ATTREG Project (ESPON 2013/1/7)
“The Attractiveness of Regions and Cities for Residents and Visitors” (2010-2012)
Presentation of quasi-final results
ESPON 2013 Programme - Internal Seminar
“Evidence-based Cohesion Policy: Territorial Dimensions ”
29-30 November 2011 - Kraków, Poland
A.P. Russo (URV, LP) and L. Servillo (KUL)
LEAD PARTNER
University Rovira i Virgili (ES)
PROJECT PARTNERS
KU Leuven (BE)
Univ. of Venice Ca’ Foscari (IT)
EURICUR Rotterdam (NL)
Univ. of Coimbra (PT)
RESEARCH SUBCONTRACTOR
Istanbul Technological University (TR)
Centre for Tourism Research (DK)
IGSO (PL)
Univ. of Ljubljana (SI)
Univ. of West England (UK)
Project background
•
Objectives of the project
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–
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–
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Understanding the attractiveness of territorial assets to different
“audiences”, looking into the 2001-08 period
Explaining mains spatial trends, classifying regions accordingly
Investigate these relations at different spatial scales, and focusing on
idiosyncrasies and “immeasurable” facts
Developing an analytic framework to asses different policy options
Policy questions
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How are regions endowed with territorial capital assets? What is their
potential attractiveness for different “audiences”?
How can this potential be liberated? How does governance intervene
in this process?
What is to be expected in the future, given the current EU policy
scenarios?
Project structure
DEFINING AND INTERPRETING
ATTRACTIVENESS
CONSTRUCTING A DATABASE OF
INDICATORS OF TERRITORIAL
ASSET ENDOWMENTS
DEVELOPING ATTRACTIVENESS
TYPOLOGIES AND ESTIMATING
THE RELATIONSHIPS BETWEEN
ASSETS AND FLOWS
VALIDATING / DEEPENING THE
ANALYSIS THROUGH CASE STUDY
RESEARCH
MODELLING SCENARIOS TO
UNDERSTAND THE IMPACT OF
POLICY DECISIONS
Main results achieved/envisaged
• New evidence related to the territorial dimensions of the
project
A. Indicators and regional typologies by flows attracted
(discriminating by migrations attracted and by
“wavelengths” of mobility): REALISED ATTRACTION
B. Indicators and regional typologies by endowments of
classes of territorial capital: POTENTIAL ATTRACTIVENESS
C. Model estimates relating A. to B. and identification and
classification of outliers: PROCESS INTERPRETATION
Unretentive for young and
mid-career age groups,
moderately retentive for the
older age group
Moderate retentiveness for all
working age groups
High retentiveness for all
working age groups
Highly retentive for younger
age group, moderately
retentive for mid-career age
group, unretentive for older
age group
Average net migration and
visiting flow rates
Low net migration and visiting
flow rates
High net migration rate,
average visiting flow rate
Average net migration rate,
high visiting flow rate
+5
Visitor arrivals per
head of pop.
Balearic Isl.
+3
+4
Salzburg
CLUSTER 4
average net
migration
rate, high
visiting flow
rate
Algarve
+2
Trento
Cornwall
Iceland
+1
Inner London
Prague
Noord Holland
Devon
Cyprus
(Amsterdam)
Veneto
Catalonia
Brussels
Vienna
Ile de France
Eastern Finland
CLUSTER 2
low net
migration and
visiting flow
rates
+2
−1
+1
Slovenia
−1
Nord-pas-de
Hovedstaden
País
Vasco
Calais (LKT) Zuid Holland
(Copengahen)
Attiki (Athens)
(Rotterdam)
Istanbul
Lubelskie
−2
Van (Eastern
Turkey)
−2
−3
−3
−4
−4
−5
−5
CLUSTER 1
average net
migration and
visiting flow
rates
+3
CLUSTER 3
high net
migration
rate, average
+4
visiting flow
rate
Net migration rate
+5
CLASS 1
High environmental capital
Average-low antropic capital
Low economic and institutional capital
Low socio-cultural capital
CLASS 2
High environmental capital
Low antropic and economic cap.
Very low institutional and sociocultural capital
CLASS 3
Very high economic, institutional,
socio-cultural capital
Average antropic cap.
Low environmental cap.
CLASS 4
High institutional and economic cap.
Average high antropic cap.
Low environmental and socio-cultural
cap.
CLASS 5
High socio-cultural cap.
Average-high environmental cap.
Average-low institutional and antropic
cap.
Low economic cap.
Looking into the future – “Policy bundles”
Index
SMART
Monument index
SUSTAINABLE
INCLUSIVE
+
Pop density
=?
=?
Rank of airport
+
-
Tourist beds
+
accessibility
++
-
GDP pre capita
=?
=?
Tertiary educated workforce
+
NACE G-I employment
=?
=?
+
Small seasonal difference
NATURA 2000 area
+
Satisfied with health service
+
Public sector employment
Student ratio
Life satisfaction
Pensionable age ratio
+
+
+
+
+
+
+
Key facts and observations for policymakers
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No (easy) recipes for economic growth
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A longer term, multi-scale perspective needed
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Ambiguous relationship between attractiveness and economic growth
Economic growth can be one of the effects of retentiveness but not necessarily always
of attractiveness – fragility from “overheating” may be the unwanted result (and it did
after 2008)
Territorial cohesion strategies that successfully address territorial capital are long-term
strategies
The mobilisation of regional attractiveness based on a combination of top-down EU and
state policies and bottom-up initiatives of local and regional stakeholders such as
municipalities, universities and businesses
Factors to be taken into account:
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•
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Time issue
Coherent aims and targets
Place-based approach
Strategic spatial (planning) measures
EU opportunities
Experiences of the project
What are the main experiences of the project with regard to integrating the policy
context and the territorial dimensions in the analysis?
– Policy dimensions
• human mobility as a key dimension of territorial cohesion; attraction policies as
part of the EU territorial toolkit
• Policy-drive of the analysis
• Interrogating policy in exemplary regions
• Involving policy stakeholders in our discussions
– Territorial dimensions
• Regional dimension – main focus of the analysis
• Local / national dimension – explored through case studies
• EU dimension – addressed in our “scenario” analysis
How can this be further strengthened?
• Better data at LUZ level
• More resources for qualitative research à la URBACT
• “Zoom in” specific regions – e.g. tourist regions, transition regions, border
regions, etc.
THANKS FOR YOUR ATTENTION!
[email protected]
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