1. ISSN 1830-9674
Statistical books
Eurostat regional yearbook 2009

2. Statistical books
Eurostat regional yearbook 2009

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Luxembourg: Office for Official Publications of the European Communities, 2009
ISBN 978-92-79-11696-4
ISSN 1830-9674
doi: 10.2785/17776
Cat. No: KS-HA-09-001-EN-C
Theme: General and regional statistics
Collection: Statistical books
© European Communities, 2009
© Copyright for the following photos: cover: © Annette Feldmann; the chapters Introduction,
Population, Household accounts, Information society, Education and tourism: © Phovoir.com;
the chapter European cities: © Teodóra Brandmüller; the chapters Labour market, Gross domestic
product, Structural business statistics and Science, technology and innovation: © the Digital Photo
Library of the Directorate-General for Regional Policy of the European Commission;
the chapter Agriculture: © Jean-Jacques Patricola.
For reproduction or use of these photos, permission must be sought directly from the copyright
holder.

4. Preface
Dear Readers,
Five years ago, 2004, was a momentous year, with 10 new
Member States joining the European Union on 1 May. This
Eurostat regional yearbook 2009 is eloquent testimony to the
economic and social progress made by these regions since
then and highlights those areas where redoubled efforts will
be needed to reach our goal of greater cohesion.
The 11 chapters of this yearbook investigate interesting as­
pects of regional differences and similarities in the 27 Mem­
ber States and in the candidate and EFTA countries. The
aim is to encourage readers to track down the regional data
available on the Eurostat website and make their own ana­
lyses of economic and social developments.
In addition to the fascinating standard chapters on regional
population developments, the regional labour market, re­
gional GDP, etc., this year’s edition features a new contri­
bution on the regional development of information society
data. As in recent years, the description of regional devel­
opments is rounded off by a contribution on the latest findings of the Urban Audit, a data collection
containing a multitude of statistical data on European towns and cities.
We are constantly updating the range of regional indicators available and hope to include them as
topics in future editions, provided the availability and quality of these data are sufficient.
I wish you an enjoyable reading experience!
Walter Radermacher
Director­General, Eurostat
Eurostat regional yearbook 2009 3

5. Acknowledgements
The editors of the Eurostat regional yearbook 2009 would like to thank all those who were involved in
its preparation. We are especially grateful to the following chapter authors at Eurostat for making the
publication of this year’s edition possible.
• Population: Veronica Corsini, Monica Marcu and Rosemarie Olsson (Unit F.1: Population)
• European cities: Teodóra Brandmüller (Unit E.4: Regional statistics and geographical informa­
tion)
• Labour market: Pedro Ferreira (Unit E.4: Regional statistics and geographical information)
• Gross domestic product: Andreas Krüger (Unit C.2: National accounts — production)
• Household accounts: Andreas Krüger (Unit C.2: National accounts — production)
• Structural business statistics: Aleksandra Stawińska (Unit G.2: Structural business statistics)
• Information society: Albrecht Wirthmann (Unit F.6: Information society and tourism)
• Science, technology and innovation: Bernard Félix, Tomas Meri, Reni Petkova and Håkan Wilén
(Unit F.4: Education, science and culture)
• Education: Sylvain Jouhette, Lene Mejer and Paolo Turchetti (Unit F.4: Education, science and
culture)
• Tourism: Ulrich Spörel (Unit F.6: Information society and tourism)
• Agriculture: Céline Ollier (Unit E.2: Agriculture and fisheries)
This publication was edited and coordinated by Åsa Önnerfors (Unit E.4: Regional statistics and geo­
graphical information) with the help of Berthold Feldmann (Unit E.4: Regional statistics and geo­
graphical information) and Pavel Bořkovec (Unit D.4: Dissemination). Baudouin Quennery (Unit E.4:
Regional statistics and geographical information) produced all the statistical maps.
We are also very grateful to:
— the Directorate-General for Translation of the European Commission, and in particular the
German, English and French translation units;
— the Publications Office of the European Union, and in particular Bernard Jenkins in Unit B.1,
Cross­media publishing, and the proofreaders in Unit B.2, Editorial services.
4 Eurostat regional yearbook 2009

6. Contents
INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Statistics on regions and cities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
The NUTS classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Coverage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
More regional information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1 POPULATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Unveiling the regional pattern of demography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Population density . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Population change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Methodological notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2 EUROPEAN CITIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Enhanced list of indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Moving from five-year periodicity to annual data collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Extended geographical coverage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Discovering the spatial dimension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Core cities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
Larger urban zones. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
Geography matters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3 LABOUR MARKET . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Regional working time patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
Brief overview for 2007 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
Regional work patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Part-time jobs: lowering the average working time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
Employees spend less time at work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Methodological notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
4 GROSS DOMESTIC PRODUCT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
What is regional gross domestic product?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
Regional GDP in 2006. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
Average GDP over the three-year period 2004–06 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
Major regional differences even within the countries themselves . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
Dynamic catch-up process in the new Member States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
Different trends even within the countries themselves. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
Convergence makes progress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
Methodological notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Purchasing power parities and international volume comparisons. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Eurostat regional yearbook 2009 5

7. 5 HOUSEHOLD ACCOUNTS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
Introduction: measuring wealth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
Private household income . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
Results for 2006 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
Primary income . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
Disposable income . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
Dynamic development on the edges of the Union . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
Methodological notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
6 STRUCTURAL BUSINESS STATISTICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Regional specialisation and business concentration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Specialisation in business services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
Employment growth in business services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
Characteristics of the top 30 most specialised regions in business services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
Methodological notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
7 INFORMATION SOCIETy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
Access to information and communication technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
Use of the Internet and Internet activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
Non-users of the Internet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
Methodological notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
8 SCIENCE, TECHNOLOGy AND INNOvATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
Research and development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
Human resources in science and technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
High-tech industries and knowledge-intensive services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
Patents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
Methodological notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
9 EDUCATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
Students’ participation in education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
Participation of 4-year-olds in education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
Students in upper secondary education and post-secondary non-tertiary education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
Students in tertiary education. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
Tertiary educational attainment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
Lifelong learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
Methodological notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
6 Eurostat regional yearbook 2009

8. 10 TOURISM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
Accommodation capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
Overnight stays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
Average length of stay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
Tourism intensity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
Tourism development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
Inbound tourism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
Methodological notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
11 AGRICULTURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
Utilised agricultural area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
Proportion of area under cereals to the utilised agricultural area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
Proportion of permanent crops to the utilised agricultural area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
Agricultural production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
Wheat production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
Grain maize production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
Rapeseed production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
Methodological notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
ANNEX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
European Union: NUTS 2 regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
Candidate countries: statistical regions at level 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
EFTA countries: statistical regions at level 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
Eurostat regional yearbook 2009 7

10. Introduction

11. Introduction
Statistics on regions and cities throughout Europe and offers a couple of expla­
nations for why they vary so much from region
Statistical information is essential for under­ to region. The three economic chapters on Gross
standing our complex and rapidly changing domestic product, Household accounts and
world. Eurostat, the Statistical Office of the Euro­ Structural business statistics all give us detailed
pean Communities, is responsible for collecting insight into the general economic situation in re­
and disseminating data at European level, not gions, private households and different sectors of
only from the 27 Member States of the Euro­ the business economy.
pean Union, but also from the three candidate
countries (Croatia, the former Yugoslav Repub­ We are particularly proud to present a new and
lic of Macedonia and Turkey) and the four EFTA very interesting chapter on the Information so-
countries (Iceland, Liechtenstein, Norway and ciety, which describes the use of information
Switzerland). and communication technologies (ICT) among
private persons and households in European
The aim of this publication, the Eurostat regional regions. This chapter tells us, for example, how
yearbook 2009, is to give you a flavour of some of many households use the Internet regularly and
the statistics on regions and cities that we collect how many have broadband access. The next two
from these countries. Statistics on regions enable chapters are on Science, technology and innova-
us to identify more detailed statistical patterns tion and Education, three areas of statistics that
and trends than national data, but since we have are often seen as key to monitoring achievement
271 NUTS 2 regions in the EU­27, 30 statisti­ of the goals set in the Lisbon strategy to make
cal regions on level 2 in the candidate countries Europe the most competitive and dynamic
and 16 statistical regions on level 2 in the EFTA knowledge­based economy in the world.
countries, the volume of data is so great that one
clearly needs some sorting principles to make it In the next chapter we learn more about regional
understandable and meaningful. statistics on Tourism, and which tourist desti­
nations are the most popular. The last chapter
Statistical maps are probably the easiest way for the focuses on Agriculture, this time mainly crop
human mind to sort and ‘absorb’ large amounts of statistics, revealing which kind of crop is grown
statistical data at one time. Hence this year’s Euro­ where in Europe.
stat regional yearbook, as in previous editions,
contains a lot of statistical maps where the data
is sorted by different statistical classes represented The NUTS classification
by colour shades on the maps. Some chapters also
make use of graphs and tables to present the statis­ The nomenclature of territorial units for statistics
tical data, selected and sorted in some way (differ­ (NUTS) provides a single uniform breakdown of
ent top lists, graphs with regional extreme values territorial units for the production of regional sta­
within the countries or only giving representative tistics for the European Union. The NUTS classi­
examples) to make it easier to understand. fication has been used for regional statistics for
many decades, and has always formed the basis
We are proud to present a great variety of subjects for regional funding policy. It was only in 2003,
tackled in the 11 chapters in this years’ edition though, that NUTS acquired a legal basis, when
of the Eurostat regional yearbook. The first chap­ the NUTS regulation was adopted by the Parlia­
(1) More information on
ter on Population gives us detailed knowledge of ment and the Council (1).
the NUTS classification different demographic patterns, such as popula­
can be found at http://
ec.europa.eu/eurostat/ tion density, population change and fertility rates Whenever new Member States join the EU, the
ramon/nuts/splash_ in the countries examined. This chapter can be NUTS regulation is amended to include the re­
regions.html
considered the key to all other chapters, since gional classification in those countries. This was
all other statistics depend on the composition of the case in 2004, when the EU took in 10 new
the population. The second chapter focuses on Member States, and in 2007 when Bulgaria and
European cities and explains in detail the defini­ Romania also joined the European Union.
tions of the various spatial levels used in the Ur­ The NUTS regulation states that amendments of
ban Audit data collection, with some interesting the regional classification, to take account of new
examples on how people travel to work in nine administrative divisions or boundary changes in
European capitals.
the Member States, may not be carried out more
The chapter on the Labour market mainly de­ frequently than every three years. In 2006, this
scribes the differences in weekly working hours review took place for the first time, and the re­
10 Eurostat regional yearbook 2009

12. Introduction
sults of these changes to the NUTS classification given on the three candidate countries (Croatia,
have been valid since 1 January 2008. the former Yugoslav Republic of Macedonia and
Turkey) and the four EFTA countries (Iceland,
Since these NUTS changes were introduced quite
Liechtenstein, Norway and Switzerland).
recently, the statistical data are still missing in
some cases or have been replaced with national Regions in the candidate countries and the EFTA
values on some statistical maps, as indicated in countries are called statistical regions and they
the footnotes to each map concerned. This ap­ follow the same rules as the NUTS regions in
plies in particular to Sweden, which introduced the European Union, except that there is no legal
NUTS level 1 regions, to Denmark and Slovenia, base. Data from the candidate and EFTA coun­
which introduced new NUTS level 2 regions, tries are not yet available in the Eurostat database
and to the two northernmost Scottish regions, for some of the policy areas, but the availability
North Eastern Scotland (UKM5) and Highlands of data is constantly improving, and we hope to
and Islands (UKM6), where the border between have even more complete coverage from these
the two regions has changed. The regional data countries in the near future.
availability for these countries will hopefully
soon be improved.
More regional information
Please also note that some Member States have a
relatively small population and are therefore not In the subject area ‘Regions and cities’ under the
divided into more than one NUTS 2 region. Thus, heading ‘General and regional statistics’ on the
for these countries the NUTS 2 value is exactly Eurostat website you will find tables with statis­
the same as the national value. Following the lat­ tics on both ‘Regions’ and the ‘Urban Audit’, with
est revision of the NUTS classification, this now more detailed time series (some of them going
applies to six Member States (Estonia, Cyprus, back as far as 1970) and with more detailed sta­
Latvia, Lithuania, Luxembourg and Malta), one tistics than this yearbook contains. You will also
candidate country (the former Yugoslav Republic find a number of indicators at NUTS level 3 (such
of Macedonia) and two EFTA countries (Iceland as area, demography, gross domestic product and
and Liechtenstein). In all cases the whole country labour market data). This is important since some
consists of one single NUTS 2 region. of the countries covered are not divided into
A folding map on the inside of the cover accom­ NUTS 2 regions, as mentioned above.
panies this publication and it shows all NUTS For more detailed information on the content
level 2 regions in the 27 Member States of the of the regional and urban databases, please con­
European Union (EU­27) and the correspond­ sult the Eurostat publication European regional
ing level 2 statistical regions in the candidate and and urban statistics — Reference guide — 2009
EFTA countries. In the annex you will find the edition, which you can download free of charge
full list of codes and names of these regions. This from the Eurostat website. You can also down­
will help you locate a specific region on the map. load Excel tables containing the specific data used
to produce the maps and other illustrations for
Coverage each chapter in this publication on the Eurostat
website. We do hope you will find this publication
The Eurostat regional yearbook 2009 mainly con­ both interesting and useful and we welcome your
tains statistics on the 27 Member States of the feedback at the following e­mail address: estat­
European Union but, when available, data is also regio@ec.europa.eu
Eurostat regional yearbook 2009 11

14. Population

15. 1 Population
Unveiling the regional pattern million (1960) to almost 500 million (497 million
on 1 January 2008). Including candidate coun­
of demography tries and EFTA countries, the total population
Demographic trends have a strong impact on the has grown over the same period from under 450
societies of the European Union. Consistently low million to 587 million.
fertility levels, combined with extended longevity The total population change has two compo­
and the fact that the baby boomers are reaching nents: the so­called ‘natural increase’, which is
retirement age, result in demographic ageing of defined as the difference between the numbers of
the EU population. The share of the older gen­ live births and deaths, and net migration, which
eration is increasing while the share of those of ideally represents the difference between inward
working age is decreasing. and outward migration flows (see ‘Methodologi­
The social and economic changes associated with cal notes’). Changes in the size of a population are
population ageing are likely to have profound the result of the number of births, the number of
implications for the EU — and also to be visible deaths and the number of people who migrate.
at regional level, stretching across a wide range Up to the end of the 1980s, natural increase
of policy areas and impacting on the school­age was by far the major component of population
population, healthcare, labour force participa­ growth. However, there has been a sustained de­
tion, social protection and social security issues cline in the natural increase since the early 1960s.
and government finances, etc. On the other hand, international migration has
The demographic development is not the same gained importance and became the major force
in all regions of the EU. Some demographic phe­ of population growth from the beginning of the
nomena might have a stronger impact in some 1990s onwards.
regions than in others. The analysis on the following pages is mainly
This chapter presents the regional pattern of de­ based on demographic trends observed over the
mographic phenomena as it is today. period from 1 January 2003 to 1 January 2008. For
this purpose, five­year averages have been calcu­
lated of the total annual population change and its
Population density components. Given that demographic trends are
long­term developments, the five­year averages
On 1 January 2007, 584 million people inhabited the provide a stable and accurate picture. They help to
European Union and candidate and EFTA coun­ identify regional clusters, which often stretch well
tries. The population distribution is varied across beyond national borders. For the sake of compara­
the 317 NUTS 2 regions that make up this area. bility, the population change and its components
Map 1.1 shows the population density on 1 Janu­ are presented in relative terms, calculating the
ary 2007. The population density of a region is the so­called crude rates, i.e. they relate to the size of
ratio of the population of a territory to its size. the total population (see ‘Methodological notes’).
Generally, capital city regions are among the most Maps 1.2, 1.3 and 1.4 show these figures on total
densely populated, as Map 1.1 shows. Inner Lon­ population change and its components.
don was by far the most densely populated, but the In most of the north­east, east and part of the
Bruxelles­Capitale, Wien, Berlin, Praha, Istanbul, south­east of the area made up by the European
Bucureşti — Ilfov and Attiki (Greece) regions also Union and the candidate and EFTA countries, the
have densities above 1 000 inhabitants per km². population is on the decrease. Map 1.2 is marked
The least densely populated region was the region by a clear divide between the regions there and in
of Guyane (France), while the next least densely the rest of the EU. Most affected by the decreasing
populated regions, with fewer than 10 inhabitants population trend are Germany (in particular the
per km², were all in Sweden, Finland, Iceland and former eastern Germany), Poland, Bulgaria, Slo­
Norway. By comparison, the European Union has vakia, Hungary and Romania, and to the north
a population density of 114 inhabitants per km². the three Baltic States and the northern parts
of Sweden and the Finnish region of Itä­Suomi.
Population change Decreasing population trends are also evident
in many regions of Greece. To the east, on the
During the last four and a half decades, the pop­ other hand, the total population change is positive
ulation of the 27 countries that make up today’s in Cyprus and, to a lesser extent, in the former
European Union has grown from around 400 Yugoslav Republic of Macedonia and Turkey.
14 Eurostat regional yearbook 2009

16. Population 1
Map 1.1: Population density, by NUTS 2 regions, 2007
Inhabitants per km2
Eurostat regional yearbook 2009 15

17. 1 Population
Map 1.2: Total population change, by NUTS 2 regions, average 2003–07
Per 1 000 inhabitants
16 Eurostat regional yearbook 2009

18. Population 1
In nearly all western and south­western regions of 2003–07. The resulting negative ‘natural popu­
the EU the population increased over the period lation change’ is widespread and affects almost
2003–07. This is particularly evident in Ireland 50 % of the EU’s regions.
and in almost all regions of the United Kingdom,
A single extended cross­border region can be
Italy, Spain, France and Portugal, including the
identified showing a natural increase of popu­
French overseas departments and the Spanish and
lation, made up of Ireland, the central United
Portuguese islands in the Atlantic Ocean. There
Kingdom, most regions in France, Belgium, Lux­
has also been positive total population change in
embourg, the Netherlands, Switzerland, Iceland,
Austria, Switzerland, Belgium, Luxembourg and
Lichtenstein, Denmark and Norway: in these
the Netherlands.
regions, in the period 2003–07, live births were
The picture provided by Map 1.2 can be refined by more numerous than deaths.
analysing the two components of total population
Deaths are more numerous than births in Ger­
change, namely natural change and migration.
many, the Czech Republic, Slovakia, Hungary,
Map 1.3 shows that in many regions of the EU Slovenia, Croatia, Romania and Bulgaria, and also
more people died than were born in the period in the Baltic States and Sweden in the north and
Figure 1.1: Total fertility rates by country, 1986 and 2006
Children per woman
SK
PL
LT
SI
RO
DE
CZ
HU
LV
PT
IT
BG
HR
ES
GR
AT
MT
LI
MK
CY
CH
EE
LU
NL
BE
DK
UK
FI
SE
IE
NO
FR
IS
TR
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
1986 2006
Source: Eurostat Demographic Statistics
Notes: 1986 data: EE, PL, MT: national estimates; LI: 1985 national estimate; HR: 1990; TR: 1990 national estimate; MK: 1994
2006 data: IT, BE, TR: national estimates
Eurostat regional yearbook 2009 17

19. 1 Population
Map 1.3: Natural population change (live births minus deaths), by NUTS 2 regions, average 2003–07
Per 1 000 inhabitants
18 Eurostat regional yearbook 2009

20. Population 1
Greece, Italy and Portugal in the south. The other Relatively high fertility rates tend to be recorded in
countries have an overall more balanced situation. countries that have implemented a range of family­
friendly policies, such as the introduction of acces­
A major reason for the slowdown of the natural
sible and affordable childcare and/or more flexible
increase of the population is the fact that inhabit­
working patterns; this is the case for France, the
ants of the EU have fewer children. At aggregat­
Nordic countries and the Netherlands.
ed level, in the 27 countries that today form the
European Union, the total fertility rate has de­ The (slight) increase in the total fertility rate that
clined from a level of around 2.5 in the early is observed in some countries between 1986 and
1960s to a level of about 1.5 in 1993, where it has 2006 may be partly attributable to a catching­up
remained since (for the definition of the total fer­ process following postponement of the decision
tility rate, see the ‘Methodological notes’). to have children. When women give birth later in
life, the total fertility rate first indicates a decrease
At country level, in 2006, a total fertility rate of
in fertility, followed later by a recovery.
less than 1.5 was observed in 17 of the 27 Member
States. To compare, Figure 1.1 also includes figures By comparison, in the more developed parts of
for 1986 and for the candidate and EFTA countries. the world today, a total fertility rate of around
Figure 1.2: Crude birth rates, by NUTS 2 regions, 2007
Births per 1 000 inhabitants
BE Prov. West-Vlaanderen Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest
BG Severozapaden Yugoiztochen
CZ Střední Morava Střední Čechy
DK Sjælland Hovedstaden
DE Saarland Hamburg
EE
IE Border, Midland and Western Southern and Eastern
EL Ipeiros Kriti
ES Principado de Asturias Ciudad Autónoma de Ceuta
FR Corse Guyane
IT Liguria Provincia Autonoma Bolzano/Bozen
CY
LV
LT
LU
HU Nyugat-Dunántúl Észak-Alföld
MT
NL Limburg (NL) Flevoland
AT Burgenland (A) Vorarlberg
PL Opolskie Pomorskie
PT Alentejo Região Autónoma dos Açores
RO Sud-Vest Oltenia Nord-Est
SI Vzhodna Slovenija Zahodna Slovenija
SK Západné Slovensko Východné Slovensko
FI Itä-Suomi Pohjois-Suomi
SE Norra Mellansverige Stockholm
UK Cornwall and Isles of Scilly Inner London
HR Središnja i Istočna Sjeverozapadna Hrvatska
(Panonska) Hrvatska
MK
TR
IS
LI
NO Hedmark og Oppland Oslo og Akershus
CH Ticino Région lémanique
0 5 10 15 20 25 30 35
National value
Source: Eurostat Demographic Statistics.
Notes: FR, UK: 2006
TR: national level
Eurostat regional yearbook 2009 19

21. 1 Population
Map 1.4: Net migration, by NUTS 2 regions, average 2003–07
Per 1 000 inhabitants
20 Eurostat regional yearbook 2009

22. Population 1
2.1 children per women is considered to be the • regions in the north­east of France and the
replacement level, i.e. the level at which the popu­ French overseas departments;
lation would remain stable in the long run if there
• a few regions in the south of Italy, in the Neth­
were no inward or outward migration. At present
erlands and in the United Kingdom.
(2006 data), practically all of the EU and the can­
didate and EFTA countries, with the exception Regions where the two components of population
of Turkey and Iceland, are still well below the re­ change do not compensate for, but rather add to,
placement level. one another are often exposed to major develop­
ments, upwards or — in some regions — down­
The analysis of Map 1.3 can also be refined by iso­
wards. In Ireland, Luxembourg, Belgium, Malta,
lating the contribution of live births to the natural
Cyprus, Switzerland, Iceland, many regions
population change. Figure 1.2 shows the regional
in France and in Norway and some regions in
differences within each country of the so­called
Spain, the United Kingdom and the Netherlands,
crude birth rates (see the ‘Methodological notes’).
a natural increase has been accompanied by posi­
The largest regional differences in 2007 were
tive net migration. However, in eastern German
in France, where the highest crude birth rate is
regions, Lithuania and Latvia and some regions
more than three times the lowest, followed by
in Poland, Slovakia, Hungary, Bulgaria and Ro­
Spain, where the highest crude birth rate is also
mania, both components of population change
three times the lowest. For the other countries,
have moved in a negative direction, as can also be
regional differences in crude birth rates are less
seen from Map 1.2. In these regions this trend has
pronounced but still significant.
led to sustained population loss.
The third determinant of population change
In 2007, the average population in the EU­27 aged
(after fertility and mortality) is migration. As
65 and older was 17 %, which means an increase
many countries in the EU are currently at a point
of 2 percentage points in the last 10 years. This
in the demographic cycle where ‘natural popula­
ageing population, especially in rural areas,
tion change’ is close to being balanced or nega­
raises issues about infrastructure and the need
tive, the importance of immigration increases
for social services and healthcare.
when it comes to maintaining population size.
Moreover, migration also contributes indirect­ The highest percentage of population aged 65
ly to natural change, given that migrants have and older can be found in Liguria (Italy), at 27 %.
children. Migrants are also usually younger and Germany follows with up to 24 % in the region of
have not yet reached the age at which death is Chemnitz and a further 14 regions above 20 %.
more frequent. Some regions in Greece, Portugal, France and
Spain also show high figures, with up to 23 % of
In some regions of the European Union, negative
their population aged 65 years and older. These
‘natural change’ has been offset by positive net mi­
regions also show low and even negative natural
gration. This is at its most striking in Austria, the
population change, with more people dying than
United Kingdom, Spain, the northern and central
being born.
regions of Italy and some regions of western Ger­
many, Slovenia, southern Sweden, Portugal and In Turkey the percentage of the population aged
Greece, as can be seen in Map 1.4. The opposite is 65 and older is as low as 3 % in the region of Van,
much rarer: in only a few regions (namely in the and on average 8 % in the other regions. Although
northern regions of Poland and of Finland and Turkey has negative net migration, the high fertil­
in Turkey) has positive ‘natural change’ been can­ ity results in a young population. Similarly, with
celled out by negative net migration. high fertility, coupled with high net migration,
only 11 % and 12 % of the population in the two
Four cross­border regions where more people
regions of Ireland are 65 and older.
have left than arrived (negative net migration)
can be identified on Map 1.4: According to projections, elderly people would
account for an increasing share of the population
• the northernmost regions of Norway and Fin­
and this is due to sustained reductions in mortal­
land;
ity in past and future decades. The ageing process
• an eastern group, comprising most of the re­ can be typified as ageing from the top, as it large­
gions of eastern Germany, Poland, Lithuania ly results from projected increases in longevity,
and Latvia and most parts of Slovakia, Hun­ moderated by the impact of positive net migra­
gary, Romania, Bulgaria and Turkey; tion flows and some recovery in fertility.
Eurostat regional yearbook 2009 21

23. 1 Population
Map 1.5: Percentage of population aged 65 years old and more, by NUTS 2 regions, 2007
22 Eurostat regional yearbook 2009

24. Population 1
Conclusion nomena have been identified, spreading across
national boundaries. While population decline is
This chapter highlights certain features of region­ evident in several regions, at aggregated level the
al population development in the area made up by EU­27 population still increased in that period
the EU­27 Member States and the candidate and by around 2 million people every year. The main
EFTA countries over the period from 1 January driver of population growth in this area is migra­
2003 to 1 January 2008. As far as possible, typolo­ tion, which counterbalanced, as seen in the maps,
gies of regions in the different demographic phe­ the negative natural change in many regions.
Methodological notes
Sources: Eurostat — Demographic Statistics. For more information please consult the Eurostat
website at http://www.ec.europa.eu/eurostat.
Total fertility rate is defined as the average number of children that would be born to a
woman during her lifetime if she were to pass through her childbearing years conforming to the
age-specific fertility rates that have been measured in a given year.
Migration can be extremely difficult to measure. A variety of different data sources and definitions
are used in the Member States, meaning that direct comparisons between national statistics can
be difficult or misleading. The net migration figures here are not directly calculated from immigra-
tion and emigration flow figures. Since many countries either do not have accurate, reliable and
comparable figures on immigration and emigration flows or have no figures at all, net migration is
generally estimated on the basis of the difference between total population change and natural in-
crease between two dates (in the Eurostat database, it is then called net migration including cor-
rections). The statistics on net migration are therefore affected by all the statistical inaccuracies in
the two components of this equation, especially population change. In effect, net migration equals
all changes in total population that cannot be attributed to births and deaths.
Crude rate of total population change is the ratio of the total population change during the year
to the average population of the area in question in that year. The value is expressed per 1 000
inhabitants.
Crude rate of natural change is the ratio of natural population increase (live births minus deaths)
over a period to the average population of the area in question during that period. The value is
expressed per 1 000 inhabitants. It is also the difference of the crude birth rate minus the crude
death rate, which are, respectively, the ratio of live births during the year over the average popula-
tion and of deaths over the average population.
Crude rate of net migration is the ratio of net migration during the year to the average popula-
tion in that year. The value is expressed per 1 000 inhabitants. As stated above, the crude rate of
net migration is equal to the difference between the crude rate of total change and the crude
rate of natural change (i.e. net migration is considered as the part of population change not at-
tributable to births and deaths).
Population density is the ratio of the population of a territory to the total size of the territory (in-
cluding inland waters), as measured on 1 January.
Eurostat regional yearbook 2009 23

26. European cities

27. 2 European cities
Introduction Moving from five-year periodicity
to annual data collection
Data on European cities were collected in the Ur­
ban Audit project. The project’s ultimate goal is to Four reference years have been defined so far for
help improve the quality of urban life: it supports the Urban Audit: 1991, 1996, 2001 and 2004. For
the exchange of experience among European cit­ the years 1991 and 1996, data were collected ret­
ies; it helps to identify best practices; it facilitates rospectively only for a reduced number of 80 var­
iables. Where data for these years were not avail­
benchmarking at European level; and it provides
able, data from adjacent years were also accepted.
information on the dynamics both within the cit­
In 2009 Eurostat launched an annual Urban Au­
ies and with their surroundings.
dit, requesting data for a limited number of vari­
The Urban Audit has become a core task of Euro­ ables. The annual data will help users to monitor
stat. Even so, the project would not have been pos­ certain urban developments more closely.
sible without sustained help and support from a
wide range of colleagues. In particular, we would Extended geographical coverage
like to acknowledge the effort made by the cities
The pilot study in 1999 covered 58 cities from 15
themselves, the national statistical institutes and
countries. Since then the number of participating
the Directorate­General for Regional Policy of
countries has doubled and the number of cities
the European Commission.
has grown sixfold. At present the Urban Audit
The Urban Audit celebrates its 10th anniversary covers 362 cities from 31 countries — including
this year. The ‘Urban Audit pilot project’ was the the EU­27, Croatia, Turkey, Norway and Swit­
first attempt to collect comparable indicators on zerland. The 321 Urban Audit cities in the EU­27
European cities, and was first conducted by the have more than 120 million inhabitants, covering
Commission in June 1999. The past 10 years have approximately 25 % of the total population. This
brought many changes, and we have constantly extended sample ensures that the results give a
made efforts to improve the quality of the data reliable portrait of urban Europe.
— including coverage, comparability and rele­ The number of cities was limited and the ones
vance. So, where we are now? The list of indica­ selected should reflect the geographical cross­
tors has been enhanced to take account of new section of each country. Consequently, in a few
policy needs; the periodicity has been reduced to countries some large cities (over 100 000 inhab­
satisfy users; and geographical coverage has been itants) were not included. To complement the
extended following successive rounds of EU en­ Urban Audit data collection in this respect, the
largement. Large City Audit was launched. The Large City Au­
dit includes all ‘non­Urban Audit cities’ with more
Enhanced list of indicators than 100 000 inhabitants in the EU­27. For these
There have been three major revisions of the list so cities a reduced set of 50 variables is collected.
far. Policy relevance, data availability and experi­ We invite all readers to explore the wealth of in­
ence with previous collections have been reviewed formation gathered in the past 10 years by brows­
to produce the current list of more than 300 in­ ing the Urban Audit data on Eurostat’s website.
dicators. These indicators cover several aspects
of quality of life, such as demography, housing,
health, crime, labour market, income disparity,
Discovering the spatial dimension
local administration, educational qualifications, Cities are usually displayed as distinct uncon­
the environment, climate, travel patterns, the nected dots on a map. This visualisation method
information society and cultural infrastructure. increases visibility but it misrepresents reality
They are derived from the variables collected by and distorts the understanding of linkages be­
the European Statistical System. Data availability tween a city and its hinterland and the under­
differs from domain to domain: in the domain of standing of linkages between cities. Cities can
demography, for example, data are available for no longer be treated as discrete unrelated enti­
more than 90 % of the cities, whereas for the envi­ ties without a spatial dimension. The recent de­
ronment data are available for less than half of the velopments in transport, communication and
cities. In 2009 we will introduce new indicators to information technology infrastructure ease the
symbolise the relationship between the city and flow of people and resources from one area to
its hinterland. another considerably. Urban–rural connectivity
26 Eurostat regional yearbook 2009

28. European cities 2
Map 2.1: Boundaries of cities participating in the Urban Audit data collection
Eurostat regional yearbook 2009 27

29. 2 European cities
and inter­urban relations have become critical the cites. Different land covers were grouped into
(2) A detailed description for balanced regional development. 44 classes in the CLC2000 (2). Each colour on
of the CLC2000 project
the map represents a different land cover class.
and the UMZ creation is To facilitate the analysis of the interaction be­
available on the website of Some of these classes are particularly important
the European Environment tween the city and its surroundings for each
Agency (http://www.eea. for our analysis of cities. Red areas, for instance,
participating city, different spatial levels were de­
europa.eu).
are territories covered with urban fabric: roads,
fined. Most of the data are collected at core city
residential buildings, buildings belonging to the
level, i.e. the city as defined by its administrative/
local administration or to public services, etc.
political boundaries. In addition, a level called
Purple areas are used for commercial or industri­
the larger urban zone was described. The larger
al purposes. Light purple represents green urban
urban zone is an approximation of the functional
areas like parks, botanical gardens, etc. The areas
urban area extending beyond the core city. of these three land cover classes lying less than
Map 2.1 illustrates the cities participating in 200 m apart were merged together to define
the Urban Audit data collection, showing the ‘built­up’ area. Port areas, airports and sport fa­
boundaries of core cities and larger urban zones. cilities were included if they were neighbours of
Not surprisingly, the largest cities in Europe in the previously defined ‘built­up’ area.
terms of population — London, Paris, Berlin and As a next step, road and rail networks and water
Madrid — tend to have the greatest larger urban courses were added if they were within 300 m of
zones in terms of area, and are readily identifiable the area defined beforehand. The area identified by
on the map. In most cases the larger urban zone this procedure is called the ‘urban morphological
includes only one core city. However, there are zone’ (UMZ). The urban morphological zones of
exceptions, such as the German Ruhr area, which Hamburg and Lyon are shown in the middle row
includes several core cities (see inset in Map 2.1). of Map 2.2. These maps also make it possible to
The demarcation of core cities is illustrated in de­ compare the UMZ and core city in terms of area.
tail in Map 2.2 while the larger urban zones are In Hamburg 82 %, and in Lyon 73 %, of the area
shown in Map 2.3. The spatial data used to pro­ of the UMZ lies within the boundaries of the core
duce most of the maps presented in this chapter city. In terms of population the intersections are
are available from the Geographic Information even greater: 90 % of the population of the core
System of the European Commission (GISCO) — city of Hamburg lives in the UMZ, and in Lyon
a permanent service of Eurostat (for more infor­ the respective figure is 98 %. As we expected, the
mation, visit Eurostat’s website). two areas are not identical but they overlap each
other to a large extent, thus ensuring that the data
Core cities collected at core city level are relevant and mean­
Throughout Europe’s history — in ancient Greece, ingful for the morphological city as well.
in ancient Rome and in the Middle Ages — a city To measure spatial inequalities within the city,
was as much a political entity as a collection of the area of the core city was divided into sub­city
buildings. This collection of buildings was usu­ districts. Sub­city districts were defined in such
ally surrounded by fortified walls. As the city a way as to keep to the population thresholds
grew the walls were expanded. In the modern set — minimum 5 000 and maximum 40 000 in­
era the significance of the city walls as part of the habitants — as far as possible. The bottom row of
defence system declined and most of them were Map 2.2 illustrates the sub­city districts of Ham­
demolished. The boundary of the city as a politi­ burg and Lyon. Key demographic and social indi­
cal entity and the boundary of the built­up area cators are available in the Urban Audit database
were no longer linked and the location of these for the more than 6 000 sub­city districts.
boundaries is no longer evident. Nowadays, a city
could be designated as an urban settlement or as a Larger urban zones
legal, administrative entity. The Urban Audit uses
City walls, even if they are preserved, no longer
this later concept and demarcates the core city by