Transcript Presentation Title in Title Case

New Challenges Facing
Metropolitan Regions
Lamia Kamal-Chaoui
Head of the OECD Urban Development
Programme
25 March, 2010
OECD Work on Cities and Metropolitan Regions
Overview
Athens, Busan, Cape Town, Copenhagen, Stockholm, Helsinki, Istanbul, Madrid, Melbourne, Mexico City, Milan, Montreal, Newcastle,
Oresund (Copenhagen/Malmo), Randstad Holland, Seoul, Toronto, Venice, Vienna-Bratislava, Guangdong (Pearl River Delta) (China),
Chicago and Johannesburg.
A new series of national urban policy reviews
(Korea, Poland, Chile)
STATISTICS ON METRO-REGIONS
OECD Roundtable of Mayors and
Ministers on Urban Strategy
(3rd meeting: May 25th: Cities and
Green Growth with the C40)
regname
TL
type unit
1990
1991
1992
1993
2
NEW SOUTH WALES
2
IN inhabitants per Km
7.3
7.4
7.4
7.5
2
VICTORIA
2
IN inhabitants per Km
19.2
19.4
19.6
19.6
2
QEENSLAND
2
IN inhabitants per Km
1.7
1.7
1.8
1.8
2
SOUTH AUSTRALIA
2
IN inhabitants per Km
1.5
1.5
1.5
1.5
2
WESTERN AUSTRALIA
2
IN inhabitants per Km
0.6
0.6
0.7
0.7
2
TASMANIA
2
PR inhabitants per Km
6.7
6.8
6.8
6.9
2
NORTHERN TERRITORRY (NT) 2
PR inhabitants per Km
0.1
0.1
0.1
0.1
2
AUSTRALIAN CAPITAL TERRITORY2(ACT) PU inhabitants per Km
115.8 118.7 120.9 122.8
2
BURGENALND
2
PR inhabitants per Km
68.4
68.8
69.3
69.6
2
NIEDEROESTERREICH
2
PR inhabitants per Km
76.3
77.1
78.0
78.6
2
WIEN
2
PU inhabitants per Km
3611.5 3647.5 3689.4 3722.0
2
KARNTEN
2
PR inhabitants per Km
57.3
57.7
58.2
58.6
2
STEIERMARK
2
PR inhabitants per Km
71.4
71.7
72.0
72.3
2
OBEROESTERREICH
2
IN inhabitants per Km
108.8 110.2 111.7 112.7
2
SALZBURG
2
IN inhabitants per Km
66.6
67.8
69.0
70.1
2
TIROL
2
PR inhabitants per Km
49.1
49.7
50.3
50.8
2
VORARLBERG
2
IN inhabitants per Km
125.5 127.6 129.2 130.2
2
REG,BRUXELLES-CAP,/BRUSSELS2HFDST,GEW,
PU inhabitants per Km
5962.8 5921.9 5891.0 5884.1
2
VLAAMS GEWEST
2
PU inhabitants per Km
425.8 427.9 430.0 431.9
2
REGION WALLONNE
2
IN inhabitants per Km
193.0 194.0 195.0 195.8
Population
-
Tokyo
Seoul
New York
Mexico City
Osaka
Rhine-Ruhr
Los Angeles
Istanbul
Paris
Chicago
Aichi
Busan
Randstad-Holland
London
Milan
Munich
Berlin
Philadelphia
Dallas
Madrid
Frankfurt
Miami
OECD Average
Houston
Washington
Fukuoka
Barcelona
Atlanta
Toronto
Hamburg
Detroit
Boston
Sydney
San Francisco
Ankara
Athens
Brussels
Rome
Phoenix
Melbourne
Guadalajara
Montreal
Izmir
Seattle
Monterrey
Minneapolis
Naples
Warsow
San Diego
Budapest
St. Louis
Lisbon
Stuttgart
Baltimore
Tampa Bay
Birmingham
Lille
Daegu
Manchester
Zurich
Pittsburgh
Copenhaguen
Denver
Prague
Valencia
Turin
Vienna
Stockholm
Krakow
Cleveland
Puebla
Leeds
Portland
Vancouver
Helsinki
Oslo
Lyon
Dublin
Auckland
5,000,000
10,000,000
15,000,000
20,000,000
25,000,000
30,000,000
35,000,000
70,000
San Francisco
Washington DC
60,000
Boston
Seattle
Per Capita GDP in PPPs (USD)
regID
AU1
AU2
AU3
AU4
AU5
AU6
AU7
AU8
AT11
AT12
AT13
AT21
AT22
AT31
AT32
AT33
AT34
BE1
BE2
BE3
Philadelphia
Denver
50,000
Atlanta
London
Chicago
Detroit
Dublin
40,000
Lyon
30,000
Phoenix
Copenhagen
Madrid
Barcelona
Leeds
Berlin
Lille
Athens
Monterrey
20,000
Munich
Sydney
Randstad-Holland
Aichi
Busan
Fukuoka
Puebla
10,000
Krakow
Ankara
-
-
2,000,000
4,000,000
6,000,000
8,000,000
10,000,000
Population
A unique international database on
78 OECD metro with a common
definition of functional areas
The Global Crisis (food, financial,
economic) environmental): what
development model do we want?
Three “E”s
paradigm
Efficiency
The OECD
Green
Growth
Strategy
Cities/Regions
Environment
Equity
Cities/Metro-regions matter to efficiency
objectives
Population (2005)
-
10,000,000
20,000,000
30,000,000
Share of national GDP
40,000,000
TOKYO
SEOUL
MEXICO CITY
NEW YORK
OSAKA
RHINE-RUHR
LOS ANGELES
ISTANBUL
PARIS
CHICAGO
AICHI
BUSAN
MILAN
RANDSTAD-HOLLAND
LONDON
MUNICH
BERLIN
MADRID
PHILADELPHIA
DALLAS
FRANKFURT
OECD AVERAGE
MIAMI
TORONTO
HOUSTON
WASHINGTON
BARCELONA
FUKUOKA
ATLANTA
HANBURG
DETROIT
BOSTON
ANKARA
A common OECD Definition
for metro-regions based on
functional areas
Stockholm
SYDNEY
SAN FRANCISCO
GUADALAJARA
ATHENS
ROME
BRUSSELS
PHOENIX
MELBOURNE
IZMIR
MONTREAL
MONTERREY
SEATTLE
MINNEAPOLIS
NAPLES
WARSAW
SAN DIEGO
BUDAPEST
ST.LOUIS
LISBON
STUTTGART
BALTIMORE
BIRMINGHAM
TAMPA BAY
LILLE
MANCHESTER
PUEBLA
DEAGU
PITTSBURGH
COPENHAGEN
VALENCIA
PRAGUE
ZURICH
DENVER
TURIN
VIENNA
VANCOUVER
78 metro-regions with more
than 1.5 million inhabitants
STOCKHOLM
KRAKOW
LEEDS
CLEVELAND
PORTLAND
HELSINKI
OSLO
LYON
DUBLIN
AUCKLAND
Stockholm
Around 50%: Budapest, Seoul, Copenhagen,
Dublin, Helsinki, Brussels, (Montreal, Toronto,
Vancouver in their respective provinces), etc.
One third: Oslo, Auckland, Prague, Tokyo,
Stockholm, London, Paris
Cities/Metro-regions matter to efficiency
objectives
•Cities are key engines of national economies. Most of the
largest OECD metro-regions have a higher GDP per capita
than their national average, a higher labour productivity
level, and many of them tend to have faster growth rates than
their countries.
•Agglomeration economies. The concentration of jobs and firms can
be beneficial: pooled labour markets, backward and forward
linkages among firms, and knowledge spill-overs can lead to higher
productivity growth.
Higher GDP per capita…
Higher Productivity…
-50%
WARSAW
0%
50%
100%
150%
-50%
WARSAW
BUDAPEST
BUSAN
PARIS
SAN FRANCISCO
PRAGUE
WASHINGTON
MEXICO CITY
NEW YORK
HOUSTON
AUCKLAND
ATHENS
BUDAPEST
ROME
BOSTON
MINNEAPOLIS
SEATTLE
STOCKHOLM
PARIS
MILAN
ATHENS
DALLAS
PRAGUE
VIENNA
DENVER
GUADALAJARA
LOS ANGELES
HELSINKI
SAN DIEGO
ATLANTA
DETROIT
AICHI
OECD AVERAGE
SAN DIEGO
BRUSSELS
BARCELONA
CLEVELAND
OECD AVERAGE
MADRID
DUBLIN
ZURICH
ISTANBUL
FRANKFURT
PUEBLA
HANBURG
TURIN
OSAKA
PORTLAND
PORTLAND
RANDSTAD-HOLLAND
LONDON
BUSAN
MILAN
COPENHAGEN
STUTTGART
MELBOURNE
BARCELONA
PITTSBURGH
MIAMI
ST.LOUIS
PHOENIX
PHOENIX
MELBOURNE
KRAKOW
ST.LOUIS
ANKARA
FUKUOKA
VALENCIA
TAMPA BAY
MANCHESTER
LILLE
TAMPA BAY
VANCOUVER
LILLE
MONTREAL
BERLIN
LEEDS
DEAGU
NAPLES
0%
50%
Higher Employment…
100% -30.0% -20.0% -10.0% 0.0%
MINNEAPOLIS
BARCELONA
BUDAPEST
KRAKOW
TURIN
VALENCIA
WASHINGTON
ZURICH
BRUSSELS
WARSAW
ST.LOUIS
SYDNEY
TAMPA BAY
PHOENIX
AICHI
LONDON
SAN DIEGO
BALTIMORE
VANCOUVER
DALLAS
PHILADELPHIA
OECD AVERAGE
LEEDS
ATHENS
MONTREAL
ANKARA
COPENHAGEN
LOS ANGELES
STUTTGART
PARIS
NEW YORK
VIENNA
HOUSTON
BIRMINGHAM
FUKUOKA
MONTERREY
OSAKA
PUEBLA
RHINE-RUHR
NAPLES
10.0% 20.0%
URBAN ASSETS
Advantages of both diversification and specialisation in high-value added
activities
More than 81% of patents are
Strong innovative capacity
produced in urban regions
Great endowment of human
capital
Lower old-age dependency ratio
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
Country
60%
50%
40%
30%
20%
10%
Stockholm vs
Sweden
0%
London
Tokyo
Washington
Denver
San Francisco
Boston
Seattle
Madrid
San Diego
Helsinki
Minneapolis
New York
Osaka
Chicago
Atlanta
Oslo
Stockholm
Brussels
Fukuoka
Phoenix
Aichi
Los Angeles
Miami
Barcelona
Dallas
Houston
Philadelphia
Detroit
Tampa Bay
Pittsburgh
Paris
Copenhaguen
St. Louis
Manchester
Randstad-Holland
Leeds
Lyon
Portland
Cleveland
Valencia
Stuttgart
Birmingham
Sydney
Melbourne
Athens
Auckland
Dublin
Lisbon
Ankara
Budapest
Warsow
Lille
Prague
Izmir
Krakow
Istanbul
-25.0%
Metro-region
Share of Labour Force with Tertiary Education
Naples
Athens
Paris
Rome
Lille
Milan
Madrid
Budapest
Brussels
Turin
Valencia
Berlin
Stockholm
London
Munich
Barcelona
Stuttgart
Frankfurt
Krakow
Helsinki
Hamburg
Istanbul
OECD Average
Warsow
Rhine-Ruhr
Ankara
Tokyo
Dublin
Manchester
Seoul
Leeds
Copenhaguen
Auckland
Daegu
Izmir
Aichi
Prague
Randstad-Holland
Melbourne
Birmingham
Oslo
Osaka
Zurich
Lisbon
Monterrey
Fukuoka
Mexico City
Guadalajara
Sydney
Puebla
Lyon
Busan
Stockholm
-30.0%
Higher level of skills
Higher capital stock per capita (physical
infrastructure, transport and
telecommunications, universities and
research institutes, etc..)
Stockholm: a strong competitive region
(GDP per capita (PPP) data for 2000)
90000
80000
Stockholm ranks 25 out of 66
OECD metropolitan regions …
70000
60000
50000
Stockholm, 37066
40000
30000
20000
10000
0
50000
45000
40000
35000
…6 out 28 OECD European
metropolitan regions
30000
25000
20000
15000
10000
5000
R
At
ti k
i
or
d
Va
le
nc
ia
N
om
he
in
un
la
id
nd
ad
de
M
ad
rid
Fr
ei
bu
rg
G
D
re
e
at
tm
er
ol
M
d
an
ch
es
te
r
om
e
R
Tu
rin
R
C
eg
io
n
M
un
ic
hIn
go
Îl e
ls
ta
dt
de
Fr
an
ce
D
ar
m
R
st
eg
ad
io
t
n
H
am
bu
rg
0
Stockholm: a strong competitive region
(GDP per capita (PPP) data for 2005)
Stockholm ranks 23 out of 78
OECD metropolitan regions …
…5 out 35 OECD European
metropolitan regions
Stockholm: a strong competitive region
(data for 1995-2000)
… and one of the highest GDP per capita growth since
1995
7.5%
London
7.0%
Greater Manchester
3.9%
Stockholm
3.7%
Napoli
3.3%
Roma
Valencia
3.1%
Milano
3.0%
2.8%
Torino
Comunidad
de
2.4%
Madrid
2.3%
Nord - Pas-de-Calais
Île
de
2.1%
France
2.0%
Barcelona
1.9%
Region München-Ingolstadt
1.5%
Noord-Brabant
1.5%
Noord-Holland
Zuid-Holland
1.3%
Stuttgart
1.2%
1.2%
Attiki
0.9%
Karlsruhe
0.9%
Darmstadt
Freiburg
0.8%
Region Berlin
0.8%
0.6%
Region Hamburg
0.3%
Rheinland
0.1%
Ruhrgebiet
Rheinhessen-Pfalz
0.0%
Budapest
0.0%
Detmold
-0.1%
-1%
0%
1%
2%
3%
4%
5%
6%
7%
8%
Stockholm: a strong competitive region (data for
1995-2005)
… and one of the highest GDP per capita growth since
1995
Productivity Growth
25%
6%
20%
4%
15%
2%
10%
0%
5%
-2%
0%
-4%
-5%
-6%
National productivity grow th
London
Prague
Leeds
Manchester
Birmingham
Naples
Stockholm
Rome
Milan
Lyon
Warsow
Busan
Turin
Munich
Dublin
Stuttgart
Helsinki
Tokyo
Fukuoka
Lisbon
Valencia
Madrid
Copenhagen
Paris
Aichi
Frankfurt
Lille
Brussels
Seoul
Oslo
Ankara
Hamburg
Randstad-Holland
Osaka
Vienna
Istanbul
Rhine-Ruhr
Barcelona
Berlin
Athens
Izmir
Krakow
Daegu
Budapest
Prague
Krakow
Budapest
Busan
Seoul
Dublin
Vienna
Stuttgart
Helsinki
Daegu
Hamburg
Brussels
Osaka
Copenhaguen
Paris
Munich
Fukuoka
Tokyo
Izmir
Athens
Berlin
Aichi
Frankfurt
Lyon
Ankara
Milan
Oslo
Rhine-Ruhr
Turin
Lille
Rome
Naples
Barcelona
Randstad-Holland
Istanbul
Stockholm
Valencia
Madrid
But Metro-regions not Always
Synonymous With Success!!
GDP and productivity growth not always
higher than national averages
Metro-region productivity grow th
0
Greece
Australia
Hungary
Poland
Slovak Rep
Spain
Mexico
Intermediate
Italy
Austria
Predominantly Urban
Netherlands
Switzerland
Japan
Denmark
• High level of poverty in all types of
metro-regions (e.g. about 50% in
Mexico City, 22% in Rotterdam, 15%
in Paris)
OECD Average
• Exclusion of immigrants
-8%
France
 Wealth and Poverty
United Kingdom
• Lower activity rates in urban regions
(44.3%) than intermediate (49.7%)
and rural (44.5%)
Korea
 The Urban Paradox
Sweden
• Persistence of high pockets of
unemployment
Naples
Berlin
Lille
Vienna
London
Detroit
Birmingham
Montreal
Osaka
Fukuoka
Lisbon
Daegu
Seoul
Pittsburgh
Cleveland
Rhine-Ruhr
Brussels
Houston
Chicago
Tokyo
St. Louis
Oslo
Auckland
Melbourne
Randstad-Holland
Leeds
Valencia
Hamburg
Portland
Denver
Toronto
Busan
Manchester
Paris
Copenhaguen
OECD Average
New York
Dublin
Lyon
Rome
Dallas
Barcelona
Atlanta
Los Angeles
Stockholm
Aichi
Sydney
Boston
Philadelphia
Seattle
Phoenix
San Francisco
Minneapolis
Baltimore
Athens
Vancouver
Budapest
San Diego
Turin
Zurich
Frankfurt
Miami
Helsinki
Tampa Bay
Washington
Krakow
Stuttgart
Prague
Milan
Munich
Madrid
Warsow
 Growth and Unemployment
United States
• Spatial polarisation (in 10 OECD
countries, up to 10% of the
population live in distressed areas)
Crime against persons (country avg=1)
Cities/Metro-regions matter to equity
objectives
One third of metro-regions have
higher unemployment rate than
their national averages
12%
10%
8%
6%
4%
2%
-2%
0%
-4%
-6%
Criminality
(30% higher in urban regions)
predominantly Rural
4
4
3
3
2
2
1
1
Cities/Metro-regions matter to equity
objectives
In many cases intraregional disparities are
widest in large metroregions in the OECD.
Cities/Metro-regions matter to environmental
objectives
Climate change may significantly impact cities
In 2070, urban population in European cities will feel as if the weather has moved south
(EU report, 2009)
Cities/Metro-regions matter to environmental
objectives
 Coastal cities are particularly vulnerable (OECD ENV WP)
The location of the 136 port cities
Port Cities at Risk:
 As of 2005, 40 million people and 5% of global GDP are exposed
 By 2070, 150 million people and 9% of global GDP expected to be exposed
Cities/Metro-regions matter to environmental
objectives
Cities contribute to climate change
 Half of the worldwide population lives in cities, projected to reach 60% by 2030 (UN, 2008)
 Cities are responsible for 2/3 of total energy consumption (IEA World Energy Outlook 2008) –
IEA projects an increase in cities’ energy use (up to 80% in US and China)
Cities/Metro-regions matter to environmental
objectives
 Cities are responsible for 2/3 CO2 emissions (IEA World Energy Outlook 2008)
 Higher level of urbanisation are correspond to higher levels of CO 2 emissions
Urbanisation (PU) and Carbon Emissions (CO2)
per capita CO2 emissions in 2006 (t of CO2 / population)
25
20
Australia
United States
Canada
15
Finland
Czech Republic
10
Norway
Austria
Ireland
Denmark
Belgium
Korea
Germany
Japan
New Zealand
Greece
Poland
Slovak Republic
Spain
France
Hungary
Switzerland
Sweden
5
Netherlands
UK
Italy
Portugal
Mexico
Turkey
0
0%
10%
20%
30%
40%
50%
60%
Urban share of total population (2005)
70%
80%
90%
Cities/Metro-regions matter to environmental
objectives
 Urban density emerges as a crucial element to reduce carbon emissions
Urban Density and Electricity Consumption
Urban Density and Carbon Emissions in Transport
30000
7000
Norway
per capita transport CO2 emissions in 2006
(kg CO2/ population)
Per capita electricity consumption in 2006 (KWh / population)
25000
20000
Finland
Canada
Sweden
15000
United States
Australia
10000
New Zealand
Belgium
Switzerland
Japan Austria
France
Germany Netherlands
Denmark
Ireland
Spain
Italy UK
Greece
5000 Slovak Republic Portugal
Korea
Czech Republic
Hungary
Poland
Turkey
Mexico
6000
United States
5000
Canada
Sweden
4000
Australia
New Zealand
Ireland
Norway
3000
Finland Denmark
Austria
Belgium
France
Italy
2000
Greece Japan
Germany Portugal
Mexico
1000 Slovak Republic Poland
Hungary
Turkey
0
0
0
0
Korea
Czech Republic
1000
2000
3000
4000
Urban density in 2005 (population / km2)
5000
6000
1000
2000
3000
4000
Urban density in 2005 (population/ km2)
5000
6000
Cities/Metro-regions matter to environmental
objectives
Population growth in metro-region's core and belt
compared
 Sprawl is to be blamed
 Expansion of urban land use since 1950 has
doubled in OECD countries and increased by five
times in the rest of the world
 In 66 of the 78 OECD metro-regions, surburban
belt grows faster than the core
Trends in urban land expansion in the world and the OECD
600,000
OECD
Rest of the World
BRICs
Urban area (km2)
500,000
400,000
300,000
200,000
100,000
0
1950
1970
1990
2000
Dallas
Denver
Atlanta
Minneapolis
Guadalajara
Houston
Dublin
Seoul
Tampa Bay
Monterrey
Washington
Puebla
Istanbul
Mexico City
Detroit
Baltimore
Portland
Budapest
Chicago
Boston
Lisbon
St.Louis
San Francisco
Vienna
Oslo
Milan
Busan
Philadelphia
Zurich
Munich
Cleveland
Paris
Hanburg
Stockholm
Tokyo
Copenhagen
London
Brussels
Prague
Warsaw
Osaka
Helsinki
Frankfurt
Krakow
Aichi
Leeds
Berlin
Rhine-Ruhr
Birmingham
Pittsburgh
-2%
-1%
0%
1%
Metro-region BELT
2%
3%
Metro-region CORE
4%
5%
Cities/Metro-regions matter to environmental
objectives
 Urbanisation levels may correspond to an increase in CO2 emissions but
emissions go down as density increases
Urbanisation, Density and Carbon Emissions
20
Australia
United States
18
Canada
16
Finland
14
Belgium
Netherlands
New Zealand
12
UK
Spain
Japan
Slovak
Republic
Sweden
10
8
6
Denmark
France
Poland
4
Germany
Portugal
2
0
Greece
Turkey
53.7%
47.2%
Austria
44.7%
41.3%
Hungary
28.5%
Czech
Republic
23.2%
16.8%
11.2%
85.0%
57.3%
Norway
Urban density in 2005
(population / km2)
Korea
Urban share of
total population (2005)
per capita CO2 emissions
in 2006
(t of CO2 / population)
Cities/Metro-regions matter to environmental
objectives
 Lifestyle matters
 Urban transportation modes influence the level of CO2 emissions (e.g. Los
Angeles vs. New York)
 Energy modes of production and energy efficiency supply influence CO2 levels
(e.g. Cape Town vs. Geneva: similar level of per capita electricity consumption
but more GHG intensity in Cape Town (relies on coal) than in Geneva (relies on
hydropower)
Concentration of Carbon Emissions in the USA
(CO2 at the county level)
A stronger, cleaner, and fairer economy : a new
paradigm for the Global Economy
Efficiency
To Complementarities/
Synergies
From Trade Offs
Cities/Regions
Environment
Equity
Exploring synergies/complementarities
Example: why environment is good for growth
Urban policy (densification or congestion charges) can contribute to a
reduction in global energy demand and CO2 emissions
Percentage reduction in total CO2 emissions in OECD with a
densification policy applied
0.1%
0.0%
-0.1%2000
-0.2%
-0.3%
Results from a CGE
model (IMACLIM with
an urban module, using
the OECD metropolitan
database)
-0.4%
-0.5%
-0.6%
-0.7%
-0.8%
2010
2020
2030
2040
2050
Exploring synergies/complementarities
Example: why environment is good for growth
In the long run, the trade off between economic growth and
environmental objectives observed at the macro economic level
disappear at the local scale
Economic growth with local climate policies
Changes in GDP with densification and congestion charges
policies (vis-a-vis baseline scenario)
This is due to complementarities
with other objectives (e.g.
pollution reduction) felt at
the local level that enhance
city attractiveness and
competitiveness
0.05%
0.04%
0.03%
0.02%
0.01%
0.00%
-0.01%
-0.02%
2000
2010
2020
2030
DS/BS
TS/BS
2040
2050
Exploring synergies/complementarities
Example: why environment is good for growth
Attractiveness and Carbon Emissions related to
Automobiles across Metro-regions
OECD average
80
New York
y = 0.0407x + 8.1829
R² = 0.0802
Today, a group of highly
attractive metro-regions are
associated with high levels of
carbon emissions
Los Angeles
60
Tokyo
50
Chicago
40
Seoul
Osaka
Atlanta
Dallas
Miami
Houston
San Francisco
20
Detroit
Boston
Phoenix
OECD average
Aichi
10
Mexico city
Krakow
-100
0
100
Sydney
Madrid
London
Melbourne
Guadalajara
0
-200
Changes in Attractiveness and Local Pollution Emissions
across Metro-regions
San Diego
Paris
200
Puebla
Auckland
300
4%
400
OECD average
30
Washington
500
Fukuoka
Osaka
Attractiveness index (2002)
3%
But, results from the CGE
model: by 2030, metroregions will loose
attractiveness if they
continue to pollute
Average growth rate of local pollution (2000-2030)
Carbon emissions (MtCO2) by automobile (2002)
70
Rome
2%
Stockholm
Dallas
Seoul
Tokyo
1%
y = -9E-05x - 0.0004
R² = 0.0353
Paris
Istanbul
Philadelphia
New York
Mexico City
Atlanta
Minneapolis
Denver
Phoenix
Chicago
Los Angeles
0%
Busan
Valencia
Hamburg
-1%
Aichi
Budapest
Manchester
Barcelona
Naples
Randstad-Holland
Munich
-2%
Melbourne
Krakow
Ankara
Lyon
Auckland
Toronto
Lille
Montreal
Guadalajara
Puebla
London
-3%
Birmingham
Leeds Madrid
Monterrey
-4%
-140
-120
-100
-80
-60
-40
-20
0
Attractiveness (effects of pollution on absolute attractiveness)
20
40
60
80
Some policy implications for the new paradigm
for urban policy
1/ Seeking co-benefits
•Examples: investment in green infrastructure and support to green R&D innovation
can create jobs – densification can reduce CO2 emissions and limit the costs of sprawl
•But also no-regret strategies: public health improvements, costs savings in energy
efficiency, Energy security and infrastructure improvements, Improved quality of life)
2/ Seeking complementarities and avoid conflicting outcomes
•Examples: Conditions for successful compact city and densification policies include
mixed land uses, mass transit services and urban amenities
3/ Capacity to act depends on optimising modes of governance
•Strategic planning is a key tool to ensure complementarities among different urban
policy objectives
•Urban finance needs to be streamlined (access to revenues, but also review of side
effects)
•Vertical collaboration is key (national governments have a key role to foster intermunicipal collaboration, provide incentives and sanctions)
The world is changing: What about Stockholm?
Why did regionalisation
progress in Sweden and not so
much in the Stockholm region?
Strengths and challenges of Swedish Multi level Governance
to implement regional growth policy
Strengths
• Balanced policy-mix: equity (mostly at the
local level) and growth (national level)
• High degree of trust & transparency in
public decision-making
• Good public-private cooperation
• Well-developed inter-municipal cooperation
for public service delivery
• Agile government, with strong consensus
building mechanisms
• …and high capacity for (gradual) reform
• Innovative governance approaches through
learning-by-doing processes (pilot
experiences)
Challenges
• Elected regional actors not enough involved in
the design & implementation of pro-active
regional growth policies – apart from pilot
regions
• Limits of regional coordination bodies
• Limited spatial/strategic planning at functional
regional scale
• Lack of effective implementation mechanisms
(RUP: broad strategies)
• Coordination gaps across levels of
government:
 Policy gap: lack of coordination across sectoral
policies at the regional scale; by-passing of CAB
 Information gap: high number of actors involved in
regional development policy at all levels (asymmetries
of information)
• Small size of counties in some cases /
widening labour market regions  critical mass
debate
Current challenges call for further adjustments
in multi-level
governance
• The governance
of Stockholm’s
functional
region
arrangements
The world is changing: What about Stockholm?
Is the concept of the Stockholm Malar
Region still valid?
What about the regional economic
development strategy?
Is there any evidence on policy
outcome? (e.g. immigrants, youth
unemployment, etc.)
Why does innovation still mainly come
from large firms?
How to make sure that policy strategy
will be implemented?
Looking forward
Anticipating/adapting to the changes of the global economy
(eg. What are the Stockholm’s main competitors and
challengers?)
Fostering synergies and seeking co-benefits (e.g. first mover
in the green economy; linking land use, transport and planning)
Making reforms happen (e.g. identifying obstacles, leadership,
roadmap, timeframe, mointoring outcome, etc.)