1. A new methodological approach
Spatial clustering of international functions in European Metropolitan Areas
A new methodological approach
Dr. Karl Peter Schön – Adam Radvanszki
Bundesinstitut für Bau-, Stadt- und Raumforschung (BBSR)
04/05 June 2013
SCORUS conference
Brussels, Belgium

2. How to identify metropolitan regions
The ‚classical‘ geographical approach:
Preselect administrative units with „urban“ characteristics
based on population size, density, or other morphological indicators
identify larger regional units (commuting areas, cont. build-up areas),
Then add indicators for metropolitan, international, global importance
And analyse to which degree urban areas are „metropolitan“, i.e. involved in global processes
artefacts ?
Does pop matter?
Comparable data?

3. Alternative approach
Start from (global) functions rather than territorial units:
Modern societies are organised in subsystems which are based on functional specialisation (Luhmann).
Five important subsystems are: politics, economy, science, transport, culture.
All these subsystems are globalizing, building their own specific (spatial) patterns of networks.
Networks consist of nodes and edges.
Where are global functions located (the nodes)?

4. Reversed approach Instead of asking:
„Where in Europe are the most significant concentrations of population („urban areas“) and what „metropolitan“ characteristics do these areas have?“
we asked:
„Where in Europe are the most significant concentrations of metropolitan functions and how do they constitute a European pattern of „metropolitan areas“?“

5. Index of metropolitan functions
5 functional areas
Politics, Economy, Science, Transport, Culture
16 group of indicators
38 indicators
The 38 normalised indicators are additively combined to 16 groups of indicators, these to an index for each functional area, these again combined to a summary index of metropolitan function

7. Requirements for the indicators
All 38 indicators meet the following requirements:
Cover the whole European territory (CoE)
Standard definition for all countries
Reliable unofficial statistical data
Exact geocoding of all data (LAU-2 or exact coordinates)

8. locations with metropolitan function
About municipalities all across Europe form the territorial reference of the analysis
On a single indicator base, units have any metropolitan function (= 7 %)

10. 8.480

21. Concentration of metropolitan functions
Out of municipalities in Europe (LAU-2 statistical units)
8.480 (=7%) have any metropolitan function
The top 480 (MFI > 1) represent 78% of all MF
The top 184 (MFI > 3) represent 63% of all MF
On a country base:
Germany = 16%
UK =12%
France = 10%
Italy = 8%
Spain = 6%
These 5 together: 52%
… and the Pentagon: ~ 50%

22. Concentration of metropolitan functions
MFI index points per 1 Mio population:
Luxembourg = 55
Switzerland =17
Sweden = 14
Belgium = 12
Norway = 12
Denmark, Austria, Netherlands = 10 (each)

25. Some characteristics These resulting 125 metropolitan regions
Account for 10% of the total area
Concentrate 50% of Europe‘s population (=350 mio inh.)
And 65% of Europe‘s GDP (=8.500 bn €)
And 80% of all metropolitan functions

27. population size and metro functions

29. Role of metropolitan areas in European territorial development
Territorial development policy should be evidence based
Territorial Agenda 2020 to support the territorial dimension in the implementation of the EU2020 Strategy
Analysis to join policy goals with evidence
Metropolitan areas in focus
Follow-up of the study on functions of european metropolitan areas
The role of metropolitan areas in european territorial development and their contribution to the EU2020 and TA2020 goals is investigated

30. Functional metropolitan areas vs. NUTS
Territorial scope: EU28
Differentiation
Metropolitan areas: capital cities and other metropolitan areas
Non-metropolitan areas:
„metropole-marginal“ areas and peripheries
Old and new EU member states
Methodological challenge:
Availability of regional data
Recalculation from NUTS to functional metropolitan areas
Method applied: data weighed with the proportion of metropolitan population within the NUTS region, based on LAU2 level

31. Uneven concentration of population
Capital cities have a similar weight in EU13 and EU15 (20%)
In EU15 more cities can show up a bundle of metropolitan functions (48% of population)
Only 5 cities can reach the benchmark of metropolitan functions in EU 13 (less than 9%)
High concentration in capitals in small countries

32. Ageing in general, but in different patterns
Youth:
Slight differences between EU15 and EU13 in the proportion
Difference in the direction of change: in EU13 proportion of youth slightly increases with peripheriality, in EU15 vice versa
Old:
Substantially more elderly in EU15
Clear tendency in EU15 : proportion of elderly increases with peripheriality

33. Peripheries have high poverty rate
Methodological problems with measuring poverty
Who is poor?
On what territorial level is information available?
Peripheries tend to have higher poverty rates
Gap between metropolitan areas and paripheries is wider in EU13
Capital cities in EU13 have higher poverty rates than other metropolitan areas

34. Metropolitan areas of large countries are the engines of the EU
High concentration of economic output in metropolitan regions
Capital cities have a high share of output in EU13
Peripheries have a dominant role in some new member states
Absolute values of GDP show where the real engines of the economy are

35. Differences in employment and productivity
Capital cities have a similar weight in employment in the old and new member states
Almost half of the employed in other metropolitan areas in old member states (less than 10% in new member states)
One quarter of employment in peripheries, in new member states more than half
Labour productivity: decreases with peripheriality, gap is wider in new member states

36. R&D concentration will cause further polarisation
R&D is concentrated
in the old member states (90%)
in some countries
in capital cities
Risk of further polarisation on the long run
Only a few areas have reached the EU2020 target

37. Environmental impacts are hard to measure
Lack of regionalised data on 20/20/20 goals
Rough estimations possible
Most of the energy is used in the metropolitan areas of the old member states
Peripheries account for a higher share of energy consumption in new member states
Metropolitan areas seem to be more energy-efficient than peripheries

38. Observations for policy consideration
The importance of metropolitan areas is different in different parts of Europe
Capital city regions have a similar weight in the old and new member states, however it varies for each member state
In the old member states, metropolitan regions have a substantial share, in new member states only a few cities can bundle metropolitan functions
The importance of peripheries in the new member states is high, where small and medium sized towns can have a crucial role in development
In most themes metropolitan areas are better off than peripheries
Risk of polarisation: differences in ageing, R&D can lead to long term polarisation between more central and more peripheral regions

39. More to go… EU2020 performance of single metropolitan areas Employment
R&D
Tertiary education
Poverty
Early school leavers
Energy consumption
Greenhouse gas emission
Renewable energy
To explore better the differences among metropolitan areas in their possibility to contribute to the implementation of the EU2020 Strategy
To better explore the role of metropolitan areas in the implementation of the common territorial priorities in the EU (TA2020)

40. Thank you for your attention! peter.schoen@bbr.bund.de
> en > publications
-> BBSR-Berichte KOMPAKT 7/2010
-> BBSR-Online-Publikation, Nr. 01/2011
-> BBSR-Analysen KOMPAKT 2013 (forthcoming, in German)