Transcript WP6_Halle_meeting_fin

Maciej Smętkowski
WP6 Territorial dimension of EU integration as
challenges for Cohesion policy
GRINCOH meeting, Halle
22th-23th November 2012
TASK 1 Harmonized socio-economic regional database for
the NUTS3 regions
•
1.1. Basic indicators (core analysis 2000-2008 – similar GDP growth trajectories)
- Population (1995-2011)
- GDP (1995-2009)
- Unemployment rate (LFS) (1999-2010)
•
1.2. Thematic indicators (data available: 2002;2006  extension planned 2008-2010)
- Structure of economy (GVA, Employment)
- Labour market (employment rate, long-term unemployment, micro-firms)
- FDIs (companies with foreign shareholdings)
- R&D (outlays and personnel)
- Human capital (higher education attainment, number of students)
- Basic infrastructure (population using sewerage network)
- Tourism (number of accommodated tourist)
•
1.3. Long-term comparisons (70-ties, 80-ties, 90-ties) – GDP per capita with focus on
regional convergence trend (source country experts, partners)
•
Remark (1): we propose transfer of Partners PM to Task3 case studies: ASE (1PM), IBS (0,5
PM), UEF (2PM)
Remark (2): other thematic indicators might be used depending on data availability by
partners (please indicate)
•
GDP trajectories and GDP per capita differences
Fig. Real GDP growth
[1989=100]
Remark (1): different time
frame for certain analysis
Solution: 2 sub-periods
- pre-crisis fast growth
2000/2002-2007/2008
- post-crisis 2008-2010/2011)
25000
Fig. GDP per capita 2005
[EUR, PPS]
20000
15000
EUR per capita
PPS per capita
10000
5000
0
Słowenia Czechy
Węgry
Estonia Słowacja Polska
Litwa
Łotwa
Rumunia Bułgaria
Remark (2): different stages of
development strongly affect
regional characteristics and
trends
Solution: Indicators relativised
by national average
TASK 2 Quantitative analyses of the socio-economic
indicators for NUTS3 regions in the CEECs
• 2.1. Regional Convergence Analysis at NUTS3 level
- cartographic methods, sigma, beta convergence
• 2.2. Spatial context of economic growth
- spatial auto-correlations
• 2.3. Economic growth factors – exploratory analysis
- correlations and regression analysis
•
Remark (1): we propose transfer of Partners PM to Task 6 case studies UEF (3PM)
•
Remark (2): division of work with WP1 task 3  different territorial scales: WP1 (NUTS2) –
broader set of indicators; WP6 (NUTS3) limited set of indicators?
TASK 2.1. Regional growth dynamics 2000-2008 (example)
Fig. GDP real growth
(country average=100)
Fig. GDP real growth vs. GDP per capita
(country average=100)
2000-2008
GDP
real growth
Zmiana
GDPPoziom
per capita
< 95
> 105
95-105
< 95
95-105
> 105
Indicator
Real values
(EUR; %)
Relativised values
(each country = 100)
1
2
GDP per capita 1998
0.8281**
-0.0035
GDP per capita 2005
0.6364**
0.0171
GDP growth in years 1998-2005
3
0.1723**
0.0729*
GDP growth in years 1998-2005 vs.
GDP per capita 1998
4
-0.0402
0.0369
5
Relativised values (N=179)
Task 2.2. Spatial
autocorrelation
1998-2005 (example)
• decreasing concentration
of separated highly and
less developed areas (1),
• polycentric spatial
structure (2),
• spatial concentration of
GDP growth (3),
• lack of neighbouring
regions level of
development impact
on GDP growth (4),
but country context
important (5).
HH – fast growth, highly developed neighbouring regions
HL – fast growth, less developed neighbouring regions
LH – slow growth, highly developed neighbouring regions
LL – slow growth, less developed neighbouring regions
TASK 2.3. Economic growth factors – exploratory analysis
2002-2006 (example)
Table. 1. K-Pearson correlations between GDP per capita change 2002-2006 (relativised by country
average) and state and change of selected variables (relativised by country average) (NUTS3 regions)*
Independent variables – (part 1)
Year
2002
GDP per capita
Employment – agriculture (%)
Employment – industry (%)
Employment market services (%)
0.25
-0.25
0.41
Employment non-market services (%)
GVA – agriculture (%)
GVA – industry (%)
GVA – market services (%)
GVA – non-market services (%)
Productivity – agriculture (%)
Productivity – industry (%)
Productivity – market services (%)
Productivity – non-market services(%)
-0.26
0.25
-0.20
0.38
Change Independent iariables – (part 2)
20022006
x
Employment rate
-0.21 Unemployment rate
Long-term unemployed (%)
Natural person conducting
business activity per 1000 inhab.
-0.25 Private investments outlays per
capita
-0.19 Number of companies with
foreign shareholdings per 1000
inhab.
R&D expenditures per capita
-0.19 R&D employment (%)
-0.66 Number of students per 1000
inhab.
Population using water-line (%)
0.39 Population using sewerage (%)
0.37 Number of accommodated tourist
per 1000 inhab.
0.34 Migration balance
* significance level 5%; values over 0.30 in bold
Source: own calculation based on Eurostat data and EUROREG database.
Year
2002
0.31
-0.27
Change
20022006
-0.19
0.35
0.26
0.22
0.26
0.27
0.22
0.28
0.22
0.20
TASK 3 In-depth comparative analysis of specific
territorial cases
• 3.1. Typology of regions based on principal component analysis
• 3.2. Thematic analyses
- successful restructuring
- border location hindering development processes
- cumulation of social problems
• 3.3. Selection of case studies at NUTS3 level
- thematic analyses supported by typology of regions
• 3.4. Case study report
•
Remark (1): selection of case study based on thematic analysis verified by regional
typology and analysis of relativised GDP growth
•
Remark (2): analysis of metropolitan areas to be coverd by Task 6
Regional typology
(2002-2006) (draft)
Principal components of regional
differentiation in CEECs:
a) Metropolisation
b) Industrialisation
c) Urbanisation (market services)
d) Dependency (agriculture and public
services)
TASK 3.2.1. Successful restructuring
Tab. Extreme cases in particular countries:
a) industry progress 2002-2008 (increase of share in employment or GVA)
b) GDP dynamics 2002-2008 higher than country average
Country
Estonia
Latvia
Romania
Czechy
Slovakia
NUTS3 region GDP per capita change
Share of industry 2002
(contry average=100)
[pp]
Employment
GVA
Põhja-Eesti
2,9
20,8
Pieriga
11,8
16,1
Timis
13,1
27,7
Jihomoravský
2,5
28,0
kraj
Trnavský kraj
14,9
30,3
Hungary
KomáromEsztergom
Latvia
Zemgale
Slovenia
Jugovzhodna
Slovenija
Czechy
Moravskoslez
ský kraj
Hungary BorsodAbaújZemplén
Poland
LegnickoGlogowski
Poland
Ciechanowsk
o-plocki
Lithuania Telsiu
apskritis)
Slovakia Zilinský kraj
Bułgaria Pazardzhik
Romania Alba
17,8
26,2
31,3
28,7
Change of industry share
2002-2008
Employment
GVA
0,2
0,6
7,9
0,5
36,5
0,6
General characteristic
-2,3
-4,8
0,9
1,1
Capital region
Metropolitan area
Large city region
Large city region
13,5
37,8
42,9
10,2
3,9
16,1
26,2
1,3
0,4
37,6
40,9
-1,1
6,9
35,6
38,4
-1,9
7,4 Metropolitan
macroregion
11,5 Metropolitan
macroregion/Old
industrial region
-4,8 Metropolitan
macroregion
1,6 Metropolitan
macroregion
4,7 Old industrial region
0,8
29,1
32,7
-3,4
0,8 Old industrial region
31,2
30,2
37,8
3,8
15,8 Raw materials industry
16,5
15,2
23,7
6,2
0,5
23,2
36,9
1,2
9,7 Raw materials industry
wy
-4,7 Raw materials industry
5,4
2,5
9,6
30,4
25,5
34,3
29,8
21,5
32,8
-0,8
2,7
-2,1
0,7 Transport corridor
15,5 Transport corridor
2,9 Other
TASK 3.2.2. Border location hindering economic growth
Extreme cases selection:
a) different types of macroregion’s external borders
b) low GDP dynamics in comparison to country average –
different periods
Remark (1): capital city regions excluded
Remark (2): focus on Western and Eastern border
TASK 3.2.3. Social problems
Tab. Extreme cases in particular countries:
a) high unemployment rate based on Labour Force Survey (LFS)
b) sorted by countries (2 extreme cases)
TASK 3.3. Case studies selection
According to the regional typology elaborated for 2002-2006:
• successful restructuring (old industrial region, industrial-agricultural,
service/industrial)
• border location (public service and productive agriculture, agriculture
weakly industrialised, agricultural insignificant market service)
• social problems (agricultural insignificant market service, other, public
service and productive agriculture)
Remark (1): some of selected cases cover more than one thematic field
TASK 3.4. Case study report - general structure
1. General ddescription (processes, SWOT analysis etc.)
2. Post-transformation development trajectory (WP1)
3. Development factors (exogenous, endogenous, others) (WP2 & WP3)
4. Labour market situation and social problems (WP4 & WP5)
5. Governance – institutional settings, strategies, instruments (WP7)
6. Cohesion policy impact (WP8)
Methods:
1. In-depth interviews (ca. 10-15) (city office, regional authorities, RDAs,
chambers of commerce, business associations, higher education
institutions, labour market & social services, implementing authorities,
others)
2. Desk research (statistical data, strategic documents, other)
Remark (1): Direct coordination with other WPs (esp. WP8)
Remark (2): Any particular nedes for your research?
TASK 6 Metropolis and its region – a challenge for
territorial cohesion
•
6.1. Statistical analysis at macroregional level
- intraregional gap in economic development level
- factors underpinning the intraregional disparities (economic structure, labour market,
demography, human capital, R&D) – expanded in comparison to previous research
•
6.2. Case studies focused on capital city macroregions (general structure)
- (1) metropolises as nodes in global space of flows
- (2) regional hinterland – resource based development
- (3) metropolis-region relationship – quantitative analysis on settlement structure and
labour commuting
- (4) metropolis-region relationship – qualitative analysis – in-depth interviews in metropolis
as well as in 2 specific locations in regional hinterland that represent both local success
& local failure (ca. 20 interviews in total)
- (5) assessment of public policy (sectoral, horizontal and regional) in the context of cityregion relationship (desk research and in-depth interviews)
•
Remark (1): Selection of case studies based on partners competences: Warsaw (PL)
EUROREG, Prague (CZ) EPRC, Budapest (HU) UEF, Tallinn (EST) IBS, Bucharest (RO)
ASE
Remark (2): we proposer transfer 2 PM EPRC to Task 5
•
•
WP 6 Task 4 Assessment of
infrastructure construction, its role in
regional development
Two general aims of infrastructure construction:
–
–
•
•
•
List of the major transport investment (EU supported and others, CEEC and
neighbouring counties, including regions outside UE)
2000-2006-2012 dynamic analysis
Infrastructure as the factor of metropolitan areas development
–
–
–
•
•
Data base for 30 metropolitan areas (MEGA’s of ESPON 1.1.1) and selected
secondary growth poles
Mutual relation analysis (between neighbouring MEGA’s): infrastructure
investment, connectivity, daily accessibility (road and rail)
Correlation/regression analysis (infrastructure development and accessibility
versus economic growth of selected MEGA’s)
Infrastructure as the factor of peripheral areas development
–
•
To support the growth of metropolitan areas and city networking (including
bottleneck elimination)
To improve the accessibility of the weakest (peripheral) regions
Changes of the accessibility indicators
Sources – results of ESPON 1.2.1 and ESPON TRACC projects, Eurostat
data, national statistics, information collected by Project partners.
Questions to partners: to what extent these goals are being achieved?
Examples of most and least successful examples?
WP6 – timeline/deadlines
• General quantitative analysis (June 2013 -14M) – BUDAPEST
CONFERENCE (D7)
• Elaboration of tools and report templates T3/T6 (June 2013 – 14M)
• Draft case study reports (December 2013 – 20M)
• Policy options as input to WP9 (EUROREG and other WP partners),
(March 2013 - 24M)
• Final case study reports and draft report of WP6 (April 2014 – 24M)
• Final report of WP6 (October 2014 -30M – D29) – LJUBLJANA
CONFERENCE (D17)
Remark (1): Tools and templates elaboration (a) partner inputs/request/comments
expected by December 2012, (b) draft tools and templates will be distributed for comments in
February 2013, (c) final comments from partners in March 2013, (d) final tools to be tested
April 2013, (e) final versions of tolls/templates available June 2013