Defining and Measuring
Metropolitan Regions – OECD work
Dev Virdee
Office for National Statistics
United Kingdom
Background
• OECD Governance Directorate:
- Territorial Policy Development Committee (TDPC)
- Public Governance Committee (PGC)
• TDPC works through:
- Urban Policy Working Party (WPURB)
- Rural Policy Working Party (WPRUR)
- Territorial Indicators Working Party (WPTI)
• WPTI:
- More than just “Indicators” - more later
- Chair – Dev Virdee
Focus of GOV Directorate:
CONCEPTUAL RELATIONSHIPS
INNOVATION AND REGIONAL
DEVELOPMENT
NEW AGENDAS AND
APPROCHES FOR PUBLIC
SERVICE DELIVERY
FOSTERING STRATEGIES
FOR REGIONAL
DEVELOPMENT
CREATING GOOD
GOVERNANCE FOR PUBLIC
INVESTMENT
REGIONAL
COMPETITIVE
NESS
CHANGING PRIORITIES FOR
PUBLIC INVESTMENT
3
Draft Programme of Work 2009-10
THEME 1
REGIONAL
COMPETITIVENESS
AND GLOBALIZATION
Adaptation of firms
Relocation trends
Financial markets and
industrial conversion
Adaptation of rural and
urban communities
Building natural
environment as an asset
Equity across urban and
rural regions
Urban rural linkages,
functional areas and
labour markets
THEME 2
INNOVATION AND REGIONAL
DEVELOPMENT
Innovation trends in regions
Innovation in firms of
different sizes, in urban and
rural areas
Agglomeration effects
THEME 3
GOVERNANCE OF PUBLIC
INVESTMENT
THEME 4
NEW AGENDA AND
APPROACHES FOR PUBLIC
SERVICE DELIVERY
Public investment for
territorial development
Public services as enabling
factors, their contribution
to growth and
development in urban and
rural regions
Trends in OECD countries
Decentralization and
multilevel governance and
tools
Regional conditions that
favour innovation
Policy instruments in use in
different regions
Aspects of public investment
in urban and rural
development
Efficacy of policies and
instruments
The decision making process
on public investment for
territorial development
Innovation in public utilities
and effects on public service
provision
Regional investment and
strategies for participation on
private and public actors
What works best to promote
regional innovation
Procedures used in OECD
countries to evaluate public
investment projects
Best practices for public
service delivery in rural,
urban and metropolitan
regions
Equity and disparities in
access for public services,
among regions and social
groups, decentralization
effects
THEME 5
FOSTERING STRATEGIES FOR
REGIONAL DEVELOPMENT
Territorial development and
public sector organization
Assessment of governance in
a comparative perspective,
at the national and subnational levels
Reform challenges and
experiences
Territorial development in
public sector budgets, what
ought to be considered, how
it is presented
Decentralization in a
comparative perspective
Rules for transparency,
integrity and efficiency
Potential of ICT to narrow
disparities, improving local
capacities for the provision
of public services
Migration
4
TDPC main events 2009-10
•Ministerial Meeting (March 2009)
•Permanent Roundtable of Mayors and Ministers
- Istanbul (2009): cities cross-border co-operation
- Shanghai (2010): OECD contribution to Shanghai Expo
•China Forum (mid-2009)
• Regulatory Reform Review
• Rural Review
WPTI role
• WPTI supports TDPC through:
Management of OECD Regional Database
Analytical work on explaining factors that determine
regional performance and growth
Regional classification (TL 2 and 3)
Regional typology (Predominantly rural, Predominantly
urban, intermediate)
Regular reports eg “Regions at a Glance”
Supporting work eg “Innovation in the North of England”
• Enhancing engagement with China, India, Brazil
and Chile
OECD Regional Database (RDB)
•
•
Regional grids - Regions in each member country are classified at two territorial
levels (TLs): Territorial Level 2 (335 macro regions) and territorial Level 3 (1679
micro regions).
For European countries this classification is largely consistent with the Eurostat
NUTS2 and NUTS3 regions
•
The classification is officially established (and relatively stable) in all OECD
member countries and used by central governments as a framework for
implementing regional policies.
•
Regional typology - Regions at the TL3 level are classified into Predominantly
Urban, Intermediate or Predominantly Rural according to the share of population
living in rural communities.
•
Metropolitan database - Definition of metropolitan regions (based on
population, pop density, commuting rate); applied for policy analysis
OECD Regional Database (RDB)
• Provides internationally comparable quantitative information
on sub-national development conditions and trends
• Includes 40 regional statistics for 30 OECD member
countries on demography, regional economic accounts,
labour market, social indicators.
• Topics, statistics and methods discussed within the WPTI
• Data collected directly through access of NSOs, other official
institutions’ web-sites and Eurostat’s New Cronos.
• Questionnaire sent to member countries annually to collect
data not accessible elsewhere.
Use of RDB
• “OECD Regions at a glance”
•
•
•
•
•
•
•
•
•
•
•
factors of national growth
unused regional resources to improve regional competitiveness
broader dimension of regional well-being
support regional competitiveness and improve social cohesion
Decomposition of regional growth around six key factors
Econometric analysis on regional competitiveness
Quantitative analysis on specific issues or areas
Member Countries for comparison and benchmarking
OECD National territorial reviews
OECD Territorial Reviews of specific regions
Innovation reviews
Issues and future developments
• Adequate for assessing territorial policies, but need more:
•
•
•
•
•
Improvement of the geographical unity of analysis
revised rural typology
proposed metropolitan areas definition
comparability of functional areas
use of geographical integrated systems for computing
according to the purpose of analysis eg Spatial
correlation in innovative cluster
• Link to policy evaluation: include information on how
territorial policies are delivered (resources, multilevel
governance, mechanism)
Defining Metropolitan Regions (MR’s)
•
•
•
•
•
OECD workshops and discussions since 2006
Views of experts sought
Considering ways to proceed December 2008
OECD keen to involve China
Particularly keen that National Statistical
Institutes should be involved in work
What are MRs and how can they be defined?
 MRs are NOT just “Metropolitan Areas” (ie. conurbations)
 MRs are NOT all “World Cities” (such as Paris)
 MRs are city regions which meet additional criteria that
identify them as having metropolitan character
MR definitions need to be fit for purpose (ie. meet OECD needs),
and applicable in as many OECD countries as possible
In practice, the need is for definitions with 2 components:
 definitions of city regions (where each is a coherent territory
providing internally most functions associated with cities (eg. high level
jobs and services)
 criteria distinguishing MRs among other city regions,
(probably including size of the MR or its urban area(s), but
possibly also other metropolitan characteristics)
Contemporary MRs can take different forms
• The linkages making MRs into integrated “wholes” go in
many directions between city centres / edge cities / airport
parks … a metropolitan region is now a ‘space of flows’
• The definition method needs to allow for polycentric MRs –
such as Randstad (Netherlands) – as well as the more
familiar monocentric MRs (such as Paris)
• MRs of different form can meet the same essential criteria:
any MR must be self-contained enough to be a city region,
and also (perhaps) large enough to be metropolitan
What are the implications for MR definitions?
• To maximise the consistency of cross-national definitions,
the method needs to be:
- very simple and readily computerised
- dependent ideally on a single – widely available – dataset
- transferable between many countries, in 2 senses…
* TECHNICALLY TRANSFERABLE
(eg. work with hugely varying ‘building block’ areas)
* GEOGRAPHICALLY TRANSFERABLE
(ie. not presuming that one particular urban form will
be present in all parts of every country)
- matching both the 2 elements of the MR concept :
-  demarcating genuine city regions, as well as
-  identifying those with metropolitan characteristics
The city is an economic entity
• Cities are centres of agglomeration
• They are centres of global connections
• They are centres of production
• They are centres of residence
• They are centres of consumption
• Locus of advanced producer services
organising ‘command and control’
• The space in which advanced
economic interactions take place
Cities are workplaces
14%
Europe employment share
50%
Cities employment share
12%
City job premium (right scale)
48%
10%
46%
8%
6%
44%
4%
42%
2%
40%
0%
1980
1990
2000
Source: GLA Economics and BAK Basle, study of 35 European cities
Employment share=proportion of population in work
City job premium =City employment share/Europe employment share-1
38
36
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Cities are centres of productivity
40
Cities
Countries
34
32
30
28
26
24
22
20
Cities are global connectors
London
Amsterdam
Paris
Frankfurt
Toronto
Munich
Boston
Milan
Chicago
Rome
San Francisco
New York
Las Vegas
Madrid
Washington
Tokyo
Los Angeles
Atlanta
Singapore
Taipei
Hong Kong
Dallas
Bangkok
Miami
Sydney
Ben Derudder & Peter Taylor (GaWC) – Porous Europe: European Cities in Global Urban Arenas
What is the economic reality of the city?
•
•
•
•
A centre of agglomeration for production
A centre of agglomeration for residence
A centre of agglomeration for consumption
Territorial definition should
– Define the community that participates in these
agglomeration externalities
– Include ‘highly dense’ morphological
concentrations of jobs and residence
– Capture the population that interacts with these
morphological concentrations on a daily basis
Proposal:
• A variety of definitions as a basis to identify
best practice and as a tool for planners
• Core-based methodology to provide
economically comparable city definitions
• TTWA method to identify urban centres
• A variety of thresholds to identify continental
standards and check sensitivity
Selection of a target set of cities
• Previous work shows there is a hierarchy of cities
• For comparability, cities should be at the same level
of the hierarchy
Not compare eg Paris with Lyons, London with Manchester,
Milan with Perugia
• Spread of continents required
Historical evolution in each continent has mutually conditioned
the relation between city and transport mode
• Consistency within continents
Establish ‘European’, ‘US’, ‘Latin American’ thresholds
Determine where are regions in which pattern of city
development is broadly similar
Short list based on size and connectivity
(final selection to be made on other criteria)
• Europe
London, Paris, Berlin, Moscow, Istanbul
• North America
New York, Toronto, Los Angeles
• Latin America
Mexico, Buenos Aires, Santiago, Rio, Sao Paolo
• Asia Pacific
Tokyo, Beijing, Shanghai, Singapore, Bangkok
• South Asia
Mumbai, Delhi, Calcutta
Next steps
• London offer to take lead
• Meeting between OECD and London
November 2008
• OECD WPTI meeting December 2008
• Further plans to be confirmed after December
meeting
Finally
• A flavour of the type of work done by the
OECD:
Urban Trends and Policy in China
Urban Trends and Policy in China
1,000,000
900,000
700,000
Largest urbanization
in human history …
from 1970-2010, China's urban population
will have grown by 281%
600,000
India
500,000
168%
400,000
USA
300,000
60%
200,000
153%
Brazil
100,000
—
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030
United States of America
Japan
United Kingdom
projection by China
Ministry of Construction:
urbanization of 60%
by 2020
60%
11th Five Year Plan
urbanization target:
47%
50%
start of national
re-engineering and
resettlement campaigns
(e.g. Great Leap Forward)
40%
start of market
reforms under
Deng Xiaoping
30%
Cultural Revolution
20%
anomalies
in statistical
reporting
10%
2019
2017
2015
2013
2011
2009
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
1977
1975
1973
1971
1969
1967
1965
1963
0%
1961
…urban policies have
been constantly
evolving during the
process
…with recent strong
emphasis on
metropolitan regions
in 2005
70%
1959
India
Russian Federation
Germany
South Africa
1957
China
Brazil
Mexico
France
1955
Urban population (Thousands)
China
800,000
High proportion living
in large cities…
Uneven distribution and
concentrated in the eastern region…
Japan
Mexico
USA
China
OECD average
Korea
France
Turkey
Canada
Spain
UK
Australia
Portugal
Greece
Ireland
Austria
New Zealand
Finland
Italy
Hungary
Denmark
What are Drivers of
urbanization?
Switzerland
Belgium
Sweden
Czech Republic
Netherlands
 Rural-urban migration
 Rapid suburbanization
Germany
Poland
Norway
Slovakia
Luxembourg
Iceland
0%
10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
> 10 million
500t to 1 million
5 to 10 million
Fewer Than 500t
1 - 5 million
Assessing urban economies in China:
Urban/Rural definitions
Macro-regions for national regional policy
Two scales of functional urban regions
Regional Urban system
Metropolitan regions
Assessing urban performance in China:
28 Regional Urban Systems (RUS)
750 million people,
58% of total China
population,
88 % of national GDP
19,472,322
NECL
UQCR
3,559,964
27,187,440
6,017,449
LNCL
BJTJ EHB
COR COR
BHCL
NXCOR
25,355,834
9,824,696
3,132,804
45,845,490
15,894,312
42,408,282Shandong
SXCOR
8,075,238
CHB
COR
19,753,695
LZCR
38,319,817
XACR
Corridor
SDCOR
49,376,182
XLCL
CHNCL
82,791,281
16,435,572
48,729,708
101,195,244
MYCOR
WYCL
AHCOR: Anhui Corridor
BHCL: Baotou-Hohhot Cluster
BJTJCOR: Beijing-Tianjin Corridor
CHBCOR: Central Hebei Corridor
CHNCL: Central Henan Cluster
CSCR: Changsha Centered Region
EGDCL: Eastern Guangdong Cluster
EHBCL: Eastern Hebei Cluster
FJCOR: Fujian Corridor
GYCR: Guiyang Centered Region
KMCR: Kunming Centered Region
LNCL: Liaoning Cluster
LZCR: Lanzhou Centered Region
MYCOR: Middle Yangtze Corridor
NCCR: Nanchang Centered Region
NECL: Northeast Cluster
NNCR: Nanning Centered Region
NXCOR: Ningxia Corridor
PRDMG: Pearl River Delta Megalopolis
SDCOR: Shandong Corridor
SXCOR: Shanxi Corridor
UQCR: Urumqi Centered Region
WYCL: Western Yangtze Cluster
XACR: XIian Centered Region
XLCL: Xulin Cluster
YDMG: Yangtze Delta Megalopolis
ZJCOR: Zhejiang Coastal Corridor
ZJCR: Zhanjiang Centered Region
AH
COR
YDMG
11,610,654
NCCR
38,693,518
GYCR
CSCR
16,241,348
KMCR
13,909,601
NNCR
14,166,929
36,256,312
PRD
MG
ZJCOR
18,254,182
FJCOR
19,202,845
EGDCL
15,345,777
10,607,941
ZJCR
per capita GDP (Y), 2004
5000 - 10000
10000 - 15000
15000 - 20000
20000 - 25000
25000 - 30000
> 30000
Concentration in East China (but the
largest RUS in the West(101 M))
Largest productivity increase and
income growth over 1998-2004
Significant differences within the
group
Not all coastal regions linked to
growth
Central and western regions are
more or less characterised by marginal
growth or stagnation
Assessing urban performance in China:
53 Metropolitan regions
Increasing Importance in China:
30% of the total population
64% of the country’s GDP
77% of China’s GDP’s growth (1998-2004)
34_Shanghai MR
16_Guangzhou MR
37_Shenzhen MR
39_Suzhou MR
05_Beijing MR
19_Hangzhou MR
43_Tianjin MR
46_Wuxi MR
31_Ningbo MR
14_Dongguan MR
32_Qingdao MR
29_Nanjing MR
Sharp differences among
Metropolitan regions,
6 out of 13 lagging are from
coastal areas
09_Chengdu MR
20_Harbin MR
22_Hohhot MR
27_Luoyang MR
08_Changzhou MR
44_Wenzhou MR
04_Baotou MR
25_Linyi MR
41_Taizhou MR
11_Dalian MR
07_Changsha MR
10_Chongqing MR
12_Daqing MR
52_Zibo MR
21_Hefei MR
18_Handan MR
02_Lanzhou MR
66
23_Jilin MR
38_Shijiazhuang MR
28_Nanchang MR
51_Zhengzhou MR
64
01_Urumqi MR
2004
40_Taiyuan MR
48_Xian MR
(29.4%)
17_Guiyang MR
% of China's GDP
26_Liuzhou MR
62
42_Tangshan MR
30_Nanning MR
13_Datong MR
33_Qiqihar MR
45_Wuhan MR
60
36_Shenyang MR
06_Changchun MR
24_Kunming MR
58
2000
15_Fuzhou MR
(29.1%)
47_Xiamen MR
53_Jinan MR
49_Xuzhou MR
35_Shantou MR
50_Yantai MR
56
03_Anshan MR
-0.60
1998
-0.40
54
185
190
195
200
-0.20
0.00
0.20
0.40
0.60
change in share of China's GDP, 1998 - 2004 (% of GDP)
(28.7% of China's population)
205
% of China's per capita GDP
210
215
220
coastal
northeast
central
western
0.80
1.00
Assessing urban performance in China:
Comparing with OECD countries
Per Capita GDP in PPPs
GDP in PPPs (Billions of USD)
0
Tokyo
New York
Los Angeles
London
Paris
Osaka
Seoul
Chicago
Rhine-Ruhr
Washington
Philadelphia
Dallas
Shanghai
Milan
Mexico City
Aichi
San Francisco
Boston
Randstad-Holland
Houston
Atlanta
Munich
Miami
Detroit
Frankfurt
Guangzhou
OECD average
Busan
Seattle
Minneapolis
Madrid
Toronto
Beijing
Phoenix
Sydney
Hamburg
San Diego
Brussels
Barcelona
Istanbul
Berlin
Rome
Denver
Melbourne
Baltimore
St. Louis
Fukuoka
Montreal
Tampa Bay
Stuttgart
Wuhan
Pittsburgh
Cleveland
Portland
Zurich
Vienna
Copenhagen
Stockholm
Athens
Birmingham
Lisbon
Manchester
Turin
Warsaw
Budapest
Changsha
Vancouver
Chengdu
Helsinki
Lille
Dublin
Oslo
Monterrey
Leeds
Prague
Lyon
Naples
Valencia
Xian
Guadalajara
Xuzhou
Chongqing
Ankara
Changzhou
Auckland
Izmir
Daegu
Puebla
Krakow
100
200
300
400
500
600
700
800
0
900 1,000
Distinct
performance
difference among
Chinese
metropolitan regions
(GDP PPPs)
While lagging in
per capita terms…
San Francisco
Washington
Boston
Seattle
Minneapolis
New York
Denver
Philadelphia
Dallas
Atlanta
Houston
San Diego
Chicago
Los Angeles
Detroit
Baltimore
Paris
Cleveland
Portland
St. Louis
Phoenix
London
Dublin
Pittsburgh
Tampa Bay
Vienna
Miami
Stockholm
Stuttgart
Milan
Lyon
Munich
Oslo
Sydney
Brussels
Toronto
Helsinki
Frankfurt
Copenhagen
Zurich
OECD Average
Rome
Randstad-Holland
Melbourne
Vancouver
Turin
Auckland
Hamburg
Tokyo
Birmingham
Montreal
Madrid
Aichi
Leeds
Manchester
Rhine-Ruhr
Lisbon
Osaka
Barcelona
Prague
Lille
Budapest
Warsaw
Fukuoka
Valencia
Busan
Berlin
Athens
Seoul
Monterrey
Naples
Shanghai
Mexico City
Guangzhou
Guadalajara
Puebla
Daegu
Krakow
Istanbul
Beijing
Izmir
Ankara
Wuhan
Changsha
Shantou
Chengdu
Xian
Chongqing
Xuzhou
10,000
20,000
30,000
40,000
50,000
60,000
70,000
Assessing urban performance in China:
Constraints to development of 53 Metropolitan
regions
35,000
Shanghai MR(A)
30,000
Shenzhen MR(A)
Wuxi MR(A)
25,000
Guangzhou MR(A)
Suzhou MR(A)
per capita GDP
Significant positive
correlation between
urbanization and
economic prosperity
Only 16 of 53 MRs
have urbanization levels
over 70%
R2 = 0.83
Dalian MR(A)
20,000
Hangzhou MR(A)
Beijing MR(A)
Tianjin MR(A)
Xiamen MR(A)
15,000
Yantai MR(A)
Tangshan MR(A)
Jinan MR(B)
Zibo MR(B)
Shijiazhuang MR(B)
Changchun MR(C)
Anshan MR(B) Fuzhou MR(A)
Ningbo MR(A)
Changzhou MR(A)
Qingdao MR(A)
Shenyang MR(B)
Taizhou MR(B)
Nanjing MR(B)
Urumqi MR(D)
Harbin MR(C)
Wenzhou MR(B)
Wuhan MR(D)
Jilin MR(C)
Zhengzhou MR(C)
Lanzhou MR(D)
Baotou MR(C)
Changsha MR(C)
Shantou MR(B)
Xian MR(D)
Taiyuan MR(C)
Nanchang MR(C)
Liuzhou MR(C)
Chengdu MR(D)
Luoyang MR(C)
Guiyang MR(C)
Nanning MR(B)
Handan MR(B)
Hohhot MR(C)
Datong MR(B)
Qiqihar MR(D)
Xuzhou MR(A)
Chongqing MR(D)
Linyi MR(A)
Kunming MR(D)
Hefei MR(C)
10,000
5,000
20
30
40
kms to nearest coastal port
(A): < 250 kms
(B): 250 - 500
(C): 500 - 1000
Current trends tends to
favour sprawling metroregions
50
60
70
80
90
non-farming population as % of MR population
(D): > 1000 kms
Pollution and congestion costs
Limit agglomeration economies
100
Assessing urban performance in China:
Constraints to development of 53 Metropolitan regions
P erc entag e of Tertiary E duc ation among population ag e 15+
Huge difference in educational attainment among
Chinese cities. Concentration of human capital in
advanced metro-regions (e.g. Beijing, Shanghai and
Guangzhou), while placing further pressure on
lagging metro regions (e.g. Chongqing)
Low ranking among OECD metro-regions
Tok y o
W as hing ton
D enver
S an
B os ton
L ondon
S eattle
Madrid
S an D ieg o
H els ink i
Minneapolis
New Y ork
O s ak a
C hic ag o
A tlanta
O s lo
S toc k holm
B rus s els
F uk uok a
P hoenix
A ic hi
L os A ng eles
Miami
B arc elona
D alla s
H ous ton
P hila delphia
D etroit
Tampa B ay
P itts burg h
P aris
OE C D
C openhag en
S t.L ouis
Manc hes ter
R ands tadL eeds
B eijing
L y on
P ortland
C leveland
V alenc ia
S tuttg art
B irming ham
S y dney
Melbourne
Nanjing
A thens
A uc k land
D ublin
L is bon
A nk ara
S hang hai
B udapes t
Taiy uan
W ars aw
L ille
P rag ue
G uang z hou
Xiamen
Tianjin
S henz hen
H ang z hou
Iz mir
D alia n
K rak ow
Is tanbul
J inan
H arbin
K unming
A ns han
C hong qing
S hantou
0
0.1
0.2
0.3
0.4
0.5
Becoming and Staying competitive
 Constraints to markets and factors mobility
 Institutional constraints (e.g. trade barriers,
employment restrictions)
 Distortions in land market as a result of
tradition (e.g. highly controlled urban core,
and collective land ownership in suburb)
 Limited transport access between the core
city and suburban towns
Environmental challenges
 420 cities out of 657 had water shortage, 110
had severe shortage (2003)
 53% monitored sections of seven key rivers
had water quality at Class V or lower (2001)
 Motor vehicle growth and increasing NOx
emission pollution
 Land consumption
Key Policy
Challenges
Ensuring equity for vulnerable groups
 Basic welfare for SOEs laid offs became
burden for some municipalities, esp. in
North-eastern provinces
 Housing, employment, education and social
welfare provisions for rural migrants
 Provision of health service, social service ,
pensions for an cities’ aging population
Improving metropolitan governance
 Gaps in planning and provision of urban
services in suburban areas
 Individual jurisdictions invest in their own
small, inefficient infrastructure within
administrative boundaries
 Participation of stakeholders in monitoring
and analyzing metropolitan regions
ban Land Use in Shanghai: 1988 (black) and 2002 (red and black)
Concluding remarks: manage urbanizing China
 China can learn from OECD experiences, both successful and failed ones
 OECD countries need to consider the global impacts of urbanization in
China and could also learn from interesting experiments
 Potential areas for future research
• Harmonise definition of metropolitan regions to facilitate comparative analysis that
could support the development of more efficient public policies
• Indentify the main drivers of China’s metropolitan regions’ economic growth and
complementary policies to support a sustainable and inclusive path
• Develop effective and realistic options for more effective metropolitan governance
Thank you for listening
Any Questions?