A new typology of European Rural and Intermediate regions. · A new typology of European Rural and...
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A new typology of European Rural and Intermediate regions. February 3-4 2011, Nordregio, Stockholm EDORA (European Development Opportunities in Rural Areas) Andrew Copus, University of the Highlands and Islands, and Nordregio
Transcript of A new typology of European Rural and Intermediate regions. · A new typology of European Rural and...
A new typology of European Rural and Intermediate regions.
February 3-4 2011, Nordregio, Stockholm
EDORA(European Development Opportunities in Rural Areas)
Andrew Copus,University of the Highlands and Islands, and Nordregio
The Presentation:
1.The thinking behind the typology
2.The data and methodology
3.The broad brush European patterns
4.Focus on the NORBA area
5.Conclusions
PART 1: The Reasoning Behind the Typology….
Drivers and processes of rural change across the EU:… The EDORA Project
…to describe the main processes of change which are resulting in the increasing differentiation of rural areas.
…to identify development opportunities and constraints for different kinds of rural areas…
…to consider how such knowledge can be translated into guiding principles to support the development of appropriate cohesion policy.
Why we need policies to strengthen Territorial Cohesion in Rural Areas?
Rural Policies are based upon generalisations.
Such as…
• The rural economy is driven by land-based industries…
• Rural areas generally show negative socio-economic trends and “vicious spirals” of decline…
• Geographical remoteness is associated with decline and disadvantage.
These still hold good in some parts of Rural Europe, but in others recent changes mean that they are becoming out of date…
The ultimate goal…Policy Guidance based on Empirical Evidence
• We need to challenge inaccurate stereotypes, (“rural myths”)…
• in favour of valid generalisations at an appropriate scale…
Macro Scale: EU Policy reflecting and structured by
Meta-Narratives of change, and Typologies of regions
+Micro Scale: Local development initiatives
taking account of all (tangible and intangible) assets.
Two levels of Differentiation,Policy Design and Targeting…
CONNEXITY
Urban-
Rural
Agri-
Centric
Economic
Competit.,
Global Capital
META -
NARRATIVES
Structural Types (Intermediate and
Predominantly Rural Areas only):
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Agrarian
...…………………………………………..
Consumption Countryside
……...……………………………………..
Diversified (Strong Secondary Sector)
…….....…………………………………...
Diversified (Strong Market Services)
D-P Typology:
IA, IR, PRA, PRR
Accumulating
Above Average
Below Average
Depleting
Accumulation
- Depletion+ Macro-level Policy Design and Targeting
=
Macro Level: Meta-Narratives and Typologies
Seven Kinds of Assets/Capital
Financial Human Social CulturalInstitutional
(Political)Built Natural
+Local/regional auditing of Intangible Assets
Micro-level endogenous place-based approaches.
=
Micro Level: - local responses determined by “Terrorial capital”
Detailed Objectives:Why make a (yet another) Typology?
• To take a typology beyond the urban-rural dimension - to integrate economic (sectoral) structure, and overall “performance”.
• To highlight the inadequacy of common misleading stereotypes about rural areas, as background to rural/regional policy debate.
• To get a picture of the broad geographic patterns produced by the 3 EDORA meta-narratives.
• To create a simple, but meaningful, (macro)regional framework for analysis of rural trends, consideration of future perspectives, and policy implications.
• To help regional and national policymakers to “benchmark” their regions in a broad European context.
Rural or “Non-Urban”?
EDORA typology cannot be (strictly speaking) a typology of Rural Areas – two reasons:
(a)(Theoretical) Rural areas do not function separately from adjacent urban areas – they are connected by a dense web of interactions.
(b)(Practical) Smallest practicable data units are NUTS 3(2), most of these contain sizable towns/cities.
It is a typology of Intermediate and Predominantly RuralRegions.
It covers EU27 +NO, CH, and TR.
Part 2: The Data and the Methodology
The EDORA Cube(Something borrowed, something new!)
…more of a three-dimensional framework for analysis, rather than a one-dimensional classification.
The three dimensions are:• Urban-Rural
(remote/accessible)• Economic structure
(diversification). • Accumulation –
Depletion(performance).
Structural Types (Intermediate and
Predominantly Rural Areas only):
-------------------------------------------------------
Agrarian
...…………………………………………..
Consumption Countryside
……...……………………………………..
Diversified (Strong Secondary Sector)
…….....…………………………………...
Diversified (Strong Market Services)
D-P Typology:
IA, IR, PRA, PRR
Accumulating
Above Average
Below Average
Depleting
Accumulation
- Depletion
Database and Methodology
-Simple step-wise multi-criteria methodology
Analysis in Excel, mapping in ArcGIS
The database used:
•27 raw data variables (mainly from Eurostat REGIO)
•12 (ratio) indicators used for Structural Typology
•5 used for Accumulation-Depletion (Performance) Scores
No. Short Name Description
Variables
used Base Year
Ag1 PCPrimeE(Tot) % Employment in Primary Activities V18,V16 2006
Ag2 PCPrimeE % Private Sector Employment in Primary Activities V18,V17 2006
Ag3 PCPrimeG(Tot) % GVA from Primary Activities V11,V9 2006
Ag4 PCPrimeG % Private Sector GVA from Primary Activities V11,V10 2006
Ag5 AWUPEmp AWU as a % of Total Private Employment V24,V16 2007
CC1 HotCat % of employmet in Hotels and Catering V26,V25 2007
CC2 BPPC Bed Places per Capita V27,V1 2006-8
CC3 NSRES Nights Spent by Residents per capita V29,V1 2008
CC4 NSNON Nights Spent by Non-Residents per capita V30,V1 2008
CC5 NSTOT Nights Spent (Total) per capita V31,V1 2008
CC6 ANA Access to Natural Areas V28 2008
CC7 PCOGA % of holdings with OGA V32 2005
CC8 LT4ESU % of Holdings <4 ESU V33,V34 2007
NR1 CEGKGR Ratio of GVA from NACE CE to GK V12,V14 2007 agriculture
NR2 CEGPGR Ratio of GVA from NACE CE to GP V12,V15 2007
NR3 CFGPGR Ratio of GVA from NACE CF to GP V13,V15 2007
NR4 CEGKEMP Ratio of Employ. in NACE CE to GK V19,V20 2007
NR5 CEGPEMP Ratio of Employ. in NACE CE to GP V19,V21 2007
AD1 NETMIG Net Migration (rate) V3,V1 2001-05
AD2 GDPpercap GDP per Capita V7,V1 2007
AD3 GDPCh Average annual change in GDP V8 1995-2006
AD4 TotEmpCh Average annual change in Employment V22 1995-2006
AD5 Unemp Unemployment Rate V23,V6 2008
Tourism
capacity /
intensity
Peri-
productivist
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Acores
Guyane
Madeira
Réunion
Canarias
MartiniqueGuadeloupe
Zagreb
Valletta
Budapest
Bratislava
Roma
Riga
Oslo
Bern
Wien
Kyiv
Vaduz
Paris
Praha
Minsk
Tounis
Lisboa
Skopje Ankara
MadridTirana
Sofiya
London
Berlin
Dublin
Athinai
Tallinn
Nicosia
Beograd
Vilnius
Kishinev
Sarajevo
Helsinki
Warszawa
Podgorica
El-Jazair
Ljubljana
Stockholm
Reykjavik
København
Bucuresti
Amsterdam
Luxembourg
Bruxelles/Brussel
Methodology and Database
No. Short Name Description
Variables
used Base Year
Ag1 PCPrimeE(Tot) % Employment in Primary Activities V18,V16 2006
Ag2 PCPrimeE % Private Sector Employment in Primary Activities V18,V17 2006
Ag3 PCPrimeG(Tot) % GVA from Primary Activities V11,V9 2006
Ag4 PCPrimeG % Private Sector GVA from Primary Activities V11,V10 2006
Ag5 AWUPEmp AWU as a % of Total Private Employment V24,V16 2007
CC1 HotCat % of employmet in Hotels and Catering V26,V25 2007
CC2 BPPC Bed Places per Capita V27,V1 2006-8
CC3 NSRES Nights Spent by Residents per capita V29,V1 2008
CC4 NSNON Nights Spent by Non-Residents per capita V30,V1 2008
CC5 NSTOT Nights Spent (Total) per capita V31,V1 2008
CC6 ANA Access to Natural Areas V28 2008
CC7 PCOGA % of holdings with OGA V32 2005
CC8 LT4ESU % of Holdings <4 ESU V33,V34 2007
NR1 CEGKGR Ratio of GVA from NACE CE to GK V12,V14 2007 agriculture
NR2 CEGPGR Ratio of GVA from NACE CE to GP V12,V15 2007
NR3 CFGPGR Ratio of GVA from NACE CF to GP V13,V15 2007
NR4 CEGKEMP Ratio of Employ. in NACE CE to GK V19,V20 2007
NR5 CEGPEMP Ratio of Employ. in NACE CE to GP V19,V21 2007
AD1 NETMIG Net Migration (rate) V3,V1 2001-05
AD2 GDPpercap GDP per Capita V7,V1 2007
AD3 GDPCh Average annual change in GDP V8 1995-2006
AD4 TotEmpCh Average annual change in Employment V22 1995-2006
AD5 Unemp Unemployment Rate V23,V6 2008
Tourism
capacity /
intensity
Peri-
productivist
If these three Ag indicators are all >EU27 (rural) mean – the region
is “Agrarian”.Indicators in italics are only used for filling
“gaps” in the database.CC Indicators grouped into three “composite”
indices. (Tourism, Access to Nat. Areas, Peri-Prod.).
If 2 or more indices exceed the EU (rural) average the region is
“Consumption Countryside”
Remaining regions are considered “Diversified”. If GVA from Private Services is
greater than GVA from Manufacturing, then the region is “D(PS)”, and vice versa –
“D(S)”.
All 5 A-D indicators combined into a single index (z scores),
Regions classified into 4 groups, using mean and +/-
0.5 SD.
Structural Typology:Defining the Agrarian Regions….
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Acores
Guyane
Madeira
Réunion
Canarias
MartiniqueGuadeloupe
Zagreb
Valletta
Budapest
Bratislava
Roma
Riga
Oslo
Bern
Wien
Kyiv
Vaduz
Paris
Praha
Minsk
Tounis
Lisboa
Skopje Ankara
MadridTirana
Sofiya
London
Berlin
Dublin
Athinai
Tallinn
Nicosia
Beograd
Vilnius
Kishinev
Sarajevo
Helsinki
Warszawa
Podgorica
El-Jazair
Ljubljana
Stockholm
Reykjavik
København
Bucuresti
Amsterdam
Luxembourg
Bruxelles/Brussel
Number of IndicatorsExceeding the EU27 Average
No Data
0
1
2
3
PU Regions
Agrarian regions
The indicators:(i) Percentage of Private Sector GVA from Primary Industries.(ii) Percentage of Private Sector Employment in Primary Industries.(iii) AWU as a percentage of Total Private Sector Employment.
Structural Typology:Defining the Consumption Countryside Regions….
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Acores
Guyane
Madeira
Réunion
Canarias
MartiniqueGuadeloupe
Zagreb
Valletta
Budapest
Bratislava
Roma
Riga
Oslo
Bern
Wien
Kyiv
Vaduz
Paris
Praha
Minsk
Tounis
Lisboa
Skopje Ankara
MadridTirana
Sofiya
London
Berlin
Dublin
Athinai
Tallinn
Nicosia
Beograd
Vilnius
Kishinev
Sarajevo
Helsinki
Warszawa
Podgorica
El-Jazair
Ljubljana
Stockholm
Reykjavik
København
Bucuresti
Amsterdam
Luxembourg
Bruxelles/Brussel
Number of IndicatorsExceeding the EU27 Average
No Data
0
1
2
3
PU Regions
These are the Consumption Countrysideregions…
The Indicator Groups:(i) Tourism capacity and intensity(ii) Proximity of natural public goods(iii) Peri-productivist agriculture
Structural Typology:Defining the Diversified - D(PS) and D(S) - Regions….
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Acores
Guyane
Madeira
Réunion
Canarias
MartiniqueGuadeloupe
Zagreb
Valletta
Budapest
Bratislava
Roma
Riga
Oslo
Bern
Wien
Kyiv
Vaduz
Paris
Praha
Minsk
Tounis
Lisboa
Skopje Ankara
MadridTirana
Sofiya
London
Berlin
Dublin
Athinai
Tallinn
Nicosia
Beograd
Vilnius
Kishinev
Sarajevo
Helsinki
Warszawa
Podgorica
El-Jazair
Ljubljana
Stockholm
Reykjavik
København
Bucuresti
Amsterdam
Luxembourg
Bruxelles/Brussel
Ratio NACE C-E:G-K
No Data
>-0.5
-0.5 - 0.0
0.1 - 0.5
>0.5
PU Regions
D(PS)
D(S)
N.B.
Agrarian and CC regions are defined first, - diversified regions are the residual
Part 3: The European Maps - Broad Patterns
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Acores
Guyane
Madeira
Réunion
Canarias
MartiniqueGuadeloupe
Zagreb
Valletta
Budapest
Bratislava
Roma
Riga
Oslo
Bern
Wien
Kyiv
Vaduz
Paris
Praha
Minsk
Tounis
Lisboa
Skopje Ankara
MadridTirana
Sofiya
London
Berlin
Dublin
Athinai
Tallinn
Nicosia
Beograd
Vilnius
Kishinev
Sarajevo
Helsinki
Warszawa
Podgorica
El-Jazair
Ljubljana
Stockholm
Reykjavik
København
Bucuresti
Amsterdam
Luxembourg
Bruxelles/Brussel
Urban-Rural Types(NUTS 3 Regions)
No Data
Predominantly Urban
Intermediate Close to a City
Intermediate Remote
Predominantly Rural Close to a City
Predominantly Rural Remote
Dijkstra-Poelman (Rurality)
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Acores
Guyane
Madeira
Réunion
Canarias
MartiniqueGuadeloupe
Zagreb
Valletta
Budapest
Bratislava
Roma
Riga
Oslo
Bern
Wien
Kyiv
Vaduz
Paris
Praha
Minsk
Tounis
Lisboa
Skopje Ankara
MadridTirana
Sofiya
London
Berlin
Dublin
Athinai
Tallinn
Nicosia
Beograd
Vilnius
Kishinev
Sarajevo
Helsinki
Warszawa
Podgorica
El-Jazair
Ljubljana
Stockholm
Reykjavik
København
Bucuresti
Amsterdam
Luxembourg
Bruxelles/Brussel
Structural Types (Intermediate andPredominantly Rural NUTS 3 Regions)
No Data
PU Regions
Agrarian
Consumption Countryside
Diversified (Strong Secondary Sector)
Diversified (Strong Private Services Sector)
Economic Structure
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Acores
Guyane
Madeira
Réunion
Canarias
MartiniqueGuadeloupe
Zagreb
Valletta
Budapest
Bratislava
Roma
Riga
Oslo
Bern
Wien
Kyiv
Vaduz
Paris
Praha
Minsk
Tounis
Lisboa
Skopje Ankara
MadridTirana
Sofiya
London
Berlin
Dublin
Athinai
Tallinn
Nicosia
Beograd
Vilnius
Kishinev
Sarajevo
Helsinki
Warszawa
Podgorica
El-Jazair
Ljubljana
Stockholm
Reykjavik
København
Bucuresti
Amsterdam
Luxembourg
Bruxelles/Brussel
Performance (A-D) Types (Intermediate andPredominantly Rural NUTS 3 Regions)
No Data
PU Regions
Depleting
Below Average
Above Average
Accumulating
Performance
Unweighted mean of the following indicators(all normalised according to the EU27 (Non-Urban) NUTS 3 meanand standard deviation):(i) Annual rate of net migration(ii) Per Capita GDP (in PPS)(iii) Annual rate of change in GDP(iv) Annual percentage change in total employment
Some Generalisations which emerge from the EDORA Typologies
• Agrarian regions are mainly concentrated in an arc stretching around the eastern and southern edges of the EU27.
• The rest of the European space is a patchwork of Consumption Countryside, Diversified (Secondary) and Diversified (Private Services).
• Agrarian regions and Diversified (Secondary) regions tend to be relatively low performers, (Depleting).
• The Consumption Countryside regions and the Diversified (Private Services) group are both high performers, and seem likely to continue to “accumulate” in the future.
What can the D-P and Structural Typologies tell us about Performance? Cross-Tabulation Analysis:
Common combinations of D-P and Structural Types
• Diversified (Mkt Serv.) + IA
• Diversified (Sec.) + IA
• Consumption Countryside + IA/PRA
• Agrarian + PRR/PRA
Cross-Tabulation of D-P and Performance Types
• 60% of population of IA regions lived in Above Average performing or Accumulating regions
• All other D-P types had a majority of population living in Below Average or Depleting regions
Cross-Tabulation of Structural and Performance Types
• Almost 50% of Agrarian region population lived in Depleting Regions, only 12% in Positive Performance categories.
• More than 2/3 of Consumption Countryside population lives in Positive Performingregions.
• The same is true of the Diversified (market services) regions.
• But only 55% of Diversified (Secondary) population lives in Positive Performingregions.
Summary: Rough ranking in terms of performance (low-high):
Agrarian, Diversified (Sec.), Consumption Countryside, Diversified (Mkt Serv.)
Part 4: Focus on the NORBA area…
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Riga
OsloTallinn
Vilnius
Helsinki
Stockholm
København
Urban-Rural Types (NUTS 3 Regions)
No Data
Predominantly Urban
Intermediate Close to a City
Intermediate Remote
Predominantly Rural Close to a City
Predominantly Rural Remote
Rurality and Remoteness…
PRR, 21
PRR, 64
PRR, 26
PRA, 18
PRA, 25
PRA, 29IR, 17
IR, 1
IR, 2
IA, 37
IA, 9
IA, 34
PU, 8PU, 1
PU, 9
0
25
50
75
100
Baltic Nordic EU27
(a) Rurality/Accessibility (Dijkstra-Poelman)% Area
Area
PRR, 10
PRR, 26
PRR, 5
PRA, 15
PRA, 26
PRA, 14
IR, 9
IR, 2
IR, 1
IA, 42
IA, 24
IA, 35
PU, 25 PU, 22
PU, 44
0
25
50
75
100
Baltic Nordic EU27
(a) Rurality/Accessibility (Dijkstra-Poelman)% Population
Pop.
PRR, 6
PRR, 20
PRR, 4
PRA, 9
PRA, 23
PRA, 10
IR, 7
IR, 1
IR, 1
IA, 41
IA, 24
IA, 30
PU, 37PU, 31
PU, 56
0
25
50
75
100
Baltic Nordic EU27
(a) Rurality/Accessibility (Dijkstra-Poelman)% GDP
GDP
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OsloTallinn
Vilnius
Helsinki
Stockholm
København
Structural Types (NUTS 3 Regions)
No Data
PU Regions
Agrarian
Consumption Countryside
Diversified (Strong Secondary Sector)
Diversified (Strong Private Services Sector)
Structural Types
Ag, 54
Ag, 4
Ag, 23
CC, 31
CC, 92CC, 45
D(Sec), 3
D(Sec), 1
D(Sec), 6
D(PServe), 5
D(PServe), 2
D(PServe), 16
0
25
50
75
100
Baltic Nordic EU27
(b) Economic Structure% Area
Area
Ag, 35
Ag, 1
Ag, 13
CC, 28
CC, 63
CC, 24
D(Sec), 2 D(Sec), 3
D(Sec), 6
D(PServe), 10 D(PServe), 10
D(PServe), 13
0
25
50
75
100
Baltic Nordic EU27
(b) Economic Structure% Population
Pop.
Ag, 22
Ag, 1Ag, 6
CC, 31
CC, 57
CC, 21
D(Sec), 2D(Sec), 2
D(Sec), 5
D(PServe), 9D(PServe), 9
D(PServe), 12
0
25
50
75
100
Baltic Nordic EU27
(b) Economic Structure% GDP
GDP
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OsloTallinn
Vilnius
Helsinki
Stockholm
København
Number of Indicators exceedingthe EU27 Mean(NUTS 3 Regions)
No Data
0
1
2
3
PU Regions
Agrarian Indicators
•Agrarian regions dominate LV and EE
•E Finland is close to qualifying too
•Most of SE and NO and all of DK has all 3 indicators below the EU average
The indicators:(i) Percentage of Private Sector GVA from Primary Industries.(ii) Percentange of Private Sector Employment in Primary Industries.(iii) AWU as a percentage of Total Private Sector Employment.
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OsloTallinn
Vilnius
Helsinki
Stockholm
København
Number of Indicators exceedingthe EU27 Mean(NUTS 3 Regions)
No Data
0
1
2
3
PU Regions
Consumption Countryside Indicators
•NO and SE, and most of FI qualify on all 3 groups of indicators
•S Finland, LT, EE and parts of DK only pass on 2 criteria (fail on tourism)
The Indicator Groups:(i) Tourism capacity and intensity(ii) Proximity of natural public goods(iii) Peri-productivist agriculture
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OsloTallinn
Vilnius
Helsinki
Stockholm
København
Z Scores(NUTS 3 Regions)
No Data
>-0.5
-0.5 to 0
0 to +0.5
>+0.5
PU Regions
Secondary to Private Services Ratio•This pattern is largely “academic” –since most NORBA regions already defined as Ag. Or CC
•Most of SE/FI regions have relatively strong Secondary sector.
•Most of Baltic and NO regions have less developed Secondary sector –so Private Services are highlighted.
Synthetic Indicator of Performance
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Riga
OsloTallinn
Vilnius
Helsinki
Stockholm
København
Performance Scores(NUTS 3 Regions)
No Data
> -1.00
-0.99 - -0.50
-0.49 - -0.25
-0.24 - 0.00
0.01 - 0.25
0.26 - 0.50
0.51 - 1.00
>1
PU Regions
Unweighted mean of the following indicators(all normalised according to the EU27 (Non-Urban) NUTS 3 meanand standard deviation):(i) Annual rate of net migration(ii) Per Capita GDP (in PPS)(iii) Annual rate of change in GDP(iv) Annual percentage change in total employment
•Most of Nordic regions have positive scores (above EU average)
•Most of Baltic regions (especially inland) have negative (below average) scores.
•NO “harmonisation” issue?
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OsloTallinn
Vilnius
Helsinki
Stockholm
København
Performance (A-D) Types (NUTS 3 Regions)
No Data
PU Regions
Depleting
Below Average
Above Average
Accumulating
A-D (Performance) Types
Deplet., 40
Deplet., 2Deplet., 13
Below, 44
Below, 35
Below, 33
Above, 6
Above, 31
Above, 29
Accum., 2
Accum., 30 Accum., 16
0
25
50
75
100
Baltic Nordic EU27
(c) Performance (Depleting-Accumulating)% Area
Area
Deplet., 26
Deplet., 0Deplet., 11
Below, 36
Below, 11
Below, 16
Above, 5
Above, 45 Above, 17
Accum., 7Accum., 22
Accum., 12
0
25
50
75
100
Baltic Nordic EU27
(c) Performance (Depleting-Accumulating)% Population
Pop.
Deplet., 16
Deplet., 0 Deplet., 5
Below, 30
Below, 9Below, 10
Above, 4
Above, 40
Above, 16
Accum., 14 Accum., 19
Accum., 14
0
25
50
75
100
Baltic Nordic EU27
(c) Performance (Depleting-Accumulating)% GDP
GDP
Some conclusions….
• The three generalisations are quite inadequate as a basis for rural cohesion policy – the rural reality is far more complex, and “mixed” – not always negative.
• Substantial contrasts between Nordic and Baltic regions, and between individual countries.
• Some “broad-brush” (European macro region) patterns can be identified, which need to be accommodated within rural/regional policy.
• More specifically the Structural Typology speaks on the difficult issue of the relative roles of CAP and Cohesion Policy….
– These should be seen as complementary, not competing…
•CAP must have significant territorial cohesion impacts in “Agrarian” and “CC” regions, probably negligible in Diversified regions.
•Perhaps this Territorial Cohesion role should in future be reflected in the calculation of Direct Payments (Pillar 1) and Pillar 2 budget allocation?
•In the diversified regions the key issue is to mobilise local territorial assets ( mostly intangibles) – multi-fund local development approaches seem promising.
Relative importance of Agriculture
Rela
tive L
evel of T
err
itorial C
ohesio
n
Impact of C
AP
Pill
ar
2
Agrarian
RegionsConsumption
Countryside
RegionsDiversified
(Secondary)
Regions
Diversified
(Market Services)
Regions
Endogenous
Tailoring
of Regional
Programmes
Micro-scale
Patterns of
(Intangible) Assets,
Regional AuditsIndividual
Region
Programme
Coordination
and Targeting
Macro-scale
(Structural)
Patterns.
Regional indicators
and Typologies
Type or
Macro-Region
For more detail see EDORA Working Paper 24, available for download from EDORA project website:
www.nordregio.se/EDORA
Thank you for your attention…
