european regional statistics gunter schäfer eurostat unit e4 - regional statistics and geographical...
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European Regional Statistics
Gunter SchäferEurostat 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 ContentNUTSLevel
Legal Base
Economicaccounts
Gross Value Added and GDPGrowth of real GDPCompensation of employeesEmploymentGross Fixed Capital FormationHousehold accounts
NUTS 2 or NUTS 3
European System ofNational AccountsRegulation
Demography Population and area Population changePopulation projectionsRegional level census 2001 round
NUTS 2 orNUTS 3
Regulation forcensus every 10years, gentleman'sagreement
LabourMarket
Economically active populationEmployment and unemploymentSocio-demographic labour force statisticsLabour market disparities
NUTS 2 or NUTS 3
Yes
Labour Cost Labour cost surveys (1996, 2000, 2004) NUTS 1 Yes
Domain Content NUTS Level Legal Base
Migration Internal migration: arrivals, departures by sex, origin and destination
NUTS 2 Gentleman's agreement
Health Causes of deathHealth care infrastructure, Health status,Hospital patients
NUTS 2 Gentleman's agreement, legal basis in preparation
Education Number of students by sex, age, education level, orientation,Educational attainment, lifelong learning
NUTS 2 Yes
Structural Business
SBS yearly and multi yearly dataCredit institutions
NUTS 1 or NUTS 2r
Yes
Tourism Tourist accommodation, arrivals, nights spent NUTS 2 or NUTS 3
Yes
Information Society
Internet accessComputer usage
NUTS 1 or NUTS 2
Yes (mandatory for NUTS 1)
Agriculture Land use/coverFarm Structure SurveysAnimal and crop productionEconomic accounts for agricultureAgri-environmental indicators
NUTS 2 or NUTS 3
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 transportTransport infrastructure, stock of vehicles and road accidents
NUTS 2 or NUTS 3
Yes
Environment Water resourcesWastewater treatmentSolid waste
NUTS 1 or NUTS 2
yes for waste statistics
Science and Technology
R&D expenditure and staffHuman resources in science and technologyEmployment in high technology sectorsEuropean patent applications to EPO
NUTS 1 or NUTS 2
Yes
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)
UrbanStatistics:ExampleItaly
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-UrbanTypologyapplied to NUTS 3
THANK YOU FOR YOUR ATTENTION
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