European Regional Statistics

1. European Regional Statistics Gunter Schäfer Eurostat Unit E4 - Regional statistics and geographical information

2. Eurostat’s tasks in the domain of regional and urban information • Regular collection of regional and urban data from National Statistical Offices • Estimation of missing data (if possible) • Assure the comparability of the data • Development of appropriate methodology of data collection and compilation • Consultancy of major users (DG REGIO)

3. Purpose of regional data • Quantitative information = basis for objective and unbiased cohesion policy • Definition, implementation and monitoring of EU regional policies (2007-2013: 347 billion euros) • Commission (DG REGIO) is main user • Selection of eligible regions • Ex-post evaluation • Regions are increasingly in focus of general public

4. Example Italy of regional aid • Allocated funds 2007-13 : Total: €28.8 billion • Convergence: €21.6 billion • Regional Competitiveness and Employment: €6.3 billion • European Territorial Cooperation: €846 million • Focus of programmes • Developing knowledge networks; • Increasing living standards; • Security and social inclusion; • Fostering business clusters, services and competition; • Internationalising and modernising the economy • Targets • Contribute to average annual GDP growth of between 2.4 and 3.1% in the ‘Convergence’ regions • Increase employment from roughly 45% to 50% in these regions

5. NUTS regions in Italy

6. Available regional Statistics

9. In addition: Urban Statistics • Since about 1990 the Urban Audit pilot project collected a wide range of statistical variables for about 350 cities • Different concepts (Core City, Larger Urban Zone, Sub-city Districts) • Many issues of data availability, organisation in Member States, types of use of the data • Urban Audit was perhaps too ambitious • Currently initiative is ongoing to redefine Urban Statistics in a simplified but also more homogenous way (e.g. definition of city)

10. UrbanStatistics:ExampleItaly

11. Challenges for Regional (and Urban) Statistics • Tight resource situation in European Statistical System • Additional indicators are requested by policy makers (e.g. government finance, enterprise demography, innovation activities) • Increasing focus of functional areas (rural-urban, mountain, coastal areas, etc.) • Exploring ways of efficiency gains and better exploiting existing information: • Flexible use of geocoded data from surveys, e.g. for functional regions • Small area estimations • Spatial analysis to combine geographic and statistical data

12. New Urban Rural Typology • Agreed with OECD • Avoids problems of previous method based on NUTS 3 • Units: 1 km² grid cells • Population grid: registered population when available, otherwise disaggregation grid (JRC) • Identify population living in urban areas: • Selection of grid cells with density > 300 inh./km² • Only groups of grid cells, representing a total population of > 5000 inhabitants • Contiguity is evaluated including diagonals

13. Rural-UrbanTypologyapplied to NUTS 3

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