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THE GLOBAL GOALS

FOR SUSTAINABLE DEVELOPMENT

CITY PROSPERITY INITIATIVE
&

The 2030 Agenda for Sustainable Development

The high-level plenary meeting of the General Assembly for the adoption of the post-2015 development agenda was held from
25 to 27 September 2015, in New York, during the United Nations summit. The 2030 Agenda for Sustainable Development is
a plan of action for people, planet and prosperity. All countries and stakeholders, acting in collaborative partnership, will imple-
ment this plan. The 17 Sustainable Development Goals and 169 targets, which are integrated and indivisible, demonstrate the
scale and ambition of this new universal Agenda, which balance the three dimensions of sustainable development: economic,
social and environmental.

1 Agenda
5 Main Areas
17 Goals
169 Targets
193 Countries

PEOPLE PLANET PROSPERITY PEACE PARTNERSHIP

The new Goals and targets will come into effect on 1 Janua-
ry 2016, and will guide the decisions we take over the next
fifteen years. All countries will work to implement the
Agenda at the regional and global levels, taking into
account different national realities, capacities and levels of
development, including national policies and priorities.
Governments also acknowledge the importance of the
regional and sub-regional dimensions, regional economic
integration and interconnectivity in sustainable
development. Regional and sub-regional frameworks can
facilitate the effective translation of sustainable
development policies into concrete action at the national
level.

The Sustainable Development Goals

1. End poverty in all its forms everywhere

2. End hunger, achieve food security and
improved nutrition and promote sustainable
agriculture

3. Ensure healthy lives and promote well-
being for all at all ages

4. Ensure inclusive and equitable quality
education and promote lifelong learning
opportunities for all

5. Achieve gender equality and empower all
women and girls

6. Ensure availability and sustainable mana-
gement of water and sanitation for all

7. Ensure access to affordable, reliable,
sustainable and modern energy for all

8. Promote sustained, inclusive and sustaina-
ble economic growth, full and productive
employment and decent work for all

9. Build resilient infrastructure, promote
inclusive and sustainable industrialization
and foster innovation

10. Reduce inequality within and among
countries

11. Make cities and human settlements
inclusive, safe, resilient and sustainable

12. Ensure sustainable consumption and
production patterns

13. Take urgent action to combat climate
change and its impacts

14. Conserve and sustainably use the
oceans, seas and marine resources for sustai-
nable development

15. Protect, restore and promote sustainable
use of terrestrial ecosystems, sustainably
manage forests, combat desertification, and
halt and reverse land degradation and halt
biodiversity loss

16. Promote peaceful and inclusive societies
for sustainable development, provide access
to justice for all and build effective,
accountable and inclusive institutions at all
levels

17. Strengthen the means of implementation
and revitalize the global partnership for
sustainable development

GOAL 11 – Targets

create jobs and prosperity while not straining land and
resources. The challenges cities face can be overcome in
ways that allow them to continue to thrive and grow, while
improving resource use and reducing pollution and poverty.

Cities are hubs for ideas,
commerce, culture, science,
productivity, social
development and much
more. At their best, cities
have enabled people to
advance socially and econo-
mically.
However, many challenges
exist to maintaining cities in
a way that continues to

Lisbon, Portugal © Giulia Lavagna

11.1 By 2030, ensure access for all to
adequate, safe and affordable housing
and basic services and upgrade slums

11.2 By 2030, provide access to safe,
affordable, accessible and sustainable
transport systems for all, improving road
safety, notably by expanding public
transport, with special attention to the
needs of those in vulnerable situations,
women, children, persons with disabili-
ties and older persons

11.3 By 2030, enhance inclusive and
sustainable urbanization and capacity for
participatory, integrated and sustainable
human settlement planning and mana-
gement in all countries

11.4 Strengthen efforts to protect and
safeguard the world’s cultural and natural
heritage

11.5 By 2030, significantly reduce the
number of deaths and the number of
people affected and substantially decrea-
se the direct economic losses relative to
global gross domestic product caused by
disasters, including water-related
disasters, with a focus on protecting the
poor and people in vulnerable situations

Goal 11 – Make cities and human settlements inclusive, safe, resilient and sustainable

Amsterdam, Netherlands © Giulia Lavagna

11.6 By 2030, reduce the adverse per
capita environmental impact of cities,
including by paying special attention to air
quality and municipal and other waste
management

11.7 By 2030, provide universal access to
safe, inclusive and accessible, green and
public spaces, in particular for women and
children, older persons and persons with
disabilities

11.a Support positive economic, social and
environmental links between urban,
peri-urban and rural areas by strengthening
national and regional development
planning

11.c Support least developed countries,
including through financial and technical
assistance, in building sustainable and
resilient buildings utilizing local materials

11.b By 2020, substantially increase the
number of cities and human settlements
adopting and implementing integrated
policies and plans towards inclusion,
resource efficiency, mitigation and adapta-
tion to climate change, resilience to
disasters, and develop and implement, in
line with the Sendai Framework for Disaster
Risk Reduction 2015-2030, holistic disaster
risk management at all levels

Data to not leave anyone behind – SDGs Monitorning needs

The General Assembly recognized that baseline data for
several of the targets remain unavailable, and called for
increased support towards strengthening data collection
and capacity building for Member States, to develop natio-
nal and global baselines where they are non-existent. They
committed to addressing this gap in data collection so as to
better inform the measurement of progress, particularly for
unclear numerical targets.

A set of global indicators is being developed to assist the
follow up and review required by Governments. Quality,
accessible, timely and reliable disaggregated data will be
needed to help with the measurement of progress and to
ensure that no one is left behind. Such data is key to
decision-making. Data and information from existing repor-
ting mechanisms should be used where possible.

DATA REVOLUTION is the opportunity to improve data that is essential for decision-making, accountability and solving
development challenges. Governments and the UN are called to enable data towards playing its full role in the realization of
sustainable development, by closing key gaps in access and use of data: between developed and developing countries and
between private and public sectors.

The data revolution for sustainable development is:

– the integration of new sources of data – such as quali-
tative data, citizen-generated data and perceptions data –
with traditional data to produce high-quality information
that is more detailed, timely and relevant to foster and
monitor sustainable development;

– the increase in the usefulness of data through a much
greater degree of openness and transparency and minimi-
zing inequality in production, access to and use of data;

– more empowered people, better policies, better
decisions and greater participation and accountability,
leading to better outcomes for people and the planet. (1)
(1) IEAG, A World that Counts Mobilising the Data Revolution for sustainable Development,
November 2014

The data revolution for sustainable urban deve-
lopment is:

– data are essential for cities to take correct decisions on
the best policies to adopt and the means used to track chan-
ges and systematically document performance at the outco-
me level. Sustainable urban development is a precondition
to sustainable development;

– cities require monitoring systems with clear indicators,
baseline data, targets and goals to support a city vision and
a long-term plan for sustainable development;

– a global monitoring mechanism, that is adaptable to
the national and local levels; one that provides a general
framework and allow cities to measure progress.

LOCALIZING the 2030 Agenda for Sustainable Development is understood as the role that regional and local governments,
such as states/regions/provinces, metropolitan areas and local authorities, play in the monitoring and implementation of the
new set of sustainable goals.

Monitoring

The monitoring progress on the goals at sub-national level
would allow better assessment of inequalities within
countries, which could include, for example, urban/rural
and regional breakdowns, and where possible, disaggrega-
tion for local authorities and marginal areas, such as slums.
Targets will also be set in a way that makes it easier to track
different types of inequalities, including spatial ones. (2)

Besides monitoring development outcomes, the global
framework proposed for Goal 11 must have a multi-sectoral
rationale that is capable of integrating several sectors of
sustainable urban development. It should cater for the
reinforcement of links of targets, players and sectors. (3)

(2) ODI, ‘Localising’ the Post-2015 agenda: What does it mean in practice?, January 2015

Main Challenges:

– comparability and standardization are crucial, as they
allow data from different sources or time periods to be
combined. Too much data is still produced using different
standards, for example, there is no standard definition of an
“urban” area. Additionally too little data are available at a
level of disaggregation that is appropriate to policy makers
trying to make decisions about local-level allocation or
monitoring equitable outcomes across regions. (1)

– data constraints are more pronounced at the local level
than at the national level. This has obvious resource and
capacity implications in terms of data collection. In fact, it
will require strengthening national statistical offices’ capaci-
ty and administrative systems. (1)
(3) Elard Integrated and Multisectoral approach, http://www.elard.eu/en_GB/integrated-multi-
sectoral- approach

La Paz, Bolivia © Giulia Lavagna

The City Prosperity Initiative – a tool to measure sustainable urban development

UN-Habitat’s City Prosperity Initiative is both a metric and a
policy dialogue, which offers cities from developed and
developing countries the possibility to create indicators and
baseline information. It also serves to define targets and
goals that can support the formulation of evidence-based
policies, including the definition of city-visions and long-
term plans that are both ambitious and measurable.
The City Prosperity Initiative (CPI) not only provides indices
and measurements relevant to cities, it also enables city
authorities, as well as local and national stakeholders, to
identify opportunities and potential areas of intervention for
their cities to become more prosperous.
We live in a world that requires choosing the best and most
sustainable options. The CPI can play a vital role in the
process of informed decision-making.

Growing and ever more complex cities and their inha-
bitants no longer have the option of making decisions
without the benefit of international validated data
and indices.

1. A FLEXIBLE MONITORING FRAMEWORK

The CPI takes into account the contextual needs and
particularities of cities. Although it promotes a new urbani-
zation model that is universal (cities that are compact,
resilient, socially diverse, energy efficient and economically
sustainable), it recognizes the need to be adaptable to
different city and country circumstances, according to diver-
se urbanization challenges and opportunities.

2. A FRAMEWORK THAT PROMOTES INTEGRATION

The CPI promotes integration in the implementation of a
more sustainable urbanization model, in order to address
the environmental, social and economic objectives of sustai-
nability. This integration looks at the mutually reinforcing
aspects of the different components of the urbanization
process.

3. AN INNOVATIVE TOOL BASED ON SPATIAL
ANALYSIS

The CPI structure provides a wealth of new analytical tools
based on spatial indicators. New indicators such as street
connectivity, public space, agglomeration economies provi-
de clear spatial distributions that help increase value
judgment and support decision-making.

4. A MULTI-SCALE DECISION-MAKING TOOL

The CPI objective is to support decision- making for multi-
scale levels of government ranging from national urban
policies to regional and metropolitan strategies; and
city-wide interventions to sub-city districts or neighborho-
ods. The CPI gives decision-makers the ability to make
adequate and evidence-based decisions from a territorial
perspective, thus articulating different tiers of government
and sectoral interventions in urban areas.

Main Functions

NATIONAL. The CPI supports the development and imple-
mentation of integrated national urban policies. Decision-
makers are provided with the knowledge to make oppor-
tune decisions about their cities small, medium or large – as
part of a national system of cities. This helps to amalga-
mate the dispersed energy and potential of urban centers,
establishing a synergetic connection between urbaniza- tion
and national development. This is the case with Mexi- can,
Colombian and Saudi Arabia programs.

CITY. The CPI produces information at city level, and when
data allows, at sub-city level. This information is critical to
support local decision-making in key priority areas of
development, such as the strengthening of urban legislation
and systems of governance, harnessing the urban economy
and enhancing urban planning.

METROPOLITAN. The CPI provides information at the
regional and metropolitan levels building linkages between
municipal governments, articulating responses that contem-
plate city regional development and better integration of
sectors. The Metropolitan CPI can detect which municipali-
ties or districts are more advanced in the prosperity path,
proposing solutions for a more harmonious urban
development. The metropolitan area of Guadalajara is a
good example.

More than 300 cities around the world

America
Buenos Aires
Ciudad Obregon
Fortaleza
Guadalajara
Guayaquil
Guatemala City
Lima
Medellin
Mexico City
Montreal
New York
Panama City
Quito
Sao Paulo
Toronto

Africa
Accra
Addis Abeba
Cape Town
Dar es Salaam
Harare
Kampala
Lagos
Lusaka
Mekelle
Nairobi

Asia and Oceania
Abha
Almaty
Bangkok
Hong Kong
Jakarta
Kathmandu
Makkah
Manila
Melbourne
Osaka
Sydney
Tokyo
Yerevan
Ulaanbaatar

Europe
Amsterdam-Utrecht
Athens
Barcelona
Berlin
Brusels
Budapest
Copenhagen
Dublin
Helsinki
Lisbon
London
Madrid
Manchester
Milan
Oslo
Paris
Prague
Stockholm
Vienna
Warsaw
Zurich

Cuzco, Perù © Giulia Lavagna

The City Prosperity Initiative – a Global Monitoring Framework for Goal 11 and the SGDs

A comparative analysis of the proposed targets for Goal 11
against the City Prosperity Index shows very high conver-
gence among the possible indicators. In general terms, it is
clear that all of the targets of Goal 11 can be covered by the
CPI framework and indicators.
The CPI, as a local monitoring tool (and composite index),
can be used to identify, quantify, evaluate, monitor and
report on progress made by cities and countries on Goal 11.
Undoubtedly, the adoption of the CPI framework and
indicators represents an added value, with several advanta-
ges.
UN-Habitat and development partners are convinced that
Goal 11 cannot be achieved in isolation, nor can the Goals
of the SDGs. In this sense, while the CPI is proposed as a
monitoring tool for Goal 11, several other Goals can be
localized and monitored at city level.
The CPI provides the framework of analysis of the interrela-
tions of Goal 11 and strategic targets across the SDGs that
have an urban dimension.

CPI FRAMEWORK ADDED VALUE
– Propose a systemic approach of the city. The CPI offers
a holistic view of sustainable urban development. It allows
establishing and understanding interrelations between
different dimensions of city development.

– Provide a single composite value. As a composite Index,
the CPI enables the understanding of the state of
development of cities in a more integrated manner. This
helps local and national governments to visualize how
inclusive, safe, resilient and sustainable cities and human
settlements are.

– Establish global benchmarks. The CPI methodology has
established global benchmarks for each one of the indica-
tors, with sound standardization methods that enable
comparisons among different indicators.

– Create baseline data and information. Cities already
implementing the CPI have been able to create baseline
data, propose local commitments for improvement and
monitor progress overtime.

– Provide a global platform for comparability. The CPI
offers a platform for comparability among cities, as well as
within different countries. This is achieved through the use
of various indicators that are homologated and grouped by
thematic targets.

– Identify priorities of sustainable urban development.
The CPI allows the disaggregation of the different compo-
nents of sustainable development in such a manner that it
is possible to identify progress and deficits. By isolating key
development issues hindering success, it is possible to adopt
appropriate policies and corrective measures.

– Provide evidence-based for policy-making and
accountability. The CPI is not only a metric, it is also a
policy dialogue that supports the formulation of more
informed policies.

– Create local/national monitoring systems. The CPI
offers the possibility for local and national governments to
establish their own monitoring mechanisms, empowering
them to monitor and report in a systematic manner.

Conceptualizing Prosperity

Productivity
A prosperous city contributes to economic
growth and development, generating
income, employment and equal opportuni-
ties that further provide adequate living
standards for the entire population.

Equity and Social Inclusion
A city is only prosperous to the extent that
poverty and inequalities are minimal. No city
can claim to be prosperous when large
segments of the population live in abject
poverty and deprivation. This involves
reducing the incidence of slums and new
forms of poverty and marginalization.

Infrastructure
A prosperous city deploys the infrastructure,
physical assets and amenities – adequate
water, sanitation, power supply, road
network, information and communications
technology, etc. – required to sustain both
the population and the economy, and provi-
de better quality of life.

Quality of life
Prosperous cities provide amenities such as
social services, education, health, recreation,
safety and security required for improved
living standards, enabling the population to
maximize individual potential and to lead
fulfilling lives.

Environmental Sustainability
The growth of cities and their economic
development do not destroy or degrade the
environment; instead, the city’s natural assets
are preserved for the sake of sustainable
urbanization. Well-planned cities promote
environmental sustainability.

Governance and Legislation
Cities are best able to combine sustainability
and shared prosperity through effective
urban governance and transformational
leadership, deploying appropriate and effec-
tive policies, laws and regulations, and
creating adequate institutional frameworks
with strong local institutions and sound
institutional arrangements.

Lima, Peru © Giulia Lavagna

GOAL 11 and The City Prosperity Initiative

11.1 Adequate, safe and affordable housing

11.2 Accessible and sustainable transport systems for all

11.3 Inclusive and sustainable urbanization

11.4 Safeguard the world’s cultural and natural heritage

11.5 Reduce the number of people affected by disasters

11.6 Reduce the environmental impact of cities

11.7 Provide universal access to safe public spaces

11.a Support links between urban, peri-urban and rural
areas

11.b Increase integrated policies and plans towards
mitigation and adaptation to climate change

11.c Building sustainable and resilient buildings utilizing
local materials

1. Economic Strength

2. Employment

3. Economic Agglomeration

4. Housing Infrastructure

5. ICT

6. Urban Mobility

7. Public Space

8. Safety and Security

9. Land Use

10. Economic Equity

11. Social Inclusion

12. Gender Inclusion

13. Air Quality

14. Waste Management

15. Energy

16. Institutional Capacity

17. Municipal Finance

18.Governance of Urbanization

CPI SUB-DIMENSIONSGOAL 11 TARGETS

SDG WITH
URBAN BASED TARGETSCPI DIMENSIONS

GOVERNANCE AND LEGISLATION

ENVIRONMENTAL SUSTAINABILITY

EQUITY AND SOCIAL INCLUSION

QUALITY OF LIFE

INFRASTRUCTURE

PRODUCTIVITY

The SDGs and The City Prosperity Initiative

8.1.1 City product per capita
8.2.1 Growth rate per employment
8.3.1 Informal employment
8.5.2 Unemployment rate
9.2.1 Manifacturing employment

3.6.1 Traffic fatalities
6.1.1 Access to improved water
6.2.1 Access to improved sanitation
7.1.1 Access to electricity
9.c.1 Mobile network coverage
17.8.1 Internet access

15.1.2 Forest (green areas) as a percentage of total land area
16.1.1 Homicide rate
16.1.3 Population subjected to violence

1.1.1 Poverty rate
5.5.1 Women in local government
8.5.1 Gender wage gap
8.6.1 Youth unemployment
10.1.1 Growth rate 40%

3.9.1 Population exposed to outdoor air pollution
6.3.1 Waste water treatment
7.2.1 Share of renewable energy
12.5.1 Solid waste recycling share

9.a.1 Investement capacity
16.6.1 Local expenditure efficiency
17.17.1 Public-private partenrship

The City Prosperity Initiative – a Global Monitoring Framework for Goal 11 and the SGDs

– Productivity. This is the only dimension that is not
comprehended in the SDG 11, but it has specific indicators
in the CPI that includes SDG 8 (Economic growth), SDG 9
(Infrastructure, industrialization and innovation);

– Infrastructure. The revised version of the CPI includes
SDG 11 (11.2 Accessible and sustainable transport systems
for all), SDG 3 (Healthy lives and well-being) SDG 6 (Water
and sanitation), SDG 7 (Modern energy), SDG 9
(Infrastructure, industrialization and innovation) and SDG
17 (Global partnership);

– Quality of life. The revised version of the CPI includes
SDG 11 (11.3 Inclusive and sustainable urbanization, 11.5
Reduce the number of people affected by disasters, 11.7
Provide universal access to safe public spaces), SDG 15
(Terrestrial ecosystems) and SDG 16 (Peaceful and inclusive
societies);

Lisbon, Portugal © Giulia Lavagna

All 10 targets and indicators of SDG Goal 11
are integrated in the CPI;

23% of all SDGs targets that can be measured
at the local level are covered by the CPI;

The City Prosperity Index can therefore be
used to identify, quantify, evaluate, monitor and
report on progress made by cities on the 2030
Agenda for Sustainable Development.

– Equity and Social Inclusion. The revised version of the
CPI includes SDG 11 (11.1 Adequate, safe and affordable
housing), SDG 1 (End poverty), SDG 5 (Gender equality),
SDG 8 (Economic growth), and SDG 10 (Reduce inequality);

– Environmental Sustainability. The revised version of the
CPI includes SDG 11 (11.6 Reduce the environmental
impact of cities), SDG 3 (Healthy lives and well-being), SDG
6 (Water and sanitation), SDG 7 (Modern energy) and SDG
12 (Sustainable consumption and production);

– Governance and Legislation. The revised version of the
CPI includes SDG 11 (11.4 Safeguard the world’s cultural
and natural heritage, 11.a Support links between urban,
peri-urban and rural areas, 11.b Increase integrated policies
and plans towards mitigation and adaptation to climate
change, 11.c Building sustainable and resilient buildings
utilizing local materials), SDG 9 (Infrastructure, industrializa-
tion and innovation), SDG 16 (Peaceful and inclusive socie-
ties) and SDG 17 (Global partnership);

SDGs and the Dimensions of Prosperity

Conclusions

The City prosperity Initiative
United Nations Human Settlements Programme

Info: Regina Orvañanos, regina.orvananos@unhabitat.org

lable at ScienceDirect

Habitat International 45 (2015) 3e9

Contents lists avai

Habitat International

journal homepage: www.elsevier.com/locate/habitatint

A framework for ‘City Prosperity Index’: Linking indicators, analysis
and policy

Cecilia Wong*

Centre for Urban Policy Studies, School of Environment, Education and Development, The University of Manchester, Manchester M13 9PL, United Kingdom

a r t i c l e i n f o

Article history:
Available online 22 July 2014

Keywords:
City Prosperity Index
UN-Habitat
Indicators
Urban planning
Spatial dynamics
Urban change

* Tel.: þ44 161 275 0680.
E-mail address: Cecilia.wong@manchester.ac.uk.

http://dx.doi.org/10.1016/j.habitatint.2014.06.018
0197-3975/

a b s t r a c t

This paper argues for a more robust and flexible framework to develop the ‘City Prosperity Index’ (CPI),
one which is able to connect indicators and analytical intelligence with the policy needs of urban
planners and government strategists. The adoption of a more progressive and balanced agenda of
‘people-centred’ urban prosperity in the UN-Habitat’s newly developed CPI has already led to a more
holistic approach to integrating productivity, infrastructure, quality of life, equity and social inclusion,
and environmental sustainability into a coherent framework. Building on this international agenda, there
is still scope to critically revise and improve the conceptual and methodological framework of the CPI,
probably in an incremental manner, to make it a more tailored policy instrument that can truly address
the different sets of challenges faced by cities in different regions under different socio-spatial contexts to
achieve sustainable prosperity.

Introduction

The measurement and use of quantitative indicators is closely
intertwined with the prevailing policy regime. It is because of this
pragmatic purpose that the policy concept to be measured is not
static but undergoes a dynamic process of problem definition
(Greer, 1969). Over the years, supranational organisations have
shown interest in assessing the state of urban development across
different nations. The World Bank (2013) has compiled the annual
world development indicators series since 1960 to monitor the
achievement towards international development goals. Since 1990,
the United Nations (2013) has published the Human Development
Index (HDI) to rank countries into four levels of human develop-
ment. Since early 2000s, Eurostat has periodically developed ‘Ur-
ban Audits’ to improve the European Commission’s knowledge of
quality of life in urban areas across Europe (EC, 2000). The Asian
Development Bank has also endeavoured to compile the Cities Data
Book to inform the management of the urban sector in Asia
(Westfall & de Villa, 2001).

Recent international policy discourse has moved away from
national and regional perspectives to focus on cities as drivers of
the growth agenda. This shift is closely related to the unstoppable
pace of urbanisation in developing countries. According to the 2011
United Nations figures, over two-thirds of the world population is

forecast to be urban dwellers by 2050; though the urbanisation
level varies in different regions and largely associates with their
development levels (UNDESA, 2012). The latest proposal to develop
a City Prosperity Index (CPI) by the UN-Habitat (2012: iv) came at ‘a
time of crisis’, as introduced by Joan Clos, the Executive Director of
UN-Habitat. The global financial crisis and the challenges brought
by climate change call for drastic solutions; cities are seen as the
driver to move from such crises towards the prosperity pathway.

The critical questions to be asked are: (1) what is distinctive
about this new CPI; (2) what are the methodological and concep-
tual challenges in developing a robust index to measure city
prosperity; and (3) what are the key parameters for developing a
robust and flexible indicator framework to measure and bench-
mark urban prosperity? This paper aims to address these key
questions and, more importantly, to identify the key underpinning
principles to improve the CPI framework to connect indicators and
analytical intelligence with the policy needs of urban planners and
government strategists.

Following this introduction, the paper will first highlight the key
characteristics and provide a critical appraisal of the CPI presented
in the State of the World’s Cities 2012/13 report (SoWC) (UN-Habitat,
2012). It will then identify some key conceptual and methodolog-
ical challenges to be addressed for future refinement of the CPI. The
fourth section will discuss the principles and ground rules that can
potentially be used to underpin the development of a robust and
policy-oriented indicator framework for the CPI by drawing from
international experience on indicators research. The final section

Delta:1_given name

mailto:Cecilia.wong@manchester.ac.uk

http://crossmark.crossref.org/dialog/?doi=10.1016/j.habitatint.2014.06.018&domain=pdf

www.sciencedirect.com/science/journal/01973975

http://www.elsevier.com/locate/habitatint

http://dx.doi.org/10.1016/j.habitatint.2014.06.018

C. Wong / Habitat International 45 (2015) 3e94

concludes by drawing out some wider methodological and practical
implications for the measurement of urban prosperity.

The wheel of prosperity: an integrative and progressive
agenda

The conception of the CPI comes with a strong assertion of the
vitality and transformative dynamics of cities and thus their
importance as ‘the world moves into the urban age’ (UN-Habitat,
2012: v) for a new type of city ‘that is a “good”, people-centred …
shedding off the inefficient, unsustainable forms of functionalities
of the city of the previous century’ (UN-Habitat, 2012: iv). These
inspirational qualities, in many ways, resemble the underpinning
rationale of the HDI to ‘shift the focus of development economics
from national income accounting to people centred policies’ (ul
Haq, 1995 quoted in Fukda-Parr, 2003: 302) by measuring life ex-
pectancy, adult literacy rate, GDP and purchasing power parity (UN,
2013). The CPI sets out with a strong critique of the ‘GDP fetishism’
and argues for the need to move towards measuring the broader
conception of human and societal well-being.

By putting prosperity within a ‘people-centred’ agenda, UN-
Habitat advocates its own approach by defining a prosperous city
as one that possesses these essential qualities:

� Productivity: contributes to economic growth and
development;

� Infrastructure: deploys infrastructure, physical assets and
amenities;

� Quality of life: provides social services for improved living
standards and guarantees safety and security;

� Equity and social inclusion: ensures equitable distribution of
wealth and benefits and eradicates poverty; and

� Environmental sustainability: protects the urban environment
and preserves natural assets while creating wealth.

These five dimensions of prosperity (see Fig. 1) are regarded as
the spokes of the wheel of prosperity, each of which is measured by

Fig. 1. The wheel of urban prosperity.
Source: UN-Habitat (2012), Figure 1.1 (p.15).

a number of indicators or sub-indices. The operational definitions
of the five dimensions of prosperity are provided in Table 1. It is
important to note that, rather than developing a total new set of
indicators, those in the HDI are used to re-calculate the productivity
and quality of life components of the CPI. This will allow continuity
and cross-comparison between the HDI at the national level and
the two components of the CPI at the city level.

One can argue that such an all-embracing definition of pros-
perity makes it apply to everything and therefore difficult to
deliver. Some may even argue that the broadened notion of pros-
perity by the UN-Habitat may strengthen economic growth as an
acceptable international policy discourse amidst the global eco-
nomic crisis. Apart from advocating a more balanced and integra-
tive framework for measuring prosperity, the UN-Habitat places
‘government, institutions, laws and urban planning’ at the centre to
achieve sustainable prosperity. Recognising that it will be difficult
for any city to achieve all five aspects on an equal basis at any point
in time, policy intervention is thus required to restore the balance.
The use of a wheel provides a graphic analogy (see Fig. 1): the hub
of the wheel represents urban power and innovative policies,
which provides balance and structure to the five inter-dependent
prosperity spokes to drive forward along the road of ‘prosperity’.
Apart from law and government institutions, urban planning is
seen as vital in providing a dynamic hub of city development. Urban
planning provides an integrative perspective by overcoming sec-
toral policy silos and provides an inclusive agenda by balancing the
nexus between different dimensions of urban functionalities
(Wong & Watkins, 2009).

Another distinctive development in the SoWC report is the
strong articulation of cities as engines of prosperity. Both the World
Bank and the United Nations focused on the national level when
compiling composite indices to benchmark performance in the
past. The agenda of seeking spatial equality has shifted to the urban
level, which signifies the importance of adopting more localised
and contextualised approaches of growth and development. The
notion that global challenges have to be met with local responses
has singled cities out as ‘ready, flexible and creative platforms’ to
provide remedy in ‘a pragmatic, balanced and efficient way’ (UN-
Habitat, 2012: 11).

This discussion shows that there are some very positive features
of the CPI. However, it is important to question the extent to which
it addresses the pitfalls of using aggregate indices to measure
development. There are other urban development indices pro-
duced by the European Commission, the Asian Development Bank
and the United Nations. Despite these efforts, our understanding of
urban change is still limited in three ways: firstly, most reports tend
to have partial global geographic coverage of specific regions (e.g.

Table 1
City Prosperity Index: definition and variables.

Productivity index It measures the total output of goods and services
(value added) produced by a city’s population during a
specific year by including variables such as capital
investment, formal/informal employment, inflation,
trade, savings, export/import and household income/
consumption.

Quality of life index It is a combination of three sub-indices: education,
health and public space.

Infrastructure
development index

It combines two sub-indices: infrastructure proper and
housing.

Equity and social
inclusion index

It has three sub-indexes: air quality (PM10), CO2
emissions and indoor pollution.

Environmental
sustainability index

It combines measures of inequality of income/
consumption (Gini coefficient) and inequality of access
to services and infrastructure.

Source: UN-Habitat, 2012: 14.

C. Wong / Habitat International 45 (2015) 3e9 5

Asian Cities Data Book); secondly, many tend to focus on ranking by
measuring performance at the national level (e.g. HDI); and thirdly,
most provide a snapshot of a particular aspect of social change. The
launch of the CPI does seem to address these issues by creating an
all-embracing index to measure the urban prosperity of cities
across the globe. This, in many ways, represents a step-change of
how we benchmark and compare urban prosperity. While the
principles and measurement framework are identified in the SoWC
report, there are still significant knowledge gaps in the framing and
operationalization of ‘prosperity’. The next section tries to dissect
the conceptual and methodological challenges of making CPI more
than just a measurement tool to inform policy-making under
different socio-spatial contexts.

Conceptual and methodological challenges: what is in store?

Urban change is a continuous process of spatial transformation.
Global financial flows and the use of telecommunications tech-
nologies have altered the international economic development
landscape in which cities compete. At the same time, long-standing
economic decline and social problems in urban areas have triggered
labour market restructuring and other socio-cultural adjustments.
The outcomes of the process of change have been mixed and are
contingent upon the endowment and exploitation of assets and
resources of the urban areas and their wider functional hinterlands.

(1) Openness of the concepts and their complex interactions

The use of a multi-dimensional wheel to integrate productivity,
infrastructure, quality of life, equity and social inclusion, and
environmental sustainability within the overarching concept of
prosperity shows the commitment to achieve a more holistic form
of urban prosperity and development. The five dimensions are
themselves fuzzy and open concepts, subject to very different un-
derstanding and interpretations (Wong, 2006) and will require trial
and error to make them workable (Innes, 1990). It is the complexity
of the development processes of the five dimensions, and the
fuzziness of these concepts, that make it a difficult task to establish
their inter-relationships. However, it is more important to under-
stand how the outcome of sustainable prosperity can be achieved,
and why it is happening, than simply to measure it.

Concepts such as environmental sustainability and social
exclusion encapsulate both the process of change and the state of
development. The operation of different aspects of prosperity may
reinforce and enhance the restructuring process of cities (such as
quality of life and productivity), but their interaction can also be
contentious (such as achieving economic growth and a sustainable
environment) (Wong & Watkins, 2009). For example, the causal
relationship between quality of life and economic prosperity is a
difficult and controversial topic. Castells (1989: 52) regards quality
of life as the result of the characteristics of the high tech industry in
Silicon Valley rather than the determinant of its location pattern.
Findlay, Rogerson, and Morris (1989) also fail to find any significant
correlation between the Quality of Life Index and the Local Pros-
perity Index in British cities. Wong (2001) finds that quality of life is
important to local economic development provided that the
traditional factors of production are already in place. Quality of life
was found to be more important in shaping the reproduction space
than the production space of cities. Likewise, Boddy (1999) finds
that a lack of social cohesion may not impede competitiveness;
cities that ‘perform’ well still tend to be an obstinate persistence of
diverse forms of social exclusion. Rapid economic growth and
exclusion can often coexist within the same urban space (Wong
et al., 2011). New York is the case in point. Ranked the world’s
second most prosperous cities (UN-Habitat, 2012: 19), its

performance on the Equity Index was far below the other di-
mensions of prosperity.

In addressing complex issues with multiple objectives and
interlocking activities like sustainable prosperity, urban planning
and policy intervention have to deal with boundaries in a flexible
way by addressing ‘polyrationality’ and understanding how cities
are socially produced by a wide variety of actors and practices
(Davy, 2008). Many of the concepts entangled in the CPI fall into
what Rittel and Webber (1973) called ‘wicked problems’ that are
embedded in a dynamic social context, which makes each problem
unique but also difficult or impossible to solve (Rae & Wong, 2012).
The concept of quality of life is a particularly problematic one as the
outcome of a people-centred notion of prosperity, to many people,
will be synonymous with quality of life.

(2) Quality of data and estimates used to develop the composite
indices

Since the variables to compute the productivity and quality of
life sub-indices are based on indicators used in the HDI, it is useful
to revisit the methodology used to compile those indicators. Ac-
cording to Human Development Report (UNDP, 2001: 137), ‘when
data are missing for one component, a country will still be included if a
reasonable estimate can be found from another source. As a result of
revisions in data and methodology over time, the HDI values and ranks
are not comparable across editions of the Report’. In general, a wider
range of indicators tends to be found at the country level than for
units at lower spatial scales. The challenge of getting accurate data
at the city level across the world will be much higher. When esti-
mated data of different indicators are combined to create sub-
indices, the errors and bias involved can be exaggerated. The ef-
fects may vary across different sub-indices and geography, as the
level of problems encountered in compiling reliable data will vary.

There is a need to understand these methodological issues as
they will cumulatively compound the problems that affect the
robustness and reliability of different sub-indices and the aggre-
gated CPI rankings. This will also limit the ability to conduct change
analysis to ascertain the dynamic performance of cities towards
achieving sustainable prosperity over time. In order to improve the
robustness of the measurement, there are three key questions to be
addressed: (a) How to get accurate data at the city level across the
world? (b) Will the robustness and reliability of different sub-
indices vary? (c) Is there any systematic measurement error
against the value computed for cities in any particular regions?
Meanwhile, the UN-Habitat should provide more discussion on the
methodological limitations and give “health warnings” on the in-
terpretations of the rankings and the analysis in the report.

The difficulties encountered in collecting the array of data for
cities at different stages of development with very different socio-
economic and political circumstances cannot be overlooked. Even
in countries with a strong monitoring culture and established data
collection practice, such as the USA and the UK, the development of
a coherent and reliable set of indicators for urban areas is not a
simple task (Wong, 2006). There was a more honest and open
discussion in the Cities Data Book project and the problems iden-
tified in the Asian exercise are not so different from those faced in
the UK (Westfall & de Villa, 2001). The challenges to compile data
for a global CPI will be even greater, as a high degree of compati-
bility and consistency is more difficult to achieve with a large
number of cities in developing countries that have less-developed
statistical systems. The cost of collecting the relevant data for the
CPI currently falls on the respective city governments and this has
proved to be a major problem as many cities have not provided data
and are excluded from the analysis. This issue was found to be
problematic even in Europe when compiling indicators for Urban

C. Wong / Habitat International 45 (2015) 3e96

Audit II (RWI, DIFU, NEA, & PRAC, 2010) e the response rates from
Germany, the Netherlands, Belgium and Luxembourg were high,
but very low from the rest of Europe. This links to the question of
how often such a data collection exercise should be carried out to
update the CPI. There is an obvious trade-off between the frequency
and cost of data collection. These more pragmatic issues are not
addressed by the UN-Habitat other than the fact that the CPI will be
developed in an incremental manner.

(3) Weighting and analytical methods

The development of composite sub-indices and an overall index
tend to be the default options used to simplify an indicator set, as it
provides a hard and fast technical synthesis (Wong, 2006). The
challenge is then how to choose the most robust ‘weighting’ system
to combine the indicators. The study by Bagolin and Comim (2008)
demonstrates the drastic change in the ranking of the HDI by
applying different weighting systems to the indicators. It is thus
important to carry out sensitivity analysis (e.g. Coombes, Wong, &
Raybould, 1993; Coombes, Raybould, Wong, & Openshaw, 1995)
of the assembled database to identify differences in the outcome
produced by alternative weighting approaches before making the
final judgement. The UN-Habitat has not clearly explained the
methodology and the weighting schemes used to create the five
prosperity indices and the overall index in the report. It only de-
clares that, ‘Although more refinement is still needed in terms of
what indicators are included in the index and with which respec-
tive weightings, those that have been selected offer the possibility
of disaggregating the different dimensions of prosperity, in the
process identifying policy intervention areas’ (UN-Habitat, 2012:
18). Since the approach used to derive weighting schemes is always
a contentious issue and subject to debate, it would be helpful for
the United Nations to open up the discussion on this methodo-
logical black box.

(4) Spatial dynamics and definition of cities

The most powerful change in our urban system has been
continuing spatial decentralisation. In the developing world, a
defining feature of cities ‘is an outward expansion far beyond formal
administrative boundaries, largely propelled by the use of the auto-
mobile and land speculation. ….. that urban land cover grew, on
average, more than double the growth of the urban population’ (UN-
Habitat, 2012: 28). In order to harness the potential pool of a pro-
fessional workforce and other development resources, the devel-
opment of cities has to be seen within the broader spatial context in
which they closely interact and connect (Robson, Parkinson, Boddy,
& Maclennan, 2000).

This raises the thorny issue of the appropriateness of measuring
city prosperity by following administrative boundaries. The prob-
lem of using administrative areas is that it may distort the spatial
dynamics operating between a city and its wider spatial context. In
the under-bounded city (see Fig. 2), the administratively defined
city is smaller than the physical urban aggregate, while the oppo-
site is true for an over-bounded city (Carter, 1981). The use of
administrative boundaries, rather than economic functional areas
(for example, labour and housing markets), can give an under-
stated/exaggerated impression of urban performance. As illustrated
in Fig. 2, with the same spatial patterns of prosperity, the different
configurations of district boundaries within the city can lead to very
different measurement outcomes. The growth of urban areas
beyond their administrative boundaries into surrounding hinter-
lands has also led to Castells (2007: 1) proclaiming that ‘the cate-
gory (“the city”) has become theoretically and practically obsolete’.
This has characterised the development patterns of many Chinese

cities (Cheng, Bertolini, Clercq, & Kapoen, 2013; Tao, Su, Liu, & Cao,
2010; Zhang, 2000). There is thus a need to define cities in a more
meaningful way to take into account the urban core and hinterland
relationship (Deas & Giordano, 2001) and to avoid the misleading
risks caused by the wrong delimitation of areas.

(5) Relationship between urban change and external global forces

The pervasive forces of globalisation act as macro agents to
accelerate the restructuring process of complex urban system and
have led to spatial inequality of development and stimulated local
actors to formulate their own strategies. While the important role
of cities as the engine of growth and the centrepiece to address
global crises is emphasised in the report, the CPI does not help to
disentangle the different driving forces of change or to examine
their interactive effects. Urban change can be due to structural
changes and historic inertia at the local level, as well as external
factors from national and global forces (Rogerson, 1999), or indeed
the interaction of internal and external factors. The SoWC report
provides some analysis on the associated performance between
national and city levels, but it is not sufficient to disentangle the
interactive effects across multiple spatial scales.

The application of statistical techniques, such as principal
component analysis in Urban Audit II (RWI et al., 2010), to explore
the relationships of the full indicator set and to detect the under-
lying dimensions of different aspects of prosperity (Wong, 2002)
would be a worthwhile exercise. Likewise, in the Cities Data Book
(Westfall & de Villa, 2001), different analytical methods were used
to carry out crosscutting, thematic analysis and benchmarking of
urban performance across the 18 Asian cities. It is important to
develop rigorous analyses to underpin the nature of interactions
between the different prosperity dimensions of the wheel and to
validate the robustness of the five-fold classification. It will remain
important to monitor issues at different spatial levels within a
coherent framework if the CPI is to be truly relevant for city man-
agement. This also links to the previous argument over the problem
of using convenient city administrative boundaries. Administrative
boundaries do not necessarily reflect functional areas in terms of
social, economic and environmental linkages. There is, therefore, a
need to build up monitoring capability to organise, analyse and
display data at varying spatial scales.

(6) Tracking progress and policy-making

In order to inform urban planning and to develop an institu-
tional framework, it is important to interpret the degree of progress
made by a city. The use of benchmarking provides a yardstick to
gauge the relative performance of a city by assessing its progress
and achievement against other comparator areas or the national
average. However, the use of the HDI to produce national rankings
has been much criticised for its failure to provide more nuanced
and contextualised interpretation of such rankings (Bagolin &
Comim, 2008). It is impossible to establish general non-
contextual laws since different areas perform under very diverse
sets of socio-economic and political circumstances. This strongly
suggests that the comparators should be among areas with similar
circumstances. In order to confront this dilemma, a structur-
eeperformance model was proposed (Carlisle, 1972) to analyse the
differential socio-economic contexts (structure) against which the
urban area performs (performance). Such an analytical framework
does not aim to develop a causal model, but will provide a
distinction between the more descriptive nature of the socio-
economic and historical conditions (structure) and the goal and
outcome-oriented performance measures (performance). However,
due to the complexity and the intertwining of different socio-

Fig. 2. Spatial boundaries and indicator values.
Source: author.

C. Wong / Habitat International 45 (2015) 3e9 7

economic issues, it is impossible to operationally untangle the web
of conditions and outcomes (Wong, 2002; Wong et al., 2004).

The use of benchmarking aims to assess relative performance,
should it be economic growth under a buoyant economy or the
resilience to economic decline during a period of recession, by
taking into account their operating circumstances as well as the
external forces of change. Taylor (2000) argues that, whilst
benchmarking against each other and against future improvements
is valid, this process can be exclusive and distort attention if simply
focussing on particular negative aspects of urban problems. The
publication of rankings will lead to the production of league tables
and, in some cases, led to the stereotyping of particular cities and
regions. This suggests that when analysing indicators, one has to be
sensitive to the presentation and dissemination of the findings
(Wong, 2006). Composite indices have the advantage of avoiding
information overload, but they tend to conceal the detailed infor-
mation on the diversity of performance over different aspects of
urban change. While the UN-Habitat argues that the CPI allows
urban authorities to have a handle on balancing different aspects of
prosperity, the use of composite sub-indices rather than displaying
individual indicator values has significantly reduced the amount of
policy intelligence.

Analytical principles of a policy-oriented indicator framework

The conceptual and methodological challenges of developing
the CPI into a robust policy instrument are not easily resolved
within a short period of time. The UN-Habitat has rightly adopted a
gradual approach to developing the CPI. However, the SoWC report
mainly mentions refinement with respect to indicators and
weighting systems. The discussion above suggests that the chal-
lenges are more than a technical fix on data and weighting
schemes, but it should involve further theoretical thinking over the
conceptualisation of different aspects of prosperity; the causal
relationship between different driving forces operating at multi-
spatial levels; the pragmatic concerns associated with data collec-
tion responsibility and costs; and capacity building with

stakeholders to ensure the development of CPI as a policy relevant
instrument.

One major ingredient missing from the SoWC report is a clear
conceptual understanding of the overarching indicator framework
and the analytical principles that underpin the development of this
framework. This is particularly important if the CPI is to be devel-
oped and adjusted over time for use as an urban management tool.
Based on previous research on developing indicators to inform
urban planning and local development (Rae & Wong, 2012; Wong,
2006; Wong & Watkins, 2009), a set of key analytical principles are
proposed for the future development of CPI. The seven proposed
principles are:

1. Consistency and comparability: data have to be collected on a
common spatial and temporal basis, under a clearly identified
set of definitions for both the indicators and the spatial defini-
tion of cities to allow meaningful analysis. The SoWC report is
unclear about the eligibility criteria for including or excluding a
city to be involved in the study. There is obvious political
sensitivity in dealing with such issue. However, ducking it rather
than working with stakeholders to find a satisfactory solution
will not help to achieve the promise made in the report.

2. Tracking progress and change: the analysis of the indicators and
sub-indices of different aspects of the CPI should provide clear
narration of the nature and direction of progress and should not
be subject to open interpretation. There is a need to ensure that
the indices are constructed in a way that will allow policy-
makers and stakeholders to track changes made in different
aspects of prosperity to steer policy interventions.

3. Benchmarking and cross-comparison: meaningful interpreta-
tion of a city’s indicator values can be enhanced by making
reference to the performance of other cities that share similar
socio-economic and political conditions. The idea of a struc-
tureeperformance model should be considered to establish the
baseline contextual conditions of all cities. Those with similar
circumstances could then be grouped together for comparison
over their prosperity performance. This means that the analysis

C. Wong / Habitat International 45 (2015) 3e98

should compare and contrast cities with similar conditions
rather than their overall CPI ranks.

4. Multi-units of analysis: due to the complexity of urban change, it
is important to develop a multi-spatial framework to provide a
flexible analytical structure for assessing city performance
against the wider national and regional contexts. The report has
already provided some analysis at the national and regional
levels, but they are not consistent and systematic. A fully
developed multi-spatial level analysis would help to develop
more informed policy intelligence.

5. Exploration of co-variations and interactive effects: there is a
need to provide sufficient details across different aspects of
urban prosperity as well as including contextual information to
facilitate the analysis of co-variations and interactive effects
across different dimensions of city prosperity. The idea of using
principal component analysis to perform some exploratory
analysis could be a very good starting point.

6. Use of soft indicators and qualitative information: while the CPI
is largely based on quantitative data, the analysis of the indicator
and index values will require the use of qualitative data and
other soft information to assess progress or to enrich in-
terpretations. While brief comments were made in the SoWC
report for certain cities, it would be very helpful to have sys-
tematic commentaries on each city. It would be useful to
develop a pen picture for each city and their associated spatial
contexts at national and global regional levels, complemented
by succinct qualitative commentaries.

7. A communicative and learning framework: to embed the CPI
into urban planning and policy making processes will require
the participation of a wide range of urban partners and
stakeholders. This means that the development of the CPI in-
dicator framework has to focus on the communication of policy
intelligence that can be shared among key partners and
stakeholders to facilitate policy learning and debate. Web-
based interactive visualisation tools will be a way forward
(Kingston, 2007; Wong, Baker, Hincks, Schulze B€aing, & Webb,
2012), as different level of analysis, pen pictures, commen-
taries, charts and graphs and indicators can be provided in one
single website to allow users to manipulate and develop their
own analysis.

The first three of these principles are inter-related in that the
achievement of one will facilitate the development of the others.
These are, therefore, seen as more critical to firmly establish the
quality threshold of the CPI as a robust and relevant measure of
urban prosperity. The fourth, fifth and sixth principles are related to
more in-depth methodological development of the analysis. Since
the CPI is a huge data collection exercise, it is important for the UN-
Habitat to extract the best policy intelligence out from the data to
inform policy thinking. However, there will be major methodo-
logical challenges and costs involved. The last principle is about
partnership and capacity building, which is politically challenging
and will take time for different stakeholders to engage in the
debate. More importantly, success in gaining political support and
the momentum necessary to develop a bona fide CPI will help to
overcome some of the data collection and methodological
challenges.

Conclusion

The emphasis on urban prosperity provides an interesting
platform for urbanists to rethink our place-making approaches and
the need to put people back to the centre of the conception.
However, this discussion highlights the methodological, conceptual
and political challenges ahead.

Since the methodological details provided in the SoWC report
are rather limited, it is difficult to make a fully robust assessment of
the CPI. It is thus important for the UN-Habitat to publish the
precise definition of different elements of CPI to elicit comments
and reviews from experts and stakeholders. In addition, there is a
need to clarify how a city is defined in the measurement of CPI and
to inject more rigour in the conceptualisation of the driving forces,
different dimensions and the outcomes of prosperity.

The analytical principles set out above aim to provide a basis to
inform the debate over what might be the most effective moni-
toring framework of international urban prosperity over time. It is
important to note that no single set of indicators will ever be
optimal, and the identified indicators by the UN-Habitat will
inevitably change when new policy issues emerge and better
quality data sets come along. It is therefore important to develop a
set of guiding principles to provide some parameters and flexibility
to establish future indicator frameworks that have utility in a va-
riety of different contexts. It is also important for stakeholders in
each region to take this framework forward and to share re-
sponsibility for its modification and refinement.

References

Bagolin, I. P., & Comim, F. V. (2008). Human Development Index (HDI) and its
family of indexes: an evolving critical review. Revista de Economia, 34(2),
7e28.

Boddy, M. (1999). Geographical economics and urban competitiveness: a critique.
Urban Studies, 36(5/6), 811e842.

Carter, H. (1981). The study of urban geography (3rd ed.). London: Edward Arnold.
Carlisle, E. (1972). The conceptual structure of social indicators. Published for the

Social Science Research Council. In A. Shonfield, & S. Shaw (Eds.), Social in-
dicators and social policy. London: Heinemann Educational Books.

Castells, M. (1989). The information city. Oxford: Blackwell.
Castells, M. (2007). Why the megacities focus? Megacities in the new world dis-

order. In J. Perlman, & S. O’Meara (Eds.), The state of the world e Our urban future
(pp. 1e16). E-publishing http://www.megacitiesproject.org.

Cheng, J., Bertolini, L., Clercq, F. L., & Kapoen, L. (2013). Understanding urban net-
works: comparing a node-, a density- and an accessibility-based view. Cities, 31,
165e176.

Coombes, M., Raybould, S., Wong, C., & Openshaw, S. (1995). The 1991 deprivation
index: a review of approaches. London: HMSO.

Coombes, M., Wong, C., & Raybould, S. (1993). Local environment index: Infra-
structural resources dimension, a final report to the Department of Employment,
Centre for Urban and Regional Development Studies. Newcastle upon Tyne:
University of Newcastle upon Tyne.

Davy, B. (2008). Plan it without a condom! Planning Theory, 7, 301e317.
Deas, I., & Giordano, B. (2001). Conceptualising and measuring urban competi-

tiveness in major English cities: an exploratory approach. Environment and
Planning A, 33(8), 1411e1429.

European Commission. (2000). The urban audit: Towards the benchmarking of quality
of life in 58 European Cities. In The Yearbook (Volume 1). Luxembourg: Office for
the Official Publications of the European Communities.

Findlay, A., Rogerson, R., & Morris, A. (1989). In what sense ‘indicators’ of quality of
life? Built Environment, 14(2), 96e106.

Fukuda-Parr, S. (2003). The human development programme: operationalizing
Sen’s ideas on capabilities. Feminist Economics, 9(2e3), 301e317.

Greer, S. (1969). The logic of social inquiry. Chicago: Aldine.
ul Haq, M. (1995). Reflections on human development. New York: Oxford University

Press.
Innes, J. (1990). Knowledge and public policy: The search of meaningful indicators.

New Brunswick: Transaction Publishers.
Kingston, R. (2007). Public participation in local policy decision-making: the role of

web-based mapping. The Cartographic Journal, 44(2), 138e144.
Rae, A., & Wong, C. (2012). Monitoring spatial planning policies: towards an

analytical, adaptive and spatial approach to a ‘wicked problem’. Environment
and Planning B: Planning and Design, 39, 880e896.

Rittel, H., & Webber, M. (1973). Dilemmas in a general theory of planning. Policy
Sciences, 4, 155e169.

Robson, B., Parkinson, M., Boddy, M., & Maclennan, D. (2000). The state of English
cities. London: Department for Environment, Transport and the Regions.

Rogerson, R. J. (1999). Quality of life and city competitiveness. Urban Studies,
36(5e6), 969e985.

RWI (Rheinisch-Westf€alisches Institut für Wirtschaftsforschung), German Institute
of Urban Affairs e DIFU, NEA Transport Research and Training, & Policy
Research and Consultancy e PRAC. (2010). Urban audit II: Second state of Eu-
ropean cities report. Research Project for the European Commission, DG Regional
Policy. Essen, Germany: RWI.

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref2

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref3

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref5

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref6

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref7

HOME

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref9

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref40

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref41

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref10

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref11

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref42

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref12

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref13

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref14

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref15

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref16

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref17

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref18

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref19

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref20

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref21

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref22

C. Wong / Habitat International 45 (2015) 3e9 9

Tao, R., Su, F., Liu, M., & Cao, G. (2010). Land leasing and local public finance in
China’s regional development: evidence from prefecture-level cities. Urban
Studies, 47(10), 2217e2236.

Taylor, M. (2000). Communities in the lead: power, organisational capacity and
social capital. Urban Studies, 37(5), 1019e1035.

UNDESA. (2012). World urbanization prospects e The 2011 revision. New York: United
Nations: United Nations Department of Economics and Social Affairs.

United Nations Development Programme [UNDP]. (2001). Human development
report 2001: Making new technologies work for human development. New York
and Oxford: UNDP.

United Nations Development Programme [UNDP]. (2013). Human development
report 2013-the rise of the South: Human progress in a diverse world. New York:
UNDP.

United Nations Human Settlements Programme [UN-Habitat]. (2012). State of the
world’s cities 2012/13: Prosperity of cities. Nairobi, Kenya: UN-HABITAT.

Westfall, M. S., & de Villa, V. A. (2001). Urban indicators for managing cities: Cities
data book. Manila: Asian Development Bank.

Wong, C. (2001). The relationship between quality of life and local economic
development: an empirical study of local authority areas in England. Cities, 18,
25e32.

Wong, C. (2002). Developing indicators to inform local economic development in
England. Urban Studies, 39(10), 1833e1863.

Wong, C. (2006). Quantitative indicators for urban and regional planning: The inter-
play of policy and methods. In Royal town planning institute library book series.
London: Routledge.

Wong, C., & Watkins, C. (2009). Conceptualising spatial planning outcomes: towards an
integrative measurement framework. Town Planning Review, 80(4/5), 481e516.

Wong, C., Gibb, K., McGreal, S., Webb, B., Leishman, C., Blair, N., et al. (2011). Housing
and neighbourhood monitor 2011: Fragility and recovery. Joseph Rowntree
Foundation. Bristol: Policy Press www.hnm.org.uk. For access to the maps and
charts in the analysis.

Wong, C., Jeffery, P., Green, A., Owen, D., Coombes, M., & Raybould, S. (2004). Town
and city indicators database project. London: the Office of the Deputy Prime
Minister.

Wong, C., Baker, M., Hincks, S., Schulze B€aing, A., & Webb, B. (2012). A map for
England: Spatial expression of government policies and programmes. London: The
Royal Town Planning Institute. http://www.rtpi.org.uk/knowledge/core-issues/
map-for-england/.

World Bank. (2013). World development indicators: 2013. Washington, DC: World
Bank.

Zhang, T. (2000). Land market forces and government’s role in sprawl: the case of
China. Cities, 17, 123e135.

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref24

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref25

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref43

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref26

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref27

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref28

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref29

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref30

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref31

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref32

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref33

http://www.hnm.org.uk

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref44

http://www.rtpi.org.uk/knowledge/core-issues/map-for-england/

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref37

http://refhub.elsevier.com/S0197-3975(14)00094-0/sref38

A framework for ‘City Prosperity Index’: Linking indicators, analysis and policy

Introduction
The wheel of prosperity: an integrative and progressive agenda
Conceptual and methodological challenges: what is in store?
Analytical principles of a policy-oriented indicator framework
Conclusion
References

lable at ScienceDirect

Habitat International 45 (2015) 1e2

Contents lists avai

Habitat International

journal homepage: www.elsevier .com/locate/habitat int

Editorial

Measuring the prosperity of cities

Introduction

The objective of this Special Edition of Habitat International is to
advance a dialog that will promote the development of a more
robust and useful measure of the prosperity of cities. The discussion
began with the publication of the State of World’s Cities 2012/13:
Prosperity of Cities report by the United Nations Human Settlements
Programme (2013). In that report UN-Habitat introduced a City
Prosperity Index based on a multi-dimensional definition of pros-
perity. Rather than measuring prosperity solely by traditional eco-
nomic measures such as productivity and income, the proposed CPI
would also include measures of Infrastructure, Equity, Sustainabil-
ity and Quality of Life. Along with Productivity, these dimensions
could be represented as spokes of a wheel. The hub of the wheel
consists of the laws, institutions and urban planning practices
that are necessary to maintain the balance across the different
dimensions.

Each of the dimensions of this definition of Prosperity contrib-
utes to an enriched understanding of the concept. An economically
rich (highly productive) city must operate sustainably or it will self-
destruct. Even the wealthiest city is not truly prosperous unless
there is an equitable distribution of the material prosperity, or if
certain groups do not have access to the available services and
amenities.

The analogy of a wheel is particularly apt. The hub of the wheel
(governance, regulation, planning) is essential to hold the individ-
ual measures in place. Even though the metrics of the individual di-
mensions are quite different, they must each attain a comparable
level of performance for the wheel to role smoothly. By measuring
each spoke separately, it is possible to identify the strengths and
weaknesses of the community and which aspects require attention.

The current version of the CPI should perhaps be considered a
“rough draft,” providing a starting point for improvements and re-
finements. The State of World Cities report offers a framework for
the CPI that has considerable potential. To move the CPI concept
forward, a number of critical questions must be considered and
resolved. Most of these concerns relate to the primary “spokes”
and the elements that make up each spoke as well.

What are the key aspects of prosperity that should be incorpo-
rated in the CPI? Are the current five appropriate? Should others
be included?

What are the appropriate metrics for each of the dimensions?
Are there global standards or do some components require local-
ized definitions?

Should the different components be assigned different weights
or is the present scheme of equal weights for each of the spokes
appropriate? Should the sub-components that have objective tar-
gets (for example 100% of dwellings connected to reliable electric

http://dx.doi.org/10.1016/j.habitatint.2014.06.016
0197-3975/© 2014 Elsevier Ltd. All rights reserved.

service) be considered differently than measures that are more
nebulous (road congestion or government corruption)?

Expert group analyses

In May, 2013, the City Prosperity Index Directorate of United Na-
tions Habitat convened ameeting of experts from around the world
to provide advice and comment on the City Prosperity Index. The
papers that are included in this volume were originally prepared
for this expert group meeting. As will be evident in reading these
papers, the expert group was not asked to directly provide an eval-
uation of the CPI. Rather, the scholars were asked to prepare a brief
paper on a topic relevant to a particular aspect of the CPI. The aim
was to introduce a broader perspective to the CPI development ef-
forts, not to provide a critique of the current version of the CPI.

The second and third papers in this Special Issue of Habitat In-
ternational deal with the requirements for the conceptual and
empirical development of an evaluative urban index. Wong’s paper
deals more directly with the current version of the CPI and seeks to
identify the elements that require further analysis and evaluation.
The Mori and Yamashita paper focuses on the more conceptual el-
ements of a City Sustainability Index. This paper describes two
different types of indicators, constraints and maximization ele-
ments, as well as introducing a framework for the logical compar-
ison of the relative sustainability of different cities.

The paper by Sands then develops an index of economic pros-
perity and applies it to mid-size Canadian metropolitan areas.
The current CPI, which uses the City Development Index to assess
productivity, provides a much richer understanding of this tradi-
tional measure of prosperity. Nevertheless, this paper does suggest
that a meaningful and useful measure of economic prosperity
might be constructed from fewer variables than at present; such
a strategy might make it easier to expand the range of the CPI to
more cities.

Jones et al. describe the development of a framework, the Local-
ized Sustainability Score (LSS), for screening urban transport pro-
jects. The framework assesses the relative importance of various
locally applicable sustainability criteria and maps the ability of
candidate urban transport projects to positively impact them. The
LSS framework can used to rank and priorities urban transport pro-
jects as part of a stakeholder-driven decision-making process.

Silva’s paper also addresses methodological issues, in this
instance the design of a weighted measure of air quality and noise
pollution. Employing local or national standards to establish the
unacceptable levels of specific pollutants from a human health
perspective, the individual indicators are combined as a single in-
dex value. Although Silva assigns equal weight to each indicator,
the methodology could also incorporate different weights.

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Editorial / Habitat International 45 (2015) 1e22

In the paper by Yigicanlar et al., a multiscalar urban sustainabil-
ity approach is used to link two sustainability assessment models
that evaluate sustainability at micro- and mezzo-levels and generate
multiscalar results for the macro-level. The paper also describes how
the development of a sustainability index that accurately reflects
multiscalar indicator data may contribute to improving UN-Habitat’s
City Prosperity Index.

The next two papers deal with efforts to develop a better mea-
sure of Quality of Life. Marans’ paper is primarily conceptual, while
Bonaiuto et al. report on en empirical study of Quality of Life mea-
surements. Both papers suggest that survey data of citizen attitudes
should be incorporated into Quality of Life indices and, indeed, that
such qualitative data may complement and, in some instances, sub-
stitute for quantitative measures.

Finally, Steed considers the question of how the quality of gover-
nance can influence measure of city prosperity. While he finds
some positive associations between prosperity and governance at
the sub-state level, the correspondence between the two is far
from perfect. The complexities in measuring, let alone changing,
some measures of governance quality (transparency, absence of
corruption) add to the difficulties of creating a simple measure of
governance quality.

Future directions

The papers included in this Special Issue suggest some of the
complexities inherent in the further development of a practical
and reliable City Prosperity Index. Several of the papers describe
new or different measures that could be incorporated in the CPI
to improve it. For each of these, as well as for many other indicators
and scales, the primary question to be answered is whether the
benefit of the improvement is worth the cost required to imple-
ment it on a global basis. There were more than 560 urban agglom-
erations with a population of at least 750,000 in 2009; one quarter
of them in China (UN-HABITAT, 2013).Would the cost of developing

the CPI for every one of them be justified by the improvement in
the quality of the results?

In the short run, there are a number of choices that will need to
be made. The current version of the CPI is a useful starting place. It
provides a model that can be used to test the utility and potential
applications of the broader concept of prosperity. It provides a
nuanced summation of important elements of prosperity.

Howwill the CPI be used? Its primary function could be to allow
comparisons to be made among cities at a single point in time. Or,
its primary function could be to allow an individual city to measure
its progress over time. The first option requires the collection of
equivalent data for all of the cities in the data set at close to the
same time. The second formulation requires the identification of
data that are consistently collected at comparable intervals that
correspond to the time period being considered. If some elements
of the index are available on a daily, or even hourly basis (say air
quality), how can these be blended with metrics that are available
only annually, or even less frequently? If only some of the compo-
nents can be updated annually, is it reasonable to publish annual
results for the CPI?

Reference

United Nations Human Settlements Programme (UN-HABITAT). (2013). State of the
world’s cities 2012/2013: Prosperity of cities. Nairobi, Kenya: UN-HABITAT.

Gary Sands, Guest Editor, Professor Emeritus*

Urban Planning Program, Wayne State University, 1051 Hartsough St.,
Plymouth, MI 48170, USA

* Tel.: þ1 734 255 5997.
E-mail addresses: Gary.sands@wayne.edu, sands.gary@gmail.com.

Available online 28 July 2014

http://refhub.elsevier.com/S0197-3975(14)00092-7/sref1

mailto:Gary.sands@wayne.edu

mailto:sands.gary@gmail.com

A T O O L T O M E A S U R E

S U S T A I N A B L E U R B A N D E V E L O P M E N T

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S U S T A I N A B L E U R B A N D E V E L O P M E N T
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CITY PROSPERITY INITIATIVE

First published in Nairobi in 2016 by UN-Habitat

United Nations Human Settlements Programme (UN-Habitat)

P. O. Box 30030, 00100 Nairobi GPO KENYA

Tel: +254 20 7623 120 (Central Office)

www.unhabitat.org

Disclaimer

The designations employed and the presentation of the material in this publication

do not imply the expression of any opinion whatsoever on the part of the Secre-

tariat of the United Nations concerning the legal status of any country, territory,

city or area or of its authorities, or concerning the delimitation of its frontiers of

boundaries. Views expressed in this publication do not necessarily reflect those

of the United Nations Human Settlements Programme, Cities Alliance, the United

Nations, or its Member States.

With 50% of the world’s population
living in cities, and this expected
to rise to 60% by 2030, the battle
for sustainable development will
be won or lost in cities. Cities are
catalysts of productivity, technology
and infrastructure expansion capable
of influencing regional and global
development.

The outcome document of the
United Nations Conference on
Sustainable Development, entitled
“The future we want”, recognizes
that if well planned and developed,
cities can promote economically,
socially and environmentally
sustainable societies. However, poor
planning, the absence of effective
governance and legal frameworks,
fragile institutions, low capacity of
local authorities, and the lack of
a sound monitoring mechanism,
reduce the possibility to promote
long-term sustainable urban
development.

Evidently, there is an urgent need
for a global monitoring mechanism,
which is adaptable to national and
local levels. This would provide a
general framework that allows cities,
countries, and the international
community to measure progress
and identify possible constraints,
thus pre-empting unintended
development.

The Report of the Sustainable
Development Solutions Network
that supports the Sustainable
Development Goals indicates that
“data and metrics are essential for
development goals to be met”.
They enable cities to make correct
decisions on the best policies to
adopt, and assist in tracking changes,
whilst systematically documenting
their performance at the outcome
level. This is fundamental towards
achieving higher levels of urban
prosperity and sustainable urban
development for all.

“Data needs improving” – stresses
the report A World that Counts,
prepared as part of the Data
Revolution efforts of the UN system.
Despite considerable progresses in
recent years, whole groups of people
are not being counted and important
aspects of people’s lives and city
conditions are still not measured.
This can lead to the denial of basic
rights, and the likelihood that people
are not able to take full advantage
of the transformative potential which
urbanization offers.

Too often, existing city data is not
adequately detailed, documented
and harmonized, or worse, it
simply is not available for critical
issues relating to urban growth and
development. This greatly impacts
the quality of decision-making. Cities
can and must do better than this.

T O W A R D
S U S T A I N A B L E U R B A N
D E V E L O P M E N T

In 2012, UN-Habitat created a tool
to measure the sustainability of
cities. This tool, known as The City
Prosperity Index, was accompanied
by a conceptual matrix, the Wheel
of Urban Prosperity. In 2013,
UN- Habitat received numerous
requests from local authorities and
central governments to estimate
their respective prosperity indexes.
Mayors and other decision-makers
wanted to know how their cities
feature in comparison with others.
This included knowledge on how
to improve the quality of life of its
inhabitants, including gaining critical
insights in to which programmes
and policies work, and the possible
impacts these actions may have.

As a result of these demands,
UN-Habitat transformed the City
Prosperity Index into a global
initiative known as the City Prosperity
Initiative. This initiative is both
a metric and a policy dialogue,
which offers cities from developed
and developing countries the
possibility to create indicators and
baseline information, often for the
first time. It also serves to define
targets and goals that can support
the formulation of evidence-based
policies, including the definition of
city-visions and long term plans that
are both ambitious, and measurable.

C I T Y
P R O S P E R I T Y
I N I T I A T I V E A TOOL TO MEASURESUSTAINABLE URBAN DEVELOPMENT

Growing and ever more complex cities and their
inhabitants no longer make decisions without the benefit
of internationally validated data and indices.
This information is a pre-requisite to deciding:

Which policies to implement
Where to allocate public and private resources
How to identify setbacks and opportunities
How to measure what has changed

UN-Habitat’s City Prosperity Initiative (CPI) is an integral
part of the Data Revolution for Sustainable Development.
It not only aims to integrate new sources of data and
increase its usefulness, but also enables city authorities,
as well as local and national stakeholders, to identify
opportunities and potential areas of intervention for their
cities to become more prosperous.

In short, we need accurate, timely and relevant city data to make important

decisions about sustainable development. The CPI can play a vital role in

this process.

50%

75%

100%

25%

50%
75%
100%
25%

Accra (Ghana)

Bogota (Colombia)

PROSPERITY INDEX

PROSPERITY INDEX
44.6%

39.4%

The CPI offers a unique and holistic view of sustainable urban development.
The CPI expresses the different dimensions of city growth in the following four
unique ways:

1 As a Flexible Monitoring Framework:

The CPI serves as a platform for a city to assess its situation and compare it
with others worldwide

The CPI acts as a strategic policy tool whereby data and information are
adapted to local or contextual needs. The tool is then used to measure
progress and identify deficiencies in different dimensions of prosperity

2 An innovative tool based on spatial analysis

The CPI measures transformation of a city’s unsustainable form and function
It aims to reinvigorate urban planning and design
It provides adequate laws and institutions
The CPI proposes local economic development solutions

3 A framework that promotes integration

The CPI assesses the possibility effects of specific policies on the different
dimensions of prosperity

The CPI allows cities to define targets and goals that can support the
formulation of evidence-based policies and measureable long-term plans

Policy simulation can predict the impact of alternative policies on the overall
urban prosperity level

W H Y U S E
T H E C P I
F R A M E W O R K

CPI an accurately determine the positive impact of a selected policy on city growth
Linking policy decisions to future impact assessments enables adoption of multisectoral, integrated actions that can

increase the likelihood of better prosperity outcomes for an entire city

4 A multi-scale decision-making tool

Overall, the CPI produces information at city level, sometimes at sub-city level, critical to support local decision-
making in key priority areas of development

CPI provides information at the regional and metropolitan levels, building links between municipal governments,
articulating responses that contemplate city regional development and better integration of sectors

50%
75%
100%
25%
50%
75%
100%
25%

Guatemala City
(Guatemala)

Quito
(Ecuador)

PROSPERITY INDEX PROSPERITY INDEX

The CPI is not a rigid blueprint, it is a
living framework – one that intention-
ally leaves room for cities to respond
to contextual needs, and to move cre-
atively according to their challenges
and opportunities. As part of this flex-
ible approach, the CPI has a double
function. Firstly, it serves as a platform
for global comparison, in which each
city can assess its situation, and com-
pare its rate and present performance
with other cities worldwide. Second-
ly, it acts as a strategic policy tool
where the data and information is
adapted to local or contextual needs,

and used to measure progress and
identify deficiencies in the different
dimensions of prosperity.

Consequently, the CPI is constructed
incrementally, at the basic level
offering regional or global
comparison and at the advanced level
providing the possibility to integrate
contextual aspects of the city. This
incremental approach includes the
potential to understand and measure
city comparative advantages, as well
as policies and actions which the CPI
is intended to assess.

The City Prosperity Index uses
a set of commonly available
indicators that exist among all
cities, acting as a platform for
regional/global benchmarking and
for comparison purposes. A more
extended version of the Index
allows for a more detailed political
and technical dialogue that is
essential for the development of
more informed public policies and
allows practitioners to document
performance of the cities at the
outcome level.

A FLEXIBLE MONITORING FRAMEWORK

41.9%44.9%

CPI INCREMENTAL
APPROACH

The form, planning and structure
of the city can conspire against
prosperity or act together to boost
it. Concerned by the need to
produce accurate, reliable, timely
and disaggregated data, UN-Habitat
has created an important innovation
in the CPI by integrating spatial
indicators and analysis in the different
dimensions of prosperity.

According to UN-Habitat, adequate
provisioning of streets and public
spaces are associated with urban
prosperity. Typically, more efficient
and productive cities with better quali-
ty of life and environmental indicators
are often cities with better street-con-
nectivity. In contrast, slums and poor
neighborhoods have on average half
the proportion of streets compared to
consolidated areas of the city. In order

to measure this fundamental dimension
of the urban form, UN-Habitat has creat-
ed a composite indicator made of three
variables – land allocated to streets,
street density and intersection density.

In order to provide ‘the right
information on the right things
and at the right time’, there is a
need of geospatial data, adequate
technology and management systems
to complement high-quality official
statistics. Spatially disaggregated
data provides relevant information
for policy makers to decide on local-
level allocation of resources and the
monitoring of equitable outcomes
across and within cities and human
settlements. Geospatial information
needs to be available quickly enough to
ensure that the data cycle matches the
decision cycle.

AN INNOVATIVE TOOL BASED ON SPATIAL ANALYSIS

GLOBAL
CITY RANKING

Global and
Regional

Monitoring

BASIC

CPI

Initial Diagnosis
internationally
Comparable

EXTENDED
CPI

In-depth Diagnosis
Comparable

within country

CONTEXTUAL
CPI

National Urban
Policies and urban
monitoring tool

Annual Global
City Ranking

CPI Report
Action Plan

CPI Report Policy
recommendation

State of
Cities
Report

A MULTI-SCALE DECISION-MAKING TOOL

The CPI provides national and
state/provincial governments,
and local authorities with the
necessary data and information to
articulate various territorial levels
for higher coordination of roles and
responsibilities.

In some cases, the CPI supports the
development and implementation of
integrated national urban policies.
Decision-makers are provided with
the knowledge to make opportune
decisions about their cities – small,
medium or large – as part of a
national system of cities. This helps
to amalgamate the dispersed energy

and potential of urban centres,
establishing a synergetic connection
between urbanization and national
development.

In other cases, the CPI provides infor-
mation at the regional and metropol-
itan levels building linkages between
municipal governments, articulating
responses that contemplate city re-
gional development and better inte-
gration of sectors. The Metropolitan
CPI can detect which municipalities
or districts are more advanced in the
prosperity path, proposing solutions
for a more harmonious urban devel-
opment.

Overall, the CPI produces
information at city level, and when
data allows, at sub-city level. This
information is critical to support
local decision-making in key priority
areas of development, such as the
strengthening of urban legislation
and systems of governance,
harnessing the urban economy and
creating employment opportunities
for all, reinforcing municipal finance,
and improving basic service delivery
and housing.

NATIONAL: The CPI supports the development
and implementation of integrated national urban
policies. Decision- makers are provided with the
knowledge to make opportune decisions about
their cities small, medium or large as part of a
national system of cities. This helps to amalgamate
the dispersed energy and potential of urban
centers, establishing a synergetic connection
between urbanization and national development.
This is the case with Mexican, Colombian and
Saudi Arabia programs.

METROPOLITAN: The CPI provides information
at the regional and metropolitan levels building
linkages betwe- en municipal governments,
articulating responses that contemplate city
regional development and better integra- tion of
sectors. The Metropolitan CPI can detect which
municipalities or districts are more advanced in the
prospe- rity path, proposing solutions for a more
harmonious urban development. The metropolitan
area of Guadalajara is a good example.

CITY: The CPI produces information
at city level, and when data allows, at
sub-city level. This information is
critical to support local
decision-making in key priority areas
of development, such as the
strengthening of urban legislation and
systems of governance, harnessing the
urban economy and enhancing urban
planning.

Global
Monitoring
Instrument

National
Initiative

Metropolitan
Strategies

City level
policies

SCALING THE CPI

In efforts towards improving
economic productivity or providing
infrastructure, some cities may further
exacerbate inequalities or negatively
impact environmental conditions. The
CPI looks at these interactions and
measures inter-sectoral relationships,
and attempts to reinforce them.

By conducting policy simulations, the
CPI assesses the possible effects of
specific regression and correlation
analysis and association of variables;
the CPI can accurately determine the
positive impact of a selected policy
on city growth.

The possibility of linking policy decisions
to ex-ante impact assessments favors the
adoption of multi-sectoral, integrated
actions that can increase the likelihood
of better prosperity outcomes for the
whole city.

At the same time UN-Habitat’s Best
Practices database was set up to show
similar results in implementation of a
more prosperous city. UN-Habitat is also
working with the University of Sydney to
develop an automatized selection and
use of best practices for policy purposes.

A FRAMEWORK THAT PROMOTES INTEGRATION

What Makes Cities Sustainable

Access by all residents to safe,
decent and affordable housing

Upgrade of slum settlements
Adequate public transport
Creation of green public spaces

Characteristics of Unsustainable City

Insufficient land for Street
Development

Poor provision of public areas
Low residential densities
Endless peripheries
Poor economies of agglomeration

THE NEW URBAN AGENDA The CPI proposes a limited
number of key, transformational
interventions, which are designed
using the main components of
the New Urban Agenda: the UN-
Habitat’s three-pronged approach
– urban legislation, urban economy
and urban planning.

1 Planning and Urban Design

Reinvigorated planning involves
political choices and commitments,
which must be turned into tools
and sustainable technical solutions.
The CPI identifies a number of
these interventions that can help
cities to increase prosperity, such
as planned infill development and
guided city expansions, multimodal
mobility development strategies,
neighborhood planning for
enhanced social diversity and mixed-
land use.

2 Urban legislation and governance

Laws and institutions provide
the normative and organizational
underpinnings of urban change
and the power and rigor generally
sustaining continuity or triggering
change. The City Prosperity Initiative
identifies transformative actions such
as the reform of urban legal systems,
regulations on urban planning,
building regulations and zoning laws,
and participatory and inclusive land
readjustments.

3 Urban economy and municipal
finance

The CPI identifies transformative
actions that can help local and
national governments develop
revenue enhancement plans which
can leverage innovative tools and
simple, transparent revenue collection
mechanisms. These mechanisms can
harness and support growth while
garnering community buy-in for public
sector revenue collection efforts.

T H E C P I A N D T H E
T H R E E – P R O N G E D A P P R O A C H
T O U R B A N I Z A T I O N

Reinvigorate Urban
Planning and Design

CPI

23
Reinforce
Institutions,
Laws and Norms

Strengthen
Local Economic
Development

1 Adopts a systemic approach of the city.
The CPI offers a holistic view of sustainable
urban development. It permits us to
establish and understand theaspects of
city development. By using this global
framework, it is possible to ensure that
different targets and indicators of Goal 11
can have a mutually reinforcing effect.

2 Provides a single value of the state of the
city. As a composite index, the CPI makes
it possible to understand the state of a
city’s development in a more integrated
manner. This helps local and national
governments assess the degree to which
cities and human settlements are inclusive,
safe, resilient and sustainable. At the same
time, the SDG targets and indicators can
be separated in specific measurements and
values.

3 Establishes benchmarks for local,
national and global monitoring. The
CPI methodology has established
precisebenchmarks with sound techniques
of standardization that enable comparisons
among different indicators. This is crucial
for the creation of a global monitoring
mechanism. National governments can
adjust the mechanism to specific needs and
requirements.

4 Creates baseline data and information.
The adoption of the CPI enables cities
to create baseline data and information,
which is extremely important to define
local targets, identify setbacks, propose
strategies for improvement, and monitor
progress.

5 Establish a global platform for
comparability. The CPI offers a global
platform with which to compare cities of
developed and developing countries. This
is achieved through the use of indicators
that are approved and grouped by targets.

6 Identify priorities of sustainable urban
development. The CPI allows for the
separation of different components of
sustainable urban development, making
it possible to identify progress or lack
of it in the different components of the
Goals (inclusion, safety, resilience and
sustainability). By isolating targets and
components or grouping them, it is
possible to adopt appropriate policies and
corrective measures.

7 Provides evidence-based metric for
policymaking and accountability. The
CPI is a metric and a policy dialogue vital
for supporting formulation of policies
and actions, based on accurate data and
diagnostics.

8 Creates local and national monitoring
mechanisms. The CPI framework offers
the possibility for local and national
governments to establish their own
monitoring mechanisms and to report in
a more systematic manner. At the same
time, the CPI remains a global monitoring
mechanism that allows aggregate data for
regional and global reporting

A Global Monitoring Framework
for SDG Goal 11 and the New
Urban Agenda

UN-Habitat is proposing that
national governments and
local authorities adopt the City
Prosperity Initiative (CPI) as a
global monitoring platform for
Sustainable Development Goal 11
indicators and other SDGs with an
urban component.

It is estimated that around one
third of urban-related indicators
can be measured at the local level,
having a direct connection to
urban policies, and a clear impact
on cities and human settlements.

Countries which apply CPI will be
able to identify, quantify, evaluate,
monitor and report on progress
they and their cities are making
in achieving the United Nations
Sustainable Development (SDG)
Goal 11.

The new CPI framework can
integrate all indicators of Goal 11
and a selected number of other
SDG indicators that have an urban
component.

ADDED VALUE OF THE CPI FRAMEWORK

EGYPT
A basic CPI is been calculated for an
impressive number of cities. A
sub-sample of 50 cities will have
detailed analysis on spatial indica-
tors. Information is linked to national
development policies and pro-poor
strategies.

SAUDI ARABIA
The “Future Cities Program”
implemented by the Kingdom of
Saudi Arabia is building national
capacities for effective
evidence-based policy to make 17
cities more inclusive, economically
diverse and prosperous.

VIETNAM
Ha Noi, HCM City, Hai Phong, Da Nang and
Can Tho are part of the CPI in this country.
The programme aims to develop an urban
observatory system for the monitoring of
SDGs indicators with an urban base.

ETHIOPIA
The Ministry of Urban Development, Housing
and Construction is implementing the CPI in 2
cities (Addis Ababa and Mekelle) with an
important component of urban resilience. CPI
was the associated with the creation of the
State of Ethiopian Cities Report.

BRAZIL, ECUADOR, PANAMA, PERU
A basic and expanded CPI has been produced for the city of Fortaleza,
Lima, Guayaquil, Quito and Panama.

Results were recently discussed with local authorities and stakehold-
ers. CAF, the Developing Bank of Latin America is supporting the CPI
in these Latin American cities. The study is concluded and action
plans are being implemented for each city

COLOMBIA
As part of the national development plan
and the challenges of the Post-conflict the
CPI identify priorities for sustainable
urban development with 10 lines of
actions in 23 cities.

MEXICO
The Mexican Housing Bank
(INFONAVIT) and The Ministry of
Agrarian Territorial and Urban
Development have implemented the
Initiative to more than 130 cities.

C P I C I T I E S M A P

The CPI has already been proven
in more than 400 cities across
the world and as a monitoring
framework it has the potential to
become the global architecture
platform for the monitoring of
SDG Goal 11.

A T O O L T O M E A S U R E
S U S T A I N A B L E U R B A N D E V E L O P M E N T
P
ro
d
uc
ti
vi
ty
In
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q
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a
nd
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o
ci
al
In
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io
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ex
E
nv
ir
o
nm
en
ta
l S
us
ta
in
ab
ili
ty
In
d
ex
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ua
lit
y
o
f
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fe
In
d
ex
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an
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a
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ex
In
fr
as
tr
uc
tu
re
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ev
el
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p
m
en
t
In
d
ex
EGYPT
A basic CPI is been calculated for an
impressive number of cities. A
sub-sample of 50 cities will have
detailed analysis on spatial indica-
tors. Information is linked to national
development policies and pro-poor
strategies.
SAUDI ARABIA
The “Future Cities Program”
implemented by the Kingdom of
Saudi Arabia is building national
capacities for effective
evidence-based policy to make 17
cities more inclusive, economically
diverse and prosperous.
VIETNAM
Ha Noi, HCM City, Hai Phong, Da Nang and
Can Tho are part of the CPI in this country.
The programme aims to develop an urban
observatory system for the monitoring of
SDGs indicators with an urban base.
ETHIOPIA
The Ministry of Urban Development, Housing
and Construction is implementing the CPI in 2
cities (Addis Ababa and Mekelle) with an
important component of urban resilience. CPI
was the associated with the creation of the
State of Ethiopian Cities Report.
BRAZIL, ECUADOR, PANAMA, PERU
A basic and expanded CPI has been produced for the city of Fortaleza,
Lima, Guayaquil, Quito and Panama.
Results were recently discussed with local authorities and stakehold-
ers. CAF, the Developing Bank of Latin America is supporting the CPI
in these Latin American cities. The study is concluded and action
plans are being implemented for each city
COLOMBIA
As part of the national development plan
and the challenges of the Post-conflict the
CPI identify priorities for sustainable
urban development with 10 lines of
actions in 23 cities.
MEXICO
The Mexican Housing Bank
(INFONAVIT) and The Ministry of
Agrarian Territorial and Urban
Development have implemented the
Initiative to more than 130 cities.

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Prosperity and the Suburban Dream: Quality of life
and affordability in western Sydn

Kathleen Mee

To cite this article: Kathleen Mee (2002) Prosperity and the Suburban Dream: Quality
of life and affordability in western Sydney, Australian Geographer, 33:3, 337-351, DOI:
10.1080/0004918022000028725

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Australian Geographer, Vol. 33, No. 3, pp. 337–351, 2002

Prosperity and the Suburban Dream: quality of
life and affordability in western Sydney

KATHLEEN MEE, University of Newcastle, Australia

ABSTRACT Over the past 10 years Sydney has experienced a remarkable wave of economic
prosperity and growth, partly due to its developing role as a regionally signi� cant global city.
Through this period, maintaining the quality of life in the city has been regarded as particularly
important. Yet traditional accounts of the global city have stressed quality-of-life features of the
inner city. In this paper I examine the implications of the prosperity of global Sydney for the
quality of life of western Sydney, paying particular attention to environmental amenity and the
affordability of housing. The paper argues, � rst, that growth in the Sydney region has
depended upon continued growth in western Sydney. It highlights key instances in which
residents have resisted developments associated with this growth and regarded as major threats
to the environmental amenity of the region. Second, the paper argues that the prosperity of
Sydney, combined with changes to government policy, have impacted upon the supply of
affordable rental housing in western Sydney. This is particularly signi� cant in the case of
public housing. Managing growth in the city will require attention to managing quality-of-life
issues in the metropolis as a whole.

KEY WORDS Global city; suburbs; western Sydney; environmental activism; housing afford-
ability; public housing.

Introduction

Over the past 10 years Sydney has experienced a remarkable wave of economic
prosperity and growth (O’Neill & McGuirk this issue). This prosperity has been due in
part to government policies that have fuelled Sydney’s growth, and helped develop its
role as a regionally signi� cant global city. These developments have impacted unevenly
within the city. The impacts of the changes discussed in this special issue for western
Sydney are far reaching. Here I examine a number of the implications of prosperity for
the residents of the western suburbs of Sydney through an understanding of the role of
the region as a suburban home.1

Discussions of global cities often assert the importance of maintaining an appropriate
‘quality of place’. As Florida (2000, p. 49) has put it, ‘to compete successfully in the age
of talent, regions must make quality of place a central element of their economic
development efforts’. Indeed, quality of life is a feature that has � gured heavily in recent
planning strategies in Sydney (DUAP 1998). Discussions of quality of life in the global
city, however, tend to focus predominantly around issues of access to cultural and
social facilities in the inner city as well as the environmental amenities of the wider city,

ISSN 0004-9182 print/ISSN 1465-3311 online/02/030337-15 Ó 2002 Geographical Society of New South Wales Inc.
DOI: 10.1080/0004918022000028725

338 K. Mee

but most particularly of inner-city regions (Florida 2000). Yet the suburbs of a global
city are part of the global city too. The development of the inner city profoundly affects
other parts of the city and surrounding regions. As the Committee for Sydney (1998)
has noted, quality-of-life issues related to the development of a more globalised city are
relevant for the metropolis as a whole.

In this paper I examine some of the implications of the prosperity of Sydney for
western Sydney. Sydney is a diverse place, and western Sydney is a diverse region
within Sydney. Understanding the impacts of the new prosperity in Sydney requires us
to consider how this prosperity might affect different regions of the city. Western
Sydney has played an important role in the geography of Sydney since World War II,
providing an affordable suburban home for a substantial proportion of the Sydney
population. Here I focus on two elements important to the quality of suburban life in
western Sydney, the quality of the natural environment and the affordability of housing.
I argue that a number of changes in the 1990s, some of them related to growth caused
by the new prosperity, have (further) challenged the quality of life in parts of the region.
In some cases the role of western Sydney in providing a suburban home for a
cross-section of residents, including some highly disadvantaged Sydney residents, has
been compromised. Drawing on case study material I argue for the need for govern-
ments to consider quality-of-life aspects in the metropolis as a whole as an important
element in managing the global city.

Western Sydney as suburban home

In the 55 years following World War II, western Sydney Local Government Areas
(LGAs) absorbed a substantial proportion of Sydney’s growth (Spearritt 2000). The
growth of western Sydney was an important part of the growth of suburban Sydney.
Generations of Sydneysiders have moved to the suburbs of western Sydney in search of
affordable housing in a suburban environment (Dowling & Mee 2000; Mee 2000).
According to Murphy and Watson (1997, p. 7) the suburban dream was ‘rampant’ in
the post-war period. Western Sydney has enabled the ful� lment of this dream, albeit a
partial ful� lment, for thousands of residents.

But what exactly constituted the suburban dream in Sydney, and particularly western
Sydney, during the post-war period? Discussing Mount Druitt and Green Valley, two
1960s public housing estates in western Sydney, Dowling and Mee (2000) note the
‘ordinariness’ of the suburban dream being pursued by residents. Those coming to
these estates were seeking affordable secure housing, in a suburban natural environ-
ment. Most importantly, the suburbs were viewed as an appropriate place to raise
children (Stretton 1970; Powell 1993; Mee 2000). The quality-of-life aspects discussed
here were crucial to this dream. The affordability of housing attracted residents and the
possibilities of the suburban environment were some of the bene� ts of suburban life
(Dowling & Mee 2000).

The creation of suburban western Sydney did not occur in an unproblematic fashion.
The rapid development of affordable housing left parts of the region with signi� cant
service de� cits and pockets of social disadvantage (Miller & Fuhr 1983; Fulop &
Sheppard 1988; Hodge 1996; Johnson et al. 1997; Gleeson & Randolph 2002). During
the post-war period, associations between western Sydney and negative aspects of
suburban life began to be made (Johnson et al. 1997). According to Spearritt (1978) the
western suburbs of Sydney were ‘giving suburbia a bad name’ from the late 1950s.
Powell (1993) claims that the attachment of the ‘slum stigma’ to western Sydney

Prosperity and the Suburban Dream 339

TABLE 1. Population change, 1996–2001, Western Sydney Local Government Areas

Local Government Area Population Increase, 1996–2001 % population increase

Auburn 56 379 5420 10.6
Bankstown 165 604 7869 5.0
Baulkham Hills 139 404 19 859 16.6
Blacktown 256 364 24 145 10.4
Blue Mountains 74 317 1811 2.5
Camden 43 945 11 836 36.9
Campbelltown 145 860 2087 1.5
Fair� eld 181 936 151 0.1
Hawkesbury 61 073 3692 6.4
Holroyd 85 760 5290 6.6
Liverpool 154 287 34 090 28.4
Parramatta 144 490 5333 3.8
Penrith 172 397 9275 5.7
Wollondilly 37 123 3710 11.1
Total western Sydney 1 718 939 134 568 8.5
Total Sydney 3 997 321 256 031 6.8

Source: ABS Census of Population and Housing, 1996 and 2001.

occurred in the 1970s. Certainly the massive growth of suburban housing in western
Sydney through the post-World War II years was also associated with a change in the
way these suburbs were viewed. Housing in western Sydney was not just seen as
affordable. Rather, it was viewed as cheap, ugly and tasteless. The environment of the
region was also derided as being (among other things) � at, treeless and boring
(Dowling & Mee 2000).

Nonetheless, the most recent census � gures suggest that the growth of western
Sydney continues to play an important part in the development of Sydney. Between
1996 and 2001, 47 per cent of the population increase in Sydney was in western Sydney
LGAs. Table 1 demonstrates that the increase in population during this time was
spatially uneven. In some LGAs there were spectacular rates of growth, with Baulkham
Hills, Blacktown, Camden, Liverpool and Penrith alone accounting for 39 per cent of
Sydney’s population increase. In all of these LGAs, population increased substantially,
with Liverpool and Camden in particular exhibiting very high rates of growth. In other
LGAs, including Fair� eld2 and Campbelltown (both immediately adjacent to the
fast-growing Liverpool), the population increase was relatively modest, both in terms of
numbers of people added to the population and in percentage terms.

Changes in numbers of dwellings in western Sydney are also indicative of western
Sydney’s continuing role as a suburban home. The region accounted for 73 per cent of
the increase in houses in Sydney between 1996 and 2001. This increase was particularly
concentrated in the LGAs with the highest population growth. Baulkham Hills, Black-
town, Camden, Liverpool, Penrith and Campbelltown accounted for 63 per cent of the
increase. Meanwhile, in other parts of western Sydney, such as Auburn, Bankstown and
Holroyd, the number of houses declined.

A slightly different story emerges when we examine the increase in the number of
semi-detached dwellings in Sydney (see Table 2).3 Contrary to the picture of western
Sydney as acre upon acre of homogeneous bungalows, there was a considerable
increase in the number of semi-detached dwellings between 1996 and 2001, with 46
per cent of the total increase in these dwellings in Sydney occurring in western Sydney.

340 K. Mee

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Prosperity and the Suburban Dream 341

The pattern of change here is somewhat different. Some areas with declining numbers
of houses experienced substantial increases in their numbers of semi-detached
dwellings (in LGAs such as Bankstown and Holroyd) as older houses were converted
to newer and smaller forms of dwellings. But there were also signi� cant increases in
semi-detached dwellings in LGAs such as Blacktown and Liverpool, where the increase
in the number of houses was also the most marked.

Western Sydney clearly continues to play a major role in providing a home for
Sydney’s increasing population. However, while older patterns of the growth of subur-
ban populations and housing continue, so too do higher density forms of growth in
peripheral and older locations. As McDonald and Kippen (this issue) point out, it is
likely that the ability of western Sydney LGAs to house a growing population will be
important for many decades to come.

In a recent survey, western Sydney residents indicated that the following factors
made the region a better place to live than other parts of Sydney: more living space;
house or land still affordable to buy or rent; good community feeling; less pollution/
better environment; more public space/parks; proximity to other family members;
quieter (Urban Frontiers Program 2001). The affordability of housing, community
spirit and environment of western Sydney are clearly valued by residents (despite
negative perceptions of these from some outside the region). According to its residents,
western Sydney is still valued as a suburban home. Interestingly, residents also indi-
cated that they thought that ‘higher population density’ would be among the most
important problems facing western Sydney in the next 10 years (Urban Frontiers
Program 2001). Clearly, the changes brie� y outlined here are beginning to cause some
concern for western Sydney residents. Density in western Sydney is increasing as a
direct consequence of Sydney’s growth, and the city’s managers need to be sensitive to
sharing the consequences of these developments equitably.

In what follows I examine in more detail two aspects of suburban western Sydney:
the quality of the natural environment and the affordability of housing. These aspects
of life are crucial to the role of the region as suburban home, and pose important
quality-of-life challenges for city managers and residents of the region.4

The threats of growth: environmental activism

During the 1990s, Sydney’s growth has been substantially western Sydney’s growth, in
terms of population and housing. Combined with past geographies of advantage and
disadvantage in western Sydney, this growth has led to a range of challenges for the
region’s governments and residents, including the challenge of providing more housing
and jobs whilst attempting to protect the environment. As Forsyth (1999) has noted,
some of the developments in western Sydney during this period were opposed by
groups of environmentalists (from both within and outside western Sydney) keen to
preserve the environmental amenity of the region.5 In media discussions concerning the
resident action groups that formed to oppose the development of an Australian Defence
Industries (ADI) site near Penrith in outer western Sydney, opposition to development
was represented in binary terms as support for the environment over housing (Jamal
2000, 2001; Connolly 2001; Taylor 2001). Environmental activism in western Sydney
during this period is consistent with attempts to maintain or improve a suburban
‘quality of life’ in a growing and prosperous city. As noted above, it is more common
to associate a high ‘quality of life’ in a global city with the conditions enjoyed by
inner-city elites. For residents of western Sydney the maintenance of the quality of

342 K. Mee

suburban life in Sydney was of continued importance during this period. In the case
of western Sydney, however, past environmental perceptions of the region and its
geography of disadvantage framed the way in which such con� icts were understood.

I want to focus here on activism opposed to the proposed development of a second
airport in western Sydney at either Badgerys Creek or Holsworthy during the 1990s.
The debate over a second airport was also reported in the media very much in binary
terms, as a battle over the environment versus desperately needed jobs (Mee 1999).
Councils opposing the development of the Badgerys Creek airport were accused of
working against the interests of their citizens, either by implication or explicitly.
However, large numbers of protesters and councillors thought the development of an
airport was not in the interests of their citizens.6 Debates about the environment and
development were translated into the federal political arena, with the Liberal holder of
the marginal western Sydney seat of Lindsay, Jackie Kelly, taking a prominent stand in
opposition both to the airport at Badgerys Creek and the development of the ADI site.

In part, the depiction of this debate in the media rests upon a misunderstanding of
everyday life in western Sydney. Western Sydney is mostly represented as an area of
lack (Powell 1993; Dowling & Mee 2000), particularly socio-economic disadvantage
and service de� cit. How surprising, then, that the people of this area would oppose the
development of an airport, promising the possibility of jobs and new services for the
region! The imagined western Sydney mobilised in such an understanding is a place of
economic disadvantage that should seek any avenue that might provide employment
and develop services.

What this binary depiction ignores is the importance of the environment of western
Sydney to its residents. As the Urban Frontiers Program (2001) research shows, the
environment of the region (including the fact that it is quiet) is highly valued by its
residents because western Sydney is a suburban home (Dowling & Mee 2000). While the
landscapes of western Sydney have been criticised and derided by outsiders for decades,
residents continue to value and seek to protect the local environment (Mee 1999). The
potential environmental consequences of an airport were viewed as completely inappro-
priate for this suburban space. Put simply, an airport in a suburban area was ‘out of
place’. Residents raised a number of concerns about the environmental impacts of
airport development, including pollution (of noise, air and water), the destruction of
native habitat and the destruction of remnant bushland. Particular concern was ex-
pressed over the potential of an airport development to impact negatively upon
children, again through the impacts of pollution and the destruction of places for
children to play. Australian suburbs have long been seen as landscapes of children
(Stretton 1970). Western Sydney residents and councils, in opposing development of
an airport in the region, argued that the airport was inappropriate in this suburban
setting. This was a very clear community claim that there should ‘not (be an airport)
in my (suburban) backyard’.

Protection of the environment is a key regional issue. Residents of western Sydney
have expressed considerable levels of concern about the impacts of past developments
on western Sydney’s environment, especially in relation to air pollution and the
condition of the Hawkesbury Nepean river system (see Fagan 2001; Urban Frontiers
Program 2001). Likewise, western Sydney residents are acutely aware of the destruc-
tion of bushland that has been associated with urban development in the region thus
far. The ADI site represented an opportunity to retain an environmental asset in
western Sydney—1500 hectares of open space—and the potential to develop the site as
a regional park (Taylor 2001). Those opposed to the development of an airport at

Prosperity and the Suburban Dream 343

Holsworthy pointed to the role of the proposed site as a regional amenity and wildlife
habitat (Mee 1999). Activists in both of these cases pointed out that their suburban
counterparts in other parts of the city had many more of these sorts of amenities
available . They also pointed out that residents’ claims to access to an attractive
environment in other parts of the city (seen as integral to a high quality of life in
Sydney), were less often questioned than when western Sydney residents sought to
protect their environment.

These events point to important questions for development in Sydney. Equity issues
are not only con� ned to employment availability , income distribution and the provision
of housing and services but also to the environmental costs of development and the
maintenance of environmental amenity. The protests against development of the ADI
site and the second airport proposals in western Sydney need to be understood in a
more complex framework that emphasises the importance of quality of life for suburban
and urban residents in a broader fashion. Residents of western Sydney saw these
developments as threats to their suburban amenity. They understood these threats in
relation to their own perceptions of the local environment and its value, and to the
distribution of these resources in Sydney more broadly.

Questions of maintaining or improving the environmental quality of western Sydney
will differ greatly in different parts of the region. For residents in areas of newer
suburban development, questions of the destruction of bushland and the potential to
convert existing government land to regional parks (as in the case of the ADI site) are
likely to be more important. For residents in older parts of western Sydney, questions
of improving or maintaining the environmental quality of existing urban areas are likely
to be more important. And, as Gleeson and Randolph (2002) argue, there are parts of
western Sydney where issues of industrial pollution are more marked. In the region
more generally, issues of air and water pollution continue to be important. In an area
as diverse as western Sydney, managing growth in a way that allows for environmental
protection, opportunities for employment close to residents’ homes and adequate
affordable housing will clearly be important. Maintaining and improving the quality of
life in the metropolis as a whole will demand attention to these issues, and residents of
western Sydney are likely to continue to mobilise when growth threatens the quality of
life in the suburbs as it is understood in western Sydney.

Affordable housing

The prosperity of Sydney has had major implications for the property market. The
affordability of housing in Sydney generally has been eroded (NSW Department of
Housing 1999; Darcy 2000). The relative affordability of housing in western Sydney
continues to be one of the region’s most attractive features for its residents. Indeed, the
availabilit y of affordable housing propelled the post-war growth of western Sydney.
Government intervention enabled the development of this affordable housing, both
through subsidies for home purchase and through the direct provision of public housing
(Allport 1987). The provision of public housing was especially important in providing
affordable housing to the less af� uent in this period, and by 2001 58 per cent of public
rentals in Sydney were located in western Sydney. As shown in Table 3, this public
rental housing is spread unevenly within the region, with major concentrations in the
Campbelltown, Blacktown, Bankstown, Parramatta and Liverpool LGAs. The rela-
tively large number of public rental dwellings in these LGAs is due in part to the
construction of large public housing estates in the region in the 1960s and 1970s. In

344 K. Mee

TABLE 3. Public rental housing in western Sydney, 2001

Local Government Area No. of public rental dwellings 2001 % public rental

Auburn 760 4.4
Bankstown 5620 10.2
Baulkham Hills 321 0.7
Blacktown 9080 11.0
Blue Mountains 381 1.4
Camden 328 2.3
Campbelltown 6545 14.0
Fair� eld 4360 7.9
Hawkesbury 810 3.9
Holroyd 2112 6.9
Liverpool 4290 8.8
Parramatta 4587 8.9
Penrith 2548 4.5
Wollondilly 128 1.1
Total western Sydney 41 870 7.4
Total Sydney 72 724 5.1

Source: ABS Census of Population and Housing, 2001.

this section I consider some of the implications of changes in the 1990s for the role of
western Sydney as a suburban home for those outside the private ownership market.

Public housing is crucial for the most disadvantaged of western Sydney’s residents.
In recent years the direct provision of public housing has been undermined by federal
government policy changes that redirect funds to supporting people in the private rental
market (Caul� eld 2000). Given the higher cost of housing in the private rental sector,
public housing is an important housing option for low-income households, particularly
in prosperous and expensive Sydney.

For much of the post-war period, the direct provision of public housing in Sydney to
low-income households was dependent upon a strategy that involved increasing the
quantity of public housing in western Sydney. Changed government funding regimes
and a policy change in favour of smaller concentrations of public housing have resulted
in a remarkable change to this policy. According to the most recent census, the amount
of public rental housing in western Sydney declined between 1996 and 2001. As Table
4 demonstrates, while there was a small increase in the amount of public housing in
some LGAs (such as Fair� eld and Auburn), there were marked declines in other LGAs,
especially Blacktown, Campbelltown and Liverpool. While some of these declines may
be due to transfers of stock to the Community Housing sector (NSW Of� ce of
Community Housing 2001), the overall picture of the provision of public housing in
western Sydney is alarming. This is especially the case given that the Department of
Housing has identi� ed that a decline of low-cost private rental housing is a major
problem for Sydney (NSW Department of Housing 1999) and that the Housing and
Data Analysis Unit of the Department of Housing has identi� ed a number of western
Sydney Statistical Subdivisions (including some of those where declines in public
housing have occurred) as areas of high housing need (NSW Of� ce of Community
Housing 2001).

Past developments of public housing have left a legacy of large estates (many in
western Sydney) with commonly high concentrations of disadvantage (Gleeson &
Randolph 2002) and a lack of service provision. In addition to this, the large-scale

Prosperity and the Suburban Dream 345

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346 K. Mee

construction of public housing in western Sydney in the 1960s and 1970s means that
the public housing managers in the contemporary period have to manage stock that
may be ill suited to the demands of new tenants and may also require signi� cant
amounts of maintenance (Gleeson & Randolph 2002). Current government policies
aimed at community renewal in some of these estates have involved attempts to better
co-ordinate the provision of services from other government agencies to these estates
(Randolph & Judd 2000; NSW Department of Housing 2000). However, more sophis-
ticated systems of allocation are required so that tenants can be located in areas that
meet their particular needs (see Ruming 2001). Government responses such as these
require adequate resources to be spent, and appropriate planning and co-ordination
of service provision. Given the concentration of public housing in western Sydney,
the further development of such policies (or the lack of them) will have profound
implications for some of the most needy residents of the region.

Consideration of public housing needs to include the bene� ts of public housing, as
opposed to other tenure forms, for low-income households. Work on even the most
derided of large-scale estates in Australia—Green Valley and Mount Druitt (see
Dowling & Mee 1997) in Sydney and Elizabeth in Adelaide (Peel 1995)—has pointed
out the very real bene� ts of these places for their residents in creating opportunities for
a stable life. Access to public housing allowed residents to plan their futures in place as
they enjoyed security in their housing supply. Residents saw this security as crucial in
a number of ways, including enabling the stable education of children and the
development of local communities (Peel 1995; Dowling & Mee 1997). In short, the
supply of public rental housing allowed those unable to afford home ownership to access
some of the bene� ts of a suburban life (and to have a reasonable quality of life).
Changes to government housing policy to provide rent assistance in the private rental
market undoubtedly assist disadvantaged people to access rental housing. More re-
search is needed, however, to determine whether such interventions provide the same
opportunities for stability as valued by residents of public housing estates in the past.
This is an important quality-of-life issue for less af� uent residents. It goes to the heart
of why affordability is an important quality-of-life issue. A high quality of life is not so
easily facilitated if access to affordable housing requires regular relocation, the estab-
lishment of new support networks and accessing different types of services. The
qualities of the housing that residents can afford are obviously important to maintaining
quality of life.

A signi� cant amount of affordable rental housing located in Sydney is still available
in western Sydney. Table 4 shows that there has been an overall increase in dwellings
occupied through various types of private tenure, but it is not so clear that this housing
will be affordable for the most needy. For those residents unable to afford home
purchase, the private rental market is becoming increasingly signi� cant. Western
Sydney is an important site for the provision of affordable private rental properties.
According to the 2001 Census, while 29 per cent of private rental dwellings in Sydney
were in western Sydney so too were nearly 47 per cent of all public rentals less than
$150 per week.7 And as Table 5 shows, the cheapest private rentals are concentrated
in very particular parts of western Sydney, with nearly half of them being located in
Fair� eld, Liverpool and Penrith alone. These � ndings are con� rmed by � gures on
weekly rents for new bonds in 2001, which also reveal that most parts of western
Sydney (all LGAs except Parramatta and Baulkham Hills) as well as Gosford and
Wyong had the cheapest available rental properties that were leased in Sydney in this
period (NSW Department of Housing 2001a, b).

Prosperity and the Suburban Dream 347

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348 K. Mee

Table 5 reveals the continued importance of public housing in providing cheap rental
accommodation. Despite the presence of relatively affordable private rental housing in
western Sydney, private rental housing costs signi� cantly more for tenants, on average,
than public housing. As the provision of public housing in western Sydney is dimin-
ished and private rental housing expands more rapidly, affordability questions for those
not purchasing housing become more acute (Randolph & Judd 2000; Gleeson &
Randolph 2002).

Relatively little public discussion thus far has considered the impacts on particular
localities of changes in government rental policies or the increasing costs of the private
rental market for the poorest residents. Past government rental policies created large
estates of public housing where disadvantage was certainly marked. Nonetheless, these
localities also provided a stable home for their residents. One bene� t of the concen-
tration of disadvantage in public housing estates is that it makes this disadvantage
visible, and governments can be pressured to create policies, such as community
renewal schemes, to address disadvantage. Given the geography of rental housing in
western Sydney it is highly likely that more disadvantaged people will be attracted to (or
simply allocated) the affordable housing available on the larger public housing estates
in western Sydney. However, there will also be many disadvantaged residents who will
gain access to more expensive housing in the private market, and who will be assisted
by the government through rent assistance. It may be that some concentrations of
affordable private rental housing will also require government strategies to address
disadvantage (Gleeson & Randolph 2002). The more dispersed nature of private rental
properties may make it more dif� cult for the disadvantage of these residents to be
identi� ed, and for governments to be lobbied, and it may make creating government
strategies to address disadvantage more dif� cult. More consideration of the spatial
effects of rental housing changes and their locally speci� c impacts is therefore urgently
required. This is a crucial quality-of-life issue for disadvantaged residents. Govern-
ments need to consider not just the price of housing but also what sort of access to
housing different types of housing provision, and places, provide.

Given the distribution of low-cost rental housing in Sydney, it is likely that some
western Sydney LGAs—those with high concentrations of public housing or the
cheapest private rental housing (or in some cases both)—will provide homes for some
of the most disadvantaged Sydney residents. These residents are also much more likely
to be dependent upon the services available in their local region. The development of
adequate social services in these parts of western Sydney is therefore of crucial
importance if these residents are also to share the bene� ts of prosperity. The mainte-
nance and enhancement of quality of life for the most disadvantaged of western Sydney
residents demand such interventions.

Conclusion

In this paper I have re� ected on the broad trends arising from Sydney’s prosperity and
considered how these can be related to changes and debates in western Sydney in the
latter half of the 1990s. I have argued that the growth brought by prosperity has led to
greater development pressures on the environment of western Sydney. In addition,
prosperity and changes to government housing policy have impacted on the affordabil-
ity of the region’s rental housing. In both of these cases, the capacity of western Sydney
to provide an enjoyable suburban home to a cross-section of residents, and for the most
disadvantaged in particular, has been eroded. Policy makers will need to address the

Prosperity and the Suburban Dream 349

challenges posed by managing the new prosperity of Sydney in a manner that is
equitable to all Sydney residents. These policies will need to deal with problems raised
by contemporary circumstances, as well as addressing inequities caused by the manner
of suburbanisation in the post-war period more generally. Maintaining an appropriate
quality of life is thought to be a key feature of a prosperous global city. Geographers
need to play an active role in pointing to the ways that quality of life needs to be
managed for those residents from across the metropolis.

Acknowledgements

I would like to thank Pauline McGuirk, Robyn Dowling, Sally Lane and Natalie Moore
for their help in developing the ideas in the paper.

Correspondence: Kathleen Mee, Centre for Urban and Regional Studies, University of
Newcastle, NSW 2308, Australia. E-mail: kathy.mee@newcastle.edu.au

NOTES

[1] As has been discussed elsewhere (Dowling & Mee 2000), there is considerable debate over what
constitutes western Sydney. For the purposes of this paper western Sydney is de� ned as the
following 14 Local Government Areas: Auburn, Bankstown, Baulkham Hills, Blacktown, Blue
Mountains, Camden, Campbelltown, Fair� eld, Hawkesbury, Holroyd, Liverpool, Parramatta,
Penrith, Wollondilly. These LGAs constitute a diverse slice of middle and outer Sydney, which is
very often represented in homogenising and negative terms (see Powell 1993; Dowling & Mee
2000).

[2] The population growth of Fair� eld was the lowest in western Sydney in this period. It should be
noted, however, that this follows signi� cant population growth in Fair� eld in every census period
from 1954 to 1996 (see Mee 2000 for more details).

[3] Semi-detached refers to the ABS classi� cation of semi-detached, row terraces and townhouses.
[4] There are a number of other important challenges for western Sydney residents caused by changes

in Sydney during the 1990s. As Gleeson and Randolph (2002) note, these include problems
caused by the lack of appropriate public transport, the lack of well-supported regional governance
mechanisms, residents’ concerns about crime and policing, and the need for the greater develop-
ment of community services. The spatial implications of changes in Sydney, and their implications
for western Sydney, need to be more broadly considered than is possible in this article.

[5] Forsyth (1999) examined reactions to the development of Rouse Hill, in the northern growth
sector of western Sydney.

[6] By the end of the 1990s every local council in western Sydney except Liverpool opposed the
development of the airport at Badgerys Creek. Liverpool had the highest absolute increase in
population numbers in western Sydney during this period, and the second highest growth rate.
Given the proximity of Liverpool to the development site (it is adjacent to the proposed site of
Badgerys Creek), the council regarded the development of Badgerys Creek as important for the
economic health of Liverpool, and included projections about the airport in its economic planning
forecasts (Liverpool City Council 1993). Liverpool Council was resolutely opposed to the
development of an airport at Holsworthy for the time that this proposal remained a possibility.

[7] For these purposes, private rentals are considered to be all those rentals not in the public sector.

REFERENCES

ALLPORT, C. (1987) ‘Castles of security: the New South Wales Housing Commission and home
ownership 1941–1961’, in Kelly, M. (ed.) Sydney: city of suburbs, New South Wales University Press,
Sydney, pp. 95–124.

CAULFIELD, J. (2000) ‘Public housing and intergovernmental reform in the 1990s’, Australian Journal
of Political Science 35, pp. 99–110.

350 K. Mee

COMMITTEE FOR SYDNEY (1998) Sydney 2020: the city we want. Summary report, Committee for Sydney,
PricewaterhouseCoopers, Sydney.

CONNOLLY, E. (2001) ‘Politicians an endangered species as protesters � ght for bushland’, Sydney
Morning Herald 2 April 2001, p. 7.

DARCY, M. (2000) ‘Housing: the great divide’, in Connell, J. (ed.) Sydney: the emergence of a world city,
Oxford University Press, Oxford, pp. 222–43.

DEPARTMENT OF URBAN AFFAIRS AND PLANNING (DUAP) (1998) Shaping our cities: the planning strategy
for the greater metropolitan region of Sydney, Newcastle, Wollongong and the Central Coast, Department
of Urban Affairs and Planning, Sydney.

DOWLING, R. & MEE, K. (1997) ‘Remembering the future of public housing’, unpublished paper
presented at the Institute of Australian Geographers Conference, Hobart, January 1997.

DOWLING, R. & MEE, K. (2000) ‘Tales of the city: western Sydney at the end of the millennium’, in
Connell, J. (ed.) Sydney: the emergence of a world city, Oxford University Press, Melbourne.

FAGAN, R. (2001) ‘Implications for work and workers’, paper presented at the Centre for Urban and
Regional Studies Conference ‘Dealing with the new prosperity’, University of Newcastle, November
2001.

FLORIDA, R. (2000) Competing in the age of talent: quality of place and the new economy, report prepared
for the R.K. Mellon Foundation, Heinz Endowments and Sustainable Pittsburgh.

FORSYTH, A. (1999) Constructing suburbs: competing voices in a debate over urban growth, Gordon &
Breach, Amsterdam.

FULOP, L. & SHEPPARD, D. (1988) ‘The life and death of regional initiatives in western Sydney: the case
of the Local Government Development Programme’, International Journal of Urban and Regional
Research 12, pp. 609–26.

GLEESON, B. & RANDOLPH, B. (2002) ‘A new vision for western Sydney: options for 21st century
governance’, issues paper 1, Urban Frontiers Program, University of Western Sydney.

HODGE, S. (1996) ‘Disadvantage and “otherness” in Western Sydney’, Australian Geographical Studies
34, pp. 32–44.

JAMAL, N. (2000) ‘Housing estate plan recipe for ecological death’, Sydney Morning Herald 13 March
2000, p. 9.

JAMAL, N. (2001) ‘Trees versus homes in land skirmish’, Sydney Morning Herald 4 October 2001, p. 6.
JOHNSON, L., LANGSWORTH, J. & SYMONDS, M. (1997) ‘Introduction’, in Grace, H., Hage, G.,

Johnson, L., Langsworth, J. & Symonds, M. (eds) Home/world: space, community and marginality in
Sydney’s west, Pluto Press, Sydney, pp. 1–30.

LIVERPOOL CITY COUNCIL (1993) The future for Liverpool as a regional centre, Liverpool City Council,
Liverpool.

MEE, K. (1999) ‘Up, up and away: discourses of nature and airport development in western Sydney’,
unpublished paper presented at the Institute of Australian Geographers Conference, Sydney,
September 1999.

MEE, K. (2000) ‘Creating the west: a dialogical analysis of representations of western Sydney in the
1990s’, unpublished PhD thesis, University of Sydney.

MILLER, L. & FUHR, R. (1983) ‘The real Sydney’, Australian Society 2, pp. 3–6.
MURPHY, P. & WATSON, S. (1997) Surface city: Sydney at the millennium, Pluto Press, Sydney.
NEW SOUTH WALES (NSW) DEPARTMENT OF HOUSING (1999) Directions for housing assistance beyond

2000: background paper, New South Wales Department of Housing, Sydney.
NEW SOUTH WALES (NSW) DEPARTMENT OF HOUSING (2000) Community renewal: transforming estates

into communities, partnership and participation, Community Renewal Unit, New South Wales Depart-
ment of Housing, Sydney.

NEW SOUTH WALES (NSW) DEPARTMENT OF HOUSING (2001a) Rent and sales report Number 57,
Housing and Data Analysis Service, New South Wales Department of Housing, Sydney.

NEW SOUTH WALES (NSW) DEPARTMENT OF HOUSING (2001b) Rent and sales report Number 58,
Housing and Data Analysis Service, New South Wales Department of Housing, Sydney.

NEW SOUTH WALES (NSW) OFFICE OF COMMUNITY HOUSING (2001) 2001/2002 community housing
assistance program, Of� ce of Community Housing, New South Wales, Sydney.

PEEL, M. (1995) Good times, hard times: the past and the future in Elizabeth, Melbourne University Press,
Melbourne.

POWELL, D. (1993) Out west: perceptions of Sydney’s western suburbs, Allen & Unwin, Sydney.
RANDOLPH, B. & JUDD, B. (2000) ‘Community renewal and large public housing estates’, Urban Policy

and Research 18, pp. 91–104.

Prosperity and the Suburban Dream 351

RUMING, K. (2001) “‘They need to escape within the community”: exploring the ideology of
community, notions of place and impacts of social mix at the local scale’, unpublished honours
thesis, School of Environmental and Life Sciences, University of Newcastle.

SPEARRITT, P. (1978) Sydney since the twenties, Hale & Iremonger, Sydney.
SPEARRITT, P. (2000) Sydney’s century: a history, University of New South Wales Press, Sydney.
STRETTON, H. (1970) Ideas for Australian cities, Transit Australia, Sydney.
TAYLOR, J. (2001) ‘Backyard battle’, Sydney Morning Herald 28 June 2001, p. 9.
URBAN FRONTIERS PROGRAM (2001) Who cares about western Sydney?, report prepared by the Urban

Frontiers Program, University of Western Sydney and the Planning Research Centre, University of
Sydney for Western Sydney Regional Organisation of Councils.

Economic Development Quarterly
26(3) 220 –230
© The Author(s) 2012
Reprints and permission:
sagepub.com/journalsPermissions.nav
DOI: 10.1177/0891242412452782
http://edq.sagepub.com

Introduction

This is a study of how income, unemployment, and poverty
are influenced by growth rates in the 100 largest U.S.
Metropolitan Statistical Areas (MSAs). The purpose of this
research is to obtain a better understanding about the statisti-
cal relationship between growth rates and basic measures of
the economic well-being of residents of these metro areas.

Most cities and metro areas in the United States are
actively pursuing growth through a combination of public
policies, investments, tax incentives, and subsidies. Growth
has many economic, social, and environmental impacts, but
this pursuit of growth is typically based on a stated desire
to provide jobs and economic prosperity for people living
in the area. “We have to grow to provide jobs” or even “We
have to grow or die” are common axioms from local offi-
cials. The “grow or die” rhetoric suggests that there are dire
economic consequences to not growing. These statements
favoring growth are usually made without evidence as to
their validity. They seem to be based on the assumption that
the additional jobs that may result from expansion of an
urban area will benefit existing residents by giving them
more employment opportunities and better wages.

Public policies and plans regarding urban growth typi-
cally involve trade-offs between costs and benefits. Local
residents may view a policy to encourage land development
or growth as negatively affecting their quality of life through
increased traffic congestion, environmental quality impacts,
loss of farm and forest lands, and loss of amenity values

(e.g., tranquility, sense of community, or open space). They
may also be concerned about higher taxes to fund the cost of
the new public infrastructure (roads, schools, sewer and
water systems, etc.) required to serve growth. However, the
prospect that new growth will bring jobs and economic pros-
perity that may benefit local residents is often viewed as
compelling enough to outweigh these costs. This study seeks
to gain insight into whether these employment and economic
benefits are supported by empirical data.

In addition to examining how past growth affects recent
employment and economic conditions, this study looks at
how these 100 metro areas fared during the Great Recession.
The Great Recession officially lasted 18 months. It started in
December 2007 and ended in June of 2009.1 Although the
effects of this recession continue, the official period of
the recession is included within the data reported here. It is
possible to compare the impacts of the recession with the
pace of growth in each metro area.

The study concludes with a comparison of the 25 slowest
growing metro areas with the 25 fastest growing to see which
group fared the best in terms of the prosperity indicators
used in this study.

452782EDQXXX10.1177/0891242412452
782FodorEconomic Development Quarterly
2012

1Fodor & Associates LLC, Eugene, OR, USA

Corresponding Author:
Eben Fodor, Fodor & Associates LLC, 394 East 32nd Avenue,
Eugene, OR 97405, USA
Email: eben@fodorandassociates.com

Relationship Between Growth
and Prosperity in the 100 Largest
U.S. Metropolitan Areas

Eben Fodor1

Abstract

This study examines the relationship between growth and economic prosperity in the 100 largest U.S. metropolitan areas to
determine whether certain benefits commonly attributed to growth are supported by statistical data. The annual population
growth rate of each metro area from 2000 to 2009 is used to compare economic well-being in terms of per capita income,
unemployment rate, and poverty rate. The study finds that faster growth rates are associated with lower incomes, greater
income declines, and higher poverty rates. Unemployment rates tend to be higher in faster growing areas, though the
correlation is not statistically significant at the 95% confidence level. The 25 slowest growing metro areas outperformed the
25 fastest growing in every category and averaged $8,455 more in per capita personal income in 2009.

Keywords

community development, job creation, jobs, state and local ED policy, sustainability

http://crossmark.crossref.org/dialog/?doi=10.1177%2F0891242412452782&domain=pdf&date_stamp=2012-06-25

Fodor 221

For this study, growth rates are based on the average annual
rate of population growth over the 9-year period of study from
2000 to 2009.2 Population growth and some other data series
were carried back to 1990 for additional evaluation, as noted
in the text. The average annual rate of population growth pro-
vides an indication of the pace of growth in each metro area.
All population data are from the U.S. Census.3

Use of the term growth with regard to metro areas could
refer to population, land area, number of buildings, or eco-
nomic product. Measurement of the growth of metro areas,
however, typically defaults to population growth as the base-
line indicator of size and rate of change. This may be partly
because of the accessibility of population statistics. It is also,
however, because the number of people present is a very real
indicator of the other growth factors associated with people,
such as developed land area and total economic activity.

Urban growth is directly linked with population growth,
as more people require more housing units and commercial
buildings for employment and shopping. There is a strong
linear correlation between urban growth (as reflected by
change in total housing units) and population growth at the
state level, so growth in housing units can be expected to
track population growth fairly closely.4

The 100 largest MSAs were selected based on 2009
population estimates from the U.S. Census for MSAs in the
50 states and District of Columbia. The Office of Budget
and Management defines the MSAs, and the most recent
listing available from the U.S. Census was used for this
study (December 2009). The study sample of 100 MSAs has
a total 2009 population of 201,501,813, which represents
78% of the population in all 366 MSAs. This constitutes a
substantial study sample representing 66% of the total U.S.
population. The 100 MSAs range in size from a population
of 510,000 to 19 million.

Background
This study builds on findings from two prior studies. The first
study by Molotch (1976) examined growth rate and unem-
ployment in Standard Metropolitan Statistical Areas (SMSAs)
in the United States from 1950 to 1970. Molotch compared
the 25 fastest growing SMSAs with the 25 slowest growing
and found no significant difference in unemployment rates
between the two groups. The finding that the faster growing
metro areas did not have better employment conditions sug-
gests that growth does not generate employment benefits, as
is commonly believed.

The second study by Gottlieb (2002) compared population
growth rates with changes in per capita income for the 100
largest MSAs from 1990 to 1998. The rate of income growth
was found to have no statistically significant relationship
with population growth. This finding suggests that, contrary
to conventional wisdom, growth may not be associated with
increasing income.

The relationship between poverty and population growth
rate in U.S. MSAs has been unclear. Whereas past economic
expansion has been associated with the lowering of poverty
rates, more recently growth has not had the same beneficial
effect on poverty because of increases in income inequality
(Gundersen & Ziliak, 2004).

There is the question of what is the best time period to use
in evaluating relationships between growth and economic
prosperity measures. Studies have examined the impacts of
economic development programs on employment over vari-
ous periods ranging from 1 year to 15 years. There are both
short-term and longer-term responses depending upon which
variable is being examined (Partridge, Rickman, & Li, 2009).
Longer time periods seem most appropriate for studying
prosperity measures, as we are interested primarily in sus-
tained results, rather than momentary effects.

The concept of prosperity is commonly associated with
economic well-being as measured by factors such as those
examined in this study—income, unemployment, and pov-
erty rates. It also may be gauged by the gross domestic
product, which measures the total economic activity of a
country, state, or region.5 Other models for prosperity are
being advanced that take into account noneconomic factors
of human well-being, such as health, satisfaction with life,
and happiness (Jackson, 2009).

Population growth of a city or region is commonly
thought to be associated with prosperity and well-being
(Carr, Bae, & Lu, 2006). Population growth is often equated
to prosperity in the popular media (e.g., El Nasser, 2011;
Welch, 2011). Economic development efforts can lead to
competition between cities to attract residents and businesses
(Basolo & Huang, 2001), resulting in population growth.

The relationship between local growth and prosperity has
not received a great deal of attention from researchers. The
dearth of research is remarkable, given the degree of public
investment in growth and the level of controversy often sur-
rounding local growth issues. State and local governments
spent $289 billion on capital construction in 2009, according
to the U.S. Census. Most of this expenditure went toward
building new schools, roads, sewage systems, and water
treatment systems that support growth.

Given that growth can profoundly influence communi-
ties, we can benefit from learning more about these effects.

The degree to which growth can be influenced by eco-
nomic development, growth management, and other local
government policies is an ongoing debate. Regardless of
this debate, there are many local officials and leaders
who believe that they can affect growth (Carr et al., 2006).
Local officials direct significant government resources,
such as tax exemptions and infrastructure provision, toward
growth-inducing strategies based on this belief. There
are also many examples of policies in state and regional
planning programs that mandate growth accommodation
through public planning and investment (Zovanyi, 1998).

222 Economic Development Quarterly 26(3)

Furthermore, growth management policies have been shown
to measurably affect local growth (Nguyen, 2007).

The political campaign finance system in most cities enables
wealthy interests to influence local elections. Progrowth con-
stituencies of developers, real estate professionals, financial
institutions, and business advocacy organizations can over-
whelm individual campaign donors in terms of total funding
(Krebs, 2005). One of the results is that city staff tend to align
themselves with progrowth politics (Calavita & Caves, 1994).

The progrowth agenda of many cities is apparent when
they are examined closely (Carr et al., 2006; Vojnovic, 2003).
Growth promotion can be explained by a number of factors
(Hammer & Green, 1996). The exact form of growth being
promoted is often unclear. Cities may be simultaneously pur-
suing job and income growth while pursuing population
growth and urban expansion.

The “grow or die” rhetoric widely used in the local public
policy arena is commonly associated with economic devel-
opment approaches that involve increasing urban growth
through expansions of urban growth boundaries or city limits
and the planning, zoning, and permitting of large tracts of
additional land for future urban development. Urban growth
is directly linked with population growth, as mentioned
earlier.

Although economic growth is often the explicitly stated
goal of public policies and economic development programs,
other political economy influences tend to direct these goals
to achieve other purposes (Dewar, 1998). The political econ-
omy of the “urban growth machine” effectively characterizes
what some of these other purposes might be (Molotch, 1976).
Urban growth serves the economic objectives of certain
wealthy and politically influential groups. This helps explain
why local rhetoric about the need for economic growth tends
to manifest itself as programs to promote more urban growth,
and hence population growth.

The argument frequently advanced by growth proponents
is that urban growth will generate benefits in terms of jobs
and economic prosperity for the local residents. It seems
more likely, however, that the opposite is true: The creation
of new jobs will attract newcomers to move into the area.
Similarly, the loss of local jobs will tend to cause people to
move away (e.g., El Nasser, 2010). Thus, jobs are a major
driver of growth rather than growth creating jobs. This is
supported by studies showing that newcomers ultimately end
up filling most new jobs (Bartik, 1993). In-migration has
been found to be the dominant response to job creation at the
metropolitan area and state levels, indicating that newcomers
tend to be the primary beneficiaries of new jobs (Partridge
et al., 2009).

Some studies have found that the growth of cities may not
be associated with greater local prosperity and well-being.
Bodley (1999) finds evidence that growth causes the rich to
get richer and poor to get poorer and more numerous.
According to Bodley, the wealthy elite are often the main

beneficiaries of local growth, in addition to being its main
proponents. Molotch (1993) finds that “contrary to popular
wisdom, there is little evidence that growth eases problems
of unemployment, high housing costs, or impoverished city
budgets. (p. 32)” And economic development efforts to stim-
ulate local economic growth through business incentives
may result in poorer economic performance (Zheng &
Warner, 2010).

The idea that cities could grow too much, that there is a
limit to social utility from increasing city size, or that there
may be an optimal city size has deep roots in the literature
(Duncan, 1949; Mumford, 1938). The case that cities, rather
than growing to an optimal size, grow to their maximum
size (Huszar & Seckler, 1975) provides some rationale for
controlling city growth. Further rationale has come from the
environmental and sustainability movements seeking to
mitigate the impacts of growth (Warner, 2006).

Increasingly researchers are recognizing that there may be
limitations to quantitative growth. Population and consump-
tion levels cannot expand endlessly with a finite natural
resource base. As human population approaches seven billion,
many are asking, “Can we have prosperity without growth?”
One approach is to redefine prosperity from traditional eco-
nomic terms to other measures of well-being (Bergmann,
2010; Jackson, 2009). Such measures of well-being may
include health, quality of life, and happiness (Bok, 2010).
Another approach is to recognize that growth has significant
costs and may not generate all the economic benefits often
attributed to it. Moving away from the growth model and
toward a sustainability model leads to a new framework for
economic development (Greenwood & Holt, 2010).

Some researchers have begun to examine the case of cities
with stable or declining populations to see how prosperity and
well-being are affected (Delken, 2008; Hollander, 2011).
These cities tend to fare better than conventional wisdom
would suggest. Residents of cities with stable and shrinking
populations have been found to have similar or even higher
life satisfaction than those in growing cities.

Income and Growth
Data for 2009 per capita personal income were compared
with the average annual population growth rate from 2000 to
2009 for each MSA. Per capita income was selected as the
basis for comparing income changes over time because other
measures, such as median household and family income, can
change over time due to changing household and family
composition. The income data from the U.S. Bureau of
Economic Analysis (BEA) includes all personal income
sources. It is calculated by taking the total personal income
for the metro area and dividing it by the total population.

As shown by the graphical data and trend line in Figure 1,
there is a strong tendency for income to be lower in faster
growing metro areas. This is a strong correlation with a

Fodor 223

>99% level of confidence.6 The data show that faster growth
corresponds with lower incomes. The slope of the trend line
shows a decline of almost $2,500 in per capita income for
each 1% increase in growth rate. This finding contradicts the
conventional wisdom that more growth will benefit local
residents by enabling them to find higher paying jobs.

Finding 1: Incomes tend to be higher in metro areas
with lower growth rates.

To see how personal income changed for each metro area in
2009, the percentage change from the previous period
(2008) was compared with growth rates. Most MSAs had a
drop in per capita personal income in 2009 because of the
recession. Figure 2 shows that faster growing metro areas
had a bigger drop in income than did slower growing areas.
This correlation is statistically significant at the 99% confi-
dence level.

Finding 2: Faster growing metro areas tended to have
a bigger drop in income in the past year (2009).

The overall drop in personal income is a result of the Great
Recession caused by the bursting of the residential real
estate bubble and the subprime mortgages and financial
derivatives that fueled it. To capture the full impact of the
Great Recession, the change in income from 2007 to 2009
was examined. As shown in Figure 3, a very strong correla-
tion exists between faster growth and declining income
during the recession (>99% significance level). Metro areas
that grew the fastest from 2000 to 2009 had the greatest
declines in personal income. Many of the fastest growing
MSAs had income declines of 6% over this 2-year period.
(The biggest decline in income was for the New Orleans

MSA, which was a statistical outlier severely affected by
Hurricane Katrina.)

The data show that the fastest growing metro areas were
the hardest hit by the recession. Many of the slower growing
areas fared much better. Many areas with stable or declining
populations saw increases in personal income.

Finding 3: Metro areas that grew faster from 2000 to
2009 tended to have greater declines in personal
income during the Great Recession (2007-2009).

As shown in Figure 4, the percentage change in per capita
personal income over the entire 2000 to 2009 period
showed a similar statistically significant correlation with
growth rates (>99% significance). Although all MSAs
showed gains in income over the 2000-2009 period, metro
areas with higher growth rates had significantly lower gains

Figure 1. 2009 Per capita personal income compared with 2000-
2009 growth rate for the 100 largest U.S. Metropolitan Statistical
Areas
Source. Fodor & Associates LLC (from U.S. Census and Bureau of
Economic Analysis data).

Figure 2. Change in per capita personal income 2008-2009
compared with 2000-2009 growth rate for the 100 largest U.S.
Metropolitan Statistical Areas
Source. Fodor & Associates LLC (from U.S. Census and Bureau of
Economic Analysis data).

Figure 3. Change in per capita personal income 2007-2009
compared with 2000-2009 growth rate for the 100 largest U.S.
Metropolitan Statistical Areas
Source. Fodor & Associates LLC (from U.S. Census and Bureau of Eco-
nomic Analysis data).

224 Economic Development Quarterly 26(3)

than slower growing areas. The linear correlation indicates
that a metro area with a stable nongrowing population
would tend to see a 43% higher income gain than an area
growing at 3% per year.

Finding 4: Metro areas with slower growth had bigger
income gains over the 2000 to 2009 period.

The slope of the linear correlation of 2000 to 2009 personal
income change with growth rate is not as steep on an annual
basis as it is for the income change for either the 2008-2009
or 2007-2009 periods, indicating that faster growing metro
areas were more severely affected by the recession.

Finding 5: Per capita personal income in faster grow-
ing metro areas was more severely affected by the
recession.

A remarkable finding from the statistical analysis of the
relationship between personal income and growth rates is
that the correlations for income were even stronger with
population growth occurring over the longer 1990 to 2009
time period, and stronger still for the prior 1990 to 2000
period. This applied to 2009 income levels and all the
income changes described above for the following periods:
2008-2009, 2007-2009, and 2000-2009. All of these correla-
tions were significant at the 99.9% confidence level. This
finding indicates that the per capita income levels of a metro
area may be strongly influenced by the rate of growth occur-
ring in a prior decade. In this case, growth rates in the 1990
to 2000 period showed the strongest correlation to changes
in income even in the most recent 2008-2009 period. Faster
growing metro areas during the 1990 to 2000 period had
lower income growth over the following 9 years and had
bigger declines in income during the 2007-2009 recession.

Finding 6: Higher growth rates occurring 10 or more
years in the past have a stronger correlation to
lower incomes in 2009 than do more recent peri-
ods, indicating that there may be long-term adverse
consequences to local residents from faster growth.

Unemployment and Growth
The unemployment rate from the U.S. Bureau of Labor
Statistics (BLS) provides an index for the local employment
conditions that reflects both the supply and demand for jobs.
Both the 2009 unemployment rate and the change in unem-
ployment rate over the 2000-2009 period were compared
with growth rates (2000-2009). If growth produced employ-
ment benefits for local residents, one would expect to see
unemployment rates tend to be lower for metro areas with
faster growth.

Figure 5 shows that the 2009 unemployment rate does not
correlate closely with growth rate. There is no statistically
significant relationship between growth rate and unemploy-
ment. The trend line shows there is a slight tendency for
metro areas with higher growth rates to have higher unem-
ployment rates.

Finding 7: Metro areas with faster growth rates do not
tend to have lower unemployment rates.

This finding is inconsistent with the belief that more growth
will create more jobs, which will help local unemployed
persons find work. There is no clear employment benefit
shown from faster growth. There may be new jobs created as
a result of growth, but apparently there are more newcomers
and job seekers moving in than there are new jobs being cre-
ated. The result is that local unemployment rates remain

Figure 4. Change in per capita personal income 2000-2009
compared with 2000-2009 growth rate for the 100 largest U.S.
Metropolitan Statistical Areas
Source. Fodor & Associates LLC (from U.S. Census and Bureau of Eco-
nomic Analysis data).

Figure 5. 2009 Unemployment rate compared with 2000-2009
growth rate for the 100 largest U.S. Metropolitan Statistical Areas
Source. Fodor & Associates LLC (from U.S. Census and Bureau of Labor
Statistics data).

Fodor 225

more or less the same, but the total number of unemployed
people increases with growth.

Unemployment data provide a gross indicator of the local
job market, but do not provide information about the quality of
the new jobs being created, such as salaries and benefits. Given
that there is no statistically significant relationship between
growth rate and unemployment, the earlier findings that per
capita income tends to be lower in faster growing areas suggests
that new jobs tend to be lower paying in these areas.

The change in the unemployment rate over the period gives
more information about how employment conditions have
changed in each metro area. The change in unemployment rate
will reflect improving or worsening employment conditions
that would not show up in ending period unemployment rates.
The change in unemployment rate is calculated as ending
period unemployment rate minus starting period unemploy-
ment rate. A positive change in the unemployment rate indi-
cates that unemployment has increased (undesirable).

The unemployment rate increased over the 2000-2009
period for all 100 MSAs, reflecting the effects of the reces-
sion. As shown in Figure 6, there is a weak tendency for the
change in unemployment to be worse (higher) in faster grow-
ing metro areas. These results were also not at the statistically
significant level. The conclusion from these data is that faster
growth is not generating improved employment conditions.
Similar to the finding for ending period unemployment, the
“conventional wisdom” that more growth will produce
improved employment conditions is not supported.

Finding 8: Metro areas with faster growth rates do not
tend to see their employment conditions improve
more than slower growing areas.

Poverty and Growth
The last statistic examined in this study is the poverty rate,
which is the percentage of the population living at or below
the official poverty level.7 Poverty rates for 2009 from the

American Community Survey were compared with growth
rates for the 2000-2009 period. As shown in Figure 7, higher
growth rates correspond to higher poverty rates. The correla-
tion is fairly strong (>90% level) but is not quite significant
at the 95% confidence level.

Finding 9: Faster growth rates tend to correspond with
higher poverty levels, but not at the statistically sig-
nificant 95% confidence level.

An interesting result of the statistical analysis is that the
2009 poverty rate correlates more strongly with population
growth rates over the longer 1990 to 2009 period and cor-
relates at the 95% confidence level with growth rates over
the prior 1990 to 2000 period. The implication of this find-
ing is that current poverty rates may be influenced by past
growth—even growth occurring more than a decade ago. If
this is the case, policies to encourage more growth could
produce longer term adverse consequences for the area 10 or
more years into the future.

Finding #10: Metro areas with higher growth rates
during the previous decade (1990-2000) tend to
have higher poverty rates in 2009.

Fastest Growing Versus Slowest
Growing MSAs
To gain more insight into how growth rates affect local eco-
nomic conditions, the 25 slowest growing MSAs of the 100
largest were compared with the 25 fastest growing MSAs.
The 25 slowest growing MSAs represented an essentially
stable population, averaging less than 0.1% per year annual
growth. The 25 fastest growing MSAs averaged 2.7% per
year annual growth. The average growth rate for all 100
MSAs in the study was 1.3% per year.

Figure 6. Change in unemployment rate 2000-2009 compared
with growth rate for the 100 largest U.S. Metropolitan Statistical
Areas
Source. Fodor & Associates LLC (from U.S. Census and Bureau of Labor
Statistics data).

Figure 7. 2009 Poverty rate compared with 2000-2009 growth
rate for the 100 largest U.S. Metropolitan Statistical Areas
Source. Fodor & Associates LLC (from U.S. Census and American
Community Survey data).

226 Economic Development Quarterly 26(3)

As shown in Table 1, the slowest growing MSAs outper-
formed the fastest growing in every category. The 25 slowest
growing MSAs averaged almost 1% lower unemployment
rates, 2.4% lower poverty rates, and a remarkable $8,455
more in per capita personal income in 2009. They also had
larger income gains from 2000 to 2009 and saw significantly
lower declines in income from the recession (2007-2009).

Finding 11: The slowest growing metro areas outper-
formed the fastest growing areas in every category
used in this study to reflect the prosperity of local
residents. Residents of the slowest growing metro
areas averaged $8,455 more per capita in personal
income than those of the fastest growing areas.

This finding suggests a need to reevaluate our thinking about
growth. The slowest growing group of metro areas had a
nearly stable population, yet significantly outperformed the
fastest growing group.

A listing of the 25 slowest and 25 fastest growing MSAs
is provided in Table 2. The MSAs are ordered alphabetically
by state. The slowest growing MSAs are located in 13 differ-
ent states, dominated by Connecticut, New York, and Ohio.
The fastest growing MSAs are located in 12 different states,
dominated by California, Florida, and Texas. The average
2009 population size of the slowest growing MSAs is
1,984,145 and the fastest growing is 2,736,578.

Conclusions
Most cities in the United States have operated on the
assumption that growth is inherently beneficial and that
more and faster growth will benefit local residents economi-
cally. This examination of the 100 largest metro areas, rep-
resenting 66% of the total U.S. population, shows those that
have fared the best have the lowest growth rates. Even metro
areas with stable or declining populations tended to fare bet-
ter than fast-growing areas.

This study compared income levels, unemployment rates,
and poverty rates with growth rates for each metro area. In
every category, faster growing metro areas fared worse than
slower growing areas. Residents of the 25 slowest growing
metro areas averaged $8,455 more personal income per cap-
ita than in the 25 fastest growing areas. They also had lower
unemployment and poverty rates. The 9-year study period
captures the effects of the Great Recession, and changes
from 2007 to 2009 show that faster growing metro areas
were more severely affected.

These findings clearly indicate that there is more to the
economic development equation than merely growth and
that growth may not even be a contributing factor. What then
accounts for the prosperity advantages found in slower grow-
ing metro areas? Reviewers of this study have offered half a
dozen possible explanations. These include geographic dif-
ferences,8 immigration patterns, industry mixes, labor union
influences, housing affordability, and the degree of reliance
on real estate development by the local economy.

Another possible explanation is that the dynamics of
growth are such that, by itself, it does not promote the gen-
eral welfare. Instead, other factors often associated with
growth may have been responsible for past prosperity. For
example, our domestic manufacturing and production capac-
ity that formerly expanded to keep pace with growth is now
largely outsourced to other countries. Now, when a U.S.
metro area expands and increases its demand for goods, for-
eign jobs are created to fill that demand and prosperity is
generated elsewhere.

The findings of this study may be a result of a combina-
tion of the above factors and perhaps others. There is ample
room for further discussion and debate to explain these find-
ings and their implications. There is also a need for further
research to improve our understanding of this complex topic.

Growth clearly provides benefits to some elements of
the local population (see Fodor, 2001; Logan & Molotch,
1987; Molotch, 1976). Foremost among these are the real
estate, financial, and land development businesses. Growth

Table 1. Comparison of the 25 Fastest and 25 Slowest Growing of the 100 Largest Metropolitan Statistical Areas for the 2000-2009
Period

Averages for each group

All 100
Metropolitan

Statistical Areas
25 Slowest

growing
25 Fastest
growing

Difference
(slowest fastest)

Average annual population growth rate 2000-2009, % 1.3 0.1 2.7 −2.6
2009 Unemployment rate, % 9.2 9.2 9.8 −0.6
2000-2009 Change in unemployment rate, % 5.4 5.4 5.7 −0.2
2009 Poverty rate, % 13.7 13.0 15.5 −2.4
2009 Per capita personal income, $ 39,190 42,908 34,454 8,455
Per capita personal income change 2007-2009, % −0.7 0.2 −2.5 2.7
Per capita personal income change 2000-2009, % 28.6 31.0 24.4 6.6

Source. Fodor & Associates LLC (from U.S. Census data and other sources).

Fodor 227

generates demand for more housing and commercial space
that these businesses build, sell, and finance. Higher demand
increases real estate prices, commissions, and loan fees and
makes the development business more profitable. These
business interests represent a wealthy and politically influen-
tial constituency in most cities that advocates in favor of
increasing local growth. They are organized and represented
through their local trade associations: the home builders
associations, the realtors associations, the mortgage bankers
associations, and the local chambers of commerce.

Although certain businesses prosper from growth, the bal-
ance of the community seems to suffer. The statistics showing
that fast-growing areas tend to have lower and declining
incomes indicate that any gains by the businesses that directly
benefit from growth are more than offset by losses to the bal-
ance of the local population. In other words, a small segment
of the local population may benefit from faster growth, but
the larger population tends to see their prosperity decline.

Growth may be associated with economic development
success; however, it is not the cause of that success. The suc-
cessful economic development program is typically the one
that creates new jobs. The new jobs tend to stimulate popula-
tion growth as people move into the area seeking to take
advantage of the new employment opportunities. As a result,

growth tends to be stimulated by job creation; but, growth is
not creating employment opportunities. Instead, it is reducing
them as newcomers fill job openings. Fast-growing metro
areas may be viewed as being prosperous simply because
people are moving to them, but the data show that these fast-
growing areas end up with lower levels of prosperity.

This study found that public policies and economic devel-
opment strategies that seek quantitative growth of a metro
area may have short- and long-term adverse consequences
for local residents. A path of high growth today may lead to
negative consequences lasting well into the next decade.

Assuming we are interested in promoting the economic
welfare of urban residents, we should reevaluate our policy
emphasis on growth. The impacts of growth on communities
are poorly understood. Given the findings of this study, the
magnitude of public investments in growth, and the potential
economic consequences for urban residents across the coun-
try, more research is clearly warranted on this important topic.

As communities seek the best course for emerging from
the recession, new strategies are needed. Continued pursuit
of more growth appears unlikely to be the solution. Perhaps
the growth model should be replaced by the stable sustain-
able community model. Under a stable community model,
the financial resources formerly required to support growth

Table 2. List of Slowest and Fastest Growing of the 100 Largest Metropolitan Statistical Areas (Listed Alphabetically by State)

25 Slowest growing 25 Fastest growing

Los Angeles-Long Beach-Santa Ana, California Phoenix-Mesa-Scottsdale, Arizona
San Francisco-Oakland-Fremont, California Tucson, Arizona
Bridgeport-Stamford-Norwalk, Connecticut Bakersfield, California
Hartford-West Hartford-East Hartford, Connecticut Riverside-San Bernardino-Ontario, California
New Haven-Milford, Connecticut Sacramento-Arden-Arcade-Roseville, California
Honolulu, Hawaii Stockton, California
New Orleans-Metairie-Kenner, Louisiana Cape Coral-Fort Myers, Florida
Boston-Cambridge-Quincy, Massachusetts-New Hampshire Jacksonville, Florida
Springfield, Massachusetts Lakeland-Winter Haven, Florida
Detroit-Warren-Livonia, Michigan Orlando-Kissimmee, Florida
St. Louis, Missouri-Illinois Atlanta-Sandy Springs-Marietta, Georgia
Albany-Schenectady-Troy, New York Boise City-Nampa, IDAHO
Buffalo-Niagara Falls, New York Charlotte-Gastonia-Concord, North Carolina-South Carolina
New York-Northern New Jersey-Long Island,
New York-New Jersey-Pennsylvania

Raleigh-Cary, North Carolina

Rochester, New York Albuquerque, New Mexico
Syracuse, New York Las Vegas-Paradise, Nevada
Akron, Ohio Charleston-North Charleston-Summerville, South Carolina
Cleveland-Elyria-Mentor, Ohio Nashville-Davidson-Murfreesboro-Franklin, Tennessee
Dayton, Ohio Austin-Round Rock, Texas
Toledo, Ohio Dallas-Fort Worth-Arlington, Texas
Youngstown-Warren-Boardman, Ohio-Pennsylvania Houston-Sugar Land-Baytown, Texas
Pittsburgh, Pennsylvania McAllen-Edinburg-Mission, Texas
Scranton-Wilkes-Barre, Pennsylvania San Antonio, Texas
Providence-New Bedford-Fall River, Rhode Island-Massachusetts Ogden-Clearfield, Utah
Milwaukee-Waukesha-West Allis, Wisconsin Provo-Orem, Utah

228 Economic Development Quarterly 26(3)

could be directed to other beneficial investments. Alternative
economic development strategies may include localizing
economies, restoring local manufacturing and production
capacity, and investing in public amenities and quality of
life. These strategies could focus on preparing local econo-
mies for the future by recognizing global imperatives such as
responding to peak oil, addressing climate change, and the
need to protect and enhance the natural environment.

Methodology

Notes

MSA Description

The general concept of a metropolitan statistical area is that
of a core area containing a substantial population nucleus,
together with adjacent communities having a high degree of
economic and social integration with that core. Each metro-
politan statistical area must have at least one urbanized area
of 50,000 or more inhabitants. MSAs have fixed geographic
boundaries based on counties or their equivalent. For more
information, see http://www.census.gov/population/www/
metroareas/aboutmetro.html.

Per Capita Personal Income Data Series
Per capita personal income data are obtained from the BEA.9
According to BEA, “per capita personal income is calcu-
lated as the personal income of the residents of a given area
divided by the resident population of that area.”10 These
population data are from the Census Bureau’s annual mid-
year population estimates. According to the BEA,

Personal income is the income received by persons
from all sources—that is, from participation in produc-
tion (such as compensation of employees, income from
self-employment, and rental income) and from current
transfer receipts from both government (such as Social
Security and Medicare benefits) and business (such as
pension benefits).11

All income is in nominal dollars, as reported by the BEA.

Unemployment Data Series
All unemployment data are from the BLS. For unemploy-
ment data, the BLS uses a different local area definition for
some areas than the Census. Because of the lack of official
county designations in some New England states, the BLS
classifies 21 metro areas as New England City and Town
Areas, or NECTAs. Fifteen of these NECTAs are reported as
MSAs by the Census. Unemployment data for the 7
NECTAs included among the largest 100 MSAs in this study
represent a slightly different geographic area than the popu-
lation data for the equivalent MSAs. However, because these

data are for the same metro areas and this study focuses on
rates of change of each area’s population (rather than abso-
lute values), this geographic difference is unlikely to have a
significant effect on the results.

Poverty Data Series
Poverty data were obtained from the 2009 American
Community Survey 1-Year Estimates for all MSAs.12

Statistical Significance
The statistical analysis used in this study is based on the ques-
tion of whether or not there is a linear relationship between
two variables. For example, the question of whether the
unemployment rate is related to growth rate is initially exam-
ined by graphical representation of the data and fitting of a
trend line. The correlation coefficient provides an indication
of how well the data match the trend line. The probability that
the trend line represents a true correlation is based on the t test
for significance. A two-tailed, nondirectional t test is applied
to all correlations. A 95% level of confidence in an outcome
is the standard research benchmark and is used here (p

ho
≤

.05). Some of the correlations in this study have a confidence
level of 99% or higher, resulting in particularly strong correla-
tions. Any level of confidence below 95% officially lacks
statistical significance. A correlation may exist between two
variables below the 95% confidence level, but statistically it
is not significant. A finding that the correlation coefficient is
very low (close to zero) between two variables is an indica-
tion that the two variables are independent of each other.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research,
authorship, and/or publication of this article.

Notes

1. According to a September 20, 2010, announcement by the
Business Cycle Dating Committee of the National Bureau of
Economic Research, http://www.nber.org/cycles/sept2010.
html.

2. Average annual rate of growth is based on the rate (expressed
as a percentage) that would yield the observed population
change for the period.

3. Source: U.S. Census Bureau, Population Division, Table 1.
Annual Estimates of the Population of Metropolitan and
Micropolitan Statistical Areas: April 1, 2000 to July 1, 2009
(CBSA-EST2009-01), release date: March 2010; and for the
1990 and 2000 Census from Table 1a. Population in Metropolitan
and Micropolitan Statistical Areas in Alphabetical Order and

Fodor 229

Numerical and Percent Change for the United States and Puerto
Rico: 1990 and 2000, Internet release date: December 30, 2003.

4. Separate research by the author finds that change in housing
units from 2000 to 2009 has a close linear relationship with
change in population at the state level (r = .94).

5. Gross domestic product was not evaluated in this study because
time series data available from federal sources for metropolitan
areas were not available for the study periods selected.

6. This is based on the probability of a nondirectional hypothesis
using a two-tailed t test. See the Methodology Notes section for
more information.

7. As defined by the Office of Management and Budget, the
weighted average poverty threshold for a family of four in
2009 was $21,954.

8. Movement of retirees to the sunny south is one example of a
geographic difference.

9. Source: 2000-2008 income data from BEA Regional Economic
Accounts, Local Area Personal Income, Table CA1-3, and 2009
preliminary data released August 9, 2010, BEA Personal Income
for Metropolitan Areas, Table 1, Personal Income and Per Capita
Personal Income by Metropolitan Area, 2007-2009 (see: http://
www.bea.gov/newsreleases/regional/mpi/mpi_newsrelease.htm).

10. See page I-6 of Local Area Methodology, http://www.bea.gov/
regional/pdf/lapi2007/lapi2007 .

11. See page 8 of Customer Guide, http://www.bea.gov/agency/
pdf/BEA_Customer_Guide .

12. American Community Survey, 2009, Table B17001. Poverty
Status in Past 12 Months by Sex by Age.

References

Bartik, T. J. (1993). Who benefits from local job growth: Migrants
or the original residents? Regional Studies, 27, 297-311.

Basolo, V., & Huang, C. (2001). Cities and economic development:
Does the city limits story still apply? Economic Development
Quarterly, 15, 327-339.

Bergmann, B. (2010). Is prosperity possible without growth? Chal-
lenge New York, 53, 49-56.

Bodley, J. H. (1999). Socioeconomic growth, culture scale, and
household well-being: A test of the power-elite hypothesis.
Current Anthropology, 40, 595-620.

Bok, D. (2010). The politics of happiness: What government can
learn from the new research on well-being. Princeton, NJ:
Princeton University Press.

Calavita, N., & Caves, R. (1994). Planners’ attitudes toward growth:
A comparative case study. Journal of the American Planning
Association, 60, 483-500.

Carr, J. B., Bae, S.-S., & Lu, W. (2006). City-county government
and promises of economic development: A tale of two cities.
State and Local Government Review, 38, 131-141.

Delken, E. (2008). Happiness in shrinking cities in Germany. Journal
of Happiness Studies, 9, 213-218.

Dewar, M. E. (1998). Why State and Local Economic Development
Programs Cause So Little Economic Development. Economic
Development Quarterly, 12, 1, 68-87.

Duncan, O. D. (1949). An examination of the problem of optimum
city size (Unpublished doctoral dissertation). University of
Chicago, Chicago, IL.

El Nasser, H. (2010, November 8). Nevada’s growth streak doused:
Population is forecast to drop in downturn’s wake. USA Today,
p. 1A.

El Nasser, H. (2011). Hard times don’t stop Vegas influx: Area
retained and gained people during recession. USA Today,
p. 2A.

Fodor, E. V. (2001). Meet the urban growth machine. In Better, not
bigger: How to take control of urban growth and improve your
community (2nd ed., pp 29-37). Gabriola Island, British Colum-
bia, Canada: New Society.

Gottlieb, P. D. (2002). Growth without growth: An alternative eco-
nomic development goal for metropolitan areas (Discussion
Paper prepared for The Brookings Institution, Center on Urban
and Metropolitan Policy). Washington, DC: The Brookings
Institution.

Greenwood, D. T., & Holt, R. P. F. (2010). Local economic devel-
opment in the 21st century: Quality of life and sustainability.
Armonk, NY: M. E. Sharp.

Gundersen, C., & Ziliak, J. P. (2004). Poverty and macroeconomic
performance across space, race, and family structure. Demog-
raphy, 41, 61-86.

Hammer, R. B., & Green, G. P. (1996). Local growth promotion:
policy adoption versus effort. Economic Development Quarterly,
10, 331-341.

Hollander, J. (2011). Can a city successfully shrink? Evidence from
survey data on neighborhood quality. Urban Affairs Review, 47,
129-141.

Huszar, P. C., & Seckler, D. W. (1975). The perverse dynamics of
urban growth. Growth and Change, 6, 3-7.

Jackson, T. (2009). Prosperity without growth: Economics for a
finite planet. London, England: Earthscan.

Krebs, T. B. (2005). Urban interests and campaign contributions:
Evidence from Los Angeles. Journal of Urban Affairs, 27,
165-176.

Logan, J. R., & Molotch, H. L. (1987). Urban fortunes: The politi-
cal economy of place. Berkeley: University of California Press.

Molotch, H. (1976). The city as a growth machine: toward a politi-
cal economy of place. American Journal of Sociology, 82,
309-332.

Molotch, H. (1993). The political economy of growth machines.
Journal of Urban Affairs, 15, 29-53.

Mumford, L. (1938). The culture of cities. New York, NY: Harcourt
Brace.

Nguyen, M. T. (2007). Local growth control at the ballot box:
Real effects or symbolic politics? Journal of Urban Affairs,
29, 129-147.

Partridge, M., Rickman, D., & Li, H. (2009). Who wins from local
economic development? Economic Development Quarterly, 23,
13-27.

Vojnovic, I. (2003). Governance in Houston: Growth theories and
urban pressures. Journal of Urban Affairs, 25, 589-624.

230 Economic Development Quarterly 26(3)

Warner, D. M. (2006). “Post-growthism”: From smart growth to
sustainable development. Environmental Practice, 8, 169-179.

Welch, W. M. (2011, March 9). Have dark days dulled shine of
the Golden State? High unemployment, foreclosures and a
staggering budget crisis detour domestic migration from Cali-
fornia. USA Today, p. A4.

Zheng, L., & Warner, M. (2010). Business Incentive Use Among
U.S. Local Governments: A Story of Accountability and Policy
Learning. Economic Development Quarterly, 24, 4, 325-336.

Zovanyi, G. (1998). Growth management for a sustainable future:
Ecological sustainability as the new growth management focus
for the 21st century. Westport, CT: Praeger.

Bio

Eben Fodor is the principal of the consulting firm Fodor &
Associates. He conducts research on urban growth and public pol-
icy topics and specializes in the economic and fiscal impacts of
land development.

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