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

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)

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

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

NUTS regions in Italy

Available regional Statistics Domain Content NUTS Level Legal Base Economic accounts Gross Value Added and GDP Growth of real GDP Compensation of employees Employment Gross Fixed Capital Formation Household accounts NUTS 2 or NUTS 3 European System of National Accounts Regulation Demography Population and area Population change Population projections Regional level census 2001 round Regulation for census every 10 years, gentleman's agreement Labour Market Economically active population Employment and unemployment Socio-demographic labour force statistics Labour market disparities Yes Labour Cost Labour cost surveys (1996, 2000, 2004) NUTS 1

Domain Content NUTS Level Legal Base Migration Internal migration: arrivals, departures by sex, origin and destination NUTS 2 Gentleman's agreement Health Causes of death Health care infrastructure, Health status, Hospital patients Gentleman's agreement, legal basis in preparation Education Number of students by sex, age, education level, orientation, Educational attainment, lifelong learning Yes Structural Business SBS yearly and multi yearly data Credit institutions NUTS 1 or NUTS 2r Tourism Tourist accommodation, arrivals, nights spent NUTS 2 or NUTS 3 Information Society Internet access Computer usage NUTS 1 or NUTS 2 Yes (mandatory for NUTS 1) Agriculture Land use/cover Farm Structure Surveys Animal and crop production Economic accounts for agriculture Agri-environmental indicators Regulations, gentleman's agreement

Domain Content NUTS Level Legal Base Maritime Policy Spatial data and indicators relevant to the coast and the sea NUTS 2 or NUTS 3 EU's Integrated Maritime Policy Transport Road, rail, maritime, inland waterways and air transport Transport infrastructure, stock of vehicles and road accidents NUTS 2 or NUTS 3 Yes Environment Water resources Wastewater treatment Solid waste NUTS 1 or NUTS 2 yes for waste statistics Science and Technology R&D expenditure and staff Human resources in science and technology Employment in high technology sectors European patent applications to EPO

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)

Urban Statistics: Example Italy

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

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

Rural- Urban Typology applied to NUTS 3

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