown that vertical specialisation for a country k is an export-weighed average of the sector
vertical specialisation export shares. The equivalent matrix notation of the expression above is uAM[I — AD] -1 X/X k, where u is a vector of 1’s,
AM is the n x n imported coefficient matrix, I is the identity matrix, AD is the n x n domestic coefficient matrix, X is n x 1 vector of exports,
Xk is total country exports and n is the number of sectors. In order to calculate the shares for sectors, X is replaced by a n x n vector with
sector exports in the diagonal and zeros elsewhere. See OECD (2010) for details.

The import dependence of exports, vertical specialisation
share of total exports, increased in almost all OECD
countries between 1995 and 2005. Vertical specialisation is
most pronounced in small countries depending on imports
for intermediate goods and countries hosting a large
Chapter IV — International competitiveness of EU industry
number of multinational firms. Relatively small EU countries
such as Estonia, Hungary and Ireland show high import
dependencies of exports compared to France, Germany and
the UK, cf. Figure IV.19.
FIgURE IV.19: Vertical specialisation of exports by country in 1995 and 2005 (%)
70
60
50
40
30
20
10
0
Luxembourg
Hungary
Estonia
Ireland
Slovak Republic
Czech Republic
Slovenia
Belgium
Portugal
Korea
Mexico
Finland
Netherlands
Denmark
Austria
Spain
Sweden
Source: OECD (2010). OECD Economic Globalisation Indicators.
Vertical specialisation as share of total industry
exports increased in almost all EU industries
between 1995 and 2005. Vertical specialisation is more
pronounced in basic EU industries which use a relatively
large share of primary goods such as coke and refined
petroleum, basic metals and chemicals. Also more
knowledge‑intensive industries, such as motor vehicles,
radio, television and communication equipment industries,
where parts and components are produced before they are
exported to another country for assembly into final goods,
show high degrees of vertical specialisation. The extent of
Poland
Italy
Romania
China
Canada
Germany
Greece
France
OECD
Turkey
Chile
United Kingdom
New Zealand
Israel
Indonesia
South Africa
Norway
Japan
Brazil
Australia
Russian
Federation
India
United States
vertical specialisation is considerably lower in EU service
industries, cf. Figure IV.20. 81
81 Due to data constraints it was not possible to calculate
vertical specialisation for the same years for all countries.
Input-output tables for 1995 and 2005 were used for Austria,
Belgium, Italy, Portugal, Spain and Sweden. Input-output
tables for 1995 and 2007 were used for Denmark, Finland,
France, Germany and Netherlands. Input-output tables
for 1996 and 2005 were used for Slovenia. Input-output tables
for 1997 and 2005 were used for Estonia. Input-output tables
for 1998 and 2005 were used for Hungary and Ireland.
125

EU industrial structure 2011 — Trends and Performance
FIgURE IV.20: Import content of exports for 15 EU countries in 1995 and 2005 (%)
126
Education services
Real estate services
Membership organisation services n.e.c.
Collected and puried water
Other services
Retail trade services
Public administration and defence services
Health and social work services
Services auxiliary to nancial intermediation
Sewage and refuse disposal services
Financial intermediation services
Insurance and pension funding services
Hotel and restaurant services
Other business services
Recreational, cultural and sporting services
Crude petroleum and natural gas
Forestry
Renting services of machinery and equipment
Wholesale trade
Computer and related services
Post and telecommunication services
Research and development services
Construction work
Trade, maintenance and repair services of motor vehicles and motorcycles
Land transport
Secondary raw materials
Fishing products
Agriculture and hunting
Other mining and quarrying products
Metal ores
Supporting and auxiliary transport services
Electrical energy, gas, steam and hot water
Coal and lignite
Printed matter and recorded media
Other non-metallic mineral products
Tobacco products
Wood and products of wood and cork
Food products and beverages
Other manufactured goods n.e.c.
Medical, precision and optical instruments
Fabricated metal products
Machinery and equipment n.e.c.
Pulp, paper and paper products
Water transport
Other transport equipment
Textiles
Leather and leather products
Air transport
Rubber and plastic products
Wearing apparel
Chemicals
Electrical machinery and apparatus n.e.c.
Basic metals
Oce machinery and computers
Radio, television and communication equipment
Motor vehicles
Coke, rened petroleum products and nuclear fuels
Vertical specialisation 1995
Vertical specialisation 2005
0 10 20 30 40 50 60
Note: due to lack of data is was only possible to calculate vertical specialisation between 1995 and 2005 for 15 EU countries. The 15 EU
countries are: Austria, Belgium, Denmark, Estonia, Finland, France, Germany, Hungary, Italy, Ireland, Netherlands, Portugal, Slovenia, Spain
and Sweden. The calculations are based on input‑output tables.
Source: own calculations using Eurostat data.

The calculations of vertical specialisation assume that all
imports originate in other countries and do not take into
account that parts of imports may consist of products that
originally are domestic. If, for example, Spain imports an
electronic good and a component in that good previously
was produced and exported from Spain, Spanish imports of
TAbLE IV.14: Indicators of RCA for manufactured goods in 2000 and 2009
that good appear as larger than they actually are. This then
overestimates the vertical specialisation for Spain. 82
Considering that an industry’s exports may include a large
proportion of imports, the validity of the traditional way to
measure the external competitiveness of industries must be
in doubt. The RCA‑indices presented above do not take into
account that a large part of the exports can be produced in
another location.
Competitiveness is assessed below using an adjusted
measure of revealed comparative advantages (RCA). The
adjusted RCA measures are calculated for different types
of goods defined according to the basic classes of goods
in the system of national accounts (SNA): intermediate
goods, capital goods, consumer goods and goods not
else classified (goods n.e.c.). 83 The adjusted RCA measures
are calculated for both exports and imports. Especially
interesting is the measure for imports of intermediates
which shows whether a country has comparative advantage
of assembly. 84
82 Kommerskollegium (2010). See also Hummels et. al. (2001) for
a more detailed discussion.
83 The categories of goods in SNA consist of aggregation of the
goods classified according to the Broad Economic Category (BEC)
classification. BEC consists of seven types of goods: consumer
goods, capital goods, industrial supplies, fuels, transport
equipment, food and beverages and goods not elsewhere
specified.
84 See OECD (2010) and Ng and Yeats (1999) for discussions of these
RCA measures.
Chapter IV — International competitiveness of EU industry
Beginning with the very broad categories of manufactured
goods, China is the only country without comparative
advantage in intermediate exports. Chinese and
Indian industries seem to be dependent on imports of
intermediate goods which are indicated by the high RCA
indicator for intermediate imports, cf. Table IV.14.
intermediate goods consumption goods capital goods goods nec
Exports imports Exports imports Exports imports Exports imports
2000 2009 2000 2009 2000 2009 2000 2009 2000 2009 2000 2009 2000 2009 2000 2009
Eu‑27 1.2 1.1 1.0 0.9 0.5 0.5 0.9 1.1 1.7 1.7 1.0 0.9 1.8 1.6 1.1 1.2
Brazil 1.5 1.7 1.2 1.1 0.5 0.4 0.5 0.6 1.2 0.7 1.1 1.2 0.5 0.6 0.4 0.6
china 0.9 0.9 1.4 1.4 1.1 0.8 0.1 0.1 1.2 2.3 1.0 1.1 0.2 0.2 0.2 0.3
india 1.4 1.3 1.6 1.5 1.0 0.9 0.2 0.2 0.2 0.7 0. 5 0.8 0.4 0.6 0.2 0.3
Japan 1.4 1.5 1.1 1.1 0.2 0.2 1.3 1.2 2.3 2.0 0.7 0.7 0.6 0.5 0.5 0.4
russia 2.3 2.2 0.9 0.6 0.1 0.1 1.3 1.6 0.3 0.2 1.2 1.5 0.1 0.8 0.2 1.0
usa 1.4 1.3 0.8 0.8 0.4 0.4 1.2 1.3 1.8 1.2 1.1 1.2 1.2 2.4 1.8 1.3
Source: own calculations using COMTRADE data.
In the table above, very broad categories of manufactured
goods were analysed. While these aggregates provide
some useful information regarding specialisation patterns
across countries, the aggregates necessarily mean that
industry differences are hidden. Looking more closely
at a disaggregation of intermediate goods allows for
separation of manufactured goods into a classification
according to technological intensity. Of the BRIC countries,
only China seems to have comparative advantages in
exports of high‑tech intermediate exports. The high RCAs
for imports indicate that China also has comparative
advantages in the assembly of intermediate goods in
medium high‑tech and high‑tech industries. 85 However,
the EU, Japan and the US also have comparative advantages
in assembling high‑tech goods, although not to the same
extent. The results in the table below are therefore not
conclusive on this point, cf. Table IV.15.
85
where int denotes intermediate goods, i industry and c country.
See Ng and Yeats (1999) and OECD (2010) for a discussion of this
indicator.
127

EU industrial structure 2011 — Trends and Performance
TAbLE IV.15: Indicators of RCA for intermediate goods according to technological intensity in 2009
Exports imports
low medium medium high low medium medium high
tech low tech high tech tech tech low tech high tech tech
Brazil 2.4 0.9 0.7 0.4 0.5 0.9 1.5 1.0
china 1.5 0.7 0.7 1.6 0.5 0.8 1.2 1.4
Eu‑27 0.9 0.9 1.2 1.0 1.2 1.0 0.8 1.1
india 1.1 1.8 0.5 0.3 0.6 1.4 1.0 0.8
Japan 0.2 0.9 1.7 1.0 1.6 0.8 0.8 1.0
russia 0.2 2.6 0.2 0.0 1.6 0.7 1.2 0.8
usa 0.7 1.0 1.3 0.9 1.0 0.9 1.0 1.2
Source: own calculations using COMTRADE data.
Even though the results in the table above are based on less
aggregated data than in table IV.14, these aggregates also
mask industry differences. There are differences even within
industries, as different firms produce different varieties of
goods. These varieties may not be substitutes if they differ
in terms of quality: one way to analyse this is by looking
at unit values. Unit values, trade values divided by trade
volumes, are often used as indicators of price and qualities
of different goods. The rationale is that countries exporting
at higher unit values offer higher quality products. Unit
values should, however, be used with caution. Unit values
are imprecise measures of quality since high values could
be the results of higher prices for similar products, higher
quality or merely a larger share of products with higher unit
values. The imprecise nature of this measure increases with
the level of aggregation that unit values are calculated for. 86
86 See OECD (2011) for a more detailed discussion.
128
Relative unit values for each country have been calculated by
division of the countries’ unit values for industries in different
technological intensities by unit values for world exports and
imports for corresponding industries. Unit values above one
indicate a relatively high quality of products. EU‑27, Japan
and US exports seem to be of higher quality than BRIC
country exports: Chinese exports of medium low‑tech goods
and Indian low‑tech goods are exceptions. The very high unit
values of Chinese imports of high‑tech goods stand out in
the table. Chinese imports of high tech goods are apparently
relatively expensive and of high quality. The result confirms
the findings from the table above, indicating that China has
a comparative advantage in assembly of high‑tech goods,
cf. Table IV.16.
TAbLE IV.16: Export and import unit values of intermediates according to technological intensity in 2009
Exports imports
low medium medium high low medium medium high
tech low tech high tech tech tech low tech high tech tech
Brazil 0.7 0.8 0.7 0.3 1.0 1.0 0.5 0.9
china 0.4 1.4 0.9 0.8 0.5 0.9 0.8 3.5
Eu‑27 2.3 1.2 1.5 1.8 1.5 0.9 1.2 1.4
india 2.9 0.8 0.7 0.1 0.6 1.3 0.3 0.7
Japan 2.5 1.3 1.6 1.8 1.5 1.0 1.6 1.5
russia 0.2 0.5 0.1 0.6 1.4 1.5 1.3 0.9
usa 1.1 0.9 0.9 1.6 2.0 0.9 1.6 2.0
Source: own calculations using COMTRADE data.
The OECD (2011) presents more detailed analyses which
confirm this picture. Half of the exports of high income
countries such as the US, Japan, Germany and France are
exports in the high quality range while some 20 % to 30 %
of the exports of China and other emerging countries are in
the high quality range. This latter group of countries export
relatively more of lower quality exports. 87
87 See OECD (2011).

IV.6 International movement of
factors of production
iv61 Fdi
The globalisation of economic activity shows itself not
only in increased trade but also in increased foreign direct
investment (FDI) which displayed a higher growth than
trade for at least the last 15 years. 88 FDI is undertaken by
multinational enterprises (MNEs which can be said to
be either vertically or horizontally integrated. Vertically
integrated MNEs undertake FDI in order to acquire
a supplier or raw materials (backwards integration) or
distributors of the product (forwards integration). The main
motive for vertical integration is to reap the benefits of
comparative advantages of different locations for parts of
the MNE production processes. Horizontal integration often
88 OECD (2010). OECD Globalisation indicators.
Chapter IV — International competitiveness of EU industry
implies duplication of the firms’ activities, i.e. localisation
of the same parts of the production process in different
countries. For the host country, FDI is a source of foreign
capital. The local economy often also benefits from the
import of knowledge transfer, such as new management
techniques and more sophisticated technologies, as well
as easier access to international financial markets and
products. 89
FIgURE IV.21: Outward EU foreign direct investment stock in 2007
100
90
80
70
60
50
40
30
20
10
0
Source: own calculations using Eurostat data.
The stocks of both inward and outward EU FDI are
concentrated in the financial and real estate sectors.
The high share of FDI in the financial sector in 2007 is
the result of the internationalisation of financial firms. In
absolute terms, financial intermediation, real estate and
business activities represent almost two thirds of overall
outward EU FDI stock and more than two thirds of inward
EU stock of foreign direct investment, cf. Figures IV.21
and IV.22.
89 Eurostat (2007b).
Financial intermediation
Real estate and business activities
Telecommunications
Manufacture of chemicals and chemicals products
Mining and quarrying
Wholesale trade
Extraction of petroleum and gas
Other
129

EU industrial structure 2011 — Trends and Performance
FIgURE IV.22: Inward EU Foreign direct investment stock in 2007
130
100
90
80
70
60
50
40
30
20
10
0
Source: own calculations using COMTRADE data.
Intra‑EU FDI illustrates the achievements of the single
market in the EU. Overall, about 62 % of inward EU FDI stock
originates from other MS. More than two thirds of inward EU
FDI is owned by MNEs in the following sectors: real estate,
FIgURE IV.23: Share of the inward EU FDI stock owned by EU firms in 2007
Real estate
Hotels and restaurants
Trade and repair of motor vehicles
Telecommunications
Retail trade
Rubber and plastic products
Other business activities
Supporting and auxiliary transport activities; activities of travel agencies
Financial intermediation
Wholesale trade
Total
Textiles and wearing apparel
Oce machinery and computers
Recreational, cultural and sporting activities
Research and development
Computer activities
Air transport
Agriculture and shing
Electricity, gas and water
Food products
Construction
Radio, television, communication equipments
Wood, publishing and printing
Mechanical products
Renting of machinery and equipment without operator and of personal and household goods
Land transport
Rened petroleum products and other treatments
Metal products
Water transport
Manufacture of chemicals and chemicals products
Mining and quarrying
Extraction of petroleum and gas
Post and courier activities
Source: own calculations using Eurostat data.
Financial intermediation
Real estate and business activities
Wholesale trade
Manufacture of chemicals and chemicals products
Mining and quarrying
Extraction of petroleum and gas
Other
hotels and restaurants, trade and repair of motor vehicles,
telecommunications, retail trade, rubber and plastic
products and other business activities, cf. Figure IV.23.
0 10 20 30 40 50 60 70 80

In many sectors, outward EU‑27 FDI stock is greater than
total inward EU‑27 FDI stock. Vertical backward integration
by EU‑27 MNEs seems to be the dominant motive, judging
from the sectoral distribution of the relative outward and
inward stocks. This is illustrated by the ‘resource‑driven’
sectors: refined petroleum products, mining and quarrying,
Chapter IV — International competitiveness of EU industry
extraction of petroleum and gas and metal products.
Horizontal integration, in order to gain access to new markets
or create localised, market‑oriented knowledge which helps
firms to adapt existing technologies and products to foreign
markets, may explain the relatively large outward EU‑27 stock
in telecommunication markets, cf. Figure IV.24.
FIgURE IV.24: EU-27 outward FDI stock to the rest of the world/EU-27 inward FDI stock from the rest of
the world in 2007 (ratio)
Telecommunications
Rened petroleum products and other treatments
Mining and quarrying
Electricity, gas and water
Extraction of petroleum and gas
Metal products
Post and courier activities
Mechanical products
Water transport
Land transport
Manufacture of chemicals and chemicals products
Radio, television, communication equipments
Construction
Food products
TOTAL
Hotels and restaurants
Oce machinery and computers
Rubber and plastic products
Financial intermediation
Air transport
Renting of machinery and equipment without operator
and of personal and household goods
Retail trade
Agriculture and shing
Computer activities
Other business activities
Wood, publishing and printing
Wholesale trade
Supporting and auxiliary transport activities;
activities of travel agencies
Research and development
Recreational, cultural and sporting activities
Trade and repair of motor vehicles
Real estate
Textiles and wearing apparel
Source: own calculations using Eurostat data.
0 1 2 3 4 5 6
131

EU industrial structure 2011 — Trends and Performance
The most FDI‑intensive sector in the EU‑27 is financial
intermediation. It is highly internationalised, as both
outward and inward FDI in the EU are relatively important.
Other sectors in which EU firms largely invest outside the
EU are resource‑rich sectors (refined petroleum, extraction
of petroleum and gas and mining and quarrying) or
132
sectors characterised by market‑seeking opportunities —
telecommunications. There is a balance between inward
and outward FDI in the relative FDI intensive sectors
chemicals, other business activities, office machinery
and computers and post and telecommunication,
cf. Figure IV.25.
FIgURE IV.25: Sectoral share in FDI stock relative to share in value added EU-27 in 2007
Financial intermediation
Rened petroleum products and other treatments
Extraction of petroleum and gas
Mining and quarrying
Manufacture of chemicals and chemicals products
Other business activities
Post and telecommunications
Oce machinery and computers
Food products
Water transport
Manufacturing
Radio, television, communication equipments
Electricity, gas and water
Real estate
Mechanical products
Rubber and plastic products
Metal products
Wholesale trade
Wood, publishing and printing
Renting of machinery and equipment without
operator and of personal and household goods
Computer activities
Hotels and restaurants
Retail trade
Trade and repair of motor vehicles
Supporting and auxiliary transport activities;
activities of travel agencies
Air transport
Textiles and wearing apparel
Land transport
Construction
Share of FDI in the country relative to share in total VA
Share of FDI abroad relative to share in total VA
0 1 2 3 4 5 6 7 8 9
Note: FDI intensity is measured as the ratio between the share of a sector’s FDI in total FDI to the share of the sector’s value added to total
value added.
Source: own calculations using Eurostat data.

iv62 internationalisation of r&d
Another feature of increased globalisation is the
internationalisation of corporate research, development
and innovation (R&D&I) activities. 90 Establishing R&D&I
activities abroad is an opportunity to access knowledge,
box IV.8: Measuring the internationalisation of R&D
Chapter IV — International competitiveness of EU industry
which is not necessarily available in the home country. It is
also a way to customise the products and services offered
to local markets abroad. Locating R&D&I abroad is often
a natural extension of the establishment of production
activities. Patent data allows for quantifying this trend.
The indicator provides a sectoral overview, cf. Box IV.8.
There are various ways to measure the internationalisation of R&D&I activities: through patent data; through surveys
such as the Community innovation survey and the European Manufacturing survey; and by using data on R&D
expenditures of foreign affiliates (published by national statistical offices). As this publication focuses on information
at sectoral level, the first type of indicator — patents — was the most suitable. The other two approaches are not
used in this publication because they lack detailed sectoral perspectives.
A patent provides both the location of the inventor and the location of the applicant. Based on these two pieces of
information, one can determine whether the patent is domestic or foreign‑owned. Moreover, patent data is available for
many years, countries and sectors. There are also intrinsic limits in using a patent indicator: not all inventions can be patented,
not all patents lead to a concrete application, and in certain sectors there are more incentives to patent than in others.
Source: European Competitiveness Report 2010.
Internationalisation of R&D has increased considerably in
the EU. The share of foreign owned patent applications in
the EU at the EPO increased from some 10 % in 1990 to 17 %
in 2007. The largest increase has been recorded by intra‑EU
patent applications, cf. Figure IV.26.
FIgURE IV.26: Share of foreign-owned patents in EU-27 patent applications 1990-2007 (%)
9
8
7
6
5
4
3
2
1
0
1990
1991
1992
1993
Note: Patents applications at the EPO.
1994
Source: OECD FATS database US Department of Commerce, ZEW/AIT calculations. 90
1995
1996
1997
1998
1999
2000
2001
2002
2003
Non-european countries
Other European countries
Intra-EU
90 See chapter 3 ‘Foreign corporate R&D and innovation in the European union’ in the European competitiveness report 2010 for more detailed
analyses.
2004
2005
2006
2007
133

EU industrial structure 2011 — Trends and Performance
The most internationalised manufacturing industries
in terms of foreign‑owned patents in the EU‑27 are
manufacture of radio, TV & communication equipment,
134
food products and beverages, office machinery, chemicals
and pharmaceuticals, cf. Figure IV.27.
FIgURE IV.27: Share of foreign-owned patents in EU manufacturing industries 2003-07 (%)
25
20
15
10
5
0
Radio, TV &
communications eq.
Food and drink
Office machinery
Chemicals
Electronic valves
and tubes
Pharmaceuticals
Note: Patents are in absolute numbers.
Source: EPO, ZEW/AIT calculations.
Scientific and
other instruments
Printing and
publishing
Coke and refined
petroleum
Pulp and paper
Electrical
machinery
Outward patenting and R&D outside the own country
is still relatively modest. On average, only 10 % of all EU‑
27 patents were granted abroad between 2003 and 2007;
Rubber and plastics
Textiles
Motor vehicles
Basic metals
Clothing
Non-metallic
mineral products
Machinery nec.
Other transport eq.
Leather and footware
Metal products
Other manufacturing
Wood and
wood products
this is the same level as US patents while BRIC countries
showed a somewhat larger share of outward patenting,
cf. Figure IV.28.
FIgURE IV.28: Share of overseas patents of total patents applications 1991-95 and 2003-07 (%)
16
14
12
10
8
6
4
2
0
EU
Source: OECD Triadic patent database, ZEW/AIT calculations.
US
JP
2003-2007
1991-1995
BRICs
Tobacco

The US is the most important location for EU outward R&D,
accounting for 60 % of overseas patents applied by EU
entities at the EPO. The BRIC share is still small but rising fast
Chapter IV — International competitiveness of EU industry
and is now larger than the Japanese share of EU outward
patenting, cf. figure IV.29.
FIgURE IV.29: Location of overseas patents applied by the EU-27 at EPO 1990-2006 (%)
70
60
50
40
30
20
10
0
1990
1991
1992
1993
1994
1995
Source: European Patent Office, ZEW/AIT calculations.
1996
1997
1998
1999
2000
2001
ROW
Korea
BRICs
Japan
Canada
Other European Countries
US
2002
2003
2004
2005
2006
135

Annexes
A.1 Statistical nomenclature
Table A.1.1 and Table A.1.2 summarise, in the first
two columns, the codes and names of sectors in the
nomenclature of economic activities, NACE Rev. 1 and NACE
TAbLE A.1.1: Sectoral nomenclature for economic activities — nACE rev. 1.1
Rev. 2. The third column contains the abridged versions of
sector names used in the figures and tables. The acronyms
in the fourth column are those used in the scatter plots.
code nacE rev 11 nacE rev 11 (short) acronym
a Agriculture, hunting and forestry Agriculture and forestry agri
b Fishing Fishing fish
c Mining and quarrying Mining and quarrying mine
ca Mining and quarrying of energy producing materials Mining of energy products
cb Mining and quarrying except energy producing materials Other mining othmin
d Manufacturing Manufacturing manuf
da Manufacture of food products; beverages and tobacco Food, drinks and tobacco foodtob
da15 Manufacture of food products and beverages Food and drink food
da16 Manufacture of tobacco products Tobacco tobac
db Manufacture of textiles and textile products Textiles and clothing textcloth
db17 Manufacture of textiles Textiles text
db18 Manufacture of wearing apparel; dressing; dyeing of fur Clothing cloth
dc Manufacture of leather and leather products Leather and footwear foot
dc19 Tanning, dressing of leather; manufacture of luggage Leather and footwear foot
dd Manufacture of wood and wood products Wood and wood products wood
dd20
Manufacture of wood and of products of wood and cork, except
furniture; manufacture of articles of straw and plaiting materials
Wood and wood products wood
de
Manufacture of pulp, paper and paper products; publishing and
printing
Pulp, paper and publishing paper
de21 Manufacture of pulp, paper and paper products Pulp and paper paper
de22 Publishing, printing, reproduction of recorded media Printing and publishing print
df Manufacture of coke, refined petroleum products and nuclear fuel Refined petroleum refin
>>>
137

EU industrial structure 2011 — Trends and Performance
code nacE rev 11 nacE rev 11 (short) acronym
df23 Manufacture of coke, refined petroleum products and nuclear fuel Refined petroleum refin
dg Manufacture of chemicals, chemical products and man‑made fibres Chemicals chem
dg24 Manufacture of chemicals and chemical products Chemicals chem
dh Manufacture of rubber and plastic products Rubber and plastics plas
dh25 Manufacture of rubber and plastic products Rubber and plastics plas
di Manufacture of other non‑metallic mineral products Non‑metallic mineral products miner
di26 Manufacture of other non‑metallic mineral products Non‑metallic mineral products miner
dj Manufacture of basic metals and fabricated metal products Basic metals and metal products metal
dj27 Manufacture of basic metals Basic metals metal
dj28
Manufacture of fabricated metal products, except machinery and
equipment
Metal products metpr
dk Manufacture of machinery and equipment n.e.c. Machinery n.e.c. machin
dk29 Manufacture of machinery and equipment n.e.c. Machinery n.e.c. machin
dl Manufacture of electrical and optical equipment Electrical and optical equipment elecopt
dl30 Manufacture of office machinery and computers Office machinery offmac
dl31 Manufacture of electrical machinery and apparatus n.e.c. Electrical machinery elecmac
dl32
Manufacture of radio, television and communication equipment and
apparatus
Radio, TV & communic. eq. telecom
dl33
Manufacture of medical, precision and optical instruments, watches
and clocks
Scientific and other instruments instr
dm Manufacture of transport equipment Transport equipment transeqpt
dm34 Manufacture of motor vehicles, trailers and semi‑trailers Motor vehicles motor
dm35 Manufacture of other transport equipment Other transport eq. trans
dn Manufacturing n.e.c. Other manufacturing othman
dn36 Manufacture of furniture; manufacturing n.e.c. Furniture; other manufacturing furnit
dn37 Recycling Recycling recyc
e Electricity, gas and water supply Electricity, gas and water supply electr
e40 Electricity, gas, steam and hot water supply Electricity and hot water supply
e41 Collection, purification and distribution of water Collection and distribution of water
f Construction Construction const
f45 Construction Construction
g
Wholesale and retail trade; repair of motor vehicles, motorcycles and
personal and household goods
Wholesale and retail trade wholretra
g50 Sale, maintenance and repair of motor vehicles Sale and repair of motor vehicles salemot
g51
Wholesale trade and commission trade, except of motor vehicles and
motorcycles
Wholesale trade wholtr
g52
Retail trade, except of motor vehicles, motorcycles; repair of personal
and household goods
Retail trade retra
h Hotels and restaurants Hotels and restaurants hotel
h55 Hotels and restaurants Hotels and restaurants hotel
i Transport, storage and communication Transport and communication transcom
i60 Land transport; transport via pipelines Inland transport inltran
i61 Water transport Water transport watran
i62 Air transport Air transport airtran
i63
Supporting and auxiliary transport activities; activities of travel
agencies
Supporting transport activities suptran
i64 Post and telecommunications Communications comm
j Financial intermediation Financial intermediation fin
j65 Financial intermediation, except insurance and pension funding Financial intermediation finint
j66 Insurance and pension funding, except compulsory social security Insurance and pension funding insur
j67 Activities auxiliary to financial intermediation
Activities auxiliary to financial
intermediation
auxfin
>>>
138

Annexes
code nacE rev 11 nacE rev 11 (short) acronym
k Real estate, renting and business activities Real estate and business activities realbus
k70 Real estate activities Real estate activities reest
k71
Renting of machinery and equipment without operator and of personal
and household goods
Renting of machinery and
equipment
k72 Computer and related activities Computer and related activities compu
k73 Research and development Research and development r&d
k74 Other business activities Other business activities
l Public administration and defence; compulsory social security Public administration pubadmin
m Education Education educ
n Health and social work Health and social work health
o Other community, social, personal service activities Other services othser
TAbLE A.1.2: Sectoral nomenclature for economic activities — nACE rev. 2
code nacE rev 2 nacE rev 2 (short) acronym
a Agriculture, forestryand fishing Agriculture and forestry agri
B Mining and quarrying Mining and quarrying mine
c Manufacturing Manufacturing manuf
c10 Manufacture of food products Food food
c11 Manufacture of beverages Beverages beverag
c12 Manufacture of tobacco products Tobacco tobac
c13 Manufacture of textiles Textiles text
c14 Manufacture of wearing apparel Clothing cloth
c15 Manufacture of leather and related products Leather & footwear foot
c16
Manufacture of wood and of products of wood and cork, except
furniture; manufacture of articles of straw and plaiting materials
Wood & wood products wood
c17 Manufacture of pulp, paper and paperboard Paper paper
c18
Printing and reproduction
of recorded media
Printing print
c19 Manufacture of coke and refined petroleum products Refined petroleum refin
c20 Manufacture of chemicals and chemical products Chemicals chem
c21
Manufacture of basic pharmaceutical products and pharmaceutical
preparations
Pharmaceuticals pharma
c22 Manufacture of rubber and plastic products Rubber & plastics plas
c23
Manufacture of
other non‑metallic mineral products
Non‑metallic mineral products miner
c24 Manufacture of basic metals Basic metals metal
c25
Manufacture of fabricated metal products, except machinery and
equipment
Metal products metpr
c26 Manufacture of computer, electronic and optical products
Computers, electronic &
optical
comput
c27 Manufacture of electrical equipment Electrical equipment electreq
c28 Manufacture of machinery and equipment n.e.c. Machinery n.e.c. machin
c29 Manufacture of motor vehicles, trailers and semi‑trailers Motor vehicles motor
c30 Manufacture of other transport equipment Other transport eq. trans
c31 Manufacture of furniture Furniture furnit
c32 Other manufacturing Other manufacturing othmanuf
c33 Repair and installation of machinery and equipment Repair of machinery repair
d Electricity, gas, steam and air conditioning supply Electricity and gas electr
d35 Electricity, gas, steam and air conditioning supply Electricity and gas electr
>>>
rentm
139

EU industrial structure 2011 — Trends and Performance
code nacE rev 2 nacE rev 2 (short) acronym
E Water supply; sewerage, waste management and remediation activities Water supply water
E36 Water collection, treatment and supply Water collection Watercol
E37 Sewerage Sewerage Sewer
E38 Waste collection, treatment and disposal activities; materials recovery Waste collection wastcol
E39 Remediation activities and other waste management services Remediation activities othwast
F Construction Construction const
F 41 Construction of buildings Construction buildings build
F42 Civil engineering Civil engineering civeng
F43 Specialised construction activities Specialised construction Specconstr
g45 Wholesale and retail trade and repair of motor vehicles and motorcycles Wholesale and retail trade wholretra
g46 Wholesale trade, except of motor vehicles and motorcycles Wholesale trade wholtr
g47 Retail trade, except of motor vehicles and motorcycles Retail trade retra
h Transportation and storage Transportation & storage trans
h49 Land transport and transport via pipelines Inland transport inltran
h50 Water transport Water transport watran
h51 Air transport Air transport airtran
h52 Warehousing and support activities for transportation
Wharehousing & support
activities for transportation
wharehous
h53 Postal and courier activities Postal & courier postal
i Accomodation and food service activities Accomodation & food accomodfood
i55 Accommodation Accommodation accomod
i56 Food and beverage service activities Food & beverage foodbev
J Information and Communication Information & Communication infocom
J58 Publishing activities Publishing publish
J59
Motion picture, video and television programme production, sound
recording and music publishing activities
Motion picture, TV & Music tvmusic
J60 Programming and broadcasting activities
Programming & broadcasting
activities
broadcast
J61 Telecommunications Telecommunications telecom
J62 Computer programming, consultancy and related activities
Computer programming &
consultancy activities
compu
J63 Information service activities Information infocom
K Financial and insurance activities Financial & insurance activities financinsur
K64 Financial service activities, except insurance and pension funding Financial activities financ
K65
Insurance, reinsurance and pension funding, except compulsory social
security
Insurance activities insur
K66 Activities auxiliary to financial services and insurance activities
Activities auxiliary to financial
and insurance activities
auxfinancinsur
l Real Estate activities Real Estate activities reest
l68 Real estate activities Real Estate activities reest
m Professional, Scientific and Technical activities
Professional, Scientific and
Technical activities
scientech
m69 Legal and accounting activities Legal and accounting activities legaccount
m70 Activities of head offices Activities of head offices headof
m71 Architectural and engineering activities Architecture & Engineering archiengin
m72 Scientific research and development
Scientific research and
development
scienc
m73 Advertising and market research Advertising & market research advert
m74 Other professional, scientific and technical activities
Other professional, scientific
and technical activities
othscienc
m75 Veterinary activities Veterinary activities veteri
n Administrative and support service activities Administration admin
n77 Rental and leasing activities Rental & leasing activities rental
>>>
140

code nacE rev 2 nacE rev 2 (short) acronym
n78 Employment activities Employment activities empl
Annexes
n79
Travel agency, tour operator and other reservation service and related
activities
Supporting transport activities suptran
n80 Security and investigation activities
Security & investigation
activities
secur
n81 Services to buildings and landscape activities Services to buildings servbuild
n82 Office administrative, office support and other business support activities Office support officesup
O Public Administration and Defence Public Administration pubadmin
O84 Public administration and defence Public Administration pubadmin
p Education Education educ
Q Human health and social work activities Human health and social work health
Q86 Human health activities Human health activities health
Q87 Residential care activities Residential care activities residcare
Q88 Social work activities without accommodation Social work activities socwork
r Arts, entertainment and recreation Arts & entertainment artentertain
r90 Creative, arts and entertainment activities Creative activities creative
r91 Libraries, archives, museums and other cultural activities Cultural activities cultu
r92 Gambling and betting activities Gamble gambl
r93 Sports activities and amusement and recreation activities Leisure leis
s Other services activities Other services activities othser
s94 Activities of membership organisations Membership organisations memberorg
s95 Repair of computers and personal and household goods
Computer and related
activities
compu
s96 Other personal service activities
Other personal service
activities
othpersser
t Activities of households as employers Households as employers househol
t97 Activities of households as employers of domestic personnel
Households as employers of
domestic personnel
househol
t98
Undifferentiated goods‑ and services‑producing activities
of private households for own use
Private households for own
use
privhousehol
u Activities of extraterritorial organisations and bodies
Extraterritorial organisations
and bodies
extraorg
u99 Activities of extraterritorial organisations and bodies
Extraterritorial organisations
and bodies
extraorg
Table A.1.3 presents final consumption expenditure of households by consumption purpose (COICOP) on a 3‑digit level for
different goods and services.
TAbLE A.1.3: Sectoral nomenclature for consumption activities (COICOP)
total total
cp01 Food and non‑alcoholic beverages
cp011 Food
cp012 Non‑alcoholic beverages
cp02 Alcoholic beverages, tobacco and narcotics
cp021 Alcoholic beverages
cp022 Tobacco
cp023 Narcotics
cp03 Clothing and footwear
cp031 Clothing
cp032 Footwear including repair
cp04 Housing, water, electricity, gas and other fuels
cp041 Actual rentals for housing
>>>
total total
cp042 Imputed rentals for housing
cp043 Maintenance and repair of the dwelling
cp044
Water supply and miscellaneous services relating
to the dwelling
cp045 Electricity, gas and other fuels
cp05
Furnishings, household equipment and routine
maintenance of the house
cp051 Furniture and furnishings, carpets and other floor coverings
cp052 Household textiles
cp053 Household appliances
cp054 Glassware, tableware and household utensils
cp055 Tools and equipment for house and garden
>>>
141

EU industrial structure 2011 — Trends and Performance
142
total total
cp056
Goods and services for routine household
maintenance
cp06 Health
cp061 Medical products, appliances and equipment
cp062 Out‑patient services
cp063 Hospital services
cp07 Transport
cp071 Purchase of vehicles
cp072 Operation of personal transport equipment
cp073 Transport services
cp08 Communications
cp081 Postal services
cp082 Telephone and telefax equipment
cp083 Telephone and telefax services
cp09 Recreation and culture
cp091
Audio‑visual, photographic and information
processing equipment
cp092 Other major durables for recreation and culture
cp093
Other recreational items and equipment, gardens and
pets
>>>
Table A.1.4 presents the extended balance of payments
services classification used in this publication. Royalties and
TAbLE A.1.4: Sectoral nomenclature for trade in services activities 91
1. Transportation
2. Travel
3. Communications services
4. Construction services
5. Insurance services
6. Financial services
7. Computer and information services
8. Royalties and license fees
9. Other business services
10. Personal, cultural, and recreational services
11. Government services
91 For a more detailed description, see European Central Bank
(2007).
total total
cp094 Recreational and cultural services
cp095 Newspapers, books and stationery
cp096 Package holidays
cp10 Education
cp101 Pre‑primary and primary education
cp102 Secondary education
cp103 Post‑secondary non‑tertiary education
cp104 Tertiary education
cp105 Education not definable by level
cp11 Restaurants and hotels
cp111 Catering services
cp112 Accommodation services
cp12 Miscellaneous goods and services
cp121 Personal care
cp122 Prostitution
cp123 Personal effects n.e.c.
cp124 Social protection
cp125 Insurance
cp126 Financial services n.e.c.
cp127 Other services n.e.c.
license fees were not included as it is not related to a special
service activity.

TAbLE A.1.5: Classification of products by activities (CPA)
code description
Annexes
01 Crop and animal production, hunting and related service activities
02 Forestry and logging
03 Fishing and aquaculture
05 Mining of coal and lignite
06 Extraction of crude petroleum and natural gas
07 Mining of metal ores
08 Other mining and quarrying
09 Mining support service activities
10 Manufacture of food products
11 Manufacture of beverages
12 Manufacture of tobacco products
13 Manufacture of textiles
14 Manufacture of wearing apparel
15 Manufacture of leather and related products
16 Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials
17 Manufacture of paper and paper products
18 Printing and reproduction of recorded media
19 Manufacture of coke and refined petroleum products
20 Manufacture of chemicals and chemical products
21 Manufacture of basic pharmaceutical products and pharmaceutical preparations
22 Manufacture of rubber and plastic products
23 Manufacture of other non‑metallic mineral products
24 Manufacture of basic metals
25 Manufacture of fabricated metal products, except machinery and equipment
26 Manufacture of computer, electronic and optical products
27 Manufacture of electrical equipment
28 Manufacture of machinery and equipment n.e.c.
29 Manufacture of motor vehicles, trailers and semi‑trailers
30 Manufacture of other transport equipment
31 Manufacture of furniture
32 Other manufacturing
33 Repair and installation of machinery and equipment
35 Electricity, gas, steam and air conditioning supply
36 Water collection, treatment and supply
37 Sewerage
38 Waste collection, treatment and disposal activities; materials recovery
39 Remediation activities and other waste management services
41 Construction of buildings
42 Civil engineering
43 Specialised construction activities
45 Wholesale and retail trade and repair of motor vehicles and motorcycles
46 Wholesale trade, except of motor vehicles and motorcycles
47 Retail trade, except of motor vehicles and motorcycles
49 Land transport and transport via pipelines
50 Water transport
51 Air transport
52 Warehousing and support activities for transportation
53 Postal and courier activities
55 Accommodation
56 Food and beverage service activities
58 Publishing activities
59 Motion picture, video and television programme production, sound recording and music publishing activities
60 Programming and broadcasting activities
61 Telecommunications
62 Computer programming, consultancy and related activities
63 Information service activities
>>>
143

EU industrial structure 2011 — Trends and Performance
code description
64 Financial service activities, except insurance and pension funding
65 Insurance, reinsurance and pension funding, except compulsory social security
66 Activities auxiliary to financial services and insurance activities
68 Real estate activities
69 Legal and accounting activities
70 Activities of head offices; management consultancy activities
71 Architectural and engineering activities; technical testing and analysis
72 Scientific research and development
73 Advertising and market research
74 Other professional, scientific and technical activities
75 Veterinary activities
77 Rental and leasing activities
78 Employment activities
79 Travel agency, tour operator and other reservation service and related activities
80 Security and investigation activities
81 Services to buildings and landscape activities
82 Office administrative, office support and other business support activities
84 Public administration and defence; compulsory social security
85 Education
86 Human health activities
87 Residential care activities
88 Social work activities without accommodation
90 Creative, arts and entertainment activities
91 Libraries, archives, museums and other cultural activities
92 Gambling and betting activities
93 Sports activities and amusement and recreation activities
94 Activities of membership organisations
95 Repair of computers and personal and household goods
96 Other personal service activities
97 Activities of households as employers of domestic personnel
98 Undifferentiated goods‑ and services‑producing activities of private households for own use
99 Activities of extraterritorial organisations and bodies
144

A.2 List of abbreviations
BEC Broad economic classification
BRIC Brazil, Russia, India and China
CPA Classification of products by activity
COICOP Classification of individual consumption by
purpose
COMEXT Statistical database from and between
European Union countries
COMTRADE Commodity Trade Statistics Database
EPO European Patent Office
FDI Foreign direct investment
IIT Intra‑industry trade
GDP Gross domestic product
GFCF Gross fixed capital formation
GL Grubel‑Loyd
ICT Information and communication technologies
IMF International Monetary Fund
IO Input‑ouput
M Imports
AT Austria
BE Belgium
BG Bulgaria
CY Cyprus
CZ Czech Republic
DE Germany
DK Denmark
EE Estonia
ES Spain
EU European Union
EU‑27 27 Member States of the European Union
FI Finland
FR France
GR Greece
HU Hungary
abbreviations
The following symbols are used in this publication:
na not available
0 figure is zero or became zero due to rounding
‑ not applicable
Small discrepancies between constituent figures and totals are due to rounding.
Closing date 30/06/2011
NACE Nomenclature Générale des Activités
Annexes
OECD
Économiques dans les Communautés
Européennes (French, EU classification system)
Organisation for Economic Cooperation and
Development
PAT Patent
RCA Revealed comparative advantage
R&D Research and development
RTB Relative trade balance
SBS Structural Business Statistics from Eurostat
Si Specialisation index
ULC Unit labour cost
UN United Nations
UNIDO United Nations industrial development
organisation
USPO The United States Patent and Trademark Office
WTO World Trade Organisation
X Exports
IE Ireland
IT Italy
LT Lithuania
LU Luxembourg
LV Latvia
MT Malta
NL Netherlands
PL Poland
PT Portugal
RO Romania
SE Sweden
SI Slovenia
SK Slovakia
UK United Kingdom
US United States
145

EU industrial structure 2011 — Trends and Performance
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148

European Commission
Eu industrial structure 2011 — trends and performance
Luxembourg: Publications Office of the European Union
2011 — 148 pp. — 21 x 29.7 cm
ISBN 978‑92‑79‑20733‑4
doi:10.2769/28487

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EU industrial structure 2011
Trends and Performance
The production of EU industrial structure is a response to the increasing interest in analysing
the competitiveness of the EU economy from a sectoral perspective. This publication
provides insight into the relative performance of individual industries, and contributes to
explaining the competitiveness of the EU economy at large. The publication covers market
sectors, from mining to market services, although, wherever necessary, it refers to the whole
economy, including primary sectors and non-market services.
The work is empirical and data oriented and consists of the creation and analysis of a system
of statistical indicators on various facets of sectoral performance and competitiveness. The
indicators cover fi elds of relevance to gain insight into the economics and policy issues
of EU sectors. The publication applies the same set of indicators to all sectors and uses
input–output data to go beyond the analysis of individual sectors separately buy capturing
sectoral interrelations, such as those between manufacturing and services sectors. From
a geographical point of view the publication covers the EU-27 as a whole and individual
Member States and it also makes comparisons with other countries, such as the US, Japan
and BRIC countries (Brazil, Russia, India, China), wherever possible.
The 2011 edition of EU industrial structure covers the following topics: the recent economic
downturn and its fragile recovery, EU sectoral structure, EU sectoral growth and the
international competitiveness of EU industry. This publication follows the path laid by EU
sectoral competitiveness indicators (2005) and EU industrial structure 2007 and EU industrial
structure 2009.
NB-BL-11-001-EN-C