territorial scenarios for europe with special regards to central european countries
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Territorial scenarios for Europe With special regards to Central European Countries Roberto Camagni with R. Capello, A. Caragliu , U. Fratesi Politecnico di Milano, ABC Department. Hungarian Regional Science Association , 11° Meeting Kaposvàr , 21-22 November , 2013. - PowerPoint PPT PresentationTRANSCRIPT
Territorial scenarios for EuropeWith special regards to Central European Countries
Roberto Camagniwith R. Capello, A. Caragliu, U. FratesiPolitecnico di Milano, ABC Department
Hungarian Regional Science Association, 11° MeetingKaposvàr, 21-22 November, 2013
Objectives of the presentation
To present results of some research works carried out within the ESPON Programme of the EU, namely:
- ET2050: development scenarios for European Regions (2013)- KIT: Knowledge, Innovation and Territory (2011-12)- Span: Spatial Scenarios for the Latin Arc Countries (2008-09)
To produce “quantitative foresights” (not forecasts) based on conditional scenario assumptions for all European regions up to 2030, with special reference to Central Eastern Countries
To present some early reflections on development policies
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Introduction
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Over the last few years, the world economy has gone through a severe period of economic downturn, the worst since the end of the second world war.
If the overall magnitude of the effects generated by the crisis is not yet fully understood, even less clear is the spatial distribution of these effects.
This explains the importance of the use of macroeconomic regional econometric and forecasting models.
Introduction
4
Regions belong to different nations with different exposure to the crisis.
Regions have different industrial specialization, as well as different capacities to exploit untapped resources, or territorial capital assets.
Macroeconomic demand side effects have different impacts :- on national economies, according to their different level of public debt and deficit, and development potential,- on the different regions, according to their consumption patterns, type
of demand (public vs. private) and productive specializations.
Financial speculation determined a differentiated rise in the spread on public bonds in different countries, exacerbating the cost of the debt service, raising public deficits, generating huge effects on public spending at central and local levels.
Introduction
5
A strong control on public expenditure and on its reduction was imposed by the EU, especially to “vicious” countries. The effects of such a reduction are expected to be stronger in those regions with a higher share of public demand with respect to the private one, being generally the poorer and less productive regions;- in “vicious” countries, private investments decreased as a
consequence of the increase in interest rates, penalizing private actors, and particularly productive regions;
- a credit crunch came as a consequence of the financial intermediaries’ decision to prefer financial investments on public bonds, when guarantees existed on sovereign default; the real sector and the most productive regions hosting it were once again penalized more than others.
In general though, is difficult to predict which regions were hit more.
The foresight tool: the MASST3 modelMASST is an econometric forecasting model. Previous versions of
MASST developed for ESPON 3.2; ESPON SPAN; DGRegio projects.
The ET2050 project is based on a new version of MASST, considering the economic crisis (two periods of model estimation), public budget constraints, innovation modes, the role of urban areas in regional growth.
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 of public bonds, exchange rates);- territorial capital elements (innovativeness, trust, accessibility);- cohesion and infastructure policies.
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The model
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The logics of the model is at the same time Top-down & Bottom-up (i.e. distributive and generative):
- national growth (determined by macro-economic elements: demand side) is distributed among regions,
- but regions add a “differential” effect (determined by presence of territorial capital: supply side) able to feed-back on national performance.
Quantitative foresight is produced for all NUTS2 regions of all 27 EU countries (270 regions).
The MASST3 model:
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Policies: Structural funds
Accessibility: - infrastructure
FDIs/Population
Functions
Spatial and territorial structure: - spatial
spillovers
Sectoral component: Dynamics of
sectoral structure
in national GDP
Exchange rates
Inflation
Δ of FDI stock
Submodel 1: National component Submodel 2: Regional differential component
Macroeconomic elements
Differential shift
Regional differential component
Territorial capital assets
Spatial and territorial structure: - spatial spillovers
National growth
Regional growth as a result of MAcroeconomic Social, Sectoral and Territorial components
Final economic effect
Population growth
Migration flows
Birth rate
Mortality rate
Sectoral component: dynamics of sectoral structure
Localization economies: Hirschman Herfindahl Index
Legend:
Exogenous variables
Endogenous variables
Relations in estimations Relations in simulation
National component of regional
growth
Social component: - trust
Urbanization economies: LUZ population
Regional specialization
Functions
MIX effects
Territorial structure: settlement
Policies: Structural funds
Dynamics of sectoral structure
FDIs/Population
Human capital
R&D
Innovation
patterns
Regional innovation
Traditional urban benefits: - quality of life - creativity
Traditional urban costs: - cost of the city - social conflict
Nonconventional urban benefits: - city networks - high level urban functions
Nonconventional urban costs: - diffused urban form
Urbanization economies (LUZ population)
Innovativeness: - product/ process innovation
Inter-sectoral productivity: - infrastructure - skills - energy cons.
All equations are differentiated between periods of crisis and of no crisis Permanent income and long-run relationships are assumed and estimated
FINAL OUTCOME
internal consumption
investments
imports
exports
Δ public
expenditure Δ public expenditure
Public exp'enditure
Interest payments
Tax revenues
exports
Δ Exchange rates
Inflation
Δ Unit Labour Costs
GDP growth in USA, Japan and
BRICs
Unemployment growth internal
consumption
Tax rates
investments
Δ interest rates
Δ Unit Labour Costs
Δ of FDI stock
in national GDP
in national GDP
in national GDP
imports
Migration Flows
Settlement structure
Regional differential GDP
Unemployment rate
Scenario Assumptions
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a) structural breaks brought in by the crisis are considered, due to emerging global contradictions:
- Stop to demand based on debt in advanced countries,- Financialization of western economies and related risks,- China and BRICs supporting western real income (through low-price
exports) and financing the trade deficit of USA : persisting?
By consequence, in the future:- the balance of the geo-political game will be different;- winning assets will be different;- spread in interest rates proportional to sovereign debts;- necessary (but probably too high) austerity measures imposed on
public deficits by the EU.
Scenario Assumptions
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b) “Regionalized” globalization, with the large “triad” areas (Europe, America, East and South Asia) more independent and more internally integrated- BRICs enter progressively in the medium and high technology game- The growth of real income in Europe will be more modest;- “Regionalized” globalization processes will enable the recovery of manufacturing activities in Europe (and the US);- A number of new technologies will develop: nanotech, biotech,
transport technologies, new materials
c) More importantly: a new paradigm will emerge: the “green economy”, due to increasing energy prices and growing concern about climate change. Many sectors touched: manufacturing, energy, transport, building and construction, tourism, agriculture (zero-km)Provides a new demand source, new jobs and a reduction in dependency on fossil fuelsIt may boost a revival of endogenous growth in Europe
Scenario Assumptionsd) Regional disparities are likely to increase (two speed growth)- Metro regions will host the advanced activities and R&D- New manufacturing activities, benefiting from technological
progress, will also locate in metro and second rank cities
e) Austerity measures will endanger growth in “vicious” , mainly southern European countries: for some times, “internal devaluations”, severe cuts in public spending and difficulties in financing private investments will determine a cumulative divergence with respect to stronger countries.
All these elements can be easily accomodated into the MASST model, thanks to the new inclusion of sectoral regional structures and constraints coming from national sovereign debt and public budget disequilibria.
Scenario Assumptions
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Concerning Central - Eastern European Countries:
i) Catching up in productivity with respect to Old 15 Countries will continue, but possibly at a lower rate due to:
- FDI dependency: they will slowly redirect towards outer eastern countries and towards trade and commercial functions, in order to benefit from increasing internal incomes (in CEECs),
- Difficulty in keeping low levels of inflation, due to difficulty in keeping wage increases in line with productivity increases,
- Outflows of profits by multinational companies,- Slow taking-off of an endogenous accumulation of capital.
ii) Difficulty in finding a more advanced innovation “pattern” with respect to the present one (mainly an “imitative innovation pattern”, driven by FDI, with an internal dualist industrial structure).
Past trends in productivity
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40.0
50.0
60.0
70.0
80.0
90.0
100.0
110.0
120.0
130.0
140.0
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Productivity per employee (2005=100)
European Union (27 countries)
Bulgaria
Czech Republic
Estonia
Croatia
Cyprus
Latvia
Lithuania
Hungary
Malta
Poland
Romania
Slovenia
Slovakia
Past trends in FDI inflows (absolute values)
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0
1000000
2000000
3000000
4000000
5000000
6000000
7000000
8000000
9000000
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Tot
al F
DI
infl
ows i
n cu
rren
t USD
(m
illio
ns)
European Union
Old15
NMS
Past trends in FDI (% on GDP)
15
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
140.00%
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
FDI i
nflo
ws a
s a
% o
f GD
P
European Union
Old15
NMS
NMS
EU27
Old15
Trends in competitiveness
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40.00
60.00
80.00
100.00
120.00
140.00
160.00
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Bulgaria Czech Republic Estonia
Croatia Latvia Lithuania
Hungary Poland Romania
Slovenia Slovakia Equal relative competitiveness as in 2004
Slovakia
Czech Republic
Poland
Hungary
Real Effective Exchange rates for the NMS, 1994-2012
Assumptions of the Baseline Scenario
- the socio-economic and demographic trends of the past will continue, and no major change will come to alter the EU economy;
- economic policies will remain the present ones;- a general slow economic recovery will start in 2016;- a slight increase in competitiveness of European countries is assumed
in 2030;- By 2030 interest rates on bonds will return back to lower, pre-crisis
values, thanks to the end of strong speculation;- the stability pact remains the same, still imposing highly restrictive
public budget policies.
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RESULTS FOR THE BASELINE SCENARIO
(2030)
Aggregate results of the Baseline scenario
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Average annual GDP growth rate
Average annual population growth rate
Average annual employment growth rate
Average annualmanufacturing
employmentgrowth rate
Average annual service
employment growth rate
EU27 1.89 0.31 1.58 1.38 1.63Old 15 1.88 0.47 1.53 1.48 1.54New 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 have a balanced growth between manufacturing and services.
Baseline: annual average GDP growth rate
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Two speed Europe; Southern peripheral countries grow less than Northern countries.
Southern European countries discount the difficult present conditions on their future evolutionary trajectories.
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.
Overall intra-national regional disparities increase.
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Roma
Riga
Oslo
Bern
Wien
Kyiv
Vaduz
ParisPraha
Minsk
Tounis
Lisboa
Skopje
Zagreb
Ankara
Madrid
Tirana
Sofiya
London Berlin
Dublin
Athinai
Tallinn
Nicosia
Beograd
Vilnius
Ar Ribat
Kishinev
Sarajevo
Helsinki
Budapest
Warszawa
Podgorica
El-Jazair
Ljubljana
Stockholm
Reykjavik
København
Bucuresti
Amsterdam
Bratislava
Luxembourg
Bruxelles/Brussel
Valletta
Acores
Guyane
Madeira
Réunion
Canarias
MartiniqueGuadeloupe
0 500250km
Baseline March 18 2013Average regional GDP growth rate
< 0.000.01 - 0.900.91 - 1.241.25 - 1.491.50 - 1.781.79 - 2.092.10 - 2.472.48 - 2.94> 2.95
Regional level: NUTS2Source: Politecnico di Milano, 2013
Origin of data: - MASST3 model© EuroGeographics Association for administrative boundaries
© Politecnico di Milano, Project ET2050, 2013
Theil index in the Baseline scenario
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.05
.1.1
5
2010 2015 2020 2025 2030Year
Total Theil index Between Country Theil indexWithin Country Theil index
Total regional disparities
Inter-national disparities
Intra-national disparities
EXPLORATORY SCENARIOS(2030)
Summary of assumptions for the exploratory scenarios
“Megas” scenarioMarket driven scenario; welfare system fully privatized; financial debt repaid in
2030; budget reduced for cohesion policies; concentration of investments in European large cities.
“Cities” scenarioPublic policies mostly at national level; actual welfare system reinforced through
increased taxation; financial debt not fully repaid in 2050; budget maintained for cohesion policies; concentration of investments in second rank cities.
“Regions” scenarioSocial policies; strong public welfare system; financial debt 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
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.
3. New 12 countries are those that gain in the regions scenario with respect to the baseline.
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
0.135
0.140
0.145
0.150
0.155
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Baseline scenario
Megas scenario
Cities scenario
Regions scenario
Theil Index by Scenario: Total Regional Disparities
Theil Index by Scenario: Between Countries Disparities
0.084
0.086
0.088
0.090
0.092
0.094
0.096
0.098
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Baseline scenario
Megas scenario
Cities scenario
Regions Scenario
Theil Index by Scenario: Inside Countries Disparities
0.040
0.045
0.050
0.055
0.060
0.065
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Baseline scenario
Megas scenario
Cities scenario
Regions scenario
GDP growth rates in the Megas scenario: differences with respect to the baseline
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.
In Eastern countries:- relatively more diffused growth, thanks to a general recovery of the EU economy.
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Roma
Riga
Oslo
Bern
Wien
Kyiv
Vaduz
ParisPraha
Minsk
Tounis
Lisboa
Skopje
Zagreb
Ankara
Madrid
Tirana
Sofiya
London Berlin
Dublin
Athinai
Tallinn
Nicosia
Beograd
Vilnius
Ar Ribat
Kishinev
Sarajevo
Helsinki
Budapest
Warszawa
Podgorica
El-Jazair
Ljubljana
Stockholm
Reykjavik
København
Bucuresti
Amsterdam
Bratislava
Luxembourg
Bruxelles/Brussel
Valletta
Acores
Guyane
Madeira
Réunion
Canarias
MartiniqueGuadeloupe
0 500250km
Megas March 18 2013Average regional GDP growth rate, difference w.r.t. baseline
< 0.000.01 - 0.120.13 - 0.200.21 - 0.260.27 - 0.310.32 - 0.370.38 - 0.420.43 - 0.49> 0.50
Regional level: NUTS2Source: Politecnico di Milano, 2013
Origin of data: - MASST3 model© EuroGeographics Association for administrative boundaries
© Politecnico di Milano, Project ET2050, 2013
GDP growth rates in the Cities scenario: differences with respect to the baseline
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).
In Eastern countries:- diffused advantages, relatively
less pronounced than in Western;
- similar increase in growth than in the megas scenario.
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Roma
Riga
Oslo
Bern
Wien
Kyiv
Vaduz
ParisPraha
Minsk
Tounis
Lisboa
Skopje
Zagreb
Ankara
Madrid
Tirana
Sofiya
London Berlin
Dublin
Athinai
Tallinn
Nicosia
Beograd
Vilnius
Ar Ribat
Kishinev
Sarajevo
Helsinki
Budapest
Warszawa
Podgorica
El-Jazair
Ljubljana
Stockholm
Reykjavik
København
Bucuresti
Amsterdam
Bratislava
Luxembourg
Bruxelles/Brussel
Valletta
Acores
Guyane
Madeira
Réunion
Canarias
MartiniqueGuadeloupe
0 500250km
Cities March 18 2013Average regional GDP growth rate, difference w.r.t. baseline
< 0.000.01 - 0.200.21 - 0.260.27 - 0.330.34 - 0.390.40 - 0.450.46 - 0.510.52 - 0.59> 0.60
Regional level: NUTS2Source: Politecnico di Milano, 2013
Origin of data: - MASST3 model© EuroGeographics Association for administrative boundaries
© Politecnico di Milano, Project ET2050, 2013
GDP growth rates in the Regions scenario: differences with respect to the baseline
Central/core regions grow less than in the baseline scenario.
Rural or peripheral areas gain relatively more than in the baseline scenario.
This holds for both Western and Eastern countries.
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Roma
Riga
Oslo
Bern
Wien
Kyiv
Vaduz
ParisPraha
Minsk
Tounis
Lisboa
Skopje
Zagreb
Ankara
Madrid
Tirana
Sofiya
London Berlin
Dublin
Athinai
Tallinn
Nicosia
Beograd
Vilnius
Ar Ribat
Kishinev
Sarajevo
Helsinki
Budapest
Warszawa
Podgorica
El-Jazair
Ljubljana
Stockholm
Reykjavik
København
Bucuresti
Amsterdam
Bratislava
Luxembourg
Bruxelles/Brussel
Valletta
Acores
Guyane
Madeira
Réunion
Canarias
MartiniqueGuadeloupe
0 500250km
Regions March 18 2013Average 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 - 0.000.01 - 0.110.12 - 0.220.23 - 0.42> 0.43
Regional level: NUTS2Source: Politecnico di Milano, 2013
Origin of data: - MASST3 model© EuroGeographics Association for administrative boundaries
© Politecnico di Milano, Project ET2050, 2013
A sensitivity analysis on disparities
Several analyses on sensitivity of total disparities were to macro-economic assumptions in the baseline scenario were run.
The most relevant and interesting:Removing the assumption of a persistence of higher inflation rates in
CEECs with respect to western countries, a higher GDP performance appears in CEECs (mainly due to higher exports and lower imports) and by consequence a much lower increase in total regional disparities in 2030.
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Conclusions
1. Difficult times ahead for inter-regional disparities(due to centralization trends, macroeconomic constraints), confirmed by the recent DG Regio “webminar”
2. A scenario supporting “cities” (first, second and possibly third rank cities) looks the most desirable: in terms of growth potential (best use of “concentrated diffusion” of territorial capital) and in terms of territorial cohesion
3. Relevant policy tasks for CEECs: - keep wage and price increases in line with productivity growth- launch a wave of endogenous capital accumulation- Find a new “innovation pattern”, based on a “smart”
specialization and on selected inter-regional cooperations.
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THANK YOU VERY MUCH FOR YOUR ATTENTION!
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