Transcript European Regional Statistics

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
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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
NUTS 2 or
NUTS 3
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
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 death
Health 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 data
Credit institutions
NUTS 1 or
NUTS 2r
Yes
Tourism
Tourist accommodation, arrivals, nights spent
NUTS 2 or
NUTS 3
Yes
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
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
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
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, Subcity 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
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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
RuralUrban
Typology
applied
to
NUTS 3
THANK YOU FOR YOUR ATTENTION
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