1. 13-Jul-07 Harmonisation of Regional and Urban Statistics – a Challenge Dr. Berthold Feldmann Eurostat – the statistical office of the European Union

2. Name of the presentation 2 / 28 Structure of the talk  What regional and urban statistics for the European Union are offered by Eurostat  The need for harmonisation  Possible obstacles  An example

3. 13-Jul-07 Chapter 1 Our data supply: What Eurostat can offer

4. Name of the presentation 4 / 28 Since 1985: Regional Statistics Covering a wide range of demographic, economic and social aspects in the regions Following the regional classification of the European Union called NUTS  97 major zones  271 macro regions  1303 smaller regions Including data for EFTA and candidate countries  Norway, Switzerland, Turkey, Croatia, Macedonia

5. Contents of REGIO database Demography and migration Regional accounts Environment Agriculture Transport Health Research & Development Business data Labour market (unemployment) Education Tourism Energy Information society

6. Name of the presentation 6 / 28 Since 2000: Urban Statistics (the “Urban Audit”) More than 300 indicators cover a wide range of social and economic aspects of the “quality of life” in cities Three different spatial units  365 cities in 27 EU Member States, plus cities in Croatia, Norway, Switzerland and Turkey  larger urban zones (= functional urban region)  sub-city information – for a reduced data set Data available for the reference years 1991, 1996, 2001, 2004

7. Name of the presentation 7 / 28 The topics covered 1. DEMOGRAPHY 1.1 Population 1.2 Nationality 1.3 Household Structure 2. SOCIAL ASPECTS 2.1 Housing 2.2 Health 2.3 Crime 3. ECONOMIC ASPECTS 3.1 Labour Market 3.2 Economic Activity 3.3 Income disparities and Poverty 4. CIVIC INVOLVEMENT 4.1 Civic Involvement 4.2 Local Administration 5. TRAINING AND EDUCATION 5.1 Education and Training (Provision) 5.2 Attainment of Educ. & Training 6. ENVIRONMENT 6.1 Climate/ Geography 6.2 Air Quality and Noise 6.3 Water 6.4 Waste Management 6.5 Land Use 6.6 Energy Use 7. TRAVEL AND TRANSPORT 8. INFORMATION SOCIETY 9. CULTURE AND RECREATION 9.1 Culture and Recreation 9.2 Tourism

8. Name of the presentation 8 / 28 Purpose of regional and urban data Quantitative information on regions and cities = basis for objective and unbiased cohesion policy of the European Commission Definition, implementation and monitoring of EU regional policies (2007-2013: 347 billion euros) Hence: Commission (DG REGIO) = major user of our statistics  Selection of eligible regions for funding  Ex-post evaluation of the policy actions

9. 13-Jul-07 Chapter 2 Why harmonisation?

10. Name of the presentation 10 / 28 Quality aspects : Eurostat’s code of practice Professional independence Impartiality and objectivity Non-excessive burden on respondents Cost effectiveness Relevance Accuracy and reliability Timeliness and punctuality Coherence and comparability Accessibility and clarity

11. Name of the presentation 11 / 28 Comparability Only if regional and urban statistics are comparable can they be used effectively by political agencies (from the Commission down to the city level)  the harmonisation of our statistics is an indispensible condition of quality The (mis-)use of non-harmonised data leads to wrong political decisions

12. Name of the presentation 12 / 28 How can we harmonise the data? Best solution: ex-ante harmonisation through common definitions  Example: unemployment ILO-definition  registered unemployed Second best: ex-post harmonisation through small area estimations  Borrow strength from similar data  Borrow strength from nearby reference years  Borrow strength from larger spatial units

13. 13-Jul-07 Chapter 3 Obstacles to harmonisation

14. Name of the presentation 14 / 28 Many obstacles in particular for regional and urban statistics Regional and urban statistics involve large volumes of data from many sources  More difficult to harmonise than 27 national figures The reduction of response burden leads to the use of administrative data  Definitions of administrative data differ between countries considerably and are difficult to change

15. Name of the presentation 15 / 28 Many obstacles in particular for regional and urban statistics (2) Spatial units differ between countries and within countries in size  modifiable areal unit problem (MAUP) Spatial units may change their delineation over time  Further efforts of estimation....

16. Varying size of regions – Belgium France (based on administrative boundaries) Population density at commune level

17. Varying size of regions – Belgium France (based on administrative boundaries) Population density at NUTS-3 level

18. 13-Jul-07 Chapter 4 An example

19. Name of the presentation 19 / 28 Urban Audit: “percentage of foreigners” There is a strong policy need for comparable statistics on nationality in European cities, expressed by our political users Finding the “greatest common denominator” – a definition which fits to most national methodologies Collecting the data for this definition Detecting outliers Documenting deviating definitions used

20. Name of the presentation 20 / 28 1) Germany – citizenship Nationals Foreigners – Persons who do not have German citizenship and are registered in Germany For historical reasons no data collection is possible on ethnicity

21. Name of the presentation 21 / 28 2) United Kingdom – concept of ethnicity White  White: British  White: Irish  White: Other White Mixed  Mixed: White and Black Caribbean  Mixed: White and Black African  Mixed: White and Asian  Mixed: Other Mixed Asian or Asian British  Asian or Asian British: Indian  Asian or Asian British: Pakistani  Asian or Asian British: Bangladeshi  Asian or Asian British: Other Asian Black or Black British  Black or Black British: Caribbean  Black or Black British: African  Black or Black British: Other Black Chinese or Other Ethnic Group  Chinese or Other Ethnic Group: Chinese  Chinese or Other Ethnic Group: Other Ethnic Group

22. Name of the presentation 22 / 28 3) Hungary – belonging to a national or ethnic minority Hungarian Belonging to a national/ethnic minority native in Hungary BulgarianGypsy (Roma) GreekCroatian PolishGerman ArmenianRumanian RutheneSerbian SlovakianSlovenian Ukrainian Belonging to other national/ethnic minority African Arab Chinese Jewish “What is your nationality?” “To which nationalities' cultural values and traditions do you feel affinity with?”

23. Name of the presentation 23 / 28 Finding the “greatest common divisor” UK – concept of ethnicity DE – concept of citizenship HU – concept of ethnic/national minority Variables to be collected at European level Number of residents who are nationals Number of residents who are nationals of another EU MS Number of residents who are not EU MS Number of nationals born abroad

24. Name of the presentation 24 / 28 Detecting outliers average = 94.8 standard deviation = 6.2

25. Name of the presentation 25 / 28 Detecting outliers

26. Name of the presentation 26 / 28 Documenting deviating definitions used

27. Name of the presentation 27 / 28 Conclusion European regional and urban statistics are used in a political context of cohesion policy Harmonisation of regional and urban statistics is an indispensible condition for the proper use of this data Harmonisation is more complex for regional and urban statistics than for national data sets When harmonisation is not possible, a good documentation of differences is the only solution

28. Thank you for your attention! Any Questions ?