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EU industrial structure - EU Bookshop - Europa

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

7


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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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

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