The urban and regional dimension of Europe 2020 : seventh progress report on economic, social and territorial cohesion.
Date: 2012-01-24
Institutions: Directorate-General for Regional and Urban Policy
Subjects: economic and social cohesion, regional development, regional economy, regional investment, regional policy, urban sociology

EN

The urban and regional dimension  
of Europe 2020
Seventh progress report on economic,  
social and territorial cohesion

Report from the Commission

November 2011

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The urban and regional dimension  
of Europe 2020
Seventh progress report on economic,  
social and territorial cohesion

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Table of contents

1. 

Introduction  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

2.  Smart growth. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7
2.1.  Education and training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2.  Research and Innovation  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.3.  Digital society . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.4.  Creative cities: Hubs of innovation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

3.  Sustainable growth  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.1.  Resource efficient Europe. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
 Sustainable cities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11
3.2. 

4. 

Inclusive growth  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
4.1.  Employment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13
 Poverty and exclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13
4.2. 
Inclusive cities: the urban paradox . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14
4.3. 

5.  Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Annexes  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

All the data behind the maps and charts of the 7th Progress Report can be downloaded here:  

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Please note that this link may not work with certain versions of Internet Explorer.  
Please try Chrome, Opera or Firefox if you encounter problems. 

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Foreword

The seventh progress report on economic, social and territorial cohesion highlights the urban and regional 
dimension of the Europe 2020 strategy. This report was adopted shortly after the publication of legislative 
proposals for the cohesion policy period 2014 to 2020. These proposals underline the critical contribution 
cohesion policy will make to smart, sustainable and inclusive growth and the Europe 2020 headline targets.

This report shows that cities and regions are faced with different combinations of development problems 
and growth potential. This is one of the main reasons cohesion policy uses an integrated approach that 
can be adjusted to local needs and opportunities. 

Cities contain some of the biggest contradictions. Cities are highly productive, yet productivity growth in 
most cities was below the national average. Living and working in cities is less polluting, but city dwellers 
are exposed to more pollution. Cities offer the greatest concentration of employment opportunities, but 
in many Member States cities have the highest share of jobless households. 

To support the preparation of the new cohesion policy programmes, this report measures the distance of 
EU regions to their national 2020 targets. This provides each region with a baseline, which can be used in 
regional development strategies, programme monitoring and evaluations. 

This analysis does not imply that all regions can or should reach the national 2020 targets. This is neither real-
istic nor desirable. The clustering of R&D, for example, can generate strong, positive spillovers. The concentra-
tion of poverty and exclusion, however, can intensify deprivation, making it even more difficult to address. 
The real challenge is to identify how cohesion policy can make the biggest contribution to positive change. 

In conclusion, for the next round of cohesion policy, programmes should select their investment priorities 
taking into account their baseline and concentrate on domains where investments will make the biggest 
contribution to smart, sustainable and inclusive growth. In this way, cohesion policy will become the efficient, 
results-oriented, integrated policy that the Union needs to realise its Europe 2020 strategy.

Johannes Hahn
Member of the European Commission 
in charge of Regional Policy

László Andor
Member of the European Commission in charge 
of Employment, Social Affairs and Inclusion

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Introduction

1

In June 2010, the European Council approved the Europe 

This progress report assesses how, in the context of cohe-

2020 strategy, the EU’s strategy for smart, sustainable and 

sion policy, regions and cities can contribute to three types 

inclusive growth. Regional and local authorities can make 

of growth of the Europe 2020 strategy. It measures the distance 

a key contribution to this strategy through the actions that 

of cities and regions to the national 2020 targets proposed 

fall within their responsibility. This is particularly critical in 

in the national reform programmes. This distance to target 

more decentralised or federal Member States. 

depends on the disparities with the country, the ambition of 

the NRP and expected speed of change.

Involving  regional  authorities  in  European  policies  can 

increase the efficiency of these policies, as highlighted by 
a number of recent studies (1). An integrated regional, or 

This analysis does not imply that all regions can or should 

reach all their national or the EU targets. For some regions, 

place-based, approach can be more efficient for policies 

the distance to the target is simply too great. Furthermore, 

with marked externalities and in countries with substantial 

for some issues it is not realistic or desirable that all regions 

internal disparities. Such an approach, however, requires 

reach the same target. For example, R&D is highly concen-

a strong administrative and institutional capacity and the 

trated in part due to benefits of clustering research. The 

right national framework conditions. 

concentration of poverty and exclusion, however, has a lot 

In the fifth Cohesion Report (2), the Commission proposed 

of negative effects. 

to further strengthen the regional and urban dimension of 

In short, cohesion policy programmes should select their 

cohesion policy and its partnership principle. The following 
public debate showed clear support for these changes (3). 

investment priorities taking into account the starting position 

of a region or city in relation to the national 2020 targets and 

The regulations for the period 2014-2020 put forward by the 

identify the concentrations to promote and the ones to fight. 

Commission on 6 October 2011 show how these changes 
will be implemented (4). 

Cohesion  Policy  is  a  key  delivery  mechanism  for  Europe 
2020 (5), with a long tradition of designing and implementing 

integrated regional and urban programmes in partnership 

with regional and local authorities, economic actors, social 

partners and civil society. It can provide Europe 2020 with 

the active support of regional and local authorities it needs 

to succeed.

1. 

2.  

3. 
4. 
5. 

 An Agenda for a Reformed Cohesion Policy, F. Barca, 2009. http://ec.europa.eu/regional_policy/archive/policy/future/barca_en.htm 
and The balance between sectoral and integrated approaches and the involvement of sub-national levels in EU Member States.  
http://ec.europa.eu/regional_policy/information/studies/index_en.cfm#2
 Fifth Report on economic, social and territorial cohesion, 2011.  
http://ec.europa.eu/regional_policy/sources/docoffic/official/reports/cohesion5/index_en.cfm 
SEC(2011) 590 http://ec.europa.eu/regional_policy/consultation/5cr/pdf/5cr_result_sec2011590.pdf 
See COM(2011) 615 http://ec.europa.eu/regional_policy/what/future/proposals_2014_2020_en.cfm#1 
 See: A strategy for smart, sustainable and inclusive growth, COM(2010) 2020. 
http://ec.europa.eu/europe2020/documents/related-document-type/index_en.htm

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Smart growth

2

The smart growth objective is to improve education, promote 

is  significant  for  many  regions  in  Portugal,  Slovakia  and 

R&D  and  innovation  and  move  towards  a  digital  society. 

Germany (see annex 1).

Through investments in education, training, research and 

innovation, the EU economy can become more productive 

The  variation  in  human  capital  between  regions  within 

and maintain or increase its global market share. This can 

a Member State is often larger than between Member States. 

in turn help to increase the number of jobs and improve 

Therefore, the national strategies need to be complemented 

their quality.

by regional policies. A recent report suggests that delegating 
more human capital development decisions to the regions (10) 

2.1.  Education and training

can be more effective. 

Human capital is one of the key determinants of regional 
growth (6). High levels of education attainment favour inno-

Europe 2020 aims to reduce the share of early school leav-

ers to less than 10 %. The share is significantly higher in most 

vation as it facilitates the rapid diffusion and absorption of 

southern European regions. In contrast, it is much lower in 

new  knowledge  and  techniques.  Regional  development 

Poland, Slovenia, Slovakia, Austria and the Czech Republic. 

is therefore closely linked to the capacity to create, retain 

The  distance  to  the  national  target  is  highest  in  Spanish 

and attract human capital, which is linked to the quality of 

and Portuguese regions and some regions in Greece, Italy 

education institutions and life-long learning opportunities. 

and Bulgaria. For this target, the convergence regions score 

Investment in education and training should go hand in hand 

better than the other regions, with almost half respecting 

with policy reforms, such as those included in the education 

this target compared to only one in four for the RCE and 

and training strategy ET 2020.

transition regions (see annex 2).

Developing and attracting (entrepreneurial) talent (7) has 

become a key source of growth as this can boost the inno-

2.2. Research and Innovation

vative milieu and can lead to more innovative, high-growth 
firms (8) in a region. 

The Innovation Union flagship underlines the role of research 

and innovation boosting job creation and economic growth. 

Regions are playing a more important role in innovation pol-

The Europe 2020 target is to increase the share of people 

icy for two reasons: the recognition of the regional and local 

aged 30-34 with a tertiary degree to 40 % by 2020. Currently, 

dimensions in national innovation strategies and the increas-

only one in five EU regions has reached this target. Member 

ing role of innovation in regional development strategies. 

States have set themselves targets ranging from 26 % to 60 %. 

The  regions  eligible  under  the  regional  competitiveness 

Research and innovation tends to be concentrated in a few 

and employment (RCE) objective score the best with (one in 
three), the transition (9) regions score average (one in four), 

economically successful regions, but a large range of develop-

ment paths exist across Europe. Also the institutional frame-

while the convergence regions score poorly (one in twenty). 

works for innovation policies are extremely varied, in terms 

of the competences of regional governments, the match 

The share of tertiary educated tends to be higher in capitals 

between administrative and functional regions, and cross-

and adjoining regions, several of which have already reached 

regional relationships. 

the Europe 2020 target. The distance to the national target 

6. 
7. 
8. 
9. 
10. 

See Regional Outlook, Paris, OECD, 2011.
See Sixth Progress Report: Creative and innovative regions. COM(2009) 295.
This is the new Europe 2020 innovation indicator.
Phasing In and Phasing Out regions are grouped as Transition regions since both receive transitional support.
 Human Capital Leading Indicators. Policy Brief, Vol. V, No. 1, P. Ederer et al. Lisbon Council, Brussels, 2011. 
http://www.lisboncouncil.net/publication/publication/64-leadingindicators.html

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Some regional innovation policies focus too narrowly on 

The Europe 2020 target is 3 % of GDP to invest in R&D and 

science and technology, which need a certain scale or criti-

Member  States  have  defined  national  targets  for  invest-

cal mass of activities not present in all regions. Innovation, 

ments in R&D. In 2009, R&D expenditure represented 2 % of 

however, goes far beyond science and technology and also 

GDP in the EU-27. R&D is typically concentrated in core areas 

includes organisational and process innovation, creativity 

such as capital and metropolitan regions. In 2008, expendi-

and design.

ture exceeded the Europe 2020 target in 24 out of 159 RCE 

regions, but only in one out of 84 convergence regions and 

A regional innovation strategy should involve a rigorous 

not in a single transition region. On average R&D expendi-

assessment  of  a  region’s  strengths  and  weaknesses  and 

ture of the convergence regions is only 0.9 % of their GDP 

benchmarking  with  other  similar  regions.  The  strategy 

(see table 1). The RCE regions exceeding the Europe 2020 

should cover all dimensions of innovation and involve key 

target are mostly located in northern countries (Germany, 

regional actors to identify targets and the appropriate policy 

UK, Sweden and Finland), Austria and capital regions such 

mix. Human capital is a key source of innovation. 

as  Hovedstaden  (Copenhagen)  and  Île  de  France  (Paris). 

In 2008, only 16 regions across Europe have reached the 

The level of technological innovation and the speed of its 
diffusion and absorption differ widely between EU regions (11). 

national targets set by 2020. Therefore, significant efforts 

are needed in all Member States to meet the national targets 

Regions  with  the  highest  innovative  capabilities  can  be 

in this respect (see annex 3). 

found in northern Europe, typically in the most innovative 

countries. However, a few regions outperform their national 

levels also in less developed countries, providing a general 

picture of high concentration of technological capabilities 

in few regions across Europe. 

Table 1: Indicators by type of region

Indicator

Year

Convergence

Transition

RCE

Tertiary educated aged 30-34, in %

Early school leavers aged 18-24, in %

2007-10

2008-10

RD as % of GDP

Employment rate aged 20-64, in %

Unemployment rate, in %

At risk of poverty or exclusion *, in %

Severe material deprivation *, in %

At risk of poverty **, in %

Low work intensity *, in %

GDP per head index (in PPS)

2008

2010

2010

2009

2009

2009

2009

2008

Change in GDP per head index

2000-2008

25

13

0.9

63

12

31

16

21

6.7

62

8.6

33

18

1.0

64

15

25

7.5

18

7.3

93

4.7

37

14

2.0

72

7.9

19

4.3

14

7.0

120

-6.1

* Only national figures were available for DE, FR, NL, PT, RO, UK and only NUTS 1 in BE, EL and HU.
** For Portugal 2005 NUTS 2 figures were used.

EU

32

14

1.9

69

9.7

23

8.1

16

9.0

100

0

11.  

 See The regional impact of technological change in 2020 by Wintjes and Hollanders 2010. 
http://ec.europa.eu/regional_policy/information/studies/index_en.cfm#1

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2.3. Digital society

The coverage and use of broadband internet tends to be 
higher in urban areas (15) than in rural areas, but in countries 

The Digital Agenda for Europe (12) promotes the fast develop-

with high share of broadband coverage this gap has almost 

ment of digital technologies and an inclusive digital society. 

disappeared. The ultra fast next generation access networks 

The availability of high-speed networks is a key factor for 

are also expected to be rolled out in large cities first. 

competitiveness, as it determines the capacity of regions to 

compete in and benefit from the global knowledge-based 

The innovative capacity of cities can also be demonstrated 

economy, technology and market.

through their productivity. Three out of four metropolitan 

areas in the EU have a higher level of productivity than the 

According to the 2011 digital agenda scoreboard, broad-

other  regions  in  their  country.  But  higher  productivity 

band (DSL) coverage in 2010 reached 95 % of the total pop-

should not be equated with higher productivity growth. 

ulation. Coverage in rural areas is significantly lower (83 %) 

Between 2000 and 2008, only two out of five metropolitan 

and represents a challenge for a number of countries where 

areas experienced higher productivity growth than the other 

less than 60 % of the rural population has access to broad-

regions in their country. 

band (Bulgaria, Slovakia, Poland and Romania). Nevertheless, 
the gap between urban and rural areas (13) has been reduced 

The comparative advantage of metro regions is strongest in 

in the recent years (e.g. Romania and Cyprus). Still further 

the Member States of central and eastern Europe, where 

investments are needed to reach the broadband targets.

metropolitan areas often have a level of productivity more 

The utilisation of the networks for private and public e-services 

is also growing but still involves a relatively limited share of 

than 50 % higher than in the rest of the country. However, 

this often only applies to the capital region, while the pro-
ductivity of secondary growth poles (16) lags further behind 

the European population. In 2010, only 41 % of the population 

the capital region than in more developed Member States. 

interacted  online  with  public  authorities  and  only  40 % 

ordered goods or services online. The percentage of turn-

over of enterprises generated online rose from 8.6 % in 2004 

to almost 14 % in 2010, confirming a trend of increasingly 

dynamic growth in this area. However, important barriers 

to the digital single market remain to be addressed. 

2.4.  Creative cities:  

Hubs of innovation

Cities have always been centres of specialisation and inno-

vation. For example, patenting is highly concentrated in a few 
metro regions (14) (see annex 4). Given the high concentra-

tion of innovative activities in cities, the full utilisation of 

their  potential  represents  one  of  the  main  resources  for 

strengthening  regional  innovation  in  both  convergence 

and RCE regions. In virtually all Member States, the share of 

tertiary educated aged 25-64 is higher in cities than in other 

areas. In 22 Member States, the share is between 10 and 25 

percentage points (pp) higher in cities (see Figure 1). 

12.  http://ec.europa.eu/information_society/digital-agenda/publications/index_en.htm
13. 

 In the EU, 47 % of the population lives in urban areas or cities, 25 % in towns and suburbs and 28 % in rural areas  
based on the degree of urbanisation classification. 
 Metro regions are one or more NUTS 3 regions that represent an agglomeration of more than 250 000 inhabitants.  
For more detail see Regional Focus 01/2011. L. Dijkstra and H. Poelman, 2011. http://ec.europa.eu/regional_policy/information/focus/index_en.cfm

14. 

15.  See Eurostat Regional Yearbook 2011, chapter 16.
16.   See ESPON interim report of Secondary Growth Poles.

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Sustainable growth

3

The sustainable growth objective aims to enhance resource 
efficiency (17) and to help the EU prosper in a low-carbon 

Some Member States are close to the target they set under 

the Climate and Energy Package. For instance Sweden has 

world,  while  preventing  environmental  degradation  and 

to increase the share of renewables by another 4.6 pp to 

biodiversity loss as well as a more competitive economy. 

reach it target of 49 % by 2020. For some, the distance to the 

It promotes more water efficiency and the use of waste as 

target is far greater and additional efforts will be required 

a  resource.  It  addresses  combating  climate  change  and 

to reach it on time. For example, the United Kingdom and 

strengthening the resilience of our territories to climate risks. 

Ireland want to increase their share of renewables by 13 and 

This includes the reduction of greenhouse gas emissions, 

12 pp by 2020. 

the promotion of renewable energies and more efficient 

energy supply systems.

3.1.  Resource efficient Europe

Sustainable growth has an important regional dimension. 

Regional characteristics directly determine the extent to 

which EU regions can produce renewable energy. For exam-

ple, the production of solar and wind energy is highly loca-

The Europe 2020 strategy aims to reduce greenhouse gas 

tion dependent. Coastal regions tend to have a high wind 

emissions by at least 20 % (and 30 %, if the conditions are 

energy potential, while southern regions with more sunny 

right) compared to 1990, and to increase energy efficiency 

days have more potential for solar energy. Moving renewa-

and the consumption of renewable energy both by 20 %.

ble energy between regions with a high potential to regions 

with a high demand will require the development of better 

Under the ‘Effort Sharing Decision’ (18), Member States have 

and more intelligent energy networks. 

adopted a mix of emission reduction targets and limits on 

emission increases (see annex 5). Some have already reached 

Regions can reduce greenhouse gas emissions by promot-

their target and only need to maintain this lower level of 

ing cleaner modes of public transport and shifting to more 

emissions. Greece, for example, committed to reduce emis-

sustainable modes of transport. Initiatives to promote cleaner 

sions by 4 % compared to 2005 levels and already had cut 

and more efficient transport have to adapt to the local con-

them  by  almost  7 %  in  2009.  Others  committed  to  limit 

text, focusing on the infrastructure in regions where it is still 

the increase in emissions and actually reduced them, like 

lacking  while  targeting  the  attractiveness  of  sustainable 

Slovakia  which  agreed  to  limit  the  increase  to  13 %,  but 

transport modes and demand management in other regions.

actually reduced emissions by 12 %. 

Regions can play a prominent role in fostering energy effi-

On the other hand, some Member States will have to reduce 

ciency. This is particularly true as regards buildings, where 

their greenhouse gas emissions significantly. For instance 

actions must adapt to the local context and climate. These 

Ireland, Denmark and Luxembourg still need to cut emissions 

actions are likely to be different between urban and rural 

by more than 10 percentage points to reach their target. 

areas or between places with old versus more recent build-

ings. The objective, however, remains the same: improving 

The picture is similar for renewable energy consumption 

energy performance in conformity with EU legislation.

(see annex 6). The share of renewable energy in gross final 

energy consumption varies from 44 % in Sweden to 0.2 % in 

Malta. All Member States, except Latvia and Slovenia, have 

increased renewable energy consumption, with especially 

high increases in Austria, Estonia and Romania. 

17.   See Roadmap to a Resource Efficient Europe. COM(2011) 571.
18.  

 In the Climate and Energy Package, the overall emission reduction goal will be accomplished through (1) the EU Emissions Trading System (ETS) and  
(2) the ‘Effort Sharing Decision’. This last decision establishes for the period 2013-2020 annual binding national greenhouse gas emission targets with 
2005 as a base year from sectors not included in the ETS – such as transport, buildings, agriculture and waste. Cohesion Policy actions can play a role 
in reducing GHG emissions in these sectors, but should not subsidise emissions reductions already covered by the ETS.

10 Report from the Commission to the European Parliament and the Council

Seventh progress report on economic, social and territorial cohesion

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3.2. Sustainable cities

As a high share of CO2 emissions occur in cities, the resource-
efficiency of cities should be further enhanced. It is there-

Cities are at the forefront of the fight against climate change, 

fore essential to make cities an integral part of the solution 

not only because they host a high share of the population 

in the fight against climate change. Policies should aim to 

and  an  even  higher  share  of  economic  activities,  but 

because working and living in cities is more resource effi-

reduce congestion, promote non-motorized transport and 
improve the energy performance of buildings (21). This would 

cient. People living in cities take shorter trips to get to work 

also improve air quality, which is lower in cities, and increase 

and are more likely to walk, cycle or take public transport. 

the health of city dwellers. However, care should be taken 

In the EU, for example, households living in urban areas are 

that these measures do not lead to urban sprawl by shifting 

three times more likely to use only public transport, walking 

jobs and residents to the outskirts of the city. 

or cycling for their transport needs (see Figure 2). They tend 

to live in flats or townhouses which require less energy to 

The  Covenant  of  Mayors  commits  cities  to  reduce  their 

heat and cool. In addition, district heating systems are more 

greenhouse gas emissions by more than 20 % by 2020 and 

efficient in dense urban neighbourhoods. 

has been signed by more than 2500 mayors in Europe rep-

In the EU, final energy demand per capita was 40 % higher 
in rural areas than in urban areas (19). A large share of that 
difference is due to the higher efficiency of cities (20). From 

an energy efficiency point of view, policies that enhance the 

appeal of urban living and working should be promoted.

resenting over 125 million inhabitants. The Smart Cities and 

Communities Initiative, which builds among others on this 

covenant, will develop a more comprehensive approach to 

urban challenges around energy, transport and ICT.

19.  World Energy Outlook 2008, IEA, Paris, 2008.
20.  The remaining difference may be due to a higher share of energy-intensive manufacturing located in rural areas.
21.  The green metropolis, D. Owen. Riverhead, 2009. and Triumph of the City, E. Glaeser. The Penguin Press, 2011.

Report from the Commission to the European Parliament and the Council
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Figure 1: Higher education by type of area, 2009

High education attainment rate 25-64 by type of area, 2009 

50 

45 

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Source: Eurostat LFS, MS ranked by share in large urban areas.  
Areas defined by degree of urbanisation: Large urban areas = densely populated, towns and suburbs = intermediate, rural areas = thinly populated. 

Figure 2: Access to a car by type of area, 2009

People who do not have a car, 2010 

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Source: Eurostat SILC, MS ranked by share in large urban areas.  
Areas defined by degree of urbanisation: Large urban areas = densely populated, towns and suburbs = intermediate, rural areas = thinly populated. 

12 Report from the Commission to the European Parliament and the Council

Seventh progress report on economic, social and territorial cohesion

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Inclusive growth

4

The Europe 2020 strategy has a strong focus on employ-

to  make  significant  progress  but  the  contribution  from 

ment creation, skills and labour market reform and explicitly 

countries and regions already close to or above 75 % will 

targets reducing poverty and exclusion. It aims to increase 

also be needed.

employment  rates  and  the  quality  of  jobs,  especially  for 

women, young people and older workers. It also wants to 

The recent crisis also led to rapid increases in unemploy-

better integrate migrants in the labour force. Furthermore, 

ment rates (see annex 8). In the three Baltic States and seven 

it will help people anticipate and manage change by invest-

Spanish regions unemployment rates increased by between 

ing in skills and training and modernising labour markets and 

10 and 18 pp. Unemployment increased least (1.8 pp) in the 

welfare systems.

4.1.  Employment

RCE regions. The convergence regions witnessed a more 

substantial increase (2.8 pp). The sharpest increase, however, 

occurred in the transition regions (6.4 pp). Despite the overall 

increases, unemployment decreased in 52 regions, mostly 

The Europe 2020 strategy aims to increase the employment 

in  Germany  but  also  in  some  regions  in  Poland,  France, 

rate to 75 % for the population aged 20-64 by 2020. Member 

Finland and Austria.

States have set national targets varying from 62.9 % in Malta 

to 80 % in Denmark and Sweden. 

4.2. Poverty and exclusion

Not all Regions are expected to reach the EU or national 

The  Europe  2020  strategy  aims  to  reduce  the  number  of 

employment  targets,  as  they  face  very  different  starting 

people at risk of poverty or exclusion by 20 million by 2020, 

positions. The employment rate in convergence regions in 

corresponding to a reduction from 23 % of the EU popula-

2010 was only 63 % after a decline due to the economic crisis. 

tion to 19 %. The share of population at risk of poverty or 

Only two convergence regions have reached the EU target 

exclusion is over 50 % in three Bulgarian regions and is 49 % 

of 75 % in 2010. If the goal was to reach the 2020 target in all 
convergence regions, 11 million people (22) would have to 

find a job. The transition regions also have a low employ-

in  Sicily  (see  annex  9).  The  lowest  rates  can  be  found  in 

Åland, Trento, Navarra and Praha, where is it 10 % or lower. 

ment rate of 64 % and would need 3 million jobs to reach 

The  at-risk-of-poverty-or-exclusion  rate  is  composed  of 

the  EU  target  in  all  these  regions.  The  RCE  regions  have 

three indicators: (1) having an income below the national 

a considerably higher employment rate of 72 %, but because 

poverty income threshold after social transfers (2) severe 

60 % of the EU working age population lives in these regions, 

material deprivation and (3) living in household with a low 

they would still need 9.4 million jobs to reach this target 
in each of these regions (23). 

work intensity (see annex 9 for the full definition). The first 

indicator is a relative poverty indicator because it measures 

the  share  of  people  with  an  income  below  60 %  of  the 

Employment rates below 60 % can be found in regions in 

national median income. As a result, someone who is consid-

southern  Spain  and  southern  Italy  and  some  regions 

ered at risk of poverty in the UK would probably not be con-

in  Romania  and  Hungary  (see  annex  7).  Many  regions 

sidered poor in Bulgaria with the same income. The second 

in  Germany,  the  UK,  the  Netherlands,  Denmark,  Sweden 

indicator is an absolute measure of poverty as it measures 

and Austria have already reached 75 %. To ensure that the 

access to nine essential items in the same way in all Member 

EU  reaches  75 %  by  2020,  especially  those  countries  and 

States.  This  indicator  is  closely  correlated  to  the  level  of 

regions where employment rates are currently low will have 

development of a country. In 2009, it ranged from 32 % in 

22.    This shows the number of jobs required for all convergence regions to have an employment rate of 75 % or higher. The jobs required to reach 75 % in all 
EU regions is 23 million. The number required to reach this target at the EU level is lower (17.6 million), as regions with employment rates above 75 % can 
compensate for regions with lower rates.

23.  Estimates based on current number of jobs and the Eurostat regional population forecast.

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13

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Romania to 1 % in Luxembourg. The last indicator measures 

The  high  share  of  people  disconnected  from  the  labour 

exclusion from the labour market. This indicator is not corre-

market in areas with the highest physical concentration of 

lated with GDP per head or even employment rates. In 2009, 

it was highest in Ireland and the UK, while the lowest rates 

job opportunities (cities) was highlighted as an urban para-
dox by the two State of European Cities Reports (25).

were in Estonia and Cyprus.

The at-risk-of-poverty rate has a strong regional dimension 

Severe  material  deprivation  and  the  at–risk-of-poverty 
rate (26) (see Figure 4 and 5) tend to be higher in urban areas 

which cannot be explained by personal characteristics such 

in  many  of  the  more  developed  Member  States,  despite 

as education, employment status, household type and age. 

higher average incomes in such urban areas. In Belgium, 

Estimates of regional poverty based on these dimensions 

Austria and the UK, severe material deprivation is between 

considerably underestimate the regional variation of pov-

erty. In other words, the at-risk-of-poverty rate depends not 

three and five pp higher in urban areas than in the rest of 
the country. Research (27) has highlighted the presence of 

only on a person’s education or employment status, but also 

large (and growing) income disparities in cities.

on where they live (‘location effect’).

Living in an urban area in a less developed Member State, 

Unfortunately,  the  at-risk-of-poverty-or-exclusion  rate  is 

however, has more advantages than living in a rural area or 

not available at regional NUTS 2 or 1 level in several large 

small town. Urban areas in these Member States tend to 

Member States. As cohesion policy aims to make a substantial 

have higher employment rates and lower shares of jobless 

contribution to reducing poverty and exclusion, especially 

households, severe materially deprived and people at risk 

in the least developed regions, a regional benchmark will be 

of poverty. In addition, average incomes are much higher. 

critical to monitor and assess its impact. Estimates indicate 

For example in Latvia, Bulgaria, Poland and Romania aver-

that convergence and transition regions score significantly 

age  incomes  in  urban  areas  are  between  40 %  and  70 % 

worse than RCE regions on at risk of poverty and exclusion 

higher than in the rest of the country. This highlights the 

concentration of poverty in rural areas, often compounded 
by poor access to services (28).

and two of its three dimensions (see Table 1).

4.3.  Inclusive cities:  

the urban paradox

The urban dimension of inclusive growth is inversely related 

to the level of economic development: the more developed 

Member States tend to have less inclusive cities.

In  more  developed  Member  States,  urban  areas  are  fre-

quently confronted with substantially higher shares of people 

living in a jobless household (see Figure 3). Also unemploy-

ment rates are higher and employment rates are lower in 

urban areas in more developed Member States. In the UK, 

Portugal,  France,  Austria  and  Belgium,  urban  unemploy-
ment rates are between three and five pp higher (24).

24. 

 The Urban Audit shows that these higher unemployment rates are not evenly distributed over all cities, but affect some cities and some neighbourhoods 
much more than others.

25.  State of European Cities Report. Commission, 2007 and 2010. http://ec.europa.eu/regional_policy/activity/urban/audit/index_en.cfm 
26. 

 This is particularly striking as the at-risk-of-poverty rate does not take into account the higher cost of living in urban areas, so probably underestimates 
the at-risk-of-poverty rate in cities.

27.  For example see the ESPON FOCI study. http://www.espon.eu/main/Menu_Projects/Menu_AppliedResearch/foci.html
28.   See also Poverty and social exclusion in rural areas, European Commission, 2008. http://ec.europa.eu/social/BlobServlet?docId=2087&langId=en 

14 Report from the Commission to the European Parliament and the Council

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Figure 3: Low work intensity by type of area, 2009

20% 

18% 

16% 

14% 

12% 

10% 

8% 

6% 

4% 

2% 

0% 

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People living in a household with low work intensity, 2009 

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  Urban disadvantage                                  Urban advantage 

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Source: Eurostat SILC, MS ranked by difference between large urban areas and other areas.  
Areas defined by degree of urbanisation: Large urban areas = densely populated, towns and suburbs = intermediate, rural areas = thinly populated. 

Figure 4: Deprivation by type of area, 2009

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Areas defined by degree of urbanisation: Large urban areas = densely populated, towns and suburbs = intermediate, rural areas = thinly populated. 

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Report from the Commission to the European Parliament and the Council
Seventh progress report on economic, social and territorial cohesion

15

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 5: Poverty by type of area, 2009

People at risk of poverty, 2009 

Large urban areas 
Rural areas, towns and suburbs 

Urban disadvantage                             Urban advantage 

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Figure 6: At risk of poverty or exclusion by type of area, 2009

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16 Report from the Commission to the European Parliament and the Council

Seventh progress report on economic, social and territorial cohesion

KN3111359ENC_001.pdf   16

03/02/12   14:44

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Conclusion

5

This report has highlighted the regional and urban dimen-

When designing regional growth strategies, cities should 

sion of the Europe 2020 strategy. It shows that significant 

play an active role. Cities are uniquely placed to promote 

efforts and investments are needed in all Europe’s regions 

innovation by offering firms of all sizes the dynamic envi-

to  achieve  the  smart,  sustainable  and  inclusive  growth 

ronments they need to succeed. They are at the forefront in 

objectives.  It  argues  that  those  needs  differ  between 

the fight against climate change, creating new models of 

regions and between cities and that policies should take 

urban development with even higher resource efficiency. 

these needs into account.

Last but not least, cities have a disproportionate share of 

social problems and poverty. As the Europe 2020 targets 

Given cohesion policy’s key role in Europe 2020, particular 

aims  to  increase  employment  and  reduce  poverty  and 

attention  needs  to  be  paid  to  the  convergence  regions, 

exclusion,  cities  need  to  address  urban  deprivation  and 

but improvements are also necessary in the transition and 

the disconnection from the labour market, especially in the 

RCE regions. 

EU-15.

The convergence regions score poorly on the smart growth 

This report provides an important input as strategies for the 

front with low levels of R&D, low shares of higher educated 

future 2014-2020 cohesion policy programmes are being 

and low productivity. Many also display low levels of employ-

prepared. In essence, it sets out the baseline situation to be 

ment and high unemployment levels. The risk of poverty 

addressed in relation to the EU2020 targets and the distance 

and exclusion is also higher in the convergence regions. 

to the national targets. Future cohesion policy programme 

must articulate how they will contribute to this catching up 

Although transition regions and RCE regions score better on 

process  in  concrete  terms.  How  will  the  investment  pro-

these issues, they also need to improve their performance 

grammes  contribute  to  change  in  these  indicators?  Are 

to  reach  the  Europe  2020  targets.  The  crisis  has  reduced 

there intermediate steps or indicators which can capture 

employment in RCE regions and revealed a lack of competi-

positive progress? Cohesion policy programmes provide an 

tiveness in some of them. Unemployment has risen in more 

opportunity  to  design  strategies  in  an  integrated  way  – 

than 100 RCE regions and 36 have an unemployment rate 

focused on the specific needs of each territory – and reflect-

above the EU average.

ing the trade-offs and synergies between different types of 

investments. 

The challenge of sustainable growth is present in all regions. 

The energy efficiency of existing and new buildings has to 

increase  everywhere.  Increasing  renewable  energy  will 

require more investment in efficient locations and in the 

network connecting supply with demand. 

KN3111359ENC_001.pdf   17

03/02/12   14:44

Report from the Commission to the European Parliament and the Council
Seventh progress report on economic, social and territorial cohesion

17

1.  Population aged 30-34 with 

tertiary education, 2007-2010

This table shows the ten regions with the highest share  
of population aged 30-34 with tertiary education 
– Average 2007-2010

MS

ES

UK

DK

BE

BE

FR

SE

NL

UK

ES

Region

tertiary education %

País Vasco

Inner London

Hovedstaden

Prov. Brabant Wallon

Prov. Vlaams-Brabant

Île de France

Stockholm

Utrecht

North Eastern Scotland

Comunidad de Madrid

60

59

56

56

55

52

51

51

51

49

This table shows the ten regions that are most distant 
from their national 2020 tertiary education target in 
percentage points

MS

PT

SK

SK

CZ

PL

DE

PT

FR

DE

PL

Region

distance to national 
target, in pp

Região Autónoma dos Açores

Západné Slovensko

Východné Slovensko

Severozápad

Kujawsko-Pomorskie

Lüneburg

Alentejo

Corse

Sachsen-Anhalt

Opolskie

-29

-26

-25

-24

-24

-23

-23

-23

-23

-23

This  indicator  shows  the  proportion  of  population  aged 

30-34 with tertiary education to the total population 30-34 

of the same age group.

Why does this matter?

Educational attainment of the population is one of the most 

important factors of economic growth. People with tertiary 

education are more likely to get a job, have a higher income 

and have higher life expectancy. Increasing employment 

rate of tertiary educated people is also likely to have posi-

tive effects on productivity. Most of the increase in the share 

of  the  tertiary-educated  working-age  population  comes 

from those under 35. Therefore, the Europe 2020 strategy 

has set the target for the share of population aged 30-34 with 

tertiary education at 40 %. The EU share in 2010 was 34 %. 

The national 2020 targets range between 60 % (Ireland) and 

26 % (Italy).

How do the EU regions score?

As well as in the case of other educational attainment indi-

cators,  the  share  of  tertiary  educated  aged  30-34  varies 

widely  in  Europe.  Considering  the  average  levels  for  the 

years 2007-2010, one region in five has reached the EU 2020 

target. The top ten regions have shares significantly above 

the EU 2020 targets and are mostly capital regions or adjoin 

capital regions. The bottom ten are located in the Czech 

Republic, Romania, Portugal and Italy (see map 1.1). Other 

regions lagging behind the European target are located in 

Greece, Bulgaria, Hungary, Slovakia and Germany. 

The distance to the national target is particularly significant 

for  Açores  and  for  some  regions  located  in  Slovakia,  the 

Czech Republic, Poland and Germany. Overall, only 25 regions 

across Europe have reached the national target in the 2007-

2010 average, mainly in capital regions, in northern Spain and 

in south Finland and Sweden (see map 1.2). 

18 Report from the Commission to the European Parliament and the Council

Seventh progress report on economic, social and territorial cohesion

KN3111359ENC_001.pdf   18

03/02/12   14:44

Annexes

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KN3111359ENC_001.pdf   19

03/02/12   14:44

Report from the Commission to the European Parliament and the Council
Seventh progress report on economic, social and territorial cohesion

1919

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2.  Early leavers from education 

and training, 2008-2010

This table shows the ten regions with the lowest share 
of early leavers from education and training aged 18-24 
– Average 2008-2010

Region

 % of early school 
leavers

MS

SK

CZ

CZ

SK

Bratislavský kraj

Jihovýchod

Praha

Západné Slovensko

PL Małopolskie

PL

CZ

PL

PL

Podkarpackie

Střední Morava

Świętokrzyskie

Podlaskie

PL Wielkopolskie

2

3

3

3

3

4

4

4

4

4

This table shows the ten regions that are most distant 
from their national 2020 early school leavers target in 
percentage points

MS

PT

PT

ES

PT

ES

PT

ES

ES

ES

ES

Region

distance to national 
target, in pp

Região Autónoma dos Açores

Região Autónoma da Madeira

Ciudad Autónoma de Ceuta

Norte

Illes Balears

Algarve

Región de Murcia

Ciudad Autónoma de Melilla

Andalucía

Castilla-La Mancha

39

31

26

25

25

23

23

23

22

20

The share of early leavers from education and training meas-

ures the number of people aged 18-24 with at most lower 

secondary education and not attending any further education 

or training, divided by the total population aged 18-24.

Why does this matter?

The reduction of early school leavers and the increase of 

educational attainment of the population are key targets of 

Europe 2020. These two strategies can provide vital support 

to Europe’s employment and growth objectives. Education 

contributes to productivity of an individual and can lead 

to  increases  in  employment,  personal  income  and  ones’ 

overall life satisfaction. People without a complete second-

ary  education  are  much  more  likely  to  be  unemployed. 

The Europe 2020 target is to reduce the early leaving from 

education and training below 10 % by 2020, while the 2008-

2010  average  is  14.5 %.  National  targets  for  this  strategy 

range between 4.5 % (Poland) and 29 % (Malta).

How do the EU regions score?

Regional  differences  in  early  school  leaving  are  high. 

Considering a three year average (2008-2010), the Europe 

2020 target has been reached in 74 NUTS 2 regions, around 

one  in  four,  requiring  then  a  substantial  effort  in  many 

regions to be achieved. Overall, the regions with the high-

est shares of early school leavers (above 30 %) are located in 

Spain and Portugal. Also Malta is in the top ten regions in 

this indicator. Regions with high shares (between 20 % and 

30 %) are also located in Greece, Italy, Bulgaria, Romania and 

United Kingdom (see map 2.1). In contrast, the lowest rates 

of early leavers from education and train ing are registered 

in particular in Slovakia, the Czech Republic and Poland. 

The distance to the national target is significant in regions 

of Spain and Portugal, as well as in Greece, Bulgaria and 

Southern Italy. Instead, several regions of Austria, Germany, 

Italy, the Czech Republic and Slovakia have already reached 

the national target (see map 2.2). 

20 Report from the Commission to the European Parliament and the Council

Seventh progress report on economic, social and territorial cohesion

KN3111359ENC_001.pdf   20

03/02/12   14:44

 
Annexes

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KN3111359ENC_001.pdf   21

03/02/12   14:44

Report from the Commission to the European Parliament and the Council
Seventh progress report on economic, social and territorial cohesion

2121

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3.  General expenditure on R&D (GERD), 2008

This indicator measures the share of regional GDP invested 

in expenditure on research and development by both the 

This table shows the ten regions with the highest R&D  
as a % of GDP in 2008

Region

GERD as % of GDP

private and the public sector.

Why does this matter? 

GERD indicates the resources devoted by a region for the 

development of innovations and the transformation of new 

ideas into market opportunities through R&D. In general, 

the majority of activities related to R&D take place within 

the private sector but the public sector also plays a crucial 

MS

DE

UK

FI

DE

UK

DK

SE

DE

Braunschweig

East Anglia

Pohjois-Suomi

Stuttgart

Cheshire

Hovedstaden

Sydsverige

Oberbayern

role  notably  by  supporting  fundamental  research.  The 

FR Midi-Pyrénées

Europe 2020 strategy includes the headline target of bring-

DE

Dresden

6.7

5.9

5.9

5.8

5.7

5.1

4.8

4.3

4.2

4.1

ing GERD to 3 % of GDP for the EU-27 by 2020. In 2008, the 

Note: AT, BE, DE, DK, IE, IT, NL, SE: 2007, EL 2005 and FR 2004.

share  was  1.9 %.  Member  states,  through  their  National 

Reform Programmes, set their targets between 0.5 % (Cyprus) 

and 4 % (Sweden) of their national GDP.

This table shows the ten regions that are the most distant 
from their national 2020 R&D target in percentage points

MS

Region

FI

Åland

SE Mellersta Norrland

AT

SE

ES

FR

ES

SE

AT

DE

Burgenland (A)

Småland med öarna

Ciudad Autónoma de Ceuta

Corse

Ciudad Autónoma de Melilla

Norra Mellansverige

Salzburg

Brandenburg – Nordost

distant to national 
target, in pp

-3.8

-3.2

-3.1

-2.9

-2.9

-2.8

-2.7

-2.7

-2.7

-2.7

Note: AT, BE, DE, DK, IE, IT, NL, SE: 2007, EL 2005 and FR 2004.

How do the EU regions score? 

The  performance  on  this  dimension  varies  widely  across 

European regions. A characteristic of GERD in developed 

countries is the geographical concentration in core areas, 

typically metropolitan and capital regions. In Europe, the 

regions  with  the  highest  GERD  to  GDP  ratio  are  located 

in northern countries (Germany, UK, Sweden and Finland). 

The  performance  is  also  high  in  Austria  and  in  capital 

regions such as Hovedstaden (Copenhagen), Madrid, Lisbon 

and Prague. At the other end of the spectrum, a series of 

regions  mainly  in  Romania,  Bulgaria,  Greece  and  Poland 

have an expenditure on R&D below 0.5 % of their GDP (see 

map 3.1).

Only 16 regions across Europe have reached the national 

targets  set  by  2020,  including  some  capital  regions  like 

Île  de  France,  Berlin,  Stockholm  and  Lazio  (see  map  3.2). 

The distance to the EU 2020 national targets is significant 

in a number of regions located in Spain and Portugal but 

also in countries performing well in this indicator (Germany, 

France,  Austria  and  Sweden),  showing  that  a  significant 

effort is required also in the most developed areas of Europe 

in order to reach the national targets. 

22 Report from the Commission to the European Parliament and the Council

Seventh progress report on economic, social and territorial cohesion

KN3111359ENC_001.pdf   22

03/02/12   14:44

Annexes

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KN3111359ENC_001.pdf   23

03/02/12   14:44

Report from the Commission to the European Parliament and the Council
Seventh progress report on economic, social and territorial cohesion

2323

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4.  Patent applications per 10 million 

inhabitants, 2006-2007

Patent applications per 10 million inhabitants is calculated 

The ten metro regions with the lowest patent application 

by dividing the total number of patent applications to the 

per 10 million inhabitants are second tier and smaller metro 

EPO in a metro region by the total population of the metro 
region multiplied by 10 million. A metro region (1) represents 

an urban agglomeration of at least 250 000 inhabitants and 

consists of one or more NUTS 3 regions. 

regions located in Poland, Romania and Bulgaria.

This table shows the ten metro regions with the highest 
patent applications per 10 million inhabitants

Metro region

Patent applications per 10 million 
inhabitants, 2006-2007

Why does this matter?

Patents, by protecting new inventions, ensure that inven-

tors can get a return on their investment someone wants to 

use their invention. Patents can promote more innovation, 

competitiveness and economic growth. Patent applications 

per inhabitant give an indication of which metro regions 

operate close to the knowledge frontier. 

How do the EU metro regions score?

MS

NL

FI

DE

Eindhoven

Tampere

Stuttgart

DE München

DE Mannheim

DE

DE

DE

DE

DE

Regensburg

Heidelberg

Nürnberg

Reutlingen

Ulm

18 003

11 632

7 405

7 180

6 502

6 486

6 063

5 972

5 777

5 394

Patent applications are the most concentrated issue discussed 

Note: Cambridge is not a metro region but scores 5 627.

in this report. Patent application rates differ between the 

metro regions by a factor of more then 1 000 (hence the log-

arithmic axis in the graph). Even application rates between 

the country with highest rate (Sweden with 2 889) and with 

the lowest rate (Romania with 12) differ by a factor of 240. 

In all Member States, the average metro region outperforms 

the average non-metro regions, with the exception of the 
UK (2).

The top ten metro regions are not capital regions. They tend 

to be second tier and smaller metro regions with a highly 

specialised industry or cluster and/or university. The differ-

ences  between  metro  regions  within  a  country  are  also 

large, with a few scoring far  above the national rate and 

many scoring below the national and even non-metro rate. 

In several MS, a second tier or smaller metro region outper-

forms the capital metro region (see graph 4.1). 

This table shows the ten metro regions with the lowest 
patent applications per 10 million inhabitants

MS

Metro region

Patent applications per 10 million 
inhabitants, 2006-2007

PL

Kalisz

PL Wloclawek

RO

BG

PL

RO

PL

RO

RO

RO

Galaţi

Plovdiv

Opole

Brasov

Olsztyn

Craiova

Cluj-Napoca

Constanţa

18

18

16

14

12

12

9

7

5

0

1. 

2. 

 The capital metro region contains the national capital. The second tier consists of the bigger metro regions just below the capital in the national urban 
hierarchy. Remaining metro regions are ‘smaller’. For more information on metro regions see Regional Focus 01/2011 by Dijkstra L. and Poelman H.
 In the UK, Cambridge and Oxford, both too small to be considered as a metro region, have such a high number of patent applications per inhabitants 
(5 627 and 3 369 resp.) that they raise the average performance of UK non-metro regions above that of the UK metro regions.

24 Report from the Commission to the European Parliament and the Council

Seventh progress report on economic, social and territorial cohesion

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Annexes

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Report from the Commission to the European Parliament and the Council
Seventh progress report on economic, social and territorial cohesion

2525

KN3111359ENC_001.pdf   25

03/02/12   14:44

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5. Green House Gas emissions 2005-2009

Change  in  GHG  emissions  outside  the  Emissions  Trading 

The distance to the target to which Member States have com-

Scheme and distance to national 2020 targets (national).

mitted also strongly varies from one country to the other. 

Why does this matter? 

A number of countries are way ahead of their target, like for 

instance Hungary and Slovakia which commit to limit their 

emissions to no more than 10 % and 13 % respectively and 

This indicator shows trends in total man-made emissions of 

where emissions actually decreased significantly. 

greenhouse gases by sectors included in the so-called ‘Effort 

Sharing Decision’. The EU as a whole is committed to achiev-

ing at least a 20 % reduction of its greenhouse gas emissions 

by 2020 compared to 1990. This objective implies a 21 % 

reduction in emissions from sectors covered by the EU emis-

sion trading scheme (ETS) compared to 2005 by 2020; and 

a  reduction  of  10 %  in  emissions  for  sectors  outside  the 

EU ETS. To achieve this 10 % overall target each Member 

State has agreed country-specific greenhouse gas emission 

reduction or limits for 2020 compared to 2005 from sectors 

This table shows the five countries that are most distant 
to their national target in 2009

MS

IE

DK

LU

DE

FR

Distance to target, percentage point

16.6

15.6

10.1

7.7

6.8

included in the ‘Effort Sharing Decision’: transport, buildings, 

In other countries, the target for emission reduction is not 

yet reached but the emissions have started to reduce, like 

for instance in Sweden where the target was set to a reduc-

tion of 17 % and emissions decreased by 11.8 % compared 

to levels of 2005. Among the Member States which have not 

reached their target, the distance to target is the highest in 

Ireland, Denmark and Luxemburg. It is the lowest in Italy, 

Spain  and  Belgium  where  additional  reduction  of  0.7 %, 

2.2 %  and  4.5 %  are  required  to  meet  the  objectives. 

The share of GHG emissions outside ETS was based on data 

on the total emissions and emissions within ETS from the 

European Environmental Agency. 

agriculture and waste.

This table shows the five countries with the highest 
GHG emissions reduction outside ETS in 2009

MS

UK

HU

SK

IT

SE

Change in GHG emissions, 2005-2009 (%)

-18.2

-16.9

-12.3

-12.2

-11.8

How do the EU Member States score? 

The reduction of GHG emissions in sectors included in the 

Effort  Sharing  Mechanism  has  been  very  high  is  some 

Member  States.  In  the  United-Kingdom  emissions  were 

reduced  by  18.2 %  while  in  Hungary,  they  fell  by  almost 

17 %. For most new Member States, the decrease is more 

modest  which  reflects  the  very  high  level  of  economic 

growth these countries have experienced. Emissions even 

increased in some countries, like for instance in Malta (+1.4 %) 

or Poland (+0.3 %). 

26 Report from the Commission to the European Parliament and the Council

Seventh progress report on economic, social and territorial cohesion

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03/02/12   14:44

 
Annexes

European Union 

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Bulgaria 

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Hungary 

Czech Republic 

Malta 

Slovenia 

Portugal 

Greece 

Cyprus 

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Report from the Commission to the European Parliament and the Council
Seventh progress report on economic, social and territorial cohesion

2727

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6. Renewable energy 2008

Consumption of renewable energy and distance to national 

2020 targets (national).

Why does this matter?

This  indicator  shows  the  share  of  renewable  energy  in 

gross final energy consumption of Member States. Sources 

of renewable energy are wind power, solar power (thermal, 

photovoltaic and concentrated), hydro-electric power, tidal 

power, geothermal energy and biomass. They constitute 

alternatives to fossil fuels and hence contribute to reducing 

This table shows the five countries with the highest  
share of renewable energy in gross final energy 
consumption in 2008

MS

SE

FI

LV

AT

PT

Share of renewable energy in gross final energy 
consumption, 2008 (%)

44.4

30.5

29.9

28.5

23.2

greenhouse  gas  emissions  as  well  as  diversifying  the  EU 

However, it is generally in the Member States where the use 

energy supply. 

of renewables is particularly low that it is also growing the 

fastest. For instance, between 2006 and 2008, the share of 

Renewable energy is also a sector which offers interesting 

renewable energy in gross final energy consumption has 

perspective for the development of new technologies and 

grown by 133 % in Luxemburg, by 100 % in Malta and 64 % 

of  new  employment  opportunities.  The  EU  Directive  on 

in Cyprus. The growth in the share of renewables in consump-

renewable  energy  has  set  targets  for  all  Member  States, 

tion is above 20 % in all Member States where it is currently 

such that the EU should reach a 20 % share of energy from 

lower than 5 %.

renewable sources by 2020 and a 10 % share of renewable 

energy  specifically  in  the  transport  sector.  The  share  of 

renewable energy consumption in the EU in 2008 was 10 %. 

How do the EU Member States score? 

The share of renewable energy in gross final energy con-

sumption is already high in some Member States. It accounts 

for more than 44 % of energy consumption in Sweden and 

more than 30 % in Finland. On the contrary, it is extremely 

This table shows the five countries that are most distant 
to their national target in 2008

MS

UK

IE

LV

FR

DK

Distance to target, percentage point

12.8

12.2

12.1

12.0

11.2

low in other countries like for instance Malta, Luxemburg or 

The situation of Member States also widely varies regarding 

the United Kingdom where renewable energy represents 

the distance to the target they have committed. Some coun-

respectively  0.2 %,  2.1 %  and  2.2 %  of  gross  final  energy 

tries like the United Kingdom, Ireland, Latvia or France must 

consumption.

increase the use of renewables by more than 12 percentage 

points to reach their targets. Other countries are already 

close  to  their  2020  objective,  like  for  instance  Romania, 

Sweden or Austria which must respectively add another 3.6, 

4.6 and 5.5 percentage points of renewables into final energy 

consumption for reaching their targets. 

28 Report from the Commission to the European Parliament and the Council

Seventh progress report on economic, social and territorial cohesion

KN3111359ENC_001.pdf   28

03/02/12   14:44

 
Annexes

European Union

Malta

Luxembourg

Hungary

Czech Republic

Cyprus

Belgium

Slovakia

Netherlands

United Kingdom

Poland

Ireland

Bulgaria

Italy

Greece

Germany

Spain

Lithuania

France

Romania

Slovenia

Estonia

Denmark

Portugal

Austria

Finland

Latvia

Sweden

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Report from the Commission to the European Parliament and the Council
Seventh progress report on economic, social and territorial cohesion

2929

KN3111359ENC_001.pdf   29

03/02/12   14:44

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7.  Employment rate age group 20-64, 2010

The employment rate divides the number of persons aged 

The  ten  regions  most  distant  to  their  national  target  are 

20 to 64 in employment by the total population of the same 

three of the four French outermost regions, three southern 

age group. The indicator is based on the EU Labour Force 

Italian  regions,  two  Hungarian  regions  and  the  Spanish 

Survey. 

Why does this matter?

The Europe 2020 strategy aims to increase the employment 

rate of people aged 20 to 64 to 75 % by 2020. In the EU, the 

rate was 69 % in 2010. Increasing the employment rate will 

help to reduce poverty and exclusion. It will also help to 

address the cost of ageing, in particular in countries with 

a pay-as-you-go pension system. To sustainably increase the 

employment rate, the EU will have to become more globally 

competitive. Investments in human capital and innovation 

in the broad sense, connections and the business environ-

ment can all contribute to this goal. National 2020 targets 

stated in the national reform programmes vary from 62.9 % 

in Malta to 80 % in Sweden and Denmark.

How do the EU regions score?

The convergence regions have the lowest employment rate 

at 63 %, the transition regions score slightly better at 64 %. 

The  competitiveness  regions  have  higher  rate  of  72 %. 

To reach the target of 75 % in 2020, the convergence regions 

need more than 5 million jobs, transition regions need 2.5 mil-

lion and competitiveness regions need 12 million jobs. 

The ten regions with the highest employment rate are all 

from  the  Northwest  of  the  EU.  Their  employment  rates 

are  unlikely  to  increase  much  more.  In  particular,  the 

Netherlands, Sweden, Denmark, Germany and the UK have 

reached high levels of employment. 

Most countries show stark regional differences, underlining 

the regional nature of labour markets and the relatively low 

labour mobility within the EU. 

The regions with employment rates below 60 % are almost 

all southern, eastern or outermost regions (see map 7.1). But 

some regions in the North-West score low too, for example 

West Wales and the Valleys in the UK, Border, Midland and 

Western in Ireland or Hainaut and Brussels in Belgium. 

enclaves Melilla and Ceuta. The UK has opted not to select 

a national employment target for 2020.

This table shows the ten regions with the highest 
employment rate in 2010

MS

FI

SE

DE

UK

NL

DE

SE

UK

SE

DE

Region

Employment rate age 
group 20-64 in %, 2010

Åland

Stockholm

Freiburg

North Eastern Scotland

Utrecht

Schwaben

Småland med öarna

Berkshire, 
Buckinghamshire 
and Oxfordshire

Västsverige

Oberbayern

83.6

81.7

80.2

80.1

79.7

79.5

79.5

79.4

79.1

79.0

This table shows the ten regions which are the most 
distant to their national 2020 employment rate target 
in 2010 in percentage points

MS

FR

IT

ES

ES

FR

IT

IT

HU

HU

FR

Region

Distance to national 2020 
employment target in pp

Réunion

Campania

Ciudad Autónoma 
de Ceuta

Ciudad Autónoma 
de Melilla

Guyane

Calabria

Sicilia

Észak-Magyarország

Észak-Alföld

Guadeloupe

-25

-24

-23

-23

-22

-22

-21

-21

-21

-20

30 Report from the Commission to the European Parliament and the Council

Seventh progress report on economic, social and territorial cohesion

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Annexes

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KN3111359ENC_001.pdf   31

03/02/12   14:44

Report from the Commission to the European Parliament and the Council
Seventh progress report on economic, social and territorial cohesion

3131

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8. Unemployment rate, 2010

This indicator measures the number of people aged 15-74 

The ten top movers between 2007 and 2010 are, with the 

who are without work but looking for work and available 

exception of Corse, German Landers, where labour mobility 

for  work,  divided  by  the  number  of  people  aged  15-74 

(from East to West Germany) can explain part of this per-

and active in the labour market, i.e. those employed and 

formance.  Unemployment  rates  dropped  also  in  some 

unemployed. 

Why does this matter?

regions of France, Poland, Austria and the UK. On the other 

side,  several  regions  in  Spain,  Ireland,  Baltic  States  and 

Greece witnessed a substantial increase in the unemploy-

ment rates. 

High unemployment is a threat to social cohesion leading 

to poverty and social exclusion and it is one of the most 

In most cases, reductions in unemployment rates are corre-

important incentives for people to leave their regions. 

lated with increased levels of GDP per capita and lower levels 

Unemployment 
rate, 2010

Change in 
unemployment 
rate, 2007-2010 
in pp

Convergence

Transition

RCE

11.9

14.8

7.9

EU

9.7

of poverty. Conversely, regions growing unemployment tend 

to have lower levels of economic growth and higher levels 

of poverty.

2.8

6.4

1.8

2.5

This table shows the ten regions with the highest rate 
of unemployment in 2010

Region

Unemployment 
rate, %

Convergence regions are faced with high unemployment 

rates due to low levels of economic activity and skills mis-

match due to restructuring and the reduction of employ-

ment in agriculture. The Transition regions have an even 

higher unemployment rate. They were hit particularly hard 

by the crisis with an increase in unemployment of 6 per-

centage points between 2007 and 2010. Competitiveness 

regions have a slightly lower unemployment rate, but they 

were still confronted with an increase of almost 2 percent-

MS

FR

ES

ES

ES

FR

ES

ES

ES

ES

Réunion 

Canarias 

Andalucía

Ciudad Autónoma de Ceuta 

Guadeloupe 

Ciudad Autónoma de Melilla 

Región de Murcia

Comunidad Valenciana

Extremadura

age points between 2007 and 2010. 

FR Martinique 

29

29

28

24

24

24

23

23

23

21

How do the EU regions score?

Regional disparities among the EU-27 regions remain high. 

One region in three has an unemployment rate above 10 %. 

The  highest  rates  are  registered  in  the  French  overseas 

departments,  which  face  specific  challenges,  and  many 

Spanish  regions.  Most  of  the  26  regions  with  unemploy-

ment rates over 15 % can be found in these two, as well as in 

Slovakia  and  in  the  Baltic  States.  In  contrast,  34  regions 

mainly located in Austria, Germany, northern Italy and the 

Netherlands have rates below 5 %. 

This table shows the regions in which unemployment 
rate decreased the fastest between 2007 and 2010 in 
percentage points

Region

MS

DE

FR

Thüringen

Corse

DE Mecklenburg-Vorpommern

DE

DE

DE

DE

DE

DE

DE

Leipzig

Sachsen-Anhalt

Brandenburg – Nordost

Brandenburg – Südwest

Bremen

Berlin

Dresden

Change in 
unemployment 
rate, in pp

-5.1

-5.0

-5.0

-4.8

-4.3

-3.9

-3.9

-3.8

-3.1

-2.9

32 Report from the Commission to the European Parliament and the Council

Seventh progress report on economic, social and territorial cohesion

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KN3111359ENC_001.pdf   33

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Report from the Commission to the European Parliament and the Council
Seventh progress report on economic, social and territorial cohesion

3333

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9. At risk of poverty or exclusion rate, 2009

This indicator is the share of people who are (1) at-risk-of-

atrisk-of-poverty-or-exclusion rate in Brussels highlights the 

poverty  and/or  (2)  severely  materially  deprived  and/or 

juxtaposition of high income and high poverty. The southern 

(3) living in households with very low work intensity.

Italian  regions  show  that  low  employment  rates  and  low 

(1)    At risk-of-poverty means having an income below 60 % 

growth rates tend to exacerbate poverty and exclusion. 

of the national median equivalised disposable income 

after social transfers. 

Germany,  France,  the  Netherlands,  the  UK  and  Portugal 

(2)    Severe material deprivation means experiencing at least 

could  not  provide  regional  figures,  which  may  influence 

4 out of 9 situations of financial strain or enforced lack 

the regions in the two tables. 

of durables. 

(3)   People living in households with very low work intensity 

are people aged 0-59 living in households where the 

adults work less than 20 % of their total work potential 

during the past year. 

The national targets based on national reform programmes 

and Commission calculations. They vary from a reduction by 

0.3 pp in the Czech Republic to 6.6 pp in Bulgaria. 

Why does this matter? 

This table shows the ten regions that are the most distant 
to their national 2020 at-risk-of-poverty-or-exclusion 
target in 2009 in percentage points

MS

Region

Distance to national 
2020 at-risk-of-
poverty-or-exclusion 
target in pp

IT

IT

IT

IT

Sicilia

Campania

Calabria

Basilicata

ES Melilla

The  Europe  2020  strategy  aims  to  reduce  the  number  of 

people at risk of poverty or exclusion in the EU with 20 mil-

lion by 2020. Reaching this target may require depending 

on the country income and employment growth, adjusting 

the welfare and/or tax system.

BE

ES

ES

BG

ES

Région de Bruxelles-Capitale/
Brussels Hoofdstedelijk Gewest *

Extremadura

Ceuta

Severen tsentralen

Canarias

28

22

21

21

20

19

18

18

17

15

How do the EU regions score?

The ten regions with the lowest at-riskof-poverty-or-exclusion 

rate are surprisingly diverse. They contain regions from the 

North and the South, from the East and the West, capitals 

and more rural regions.

The regional breakdowns often reveal substantial internal 

variation. For example, Spain, Italy and Belgium all three 

have  a  strong  North-South  divide.  In  Bulgaria,  Hungary, 

Poland, Slovakia and the Czech Republic the capital region 

has the lowest rate, while in Austria, Belgium the opposite is 

true. Overall there is a link to GDP per head, with the highest 

rates in Bulgaria, Romania. This is particularly due to their 

high rates of severe material deprivation.

The ten regions which are most distant to their national 2020 

target are located in southern Italy (four regions), Spain (four 

regions) and one region in Bulgaria and one in Belgium. The 

combination  of  a  high  GDP  per  head  and  relatively  high 

* Average 2007-2009
Note: For DE, FR, NL, PT and UK only national level data was available. 
For BE, EL and HU only NUTS1. AT and BE is average 2007-2009.

This table shows the ten regions with the lowest
at-risk-of-poverty-or-exclusion rate in 2009

MS

FI

IT

ES

CZ

CZ

CZ

IT

CZ

ES

CZ

Region

At-risk-of-poverty-or-
exclusion rate 2009, in %

Åland

Provincia Autonoma Trento

Comunidad Foral de 
Navarra

Praha

Střední Čechy

Severovýchod

Provincia Autonoma  
Bolzano/Bozen

Jihozápad

País Vasco

Jihovýchod

5

9

10

10

11

12

13

13

13

13

Note: For DE, FR, NL, PT and UK only national level data was available. 
For BE, EL and HU only NUTS1. AT and BE is average 2007-2009.

34 Report from the Commission to the European Parliament and the Council

Seventh progress report on economic, social and territorial cohesion

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Annexes

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03/02/12   14:44

Report from the Commission to the European Parliament and the Council
Seventh progress report on economic, social and territorial cohesion

3535

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
10. GDP/head 2008 

Gross  Domestic  Product  per  head  in  Purchasing  Power 

This shows that poor regions are catching up with the rest 

Standards.

Why does this matter? 

of the EU and is consistent with the fact that convergence 

among  EU  regions  in  terms  of  GDP/head  has  increased. 

Between 2000 and 2008, the coefficient of variation, which is 

a statistical measure of regional disparities, indeed decreased 

Gross domestic product (GDP) is the total value of all goods 

by 10 %. 

and services produced within a region in a given period of 

time. GDP/head is the level of output per inhabitant which 

is  an  indication  of  the  average  level  of  economic  wealth 

generated  per  person.  In  order  to  compare  regions,  it  is 

computed in Purchasing Power Standards (PPS) which elimi-

nates differences in purchasing power due to different price 

levels between regions. 

In general, the level of GDP per head is closely related to glo-

bal economic performance, in particular to production, factor 

productivity and employment. Change in time is also used 

as an indicator of the pace of economic development. 

How do the EU regions score? 

The geographical distribution of GDP/head underlines large 

development  gaps  between  EU  regions  and  particularly 

between the Western and the Central and Eastern Member 

States. Eight of the top ten regions are located in the West. 

They are also often capital city regions. At the other end of 

the spectrum, several regions in Bulgaria and Romania have 

levels of GDP/head below 30 % of the EU-27 average. The 

lowest level is 27 % in Severozapaden, Bulgaria. 

Regions where GDP per head has increased often host the 

national capital or a large city. Strong growth is also fre-

quently observed in regions with a low level of GDP/head, 

like for instance Vest, Romania whose GDP/head is only 51 % 

of the EU average but whose index has grown by almost 

24 percentage points between 2000 and 2008. On the other 

hand, growth has often been modest in regions with high 

levels of GDP per head, particularly in Northern Italy or in 

some capital city regions like Wien or Région de Bruxelles-

Capitale. In the latter, GDP/head index decreased from 256 in 

2000 to 216 in 2008.

MS

UK

LU

BE

NL

DE

CZ

FR

SE

SK

MS

SK

RO

NL

CZ

BG

LU

UK

RO

EE

This table shows the ten regions with the highest  
GDP per head in PPS in 2008

Top Ten regions

GDP per head in PPS 
EU-27 = 100

Inner London *

Luxembourg (Grand-Duché) *

Région de Bruxelles-Capitale *

Groningen **

Hamburg 

Praha 

Île de France 

Stockholm

Bratislavský kraj

AT Wien 

* Overstated due to commuter flows.
** Overstated due to GVA from off-shore gas production.

This table shows the ten regions with the biggest 
increase in GDP per head in PPS between 2000 and 2008, 
in difference in index points

Top Ten Movers

Difference in EU-27 
GDP per head index 
points

Bratislavský kraj

Bucureşti – Ilfov

Groningen **

Praha

Yugozapaden

Luxembourg (Grand-Duché) *

Inner London *

Vest

Eesti

HU

Közép-Magyarország

* Overstated due to commuter flows.
** Overstated due to GVA from off-shore gas production.

343

280

216

198

188

172

168

167

167

163

58

57

48

36

35

35

31

24

23

22

36 Report from the Commission to the European Parliament and the Council

Seventh progress report on economic, social and territorial cohesion

KN3111359ENC_001.pdf   36

03/02/12   14:44

 
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3737

KN3111359ENC_001.pdf   37

03/02/12   14:44

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
KN3111359ENC_001.pdf   38

03/02/12   14:44

European Commission

The urban and regional dimension of Europe 2020
Seventh progress report on economic, social and territorial cohesion

2011 — 37 pp. — 21.0 × 29.7 cm

ISBN 978-92-79-21727-2
doi:10.2776/50938

HOW TO OBTAIN EU PUBLICATIONS

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details on the Internet (http://ec.europa.eu) or by sending a fax to +352 2929-42758.

Priced publications:
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KN3111359ENC_001.pdf   39

03/02/12   14:44

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