Transcript 2 nd EU-China regional seminar 8 th October 2007

European Regional Classification,
Statistics & Geography
Roger Cubitt, Head of Unit
AIM OF THIS TALK:
Increase your
knowledge
about what
Eurostat
does concerning
regional classification
regional statistics and
geographical information
2nd EU-China regional seminar
8th October 2007
Structure of my talk
1. The scope of European regional
statistics
2. The regional classification
(NUTS)
3. Geographical Information
(a brief look!)
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Chapter 1
Regional Statistics
Eurostat Unit D2
2nd EU-China regional seminar
8th October 2007
Eurostat tasks in the domain of
regional information
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Regular collection of regional data from
National Statistical Offices
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Estimation of missing data
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Development of appropriate methodology
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Satisfy (ad-hoc) user needs

Make users aware of the available information
through adequate dissemination
2nd EU-China regional seminar
8th October 2007
Purpose of regional data

Quantitative information = basis for objective
and unbiased structural and cohesion policy

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
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 Ex-post evaluation
Contents of Regio database
Demography
Unemployment
Regional
accounts
Tourism
Health
Agriculture
Labour market,
unemployment
Transport and energy
Environment
Business
data
Science &
Technology
Education
National level
Data flow of regional statistics
Source 2
Source 4
Source 1
Source 5
Source 6
National Statistical Office
Thematic production db
Eurostat
Source 3
Thematic production db
Thematic production db
production db
regional statistics
Source 7
Thematic production db
New Cronos
REGIO
2nd EU-China regional seminar
8th October 2007
Publications
 The regional yearbook
 easy-to-read commentaries, maps, graphs (160 pages)
 CD-ROM included
 appears around September each year
 bestseller of Eurostat
 Statistics in Focus
 12 pages of text, tables and maps
 January: regional accounts; September: unemployment
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 At irregular intervals: further topics treated
2nd EU-China regional seminar
8th October 2007
Publications (2)
 Portrait of the Regions
 Started 1992
 Covers all MS and CC
 Web site under construction, will open mid 2005
 Methodological publications
 Regional classification NUTS
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 Reference guide: exhaustive description of the
database content
2nd EU-China regional seminar
8th October 2007
Urban Statistics – what for ?
 “Cohesion” = the basis of Regional EU Policy
 Target = fewer disparities between European regions
 Cities (=urban agglomerations) play a specific and important
role in this policy goal
 Hence: In the mid 90s, the Commission saw a growing need
for reliable, quantitative urban data
 Eurostat was commissioned by DG REGIO to carry out
the Urban Audit project
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 Until then, no comparable urban statistics existed at a
EU level, and very little at national levels
2nd EU-China regional seminar
8th October 2007
The 2003 Urban Audit data collection

333 variables collected
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268 EU cities involved
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189 cities in EU-15
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plus 69 cities in new MS and 2 CC
Three spatial units:
core city, larger urban zone, sub-city districts
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In addition: perception survey in 31 cities of old MS,
January 2004
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2nd EU-China regional seminar
8th October 2007
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
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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
2nd EU-China regional seminar
8th October 2007
Examples of Indicators
Obvious indicators
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Population
Income
GDP
Unemployment
Poverty
Unusual indicators
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Crime rate
Days of sunshine
Cinema places
Noise level
Mode of transport to
work
2nd EU-China regional seminar
8th October 2007
Chapter 2
The regional classification “NUTS”
What and how!
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2nd EU-China regional seminar
8th October 2007
The regional classification NUTS

NUTS = “nomenclature des unités territoriales
statistiques”
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Over 25 years in use, without legal base
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Favours institutional breakdowns
(primarily administrative divisions in force)
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But for 10 years the basis for Structural Funds
i.e. no functional regions
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Hierarchical nomenclature with three levels
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Since July 2003, an EU Regulation
2nd EU-China regional seminar
8th October 2007
NUTS Regulation 1059/2003 (EU)
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The NUTS Regulation is the base for regional
statistics in the EU. The aim is to have harmonised
and stable regional statistics across the EU

The regional classification is in turn the base for EU
regional policy
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Eligibility areas are selected on the basis of regional
statistical indicators
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Regional, local and urban data are used by the
Commission for policy and analysis
2nd EU-China regional seminar
8th October 2007
Content of the Regulation
 Rules for managing the NUTS
 Annex 1 – list of regions
 Annex 2 – administrative/nonadministrative status
by NUTS level
 Annex 3 – smaller territorial units
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2nd EU-China regional seminar
8th October 2007
The basic criteria for EU regions
Population thresholds for NUTS levels
 NUTS 1 – 3 000 000 to 7 000 000
 NUTS 2 – 800 000 to 3 000 000
 NUTS 3 – 150 000 to 800 000
 Administrative regions: average size
 Non-administrative regions: each region has
to comply with thresholds
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2nd EU-China regional seminar
8th October 2007
Management of the NUTS
Stability
 Avoid breaks in statistical time series
 Rules for how to modify the annexes
 At least 3 years of stability
 Non-administrative regions – change only if
standard deviation in terms of population is
reduced
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2nd EU-China regional seminar
8th October 2007
Local Administrative Units
NUTS underpinned by more detailed
levels
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LAU 1 = former NUTS 4
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LAU 2 = former NUTS 5
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Not covered by NUTS regulation
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But: lists of LAU by NUTS level 3 units have to be
supplied to Eurostat
Chapter 3 - a brief look at GI
GISCO
a link between statistics
and geography
2nd EU-China regional seminar
8th October 2007
Geo-referenced data can be tailored to
selected policy areas
 Common Agricultural
Policy
GISCO PROVIDES:
 Environment policy
 Administrative
boundaries
 Regional Policy
 Rivers, lakes
 Transport Policy
 Elevation
 and many others ….
 Transport networks
 etc.
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GISCO Reference Database
Topographic data - Administrative boundaries
Administrative regions
1: 1M
Statistical regions
NUTS classification
(v. 1995, 1999, 2003)
1: 1M, 1: 3M, 1: 10M
GISCO Reference Database
Topographic data - Altimetry - Digital Elevation Model
DEM for Europe
1 : 3M, 30 arc-second
DEM
(1 km x 1 km)
1 : 20M, 5 arc-minutes
(9.3 km x 9.3 km)
1 m contour intervals
World DEM
1 : 3M, 30 arc-second
DEM
(1 km x 1 km)
available soon:
DEM for Europe, 100m
resolution up to 60° North
GISCO Reference Database
Topographic data - Hydrography
Water patterns
(incl. TEN inland waterways)
1:1M
1:3M
1:10M
Watersheds
Major sea drainage basins
of Europe
1:1M, 1:3M, 1:10M
GISCO Reference Database
Topographic data - Infrastructure
Roads network
in Europe ver. 4
incl. Road segments
eligible to TEN program
ver. 3
(TEN 2003 update
available 2nd half 2005)
1:1M
Example
2nd EU-China regional seminar
8th October 2007
Future challenges of regional
statistics
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The needs of users are occasionally difficult
to grasp
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Number of projects increasing,
human resources decreasing
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Defining priorities for data suppliers who
work under difficult financial constraints
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It takes several years to create new
statistics
(but they are quickly destroyed)
2nd EU-China regional seminar
8th October 2007
Regional Classification Issues
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The different NUTS regions across the EU are heterogeneous
making some analyses difficult
The use of population as a sole classification criteria
compounds the problem.. but what else to use?
“Functional” regions would provide a better analysis
framework but would be incompatible.
The choice of territorial breakdown depends on the spatial
pattern of the observed phenomenon
Data based on geo-location could help solve these problems
but is counter to existing collection processes in all but a few
member states
Issues with administrative
divisions
Population density by administrative units
LAU 2
Level
Issues with administrative
divisions
Population density by administrative units
NUTS 3
Level
Issues with administrative
divisions
Population density by administrative units
NUTS 2
Level
Issues with administrative
divisions
Population density by administrative units
NUTS 1
Level
Regular Raster or Grids
 Usage of equally sized grids as additional
and complementary information to
administrative units
 Spatial Analysis based on grids and
application of results on administrative
units
Regular Raster or Grids
Grid of 10 km resolution
Regular Grids
 Population grid as means for spatial
analysis of per capita statistics
 Generation of population grid using spatial
modelling techniques
Regular Grids
Population density
Average
Population
density by
commune
Regular Grids
Population density
CORINE
Land Cover as
co-variable
Regular Grids
Population density
Population
Disaggregated
density by
population
canton map
density
Examples
 Distribution of nitrogen deposition
 Population / GDP in coastal zones
 Accessibility of services
Distribution of nitrogen
deposition
Nitrogen
deposition
by grid cell
Distribution of nitrogen
deposition
Aggregation to
NUTS 3 region
Distribution of nitrogen
deposition
Aggregation
from NUTS 3 to
EuroFarm region
and inclusion of
values in
statistical
modelling of
nitrogen flow
Examples

Distribution of nitrogen deposition
 Population / GDP in coastal zones
 Accessibility of services
Spatial Data Analysis
Population in coastal and inland areas
Population / GDP in coastal zones
Disaggregated
population
density (raster
data)
Population / GDP in coastal zones
Selection of
adjacent regions
“All regions
bordering the
coastline“
Population / GDP in coastal zones
Selection of
regions within
defined distance
Population / GDP in coastal zones
Cut out all areas
within defined
distance (buffering)
Population / GDP in coastal zones
Calculate ratio
between
landlubbers and
seamen:
More than half of
population live near
the coast on a
quarter of the total
area.
Population / GDP in coastal zones
Population density as a function of
distance from the coast.
Population Density
Population density
400
300
200
100
0
2.5
10.0
17.5
25.0
32.5
40.0
47.5
Distance from coast
55.0
62.5
70.0
77.5
Population / GDP in coastal zones
What about the
economic
importance of
coastal areas in
Spain?
GDP by NUTS 3
region.
Population / GDP in coastal zones
GDP per inhabitant.
Sum of GDP of
landlubbers and
seamen.
Calculation of ratio.
Examples
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Degree of urbanisation
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Distribution of nitrogen deposition
 Population / GDP in coastal zones
 Accessibility of services
Accessibility of primary schools in Austria
 Indicators for describing rural areas
 Calculation of average distances to primary
schools by LAU2
 Aggregation of results to higher NUTS
levels
Accessibility of primary schools in Austria
Location of primary schools in Austrian communes
Accessibility of primary schools in Austria
Distribution of population based on grid
Accessibility of primary schools in Austria
Allocation of school vicinity areas (Shortest distance)
Accessibility of primary schools in Austria
Calculation of distance from each grid cell to closest school
Accessibility of primary schools in Austria
Weight with number of inhabitants
Accessibility of primary schools in Austria
Aggregate to LAU 2, NUTS 3, … level
Thanks for listening !
Any Questions ?