Transcript scenario

ERSA-DGRegio lectures
Bruxelles, 8 April 2016
Territorial scenarios for Europe:
future alternative growth strategies
Roberta Capello
In cooperation with Roberto Camagni, Andrea Caragliu, Ugo Fratesi
Politecnico di Milano and Past President of RSAI
Objectives of the presentation
To present scenarios for European territory in the future (2030) under
alternative assumptions on specific driving forces of change.
Scenarios have been built in the ESPON ET2050 project and in the FP7
GRINCOH project.
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The foresight tool: the MASST-3 model
Scenarios are based on the MASST model
MASST is an econometric forecasting model. Previous versions of MASST
developed for ESPON 3.2 (2004-5); ESPON SPAN (2010-11); DGRegio
projects.
The model is able to simulate effects on regional growth of:
- the economic crisis;
- macroeconomic elements (public budget constraints, sovereign debt,
spread in interest rates on public bonds, exchange rates);
- territorial capital (innovativeness, trust, agglomeration economies, HC);
- cohesion and infrastructure policies.
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Methodology for building scenarios: a sketch
The methodology for building scenarios is made on the following steps:
• starting from a ‘seminal idea’ about the driving forces believed to
characterize future economic-territorial development
(assumptions),
• the basic characteristics of a scenario are built, together with the
relevant conditional elements, the most likely bifurcations in the
driving forces (qualitative assumptions);
• these conditional elements are plugged into the econometric
model, as assumed values of the independent variables of the
model (quantitative assumptions: levers of the model);
• identifying the magnitude of the most likely effects on European
regions through a simulation procedure (scenarios).
The simulation period runs from 2013 through 2030.
Conditional elements: integrated scenarios
A scenario is an integrated vision of the different driving forces that are
expected to have effects on future trajectories. Therefore:
- individual driving forces must be related to each other, and cross feedback effects must be underlined, i.e. the assumptions have to be highly
consistent: this overall coherence has to be reflected in the label given
to the scenario;
- one has to assume an “if.... then..” logic, keeping assumptions
carefully separated from effects;
- the assumptions on the driving forces should be as differentiated as
possible, sometimes even opposite to each other, so as to yield
differentiated images.
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Assumptions of the Baseline Scenario (2030)
- the socio-economic and demographic trends of the past will continue,
-
-
and no major change (beyond the crisis) will alter the EU economy;
economic policies will remain the present ones (stable budget for SFs);
a general slow economic recovery will start in 2016;
a slight increase in competitiveness of European countries is assumed in
2030;
interest rates on bonds will return back to lower, pre-crisis values, thanks
to the end of strong financial speculation;
the stability pact remains the same, imposing highly restrictive fiscal
policies.
n.b. These assumptions were agreed in December 2011, and revisited after
Draghi’s interventions in July/September 2012, which stopped the
speculations on the euro. The final conditional quantitative foresights
have been run in early 2013.
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RESULTS FOR THE
BASELINE SCENARIO
(2030)
Aggregate results of the Baseline scenario
Average
Average annual
annual GDP
population
growth rate
growth rate
Average annual
employment
growth rate
Average annual
manufacturing
employment
growth rate
Average annual
service
employment
growth rate
EU27
1.89
0.31
1.58
1.38
1.63
Old 15
1.88
0.47
1.53
1.48
1.54
New 12
1.93
-0.38
1.90
0.98
2.33
1. The New12 countries grow a little more than the Western countries.
2. New12 countries increase employment in services more than in manufacturing,
entering a new stage of development.
3. Western countries show a balanced growth between manufacturing and services.
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Baseline: annual average GDP growth rate
Two speed Europe; Southern peripheral
countries grow less than Northern
countries.
Reykjavik
!
Canarias
Baseline March 18 2013
Average regional GDP growth rate
< 0.00
0.01 - 0.90
0.91 - 1.24
1.25 - 1.49
1.50 - 1.78
1.79 - 2.09
2.10 - 2.47
2.48 - 2.94
> 2.95
Guadeloupe
Réunion
Martinique
Southern European countries discount
the difficult present conditions on their
future evolutionary trajectories.
Helsinki
!
Oslo
!
Guyane
Tallinn
!
Stockholm
!
Madeira
Riga
!
København
!
Dublin
!
Vilnius
!
Minsk
!
Acores
Amsterdam
!
London
!
Berlin
!
Eastern European countries still grow
more than the EU 15, but this is not
enough to catch up the GDP per capita
levels of the Western countries in 2030.
Warszawa
!
Kyiv
!
Bruxelles/Brussel
!
Praha
!
Luxembourg
!
Paris
!
Bratislava
Wien
!
!
Bern
!
Kishinev
!
Budapest
!
Vaduz
!
Ljubljana
!
Zagreb
!
Bucuresti
!
Beograd
!
Sarajevo
!
Sofiya
!
Podgorica
!
Madrid
!
Roma
!
Lisboa
!
Skopje
!
Ankara
!
Tirana
!
Overall intra-national regional disparities
increase.
Athinai
!
El-Jazair
!
Ar Ribat
!
Nicosia
!
Tounis
!
Valletta
!
© Politecnico di Milano, Project ET2050, 2013
0
250
500
km
Regional level: NUTS2
Source: Politecnico di Milano, 2013
Origin of data: - MASST3 model
© EuroGeographics Association for administrative boundaries
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Theil index in the Baseline scenario (2030)
0.160
0.140
Total regional disparities
0.120
0.100
Inter-national disparities
0.080
Intra-national disparities
0.060
0.040
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Total Theil Index
Between Countries Theil Index
Within Countries Theil Index
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EXPLORATORY SCENARIOS
(2030)
Summary of assumptions for the exploratory
scenarios
“Megas” scenario
Market driven scenario; welfare system fully privatized; financial debt
repaid in 2030; budget reduced for cohesion policies; concentration of
investments in European large cities.
“Cities” scenario
Public policies mostly at national level; actual welfare system reinforced
through increased taxation; financial debt fully repaid in 2050; budget
maintained for cohesion policies; concentration of investments in
second rank cities.
“Regions” scenario
Social policies; strong public welfare system paid through debts; financial
debt not repaid in 2050; budget significantly increased for cohesion
policies; concentration of investments in rural and cohesion areas.
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Aggregate GDP growth results for the exploratory
scenarios
Aggregates Baseline Megas Cities Regions Megas vs. baseline Cities vs. Baseline Regions vs. Baseline
EU27
1.89
2.22
2.31
1.82
0.33
0.42
-0.06
old15
1.88
2.22
2.31
1.81
0.34
0.43
-0.07
new12
1.93
2.22
2.23
1.98
0.29
0.30
0.05
1. The “Cities scenario” is the most expansionary: territorial capital and
the urban system are better exploited than in the other scenarios.
2. This holds also for New 12 countries, even if to a more limited degree
3. New 12 countries are those that gain in the regions scenario with
respect to the baseline.
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GDP growth rates in the Megas scenario:
differences with respect to the baseline
Reykjavik
!
Canarias
Megas March 18 2013
Average regional GDP growth rate, difference w.r.t. baseline
< 0.00
0.01 - 0.12
0.13 - 0.20
0.21 - 0.26
0.27 - 0.31
0.32 - 0.37
0.38 - 0.42
0.43 - 0.49
> 0.50
Guadeloupe
Réunion
Martinique
Helsinki
!
Oslo
!
Guyane
Tallinn
!
Stockholm
!
Madeira
Riga
!
København
!
Dublin
!
Vilnius
!
Minsk
!
Acores
Amsterdam
!
London
!
Berlin
!
Warszawa
!
Kyiv
!
Bruxelles/Brussel
!
In Western countries:
- strong advantages to rich and
central regions;
- rural areas of rich regions
gain relatively less;
- relatively poor countries (like
Greece) take advantage of a
general increase in demand.
Praha
!
Luxembourg
!
Paris
!
Bratislava
Wien
!
!
Bern
!
Kishinev
!
Budapest
!
Vaduz
!
In Eastern countries:
- relatively more diffused
growth, thanks to a general
recovery of the EU economy.
Ljubljana
!
Zagreb
!
Bucuresti
!
Beograd
!
Sarajevo
!
Sofiya
!
Podgorica
!
Madrid
!
Roma
!
Lisboa
!
Skopje
!
Ankara
!
Tirana
!
Athinai
!
El-Jazair
!
Ar Ribat
!
Nicosia
!
Tounis
!
Valletta
!
© Politecnico di Milano, Project ET2050, 2013
0
250
500
km
Regional level: NUTS2
Source: Politecnico di Milano, 2013
Origin of data: - MASST3 model
© EuroGeographics Association for administrative boundaries
GDP growth rates in the Cities scenario:
differences with respect to the baseline
Reykjavik
!
Canarias
Cities March 18 2013
Average regional GDP growth rate, difference w.r.t. baseline
< 0.00
0.01 - 0.20
0.21 - 0.26
0.27 - 0.33
0.34 - 0.39
0.40 - 0.45
0.46 - 0.51
0.52 - 0.59
> 0.60
Guadeloupe
Réunion
Martinique
Helsinki
!
Oslo
!
Guyane
Tallinn
!
Stockholm
!
Madeira
Riga
!
København
!
Dublin
!
Vilnius
!
Minsk
!
Acores
Amsterdam
!
London
!
Berlin
!
Warszawa
!
In Western countries:
- more widespread and
diffused growth at
intranational level;
- strong countries like Germany,
the Netherlands, Austria,
increase less than Southern
countries (catching-up).
Kyiv
!
Bruxelles/Brussel
!
Praha
!
Luxembourg
!
Paris
!
Bratislava
Wien
!
!
Bern
!
Kishinev
!
Budapest
!
Vaduz
!
Ljubljana
!
Zagreb
!
Bucuresti
!
Beograd
!
Sarajevo
!
Sofiya
!
Podgorica
!
Madrid
!
Roma
!
Lisboa
!
Skopje
!
Ankara
!
Tirana
!
Athinai
!
El-Jazair
!
Ar Ribat
!
Nicosia
!
Tounis
!
Valletta
!
© Politecnico di Milano, Project ET2050, 2013
0
250
500
km
Regional level: NUTS2
Source: Politecnico di Milano, 2013
Origin of data: - MASST3 model
© EuroGeographics Association for administrative boundaries
In Eastern countries:
- diffused advantages, relatively
less pronounced than in
Western;
- similar increase in growth than
in the megas scenario.
GDP growth rates in the Regions scenario:
differences with respect to the baseline
Central/core regions grow less
than in the baseline scenario.
Reykjavik
!
Canarias
Regions March 18 2013
Average regional GDP growth rate, difference w.r.t. baseline
< -0.22
-0.21 - -0.17
-0.16 - -0.11
-0.10 - -0.06
-0.05 - 0.00
0.01 - 0.11
0.12 - 0.22
0.23 - 0.42
> 0.43
Guadeloupe
Réunion
Martinique
Rural or peripheral areas gain
relatively more than in the
baseline scenario.
Helsinki
!
Oslo
!
Guyane
Tallinn
!
Stockholm
!
Madeira
Riga
!
København
!
Dublin
!
Vilnius
!
Minsk
!
Acores
Amsterdam
!
London
!
Berlin
!
This holds for both Western
and Eastern countries.
Warszawa
!
Kyiv
!
Bruxelles/Brussel
!
Praha
!
Luxembourg
!
Paris
!
Bratislava
Wien
!
!
Bern
!
Kishinev
!
Budapest
!
Vaduz
!
Ljubljana
!
Zagreb
!
Bucuresti
!
Beograd
!
Sarajevo
!
Sofiya
!
Podgorica
!
Madrid
!
Roma
!
Lisboa
!
Skopje
!
Ankara
!
Tirana
!
Athinai
!
El-Jazair
!
Ar Ribat
!
Nicosia
!
Tounis
!
Valletta
!
© Politecnico di Milano, Project ET2050, 2013
0
250
500
km
Regional level: NUTS2
Source: Politecnico di Milano, 2013
Origin of data: - MASST3 model
© EuroGeographics Association for administrative boundaries
Theil Index by Scenario: Total Regional Disparities
0.155
0.150
Ba seline scena rio
Mega s scena rio
Cities scena rio
0.145
Regions scena rio
0.140
0.135
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
The “Cities” scenario is also the most cohesive! (disparities
increase less)
Theil Index by Scenario: Between Country
Disparities
0.098
0.096
0.094
0.092
Ba seline scena rio
Mega s scena rio
Cities scena rio
0.090
Regions Scena rio
0.088
0.086
0.084
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
The “Cities” scenario is the most cohesive! (disparities shrink
more)
Theil Index by Scenario: Inside Country Disparities
0.065
0.060
0.055
Ba seline scena rio
Mega s scena rio
Cities scena rio
Regions scena rio
0.050
0.045
0.040
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
In this case, the “Regions” scenario is the most cohesive (et pour
cause!)
Conclusions: Designing new cohesion policy:
competitiveness vs. cohesion?
The (supposed) trade-off between two goals, efficiency and
equity, has always characterized the European policy
debate and the suggested strategies:
- a “competitiveness” strategy, favoring highest returns on
investments on core areas, the “champions”, so to
achieve higher aggregate growth rates and obtain higher
fiscal revenues on which redistributive policies can rely;
vs.
- a “cohesion” strategy oriented towards the support of
weaker and peripheral regions, favoring equity rather than
competitiveness goals.
Competitiveness vs. cohesion:
beyond the trade-off (1)
Recently the very existence of this efficiency/equity
trade-off was questioned (OECD, 2001; Camagni, 2001;
Camagni, Capello, 2015) emphasizing:
- the aggregate development effects of sound spatial
development policies (wider utilization of territorial
capital), on the one hand, and
- the economic and social costs of a spatially
concentrated development process on the other
(inflationary pressures in particular).
Our impression is that the trade-off idea appears as a
misleading, short-term (and old) approach to territorial
policies.
Competitiveness vs. cohesion:
beyond the trade-off (2)
Modern territorial development policies should be designed so
as to maximize the returns to public investments (“do more
with less”).
This goal is achieved through the capability of single policies to:
- intervene bottom-up through local actors, depositaries of
relevant local information;
-act on the specificities of each single area,
- push local actors to “tap” and mobilize previously
“untapped” assets of territorial capital.
the aggregate development effects will be maximized, and
at the same time the economic and social costs of an
unbalanced development process will be kept under
control.
THANK YOU VERY MUCH FOR YOUR ATTENTION!
Roberta Capello
Department ABC - Politecnico di Milano
Piazza Leonardo da Vinci 32 - 20133 MILANO
tel: +39 02 2399.2744 - 2399.2751
fax: +39 02 2399.9477
[email protected]
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