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List of Tables and Figures .................................................................................. vii
Foreword ............................................................................................................... ix
Acknowledgments ................................................................................................ xi
Executive Summary ........................................................................................... xiii
Introduction ........................................................................................................... 1
I. What Do We Know About Economic Growth and Poverty in Urban
Areas?..................................................................................................................... 3
A. Urbanization ................................................................................................... 3
Regional Urbanization Trends ............................................................................ 4
Consequences of Rapid Urbanization ............................................................. 4
The Importance of Cities ................................................................................. 4
Definition of Urban Areas .................................................................................. 5
Causes of Urban Growth ..................................................................................... 5
Natural Urban Population Growth ................................................................. 5
Rural-to-Urban Migration .............................................................................. 5
Reclassification of Areas................................................................................. 6
B. Urbanization and Economic Growth .............................................................. 6
Drivers of Economic Growth .............................................................................. 7
Manufacturing and Services ............................................................................... 7
C. The Problem: The Urbanization of Poverty ................................................... 8
The Urban Poor and Slums ................................................................................. 8
Urban Poverty ..................................................................................................... 8
Housing ......................................................................................................... 10
Electricity, Water, and Sanitation ................................................................. 11
Public Transportation ................................................................................... 13
Environmental Degradation and Sustainability ........................................... 14
Health ............................................................................................................ 16
Education ...................................................................................................... 18
Financial Services ......................................................................................... 19
Crime............................................................................................................. 20   iii

II. Subnational Policies that Drive Economic Growth and Reduce Poverty in
Developing Countries.......................................................................................... 22
A. Decentralization ........................................................................................... 22
B. Economic Policies ........................................................................................ 23
Investment Promotion ....................................................................................... 23
Participatory Budgeting .................................................................................... 25
Reducing the Informal Sector ........................................................................... 25
Municipal Solid Waste Management Systems ................................................. 25
C. Infrastructure Policies .................................................................................. 26
Land Tenure and Property Rights ..................................................................... 26
Housing ............................................................................................................. 28
Housing Finance ........................................................................................... 28
Participatory Slum Upgrading Programs .................................................... 29
Property Taxes .............................................................................................. 30
Water and Sanitation ......................................................................................... 31
Condominial Water Supply ........................................................................... 31
Communal Sanitation Provision ................................................................... 31
Public-Private Partnerships in Urban Infrastructure Provision .................. 32
Electricity and Non-governmental Organizations ............................................ 33
Public Transportation ........................................................................................ 33
Traffic Calming ............................................................................................. 35
Bicycle Infrastructure ................................................................................... 35
Bus Rapid Transit ......................................................................................... 36
Additional Considerations ............................................................................ 37
D. Human Capital Policies ................................................................................ 37
Public-Private Partnerships ............................................................................... 39
PPPs and Education ..................................................................................... 39
PPPs and Health ........................................................................................... 39
Targeted School Fee Reduction .................................................................... 39
Conditional Cash Transfer Programs .......................................................... 40
Technical and Vocational Education and Training ...................................... 41
Provision of Iron Supplements and Deworming Drugs in Schools .............. 41
Community-Based Health Insurance ............................................................ 42
Microfinance and Health Education ............................................................. 43   iv

E. Financial Services ......................................................................................... 43
Collaboration and Usage of Pre-Existing Financial Networks ......................... 44
Life Insurance ................................................................................................... 45
Microcredit ........................................................................................................ 45
F. Corruption ..................................................................................................... 46
Types of Corruption .......................................................................................... 46
Corruption in Public Auctions ...................................................................... 46
Corruption in Police Forces ......................................................................... 47
G. Summary ...................................................................................................... 48
III. Policy Performance Indicators at the Subnational Level ......................... 50
A. Fiscal Decentralization Databases ............................................................... 50
B. Global City Indicator Facility ...................................................................... 51
Indicators .......................................................................................................... 51
Methodology ..................................................................................................... 53
Merits of GCIF .................................................................................................. 54
Drawbacks ........................................................................................................ 54
City Services ..................................................................................................... 56
Health ............................................................................................................ 56
Education ...................................................................................................... 58
Civic Engagement ......................................................................................... 59
Environment .................................................................................................. 60
Solid Waste.................................................................................................... 60
Water ............................................................................................................. 61
Wastewater .................................................................................................... 61
Electricity ...................................................................................................... 62
Finance ......................................................................................................... 63
Urban Planning ............................................................................................ 64
Transportation .............................................................................................. 64
Quality of Life .................................................................................................. 67
Economy ........................................................................................................ 67
Technology and Innovation ........................................................................... 67
Shelter ........................................................................................................... 68
v

C. Green City Index .......................................................................................... 69
Methodology ..................................................................................................... 69
Merits ................................................................................................................ 70
Drawbacks ........................................................................................................ 70
GCI Indicators ................................................................................................... 71
Energy and CO
2
............................................................................................ 71
Land Use and Buildings ................................................................................ 72
Transportation .............................................................................................. 72
Waste ............................................................................................................. 73
Water ............................................................................................................. 73
Sanitation ...................................................................................................... 74
Air Quality .................................................................................................... 74
Environmental Governance .......................................................................... 75
D. Doing Business Project ................................................................................ 75
Indicators .......................................................................................................... 76
Merits ................................................................................................................ 77
Drawbacks ........................................................................................................ 77
E. Additional Indicators .................................................................................... 78
F. Comparison of City-level Indicators, MCC Indicators, and Section II
Subnational Policies .......................................................................................... 78
Conclusions .......................................................................................................... 88
Appendix A: Population Trends and Urban Growth ...................................... 92
Appendix B: Definition of Urban Area ............................................................. 94
Appendix C: Emerging Health Issues in Urban Areas.................................... 95
Appendix D: Decentralization Databases and Comparison to MCC
Indicators and Section II Policies ...................................................................... 96
Appendix E: GCIF Indicators ........................................................................... 98
Appendix F: GCIF City Coverage in MCC Eligible Countries .................... 107
Appendix G: Doing Business Coverage and Methodology ........................... 109
Appendix H: Additional Databases and Comparison with MCC Indicators and Section II Policies ....................................................................................... 111
Works Cited ....................................................................................................... 121   vi

Figure 1. World Urban Population and Economic Performance, 1970-2010 ......... 6
Table 1. Urban Poverty: Challenges and Opportunities ......................................... 9
Table 2. GCIF City Service and Quality of Life Categories ................................. 52
Figure 2. Summary of GCIF Categories, Themes, and Indicators ........................ 53
Table 3. Comparison of GCIF with MCC Indicators and Section II Policies ...... 79
Table 4. Comparison of Green Cities Index with MCC Indicators and Section II
Policies .................................................................................................................. 83
Table 5. Comparison of Doing Business with MCC Indicators and Section II
Policies .................................................................................................................. 87
Table 6. Evaluation of MCC Indicator Preferences with City-Level Databases .. 89
Figure A1. Population Estimates: Total, Rural, and Urban, 2000-2030 ............... 92
Table A1. Urban Population Percentages by Geographic Region, 1950-2050 ..... 93
Table A2. Average Annual Rate of Change of the Urban Population by
Geographic Region, 1950-2050 ............................................................................ 93
Table C1. Emerging Urban Health Issues: Notional Variation with Urban
Development ......................................................................................................... 95
Table C2. Urban Health Risks .............................................................................. 95
Table D1. Global Observatory on Local Democracy and Decentralization
Database Comparison ........................................................................................... 96
Table D2. World Bank’s Decentralization and Subnational Regional Economics
Database Comparison ........................................................................................... 97
Table E1. GCIF Profile Indicators ........................................................................ 98
Table E2. GCIF Performance Indicators .............................................................. 99
Table E3. Future GCIF Indicators ...................................................................... 104
Table F1. GCIF City Coverage in MCC Eligible Countries ............................... 107
Table G1. Doing Business Indicators and Geographic Coverage ....................... 109
Table H1. UN-HABITAT Urban Development Index ....................................... 112
Table H2. UN-HABITAT Urban Governance Index ......................................... 114
Table H3. Local Governance Barometer ............................................................ 115
Table H4. Local Integrity Initiative .................................................................... 116
Figure H1. Multidimensional Poverty Index Indicators ..................................... 119   vii

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The La Follette School of Public Affairs at the University of Wisconsin–Madison offers a two-year graduate program leading to a Master of Public Affairs or a
Master of International Public Affairs degree. In both programs, students develop analytic tools with which to assess policy responses to issues, evaluate implications of policies for efficiency and equity, and interpret and present data relevant to policy considerations.
Students in the Master of International Public Affairs program produced this report for the Millennium Challenge Corporation. The students are enrolled in the
Workshop in International Public Affairs, the capstone course in their graduate program. The workshop challenges the students to improve their analytical skills by applying them to an issue with a substantial international component and to contribute useful knowledge and recommendations to their client. It provides them with practical experience applying the tools of analysis acquired during three semesters of prior coursework to actual problems clients face in the public, non-governmental, and private sectors. Students work in teams to produce carefully crafted policy reports that meet high professional standards. The reports are research-based, analytical, evaluative, and (where relevant) prescriptive responses for real-world clients. This culminating experience is the ideal equivalent of the thesis for the La Follette School degrees in public affairs. While the acquisition of a set of analytical skills is important, it is no substitute for learning by doing.
The opinions and judgments presented in the report do not represent the views, official or unofficial, of the La Follette School or of the client for which the report was prepared.
Melanie Frances Manion
Professor of Public Affairs and Political Science
May 2012 ix

x

We would like to thank Andria Hayes-Birchler of the Millennium Challenge
Corporation for her helpful insight and direction. We would also like to acknowledge Professor Melanie Manion, our faculty advisor, for her encouragement and guidance throughout the semester. Finally, we would like to recognize Karen Faster, Publications Director at the La Follette School of Public
Affairs, for her assistance in editing the report. We are exclusively responsible for the content and recommendations stated in this report. xi

xii

Increasing levels of urbanization present unique opportunities and challenges for economic growth and poverty reduction for cities located in low-income countries
(LICs) and lower middle-income countries (LMICs). In this report, we assess: 1) whether the Millennium Challenge Corporation (MCC) should provide aid to cities; 2) which subnational policies can successfully reduce poverty and increase economic growth; and 3) whether city-level indicators are available to appropriately measure a city’s policy performance. We find that available citylevel data does not adequately satisfy all MCC indicator requirements, but ongoing collection efforts will likely result in a comprehensive set of useful indicators within the next five years. With more complete data for cities in LICs and LMICs, MCC can potentially use these indicators to distribute aid to cities.
Given the potential of city-level policies to reach large numbers of urban residents and the influence of these policies on national economic and social outcomes, we recommend MCC consider funding initiatives at a municipal level.
In Section I, we review the literature on economic growth and poverty reduction in urban areas of LICs and LMICs. We discuss urbanization, economic growth, and challenges specific to the urban poor. In Section II, we provide an overview of successful subnational policies that drive economic growth and poverty reduction in LICs and LMICs. In Section III, we identify and analyze databases and city-level indicators that measure cities’ performance across a wide spectrum of issues and policies that can drive economic growth and reduce poverty in LICs and LMICs. We also compare city-level indicators with MCC indicators and summarize their relationship to subnational policies reviewed in Section II. We conclude with our recommendations.
Subnational funding would allow MCC to award aid directly to urban areas, where poverty is increasing at a faster rate than in rural areas. Cities also provide excellent opportunities to stimulate economic growth due to urban circumstances, such as agglomerations and knowledge spillovers. Depending upon the policy and context, outcomes related to economic growth and poverty reduction require different levels of fiscal and political decentralization within countries.
The nearly 200 indicators we analyzed that are available to MCC are not yet sufficiently developed or adequately comprehensive in city coverage to allow for the cross-city comparisons needed for a city-level grant selection process. In the coming years, databases of city-level indicators will continue to improve in city coverage and number of indicators available. We estimate that MCC will be able to start conducting city-level selection processes within the next five years. With improved indicator data, MCC would be able to distribute aid to cities that have good policy performance. We recommend yearly monitoring of updates made to the databases we identify in this report. xiii

xiv

Created through the Millennium Challenge Act of 2003, the Millennium
Challenge Corporation (MCC) is an independent U.S. foreign aid agency focused on assisting low-income countries (LICs) and lower middle-income countries
(LMICs). In determining a country’s eligibility for funding, the MCC undertakes a rigorous evaluation process. Initially, eligible countries are required to meet the following two criteria: 1) fall within the World Bank’s gross national income
(GNI) per capita classifications for LICs (below $1,915 GNI per capita) or LMICs
(between $1,916 and $3,975 GNI per capita); and 2) meet eligibility requirements for assistance under part I of the Foreign Assistance Act of 1961. MCC then assesses eligible countries using publicly available, third-party indicators that measure a country’s policy performance related to economic growth, poverty reduction, and good governance. Evaluations of country performance are measured through 17 indicators under three categories: Ruling Justly, Investing in
People, and Encouraging Economic Freedom. Countries that meet the criteria for initial eligibility are evaluated using all of the MCC indicators, after which grants are given to countries that have shown a commitment to good governance, poverty reduction, and economic growth through their national policy decisions.
MCC grants are intended for poor, well-governed countries, but there are varying levels of poverty and government quality within those countries. For this reason,
MCC asked us to explore the feasibility and advisability of evaluating city-level policy performance. MCC wanted the assessment to address whether it would be possible for MCC to conduct comparative assessments of the quality of governance in cities in LICs and LMICs and whether an urban environment would be more or less inviting for investments aimed at promoting economic growth and reducing poverty. In short, should MCC grants be awarded to wellgoverned cities? If so, are there appropriate mechanisms to make these evaluations at the subnational level? Our analysis is divided into three parts, summarized below. We conclude the report with our recommendations.
In Section I, we conduct a literature review on the prospects and obstacles related to economic growth and poverty reduction in urban environments. We categorize the most important opportunities and challenges for economic growth and poverty reduction into the following issue areas: housing; electricity, water and sanitation; public transportation; environmental degradation and sustainability; health; education; financial services; and crime.
In Section II, we use our findings from Section I to investigate potential subnational and city-level policies that can contribute to economic growth and poverty reduction in urban areas. Where possible, we identify the subnational conditions ideal for successful project implementation at the municipal level. We discuss city-level and other subnational policies within the categories of economic growth, infrastructure, human capital, financial services, and corruption.
1

In Section III, we identify city-level indicators that successfully measure policies and important outcomes related to economic growth and poverty reduction. Three databases stand out: the Global City Indicators Facility (GCIF), the Green City
Index (GCI), and the Doing Business project. Once it is made publicly available,
GCIF will be the largest annually updated database of city-level indicators. To date, 73 cities in 20 MCC eligible countries provide data for GCIF’s expanding dataset. These cities are uniformly measured according to 33 core indicators that are divided into 20 categories. GCI provides publicly available qualitative and quantitative city-level indicators with a social and environmental focus. Cities included in the GCI are ranked intra-regionally by 20 indicators across eight categories, and 22 of the 54 cities examined are in MCC eligible countries. The
Doing Business project provides useful measures on the ease of doing business and compares cities globally and within countries. We also identify institutions that publicly provide individual indicators measuring specific categories at the urban and subnational level. In total, our analysis identifies close to 200 indicators and provides direction on evaluating policies and outcomes between countries and cities.
2

In this section, we review the literature on economic growth and poverty in urban areas of developing countries.
1,2 Sub-section A describes regional urbanization trends, defines the concept of urban area, and analyzes the predominant drivers of urban growth. Sub-section B examines the relationship between urbanization and economic growth. Sub-section C presents eight issue areas that represent challenges for the urban poor in developing countries. Sub-section C also discusses opportunities to address these eight challenges and improve the welfare of people living in urban poverty and briefly introduces general policy opportunities targeting urbanization issues.
Global urbanization levels have increased rapidly during the twentieth century.
Thirteen percent of the world’s population lived in urban areas in 1900, rising to
29 percent in 1950 and reaching 51 percent in 2010. Most projections show urbanization reaching 60 percent by 2030 (see Figure A1 and Table A1, Appendix
A). Urbanization rates in the developed world have largely stabilized, and over 90 percent of the increase in the world’s urban population will occur in developing countries (see Table A2, Appendix A). The increasing urbanization trend is also accompanied by a slowing of rural population growth rates in developing countries (UNEP 2002).
1 Throughout the first section, we use the phrases “developed countries” and “developing countries” for purposes of continuity. Section I offers a literature review of economic growth and poverty reduction in urban areas from a variety of academic fields, and a diverse vocabulary is used to describe what is meant by “developing countries.” Examples include: “The Global South,”
“poor countries,” “low-income countries,” “low-middle-income countries,” “middle-income countries,” “highly-indebted countries,” “third-world countries,” “developing countries,” and
“the developing world.” In sections II and III, we use terminology that specifically describes the macroeconomic conditions of MCC program-eligible countries: “low-income countries” and
“low-middle-income countries.”
2 With MCC’s focus on economic growth and poverty reduction, in the following section we discuss positive outcomes related to economic growth, poverty reduction, or both. In our evaluations, we do not identify when specific types of economic growth lead to increased poverty or when examples of poverty reduction also stagnate economic growth. The literature demonstrates that economic growth is a necessary, but insufficient condition for poverty reduction, and suggests additional government-based policies related to income distribution that best address relative and absolute poverty (Kakwani et al. 2004; WRI 2005; UNDP 2006; Foster
2012). In Section III, we briefly discuss the Gini coefficient indicator as part of the Global Cities
Indicator Facility, and we explain its relevance to measuring inequalities that may arise from some policies that promote economic growth.
3

Regional Urbanization Trends
The most urbanized area in the world is the Latin American and Caribbean region.
This region is characterized by a high number of megacities; large urban agglomerations of 10 million people or more (Fay 2005, 1; Cohen 2004, 29;
Henderson 2002, 89). Urbanization in Africa is characterized by uneven population distribution, concentration of investments in larger cities, and extensive slum areas. The East Asian and Pacific region and the sub-Saharan
African region both have high rural-to-urban population ratios and the highest rates of urbanization during the last decade according to World Development
Indicators (World Bank 2008). In Asia, national policies and investments played an important role in urban growth and significantly contributed to the area’s economic growth. National governments often determine which cities and regions will benefit the most from public resources and then promote their development above others. In other cases, local authorities and other actors, including the private sector, foster urban growth (UN-HABITAT 2008, 15).
Consequences of Rapid Urbanization
While urbanization can result in social improvements and a better quality of life for urban residents, the urbanization process in many developing countries is accompanied by many negative externalities such as increased inequality, health risks, and marginalization of the urban poor. Rapid urbanization and inadequate urban planning also contribute to poor air and water quality, excess mortality associated with the urban heat island effect, increased motor vehicle and pedestrian injuries, and increased violent crime (Campbell-Lendrum and Corvalán
2007, 113; McMichael 2000, 1117-1116). Without an appropriate governmental response to rapid urbanization, the urban poor often find themselves living in overcrowded and polluted environments without basic services (de Snyder et al.
2011, 1184).
The Importance of Cities
The positive externalities of urbanization include increased efficiency and productivity from agglomeration, economies of scale, innovation, and specialization (Zhang 2011, 4). People are attracted to cities because of the availability of diverse opportunities, access to goods and services, and the potential for a higher quality of life (St. Pierre Schneider et al. 2009, 281). Cities are traditionally the drivers of innovation, employment, and country-level economic growth (Spence, Annez, and Buckley 2009, x; Henderson 2002).
Historically, no country has ever “achieved sustained economic growth or rapid social development without urbanizing” (UN-HABITAT 2010b, x). Urbanization has the potential to stimulate economic growth and attract more residents to cities.
Political and economic power may shift from the national level to the local level as individual cities can more easily “break away from the fate of their national economies” due to factors including globalization and the corresponding increased economic influence of urban areas (Cohen 2004, 37).
4

Definition of Urban Areas
No consensus exists in the literature about what constitutes an “urban area,” and some definitions are contradictory (Cohen 2006, 65). Classifications of urban areas differ by country, region, and international organization (see Appendix B).
Taking these variances into consideration, we define an “urban area” as:
1.
A locally delineated agglomeration of people with both formal and informal boundaries that has population densities consistent with national standards, and
2.
an agglomeration that is legally administered by a local government, governing body, or council, and
3.
an agglomeration of at least 2,500 people that satisfies conditions 1 and 2.
Causes of Urban Growth
Current literature attributes the increases in urban growth to three processes: natural urban population growth, rural-to-urban migration, and reclassification of rural areas as urban areas (Sheng 2002, 3).
Natural Urban Population Growth
Natural urban population growth occurs when birth rates surpass death rates in a given period of time (UN-HABITAT 2006a).
Rural-to-Urban Migration
Push and pull factors drive urbanization. Push factors are unfavorable rural conditions that drive rural residents to urban areas. Pull factors are positive urban conditions that attract people to migrate to urban areas (University of Michigan
2006; Oglethorpe et al. 2007). Unemployment, lack of educational facilities, limited infrastructure and health services, land scarcity, and low wages are the most common push factors contributing to urban migration. Additionally, unpredictable environmental conditions increase instability for rural residents.
Climate change has resulted in diminished agricultural capacity and increased frequency of floods and droughts. Political instability and conflict have also caused many rural residents to relocate to urban centers. On the other hand, pull factors that attract people to cities include educational and employment opportunities, better health services, greater variety of cultural offerings, and the provision of public and financial services (University of Michigan 2006).
Rural-to-urban migration is generally considered beneficial for both rural migrants and their extended family members who remain in rural areas. The potential benefits of rural-to-urban migration—connectivity to the “outside world,” remittances, and status—are believed to exceed relocation costs— disconnected families, travel expenses, and a general sense of displacement.
Information asymmetries, however, can undermine migration benefits, as migrants’ decisions may be based on inadequate or inaccurate information.
During periods of economic recession, high numbers of rural residents may be forced to move in search of jobs and better living conditions, but few cities and
5

towns have sufficient housing, infrastructure, employment opportunities, and services to absorb the inflow of migrants. In the absence of sufficient infrastructure, migrants end up living in crowded conditions and working in the informal labor market. The result is an increasing urban population with deteriorating living conditions (Sheng 2002).
Reclassification of Areas
As cities expand and spill over municipal boundaries into surrounding rural areas, nearby rural settlements are converted into urban settlements. This transition makes urbanization both an administrative process and a demographic process
(Sheng 2002). For example, in China during the last decade, urban growth has been accompanied by the state-led replacement of rural space by urban space through the creation of provincial level municipalities, the expansion of existing municipalities, and the reclassification of counties to municipalities (McGee
2008, 161).
The literature is mixed regarding the relationship between economic growth and urbanization. Many of the developing countries that urbanized most rapidly in the last two decades also demonstrated more rapid economic growth (Zhang 2011, 1).
We see this trend for developing countries in the East Asian and Pacific region which experienced urbanization and increased levels of economic growth.
Moreover, at a global level, there is a positive association between larger urban population and higher gross domestic product (GDP) per capita. Figure 1 shows this relationship based on the World Development Indicators.
Figure 1.
World Urban Population and Economic Performance, 1970-2010
6,500
6,000
5,500
5,000
4,500
4,000
2010
3,500
3,000
1,000
1970
1,500 2,000 2,500 3,000 3,500
Urban population (millions)
Source: World Bank 2008. 2008 World Development Indicators .
4,000
6

Although economic growth and urbanization are positively associated, urbanization can occur in the absence of economic growth. Many countries in sub-Saharan Africa experienced sizable increases in urbanization over the last 20 years, yet they did not benefit from economic development to the same extent as other urbanizing developing countries (Briggs and Yeboah 2001, 18-26). Whether urbanization exacerbated the poverty rates in these sub-Saharan countries is unknown (Spence et al. 2009, 8). However, it is possible that urbanization and economic growth policies can also result in the unintended consequence of higher inequality (Dudwick et al. 2011, 90).
Drivers of Economic Growth
Economies of scale and agglomeration in urban areas make economic development possible through industrialization. Urban economic growth can facilitate development through remittances, new markets, and increased human capital. Cities play an important role as providers of employment, services, cultural offerings, educational opportunities, and technological development
(WHO and UN-HABITAT 2010, iv). While evidence suggests that countries urbanize as they grow, more gradual urban growth permits higher standards of living during the transition phase. By contrast, countries with unrestrained growth experience lower standards of living.
Manufacturing and Services
Urbanization per se does not drive economic growth; rather the development of an urban manufacturing sector promotes higher levels of productivity, which in turn can stimulate economic growth (Henderson 2003, 47-71). Productivity gains are derived from technological innovations, investments in human capital, and knowledge spillovers. Knowledge spillovers are usually related to spatial proximity and the geographic distribution of firms. The shift to urban areas has created the opportunity to exploit scale economies of local agglomeration
(Henderson 2002, 90). High urban densities reduce transaction costs and shorten distances, facilitating the acquisition and diffusion of knowledge. Industry
“clusters” concentrate firms, workers, and skills in a given area. Knowledge spillovers in the form of information exchange among firms create positive externalities that generate growth. Greater urban productivity raises family incomes and, consequently, the demand for products and services (International
Housing Coalition 2009, 3).
In some countries, much of the economic growth has been attributed to the growth of industries and services. The demand for services has been growing in developing countries as a percentage of total production. As cities develop, urban residents demand more health, education, water, electricity, and other services to improve their quality of life. At the same time, the greater the availability of services in urban areas, the higher the likelihood rural residents will migrate to urban areas. This process reinforces urbanization and further increases the demand for services.
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Even though manufacturing and services have the potential to promote economic growth, negative spillovers from urbanization, including congestion, may discourage firms from locating in larger cities. Moreover, the higher concentration and higher demand for services, in the absence of adequate infrastructure and service provision, may also lead to deteriorating living conditions.
Urbanization can serve as a catalyst for economic growth and long-term poverty reduction at the national level while also stimulating increased rates of localized urban poverty in the short-term (Banks 2011, 1). One of the detrimental effects of rapid urbanization is that urban poverty has grown faster than rural poverty
(Léautier 2006, ix). The incidence of absolute poverty, however, remains higher in rural areas (UNFPA 2007, 16). Therefore, it is important to stimulate both urban and rural poverty reduction and the provisions of adequate housing; infrastructure; educational systems; and health, safety, and other basic services
(Zhang 2011, iii).
The Urban Poor and Slums
Urban growth and expansion in developing countries is frequently characterized by informality, illegality, and unplanned settlements referred to as slums
(Moreno, Oyeyinka, and Mboup 2010, x). Inhabitants of slum settlements are disadvantaged by the poor social services, health outcomes, and housing conditions in their communities. They are also negatively affected by the lack of basic amenities, security, and stable incomes and livelihoods (Zulu et al. 2011,
186). These inequities can lead to rising violence, environmental degradation, and underemployment (Moreno and Warah 2006, v). Martine and Marshall (2007, 16) estimate that one in three city dwellers worldwide, or approximately one billion people live in slums. The burden of slums is particularly prevalent in Asia which has 60 percent of the world’s slum dwellers (DFID 2010, 2).
Estimates of slum population growth vary. The United Kingdom’s Department for
International Development estimates that there will be two billion people living in slums around the world by 2030 (2010, 2). Moreno and colleagues (2010, xii) estimate, however, that the total number of slum dwellers will decrease from the current estimate of one billion to 889 million by 2020. Over the past ten years, the absolute number of slum dwellers in the developing world has increased even though the proportion of the urban population living in slums decreased during the same period (Moreno, Oyeyinka, and Mboup 2010, xii). Therefore, while establishing a consensus on the absolute number of slum dwellers in the coming decades is difficult, it is clear that if the population growth in urban slums outpaces slum reduction efforts, the total number of slum dwellers will increase.
Urban Poverty
Urban poverty is associated with limited access to employment and income, inadequate housing and services, limited access to health and educational
8

opportunities, unhealthy environments, and limited social protection mechanisms
(Léautier 2006, ix). The urban poor are more integrated into the market economy than the rural poor. Therefore, urban poverty is more responsive to economic growth and more vulnerable to economic fluctuations. For the urban poor, the transmission of macroeconomic shocks usually occurs through the labor market, and job loss is an important consequence (Fay 2005, 3). In addition, inept or corrupt governance at the city level impairs the ability of poor residents to benefit from global opportunities and contribute to city- and country-level economic growth (Léautier 2006, ix). While local governments are charged with providing health and human services to all residents, this does not occur in most developing countries. Studies of the urban poor in sub-Saharan Africa show higher morbidity rates, lower access to health services, higher rates of mortality, and a higher incidence of risky sexual practices when compared to their rural poor counterparts
(Zulu et al. 2011, 186). These challenges limit the ability of the urban poor to escape poverty.
We categorize the most important challenges and opportunities associated with urban poverty in developing countries into the following eight issue areas: housing; electricity, water, and sanitation; public transportation; environmental degradation and sustainability; health; education; financial services; and crime.
Table 1 summarizes these challenges and opportunities.
Table 1.
Urban Poverty: Challenges and Opportunities
Issue Areas Challenges
Housing
Insecure property tenure; incremental building; spatial inequality; inefficient land and housing markets; poor urban planning
Opportunities
Settlement upgrading projects; increase land tenure security; greater provision of government services; economic gains in the property markets
Electricity,
Water, and
Sanitation
Public
Transportation
Capital-intensive; legal and physical barriers to expand services; low demand and ability to pay; under-provision of services
Large up-front costs; lack of political will; lack of public support; opportunities for corruption
Economies of scale in expansion and operation; higher willingness to pay compared to rural areas
Decreased travel time; greater equity of mobility; sustainable environmental improvements
9

Issue Areas
Environmental
Degradation and
Sustainability
Health
Poor municipal waste management; e-waste disposal; contaminated surface and groundwater supply; emissions; flooding
Challenges Opportunities
NGOs role in raising public awareness of pollution; broadbased benefits to investing in better waste management and climate change mitigation strategies
Communicable diseases; noncommunicable diseases; traffic accidents/injuries; health inequity
Multisectoral interventions; public health campaigns
Education
Financial
Services
Crime
Limited funding; privatization of primary education; lack of attention to quality of classroom learning
Early childhood education has highest rates of return among vulnerable populations; increase economic growth with higher educated population
Barriers to formal financial services: rigorous documentation requirements, high rates of financial illiteracy, lack of trust in financial institutions
Income inequality; weak institutions; corruption; large youth population; proliferation of gangs
Source: Authors.
Provide combination of private and government financial services; increase savings ability and financial literacy
Reduce corruption; support effective law enforcement
Housing
The primary urban housing challenges discussed in the literature are insecure property tenure, incremental housing construction, and spatial inequality.
Insecure Property Tenure
While property ownership problems can arise in both rural and urban areas, urbanization provides a distinct set of challenges for poor residents who often lack property rights or protections. Slums and unauthorized housing develop outside of planned urban zoning areas, and residents are, thus, considered illegal occupants.
Urban poor who are legally entitled to their property may lack official documentation for their homes and are vulnerable to eviction by landlords or corrupt government officials. The few residents who have official documentation remain highly vulnerable to the preferential treatment of wealthier, established interests through what are often inconsistent and corrupt judicial systems (UNDP
2008).
The lack of stability resulting from poorly defined property rights has many negative consequences. Evictions may come from landlords without reason,
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justification, or prior notification (Struyk and Giddings 2009). The government can conduct unexpected evictions through eminent domain laws whereby they seize property without the owners’ permission. Eminent domain laws are often poorly developed or advertised in developing countries. If the government chooses to confiscate land, residents receive no prior notification and lack an appeals process. These unpredictable conditions make it difficult for the urban poor to hold down jobs or to complete school. Some evidence suggests that many residents curtail their work hours and keep children home from school to safeguard ownership of their home through constant occupancy (Field 2005, 5).
Decreases in productivity and unanticipated costs resulting from forced evictions tend to increase fiscal instability among the urban poor.
Spatial Inequality
Urban spatial inequality in developing countries is more than a reflection of income inequalities among individual households. Multiple factors come into play, including inefficient land and housing markets, ineffective financial mechanisms, and poor urban planning. Socioeconomic disparities and the larger processes of urban development, governance, and institutionalized exclusion of specific groups also contribute to the spatial inequalities. For example, slum dwellers may have to endure longer commuting times and higher transportation costs if the slum is isolated and disconnected from the urban network. Some argue that the physical and social distance between poor and rich neighborhoods creates a spatial poverty trap. A spatial poverty trap is comprised of six challenges: 1) severe job restrictions; 2) high rates of gender disparities; 3) deteriorated living conditions; 4) social exclusion and marginalization; 5) lack of social interactions; and 6) high incidence of crime (Moreno, Oyeyinka, and Mboup 2010, xiii). An absence of policy coordination between national and local governments limits a city’s ability to manage urban development and implement strategies to mitigate the negative impacts of spatial inequality.
Opportunities for Urban Housing
Settlement upgrading projects are one type of opportunity to improve low-income housing and slums in urban areas. This type of urban renewal focuses on improving property tenure security and on greater provision of government services. Regularization of land tenure is important because residents who possess a housing plot with a formal land title are more inclined to invest and make improvements to their property (Choguill 1999, 299; Bredenoord and van Lindert
2010, 281; Field 2005). This investment in turn improves the real estate markets in lower income areas and can drive local economic growth (Field 2006). Business development in the form of home-based micro-enterprises is more feasible once a slum begins to receive government services such as electricity, water, sewage, and garbage collection. In fact, slums are frequently the primary location of informalsector businesses in developing countries (Majale 2008, 271).
Electricity, Water, and Sanitation
While the absolute need for electricity, water, and sanitation is greater in rural areas, the rapid pace of urbanization is threatening recent gains made by cities
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in provision of these services. Moreover, the greater economies of scale present in cities allows for more cost-effective extension of services to the urban poor rather than expanding access to rural areas.
In terms of access to improved water and sanitation, the need remains greatest among rural populations. However, due to rapid urban population growth between
1990 and 2010, the number of urban residents lacking access to improved water and sanitation actually increased. By contrast, the number of rural residents lacking access to improved water and sanitation only declined (WHO/UNICEF
JMP 2012, 12, 23). Therefore, although many more rural residents use unimproved water sources and sanitation than do urban residents, the worldwide trend of rapid urbanization necessitates attention to cities to ensure that prior improvements in urban areas are not lost.
Electricity is less critical to poverty reduction than access to water and sanitation, largely due to adverse health outcomes that result from the latter two services.
Even so, lack of access to modern energy services is still a serious hindrance to economic and social development, and 85 percent of those without access to electricity live in rural areas (OECD/IEA 2010, 17). Although urban residents have greater access to electricity, 40 percent of those residents obtain it illegally.
Therefore, the challenge of electricity in rural areas is one of access, whereas in urban areas, challenges relate to illegal hookups and reducing the financial losses to providers that result from theft.
Opportunities for Provision of Electricity, Water, and Sanitation Services
Generally, the concentration of population, activities, and industrial productivity in cities leads to a declining effective price of infrastructure, including power and water supply (Mitra and Mehta 2011, 171). For water services, economies of scale decrease costs for water treatment and bill collection, and the willingness to pay for services is often higher in urban areas (Satterthwaite and McGranahan 2007, 32).
Similarly, providing legal electricity to urban slum dwellers can be profitable because providers can take advantage of the high densities of urban dwellers and reduce losses from theft (Baruah 2010, 1016-1017). Theft of electricity through illegal connections can account for 50 percent of electricity losses to providers
(Sawin and Hughes 2007, 93). As electric power industries are among the most capital-intensive industries in an economy and drain the scarce financial resources of developing country governments, it is important that electricity providers be able to recuperate capital expenditures (Humanitarian Technology Challenge 2010).
Moreover, entities that exist in cities, such as municipal committees, can help to structure popular participation in local governments. Such civil society participation promotes greater interaction between “government institutions, social agents and market agents to promote social inclusion and participation in the implementation of more adequate and socially just urban policies” (Costa et al. 2009, 3133).
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Public Transportation
Well-designed urban public transportation systems can be highly effective economic and social equalizers (ITDP 2009). Although some public transportation projects have large net benefits, other projects have favored a minority of wealthier commuters using high-cost rail and bus options at the expense of the poorer majority who walk, bike, and use less expensive means of transportation (Ahmed et al. 2008). The most successful urban public transportation infrastructure developments have considered the local demographics, environmental consequences, project feasibility, and medium- to long-term economic benefits of project designs (Wang, Lu, and Peng 2008, 85).
Public transportation infrastructure costs range considerably and largely depend upon the urban area, project design, and administrative capacity. Depending upon the goals and resources of urban areas, solutions to congestion, pollution, and connectivity can vary from small neighborhood-specific initiatives to large-scale regional projects. Extensive public transportation networks often have large upfront costs. Urban areas in developing countries also have difficulty setting user fees at levels that sustain operating costs but remain appropriately priced for most potential riders (Ahmed et al. 2008, 126). Diverting traffic during construction can limit mobility and, subsequently, have a negative effect on financial activity.
Public transportation infrastructure construction can also result in damages to short-term air and water quality.
Political feasibility is often the greatest barrier in planning and implementing public transportation projects. Large-scale projects make both public and private land reclamation difficult. Gaining bureaucratic consensus and mobilizing public support for public transportation can be difficult in urban areas with expanding motor-vehicle usage. Finally, it is difficult to convince the general public that an alteration or reduction of road space for public transportation is physically possible and beneficial overall, despite net benefits for a large portion of potential low-income users (Ahmed et al. 2008, 136-138). In the end, political constituencies or business interests may have more influence on design and implementation than the efficiency or equity of the project. Some of the easiest and most profitable forms of corruption are associated with infrastructure projects
(Johnston 2005, 27).
Opportunities for Public Transportation
Intra-city connectivity and widespread access to public transportation have contributed to economic growth in urban areas of developing countries (World
Bank 2006a, 16). The planning, design, and implementation stages can lead to short- and medium-term employment opportunities. Although most are laborintensive positions, projects have also led to an increase in long-term, higher skill employment opportunities associated with the maintenance and expansion of existing infrastructure.
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In comparison to the status quo, increased modes and volume of public transportation are associated with shorter travel times, improved intra-city connectivity, a reduction in stress, greater social cohesion, and improved health conditions from sustainable reductions in carbon emissions (Ahmed et al. 2008,
126; Evren and Murat 2001, 800; Woodcock et al. 2009). Health improvements and increased income are positively associated with well-designed urban public transportation projects. Urban infrastructure improvements also have significant spillover effects (Woodcock et al. 2009), as cities have copied the successful design and implementation strategies of nearby cities (Cernansky 2011). Some urban infrastructure projects have resulted in better governance and greater accountability (Hossain 2008; Hironori et al. 2010). Although expanding public support for public transportation infrastructure can be challenging, a re-framing of its purpose at the core of the planning stage could garner widespread support for issues of equity that are often ignored by the political elite (Wilsson 2001).
Environmental Degradation and Sustainability
Two main issues need to be addressed when discussing environmental degradation. The first is municipal solid waste management and the second is the impact of climate change. Both issues have ramifications for health, education, infrastructure, economic growth, and poverty. Further, urban populations are susceptible to a “double-exposure” whereby particular developing regions, sectors, or populations are confronted by the impacts of both climate change and economic globalization (O’Brien and Leichenko 2000, 227).
Municipal Solid Waste Management
Urban population growth will greatly increase the amount of solid waste generated. As cities grow, subnational and municipal governments will need to adjust solid waste management to address this increase. Municipal solid waste management has impacts on health, surface and groundwater supplies, riparian and littoral ecosystems, and agriculture. It also has significant environmental health implications across income groups, although the poor tend to be disproportionately harmed (Ahmed and Ali 2004, 468). On average, cities in developing countries spend approximately 30 percent of their budgets on solid waste management, while only 50 to 70 percent of solid waste is actually collected (Henry, Yongsheng, and Jun 2006, 94). The remainder is tossed into open-pit landfills that are inadequately maintained and a major source of pollution and disease (Gowda et al. 1995, 157).
When local governments cannot sufficiently collect and dispose of their solid waste, informal economies emerge to fill the void. This informal sector is an important source of income for urban populations as well as a form of trade among the urban poor; items salvaged from local landfills and trash pits are re-sold to lower-income populations (Wilson, Velis, and Cheeseman 2006, 797). This informal economy can be divided into four sectors: itinerant waste buyers, street waste collectors, municipal waste collection crews, and dump collectors (Wilson, Velis, and
Cheeseman 2006, 798). Itinerant waste buyers buy recyclable materials from
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households; street waste collectors collect waste thrown into the streets before municipal collection; municipal waste crews recover material with municipal solid waste vehicles; and dump collectors reclaim usable or recyclable waste from landfills. Economically and socially marginalized groups typically complete the informal collection of municipal solid waste (Ahmed and Ali 2004, 469). While informal employment opportunities arise in the waste management sector, participants frequently lack basic provisions to protect themselves from shards of glass, pieces of metal, disease, and bacteria present in the piles of solid waste.
An issue pertaining to the informal waste management sector is electronic waste
(e-waste) disposal and recycling. In urban areas of developing countries, the recycling and trade of e-waste is especially profitable because valuable materials, such as copper, gold, silver, and aluminum can be extracted and resold. Many developed countries are exporting their e-waste to developing countries for processing or disposal as a part of aid programs for the poor, or because of prohibitions against dumping e-waste in landfills in developed countries
(Osibanjo and Nnorom 2007, 494). Many e-waste recyclers, however, are informal operations administered by the urban poor with little concern for the environmental and health impacts of processing (Osibanjo and Nnorom 2007,
496; Nnorom and Osibanjo 2008, 855). Many processing methods in urban areas in developing countries involve sky incineration, cyanide leaching, and smelting.
The waste materials are then dumped into local open sewers or pit landfills, which can contaminate water supplies.
Opportunities for Municipal Waste Management
The issue of waste management can be addressed at a subnational if not urban level. Waste management is typically a local issue with very few tangible impacts outside of the immediate urban area, at least in the short-term. For example, nongovernmental organizations (NGOs) have been instrumental in bringing attention to the impacts of dumping hazardous chemicals and materials into local water supplies (El-Fadel et al. 2001, 296). Investing in waste management at the local level would be an efficient way to alleviate these problems while helping all income classes, and particularly the urban poor.
Climate Change
Urban populations in developing countries are increasingly contributing to and being affected by climate change. Emissions impact assessments (IPAT) 3 show that as developing countries continue to urbanize, CO
2
emissions will increase
(Martinez-Zarzoso and Maruotti 2011, 1351). Recent estimates attribute 800,000 deaths to urban air pollution worldwide per year (Campbell-Lendrum and
3
IPAT calculations are a way to measure the impacts of a given environmental policy. They are typically used for assessing the impact of greenhouse-gas emissions and anthropogenic emissions over a given period of time. The (I) stands for “Impact,” (P) is for “Population,” (A) is for
“Affluence,” typically measured as gross domestic product (GDP)/capita, and (T) is for
“Technology,” typically measured as Energy/GDP, or Emissions/GDP. The equation is thus:
I = P * A * T.
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Corvalán 2007, 113). Higher greenhouse gas emissions are attributable to both increased transportation and industrialization and larger amounts of cities’ organic solid waste, which produces methane (Couth and Trois 2010, 2336).
Climate change will disproportionately affect the poorest urban residents of developing countries. They will be most affected by rising sea levels, outdoor air pollution, water scarcity, urban heat islands, population density, and rural-tourban migration (Campbell-Lendrum and Corvalán 2007, 109). Rising sea-levels and more powerful storms will lead to flooding in coastal urban areas where the poor bear the brunt of the damage (Knutson and Tuleya 2004, 3493; Campbell-
Lendrum and Corvalán 2007, 113).
Populations living in water-stressed areas will be particularly affected as uncertainty about the future availability of water due to climate change could lead to a number of political issues and conflicts which will disproportionately affect the urban poor (Kivaisi 2001, 546). Moreover, as rainfall becomes less predictable and less abundant due to climate change, sustaining agricultural livelihoods will be increasingly difficult (Barrios, Bertinelli, and Strobl 2006, 358). Less rainfall reduces crop yields in developing areas that lack effective irrigation (Parry et al.
2004, 63), leading to more urban migration (Adger et al. 2003, 189).
Opportunities Arising from Climate Change
Both urban and rural areas are affected by climate change. Access to clean water is a shared concern of urban and rural areas. CO
2
and greenhouse gas emissions from factories and automobiles are of greater concern in urban areas (Kundzewicz et al. 2008, 7). Therefore, strategies to address the causes and impacts of climate change will likely encompass both national and subnational policies.
Health
The global transition from rural to urban living has both positive and negative impacts on population health. Among the negative urban impacts are a triple threat of communicable diseases, non-communicable diseases, and accidents/ injuries (Friel et al. 2011, 861). Access to health services in urban areas is typically better than in rural areas (Fay 2005, 9). The availability of health care services, however, does not ensure affordability and the timely utilization of health services (WHO and UN-HABITAT 2010 iv). Inequalities in the social distribution of health care can be observed at a country level (the urban-rural divide) and at a city level (the rich-poor divide) (Friel et al. 2011, 861). Social inequalities and various forms of exclusion exacerbate health risks in urban areas.
Despite important improvements in health indicators among urban populations over the past century, the unequal health distribution in cities can result in worse health outcomes among the urban poor compared to the rural poor (Friel et al.
2011, 862).
Urban populations are often thought to have better access to health care services than their rural counterparts. In fact, the high level of inequality found in cities in
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developing countries contributes to a variety of additional challenges for the urban poor. These challenges include an inability to pay for goods and services, a lack of social support systems (Pridmore et al. 2007), unhealthy and unsafe living and working conditions (Kjellstrom et al. 2007), exposure to crime and violence
(Campbell and Campbell 2007, 59), limited food choices (Dixon et al. 2007, 119), isolation (Pridmore et al. 2007), and powerlessness (Burris et al. 2007). In an attempt to remedy these challenges of the urban poor, some governments have focused on improving access to services and increasing spending on health care.
Although this is a crucial element of improving the health of the urban poor, real health outcome improvements also require the reduction of urban poverty on a broad scale.
Women and children living in slums bear the largest burden resulting from poor sanitation and housing conditions and poor-quality or unaffordable health services. These children have low rates of vaccination and high levels of malnutrition and infectious disease (Zulu et al. 2011, 195). Van de Poel,
O’Donnell, and Van Doorslaer (2007, 1992) found that urban children in developing countries are 40 percent more likely to be at risk for stunted growth and mortality than rural children. African children living in informal settlements in sub-Saharan cities are more likely to die from easily preventable respiratory and waterborne diseases than their rural counterparts (Moreno and Warah 2006,
51). Key health challenges for women living in slums are vulnerability to HIV infection, high maternal mortality rates, and inadequate access to reliable family planning services and products (Zulu et al. 2011, 195-196). A woman’s ability to limit the size of her family also directly affects the educational opportunities for her daughters because girls from smaller households have a higher likelihood of staying in school (UNFPA 2005, ix).
Non-communicable diseases and injuries are increasingly important population health problems among the urban poor (Campbell and Campbell 2007). Noncommunicable diseases with a significant impact on residents of informal settlements include obesity, diabetes, cancer, chronic heart diseases, stroke, and hypertension (Mercado et al. 2007, 10). Addo, Smeeth, and Leon (2007) found that the urban poor have higher levels of hypertension compared to rural populations in lower-middle income countries. There has also been an increasing level of obesity among socially marginalized city dwellers (Kjellstrom et al. 2007,
86-97). Moreover, the incidence of non-communicable diseases generally increases with decreasing social status in urban environments (Fleischer et al.
2008). The urban poor also comprise large proportions of the pedestrians, bus and truck passengers, and cyclists in poor countries, resulting in a higher rate of morbidity and mortality from traffic injuries (Nantulya and Reich 2003) (see
Table C1 in Appendix C for a list of emerging urban health issues and the variation in burden by key features in urban growth and Table C2 for a breakdown of urban health issues by type of health risk).
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Opportunities for Urban Health
Urban governance structures that support participation, social capital, social accountability, and social inclusion can lead to public health improvements which can in turn serve as a significant stimulus in ameliorating urban poverty. Public health campaigns with a focus on urban poverty as an urgent public health issue can create a policy window to increase levels of equity and overall health in cities in developing countries (Mercado et al. 2007, 8). Additionally, the World Health
Organization (WHO) finds that public health campaigns and other types of interventions with a goal of increasing health equity and health outcomes “can unite individuals, communities, institutions, leaders, donors, and politicians from divergent sectors, even in complex and hostile contexts where structural determinants of health are deep and divisive” (Mercado et al. 2007, 11). Although the health challenges of the urban poor are sizable, an increased focus on improving urban health equity could have positive resonating effects throughout a country’s economy and society.
Education
Developing countries have the potential to benefit from large social and private returns to primary education (Psacharopoulos and Patrinos 2004, 16). The large spillover effects from increasing the coverage and quality of primary urban education include reduced crime, improved health, and increased civic participation (Hanushek and Woessmann 2008, 615). Nevertheless, factors such as poverty, gender inequity, disability, child labor, and minority group status can exclude children from schooling. Decisions to attend school are highly responsive to education costs and subsidies. Social networks and sporadic economic shocks also influence decisions about sending children to school or into the labor market
(Kremer and Holla 2009). Improving access to education is important as it is a significant driver of economic growth and poverty reduction (UNESCO 2012).
Developing countries spend less than half of the GDP per capita on primary education when compared to developed countries, even though a higher fraction of the population in developing countries is of school age (Kremer and Holla
2009, 531). Further, many developing countries fund public education at half of the required levels needed to generate the highest rates of return (Psacharopoulos and Patrinos 2004, 24). Early childhood education and primary education bring about the greatest social returns in developing countries, but often receive smaller expenditures than higher education (Kendall 2011).
Successful urban education in developing countries has been a broad-based effort to offer primary, secondary, community, technical, and vocational education to both children and adults, but significant barriers to access and quality learning remain (UNESCO 2012). Insufficient expenditure in education has accounted for low teacher salaries, high student-teacher ratios, limited instructional resources, and poor school facilities. Low PISA (Programme for International Student
Assessment) test scores suggest that children learn remarkably little in many developing countries (Hanushek and Woessmann 2008, 658). This presents a
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serious challenge as scores are indicative of cognitive skills that predict individual earnings, income distribution, and economic growth (Hanushek and Woessmann
2008, 657). In response, low-income families may spend up to half of their income on private education opportunities or take out large loans with high interest rates to pay for higher quality private schooling (Kendall 2011). Many developing countries are involving the private sector to improve a small number of high-quality schools (World Bank 2011a, 15). These efforts have undercut the national public education system and ignored the most vulnerable urban populations who would bring about the greatest social and private returns from higher quality primary education (World Bank 2011a, 3, 15).
Opportunities for Education
Increased access and higher quality instruction are the two most important factors for improving urban education. Early childhood education targeted at the most vulnerable urban populations, especially girls, has the greatest social returns for urban areas (AusAID 2011). A mother’s education level, more than any other factor, influences a child’s future education and earnings (Nguyen 2008, 43).
Governments providing quality, context-appropriate education for both children and adults in formal and non-formal settings increase economic growth and reduce poverty. Low-cost initiatives, such as information campaigns that educate poor urban populations about the high private returns to education, can increase enrollment rates (Jensen 2010), lower attrition rates, and help students achieve higher test scores (Nguyen 2008, 1).
Financial Services
For decades, international financial institutions have focused on structural readjustment policies as engines of economic growth and poverty reduction
(Banerjee and Duflo 2004). Income divergence between and within countries has led to a rethinking of economic strategies and increased efforts to integrate the poor into formal financial structures through financial services at the individual level (Deininger and Squire 1997, 38-41). More than half of the poorest residents of developing countries do not rely on the formal financial sector for savings, credit, and other services. The poorest 20 percent of urban dwellers largely operate outside of the formal financial system (Gopinath Oliver, and Tannirkulam
2010). Economic shocks related to the loss of employment, sudden deaths of family breadwinners, and emergency health care costs are the most common financial challenges that face the poor (Christopher 2011). Despite better financial collaboration between public and private sectors, poor families utilizing formal financial services are not guaranteed increased welfare (Rajan 2009). As an example, microcredit has received a great deal of attention from international aid organizations, but studies have shown that the use of microcredit services alone can drive poor families into higher levels of debt and poverty (Sriram 2010, 1-4).
A comprehensive set of financial services has emerged as the ideal strategy, whereby a single customer simultaneously accesses formal savings accounts, insurance packages, pension options, and credit (Rajan 2009, 49).
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In developing countries, poor urban residents have greater access to financial services than the rural poor, but additional constraints prohibit widespread uptake.
The poor face a number of barriers to opening bank accounts and accessing other services in the formal financial system (Fischer 2008, 39). Common financial challenges to many poor families include inefficiencies in the collection and processing of banking information, rigorous documentation requirements
(collateral and official government documentation), unsafe conditions near transaction points (Rojas-Suárez 2006), financial illiteracy, and a general lack of trust in financial institutions (Karlan et al. 2009). Informal business practices are commonplace even in urban areas of developing countries and account for the large proportion of unbanked adults who access credit primarily through the black market at rates between two and twenty times the formal interest rate. Additional costs to banks associated with monitoring low-income, high-risk customers have increased interest rates (IFC 2010) and have prevented low-income entrepreneurs from sufficiently accessing credit packages large for small- and medium-sized business development (Christopher 2011).
Opportunities for Financial Services
Financial literacy (Cole, Sampson, and Zia 2011) and savings behaviors (Dupas and Robinson (2011) have been identified as two necessary, but insufficient, factors for economic growth and poverty reduction. A holistic set of widely accessible financial services can mitigate economic shocks and increase financial security. A combination of private financial services and government interventions at the national level could foster economic growth through increased efficiency and certainty.
Crime
Urban crime in developing countries is often influenced by disproportionate economic growth, economic and spatial inequality, weak institutions, low levels of education, corruption, and the rising prevalence of gangs and drugs. In developing countries, these issues are exacerbated by the process of urbanization, ethnic divisions, and growing youth populations. Large and increasing male youth populations, and the presence of scarce economic opportunities, contribute to higher crime rates in urban areas (Kunkler and Peters 2011, 279; Buhaug and
Urdal 2009, 9). The literature on urban crime in developing countries focuses primarily on the links between economic inequality, disproportionate economic growth, corruption, and crime. The literature also estimates the costs of crime, which are measured as both economic and social costs. These costs include forgone productive activities, such as investment and lost tourism revenues, higher security costs from violence and crime prevention, and the erosion of social values (Fay 2005, 8-9).
GDP per capita growth rates are shown to be negatively correlated with crime rates, specifically rates of homicide (Guillaumont and Puech 2011, 12). Other studies bolster this assertion and show that economic inequality, as measured by the Gini coefficient, has a positive relationship with crime rates for both robbery
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and homicide (Fajnzylber, Lederman, and Loayza 2002, 1347). In other words, as inequality grows, crime rates go up and further stall GDP growth rates. Links also exist between economic instability, economic shocks, and crime rates. For example, robbery is particularly sensitive to short-term economic inequality and instability, while homicide is subject to both short- and long-term instability
(Guillaumont and Puech 2011, 13). Crime also contributes to the spatial inequality in cities in developing countries as the wealthy create “fortified enclaves” for themselves with gated communities and private security forces to keep out the poor (Landman 2010, 50).
In developing countries, urban instability is associated with civil conflicts, weak leadership, ethnic fractionalization, and rent-seeking (Buhaug and Urdal 2009, 2).
The poor’s lack of trust in local governmental institutions (especially the police) contributes to higher crime rates, particularly in larger cities where vigilantism and victimization are more prevalent (Gaviria and Pagés 2002, 182). As public institutions deteriorate, criminal enterprises proliferate. Gangs become attractive options for the urban poor because of the economic and security opportunities they can potentially provide, undermining the efficiency of traditional markets and governing institutions.
Opportunities for Crime
As crime rates are typically higher in urban areas, programs focusing on urban crime could have a greater potential to be effective in both the short- and longterm. Effective law enforcement is an essential underpinning of economic development while corruption is detrimental to growth (Bowles, Akpokodje, and
Tigere 2005, 349; Salifu 2008, 276). Efforts to crack down on corruption could also be highly effective. Many attempts have already been made in different contexts over the years at both the national and local levels, with varying levels of success in reducing crime rates. Targeting urban crime could be an effective way to deal with both local crime, such as robbery and homicide, and international concerns, such as the drug trade.
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In this section, we review successful subnational policies which drive economic growth and poverty reduction in developing countries. Sub-section A explains how decentralization is both a qualifying condition for cities to undertake such policies and necessary for policy success. Sub-section B discusses the subnational use of traditional economic growth policies. Sub-section C focuses on infrastructure. Sub-section D examines human capital’s role in long-term economic growth and poverty reduction and discusses subnational policy options in health and education. Sub-sections E and F look at policies related to financial services and corruption, respectively. Lastly, Sub-section G provides a summary and discussion of the policies we researched that were the most applicable, successful, and feasible for implementing at a subnational level.
A necessary component of urban and subnational policy success is the level of decentralization, that is, “the transfer of authority and responsibility from lower to higher levels of government” (Kristiansen and Pratikno 2006, 219). Without an effective means of decentralization, potential policies, initiatives, and investments would be better focused at the national level.
Economists have posited that decentralization improves the efficiency of subnational and urban governments by creating competition and stimulating economic growth (Davoodi and Zou 1998, 244). The decentralization theorem asserts local governments can provide Pareto-efficient levels of services for their respective jurisdictions more effectively than central governments (Oates 1972,
35; Bahl and Wallace 2005, 85). These services include infrastructure investments, tax incentives for businesses, and overall regulatory structures conducive to economic growth. The two primary implications of this theorem are:
1) a local government’s comparative advantage in assessing and collecting taxes results in increased levels of revenue mobilization which stimulates economic growth; and 2) local populations will be more willing to pay for the services they want at the levels they want (Bahl and Wallace 2005, 84).
Evidence on whether or not decentralization contributes to economic growth is inconclusive, and the outcome is influenced by the contexts and institutions in the countries in which it occurs (Davoodi and Zou 1998, 254; Bird and Rodriguez
1999, 300). Good governance is crucial for effective decentralization, specifically administrative and fiscal management, and the control of corruption (Ebel and
Yilmaz 2002, 102; World Bank 2009b, 5). Poorly executed decentralization policies and processes can threaten macroeconomic stability and risk increased fiscal disparities (Bahl and Wallace 2005, 94; Allers and Ishemoi 2011, 287).
Rather, most successful decentralization attempts occurred when stable budgets, fiscal management processes and political situations, as well as appropriate
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institutions, were in place prior to decentralization (Tanzi 2001, 12). When these conditions existed, studies of fiscal decentralization have demonstrated a positive association between increased economic growth via increased capital investment at the local level and more efficient resource allocation (Lin and Liu 2000, 16).
When implemented correctly, decentralization affords subnational governments the ability to tailor fiscal policies, such as tax and investment incentives, to local needs and to set conditions that foster economic growth.
To be effective, a decentralized government system requires support from both central and subnational government entities (UN-HABITAT 2006a, 173). Urban and subnational policies and aid initiatives are unlikely to be effective without significant levels of decentralization. Adequate levels of decentralization should be a major consideration for targeting aid below the national level.
Industrial and fiscal policies provide the traditional methods of stimulating economic growth in developing countries. Encouraging foreign direct investment
(FDI), creating economic trade zones, and administering tax policy are all traditionally national policies that contribute to reliable and sustained growth in developing countries. While the literature provides few examples of these traditional policies implemented at the subnational level, some countries have succeeded in doing so.
Industrial policy connotes policy meant to stimulate specific economic activities.
It does not refer only to industry or the manufacturing sector, but also addresses non-traditional agriculture or service sectors (Rodrik 2007, 3-4). Many governments conduct different forms of industrial policy that do not necessarily protect infant industries. These include investment promotion, FDI, export facilitation, and free trade zones (Rodrik 2010). Industrial policy is designed and implemented at the national level. Subnational governments, however, can implement complementary activities to maximize potential benefits toward promoting economic growth and poverty reduction.
Investment Promotion
Private investment can be enhanced by policies associated with the development of the necessary infrastructure and the provision of adequate legal and institutional arrangements for the protection of private property. The evidence suggests that investment promotion efforts increase FDI in developing countries.
Some countries and subnational entities have provided fiscal incentives, cut bureaucratic procedures, and provided information to foreign investors (Harding and Javorcik 2007, 2).
According to the World Bank, many developing countries need to focus on attracting investment and enhancing national and subnational capacity to promote investment (World Bank 2009b). States and cities, rather than countries, are
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increasingly important in competing for investments, especially FDI. The World
Bank identifies three broad categories of practices that facilitate investment: 1) fostering a private sector-minded culture; 2) accumulating deep business knowledge; and 3) implementing internal systems for consistently good facilitation. Some important elements of these categories include: training staff and knowledge accumulation; offering salaries and bonuses closer to private sector standards; concentrating efforts in priority sectors; coordinating the facilitation with local and international networks and partners; establishing a minimum level of in-house research; and developing account managers with knowledge in particular sectors (World Bank 2009a, 2). For example, investors consider the technical skills of local residents when deciding where to invest.
Therefore, subnational governments can provide vocational training and establish community colleges to attract investment to their regions and help residents take advantage of the potential new jobs created.
Laws, regulations, and institutional arrangements shape the economic activity of cities and regions and have important implications for economic growth. Even if policies are developed at the national level, they are implemented at the local level and, accordingly, can vary widely within a given country. Foreign investors have to negotiate with local authorities over licenses, access to public services, buildings, and tax incentives and subsidies, all of which affect their ability to operate. In the Philippines, starting a business in the city of General Santos is easier than in San Juan (World Bank 2011b). In Indonesia, dealing with construction permits is easier in Yogyakarta than in Balikpapan, and it is easier to register property in Bandung than in Jakarta (World Bank 2012). Ideally subnational governments can help ease administrative hurdles and standardize procedures required for doing business, thereby improving the business climate.
Moreover, due to greater trade openness, local governments play a role in facilitating the entry and exit of firms and contributing to investor confidence.
Finally, urbanization has increased demand for goods as well as infrastructure expansion, thus requiring more localized investments (Magrassi 2000, 3).
Indian states have had success in attracting investment. For example, the government of Karnataka has pursued a progressive industrial policy characterized by an attractive package of investments and concessions. These efforts included infrastructure investments, such as telecommunication and transport improvements, to make private investment more attractive and effective.
Moreover, the state of Karnataka has invested in promoting entrepreneurship among the local population, in particular in rural areas and among disadvantaged groups. Finally, the state has focused on increasing value-added goods and services through research and development activities (Bajpai and Sachs 1999, 6).
In Russia, FDI is not only concentrated in traditional business centers, but also in provincial cities because of local government-led reforms (Meyer and Nguyen
2005, 64).
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Participatory Budgeting
Participatory budgeting allows community-led councils to play a significant role in policy and municipal budgeting decisions for health, education, and other public services (Moreno and Warah 2006, 170). Brazil was one of the first countries to introduce participatory budgeting in certain municipalities. After the implementation of participatory budgeting in Porto Alegre, the number of public schools increased from 29 to 84 (Moreno and Warah 2006, 170). Porto Alegre’s budget allocation for health and education increased from 13 percent in 1985 to
40 percent in 1996 (Bhatnagar et al. 2004, 3). Effective participatory budget processes can result in a more inclusive and equitable allocation of public resources. Success, however, depends on: incentives for mayors to delegate decision-making authority, effective rules delegating this authority to citizens, and response by civil society organizations and citizens (Wampler 2007, 4).
Reducing the Informal Sector
Some estimates indicate that nearly 60 percent of the labor force in developing countries is employed in the informal sector, including activities such as commerce, agriculture, construction, manufacturing, transportation, and services
(van Rooyen and Antonites 2007). Other sources estimate that between 25 and 75 percent of non-agriculture-based employment in developing countries is in the informal sector (ILO 2002, 6). Subnational governments can create a conducive environment for local economic development to reduce the informality of employment in developing countries. Reducing the informal sector has positive externalities: reduced tax evasion, promotion of labor and institutional regulations, and reduction of crime and corruption. One policy that has been implemented at the local level to reduce the informal labor sector is “training for employment.” This policy creates jobs by linking potential employees with labor opportunities while providing mentorship (van Rooyen and Antonites 2007, 340).
Other local initiatives that formalize the informal economy include local advisory agencies that provide information, loans, advice, and support services to local informal entrepreneurs on how to formalize their ventures (Williams 2005, 344).
Local governments can also provide a shared infrastructure facility or incubator to support potential entrepreneurs in the start-up phase of development. All of these activities, if already in use, can be broadly expanded to facilitate the transfer of work from the informal to the formal economy.
Municipal Solid Waste Management Systems
In urban areas of developing countries, the effectiveness of solid waste management systems is often one of the indices for assessing good city-level governance (Nzeadibe 2009, 93). In addition, the incorporation of informal sector recyclers into cities’ formal solid waste management systems creates economic growth opportunities for the informal recyclers, the beneficiaries of their recycled goods, and reduces waste management expenses for municipalities. Two percent of the population in Latin American and Asian cities depend on informal recycling for their livelihood. Many people engaged in informal sector recycling may be prevented from entering more formal employment due to poor education, physical
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disability, or their marginalized status in society, leaving recycling as one of few ways they can support themselves. In addition, the informal recycling sector provides a reliable supply of secondary raw materials for the local manufacturing industry, thereby replacing more expensive imported raw materials. Moreover, informal waste management systems reduce the cost of formal waste management at no direct cost to taxpayers (Wilson, Velis, and Cheeseman 2006).
The major challenges to incorporating informal sector recyclers include changing the negative perception of local officials toward these groups and the significant health and safety risks associated with informal recycling. Health and safety risks can be mitigated through supportive public policies that stimulate and improve working conditions, and improving the legitimacy of their work should help change negative perceptions about them. Despite these challenges, Wilson, Velis, and Cheeseman (2006, 806-807) argue that the benefits of incorporating informal sector recyclers into formal solid waste management systems outweigh the costs, particularly given the expense of developing new formal recycling and recovery systems. Rather, they encourage developing countries to build upon, instead of attempting to replace, informal sector recycling systems. In fact, in a recent survey of recycling systems in low- and middle-income countries, the informal sector outperformed the formal waste management system in terms of the amount of materials recycled, total net costs, and its ability to sustain the livelihoods of waste workers. Moreover, in many low- and middle-income countries, informal sector recycling is the only system of recycling available (Scheinberg et al. 2011, 196).
One effective way to formalize informal sector recyclers is to organize and train them into micro and small enterprises, which boosts their ability to add value to collected materials while also helping their activities become more legitimized and socially acceptable. Working with micro and small enterprises has also been recognized as an important form of public-private partnership (PPP), successfully pursued in the case of Sao Sebastiao in Brazil in which the Catadores created a cooperative and succeeded in legitimizing their profession (Wilson, Velis, and
Cheeseman 2006, 806).
Below, we discuss some successful efforts subnational governments have taken to provide adequate infrastructure, which is vital to economic growth and poverty alleviation.
Land Tenure and Property Rights
We use the term “land tenure” to refer to the right to occupy land or the right to not be evicted from land for a set amount of time. Municipalities may confer permanent property rights or non-permanent land tenure, which can lead to differing development outcomes. Moreover, the ability of municipalities to confer permanent property rights or non-permanent land tenure differs from country to country. Therefore, we include a general discussion of the advantages and
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disadvantages to both types of land tenure, as well as a discussion of the policies available to municipalities in conferring land tenure to their residents.
Ninety-four percent of slums emerge as unplanned settlements where access to services is minimal to nonexistent and overcrowding is normal. Lack of land tenure contributes to the informal and unplanned nature of these settlements (UN-
HABITAT 2006b). Many scholars argue that land tenure is essential to sustained urban development as it supports cost recovery of infrastructure, which is important due to the capital-intensive nature of such projects (Werlin 1999;
Choguill 2007; Das and Takahashi 2009). In the case of participatory or “selfhelp” models of slum upgrading, land tenure can provide the urban poor with incentives to pay for costly connection fees for electricity, water, and sanitation
(Das and Takahashi 2009; Baruah 2010, 1016). Moreover, tenants with secure land tenure are more likely to invest in property and have more time and resources to devote to work and educational pursuits (Field 2005, Field 2006).
In some cities, permanent property rights seem to have led to improved living conditions for residents of slums (Gulyani, Bassett, and Talukdar 2012).
However, attempts to formalize land tenure into permanent property rights invite litigation, because slums often emerge on private land (Das and Takahashi 2009,
225). In addition to inviting litigation, such attempts are administratively complicated and expensive, susceptible to abuse, and risk the distortion of land and housing markets (UN-HABITAT 2008). For example, conferring permanent property rights to residents led to only short-term gains for low-income owners in cities in Brazil, Senegal, the Philippines, and Cambodia (Dyal-Chand 2010) because increases in land value caused large numbers of newly titled low-income landowners to quickly sell their homes. Although such problems of unregulated land markets can be mitigated by government intervention (Payne 1996, 16), the situation illustrates a marked difference between providing permanent property rights in urban versus rural environments: in rural areas, the policy seems more clearly to result in “greater stability, investment in real estate, and increases in income and human development” (Dyal-Chand 2010, 91).
Successful secure land tenure policy for the urban poor depends on each city’s specific circumstances (UN-HABITAT 2008). A dogmatic march toward individual titles, while tempting in theory, will likely fail to achieve policy outcomes (Payne 1996, 22). The United Nations Human Settlements Program
(UN-HABITAT) recommends that “in this sense, it is preferable to consider tenure and property rights as a continuum with different shades of grey as well as black and white categories” (2008). In our analysis, we reviewed policies along a continuum and found that those “grey” or intermediate policies may be most applicable in a number of urban contexts.
The UN-HABITAT (2008) describes the three common policies adopted in urban settings along with their benefits and limitations: 1) evict unauthorized settlers; 2) issue property titles in beneficiaries have adequate income; and 3) implement
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intermediate tenure policy options. The first of these policies can be effective only when local governments take additional action to provide housing for displaced residents, as forced evictions disrupt vulnerable communities, decrease the amount of housing available for the urban poor, and move them away from educational and work opportunities. The second policy, issuance of property titles, provides both a high degree of security as well as a valuable asset to poor households. It can also increase their access to formal credit and encourages residents to invest in improvements to their property while providing local governments with revenues from property taxes. In addition to inviting litigation, this policy is administratively complicated and expensive, is susceptible to abuse and may encourage unauthorized development. Moreover, this policy risks the distortion of land and housing markets and may result in rents and property taxes that are unaffordable for tenants. The third policy of implementing intermediate tenure programs provides many of the same benefits as issuing property titles discussed above, while minimizing the land and housing market distortions.
Intermediate tenure policies can also increase social cohesion by decreasing residents’ incentives to sell their property for profit. Such policies include temporary occupation licenses, private land leases, certificates of rights, declarations of possession, and homeowners associations. This policy option is optimal for local governments concerned with distorted markets or a high potential for litigation in formalizing property rights, and it may be most applicable in a number of cities.
Housing
Three policy-supported actions are available to government officials to provide their citizens with adequate housing, and all have been implemented by national and subnational governments. First, governments can build residential units and either give or rent them to citizens at full or subsidized rates. This was the dominant strategy after World War II through the early 1970s. Second, governments can take precise steps to lower the price of housing in an attempt to make it more affordable to residents. This strategy was dominant from the late
1970s through the 1980s, but housing was still unaffordable for about 20 percent of most urban populations. Third, attempts have been made at national and subnational levels of government to improve the housing market to facilitate home ownership by improving access to residential land or by making home loans readily available. This strategy is sometimes referred to as the “enablement strategy” (Choguill 2007, 146).
Housing Finance
UN-HABITAT has calculated that one-sixth of the world’s population lives in slums. This proportion could rise to over one-third by 2040 (Merrill 2009, 1).
The majority of these people will never be able to afford or have access to formal mortgage finance (Merrill 2009, 1; Stein and Castillo 2005, 48). Given the recent emphasis on the “enablement strategy” as the most viable housing policy for lowincome populations, the importance of innovative and nontraditional financial schemes and institutions is becoming increasingly clear. These methods include
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microfinance for housing and revolving loan funds (Merrill 2009; Stein and
Castillo, 2005). These innovative schemes demonstrate that “the housing needs of the poor can be financed in a way that is economically viable, affordable, and consistent with test methods of delivering finance services to the poor” (Stein and
Castillo 2005, 49). In these programs, credits are given and interest charged, but not necessarily at market rates. These types of programs also accept a wide variety of collateral and security from households. Flexibility in the use of collateral has allowed for the participation of low-income households even if they have not resolved the legality of their land tenure (Stein and Castillo 2005, 50).
Such housing loans also help lower-income urban residents pay for costly service connection fees (Satterthwaite and McGranahan 2007, 31). Once these credits are recovered, they are reinvested into new loans for households in the same income group, allowing for reinvestment of capital into the same target population over a long period of time (Stein and Castillo 2005, 50).
Funding for the institutional development of intermediary organizations is critical to the success of the housing improvement lending programs. In addition, highquality credit analysis and client screening are important to secure cost-recovery.
Creativity in the recognition of collateral for loans also contributes to higher levels of cost-recovery. Alternative forms of collateral could include considerations such as the number of years the family has lived on a site without the threat of eviction by original owners and the payment of taxes by the household to governmental institutions (Stein and Castillo 2005, 65).
Participatory Slum Upgrading Programs
In the context of increased decentralization in developing countries, slum upgrading has become “a collaborative urban service provision and development approach that seeks participation by local government, NGOs, and citizens” (Das and Takahashi 2009, 213). Slum upgrading programs typically seek to improve water, sanitation, electricity provision, and waste collection, in addition to housing (Werlin 1999). The strengths of this infrastructure improvement policy include the empowerment of residents (Lucas 1976, 142). Active participation confers a sense of ownership over infrastructure projects, helping to ensure their management and maintenance (Ibem 2009, 130).
Ibem (2009) finds infrastructure projects led and financed by the community to be appropriate only for small- and medium-scale projects. These types of projects also tend to be delivered more slowly than projects funded by government-community partnerships that often involved lending from multilateral organizations. On the other hand, without community engagement in projects led by governments or development agencies, cost recovery for ongoing management and maintenance of infrastructure is not planned, leading to only short-term gains for slum residents and a wasted infrastructure investment
(Werlin 1999, 1528-29).
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Property Taxes
Locally levied property taxes tend to be the most effective fiscal policy tool for generating local government revenue. Property taxes that are locally administered and controlled can create competition between urban areas, while providing incentives for businesses and households to develop (Lewis 2003, 230). In developing countries property taxes are a means of broadening the tax base for local governments because they are harder to evade than income taxes and less burdensome that value-added taxes (VATs). They are also arguably less regressive than consumption taxes, although the issue of regressivity is far from resolved (Connolly and Bell 2010, 978). Property taxes are under-utilized in developing countries: they account for only 0.6 percent of GDP, compared to
2.1 percent of GDP in member countries of the Organisation for Economic Cooperation and Development (Connolly and Bell 2010, 978). They are also relatively inelastic in terms of tax-base supply, making them a reliable and consistent source of revenue over time (Slack 2011, 10). Reliable revenue sources are vital for local governments as they are typically the “service providers of last resort,” particularly for the poor (Chernick and Reschovsky 2006, 427). To be effective, property taxes require a reliable system of property rights, property ownership data, and an effective property valuation system (Aluko 2005, 208).
Property taxes are assessed by a variety of methods. For urban areas in developing countries, these mainly consist of area-based taxes and value-based taxes. Areabased taxes are calculated based on the physical space or land occupied by the property and are the easiest to determine and administer; but, they may be the most unequal regarding assessed value and impacts on poorer populations
(Connolly and Bell 2010, 979). Value-based taxes are calculated by assessing the fair market value of the property. This tax is more difficult to calculate and administer, although it is much fairer to poorer populations (Aluko 2005, 205).
Area-based and value-based property taxes are promising fiscal policies urban areas can implement to foster economic growth and reduce poverty. Property taxes can be effective at raising revenue in the short term if their implementation is coupled with a “mass property assessment” to efficiently eliminate backlogs of inaccurate and incomplete tax rolls and property valuations (Kelly 2000, 10).
However, the lack of effective tax administration and the absence of an accurate tax roll in many developing countries can undermine the effectiveness of this policy (Aluko 2005, 209).
The debate on whether or not to use an area-based system or a value based- system is unsettled. Area-based systems are preferable in municipalities where tax administrations are inefficient or lack sophistication. In the short term, it may be preferable to have an area-based system so people can become accustomed to paying property taxes. Additionally, it immediately broadens the tax base
(Connolly and Bell 2010, 979). In the long term, however, as countries develop their economies and tax administration systems, area-based taxes become increasingly unequal, especially when factoring in predicted market values. Area-
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based taxes can also decrease the accuracy of the property tax levy as higher value property can be undervalued and lower value property can be overvalued. Over the long term, a policy shift toward a value-based system will assist urban governments in collecting a greater portion of all available potential revenue
(Chernick and Reschovsky 2006, 418).
Water and Sanitation
More than two billion people worldwide gained access to improved drinking water between 1990 and 2010, and the Millennium Development Goal for drinking water was met five years ahead of schedule in 2010. Unfortunately, the world is unlikely to meet the Millennium Development Goal target for sanitation
(WHO/UNICEF JMP 2012, 2). Ninety-six percent of the worldwide urban population has access to safe drinking water, while only 79 percent has access to improved sanitation (WHO and UNICEF 2012, 12, 23). Regional disparities are significant. Improvements in sanitation increase economic growth by reducing the economic losses associated with the direct costs of treating sanitation-related illnesses and lost income from reduced or lost productivity. Moreover, poor sanitation leads to loss of time and effort caused by “distant or inadequate sanitation facilities, lower product quality resulting from poor water quality, reduced income from tourism, and clean-up costs.” For example, in Cambodia, poor sanitation led to losses of about seven percent of GDP in 2005; in India, inadequate sanitation led to economic losses of more than six percent of GDP in
2006 (Van Minh and Viet Hung 2011, 65-66). Despite the great need for sanitation improvements in slums, progress has been slow due to low prioritization by stakeholders, inadequate funding, implementation of inappropriate (unsustainable) technologies, and the difficulties of shared responsibilities (Isunju et al. 2011, 368).
Condominial Water Supply
Condominial water supply programs help to reduce the high costs of water and sanitation connections charged to residents. Under such programs, water and sanitation agencies provide pipes to groups of households which take responsibility for installing the pipes in their homes or yards and maintaining them (Satterthwaite and McGranahan 2007, 33; Werlin 1999, 1530). A project that operates in Karachi, Pakistan cut residents’ unit costs to one-fifth of what they would have been charged by the water and sanitation agency (Satterthwaite and McGranahan 2007, 35). In Buenos Aires, Argentina, a private company extended water supply to some of the poorest neighborhoods by providing technical assistance to community members, including training for specialized labor; residents provided labor and helped obtain building materials (Koppenjan and Enserink 2009, 290).
Communal Sanitation Provision
Communal sanitation refers to sanitation facilities shared by a number of households. It is less expensive than household provision and often easier to provide in existing high-density settlements (Satterthwaite and McGranahan
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2007, 36). Schouten and Mathenge point to research conducted in urban and periurban areas of developing countries showing that the poor are rarely connected to an underground sewer system and are unlikely to be connected in the future: “It is not only the cost of connection and maintenance fees that prevent slum dwellers from gaining access to the sewer network, but also the lack of a regular water supply on which such a system relies” (Schouten and Mathenge 2010, 816). This explains why communal facilities are the most common sanitation option in slum areas. Communal sanitation facilities can be improved upon when communities participate in the planning, implementation, and management. For example, the
Mumbai city government constructed communal toilets for its slum residents, but a third malfunctioned within six months of construction due to unreliable water supply, overuse and poor maintenance by the provider; the sanitation situation improved when communities became involved in planning, implementing, and maintaining the facilities by charging residents a monthly user fee to reimburse expenses (Schouten and Mathenge 2010, 816-817).
Despite these potential benefits, the WHO and the United Nations Children’s
Fund (UNICEF) have excluded communal sanitation facilities as forms of
“improved” sanitation. The reason for this exclusion is because limited data show that they fail to ensure hygienic separation of human excreta from human contact and because concerns remain about the accessibility of communal facilities during the day and the security of such facilities for users at night (Schouten and
Mathenge 2010, 815). Satterthwaite and McGranahan (2007, 37), however, suggest that “public or communal facilities are worth considering where it is not possible to provide water connections and good sanitation to each household.”
This situation is typical in slums of low and lower-middle income countries.
Public-Private Partnerships in Urban Infrastructure Provision
A lack of public funds and inefficiencies of public service provision have given rise to private investment in public urban infrastructures, including water and sanitation, roads and bridges, and public transportation. Private involvement in public infrastructure can improve efficiency, provide better quality, help extend public service delivery, and increase population coverage by raising private investment financing and relieving government budget deficits (Koppenjan and
Enserink 2009, 284-285). Reduced risk to the public sector has also been noted as a benefit of partnerships with the private sector (Jamali 2004, 417).
Concerns about PPP in urban infrastructure provision arise because of the private sector’s focus on short-term return on investment, which is not always compatible with longer term social, environmental, and financial sustainability. Koppenjan and Enserink (2009, 287) suggest three strategies for balancing private sector involvement and sustainability goals. First, cities can work with the private sector to develop projects that create positive cash flows. This strategy requires the willingness and capacity of users to pay for services and/or combining potentially profitable ventures with unprofitable public infrastructure investments (e.g., profitable water contracts with unprofitable sanitation investments). Second, cities
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can balance policies to attract investors while maintaining competition. This is important because competition serves as a mechanism to limit the drive for profit maximization. Without competition, users bear the cost in terms of rising prices and poor delivery (Koppenjan and Enserink 2009, 287). Third, cities can balance public and private priorities through benefit-sharing arrangements, so that private providers share the profit with the government. That way, if profits exceed a certain level, it can be partially directed to the government, allowing “private investments in profitable infrastructural projects help make public funds available for investments in less profitable projects” (Koppenjan and Enserink 2009, 290).
Electricity and Non-governmental Organizations
Electricity is important to economic development because it enhances the educational and productive capacities of slum residents (Azoumah et al. 2010,
131). On a macroeconomic level, as analyzed in over 100 countries, there is a strong correlation between electricity consumption and economic growth, although the direction of the causal relationship requires additional research (Yoo and Kwak 2010, 161). Accordingly, electricity consumption and access to electricity have important implications for economic growth in developing countries at both the microeconomic and macroeconomic levels.
Non-governmental organizations (NGOs) help to fill gaps in the provision of basic services, such as water, sanitation, and electricity. Such gaps often result from both public and private service providers’ ignorance or inability to assist the un-served or ill-served urban poor, due to legal barriers or economic impracticability (Baruah 2010). In their evaluation of the Slum Networking
Project in Ahmedabad, India (now known as Parivartan), Das and Takahashi
(2009, 214) note that the high level of NGO autonomy was vital to the success of that endeavor. In her review of slum electrification in the Slum Networking
Project, Baruah also lauded the role of NGOs to bridge the communication gaps between the various actors involved, particularly the NGOs’ ability to engage slum dwellers in the process and obtain short-term tenure security from the municipal government. This temporary land security incentivized slum dwellers to pay for water, sanitation, and electricity connections, thereby providing cost recovery to service providers (Baruah 2010, 1016). Moreover, most of the programs that have successfully provided housing finance to low-income populations in many Central American countries began as NGOs (Stein and
Castillo 2005, 52).
Public Transportation
One of the most significant contributing factors to urban poverty and overall economic inefficiency is the lack of equitable and accessible public transportation. Intra-city connectivity and widespread access to public transportation contribute to economic growth (World Bank 2006a, 16) and reduce urban poverty by providing the largest net benefits to low-income users (Ahmed et al. 2008, 136-138). Urban infrastructure projects can also have significant
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spillover effects on nearby cities (Open Bicycles Project 2009) and result in better governance and greater accountability (Hironori, Onga, and Diaz 2010).
Transportation corridors are some of the most valuable places in a city, and road space distribution can have significant effects on income inequality, poverty reduction, and economic growth (ITDP 2009). Urban sprawl and increasing road space for motor vehicles is not a natural reflection of free markets (Marshall
2008), as subsidies, fees, and externalities are often associated with land and transportation development (Levine 2006). Traffic congestion reduces urban productivity through its impact on the effective size of the urban labor market, measured by the number of people who can access jobs at a reasonable time and cost (Prud’homme and Lee 1999). Other inefficiencies can impede growth. For example, consumers are not incentivized to use resources efficiently as they do not directly pay for the environmental and economic costs they impose (World
Bank 2008).
Distorted institutional incentives, not a lack of knowledge or access to successful methods, have been the primary cause of poor policies and inefficiencies.
Decentralization has put increasing financial pressure on urban governments and incentivized unsustainable planning practices (World Bank 2009b). Local governments often raise funds to meet short-term fiscal goals. The lease of land use rights and large-scale public-private investments in urban expressways, ring roads, and subways are commonplace. Projects can impede long-term economic growth, as transportation networks are often constructed primarily for short-term revenue generation and not transportation efficiency (World Bank 2009c, 9).
Effective approaches to decentralized public transportation services require changes to a community’s power structures (Bardhan and Mookherjee 2007).
Central components include government responsiveness to the local needs of the majority, and genuine opportunities for participation from disadvantaged populations in the political process. Large low-income countries, such as India, have been relatively successful in coordinating national public transportation policies with local urban government strategies. An ideal national-urban level coordination effort, however, would look different in a country in which the only large urban area is the capital city.
According to the World Bank, in a healthy economy, no more than 10 percent of households should spend more than 15 percent of its household income on transportation costs (Gwilliam 2002, 35). Twenty percent of workers in Mexico
City spend more than three hours traveling to and from work each day (World
Bank 2009c; Cervero 2011, 6). In New Delhi and Manila, transportation through informal minibuses and motorized tricycles to and from work can cost 20 to
25 percent of the daily wages for low-wage workers, who make up the largest percentage of the urban workforce. In the suburbs of Dar es Salaam, transportation expenditures through similar means are as high as 30 percent of income
(Ferrarazzo and Arauz 2000; Kaltheier 2002; Cervero 2011, 6).
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Successful city planning efforts that create effective public transportation do not decrease the total time traveled in a day; they improve accessibility, and thus directly increase productivity by allowing for more trips per day. For the poorest urban dwellers, enhancing access is more important than reducing travel-time expenditures. Increasing the territorial sphere for job searching, saving on food purchases, accessing medical clinics, and seeking better educational opportunities is likely to benefit the poor more than saving time moving along an expanded roadway (Cervero 2011, 17). The ability of poor urbanites to access opportunities and services is essential for poverty reduction in low-income and lower middleincome countries.
Reductions in emissions and increased physical activity resulting from various transport policies can also result in significant economic benefits from greater worker productivity, and additional worker years are the result of avoided emissions and increased physical activity.
Traffic Calming
The urban poor experience a disproportionately high rate of traffic fatalities and injuries (Thakuriah 2009). Traffic calming measures, such as concrete or plastic
“rumble strips” and speed humps, effectively reduce traffic fatalities and injuries
(Forjuoh 2003). These interventions decrease the speed of traffic and subsequently deter the growth of personal motor vehicle usage, a primary cause of traffic fatalities (Montgomery 2006). Rumble strips and speed humps installed on one Accra road in Ghana were directly associated with a 35 percent reduction in crashes and a 55 percent reduction in fatalities (Afukaar 2003, 77). The reduction of vehicle speed is one of the most effective interventions to reduce traffic fatalities and injuries, with benefits accruing immediately upon installation.
Traffic calming mechanisms are inexpensive, easily constructed, and accessible to even the most resource-strapped urban areas. Constructing rumble strips and speed humps are usually the most cost-effective and politically feasible transportation infrastructure in urban areas. Initial political hurdles to constructing traffic calming mechanisms in central locations can often be overcome by initial trials in poorer locations on the outskirts of urban centers (Siddiqi 2012). As the majority of people commuting do not travel in personal motorized vehicles, public support for traffic calming infrastructure can accumulate quickly (Open Bicycles
Project 2009). Informal entrepreneurs, women, and children are especially supportive of such measures, as decreased traffic, both in volume and speed, create more public spaces for economic activity and safer roadway environments.
Bicycle Infrastructure
Bicycle infrastructure consists of metal or concrete barriers separating cyclists from motorized traffic and pedestrians, lock-up stations, and inter/intraneighborhood bike rental systems. Barriers increase roadway safety, incentivize bicycle usage, and increase travel certainty for all commuters. Bicycle stations and rental systems provide smooth transition from low- to high-density areas, and
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serve as reliable feeder routes to commuters connecting to larger transportation arteries frequented by minibus/van, bus, or metro lines. Non-motorized transport planning has become essential for dense and growing urban areas.
Bicycles outnumber cars by almost one billion (UNEP 2011, 2), and the ratio of bicycles to cars in low-income and lower middle-income countries is much greater. Cyclists use only one-third of the road space occupied by a car (UNEP
2011, 6). The International Energy Agency identifies an increase in bicycle infrastructure as one of three components necessary for a reduction of greenhouse gas emissions (UNEP 2011, 4). Bicycle infrastructure leads to fewer harmful emissions from cars and an increase in physical activity, resulting in higher worker productivity and more worker years. Urban pollution in developing countries directly contributes to additional health care costs that can amount to five percent of national GDP (UNEP 2011, 7). Designating road space for nonmotorized transport is one of the most cost-effective policies for saving hundreds of thousands of lives in low-income countries (UNEP 2011, 5).
Secure, well-designed bicycle infrastructure decreases commuter times and traffic-related fatalities and injuries. Bicycle infrastructure is directly related to increased bicycle usage, reduced air pollution, health benefits, and increased equity of mobility. Separate bicycle lanes also facilitate a stronger socialization of traffic regulations, further increasing safety. High-quality bicycle infrastructure is relatively affordable and can cost less than two percent of the cost of Metro rail construction per kilometer (Siddiqi 2012). Finally, bicycle infrastructure allows for greater commuting efficiency, worker productivity, and provides additional economic opportunities in bicycle manufacturing, retail, and maintenance.
Bus Rapid Transit
Bus rapid transit (BRT) is an urban public-transit bus system that uses highcapacity, multiple-car trains to combine the benefits of light rail transit with the flexibility and efficiency of bus transit. BRT consists of high-quality median aligned stations with level boarding, dedicated lanes on surface streets, and busways completely separated from traffic. BRT maximizes efficiency and mobility by utilizing curbside passenger pick-up when off of the BRT-specific corridor and median-side pickup when on the corridor. BRT also has pre-board ticketing, realtime information at stations, and is often connected to secure bicycle facilities that anchor feeder routes into less dense urban areas (ITDP 2012b).
Cities often administrate these services but contract out bus service lines, creating both an important public good and spurring economic growth through private contracts (ITDP 2009). BRT costs vary, but are estimated to be approximately
USD $2 million per kilometer in Indian urban centers, one-seventh the cost of a kilometer of Metro rail track (Siddiqi 2012). The cost of construction and maintenance of BRT systems are lower than the direct and indirect costs of roadways designed for individual motor vehicles. Existing fleets of buses make rapid transit an even more cost-effective strategy for high-density urban areas.
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BRT reduces roadside accidents, pollution, and travel times, and improves urban health and social cohesion (Plotkin 2007, 13). In just seven months of the
Ahmedabad, India BRT opening, 34 percent of commuters had shifted from private vehicles to the public system (ITDP 2012a). A World Bank evaluation of proposed bus-way improvements in Lima, Peru, related 75 percent of the estimated project benefits to commuter time-savings (Cervero 2011, 16). In an appraisal of a proposed BRT in Lagos, Nigeria, the World Bank highlighted the lower cost of access to basic social services, local markets, and jobs for women, the elderly, and the physically challenged (World Bank 2007, 26). Overall, BRT allows for spatial-economic equality, as more low-wage workers can efficiently commute to employment opportunities in the urban center, far from their low-cost homes on the peripheries of cities.
BRT projects in Bogotá, Colombia, Ahmedabad, India, and a number of cities in
China demonstrate additional benefits (Plotkin 2007, 6). BRT was used as a comprehensive effort to improve economic and social conditions. Projects improved informal housing areas, created pedestrian-only zones, increased bicycle infrastructure, and spurred economic activity through formalizing vendors
(Siddiqi 2012). By coupling affordable housing with affordable transport, Bogotá improved access to jobs, services, and commercial centers while reducing the joint costs of housing and transport, which usually account for the majority of the poor’s income (Cervero 2011, 16). The Bogotá BRT also improved class relations by increasing ridership through marketing the service broadly across the socioeconomic spectrum (ITDP 2009).
Additional Considerations
Metro rail systems may be appropriate for extremely high-density urban areas, but are often not as cost-effective as BRT. Many Metro rail systems require commuters to spend valuable time ascending/descending stairs, whereas BRT platforms provide “rail-like level access” on the street level. Additionally, Metro rail projects require expensive infrastructure and present easy opportunities for corruption during contracting (Johnston 2005).
Traffic calming and bicycle infrastructure projects are ideal for almost any urban environment in low-income and low-middle income urban areas. They are inexpensive, easily maintained, and highly effective.
A country’s investment in human capital is an important factor in long-term economic growth and poverty reduction. Education is fundamental for establishing a skilled workforce, which in turn can push the industrial and service sectors to innovate, expand, and fully participate in the globalized economy.
Investments that improve access to health services and health-related outcomes can have a significant positive impact on a country’s economic growth (Grimm
2011, 470). Additionally, the relationship between health and economic growth
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has been shown to be bi-directional. Health boosts economic growth by
“increasing the productivity of workers, by enhancing the acquisition of cognitive skills, and by raising the incentive to accumulate human and physical capital”
(Grimm 2011, 470). In the other direction, strong economic growth and higher incomes contribute positively to health as countries with higher average per capita income can “provide better health technology and supply better and more healthrelated public goods and services” (Grimm 2011, 470).
Decentralization of health care and educational services may provide opportunities for municipal governments to more adequately address local preferences and needs (Matthews et al. 2010, 6). In developing countries with scarce resources for social services, it is particularly important to maximize allocative efficiency by tailoring education and health services to local needs and the local environment. External agencies, national actors, and local actors need to coordinate efforts to identify, develop, design, fund, execute, monitor, and evaluate education and health programs that adequately reflect local preferences and capacities (Freeman and Faure 2003, xxiii). Municipal governments, however, must have sufficient institutional and administrative capacity to effectively deliver education and health services at a local level.
Decentralization with uneven local government capacity is especially complicated in situations where planning and design functions are passed on to municipal actors, or where the locality lacks sufficient funds and costs are transferred from central to local levels (Freeman and Faure 2003, 56). To raise additional local revenue, municipal governments may depend on external grants, transfers from the central government, or approval from the central government to levy additional taxes. For example, the central government of the Philippines transferred responsibilities for health services and primary education to municipal governments, while increasing the financial resources of local governments to meet their increased responsibilities (Moreno and Warah 2006, 171). NGOs can help to bridge the resource gap by delivering primary health care and first referral services in remote areas and urban slums, thus improving access for disadvantaged groups (World Bank 2011c). A downside to decentralization is that inexperienced municipalities may contract out to poor-quality private providers with inadequate capacity to provide services for residents, particularly lowincome residents (Matthews et al. 2010, 6). Additionally, it is often easier and less expensive for central governments to obtain specialized technical knowledge that may be needed in health or education service provision (Faguet 2004, 874).
Next, we discuss specific policy mechanisms designed and/or implemented at a subnational level that can improve health and education outcomes.
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Public-Private Partnerships
Public-private partnerships (PPPs) are agreements between public and private entities to share in the provision of public services that are traditionally provided by the government. This collaboration has the potential to improve the quality and efficiency of service delivery.
PPPs and Education
One response to address the excess demand for basic educational services and the need for higher service quality is increased private sector participation
(Genevois 2008, 6). PPPs can potentially complement and enhance the role of government in educational services and reduce deficiencies in state education programs (Genevois 2008, 5). Businesses, religious institutions, and NGOs have an incentive to participate and work with governments to improve education. The private sector benefits from an educated population because skilled, productive workers are necessary for companies to innovate and grow. The extreme resource constraint of the public sector in developing countries, combined with evidence of positive PPP impacts, have resulted in new private management, financing, and investment in education (Genevois 2008, 5). For example, private institutions have played an important role in education in Indonesia, where Muslim,
Protestant, and Catholic organizations have been prime actors in the provision of educational services (Kristiansen and Pratikno 2006, 514). Although PPPs can add value, they can also be misused if not properly designed and implemented
(Genevois 2008, 12).
PPPs and Health
Private actors and government actors have an incentive to coordinate and utilize each other’s comparative advantage to efficiently address inadequacies in health service provision. For example, Brazil’s decentralized response to HIV/AIDS relied upon coordination with multiple private actors and improved the provision of targeted services to at-risk groups despite the challenges posed by insufficient subnational resources and lack of political will to enact AIDS-related policy
(Gómez 2011, 95; Gómez 2010, 529-530).
Targeted School Fee Reduction
Researchers continue to debate the conditions under which implementation or elimination of fees can increase service utilization and improve health and education outcomes. School user fees may be useful when there are inadequate public resources for education, public expenditure administration and management systems are weak or insufficient, governance problems prevent schools from receiving resources, and government-provided education is poor due to inadequate monitoring (Hillman and Jenkner 2002, 259).
A study by Barrera-Osorio, Linden, and Urquiola investigated the effects of a feereduction initiative called Gratuidad that was introduced by the municipal government of Bogotá, Colombia in 2004. Municipalities manage the public schooling fees in Colombia. The Gratuidad fee-reduction initiative targeted the
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most vulnerable households in Colombia. The program gave fee reductions to children from households in the poorest two categories of a national index. The researchers found that the program increased primary school enrollment for students in the lowest category by three percent and increased high school enrollment for students in the second lowest category by six percent. These positive impacts were even larger among at-risk students and did not demonstrate systematic variation between male and female students (Barrera-Osorio, Linden, and Urquiola 2007).
Conditional Cash Transfer Programs
Conditional cash transfer (CCT) programs work by providing cash payments to poor households that are “contingent upon certain verifiable actions” including school attendance and utilization of basic preventative health care services (De la
Brière and Rawlings 2006, 4). CCTs represent a negative user fee for the recipient, as households are essentially paid to utilize services provided by public institutions, such as schools and hospitals (de Janvry and Sadoulet 2005, 3). As a measure of their success, proponents of CCTs point to the rigorous evaluations and positive outcomes of these programs across a variety of contexts (Adato and
Hoddinott 2007, 300). CCT programs have been successful in increasing a number of school-related outcomes, such as school enrollment, daily attendance, the total number of years in school, and graduation rates (Das, Do, and Özler
2005, 59; Baez and Camacho 2011, 33). Studies have also shown that CCT programs mitigate the effects of economic downturns on low-income populations by keeping students in school when families temporarily lose part of their income
(de Janvry, Finan, and Sadoulet 2004, 18). In addition, CCT programs have increased the use of preventive services and improved nutrition and health, especially for children (Attanasio et al. 2005, 10; Lagarde, Haines, and Palmer
2007, 1900; Rawlings and Rubio 2003, 15).
While administratively efficient, CCTs require high up-front operating costs, with the greatest expense incurred by recipient targeting and conditionality monitoring
(De la Brière and Rawlings 2006, 21). PROGRESA, a well-known CCT program in Mexico, had administrative start-up costs of $1.34 for every dollar spent on actual aid in the first year; however, the same ratio was five cents per dollar of aid after the third year (Adato and Hoddinott 2007, 303). Movements toward decentralization have encouraged many countries to delegate the delivery of
CCTs and other social assistance services to states, provinces, and municipalities
(De la Brière and Rawlings 2006, 16). Central governments, however, contribute to the design of, and funding for, these social programs. In Chile, municipal governments administer Programa Puente (Project Bridge), which targets the
100,000 poorest families in urban areas and provides them with a CCT-related monetary transfer. Additionally a social worker is assigned to assist these families for two years (De la Brière and Rawlings 2006, 14). Municipal governments play important roles in social assistance programs in other Latin American countries as well. The Colombian central government coordinates with municipalities to administer a social assistance program called Famílias en Acción (Families in
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Action). Additionally, Brazilian municipalities were initially responsible for service delivery of a social assistance program called Bolsa-Familia (Family
Allowance).
Technical and Vocational Education and Training
Provision of technical and vocational education and training (TVET) can be a local educational policy tool that contributes to poverty reduction and economic growth by placing an emphasis on curricula that are directly tied to the acquisition of employable skills in the local job market. When TVET upgrades the skills of the local workforce, it helps individuals find employment, adds to overall labor force productivity, and can stimulate national economic development (UNDP
2011, 105). In this way, TVET can fulfill both short-term poverty reduction goals and long-term economic growth goals. TVET can also serve as a useful policy tool for a municipal government to lower urban youth unemployment, which can reduce urban crime levels as discussed in Section I.
Although there have been mixed results of TVET programs in industrialized countries, the returns to training in middle- and low-income countries may be higher because the initial level of technical and vocational skills in the population may be lower and specialized skills are more valuable in the local workforce as they are required for good jobs in the formal sector (Attanasio, Kugler, and
Meghir 2011, 189). A successful urban TVET program, Jóvenes en Acción
(Youth in Action), was introduced in the seven largest cities in Colombia between
2001 and 2005. This program provided six months of training (three months of in-classroom training and three months of on-the-job training) to unemployed men and women between the ages of 18 and 25 that were within the two lowest socioeconomic strata in these cities (Attanasio, Kugler, and Meghir 2011, 189).
The program had significant positive impacts on female participants including an increase of seven percent in the probability of paid employment and an increase of 20 percent in wages (Attanasio, Kugler, and Meghir 2011, 190). The program had differential impacts on female and male participants, as male participants only had significantly positive results related to formal employment. Male participants were five percent more likely to hold a formal job and saw a 23 percent increase in formal wages while female participants were seven percent more likely to hold formal employment and saw a 33 percent increase in their formal wages
(Attanasio, Kugler, and Meghir 2011, 190).
Provision of Iron Supplements and Deworming Drugs in Schools
Children in developing countries have a high incidence of anemia. Iron deficiency anemia harms children by stunting physical growth, impairing cognitive performance, and weakening the immune system (Bobonis, Miguel, and Puri-
Sharma 2006, 692). Horton and Ross (2003) analyzed data from ten developing countries and calculated the median total productivity loss from iron deficiency
(due to motor and mental impairment in children and low work productivity in adults). They found median physical productivity loss to be $2.32 per capital.
When adding cognitive loss due to childhood iron deficiency, the median
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economic loss increased to $16.78 per capita, which represented about four percent of national GDP (Horton and Ross 2003, 71). A project in which iron supplements and deworming drugs were provided to two- to six-year-old preschoolers in the slums in Delhi, India, showed improved health and education outcomes. Children treated by this program have a 69 percent baseline level of anemia and 30 percent suffered from intestinal worm infections (Bobonis, Miguel, and Puri-Sharma 2006, 693). The average preschooler gained 1.1 pounds during the first five months of the project and preschool-participation rates increased by
5.8 percent (Bobonis, Miguel and Puri-Sharma 2006, 693). This increased participation was equated to a reduction of one-fifth in preschool absenteeism in the sample schools. The positive health and educational outcomes of this program were most significant for girls and children from the lowest socioeconomic sections of the population as these are the preschoolers with the highest baseline anemia rates. This type of conclusion supports the argument that an iron supplement and deworming drug provision program can boost school participation by reducing anemia (Bobonis, Miguel, and Puri-Sharma 2006, 693).
Community-Based Health Insurance
In countries with large informal or agricultural sectors, national tax-based and social insurance schemes have limited efficacy, while private or employmentbased schemes may neglect low-income households (Molyneux et al. 2007, 382;
Ensor 1999, 875, 878). When formal sector insurance programs adequately cover only higher income households, there may be opportunities to initiate communitybased health insurance schemes (Molyneux et al. 2007, 392). These communitybased initiatives can improve health service access, affordability, quality, and community participation. Community-based health systems can be established for insurance purposes (whereby the financial risk of health care is shared among a group) and for prepayment schemes (whereby a set of defined, non-transferable health care services is paid for in advance by an individual) (Molyneux et al.
2007, 382).
In Rwanda, members of community-based insurance schemes are the owners, managers, and financiers of the community insurance system. In this system, members pay an annual premium to receive basic health care, such as preventive and curative care, family planning and reproductive health services, maternity care, and drugs free of charge in health centers and district hospitals. An evaluation of Rwanda’s community-based insurance scheme found that insurance members were using health services more frequently (1.5 visits per year) than non-members (0.2 visits per year) (Dmytraczenko, Rao, and Ashford 2003, 2).
Three provinces in Egypt have a similar system whereby “contributions from individuals and employees are combined into social health insurance funds that grant enrollees an essential package of health services... [which] includes child immunizations, reproductive health services, and prevention and treatment of communicable diseases” (Dmytraczenko, Rao, and Ashford 2003, 2). In Bolivia, municipal governments are required to use at least six percent of the funds they receive in transfers from the central government to support a locally-based
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insurance fund. The fund then guarantees some reproductive health services, child health services, and other types of free care for all clients of the insurance fund.
This system has contributed to the increased use and quality of health services
(Dmytraczenko, Rao, and Ashford 2003, 2). It is clear, however, that the Bolivian municipal insurance system could not function without fiscal support from the central government.
Microfinance and Health Education
Although microfinance programs generally focus on microloans 4 aimed at growing small-scale businesses or creating new enterprises, microfinance can serve additional purposes. Some microfinance programs provide health education to loan recipients (Watson and Dunford 2006, 6). Evaluations of microfinance programs with integrated health education elements in Ghana and Bolivia found that program participants had better knowledge of the health topics compared to non-participants (Watson and Dunford 2006, 8). Local governments could recruit microfinance institutions to their municipalities in an effort to reduce poverty through improved health education, female empowerment, and local economic growth. Through these outcome measures, microfinance has been shown to be a viable poverty alleviation strategy at the local level. If microfinance can help women stay healthy, it is more likely that these women can more fully contribute to household well-being and national productivity (UNFPA 2005, ix).
Microfinance programs that provide reproductive health education contribute to family planning efficacy and higher education outcomes among women clients.
Fewer unwanted births also reduce the public expenditure needs for health, education, and social services. When women are uneducated or lack the power to negotiate for safer sex, they have a greater probability of contracting HIV and other sexually transmitted diseases. Lowering the risk of premature death or disability due to HIV/AIDS or complications with pregnancy and childbirth reduces the public expenditure needed to support orphans and destitute families
(UNFPA 2005, x).
Governments, NGOs, and private firms at the federal and subnational level recognize that microfinance is directly related to health and its subsequent spillover effects. Efforts to expand access and uptake of microfinance and financial literacy for women, specifically at the urban level, are important components of most low-income and lower middle-income countries.
The informality of an economy has been cited as a partial explanation for the discrepancy between economic growth and poverty reduction; but, low uptake rates of financial services are even more important (ILO 2002). Most of the
4 Microcredit or microloans are one aspect of microfinance, whereby small loans are provided to typically poor borrowers who lack collateral, steady employment, and credit history.
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“unbanked” (those without formal savings accounts) comprise the majority of the informal economy. Forty percent of Indian adults are unbanked and do not consistently utilize any formal financial institutions or services (Subbarao 2010).
In Zambia and Lesotho, unbanked populations are as high as 60 and 80 percent, respectively (Mwape 2012; CGAP 2009, 59). In addition to savings accounts, life insurance and microcredit are other important financial services accessed by the urban poor at low rates.
The use of financial services can act as an alternative social safety net beyond an extended family or informal insurance pool of community members. Formal financial services generally provide better options than local moneylenders who can charge up to 120 percent per annum (Banerjee 2005, 7). Saving accounts, microcredit, insurance, and other financial services that are properly regulated by the government can also serve as gateways to consistent activity within the formal economy and can help absorb financial shocks, such as death, illness, and economic crisis.
Not all financial services directly reduce poverty or spark economic growth, but they are tools that facilitate more favorable conditions for these two outcomes.
Identified barriers to financial inclusion in urban areas relate to financial illiteracy, income and assets, housing laws, proof of identity, a lack of institutional trust, and gender (Alderman and Paxson 1992). It is important to note that access to services does not guarantee usage. Countries are actively working to integrate their populaces into the formal economy and view financial literacy as a key factor. Increasing the uptake of financial services is a key component of economic growth and poverty reduction (Cohen and Lee 2008, 43).
Credit agencies and consistent business regulations strive to create affordable and competitive environments through market certainty for both consumers and firms.
Parameters for financial services, such as mobile banking, microcredit, savings accounts, and insurance plans, are almost always legislated and enforced by federal authorities. Market certainty increases efficiency, the likelihood of business development and investment, and provides greater risk management for financial service providers. All of these components of financial services are consistent with short- and long-term economic growth. Regulations and credit bureaus, however, are generally orchestrated at a national level, and there are few opportunities for subnational policies beyond basic coordination efforts.
Collaboration and Usage of Pre-Existing Financial Networks
Despite central government dominance of regulation, the promotion and implementation of financial services in urban areas of most low-income and lower middle-income countries is done at both national and subnational levels.
Businesses alone are often ill-prepared to service low-income urban populations
(Baker and McClain 2008). A variety of public and private entities are involved in improving access to affordable financial services. Collaboration between central, subnational, and city governments have enabled pre-existing networks and
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businesses to offer savings accounts and other financial services in urban areas.
In India, post offices, local food shops, and small tobacco vendors have all played important roles in formalizing financial transactions for predominately lowincome laborers in urban areas. Remittance transfers, savings accounts, and even microloans have increased in these newly-formalized financial transaction points.
Although these new spaces for financial services are regulated at the federal level, the bulk of promotion and coordination efforts take place at state and city levels.
Subnational governments have implemented other financial services. In India, the
Common Service Center (CSC) acts as a multiple-services single-point model for a variety of transactions. This federally initiated program evenly splits costs between the central and state governments and reaches both urban and rural populations.
Among other services, many CSCs offer tax and utility payment options, insurance plans, ration cards, and government applications. Responsibilities for CSC operations are divided among the federal, state, and local levels and include partnerships with private firms throughout the country (MCIT 2012, 1).
Life Insurance
The majority of efforts to improve access and uptake of insurance schemes appropriately focus on covering rural farmers from widespread weather-related calamities (Murdoch 2006, 3). Informal insurance schemes in rural areas have proven to be successful in Indonesia when related to shocks at the household level, such as deaths and severe illness (Murdoch 2006). Urban populations, however, cannot form sustainable informal insurance pools like the rural poor.
Community ties are generally weaker in urban areas, with much less asset certainty due to frequent moving within the city.
Significant opportunities exist for subnational governments to assist formal financial institutions, NGOs, and other partners to collaborate in offering life insurance options in urban areas. For one, life insurance has a smaller scope for moral hazard than other types of insurance, such as health and housing
(McKelvey 2012). Additionally, the benefits of providing the poor with life insurance are significant, allowing for a more effective smoothing of consumption in times of financial crisis. The ability of a family to better absorb the death of the breadwinner means that as the productivity of other family members increases, they are able to maintain near normal levels of nutrition and health. Microfinance institutions in India have taken advantage of these opportunities and successfully offered life insurance schemes to low-income populations in urban areas
(Venugopal 2011).
Microcredit
In addition to financing life insurance, health care, housing, and weathering shocks, microcredit is also used for income-generating activities such as education expenses and household assets such as motorbikes. Microcredit has demonstrated positive financial impacts for some borrowers. Business owners who expand operations and others with consistent income-generating activities
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have benefited the most. Few financial models, however, have yet to reach the bottom 20 percent of urbanites in low-income and middle-income countries
(Sriram 2010, 3). Multiple loans taken by customers, faulty incentive structures to loan providers, and uncertain regulations have even increased poverty for some
(Armendáriz and Murdoch 2010). Despite significant challenges, subnational governments continue to work with private firms, NGOs, and other partners to provide access to credit. City governments often collaborate with federal authorities to monitor the implementation of bank regulations requiring increased access to financial services for low-income populations. Orchestrating a comprehensive set of financial services offered through the formal sector, ideally banks, is one of the most important roles for city governments in assisting the poor (UNESOC 2006).
Corruption in governance is wide-reaching and varied, ranging from bribery to election fraud. Evidence suggests that corruption harms economic growth by increasing the costs of doing business and diverting funds away from the government (Mauro 1997). Corruption can also discourage long-term local economic development by making localities unattractive to firms (Chene 2010, 6).
Types of Corruption
For the purposes of this report, we focus on two types of corruption: corruption in bids for public projects and police corruption. We selected these subsets of corruption because they are especially prevalent in urban areas, negatively impact economic development, and preferably are addressed at the local government level (Rinaldi, Purnomo, and Damayanti 2007, 9).
Corruption in Public Auctions
Corruption in public project auctions can be broadly separated into two categories: vertical and horizontal corruption. Vertical corruption describes when bidders and auctioneers form a side agreement, gaining an advantage over other bidders. Horizontal corruption occurs when bidders collude and form a cartel in an attempt to fix prices and undermine other competition. Both types of corruption in public auctions create barriers to entry, undermine allocative efficiency, and discourage honest firms from entering the market (Boehm and
Olaya 2006, 438). Ultimately, the projects become more expensive for municipalities and suffer from reduced quality (World Bank 2011a, 17). Boehm and Olaya (2006, 447) assert that, “due to the very diverse nature of public procurement, ranging from the buying of paper clips to big infrastructure projects, detailed policy guidelines are impossible.” They also argue that the most effective check against corruption is to increase competition by introducing transparency in bidding projects. Increasing transparency in bidding projects also reduces information asymmetries and encourages honest firms to participate
(Transparency International 2003, 4). Another policy solution that can be implemented on a local level is developing accurate cost estimates for projects by
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independent auditors to compare bids against (World Bank 2011a, 26). The U.S.
Department of Transportation recommends that estimates should be within “10 percent of the low bid for at least half of the projects. If this degree of accuracy is not being achieved over ... one year, confidence in the engineer’s estimates may decline” (Government of the United States 2004).
Finally, for municipalities with sufficient financial resources, there is evidence that hiring independent procurement evaluators can reduce collusion. As an example, the World Bank cites the Philippine National Roads Improvement and
Management Project. An independent procurement evaluator was required to develop “specific systems to identify or detect indicators of corrupt practices in the bids, including collusion, price-rigging, fraud, obstruction or coercion”
(Government of the Philippines 2007). While the evaluator could not veto corrupt decisions, his presence and constant communication with the World Bank and other partner organizations discouraged corruption in the bidding and implementation phases (World Bank 2011a, 23).
Corruption in Police Forces
Police corruption is a pervasive problem with a wide range of economic and social implications. It varies from city to city and can include corruption of authority, kickbacks, opportunistic theft, shakedowns, protection of illegal activities, direct criminal activities, and internal payoffs (Barker and Roebuck
1973, 21-36). These activities discourage investment from legitimate firms and increase the cost of conducting business (Chene 2010, 6).
Police reform policies that have been successful include: purging the most corrupt police officers (Varenik 2007, 394); increasing pay (Campbell 2002, 239); improving training (Urbalejo 2003, 39); revising promotion standards (Mohar
2009, 175); increasing oversight (La Rose and Maddan 2009, 337); and creating independent audit agencies (Meagher 2005, 73). While these reforms have been initiated at both the national and subnational levels, and require high levels of coordination, they are often most successful when implemented at a local level.
Local governments can better tailor these reforms to their specific needs where there are higher levels of administrative decentralization.
The first and most intuitive solution to police corruption is to identify and fire any and all of the corrupt police officers. If pursued, this policy requires caution.
Thoroughly corrupt police forces can ill afford to decommission their entire police force and start anew without risking takeover by other powerful actors such as drug cartels. One possible solution is to begin the “purging” process in a piecemeal fashion by picking the most troubled agencies and offsetting the purges to avoid a large blow to the power of the police. These purges can result in potential human rights abuses, which can be safeguarded against if the judiciary can be strengthened and the rule of law preserved (Varenik 2007, 394).
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Another strategy is to improve the quality of the police force, which can be achieved by increasing the pay of all local officers (Campbell 2002, 239) and improving police training and promotion standards. Better training would incorporate a code of ethics, morality, and human rights training along with better tactical training. Improving the quality of police training improves the image and professionalism of the police force and creates a civil service sector “that is made up of honest and efficient police forces who are respectful of human rights”
(Urbalejo 2003, 39). Promotion systems that give more weight to seniority than merit can increase corruption. This issue was a major stumbling block in
Colombia in the 1990s and led to reforms that created multiple career tracks. The creation of multiple career tracks takes advantage of every officer’s talents. A similar reform could be effective in developing countries by giving officers a professional goal that could potentially supersede the temptation to accept bribes
(Mohar 2009, 175).
A final policy solution is to introduce transparency in the police force. Increasing civilian oversight proved successful in Colombia, Hong Kong, and New York.
Greater interaction with the public can enhance the public image of the police in their communities (LaRose and Maddan 2009, 337). An independent audit agency or anti-corruption agency can contribute to better oversight of the policy force
(Varenik 2007, 408). Anti-corruption agencies have been successful in reducing police corruption in Hong Kong and Singapore (Meagher 2005, 73). However, the effectiveness of these programs depends on a strong judiciary, which may not exist in many developing countries.
The policies outlined above are a selection of the most relevant and successful subnational policies we identified from our literature review. The descriptions of policies provide an introduction to a variety of possible subnational policies that can reduce poverty and stimulate economic growth in urban areas.
Of the policies that we discussed, some can be more easily implemented across a wider range of urban contexts, have a more significant rate of success, and are more cost-effective. These policies include investment promotion, participatory slum upgrading, condominial water supply, traffic calming measures, provision of iron supplements and deworming drugs, and police reform. Investment promotion measures, such as providing a stable business climate, providing technical skills to local residents, and facilitating the entry of new firms, are increasingly important as cities compete in the global marketplace for foreign direct investment. Participatory slum upgrading addresses urban service provision and contributes to resident empowerment via active participation and ownership over infrastructure projects that in turn contribute to better management and maintenance of projects.
Condominial water supply contributes to lower connection costs and provides for community maintenance of water and sanitation services, thereby encouraging lowincome residents to invest in these basic services. Traffic calming measures help
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lower the incidence of traffic-related injuries and fatalities, which disproportionately affect the urban poor. Provision of iron supplements and deworming drugs is a relatively inexpensive policy that has been shown to improve both school attendance and other child health outcomes. Police reforms, such as increasing officer pay, can drastically improve the quality of public safety services, which are integral to urban areas, and specifically in low-income neighborhoods.
These policies demonstrate that municipal governments have policy tools available to improve the overall welfare of their cities. Some of these policies focus more heavily on promoting urban economic growth while other policies significantly contribute to urban poverty reduction. In Section III, we address the extent to which indicators are available to effectively measure these policies.
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In this section, we provide a list of databases and city-level indicators that measure a city’s performance across a wide spectrum of issues and policies that can drive economic growth and reduce poverty in low-income and lower middleincome countries. We also rate the ability of each indicator to measure the effectiveness of policies identified in Section II of this report and compare citylevel indicators to current MCC indicators. Sub-section A outlines fiscal decentralization databases, which help determine the feasibility of awarding grants directly to cities. Sub-section B provides an overview of the Global City
Indicator Facility, Sub-section C analyzes the Green City Index, and Sub-section
D evaluates the Doing Business project. In Sub-section E, we introduce additional valuable indicators that lack comprehensive coverage or have irregular data collection. Sub-section F provides a comparison of city-level indicators, MCC indicators, and Section II subnational policies.
MCC cannot effectively award grants to city governments if the city is located in a country that is not sufficiently decentralized in both fiscal and political matters.
In a highly centralized country, a municipal government that receives an MCC grant may have limited authority over implementing new policies and utilizing the grant money for locally designed and/or implemented programs. For this reason, we researched fiscal decentralization indicators that MCC can use to assess the level of fiscal decentralization within a country. Measures of fiscal decentralization are typically defined as the level of local government expenditures expressed as a percentage of national GDP, or as a percentage of total government expenditures (Ebel and Yilmaz 2002, 104). We chose to focus on local government expenditures instead of revenues for two reasons: 1) We were unable to find consistent comprehensive data on local government revenues; and 2) raising consistent tax revenue in developing countries is often difficult with inconsistent impacts for poorer populations compared to expenditures (Bird and
Zolt 2005, 1627). The World Bank’s Decentralization and Subnational Regional
Economics Database and the United Cities and Local Governments Global
Observatory on Local Democracy and Decentralization (UCLG GOLD) Report are two of the better databases for measuring fiscal decentralization.
The World Bank uses the International Monetary Fund’s Government Finance and Statistics (GFS) database to create its indicators, measuring subnational shares of expenditures, and vertical fiscal imbalances to determine a country’s level of fiscal decentralization. The higher the percentage of local expenditures as a share of national expenditures, the more decentralized the country.
The UCLG GOLD Report documents fiscal decentralization in much the same manner as the World Bank. However, it goes one step further and includes local
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investment expenditures as a percentage of GDP and as a percentage of total government expenditure. This indicator measures the local business climate as well as local government finance and provides a proxy for the level of central government involvement in local business. The UCLG GOLD Report also includes measurements of how subnational governments are constructed, such as the various tiers/levels of subnational government within countries (UCLG 2007).
The three levels include an upper tier (state/provincial level), intermediate tier
(district/county level), and lower tier (municipal level) (UCLG 2007).
Both the World Bank and UCLG databases use third-party data that is publicly available to create their indicators. They also have broad country coverage: 149 countries in the World Bank database (35 MCC eligible countries) and 82 countries in the UCLG database (25 MCC eligible countries). The World Bank data, however, have not been updated since 2001 (although the IMF source data used to create the indicators are updated on an annual basis), and the UCLG data have not been updated since 2007. Irregular and infrequent data collection does not allow for an evaluation of year-to-year fluctuations and modifications to the distribution of revenue raising and expenditure responsibilities between national and subnational government entities.
If MCC is considering distributing aid at the subnational level, it would be important to use a national fiscal decentralization indicator in the city selection process. Appendix D provides further discussion of decentralization databases and comparisons to MCC indicators and Section II policies.
Developed in 2008 by the World Bank and UN-HABITAT, the Global City
Indicator Facility (GCIF) is one of the most globally comprehensive databases for city-level measurements and indicators (GCIF 2011, 4). GCIF restricts its analysis and data collection to the world’s 4,000 cities with populations than 100,000 residents (GCIF 2006, 2). Out of the 186 cities participating in GCIF, 73 cities are in 20 different MCC eligible countries.
Indicators
GCIF indicators are organized into 25 themes that measure a range of urban issues and factors of urban life (GCIF 2007). These 25 themes are further divided into three categories of indicators: City Services, Quality of Life, and Profile. City
Services indicators measure the level of services provided by city governments and other entities. Quality of Life indicators measure critical factors of city living that contribute to the overall quality of life, but that are not the direct responsibility of any local service provider (see Table 2 for a list of the indicator themes). Profile indicators measure basic city statistics within five themes: people, housing, the economy, government, and geography and climate. The economy and housing profile indicators are valuable because they provide information on annual average household income, GDP per capita, Gini
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coefficients, total employment, average annual unemployment rate, dwelling density, and persons per dwelling 5 . These are critical factors for assessing cities in low-income and lower middle-income countries . In total, there are 115 GCIF indicators: 33 core, 43 supporting, and 41 profile indicators. All of the cities are expected to report data on an annual basis for all of the core and profile indicators, and they are encouraged, but not expected, to provide data on supporting indicators (GCIF 2008, 31). The core and supporting indicators fall under
GCIF performance indicators whereas profile indicators are basic statistics and background information (GCIF 2007). Figure 2 provides a visual representation of indicator organization. Appendix E provides detailed information on GCIF indicators.
Table 2.
GCIF City Service and Quality of Life Categories
City Service
Themes
Education
Energy
Finance
Fire and emergency response
Governance
Health
Recreation
Quality of Life
Themes
Safety
Solid Waste
Transportation
Water
Wastewater
Civic engagement
Economy
Environment
Shelter
Social equity
Technology and innovation
Source: GCIF 2012b.
5 As discussed in Section I, economic growth is important and a necessary condition for long-term poverty reduction; however, it is important that growth not be offset by a rise in inequality. The
GCIF Gini coefficient indicator appropriately measures changes in inequality that relate to any increases in poverty that may occur from policies increasing economic growth. This is of particular importance when MCC accounts for the opportunity costs of promoting economic growth by funding urban areas. For further information, see “Pro-Poor Growth: Concepts and
Measurement with Country Case Studies” (Kakwani et al. 2004), “The Path Out of Poverty”
(UNDP 2006),” and “New Frontiers in Poverty Measurement” (Foster 2012).
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Figure 2.
Summary of GCIF Categories, Themes, and Indicators
City Services 13 Themes
27 Core
Indicators
31 Supporting
Indicators
Glocal City
Indicators
Quality of
Life
7 Themes
6 Core
Indicators
12 Supporting
Indicators
Profile
Indices
5 Themes 41 Indicators
Source: GCIF 2012.
We limit our discussion to themes and indicators that are directly related to poverty reduction or economic growth and to themes with core indicators.
Indicators that are tangentially related to poverty reduction or economic growth, or indicators we think do a poor job of measuring their theme, are discussed in further detail in Appendix E. We also discuss themes that only have supporting indicators in Appendix E. Supporting indicators have some value; however, as
GCIF does not require cities to report supporting indicators their usefulness is limited.
Methodology
GCIF is constructed through a collaboration between cities and members of the
World Bank, UN-HABITAT, and city focused NGOs (e.g., International Center for Local Environmental Initiatives (ICLEI) and UCLG)) to construct a database and set of indicators that reflects the needs and challenges faced by cities (GCIF
2008, ii). Indicators must be: 1) generally available and current; 2) readily comparable across cities; 3) relevant for decision-making; 4) linked to established goals (e.g., Millennium Development Goals); 5) cost-effective to collect; 6) meaningful to cities across the globe; 7) understandable; and 8) clear as to what a change in the indicator implies. Further, the indicators and the data must be collected, interpreted, and reported in a manner that complies with standards set by the International Organization for Standardization (ISO) (GCIF 2011, 8).
Data for the GCIF indicators are primarily collected from censuses; national household surveys; demographic, health, and living standards surveys; vital statistics registries; administrative and infrastructure data available from public or
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private companies; and specific surveys (GCIF 2006, 11). National censuses provide the most comprehensive datasets but due to their cost they are collected less frequently, ranging from every five to ten years. GCIF’s framework for establishing a compendium of indicators requires that cities actively participate in indicator administration. GCIF also collects city performance data in a standardized format that requires indicators to be relevant worldwide, robust, easy to understand, and self-sustaining (GCIF 2008, 11). Utilizing this framework, the data used to comprise the indicators are screened for their timeliness, comparability, policy-relevance, collection cost-effectiveness, meaningfulness, understandability, and a clear indication of the directionality of the indicator outcomes (GCIF 2008, 14-15).
Merits of GCIF
GCIF indicators meet half of MCC’s indicator requirements. GCIF provides indicators that are comparable across cities, have a clear empirical link to economic growth and poverty reduction, measure factors that governments can influence, and are consistent from year to year (MCC 2011, 13). GCIF is the only comprehensive and standardized database that exists to measure and monitor city performance (Bhada and Hoornweg 2009, 1). It measures indicators ranging from higher education to health care, which all significantly affect a city’s potential for economic growth and poverty reduction. GCIF indicators also measure factors that local governments can influence through policy implementation, such as improvements in transportation, social services, and solid waste. Lastly, GCIF is consistent from year to year, as cities must report annually on all of the core and profile indicators in Performance Statements and Financial Statements (GCIF
2008, 31).
In many cases, GCIF indicators are more specific and targeted than current MCC indicators. GCIF indicators evaluate access to basic needs such as water, shelter, and electricity, as well as services such as transportation and education, which all greatly impact the potential for economic growth (McCarney 2010). Assessing cities at this level of detail and specificity is important because inconsistency in the provision of services and inequality of opportunity often leads to higher income inequality between lower and higher income residents of cities. By providing such a level of specificity, GCIF makes city policymakers aware of such disparities and provides for greater accountability by city policymakers to their residents (Bhada and Hoornweg 2009, 1).
Drawbacks
In evaluating the shortcomings of GCIF, we consider two separate sets of criteria.
First, does GCIF meet the key criteria for a useful global city indicator program?
Second, does GCIF meet current MCC indicator requirements?
A 2006 World Bank report identified the following keys to a successful global indicator program: 1) Sustainable over time; 2) credible and legitimate collection of information; 3) understandable; 4) timely and up-to-date; 5) important and
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relevant indicators; 6) inexpensive; and 7) accessible and easily navigable (World
Bank 2006b, 44).
GCIF meets most of these standards. However, as member cities enter their own data, the credibility of the information could be called into question. Additionally, individual city data are not updated year-to-year or consistent in the time-span.
Lastly, while the database is easily navigable and does not require any special software, not all of the results are accessible to the public. These factors are also problematic under MCC indicator requirements.
First, GCIF uses indicators that are developed by an independent third party; however, cities must enter their own data into the GCIF system. GCIF cautions:
Each member city has discretion for entry of data and descriptive material for their city profile and city data performance measures. The Global City Indicators
Facility is not responsible for the accuracy of this information. However, ISO standardization and thirdparty verification of indicator methodologies is currently being developed (GCIF 2008).
Until GCIF implements quality-controls for the data entry, the information may not meet MCC standards and scrutiny.
Second, GCIF does not have data for all of the eligible cities, nor does all of the current data cover a comprehensive span of time. While cities are being added each week, many cities still have no available data. Additionally, the cities that are most able to collect and report data for indicators are more commonly found in high-income rather than low-income countries (see Appendix F). Cities in countries eligible for MCC grants will likely have less access to resources that allow them to gather and report reliable and consistent data; however, this disadvantage is not specific to GCIF. Any city-level indicator database will find more accessible data for cities in high-income countries.
The third disadvantage of the GCIF database is that the information is not publicly available; much of the data are only available to GCIF member cities.
While MCC will likely be able to gain access to these data, the indicators do not meet the “publicly available” criteria. GCIF intends to make all of its indicators publicly available, but it offers no specifics as to when the data will be released
(GCIF 2008).
While the GCIF database does not meet MCC’s indicator requirements in its current form, the majority of its drawbacks are challenges any city-level indicator program would face in its development stage. GCIF is on track to provide reliable indicators comparable across cities and over time. Although city indicator programs may not be ideal for city-to-country comparisons, many indicators
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that are city specific would provide a good city-to-city comparison. MCC could isolate city-specific indicators and identify the analogous national indicators.
City Services
Indicators that fall within the City Services category measure the level of services provided to city residents by municipal governments and other entities.
6
Health
Core Indicators:
● Number of inpatient hospital beds per 100,000 city residents
● Number of physicians per 100,000 city residents
● Average life expectancy
● Under age five mortality per 1,000 live births
Supporting Indicator:
• Number of nursing and midwifery personnel per 100,000 city residents
Number of Inpatient Hospital Beds per 100,000 City Residents
The purpose of this indicator is to monitor the level of health service delivery, which is an important part of a health care system. According to GCIF, inpatient public hospital bed density is one of the few health-related indicators that can describe hospital capacity and can be collected on a global scale. This measurement accounts for inpatient and maternity beds in public hospitals. Beds in wards that are closed due to lack of health workers are also included in this measurement, which could create inconsistencies in the data as inaccessible hospital beds do not contribute to health delivery for city residents. Another limitation of this indicator is that data collection relies on administrative records reported by public inpatient facilities or censuses of health care facilities; both of which could vary greatly in quality (GCIF 2012a).
Number of Physicians and Nursing and Midwifery Personnel per 100,000 City
Residents
The core indicator for the availability of physicians is a crucial element of the quality of a city’s health care system. The supporting indicator for the number of nursing and midwifery personnel contributes to understanding the level of health service delivery in a city. The number of physicians focuses on generalists in clinics instead of hospitals because the measurement emphasizes the first access point for patients in a city’s health care system. The WHO states that the number of physicians and other healthcare workers in a city is positively associated with immunization coverage, outreach of primary care, and infant, child, and maternal survival (WHO 2006, xv). Cities are expected to submit these data from sources that are updated on a yearly basis. Similar to administrative records, the accuracy
6 Methodology for all of the indicators was accessed through the portal: http://www.cityindicators.org/Reports.aspx. After selecting a city and a theme, click on the
“Generate Report” button and methodology for all of the relevant indicators will be displayed in a
PDF file. The citation “GCIF 2012a” refers to these indicator reports.
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and completeness of different types of human resource data can vary widely between cities (GCIF 2012a).
Average Life Expectancy
This indicator measures the overall mortality level of a city population, which is crucial for determining the size of populations and future population growth, and is closely correlated with local health conditions. This measurement is calculated as the average number of years lived by a group of people born in the same year, under the assumption that overall health and living conditions at the time of their birth were consistent throughout their lives. Average life expectancy measurements signal the potential return on investment in human capital, which could affect the degree of investment in human capital in a city; however, this measurement is more complicated than data collection for other indicators and could be difficult for some cities to supply to GCIF (GCIF 2012a).
Under Age Five Mortality per 1,000 Live Births
This indicator is a leading measure of the level of child health and overall development in cities. Cities are expected to collect this information from vital registration records, national censuses, or household surveys. GCIF states that the best source of data for this indicator is a complete vital statistics registration system that covers a minimum of 90 percent of vital events in a city. This level of record keeping, however, is uncommon in developing countries. For this reason,
GCIF acknowledges that many cities may derive the data for this indicator from sample surveys, which vary greatly in quality, may be conducted every three to five years, and are subject to recall and sampling error (GCIF 2012a). According to UN-HABITAT, child mortality rates are higher in slums than in rural and nonslum urban areas (2006b, 110). Child mortality data could be a somewhat noisy measure of overall urban poverty conditions because slums have the highest child mortality rates while children living in non-slum urban areas have the lowest rates of child morality.
Relation to Section II Health Policies
In Section II, we discussed the importance of access to health care and public health information to economic growth and poverty reduction. If workers are healthy, they are more likely to be productive and able to support their families, directly contributing to economic growth and the reduction of poverty in an urban center. Specific policies from Section II that encourage and lead to better health outcomes include: public-private partnerships (PPPs), provision of iron supplements and deworming drugs, conditional cash transfer (CCT) programs, community-based health insurance, and programs that combine microfinance and health education.
PPPs can address inadequacies in health care service provision and could contribute to improvements in each of the core health GCIF indicators. PPPs could have a greater short-term, direct effect on the number of physicians and hospital beds in a city, whereas the impact of PPPs on the average life expectancy and under age five mortality indicators may be more long-term and indirect. CCT
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programs are a policy tool used to increase the use of preventative health services and improved nutrition and health among city residents, especially children.
Community-based health insurance was discussed as another policy tool to increase utilization of health services. Both CCT programs and community-based health insurance policies are directly related to the average life expectancy and under age five mortality indicators. Lastly, iron supplements and deworming campaigns and the combined microfinance and health education programs could directly improve average life expectancy and under age five mortality indicators.
Education
Core Indicators:
● Student/teacher ratio
● Percentage of students completing primary education
● Percentage of students completing secondary education
Supporting Indicators:
● Percentage of school-aged population enrolled in schools
● Percentage of male school-aged population enrolled in schools
● Percentage female school-aged population enrolled in schools
GCIF states that city data for these education indicators should come from the national education ministry/department. Surveys or national censuses could also be used if the national ministry does not have sufficient data (GCIF 2012a).
Student/Teacher Ratio
GCIF’s indicator for student/teacher ratio is the number of enrolled primary school students (defined as 1st through 5th/6th grade) divided by the number of full-time equivalent primary school classroom teachers. The student/teacher ratio illustrates the adequacy of teacher availability, teacher workload, and the strength and quality of an education system. A low student/teacher ratio indicates that students have access to a greater availability of teacher services and are more likely to have higher educational attainment. This indicator reflects both the cost and quality of a city’s educational system. Two drawbacks of this indicator are that it does not account for private educational facilities, which may play a more important role in the educational system in cities, and it only addresses student/teacher ratios in primary schools, not secondary or higher education facilities (GCIF 2012a).
Primary and Secondary Education Completion
Referred to as the education “survival rate,” this indicator measures “the holding power and internal efficiency of an education system” (GCIF 2012a). GCIF considers the survival rate through fifth grade of primary education particularly crucial because it is considered a prerequisite for sustainable literacy, which affects the quality of a city’s workforce. Cities are expected to provide data on students completing secondary education if available and to clarify if private school data are included in this measure. Cities should also report on survival rates by gender for primary and secondary education if the data are available
(GCIF 2012a).
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School-aged Enrollment in Schools
This indicator is the number of school-aged children enrolled in primary and secondary school divided by the total school-aged population. These data can be further divided into separate gender-specific indicators by using male/female school enrollment numbers divided by the total number of male/female schoolaged population. Primary school does not include kindergarten enrollment, starts between the age of five and seven, and lasts about five years. Secondary school begins around age 10 or 12 and lasts about seven years. The school-aged population is defined as the estimated number of children in a city between ages five and 19. Cities are encouraged to report enrollment in both private and public schools, as private schools may be particularly crucial to a city’s education system. This indicator evaluates the degree of educational opportunity in a city
“by indicating how widespread formal education is in the city among school-age children” and the possible differential in enrollment between males and females
(GCIF 2012a).
Relation to Section II Education Policies
In Section II we discussed subnational policies that can improve educational outcomes in urban areas. PPPs can increase investment in urban education systems. Increased funding for education to hire new teachers and build new school infrastructure can decrease the student/teacher ratio and reduce dropout rates. These potential policy outcomes can thereby directly affect all three GCIF core indicators: student/teacher ratio, percentage of students completing primary education, and percentage of students completing secondary education. CCT policies also directly relate to primary and secondary school completion rate indicators. CCT programs have been found to improve school enrollment, daily attendance, total number of years in school, and graduation rates. Provision of iron supplements and deworming drugs can increase primary and secondary school participation rates, which is related to school completion rates. Targeted school fee reduction policies have also been shown to increase both primary and secondary school enrollment and could also positively affect primary and secondary school completion depending on the initial level of school fees and the initial completion rates. However, cities may not provide school enrollment data to GCIF because the school enrollment indicators are supporting indicators and data provision is optional.
Civic Engagement
Core Indicator:
● Voter participation in municipal elections
Supporting Indicator:
• Number of elected officials per 100,000 city residents
Both indicators are collected and reported by local municipal governing agencies and electoral boards. GCIF indicators provide a solid measure of civic engagement, but measurements for the number of circulated newspapers and types of elections held could give a more complete picture of civic engagement
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and freedom of information. Civic engagement has been demonstrated to have an “especially large statistical effect on perceptions of mutual respect and social cohesion,” while increased “political participation seems to create positive externalities for social capital in ethnically diverse areas,” which can contribute to economic growth and poverty reduction in the long-term (Andrews 2009, 437).
Environment
Core Indicator:
● PM10 concentration (particulate matter that is suspended in the air around cities)
Supporting Indicator:
• Greenhouse gas emissions measured in metric tons per capita (tons/capita)
Particulate matter is generated by the combustion of fossil fuels from cars, factories, and other human activities. Particulate matter has been shown to have adverse effects on respiratory systems and can even cause death. As cities grow, the increase in greenhouse gases emissions induces climate change. Data for both indicators are collected and reported by the International Center for Local
Environmental Initiatives (ICLEI). ICLEI works in partnership with the UN’s
Intergovernmental Panel on Climate Change and the European Union to establish its standards and collection methods. The results from ICLEI are not publicly available. Particulate matter and greenhouse gas emissions negatively affect economic growth and poverty reduction through the health impacts (e.g., respiratory illness and death) that result from higher levels of emissions.
Developing policies that incorporate these concerns into a broader environmental framework will have positive impacts through increased labor productivity and a healthier population (Nemet, Holloway, and Meier 2010, 6).
Solid Waste
Core Indicators:
● Percentage of a city’s waste that is recycled
● Percentage of a city’s population with regular solid waste collection
Supporting Indicators:
● Percentage of solid waste that is openly burned
● Percentage of solid waste that is incinerated
● Percentage of solid waste that is openly dumped
● Percentage of solid waste that is landfilled
● Percentage of solid waste that is disposed by other means
Solid waste treatment and disposal are a critical function of well-run cities, as the effectiveness of solid waste management systems provides a good proxy for the quality of city-level governance (Nzeadibe 2009, 93). Improper disposal can have environmental, health, and economic impacts. All of the solid waste indicators are collected and reported by local municipal bodies, public services, or major contractors. This is a fairly comprehensive set of indicators for solid waste management at the city level. The only measure that is arguably missing is
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whether or not solid waste collection is administered by the local municipality, private contractors, or a PPP. In addition to reducing environmental, health and economic problems, an effective solid waste management system can boost economic growth and reduce poverty by formalizing the existing informal recycling system that is prevalent in many LICs and LMICs.
Water
Core Indicators:
● Proportion of the population that has access to potable water supplies
● Proportion of the population with access to improved water supplies
(piped water, public taps, and boreholes)
● Total domestic water consumption per capita (liters/day)
Supporting Indicators:
● Average annual hours of water service interruption
● Percentage of water loss (leakage) in piped water provision
● Total water consumption per capita (liters/day)
The two indicators for per capita water consumption are slightly different in that the core indicator excludes commercial and industrial consumption, while the supporting indicator includes commercial and industrial water consumption.
The data for these measurements are collected and reported by local municipal agencies, utility providers, and major contractors. However, these indicators do not describe the type of service providers (municipalities, utilities, or PPPs).
Access to clean and potable water is typically associated with healthier populations, which increases productivity, strengthens the economy, and reduces poverty. Policies such as condominial water supply and PPPs are instrumental in addressing the water issues confronting cities.
Wastewater
Core Indicators:
● Percentage of the city population that is served by wastewater collection
● Percentage of city wastewater that receives no treatment
Supporting Indicators:
● Percentage of a city’s wastewater that receives primary treatment
●
(screening)
Percentage of a city’s wastewater that receives secondary treatment
(microbial oxidation)
● Percentage of a city’s wastewater that receives tertiary treatment
(microstraining/filtering)
Wastewater treatment is critical to sustaining environmental quality while preventing the spread of waterborne diseases such as diarrhea and cholera. Data for wastewater are collected and reported by the local municipal agencies, public
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service/utility providers, and major contractors. The wastewater indicators do not identify the service provider.
Access to suitable wastewater treatment positively affects the health of city residents, particularly those residents living in slums. Again, the condominial water supply and PPP involvement can positively affect the percentage of city population served by wastewater collection. Moreover, as mentioned above, wastewater collection and treatment are a part of urban infrastructure, which can function better with the involvement of PPPs.
Electricity
Core Indicators:
●
●
Percentage of city population with authorized electrical service
Total residential electrical use per capita (kWh/capita)
Supporting Indicators:
●
●
Total electrical use per capita (kWh/capita)
Average number of interruptions per year per customer
● Average length of electrical interruption (in hours)
Percentage of City Population with Authorized Electrical Service
This core indicator measures the percentage of city residents with a lawful connection to the electricity supply system. Access to electricity helps raise the educational and productive capabilities of residents (Azoumah et al. 2010, 131).
In addition, it is a contributing indicator of sustainability and health (GCIF
2012a). Moreover, scholars note that electricity obtained illegally is unreliable, expensive, and dangerous for users (Baruah 2010, 1014). Finally, the greater the percentage of a city population with unauthorized access to electricity, the greater are system losses for electricity providers (Sawin and Hughes 2007, 93). Given the complex issues involved in allowing electricity service providers to expand electrical transmission lines to urban informal settlements and convincing lowerincome services to pay for such connections, the involvement of NGOs has been very important. Therefore, we highlighted supporting NGOs as a policy for city governments to pursue. This GCIF measure should allow cities to directly connect support for NGOs involved in this area to the amount to which authorized electrical service has expanded.
Total Residential Electrical Use Per Capita and Total Electrical Use Per Capita
Residential electrical use is a core indicator and measures the total annual residential electrical usage of a city in kilowatt hours divided by the total official population of the city. Total electrical use is a supporting indicator which also includes industrial electrical use. These measures are important because electricity consumption of 1000 kilowatt hours per capita per year is directly associated with
GDP per capita (Nkomo 2007, 13).
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Average Number of Interruptions per Year per Customer and Average Length of Electrical Interruptions (in hours)
These supporting indicators track and benchmark the reliability of electricity services. They are used to determine whether electricity access will actually raise the productivity of people and businesses, as unreliable electricity service hinders business operation.
Finance
Core Indicator:
● Debt service ratio
Supporting Indicators:
●
●
●
Tax collected as percentage of tax billed
Own-source revenue as a percentage of total revenues
Capital spending as a percentage of total expenditures
Debt Service Ratio
The debt service ratio is calculated by dividing total long-term debt servicing costs (including lease payments, temporary financing, and other debt charges) by a municipality’s own source revenue (total revenue less transfers). Similar to other GCIF indicators, the debt service ratio provides little information about a city’s financial situation without additional context. For example, a high debt ratio could indicate financial collapse or an aggressive and quick repayment approach emblematic of a strong economy. Likewise, a low municipal debt service ratio could indicate fiscal weakness or a strong and responsible government (GCIF
2012a). Further measurements are necessary for this indicator to have any real value.
Tax Collected as Percentage of Tax Billed
The GCIF supporting indicator measuring the ratio of collected tax revenue to taxes billed is one of the most important appraisals of a city’s fiscal health. This indicator measures both the working population eligible for tax levies and those who actually paid. The collection of taxes is imperative to sustaining economic growth and reducing poverty in the long-term. The ratio provides MCC with a snapshot of a municipality’s fiscal leverage and efficacy of governance.
Additionally, the supporting indicator measuring capital spending as a percentage of total expenditures, compliments the tax collection ratio, and may reflect a city’s financial capacity to make investments related to growth (GCIF 2012b). Finally, other indicators measuring own-source revenue as a percentage of total revenues, and the percentage of local government revenues originating from fees, charges, and taxes further strengthens the measurement of a municipality’s overall financial well-being.
Drawbacks
GCIF financial indicators provide important information related to the fiscal health of a municipality. They do not, however, provide insight into the access and uptake of financial services. The utilization of financial services can be
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especially important for poor urbanites because few social safety nets exist for impoverished populations to absorb economic shocks (ILO 2002).
Urban Planning
Core Indicator:
● Jobs/housing ratio
Supporting Indicators:
● Areal size of informal settlements as a percent of city area
● Green area (hectares) per 100,000 city residents
Jobs/Housing Ratio
The core indicator measuring jobs/housing ratio defines employment as all types of jobs, including those in retail, industrial, government, and office sectors located within the city boundaries. Housing is defined as all dwelling units available for habitation. The indicator does not take into consideration the informal sector. In some urban areas of low-income countries, significant portions of the economy and the majority of employment opportunities are classified as part of the informal sector. Furthermore, the average number of residents per household varies dramatically across cities. Accordingly, the GCIF is lacking in these two aspects.
Areal Size of Informal Settlements as a Percent of City Area and Green Area
(hectares) per 100,000 City Residents
Despite serious limitations of the core indicator, the two supporting indicators may prove useful in evaluating how urban policies affect specific economic and social outcomes. When both metrics are combined—areal size of informal settlements as a percent of city area and green area (hectares) per 100,000 city residents—MCC will be able to make useful inferences related to a city’s zoning policies, land usage, resident property rights, and overall urban planning sustainability. One drawback to consider is the GCIF recommendation to limit city calculations of all of the informal settlements to those above two square kilometers. This consideration can be problematic with respect to some urban areas where informal settlements are disbursed throughout the entire city, with a small percentage of the total informal housing deriving from massive slums.
A dearth of evidence supports the importance of legal frameworks related to land ownership, distribution, and multi-year urban plans forecasting patterns of growth and efficiency (Saunders 2011). Assuming GCIF’s successful expansion of the urban planning indicators, MCC will have a comprehensive set of data to assess a range of outcomes related to urban planning.
Transportation
Core Indicators:
● Number of kilometers of high capacity public transit system per 100,000
● city residents
Number of kilometers of light passenger transit system per 100,000 city residents
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●
●
Number of personal automobiles per capita
Annual number of public transit trips per capita
Supporting Indicators:
●
●
Number of two-wheel motorized vehicles per capita
Commercial air connectivity (number of nonstop commercial air
● destinations)
Transportation fatalities per 100,000 city residents
At a national level, transportation measurements involve evaluations of multimodal connectivity to neighboring countries and cities within countries, 7 whereas city-level measures should be primarily concerned with a few specific modes of transport within a city. As discussed in Section II, economic growth and poverty reduction related to improved intra-city accessibility through public transportation have been best demonstrated through three policies in a variety of contexts— traffic calming, bicycle infrastructure, and bus rapid transit.
Of all the urban transport policies and available tools for evaluation, GCIF’s supporting transportation indicator—transportation fatalities per 100,000 people—is the most reliable across all urban areas. As discussed in Section II, traffic calming measures have been cited as one of the most cost-effective urban policies, given the low project cost and efficacy in reducing traffic speeds. The relationship between policy implementation and outcome measures is often difficult to prove; however, causality is relatively easy to establish through traffic calming measures and traffic fatalities. Furthermore, given the high incidence of fatalities among the poorest urban commuters, planners are confident to cite poverty reduction as an almost assured outcome from any significant reduction in traffic fatalities (Siddiqi 2012).
Although the transportation fatalities indicator looks promising, in both its accuracy and relevance to outcomes, most of the other GCIF indicators do not. When assessed as individual measurements, most of the other GCIF core indicators are of little value. Informalities of transportation are unaccounted for by GCIF data. GCIF’s personal automobile measure only accounts for registered automobiles, an uncommon legal practice among large percentages of drivers in low-income and lower middle-income countries . GCIF public transportation trips account for neither manually ticketed fares nor informal transport options, both of which are common practices in urban areas of poor countries. Additionally, bicycles are classified as two-wheel motorized vehicles under GCIF definitions,
7 Given the importance of global, regional, and subnational trade and the relationship between shipping infrastructure (roads, rail), urban public transport (accessibility, equity), and economic activity, MCC may want to consider transportation indices at the national level. For example, successful changes to highly inequitable urban public transport in MCC eligible countries such as
Senegal, or poor intra-country infrastructure connectivity such as in Nepal, could be appropriately measured by national level transportation indices.
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thus eliminating any possibility of measuring bicycle usage generated by dedicated cycle infrastructure.
The combination of core measures estimating number of kilometers of high capacity public transport (rail metro and subway) and number of kilometers of light transport (formal bus operations, streetcars, and tramways) can provide important information on a city’s public transportation options. These two metrics, however, demonstrate GCIF’s sole concentration on the supply side of infrastructure. To adequately evaluate transport systems, information is necessary on both the supply and demand side of transportation. For example, although two of the core indicators measure mobility, or the actual physical linkages between spaces, accessibility is the most important component of transport related to sustainable economic growth and poverty reduction (Litman 2012). “Mobility can be misleading because it doesn’t measure how readily people got to where they were going; it just measures how far they were moved” (Walker 2012).
Conversely, accessibility consists of individuals’ ability to freely move around, and it accounts for logistics, pricing, and opportunity costs. In short, mobility is how far you can go in a given time, whereas access is how many useful or valuable things you can do (Litman 2012). Both mobility and accessibility are relevant; however, accessibility is a much more direct and relevant measure of economic growth and poverty reduction.
Finally, price and equity of access, two key variables, are not captured by current
GCIF data. It should also be noted, that GCIF is considering the inclusion of an urban accessibility index. Although aggregate indices have been criticized for their high variability in accuracy (Siddiqi 2012), an urban accessibility index could be the most important measure available for evaluating the success of major public transport projects. For an invaluable guide on evaluating appropriate transportation indicators, see “Transit Oriented Development Performance
Evaluation.” 8
There are a number of international and regional databases that measure a variety of transportation outcomes, however, most data are disbursed among country-led and regional initiatives, or are at the national level. Ongoing efforts are being made to consolidate data across organizations, For additional information on specific databases measuring public transportation outcomes, see the public transportation section in Appendix H.
8
Todd Litman, Executive Director of the Victoria Transport Policy Institute, provides a comprehensive guide for assessing transportation outcomes in “Transit Oriented Development
Performance Evaluation.” The publication can be accessed online at http://www.vtpi.org/tdm/tdm131.htm.
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Quality of Life
Quality of Life indicators measure critical factors of city living that contribute to the overall quality of life, but that are not the direct responsibility of any local service provider.
Economy
Core Indicators:
● City product per capita
● City unemployment rate
Supporting Indicator:
● Percentage of persons in full-time employment
The city product per capita is the gross national product of the city. It is an important indicator of overall economic development. GCIF also considers it as a proxy measurement of the level of investment in the economy, the efficiency of the public and private sector, and employment generation. The GCIF economy indicators depend on the ability of each subnational government to collect accurate market and labor force data at the city level. However, it is difficult to collect accurate market data in low-income and lower middle-income countries given the high prevalence of informal market sectors and the high number of informal laborers that are usually unaccounted for in surveys.
City unemployment, the other core indicator, is measured as the percentage of the labor force actively seeking work that is unable to find a job at a given point in time. The unemployment rate can be one of the most important measures of economic growth and poverty and will provide MCC with a macro-level snapshot of an urban area’s economic strength.
Technology and Innovation
Core Indicator:
● Number of internet connections per 100,000 city residents as a core indicator
Supporting Indicators:
● Number of new patents per 100,000 city residents/corporations per year
●
●
Number of higher education degrees per 100,000 city residents
Number of telephones (landlines and cellular phones) per 100,000 city residents
Number of Internet Connections per 100,000 City Residents
This core indicator measures the level of information access and communication technology connectivity in a city. Studies have demonstrated increased productivity and economic growth as a result of greater diffusion of information technology (IT), including internet access (Wallsten 2005, 501-503). Specifically, IT technologies have been shown to benefit export-oriented firms in Eastern Europe and auto
67

components firms in India. Moreover, IT has been found to stimulate regional economic growth in Taiwan and Bangalore (Wallsten 2005, 501-503).
Number of New Patents Per 100,000 City Residents/Corporations per Year
The number of patents issued to resident individuals or corporations of a city is a supporting indicator of commercial and technological innovation (GCIF 2012a).
As such patents are typically issued by the national government, cities will need to obtain such information from that higher-level government (GCIF 2012a).
Number of Higher Education Degrees per 100,000 City Residents
This supporting indicator helps to determine the skill level of city residents, which can be an important measurement when foreign investors evaluate where they would like to invest (see Section II, Investment Promotion). City governments may expect to see greater interest by foreign investors in their locales assuming more of their residents receive higher education degrees.
Number of Telephones (landlines and cell phones) per 100,000 City Residents
Although landlines and cellular phones may be counted separately, both measures indicate the level of communication technology connectivity within a city (GCIF
2012a). This supporting indicator is important because telecommunications are a major determinant of market development and economic growth, as they function to reduce information asymmetries (Andonova 2006, 29).
Shelter
Core Indicator:
● Percentage of population living in slums
Supporting Indicators:
●
●
Percentage of households that exist without registered legal titles
Number of homeless people per 100,000 city residents
Slums are a universal challenge for all cities in developing countries and must be actively managed by municipal governments. GCIF uses the UN-HABITAT’s definition of slums:
A slum household is a group of individuals living under the same roof in an urban area who lack one or more of the following five conditions:
1) Durable housing; 2) Sufficient living area; 3) Access to improved water; 4)
Access to sanitation; 5) Secure tenure” (UN Human Settlements Programme,
2006). Those living in slums often suffer from compromised health, insecure property rights, and a decrease in educational and employment opportunities as discussed in Section II.
MCC has an indicator for measuring land rights and access; however, it does not address the urban-specific nature of slums and illegal housing developments that plague cities. As slums are endemic to cities and create a wide range of challenges, it is important to include some measurement of their prevalence in cities it evaluates. Section II describes the benefits to cities that accompany adequate property rights and land tenure programs.
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The Green City Index (GCI) is commissioned by Siemens, the German-based multinational corporation, and conducted by the Economist Intelligence Unit
(EIU), an independent research unit within The Economist Group. The GCI is comprised of six regional indices, three of which apply to MCC eligible countries
(Africa, Latin America, and Asia). As of 2011, the three relevant regional indices measure 54 cities in 30 countries and provide indicators in eight categories:
Energy and CO
2
, Land Use and Buildings, Transportation, Waste, Water,
Sanitation, Air Quality, and Environmental Governance. The three publicly available, regional indices provide both qualitative and quantitative city-specific data measures for a total of 37 indicators (see Table 4).
9
The following analysis exclusively considers indicators measuring cities in Latin
America, Africa, and Asia. The African and Asian GCIs were released in late
2011, and the Latin American GCI was released in 2010. Data for the indicators were collected from April 2010 through May 2011, and the majority of data evaluated in all three regional indices are from 2007 to 2010.
Methodology
The GCI is comprised of aggregate scores of all indicators, which GCI plans to collect on an annual or biannual basis. Cities are scored first by category, and then ranked based on their overall scores for all of the indicators and categories.
Category scores are based on a scale of 0 to 100 with each indicator given equal weight. The GCI also gives equal weight to each category, so no one indicator or category dominates a city’s overall score, thus ensuring that all of the measures of a city’s performance are given equal weight (Siemens 2011, 30).
The GCI utilizes both quantitative and qualitative indicators. Quantitative indicators were created using data from national statistics offices, city authorities, local utility service providers, municipal bureaus, and environmental ministries.
Qualitative indicators were evaluated and scored by EIU regional experts based on objective scoring criteria that considered cities’ targets, strategies, and concrete actions (Siemens 2011, 28). All of the qualitative indicators were then re-scored on a scale of 1 to 10, with 10 assigned to cities which met all of the criteria on the given indicator checklist. Once all of the indicators have been measured, the cities receive scores for each category and are ranked on a Likert scale of
: well above average, above average, average, below average, or well below average. The rankings are determined based on how the cities score relative to cities in its evaluated region.
9 Due to the lack of GCI data on European cities located in MCC eligible countries—neither
Tirana, Albania, Chisinau, nor Moldova were included in the most recent GCI—we chose not to analyze the European GCI. Likewise, MCC will also have little interest in the Australia/New
Zealand Green Cities Index, which Siemens plans to publicly release in late 2012 (Stelzner 2012).
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Merits
When only taking gross national income per capita into consideration, nearly half of the total cities measured by the GCI are in low-income or lower middle-income countries. Twenty indicators are collected across all three regional data sets and five of the eight GCI categories have three or more indicators in common. An additional seven indicators are common between the Latin American and Asian cities. A wide range of categories covered in all three GCIs provide MCC with a foundation of measures that capture outcomes related to economic growth and poverty reduction.
In addition to providing one of the most comprehensive and useful sets of indicators measuring urban environmental issues in low-income and lower middle-income countries, the GCI also provides an indispensable analysis of their methodology.
10
Each GCI regional report includes expert analyses from economists, urban planners, and environmental specialists summarizing the results and providing reasoning for each of the 37 indicators.
The methodology of GCIs utilized by analysts provides an additional advantage.
Cities in each regional GCI are compared as a grouping, from which MCC can make regionally-based comparisons. The GCI methodological framework allows for more accurate regional comparisons when compared to other databases, like
GCIF, which provide stand-alone figures or information that are entirely independent from other cities’. Further, EIU analysts are experts on the regions and subjects they evaluate. At its core, the GCI provides a more detailed analysis of cities on a regional basis.
According to Siemens, a second phase of the GCI is in progress. The goal is to update each regional GCI every one to two years; however, this will depend upon funding. Further, any new indicators in the coming years are likely to be focused on additional environmental outcomes (Stelzner 2012). The company’s global leverage in data collection may be on par with that of even the largest international institutions, due to their multi-functionality in a variety of sectors.
Drawbacks
While GCI covers many cities in countries below the GNI MCC eligibility threshold, it does not cover many cities in MCC eligible countries as defined by the fiscal year 2011 Compact and Threshold Countries Report. African GCI assesses 15 cities, with six cities situated in MCC eligible countries. In the Latin
American GCI, 17 cities are assessed; however, only one of them is situated in an
MCC eligible country. The Asian GCI assessed a total of 22 cities, and only two
10 All GCIs can be accessed from this Siemens website: http://www.siemens.com/entry/cc/en/greencityindex.htm.
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of them are in MCC eligible countries. Although GCIs provide a more in-depth evaluation of outcomes on a regional level, the statistical methodology of regional comparisons may not allow for the same degree of accuracy as a cross-regional comparison conducted through GCIF and other databases.
MCC should also note that Siemens’ global reach is through private ventures, and further research is needed to determine the level of neutrality involved in its research targets. For example, although San Salvador is an important city in
Central America, and would ideally be measured by the Latin American GCI,
Siemens may intentionally choose not to collect data for reasons related to a lack of business incentives. Additional conversations with Siemens personnel are required to gauge the impartiality of the project. Although the GCI may be superior to that of the current indicators collected through GCIF, the GCI collection process requires further MCC scrutiny due to Siemens’ explicitly private business interest in the GCI project.
GCI Indicators
Although the GCI includes a total of 37 indicators among the three regional GCIs, and a number of good measures are shared by two out of the three GCIs, the following analysis only considers indicators shared across all three GCIs—Latin
America, Africa, and Asia. Comparisons to MCC indicators and Section II policies can be seen in Table 4.
Energy and CO
2
The Energy and CO
2
category for the Green Cities Index includes the following indicators:
● Energy consumption per unit of GDP
●
●
●
Electricity consumption per unit of GDP
CO
CO
2
2
emissions per capita
emissions from electricity generation per capita
●
●
●
Access to electricity
Clean energy policy
Climate change action plan
The GCI has five quantitative measures and two qualitative measures for evaluating a city’s energy consumption and CO
2
emissions. Energy consumption per unit of GDP and electricity consumption per unit of GDP are measured as the gigajoules (GJ) or megajoules (MJ) consumed per person. CO
2 emissions are measured as the kilograms of CO
2
generated per person. Access to electricity is measured as the percentage of households with access to electricity, with no distinction as to whether or not the connection is legally or illegally obtained. The two qualitative indicators are clean energy policy and climate change action plan.
They measure a city’s efforts to reduce its carbon emissions, and its strategy to combat its contribution to climate change, respectively. These indicators adequately capture energy consumption behaviors and their impacts on a city.
Energy and climate issues increasingly dominate many political and economic
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discussions, and the economic futures of many cities will be directly affected by the energy consumption patterns of industry and individuals. Further, evidence exists that as developing populations approach per capita electricity consumption of 1000 kWh per capita, the returns to human capital increase dramatically
(Benka 2002, 39). The only policy related to electricity consumption that we discussed is the involvement of local NGOs to help provide better service provision.
Land Use and Buildings
The Land Use and Buildings category includes the following indicators:
●
●
Population density
Population living in informal settlements
●
●
Eco buildings policy
Green spaces per capita
● Land use policy
The Land Use and Buildings category is comprised of three quantitative indicators and two qualitative indicators. Overall, GCI’s Land Use and Buildings policies are more related to a city’s environmental sustainability efforts than to economic growth and poverty reduction. The indicator most relevant to economic growth and poverty reduction is the population living in informal settlements.
However, only the GCI Index for African cities includes this indicator; it is not provided for cities in Asia and Latin America. This indicator provides critical information, because populations living in slums often suffer from compromised health, insecure property rights, and a decrease in educational and employment opportunities. Other indicators in this category are more relevant to measuring environmental sustainability efforts, which, although important, are not as closely related to economic growth and poverty reduction. For example, GCI’s land use policy indicator measures a city’s efforts to minimize the environmental and ecological impact of urban development; the eco-buildings indicator measures a city’s efforts to minimize the environmental impact of buildings; and green spaces per capita measures the sum of all public parks, recreation areas, greenways, waterways, and other protected areas per city inhabitant (Siemens 2012). In terms of our Section II policies, those related to secure land tenure, participatory slumupgrading, and housing finance impact the proportion of city residents living in slums.
Transportation
The Transportation category includes the following indicators:
● Public transport network
●
●
●
●
●
Superior public transport network
Length of mass transport network
Urban mass transport policy
Congestion reduction policy
Stock of cars and motorcycles
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Overall, GCI transportation indicators provide a moderately comprehensive assessment of a few crucial policies related to intra-city accessibility. Various indicators capture the length of bus, rail, tram, and subway lines, and the level of traffic congestion in urban areas. One of the most useful GCI transportation indicators evaluates the success of a city’s efforts to implement a mass transportation system as an alternative to private vehicles. It should be noted, however, that since all of the GCI indicators are evaluated on a regional basis, the benchmark for quality depends upon the best mass transit system evaluated, which may not be high in particular GCI regions.
Waste
The Waste category includes the following indicators:
● Waste generated per capita
●
●
●
Share of waste collected and adequately disposed
Waste collection and disposal policy
Waste recycling and re-use policy
The Waste CGI indicators are comprised of two quantitative measures and two qualitative measures. The per capita measure of waste generated is measured as the amount of waste generated (kg) per person, while the share of waste that is adequately disposed of is measured as the overall percentage of waste that is landfilled, incinerated, or recycled at a regulated facility. The qualitative measures for waste collection policy and recycling policy evaluate a city’s efforts to improve and/or sustain its disposal and recycling policies. All of the waste indicators presented by the GCI provide a solid measurement of the policies we have discussed in Section II. In particular they address the volume of waste generated, as well as how it is disposed. They also capture the intended outcomes of formalizing informal sector recyclers and trash collectors.
Water
The Water category includes the following indicators:
●
●
Access to potable water
Water consumption per capita
●
●
Water system leakages
Water quality policy
● Water sustainability policy
The GCI has three quantitative water indicators and two qualitative water indicators. The three quantitative indicators are access to potable water, water consumption per capita, and water system leakages. Access to potable water measures the share of the total population with access to on-site piped water sources, or the close proximity of protected communal sources; water consumption per capita is the total water consumed by the city on a daily basis
(L/person); and water system leakages are measured as the percentage of water lost in transmission between supplier and user, excluding illegally sourced water or on-site leakages. The qualitative indicators, water quality policy and water
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sustainability policy, measure a city’s efforts to improve the quality of its water as well as ensuring the efficient provision its water supply. The Water indicators provide an accurate depiction of the water infrastructure that exists within cities.
In terms of the policies that are pertinent to these indicators the improvement of condominial water supply, PPPs, and decentralized governance of service provision directly tie to these measurements.
Sanitation
The Sanitation category includes the following indicators:
● Population with access to improved sanitation
●
●
Share of wastewater treated
Sanitation policy
Improved sanitation reduces economic losses resulting from sanitation-related illnesses and its associated reduced productivity (Van Minh and Viet Hung 2011,
65). The GCI indicator for population with access to improved sanitation measures the share of the total population with direct connections to sewerage or access to improved on-site sources, such as septic tanks and improved latrines that are not accessible to the public. It excludes open public latrines or sewers and other shared facilities (Siemens 2012). Therefore, while condominial water supply, PPPs, and decentralized governance of service provision are related to this indicator, our subnational policy of communal sanitation would not impact this indicator. Share of wastewater treated measures wastewater collected and treated to a basic or primary level, though the definition of “basic” or “primary” are not provided. This indicator could also be improved through condominial water supply, PPPs, and decentralized governance of service provision. Finally, the qualitative sanitation policy indicator measures a city’s efforts to reduce pollution associated with inadequate sanitation, which is important due to its health impacts. Our Section II policies, however, do not directly address this indicator.
Air Quality
The Air Quality category includes the following indicators:
●
●
●
Nitrogen dioxide (NO
Sulfur dioxide (SO
2
2
) concentration levels
) concentration levels
Suspended particulate matter (PM) concentration levels
● Clean air policy
City air quality is becoming an increasingly important issue particularly in cities in developing countries. Typically, cities in developing countries lack the more sophisticated mitigation and production technologies found in developed countries that can result in lower air quality. Some of these technologies include flue-gas desulfurization for factories and plants, high-efficiency boilers for energy production, and more fuel-efficient vehicles. Further, developing countries are not legally bound to pursue mitigation or air pollution policies under the Kyoto
Protocol in the same fashion as more developed countries. All of these factors contribute to lower levels of air quality around cities, which can have negative
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health impacts. The GCI has three quantitative measures for assessing air quality and one qualitative measure. The three quantitative indicators measure the annual daily mean concentrations for nitrogen dioxide, sulfur dioxide, and particulate matter. These three types of emissions contribute to climate change (NO
2
), acid rain (SO
2
), and respiratory problems (PM). The qualitative indicator, clean air policy, measures a city’s efforts to reduce air pollution through policy initiatives and the incorporation of best practices. Overall, these indicators provide a good measure of efforts to reduce air pollution in cities. Cities alone, however, are not sufficient to enact comprehensive air pollution strategies, as there must be some coordination with central levels of government, and indeed other nations.
Environmental Governance
The Environmental Governance category includes the following indicators:
● Environmental management
●
●
Environmental monitoring
Public participation
Measuring the level of a city’s environmental governance is inherently a qualitative exercise. The GCI use three qualitative measures to assess environmental governance. Environmental governance measures the extensiveness of environmental management undertaken by a city; environmental monitoring measures a city’s efforts to monitor its environmental performance; and public participation measures a city’s efforts to involve the public in environmental decision-making. Evaluating the effectiveness of environmental regimes in cities is difficult, and the GCI is not very specific on what is measured, or how measurements are made, while only asserting that assessments are based on expert opinion. This difficulty invites criticism to this measure as a valid indicator for assessing performance. Furthermore, there are few policies that can be directly tied to these measures other than decentralized service provision of utilities.
The Doing Business database was developed by the International Finance
Corporation of the World Bank Group and launched in 2002. This database provides measures of business regulations and enforcement for small- and medium-sized local firms in 183 countries and selected cities at the subnational and regional level. Countries are ranked from 1 to 183 on the ease of doing business within them. A high ranking indicates that the country has a regulatory environment conducive to starting and operating a new business. The economic index averages the country’s percentile rankings, based on a variety of indicators, giving equal weight to each topic. These measures allow for comparisons and competition between countries toward more efficient regulation and reforms to improve the business climate (IFC and World Bank 2012). Because entrepreneurs consider regulations when determining whether to start a business, the simplicity or complexity of complying with regulations influences their decision.
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Since 2006, the Doing Business database has provided subnational reports. It has evaluated more than 345 cities and several regions, and the database is expanding
(see Appendix G). In each case, the reports produce a ranking showing a specified number of cities in the selected country in terms of the available indicators.
Moreover, the reports summarize the key information available for each indicator and provide a benchmark against the regional average and high-income economies from the Organization for Economic Co-operation and Development.
Indicators
The Doing Business database provides the following quantitative measures or indicators:
● Starting a business:
Identifies the bureaucratic and legal obstacles an entrepreneur has to overcome to incorporate and register a new firm. It
●
● examines the procedures, time, and cost involved in launching a commercial or industrial firm with up to 50 employees and start-up capital of 10 times the economy’s per-capita GNI.
Registering property: Examines the steps, time, and cost involved in registering property, assuming a standardized case of an entrepreneur who wants to purchase land and a building that is already registered and free of title dispute.
Dealing with construction permits:
Tracks the procedures, time, and costs to build a warehouse (including obtaining necessary licenses and permits, completing required notifications and inspections, and making utility
●
●
● connections).
Paying taxes:
Addresses the taxes and mandatory contributions that a medium-sized firm has to pay or withhold in a given year, as well as measures of administrative burden in paying taxes.
Trading across borders:
Looks at the procedural requirements for exporting and importing a standardized cargo of goods. Documents associated with every official procedure are counted—from the contractual agreement between the two parties to the delivery of goods (along with the time necessary for completion).
Enforcing contracts:
Looks at the efficiency of contract enforcement by
●
●
● following the evolution of a sale of goods dispute and tracking the time, cost, and number of procedures involved from the time the plaintiff files the lawsuit until actual payment.
Resolving insolvency: Identifies weaknesses in the existing bankruptcy law and the main procedural and administrative bottlenecks in the bankruptcy process.
Getting credit:
Explores credit information registries and the effectiveness of collateral and bankruptcy laws in facilitating lending.
Getting electricity:
Tracks the procedures, time, and cost required for a business to obtain a permanent electricity connection for a newly constructed warehouse.
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● Protecting investors: Measures the strength of minority shareholder protections against misuse of corporate assets by directors for their personal gain.
Merits
The Doing Business database is developed by the IFC at the World Bank. The database is considered a third-party source that provides transparent information based on facts, laws, regulations, and standardized case studies. The indicators are designed following a methodology that follows-up with local respondents multiple times to ensure accuracy and clarify potential misunderstandings.
Although subnational reports and data are relatively new and do not cover the entire population of cities of all of the countries covered, they can be compared with cities within countries and between regional and international averages.
Doing Business indicators are based on the idea that a vibrant private sector, with firms investing, creating jobs, and improving productivity, promotes economic growth and expands opportunities for the poor (IFC and World Bank 2012). This goal is consistent with the MCC objective of promoting economic growth at the national and subnational level. However, the ease of doing business, based on private perceptions and judgments, also provides information about legislation and regulations that result from public policies. Therefore, some indicators measuring the private sector can partially inform MCC about the public policies that contribute to the ease of doing business in a specific city, region, or country.
The Doing Business database allows us to directly associate these indicators with subnational policies described in Section II of our report, in particular investment promotion policies.
Drawbacks
The Doing Business indicators do not cover a wide range of cities around the world. In some countries, they only focus on the largest cities. Each report varies according to the information available for each country/region. Indicators are limited in scope and only focus on some areas of doing business. This limitation creates inconsistencies when comparing cities, and hinders the ability to relate these indicators to investment promotion policies discussed in Section II.
The Doing Business database only measures the formal economy, with its sole focus on the private sector. Given the importance of informal employment in lowincome and lower middle-income economies, Doing Business indicators does not adequately account for all economic activity. In the absence of information on the informal sector, analyses are limited in understanding policies related to urban economies in low-income and lower middle-income countries. For additional information on future indicators measuring the informal economy and their relation to Doing Business, see the Mobile and Development Intelligence section at the end of Appendix H.
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MCC gathers national level indicators from 14 different institutions. A number of international and regional efforts measure a variety of outcomes; however, most data are disbursed among country-led and regional initiatives or measure nationallevel outcomes. Although the majority of Section III focuses upon two relatively comprehensive databases, we recognize the importance of discussing additional organizations that measure a smaller set of categories or even a single indicator.
Appendix H discusses: U.N. Habitat Urban Development Index; urban governance databases; transportation databases; financial services databases; and national-level urban databases.
After careful evaluation of all of the relevant indicators and policies, we constructed a table to assess how our policies and indicators compare. We evaluated our comparisons based on how well city-level indicators fit with current
MCC categories and indicators. We also explain how city-level indicators capture important outcomes of policies discussed in Section II. We stratified and scored these comparisons on a “good,” “fair,” or “poor” scale. A “good” score was given if there was an equivalent MCC indicator and/or a close correlation between a subnational policy and an indicator measurement. A “fair” score was given if there was an approximate MCC indicator and/or a moderate correlation between the subnational policy and the indicator measurement. A “poor” score was given if there was no equivalent MCC indicator and/or little relationship between the subnational policy and the indicator measurement. Indicators that had no corresponding or related subnational policy received a score of “N/A.” In Tables
3, 4, and 5, we compare GCIF core indicators, Green City Index, and Doing
Business indicators, respectively, with MCC indicators and Section II policies.
Appendix H contains the comparisons table for other databases discussed.
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Table 3.
Comparison of GCIF with MCC Indicators and Section II Policies
GCIF Indicator Fit with MCC Indicator
Policies and
Correlation with Policy
Outcome
Voter participation
PM10 concentration
Civic Engagement
Voice and accountability
(good)
Environment
Natural resource management; natural resource protection
(fair)
Water
Natural resource management; child health; government effectiveness (good)
N/A
N/A
Condominial water supply (good)
Percentage of population with potable water
Percentage of population with improved water source (piped)
Total domestic water consumption
Regulatory quality (fair)
Natural resource management; child health; government effectiveness (good)
Regulatory quality (fair)
Natural resource management
(fair)
Regulatory quality (fair)
PPPs (fair)
Condominial water supply (good)
PPPs (fair)
Condominial water supply (fair)
PPPs (fair)
Percentage of city served by wastewater collection
Wastewater
Natural resource management
(good); government effectiveness (fair)
Regulatory quality (fair)
Condominial water supply (good)
PPPs (fair)
Percentage of wastewater that receives no treatment
Natural resource management; child health (good)
N/A
Solid Waste
Percentage of city waste that is recycled
Natural resource management
(good)
Incorporate informal sector recyclers into formal solid waste management system
(good)
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GCIF Indicator
Percentage of city with regular solid waste collection
Fit with MCC Indicator
Natural resource management
(good)
Policies and
Correlation with Policy
Outcome
Incorporate informal sector recyclers into formal solid waste management system
(fair)
Electricity
Percentage of population with authorized electrical service
Total residential electrical use per capita
(kWh per capita)
Investing in people (poor)
Investing in people (poor)
Technology and Innovation
Number of internet connections per
100,000 city residents
Telecommunications
(landlines and mobile phones)
Number of higher education degrees per city residents
Investing in people (poor)
Investing in people (poor)
Investing in people (poor)
City product per capita
City unemployment rate
Economy
N/A
N/A
Health
Number of in-patient hospital beds per
100,000 city residents
Number of physicians per
100,000 city residents
Public expenditure on health
(poor)
Public expenditure on health
(good)
Support for NGOs
(good)
Support for NGOs
(good)
N/A
N/A
FDI attraction (good)
Economic policies
(good)
Economic policies
(good)
PPPs (fair)
PPPs (fair)
80

GCIF Indicator
Average life expectancy
Under age five mortality per 1,000 live births
Fit with MCC Indicator
Child health, immunization rates (fair)
Child health, immunization rates (good)
Policies and
Correlation with Policy
Outcome
PPPs (fair); communitybased health insurance
(good); conditional cash transfer programs (fair); microfinance and health education (good); communal sanitation provision (good); municipal solid waste management systems
(good)
PPPs (fair); communitybased health insurance
(good); conditional cash transfer programs
(good); microfinance and health education (good); iron supplements and deworming drugs
(good); communal sanitation provision
(good); municipal solid waste management systems (good)
Student/teacher ratio
Percentage of students completing primary education
Percentage of students completing secondary education
Education
Public expenditure on primary education (good)
Girls primary education completion; girls secondary education enrollment public expenditure on primary education (fair)
Girls primary education completion; girls secondary education enrollment (fair)
PPPs (fair)
PPPs (fair); targeted school fee reduction
(good); conditional cash transfer program (good); iron supplements and deworming drugs (good)
PPPs (fair); targeted school fee reduction
(good); conditional cash transfer program (good); iron supplements and deworming drugs (fair)
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GCIF Indicator Fit with MCC Indicator
Policies and
Correlation with Policy
Outcome
Transportation
Number of kilometers of high capacity public transit system per
100,000 city residents
Number of kilometers of light passenger transit system per 100,000 city residents
Number of personal automobiles per capita
N/A
N/A
Rapid bus transit (fair); bicycle infrastructure
(poor)
Rapid bus transit (poor); bicycle infrastructure
(poor)
Number of public transit trips per capita
N/A
N/A
Rapid bus transit (fair); bicycle infrastructure
(fair); traffic calming measures (fair)
Rapid bus transit (good); bicycle infrastructure
(good); traffic calming measures (fair)
Finance
Tax collected as percentage of tax billed
Fiscal policy (fair) Property taxes (fair)
Shelter
Percentage of city population living in slums
Land rights and access (fair)
Property rights and land tenure (good)
Urban Planning
Jobs/housing ratio Land rights and access (fair)
Land tenure (fair); property rights (fair); housing finance (fair); participatory slum upgrading (good); vocational and technical education/training (good)
Source: GCIF 2012a.
82

Table 4.
Comparison of Green Cities Index with MCC Indicators and Section II Policies
GCI Indicator Fit with MCC Indicator
Policies and Correlation with Policy Outcome
Energy and CO
2
Access to electricity Regulator quality (poor) Support for NGOs (good)
Electricity consumption per capita
Climate change action plan
Clean energy policy
CO
2
emissions per capita
CO
2 emissions from electricity consumption per capita
Energy consumption per unit of GDP
Population density
Population living in informal settlements
Eco buildings policy
Investing in people
(poor)
Natural resource protection (good)
Natural resource protection (good)
Natural resource protection (good)
Natural resource protection (good)
Support for NGOs (good)
N/A
N/A
N/A
N/A
Investing in people
(poor)
Support for NGOs (good)
Land Use and Buildings
Land rights and access indicator (poor)
Property rights and land tenure (good); participatory slum upgrading (good); housing finance (poor)
Land rights and access indicator (good)
Property rights and land tenure (good); participatory slum upgrading (fair); housing finance (fair)
Natural resource protection (poor)
Condominial water supply
(fair); governance of service delivery (fair); incorporate informal sector recyclers into formal solid waste management system (fair)
Green spaces per capita
N/A Reducing corruption (poor)
83

GCI Indicator
Land use policy
Public transport network
Superior public transport network
Length of mass transport network
Urban mass transport policy
Congestion reduction policy
Stock of cars and motorcycles
Waste generated per capita
Share of waste collected and adequately disposed
Fit with MCC Indicator
Natural resource protection (fair)
Policies and Correlation with Policy Outcome
Property rights and land tenure (poor); bus rapid transit bicycle infrastructure
(fair); traffic calming (poor); governance of service delivery (fair); condominial water supply (fair); incorporate informal sector recyclers into formal solid waste management
system (fair)
Transportation
N/A Bus rapid transit (good)
N/A
N/A
Bus rapid transit (fair); bicycle infrastructure (poor); traffic calming (poor)
Bus rapid transit (fair)
N/A
N/A
N/A
Bus rapid transit (good); bicycle infrastructure (good); traffic calming (good)
Bus rapid transit (good); bicycle infrastructure (good); traffic calming (good)
Bus rapid transit (fair); bicycle infrastructure (fair); traffic calming (fair)
Waste
Natural resource management (good)
Natural resource management (good)
Incorporate informal sector recyclers into formal solid waste management system (poor)
Incorporate informal sector recyclers into formal solid waste management system
(good)
84

GCI Indicator
Waste collection and disposal policy
Fit with MCC Indicator
Natural resource management (good)
Policies and Correlation with Policy Outcome
Incorporate informal sector recyclers into formal solid waste management system
(good)
Waste recycling and re-use policy
Natural resource management (good)
Incorporate informal sector recyclers into formal solid waste management system
(good)
Access to potable water
Water
Natural resource management (good); child health (good)
Condominial water supply
(good); PPPs (fair)
Water consumption per capita
Natural resource management (fair)
Condominial water supply
(fair); PPPs (fair)
Water system leakages
Natural resource management (good); regulatory quality (fair)
Condominial water supply
(good); PPPs (fair)
Water quality policy
Natural resource management (good); regulatory quality (good)
Condominial water supply
(good); PPPs (good)
Water sustainability policy
Natural resource management (good); regulatory quality (good)
Sanitation
Condominial water supply
(good); PPPs (good)
Population with access to improved sanitation
Child health indicator
(good)
Communal sanitation provision (poor); condominial water supply
(good); PPPs (fair)
85

GCI Indicator
Share of wastewater treated
Fit with MCC Indicator
Policies and Correlation with Policy Outcome
Child health indicator
(fair)
Condominial water supply
(good); PPPs (fair)
Sanitation policy
Child health indicator
(good)
Communal sanitation provision (fair); condominial water supply (good); PPPs
(fair)
Nitrogen dioxide concentration levels
Sulfur dioxide concentration levels
Suspended particulate matter concentration levels
Clean air policy
Environmental management
Environmental monitoring
Public participation
Air Quality
Natural resource protection (good)
Natural resource protection (good)
Natural resource protection (good)
Natural resource protection; regulatory quality (good)
Environmental Governance
Regulatory quality (poor)
Regulatory quality (poor)
Voice and accountability
(poor)
Source: Siemens 2011.
N/A
N/A
N/A
N/A
N/A
N/A
N/A
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Table 5.
Comparison of Doing Business with MCC Indicators and Section II Policies
Doing Business
Indicator
Fit with MCC Indicator
Policies and Correlation with Policy Outcome
Starting a business Business start-up (good) Investment promotion (good)
Registering property Regulatory quality (good) Investment promotion (good)
Dealing with construction permits
Paying taxes
Regulatory quality (good) Investment promotion (good)
Regulatory quality (good) Investment promotion (good)
Trading across borders Regulatory quality (good) Investment promotion (good)
Enforcing contracts
Resolving insolvency
Getting credit
Getting electricity
Protecting investors
Rule of law (good)
N/A
Investment promotion (good)
Investment promotion (fair)
Access to credit (good) Investment promotion (good)
N/A Investment promotion (good)
N/A
Investment promotion
(good); reducing corruption
(good)
Source: ICF and World Bank 2012.
87

The Millennium Challenge Corporation (MCC) should consider awarding grants to cities in low-income countries (LICs) and lower middle-income countries
(LMICs) once existing databases and indicators are further developed to permit comprehensive city-level and cross-city evaluations. Urban areas will play an increasingly important role in the national economic development of LICs and
LMICs due to increasing urbanization. Cities are, and will continue to be, the drivers of economic growth. Moreover, most of the world’s urban population growth will occur in developing countries over the next 15 years. This demographic trend will place an increased strain on the already inadequate levels of municipal service provision in cities in LICs and LMICs. Worldwide urban poverty is already increasing at a faster rate than rural poverty. Without municipal policies that improve service provision and infrastructure to manage population growth, cities risk increasing poverty, thereby hindering the potential for sustainable economic growth.
MCC should also consider the trade-offs entailed by providing city-level funding.
Grants focused on the city level may directly impact funding for national-level policies focused on rural areas of LICs and LMICs, which tend to have higher absolute poverty rates and stagnant economic growth. Data on remittances could partially measure the economic spillovers to rural areas from urban-based economic growth and poverty reduction. However, additional non-income based opportunity costs should also be considered. For example, national-level policies related to social and environmental outcomes may be neglected at the cost of focusing funds at the city level.
A more precise specification of MCC goals could provide important direction for its selection process of useful indicators. Preferences for various types of poverty reduction and economic growth may change MCC’s desired subnational policy outcomes and the corresponding indicators used to measure these goals.
Regardless of the assessment outcome, MCC would benefit from defining its preferences for poverty reduction among three general levels: those living well below the poverty line, those living just below the poverty line, and those just above it. MCC could then prioritize funding and city comparisons accordingly.
Similarly, MCC would gain from delineating preferences among economic growth outcomes. For example, policies biased toward strong economic growth in the short term could have drastically different outcomes from policies promoting long term and sustainable growth.
In this report, we highlighted policies with the potential to positively affect welfare outcomes for poor urban populations. Some of these policies demonstrate positive impacts on economic growth, poverty reduction, or both across many different cities. However, we note that policy success is almost always dependent on effective implementation and other contextual factors. The relationship between national and subnational governments and the level and type of
88

decentralization are important components of city-level policy success. Valuable and sustainable policies also involve genuine and equitable local input to reflect the needs of relevant communities. Of all the policies that we identify in this report, six stand out as being effective across urban environments in LICs and
LMICs: investment promotion, participatory slum upgrading, condominial water supply, traffic calming measures, provision of iron supplements and deworming drugs, and police reform.
From our review of nearly 200 city-level indicators, we compiled a compendium of indicators to help MCC evaluate the effectiveness of city-level policies. In our analysis, we recommended three databases that meet many of MCC’s indicator selection criteria. The comprehensive nature of the Global City Indicator Facility
(GCIF) and Green City Index (GCI) provide the best starting point for MCC’s consideration of urban-level indicators. They are the most viable, large datasets available for eventual use. The Doing Business database also provides useful indicators, specifically related to investment promotion. Table 6 summarizes the status of indicators in these databases in terms of MCC indicator preferences.
Table 6.
Evaluation of MCC Indicator Preferences with City-Level Databases
MCC Indicator Preferences GCIF GCI
Doing
Business
Developed by independent third party Good Fair Good
Analytically rigorous methodology and objective, and high-quality data
Good Good Good
Publicly available Poor Good Good
Broad city coverage Good Fair Fair
Comparability across cities Good Fair Fair
Linkage—theoretically or empirically—to economic growth and poverty reduction
Good Good Good
Linkage to policies that city governments can influence within two-three years
Good Good Good
Consistency in results from year to year
Source: Authors.
Good Fair Poor
89

The GCIF includes the most extensive set of city-level indicators across urban issue areas. All of the data are annually collected from reputable third-party sources such as the World Bank and UN-HABITAT. Of the 186 cites uniformly measured by 33 core GCIF indicators, 73 are in MCC eligible countries, and the number of participating cities and indicators continues to grow (see Appendix E for Future Indicators). Although all GCIF indicators are measured at the individual city level, some indicators are sourced from databases that capture national-level outcomes as well, which may allow MCC to make city-country comparisons.
A few challenges prevent MCC from considering immediate use of GCIF data for evaluating cities. First, GCIF data are not publicly available; GCIF personnel informed us that GCIF will publicly release all data in the near future, but the current inaccessibility to GCIF data prevents us from verifying its quality.
Second, local capacity constraints of cities in LICs and LMICs prevent most institutions that source GCIF data from consistent collection efforts at the city level. Third, even if we assume that GCIF publicly releases data in the near future, consistent data collection across hundreds of urban areas in LICs and
LMICs is only likely to occur within the next five years. If GCIF is able to annually collect data for its 33 core indicators across a larger number of participating cities and it releases all information to the public, MCC may be able to use many GCIF indicators within one to two years. Under the current circumstances, we recommend MCC consider the use of GCIF indicators and contact GCIF personnel about a likely timeframe for public release of the data.
The GCI provides detailed indicators for a number of social and environmental issues that impact economic growth and poverty reduction. Its 20 indicators uniformly measure data for selected cities, are publicly available, and analytically rigorous. However, only 22 of its 54 cities are in MCC eligible countries, and data collection is only tentatively scheduled to begin in the next year or two. Further, evaluations of cities are only comparable within the three regions of Latin
America, Africa, and Asia. Although MCC’s use of GCI indicators to evaluate cities for grants in the near future is highly unlikely due to CGI’s minimal city coverage and provisional future data collection, it does provide useful information. We recommend MCC examine GCI indicators’ unique 5-level Likert scale evaluation process and GCI’s intra-regional city-comparisons to learn about its innovative methods of city assessments and comparisons.
The Doing Business database ranks business regulations of small- and mediumsized local firms at the national and subnational level. Its third-party sourced data are captured through publicly available indicators at both the city and national level, and the database has already been used by MCC. Although these indicators are closely correlated to the presence of business-related policies, the Doing
Business city-level indicators are not available for a wide range of cities around the world, and only cover some areas of the business environment. In addition,
Doing Business only gathers information related to the formal private sector,
90

which is a significant drawback for assessing the many urban areas in LICs and
LMICs with high levels of informal economic activity. Doing Business indicators will be more useful once the database has better city coverage and complementary informal sector indicators become available through the Doing Business database or another database.
MCC draws on 14 different organizations to create the 17 indicators used for country selection. In addition to the GCIF, GCI, and Doing Business indicators, we noted other “partial” or single-issue databases in our report. We recommend the World Bank/IMF Government Finance Statistics database and the United
Cities and Local Government’s GOLD Report for measuring fiscal decentralization. We also evaluated several other databases in the appendices of our report; these can be used as supplements to the databases discussed in greater detail. These databases address issues of good governance, urban development, transportation, multidimensional poverty, and mobile finance. We did not include them in the body of the report due to their lack of city or issue coverage, timeliness of data, or public availability. Finally, indicators that measure citylevel corruption, environmental outcomes, and facets of informal economies are not appropriately measured by indicators, do not exist, or lack significant citylevel coverage.
The databases we identify in this report provide comprehensive city-level indicators that measure a variety of policies and urban conditions relating to economic growth and poverty reduction. Despite the sizable number of indicators we discovered, available city-level data still falls short of MCC preferences and requirements when compared to existing country-level indicators. We expect that ideal city-level data for measuring MCC grant applicants are likely to be available within the next five years, although the identified databases serve as adequate foundations for further data consolidation and uniformity. Increased data collection initiated by international institutions and governments in LICs and
LMICs at both the national and subnational level will allow for significantly greater performance assessments of urban outcomes. Overall, there is potential for
MCC to consider giving aid to cities within the next five years, however, more work must be done to develop a reliable set of indicators for evaluating cities and their policies.
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Appendix A presents information on population trends and urban growth rates at the global and regional level. Figure A1 shows the global projections of total population, total rural population, and total urban population from the year 2000 up the year 2030. Table A1 presents the proportion of the world population living in urban areas and urban population percentages by region from 1950 to 2030.
Similarly, Table A2 presents the average annual rate of change of the global urban population and the rate of change of the urban population by geographic region, from 1950 to 2030.
Figure A1.
Population Estimates: Total, Rural, and Urban, 2000-2030
9,000
8,000
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
2000 2010 2020 2030
Urban
Year
Rural Total
Source: UN-HABITAT 2009
.
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Table A1.
Urban Population Percentages by Geographic Region, 1950-2050
(Percentages)
1950 1970 1980 1990 2000 2010 2020 2030 2040 2050
World
More developed regions
Less developed regions
28.8
36.1
38.9
42.6
46.4
50.5
54.4
59.0
63.9
68.7
52.6
64.7
68.3
70.8
72.7
75.2
77.9
80.9
83.7
86.2
17.6
25.3
29.4
34.8
40.0
45.1
49.8
55.0
60.5
65.9
Less developed regions, excluding China 20.2
28.7
33.5
37.9
41.4
44.4
48.2
53.1
58.6
64.2
Sub-Saharan Africa
Africa
Asia
Europe
Northern America
Oceania
Latin America and the Caribbean
11.0
19.5
23.9
28.3
32.7
37.2
42.2
47.9
54.0
60.1
14.4
23.6
27.9
32.1
36.0
40.0
44.6
49.9
55.7
61.6
16.3
22.7
26.3
31.5
36.8
42.2
47.2
52.8
58.8
64.7
51.3
62.8
67.3
69.8
70.8
72.8
75.4
78.4
81.5
84.3
41.4
57.1
64.3
70.3
75.5
79.6
82.6
84.9
86.9
88.8
63.9
73.8
73.9
75.4
79.1
82.1
84.6
86.7
88.5
90.1
62.0
70.8
71.4
70.7
70.4
70.2
70.4
71.4
72.8
74.8
Source: DESA 2011.
Table A2.
Average Annual Rate of Change of the Urban Population by Geographic Region, 1950-2050
(Percentages)
World
More developed regions
Less developed regions
Less developed regions, excluding China
Sub-Saharan Africa
Africa
Asia
Europe
Latin America and the Caribbean
Northern America
Oceania
1950-
1955
4.9
4.6
3.9
2.1
3.1
2.3
4.2
3.9
4.5
2.7
2.9
196519751985-
1970 1980 1990
5.1
4.7
3.3
1.6
2.7
1.8
3.6
4.1
2.7
1.1
3.9
4.0
4.8
4.5
3.7
1.1
3.9
1.6
3.4
1.0
2.8
1.4
2.6
1.4
1.6
Source: DESA 2011.
4.5
4.1
3.6
0.7
2.6
1.0
3.6
3.4
199520052015202520352045-
2000 2010 2020 2030 2040 2050
2.2
1.9
1.8
1.5
1.3
1.1
0.6
0.7
0.6
0.4
0.3
0.2
3.0
2.4
2.1
1.8
1.6
1.2
2.7
2.3
2.2
2.0
1.8
1.5
3.9
3.7
3.4
3.1
2.7
2.3
3.4
3.4
3.1
2.8
2.5
2.1
2.9
2.3
2.0
1.7
1.4
1.1
0.1
0.4
0.3
0.2
0.2
0.1
2.2
1.6
1.2
0.9
0.6
0.3
1.7
1.3
1.1
0.9
0.7
0.5
1.4
1.3
1.2
1.1
1.0
0.9
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It is difficult to define the term “urban area” because there are no set standards for terminology, geographical boundaries, or absolute numbers. The United Nations
Human Settlements Program (UN-HABITAT) defines a metropolitan area as “the set of formal local government areas which are normally taken to comprise the urban area as a whole and its primary commuter areas” (UN-HABITAT 2009).
Alternatively, DESA defines a metropolitan area as “both the contiguous territory inhabited at urban levels of residential density and additional surrounding areas of lower settlement density that are also under the direct influence of the city”
(DESA 2011). The United States Census defines an urban area as “a densely settled core of census tracts and/or census blocks that meet minimum population density requirements, along with adjacent territory containing non-residential urban land uses as well as territory with low population density included to link outlying densely settled territory with the densely settled core” (U.S. Census
Bureau 2012).
In terms of absolute numbers, the U.S. Census holds that a population of 2,500 residents or more constitutes an urban area (2012). International urban area limits depend on the country and range from 200 residents (Iceland) to 10,000 residents
(Italy) (FAO 2012). The difficulty in defining an urban area has led the World
Bank to adopt DESA’s definition of urban area (World Bank 2008, 133). The term “urban agglomeration” has been used as a substitute for urban area, but its parameters are inconsistent. UN-HABITAT defines urban agglomeration as “a city or town proper and the suburban fringe or thickly settled territory lying outside, but adjacent to, its boundaries” while DESA’s definition is “the de facto population contained within the contours of a contiguous territory inhabited at urban density levels without regard to administrative boundaries” (UN-HABITAT
2009, 4; DESA 2011). No urban area definition is wholly consistent with the others, which is why we are using this definition of urban area in our report:
1. A locally delineated agglomeration of people with both formal and informal boundaries that has population densities consistent with national standards, and
2. an agglomeration that is legally administered by a local government, governing body, or council, and
3. an agglomeration of at least 2,500 people that satisfies conditions 1 and 2.
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Table C1 displays an evaluation of emerging urban health issues by the category of health burden and several key features of urban growth. Table C2 provides a list of urban health risks organized by communicable diseases, non-communicable diseases, and other public health concerns.
Table C1.
Emerging Urban Health Issues: Notional Variation with Urban Development
Problem Type
Variable with
Urban
Growth
Changes with
Spread in City
Growth
Risk for the
Poor
Variable with Age and Gender
Communicable diseases
Traffic injuries High Somewhat High High
Violence Somewhat Somewhat High High
Obesity Somewhat Low High High
Unsafe settlements
Source: Campbell and Campbell 2007, 157.
Note: Rows represent categories of health burden and the columns represent key features of future urban growth.
Table C2.
Urban Health Risks
Communicable Diseases
HIV/AIDS and other sexuallytransmitted diseases
Vector-born diseases (malaria, dengue, yellow fever, etc.)
Typhoid fever
Influenza (including H5N1)
Non-Communicable
Diseases
Other Public Health
Concerns
Effects of drug/alcohol dependence
Chronic respiratory diseases
Cancer
Motor vehicle-related deaths/injuries
Homicide, domestic violence, other violent crime
Limited food choices, malnutrition
Chronic heart disease Unsafe living conditions
Tuberculosis Stroke pollution
Diarrhea diseases (such as cholera)
Pneumonia
Hypertension
Mental health problems
High maternal mortality
Low vaccination rates
Viral hepatitis Diabetes Urban heat island effect
Obesity
Source: Authors.
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Table D1 compares Global Observatory on Local Democracy and
Decentralization database indicators with MCC indicators and Section II policies.
Table D2 compares World Bank’s Decentralization and Subnational Regional
Economics database indicators with MCC indicators and Section II policies.
Table D1.
Global Observatory on Local Democracy and Decentralization Database
Comparison
Indicator Fit with MCC Indicator
Policies and
Correlation with
Policy Outcome
Fiscal decentralization-local expenditures
(percent of GDP)
Fiscal decentralization- local expenditures
(percent of government expenditures)
Fiscal decentralization-local investment expenditures
(percent of GDP)
Fiscal decentralization- local investment expenditures
(percent of GDP)
Fiscal policy (fair)
Fiscal policy (fair)
Fiscal policy (fair)
Fiscal policy (fair)
Decentralization,
VATs; income taxes; property taxes (good)
Decentralization,
VATs; income taxes; property taxes (good)
Decentralization,
VATs; income taxes; property taxes (good)
Decentralization,
VATs; income taxes; property taxes (good)
Source: UCLG 2007
96

Table D2.
World Bank’s Decentralization and Subnational Regional Economics
Database Comparison
Indicator Fit with MCC Indicator
Policies and
Correlation with
Policy Outcome
Fiscal decentralization- subnational government’s share of expenditures
Fiscal decentralization- vertical fiscal imbalances
Fiscal policy (fair)
Fiscal policy (fair)
Decentralization,
VATs; income taxes; property taxes (good)
Decentralization,
VATs; income taxes; property taxes (good)
Source: World Bank 2001.
97

Appendix E presents all of the available indicators developed by GCIF. Table E1 lists GCIF profile indicators. Table E2 lists GCIF performance indicators and is followed by a discussion of GCIF indicator themes that only indirectly relate to economic growth and poverty. Table E3 lists GCIF future indicators.
Table E1.
GCIF Profile Indicators
Theme Indicator
Total city population/ Population density (per square kilometer)
Percentage of country’s population
Percentage of population that are children (age 0-14)
People
Percentage of population that are youth (age 15-24)
Percentage of population that are adult (age 25-64)
Percentage of population that are senior citizens (age 65+)
Male to female ratio (number of males per females)
Annual population change
Population dependency ratio
Percentage of population that are new immigrants
Percentage of population migrating from elsewhere in the country
Average household income (US$)
Annual inflation rate based on average of last 5 years
Cost of living
Income distribution (Gini coefficient)
Economy
Country’s GDP (US$)
Country’s GDP per capita (US$)
City product (US$)
City product as a percentage of country’s GDP
Total employment
Employment percentage change based on the last 5 years
Number of businesses per 1,000 population
Annual average unemployment rate
Commercial/industrial assessment as a percentage of total assessment
98

Theme Indicator
Total number of households
Housing
Government
Total number of occupied dwelling units (owned and rented)
Persons per unit
Dwelling density (per square kilometer)
Type of government (e.g., local, regional, county)
Gross operating budget (US$)
Gross operating budget per capita (US$)
Geography and
Climate
Gross capital budget (US$)
Gross capital budget per capita (US$)
Region
Climate type
Land area (square kilometers)
Percentage of non-residential area (square kilometers)
Annual average temperature (degrees Celsius ( 0 C))
Average annual rain (mm)/Average annual snowfall (cm)
Source: GCIF 2012b.
Table E2.
GCIF Performance Indicators
Theme Core Indicator
City Services
Supporting Indicator
Education
Student/teacher ratio
Percentage of students completing primary and secondary education: survival rate
Percentage of students completing primary education
Percentage of school-aged population enrolled in schools
Percentage of male school-aged population enrolled in schools
Percentage of female school-aged population enrolled in schools
Percentage of students completing secondary education
Number of in-patient hospital beds per 100,000 city residents
Number of nursing and midwifery personnel per
100,000 city residents
Health
Number of physicians per 100,000 city residents
Average life expectancy
99

Theme
Safety
Transportation
Urban
Planning
Solid Waste
Core Indicator
Under age five mortality per 1,000 live births
Number of police officers per
100,000 city residents
Number of homicides per 100,000 city residents
Km of high capacity public transit system per 100,000 city residents
Supporting Indicator
Violent crime rate per
100,000 city residents
Km of light passenger transit system per 100,000 residents
Number of two-wheel motorized vehicles per capita
Commercial air connectivity (number of nonstop commercial air destinations)
Transportation fatalities per 100,000 city residents
Number of personal automobiles per capita
Annual number of public transit trips per capita
Jobs/Housing ratio
Number of homicides per 100,000 city residents
Percentage of city’s solid waste that is recycled
Areal size of informal settlements as a percent of city area
Green area (hectares) per
100,000 city residents
Percentage of the city’s solid waste that is disposed of in an incinerator
Percentage of the city’s solid waste that is burned openly
Percentage of the city’s solid waste that is disposed of in an open dump
Percentage of the city’s solid waste that is disposed of in a sanitary landfill
Percentage of the city’s solid waste that is disposed of by other means
100

Theme
Wastewater
Water
Electricity
Finance
Governance
Core Indicator
Percentage of city population served by wastewater collection
Percentage of the city’s wastewater that has received no treatment
Percentage of city population with potable water supply service
Supporting Indicator
Percentage of the city’s wastewater receiving primary treatment
Percentage of the city’s wastewater receiving secondary treatment
Percentage of the city’s wastewater receiving tertiary treatment
Total water consumption per capita (liters/day)
Domestic water consumption per capita (liters/day)
Percentage of city population with sustainable access to an improved water source
Percentage of city population with authorized electrical service
Total residential electrical use per capita (kWh/year)
Percentage of water loss
Average annual hours of water service interruption per household
Total electrical use per capita (kWh/year)
The average number of electrical interruptions per customer per year
Average length of electrical interruptions (in hours)
Debt service ratio (debt service expenditure as a percent of a municipality’s own-source revenue)
Tax collected as percentage of tax billed
Own-source revenue as a percentage of total revenues
Capital spending as a percentage of total expenditures
Percentage of women employed in the city government workforce
101

Theme
Fire and
Emergency
Response
Recreation
Civic
Engagement
Culture
Economy
Environment
Shelter
Social Equity
Core Indicator
Number of firefighters per 100,000 city residents
Supporting Indicator
Response time for fire department from initial call
Number of fire related deaths per
100,000 city residents
Square meters of public indoor recreation space per capita
Square meters of public outdoor recreation space per capita
Quality of Life
Voter participation in last municipal election (as a percent of eligible voters)
Citizen’s representation: number of local officials elected to office per
100,000 city residents
Percentage of jobs in the cultural sector
City product per capita
City unemployment rate
PM10 (particulate matter) concentration
Percentage of city population living in slums
Percentage of persons in full-time employment
Greenhouse gas emissions measured in tones per capita
Percentage of households that exist without registered legal titles
Number of homeless people per 100,000 city residents
Percentage of city population living in poverty
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Theme
Technology and Innovation
Core Indicator
Number of internet connections per 100,000 city residents
Supporting Indicator
Number of new patents per 100,000 per year
Number of higher education degrees per
100,000
Number of telephone connections (landlines and cell phones) per 100,000 city residents
Number of landline phone connections per 100,000 city residents
Number of cell phone connections per 100,000 city residents
Source: GCIF 2012b.
The following are GCIF themes and corresponding indicators that relate indirectly to economic growth and poverty.
Fire and Emergency Response
Core Indicators:
● Firefighters per 100,000 city residents and
● Fire related deaths per 100,000 city residents.
Supporting Indicator:
● Response time for fire department from initial call.
By measuring per 100,000 city residents, cities of different sizes are easily comparable. Moreover, the number of deaths per year is a measure of the effectiveness of a city’s fire services, which is usually reported by most countries.
Fire response is an important municipal service that protects the lives of city residents and city property.
Social Equity
Supporting Indicator:
● Percentage of city population living in poverty.
This indicator only represents a proxy measure of social equity by measuring the proportion of city residents living below the poverty line, whereas the GCIF income distribution/Gini coefficient profile indicator is a more accurate measurement of the level of wealth inequity. This indicator applies current
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average persons per household figures to all households to determine the percentage of city population living in poverty, which is a potential drawback as it may be difficult to distinguish between household size in poor and more affluent households. MCC does not utilize indicators that correspond directly to measures of social equity. Using a city-level social equity indicator is important because inequality levels correlate highly with poverty rates and the outlook for economic growth. Inequality levels also directly affect other aspects of city residents’ welfare, such as health and education outcomes. The WHO states that “being excluded from the life of society and treated as less than equal leads to worse health and greater risks of premature death. The stresses of living in poverty are particularly harmful to pregnant women, babies, children, and old people” (WHO
2006, 16). The city-level Gini coefficient GCIF profile indicator is probably a more accurate measurement of inequality, although the percentage of city population living in poverty is a good supporting measurement.
Governance
Supporting Indicator:
● Percentage of women in the city government workforce.
This indicator provides a direct measurement of the level of gender equity within a city government’s hiring system. Higher levels of gender equity have been demonstrated to improve economic growth and reduce poverty in developing nations (UN-HABITAT 2004, 62). This logic can be extended to cities.
Table E3 lists the indicators being developed by GCIF to be used in the future.
Table E3.
Future GCIF Indicators
Theme Indicator
Education
Health
Finance
City Services
Number of libraries per 100,000 city residents
Number of visits to library per 100,000 city residents
Performance of standardized tests
Number of institutions of higher learning within 500 kilometers
Percentage of city population enrolled in institutions of higher learning
Annual HIV/AIDS death rate per 100,000 city residents
Disaggregation of immunization against infectious childhood diseases
Disaggregate of own-source revenue as a percentage of the total revenues into categories of property tax, sales tax, user fees and charges, and other revenue sources
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Theme Indicator
Recreational use level
Recreation
Recreation and Culture Index
Perception of safety
Safety
Juvenile crime (gangs and youth related crimes)
Fire and
Emergency
Response
Emergency medical services indicator
Number of fire trucks per 100,000 city residents
Number of ambulances per 100,000 city residents
Response time for emergency services from initial call
Outcome indicators such as rates of fire or property damage and ultimate health/survival rates of patients
Electricity
Urban
Planning
Share of renewable energy use out of primary energy supply
Residential energy use per household by types of energy
Total energy use index
Legal issues related to land acquisition
Enforcement regulations
Planning standards
Frequency of official reviews of master city plans
City governance index
Average number of days to obtain a business license
Governance
Requests for service response time
Civic engagement
Solid Waste Informal waste-pickers
Water quality index
Water
Incidence of waterborne diseases
Disaggregated measure of population with access to potable water
(according to type of connection)
Wastewater
Transportation
Water quality
Wastewater treatment effectiveness
Assimilative capacity of receiving water body
Shape/condition of infrastructure
Total municipal road and transit expenditure per capita
Urban accessibility index
Technology and Innovation
Quality of Life
Venture capital investment
Broadband penetration rate
Creativity index
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Theme Indicator
Social Equity
Social capital index
Economy Competitiveness index
Attendance at cultural events per capita
Culture Multiculturalism
Creative cities index
Environment
Shelter
Greenhouse gas index
Number of days that exceed PM10 (particulate matter)
Link between air quality and respiratory illnesses
Sustainable cities/climate change plans
Greenhouse gas emission from municipal operation
Housing price/income ratio
Housing rent/income ratio
Homelessness
Source: GCIF 2012b.
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Table F1 lists cities that provide data to GCIF and are located in MCC eligible countries.
Table F1.
GCIF City Coverage in MCC Eligible Countries
MCC
Country
Albania
Armenia
Benin
Burkina Faso
Cape Verde
El Salvador San Salvador, Santa Ana
Georgia
Ghana Sekondi-Takoradi
Guyana
Honduras
GCIF City
Jordan Amman
Kenya Mombasa
Kyrgyz
Republic
Lesotho
Liberia Monrovia
Madagascar Alaotra-Mangoro, Anjozorobe, Antananarivo
Malawi Lilongwe
Mali Bamako
Moldova
Mongolia Darkhan
Morocco Kenitra
Namibia Windhoek
Nicaragua
Niger
Paraguay
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MCC
Country
GCIF City
Philippines
Alaminos, Antipolo, Baguio, Balanga, Bayawan, Calbayog, Cauayan,
Cotabato, Dapitan, Dipolog, Escalante, Isulan, Kabankalan, Laoag,
Ligao, Makati, Malabon, Mandaluyong, Mandaue City, Marikina,
Masbate, Munoz, Olongapo, Oroquieta, Palayan, Passi, Puerta
Princesa, Quezon, Roxas, San Fernando, San Jose Del Monte, San
Pablo, Surigao, Tabaco, Tacurong, Tagatay, Tarlac, Toledo,
Tuguegarao, Vigan, Zamboanga
Philippines
Rwanda Kigali
São Tomé and Principe
Senegal
Tanzania
Dakar, Nioro du Rip
Dar es Salaam
Timor-Leste
Uganda Kampala
Ukraine Boryspil, Cherkasy, Dnipropetrovsk, Horlivka, Kryvyi Rih, Lviv
Vanuatu
Zambia
Source: GCIF 2012c.
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Doing Business began to publish subnational data reports in 2006. Some reports provide city-level data for cities in a particular country while other reports include regional data from various countries. Listed below is the number of cities covered for each country or region. The number of cities covered appears in parentheses.
2006: Brazil (13)
2007: Bangladesh (4), India (12), Pakistan (6)
2008: South East Europe (22), Philippines (25), Small Island Developing States
(32), China (30), Egypt (3), Morocco (8)
2009: Russia (10), India (18), Italy (1), Mexico (32), Small Islands Developing
States (33)
2010: Tanzania (1), Pakistan (13), Nigeria (37), Colombia (21), Kenya (11)
2011: South East Europe (22), Philippines (25), Southern Sudan (1), Arab World
(20)
2012: Indonesia (20)
Table G1 summarizes the type of indicator and the country where the city-level indicator is available. Moreover, the last column of the table shows both cities/countries/regions covered by the database that are eligible to receive an
MCC grant.
Table G1.
Doing Business Indicators and Geographic Coverage
Indicator Coverage
Coverage under MCC
Eligibility
Starting a business
Indonesia, Philippines, Pakistan,
Nigeria, Colombia, Russia,
Kenya, India, Mexico, China,
Egypt, Morocco, Brazil
Indonesia, Philippines,
Pakistan, Nigeria, Kenya, India,
Egypt, Morocco
Registering property
China, Colombia, Egypt, India,
Indonesia, Kenya, Mexico,
Nigeria, Pakistan, Philippines
Indonesia, Philippines,
Pakistan, Nigeria, Kenya, India,
Egypt
Dealing with construction permits
Colombia, Egypt, India,
Indonesia, Kenya, Mexico,
Morocco, Nigeria, Pakistan,
Philippines
Indonesia, Philippines,
Pakistan, Nigeria, Kenya, India,
Egypt, Morocco
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Indicator Coverage
Coverage under MCC
Eligibility
Pakistan, India Paying taxes Colombia, India, Pakistan
Trading across borders
India, Pakistan Pakistan, India
Enforcing contracts
China, Colombia, India, Kenya,
Mexico, Morocco, Nigeria,
Pakistan
Pakistan, Nigeria, Kenya, India,
Morocco
Resolving insolvency
Getting credit
India India
N/A N/A
Getting electricity
N/A N/A
Protecting investors
N/A N/A
Source: ICF and World Bank 2012.
The indicators are based on standardized case studies, which complement the perception surveys that explore the major constraints experienced by businesses and the set of regulations that apply to businesses in a particular city. This information is derived from two types of data. The first type of data comes from an analysis of the laws and regulations by local experts and Doing Business experts from the International Finance Corporation. The second type of data is related to indicators that measure the efficiency in achieving a particular regulatory goal.
Respondents have to complete written questionnaires and provide references to relevant laws, regulations, and fees. This information is checked for accuracy by comparing it with formal legal documents that outline relevant laws and regulations. Most of the respondents are legal professionals, such as lawyers or judges. Other respondents include notaries, accountants, architects, freight forwarders, and other professionals related to the indicator topic (IFC and World
Bank 2012).
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Appendix H discusses the UN-HABITAT Urban Development Index, urban governance databases, transportation databases, financial services databases, the Oxford Multidimensional Poverty Index, and national-level urban databases.
Tables H1 through H4 compare the indicators in each database to MCC indicators and Section II policies.
The UN-HABITAT Urban Development Index (UDI) is a comprehensive dataset that contains a variety of urban indicators and uses the standard UN definition of
“urban agglomeration” as its criteria for the size of cities that are measured. The
UDI relies on a collaborative effort between national statistics offices, urban ministries, city authorities, and the larger research community for the collection and interpretation of data and the construction of indicators. Particular emphasis is placed on utilizing the opinions and analyses of qualified experts for data and indicator interpretation. Most of the indicators presented by the UDI are nationallevel urban data. The UDI has eight city-level indicators: service provision within cities, primary education enrollment, Gini coefficient, percentage of children with diarrhea (in last two weeks), percentage of children with acute respiratory illness, percentage of children with fever (in last two weeks), percentage of malnourished children, and percentage of children immunized against measles. These indicators reflect human capital levels in cities and display existing social conditions in lowincome and low-middle income countries. Further, various Section II policies are measured by these indicators.
The UDI indicators are publicly available and are generally accepted to be reliable third-party data, however, many of the city-level indicators have a four to eight year gap in data collection. Although some 2011 data exists, the majority of citylevel data are currently only through 2009. Compared to the GCIF indicators, which are updated on an annual basis, UDI indicators lack a consistent measurement of year-to-year change. UDI indicators also do not have the same breadth of coverage as the GCIF indicators for issue and policy areas in cities.
Given these concerns, UDI data may only serve as a complement to other indicator databases, such as GCIF. Table H1 compares the UDI indicators to
MCC indicators and Section II policies.
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Indicator
Table H1.
UN-HABITAT Urban Development Index
Fit with MCC Indicator
Policies and
Correlation with
Policy Outcome
Services in cities
Natural resource management
(good)
Condominial water supply (good); PPPs
(good)
Enrollment in primary education
Gini coefficients
Percentage of children with diarrhea
Percentage of children with acute respiratory infections
Percentage of children with fever
Percentage of malnourished children
Percentage of children immunized against measles
Total public expenditure on primary education (good)
N/A
Child health (good)
Child health (good)
Child health (good)
Child health; immunization rates (fair)
Child health; immunization rates (good)
Source: UN-HABITAT 2009.
PPPs (good); targeted school fee reduction
(fair); conditional cash transfer programs
(good)
N/A
Community-based health insurance (fair); microfinance and health education (fair); condominial water supply (good); communal sanitation provision (good); municipal solid waste management systems
(good)
Community-based health insurance (fair); iron supplements and deworming drugs (fair); microfinance and health education (fair)
Community-based health insurance (fair); iron supplements and deworming drugs (fair)
Conditional cash transfers (fair); iron supplements and deworming drugs (fair)
Conditional cash transfers (fair); PPPs
(fair); communitybased health insurance
(fair); microfinance and health education (fair)
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Good governance at the city level is associated with higher quality service provision and infrastructure services and has been demonstrated to have a positive impact on GDP growth through increased competition and decreased corruption
(Kaufmann, Leautier, and Mastruzzi 2005). Typically, most governance indicators are used to gauge the effectiveness, equity, participation, accountability, and security of governing institutions (UN-HABITAT 2004, 4). Other governance indicators consider institutional construction and efficacy, degree of citizen representation, the incidence of corruption, and type of government. Prioritizing these measures is difficult and is often determined by the pre-existing norms and values of the evaluating institutions. Ultimately, quantifying good governance relies on a number of assumptions and is open to debate and interpretation
(Stewart 2006, 197). Ideally, governance indicators should be applicable across cities and countries, consistently collected and updated, and provide a comparable baseline over time. Most city-level governance indicators are in a preliminary development phase with low levels of comparability and applicability when compared to national-level governance indicators (Holden 2006, 182). In the following discussion, we provide descriptions of three governance indicator databases: the UN-HABITAT Urban Governance Index, the Local Governance
Barometer, and the Local Integrity Initiative.
The UN-HABITAT Urban Governance Index (UGI) 11 was developed in 2004 as a preliminary framework to assess good governance at the city level. Originally created as a pilot project in 24 cities in 15 countries (17 of which are in lowincome or low-middle income countries), the UGI focuses on governance processes. It evaluates good governance with indicators organized into four subindices: Effectiveness, Equity, Participation, and Accountability. The indicators associated with these principles evaluate the quality of city governance structures, institutions, and procedures. Much of the data was collected and interpreted through a series of field tests conducted by experts and participating city personnel.
The Effectiveness sub-index evaluates cities based on the performance of their fiscal policies (such as local revenue raising, transfers, and tax collection). The
Equity sub-index looks at service provision, women in government, and “pro-poor” policies that exist in cities. The Participation sub-index assesses civic participation and voter turnout. The Accountability sub-index looks at government transparency, local institutional control compared with central government involvement, the existence of anti-corruption commissions, and frequency of independent audits. The
UGI weights these measures to calculate a final indicator ranging from 0 to 1, with
0 reflecting “poor performance” and 1 “excellent performance.”
11 All information and methodology was obtained from 2004 UN-HABITAT report “Urban
Governance Index-Conceptual Foundation and Field Test Report.”
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The UGI is more successful than GCIF in measuring city-level governance quality. UGI’s measures are very comprehensive, addressing a wide range of governance elements including fiscal policy, civic participation, gender equality, and a measurement and assessment of corruption. UGI, however, does not cover as many cities as GCIF and has not been updated since its creation in 2004.
Despite the current infrequency of data collection, UGI may be used as a framework for GCIF’s future “city governance index” (UN-HABITAT 2004, 18;
GCIF 2008, 9). Table H2 compares the UGI indicators to MCC indicators and
Section II policies.
Table H2.
UN-HABITAT Urban Governance Index
Indicator
Effectiveness
Fit with MCC Indicator
Government effectiveness
(good)
Policies and
Correlation with
Policy Outcome
Tax administration
(fair)
Equity Political rights (good) N/A
Participation
Political rights; voice and accountability (good)
N/A
Accountability
Political rights; voice and accountability (good)
Police reform (good); auction reform (good)
Source: UN-HABITAT 2004.
Aside from UGI’s governance indicators, two smaller databases have a regional focus on urban governance: the Local Governance Barometer (seven countries, 33 subnational governments) and the Local Integrity Initiative (2 countries, 18 subnational governments).
The Local Governance Barometer (LGB) 12 was developed with the support of
NGOs such as SNV, the Institute for Democracy in Africa (Idasa), and PACT.
Using evaluation criteria similar to the UGI (effectiveness/efficiency, rule of law, accountability, participation, and equity), the LGB assesses how well governed specific cities and provinces in seven African countries are. The LGB is created using both a core model and a specific model. The core model uses universal criteria derived from academic research and expert opinions. The specific model
12 All of the information and methodology discussed was obtained from Local Governance
Barometer website: http://www.pact.mg/lgb/.
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uses contextual criteria to measure and assess the universal criteria. This method of assessment effectively reduces the comparability of the data across cities and countries. The LGB works with local officials to tailor the indicators and data collection to local needs and concerns. Much of the data collected by the LGB are in the form of academic studies, focus group discussions, and community surveys.
Data are then processed and localities are given a score from 0 to 100, with 0 being “poorly governed and 100 being “well governed.” Table H3 compares the
LGB indicators to MCC indicators and Section II policies.
Table H3. Local Governance Barometer
Indicator efficiency
Rule of law
Effectiveness and
Accountability
Fit with MCC Indicator
Government effectiveness
(good)
Rule of law (good)
(good)
Voice and accountability
Policies and
Correlation with
Policy Outcome
Police reform, auction reform (fair)
Police reform (good)
Police reform, auction reform (fair)
Participation
Political rights; voice and accountability (good)
N/A
Equity Political rights (good) N/A
Source: Local Governance Barometer 2012.
The Local Integrity Initiative (LII) 13 was created by the NGO, Global Integrity, and has compiled a series of local governance indicators for very specific contexts. In particular the LII has recently created two local governance indices, the Kenya City Integrity Report and the Liberia Local Governance Toolkit (LII
2012a; 2012b). Both employ a bottom-up approach toward assessing transparency and corruption at the local level. Rather than measuring the incidence or existence of corruption, these indices measure the effectiveness of the policies and reforms aimed at addressing corruption. The only difference between these indices is their area of focus. The Kenya City Integrity Report focuses on the three biggest cities in Kenya (Nairobi, Mombasa, and Kisumu), while the Liberia Local Governance
Toolkit focuses on 15 Liberian counties.
13 All of the information and methodology discussed was obtained from Local Integrity Initiative
(http://www.globalintegrity.org/local), Kenya City Integrity
(http://www.globalintegrity.org/local/kenya/), and Liberia Local Governance Toolkit
(http://local.lr2007.globalintegrity.org/).
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Both indices are constructed in a similar manner. First, they employ three concepts to evaluate local governance policies and reforms: 1) existence of public integrity mechanisms; 2) effectiveness of mechanisms; and 3) citizen access to mechanisms. Second, their measurements are divided into five categories: 1) city information transparency; 2) city elections; 3) city government conflicts of interest safeguards; 4) city fiscal and budgetary management; and 5) city public administration and business relations. They also both collect data using a “lead researcher” and several “peer reviewers” to evaluate the de jure and de facto measures of the data. Further, they score the effectiveness of a given city’s governance structure and institution on a 0 to 100 scale with 0 being “poorly governed” and 100 being “well governed.”
Drawbacks and Comparisons of LGB and LII
The LGB and the LII are both good attempts at assessing and measuring corruption at the local government level. Their indicators are designed to capture a broad measure of governance with a focus on corruption. Compared to the GCIF and UGI, however, they are not effective for broad city-to-city comparisons.
Further, the LGB is inconsistent in its application and indicators as city-level data collection may vary between countries. Additionally, the LII has only been tracked for one year. Moreover, the LGB is not publicly available although both
LII country datasets are publicly available. Table H4 compares the LII indicators to MCC indicators and Section II policies.
Table H4. Local Integrity Initiative
Indicator Fit with MCC Indicator
Policies and
Correlation with
Policy Outcome
City information transparency
City elections
Freedom of information (good)
Political rights (high)
Auction reform (poor)
N/A
Safeguards against city government conflicts of Interest
City fiscal and budgetary management
City public administration and business relations
Voice and accountability;
Government effectiveness (fair)
Government effectiveness (fair)
Voice and accountability; government effectiveness (fair)
Auction reform (good)
Auction reform (poor)
Auction reform (poor)
Source: Local Integrity Initiative 2012a
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No global institution collects all of the data related to public transportation at a city level. A number of international and regional organizations, however, gather relevant information that MCC may consider for indicators directly related to economic growth and poverty reduction.
The International Association of Public Transport
The International Association of Public Transport (UITP) has a regional office on every continent. Because each regional office currently collects its own data,
MCC may consider approaching UITP about their current efforts in organizing data collection globally. The African office is holding an upcoming UITP regional conference in Johannesburg, South Africa, and it may be an appropriate forum for
MCC to approach UITP about coordinating future indicator uniformity. More information can be found at http://www.uitp.org/regions/africa/Sub-regions.cfm.
EMBARQ
EMBARQ, a not-for-profit initiative of the World Resources Institute, has five regional Centers for Sustainable Transport. Data collected as part of EMBARQ’s
Key Performance Indicators (KPI) measure five public transportation categories:
1) passengers served; 2) travel time savings; 3) project investment; 4) lives saved; and 5) CO
2
equivalent emissions avoided. EMBARQ’s KPIs also provide additional measurements of bicycle and pedestrian infrastructure and other urban development projects. EMBARQ’s KPI currently measures over 100 cities and plans to publicly provide KPI data on 200 cities in the near future (Cooper 2012).
Bus Rapid Transit
The Bus Rapid Transit (BRT) Database is a global collaboration among dozens of regional and international organizations interested in better evaluating bus rapid transit outcomes in cities around the world. Although only 125 cities are assessed, primarily in Latin America, BRT is expanding its efforts and plans to continuously add cities in the coming months and years. Their comprehensive data capture a variety of outcomes related to the following categories: quality of service, cost, comfort, travel time, type of BRT infrastructure, demographics, and urban economics. Individual data can be accessed from the 6th BRT Database at http://www.brt.cl/brt-database-v6-2/.
We found two additional Financial Services databases: the World Bank Global
Findex database and the Mobile and Development Intelligence database. These databases are discussed below.
World Bank Global Findex
In April of 2012, the World Bank launched Global Findex, the first public database of indicators designed to consistently measure financial information
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related to savings, borrowing, payments, and risk management across 148 countries. Upon its full release in October 2012, the public will be able to disaggregate Global Findex information by a few individual characteristics and distinguish between rural and urban situations at the national level. Although individual urban area statistics will be available upon request, statistics result from 1,000 sample surveys per country.
It should be noted that data inferences may be sufficient for countries where only a few cities are sampled; however, some MCC eligible countries with many large urban areas may have too few data points for MCC to evaluate differences with any confidence.
Every three years, data on the following indicators will be released for all 148 participating countries. All of the data relates to adults 15 years or older in each country (Klapper 2012; Klapper and Demirguci-Kunt 2012).
•
•
•
Percentage of bank accounts held through formal financial institutions
Percentage who saved at a formal financial institution in the past year
Percentage who took a loan from a formal financial institution in the past year
•
•
•
Percentage who used an account to receive wages
Percentage who used an account to receive government payments
Percentage who used an account to receive remittances
Further information related to the World Bank Global Findex can be found at http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/E
XTPROGRAMS/EXTFINRES/EXTGLOBALFIN/0,,contentMDK:23147627~pa gePK:64168176~piPK:64168140~theSitePK:8519639,00.html.
Mobile and Development Intelligence
The Mobile and Development Intelligence database includes measurements of the social and economic impact of mobile phones. Data collection includes information related to financial services such as savings and remittances in almost every low-income and lower middle-income country. Although all of the information is at the national level, project personnel indicated to us that data will become publicly available at the city level (Morrison 2012).
Some of the Mobile and Development Intelligence indicators appropriately capture information directly related to the informal economy, which account for a significant portion of overall economic activity in low-income and lower middleincome countries. Once city-level data are made publicly available, many of the indicators will appropriately complement Doing Business indicators that measure the formal economy. More information can be found at http://www.mobiledevelopmentintelligence.com/our_vision.
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Oxford Multidimensional Poverty Index
The Oxford Poverty and Human Development Initiative released the Oxford
Mulidimensional Poverty Index (MPI) in 2012. Figure H1 provides a summary of the MPI methodology. The MPI measures 28 of the 36 MCC partner countries at the subnational level. Subnational data include regional statistics and nationallevel rural and urban data; however, specific city-level data are not included. Data are collected from a variety of sources, are publicly available, and the majority of indicators will be updated annually or every two years. MPI data is divided into ten indicators across three equally weighted categories. The education category is measured by two indicators: number of years of schooling and school attendance.
The health category is measured by two indicators: child mortality and nutrition.
The standard of living category is measured by six indicators: cooking fuel; sanitation; water; electricity; floor (type of housing); and asset ownership. Each of the two indicators that measure the education and health categories account for one-sixth of the total index score, and each of the six indicators that measure the standard of living category account for one-eighteenth of the total index score
(OPHI 2012). Additional information on the MPI and the countries that have subnational data can be found at http://www.ophi.org.uk/policy/multidimensionalpoverty-index/mpi-country-briefings/.
Figure H1.
Multidimensional Poverty Index Indicators
Source: Oxford Poverty and Human Development Initiative 2012.
National-level Urban Databases
A national-level urban data indicator is a measure or dataset that aggregates urban data at the national level. These indicators are useful for providing a snapshot of urban conditions within countries. However, they do not provide city-level data.
UN-HABITAT’s Urban Development Index (UDI) and Global Urban
Observatory Network are two examples of databases with national-level urban data. WHO’s Global Health Observatory Data Repository and the World Bank’s
Urban Development Indicators also fall under this category.
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These indicators are very useful in providing and tracking urban information.
They cover a wide variety of topics including population growth rates, slum growth rates, access to services, environmental conditions, and energy and electricity prices. Further, these data can be tracked over time and are collected and interpreted by reputable third-party organizations. They also allow for crosscountry comparisons. They do not, however, provide any specificity regarding individual cities, and therefore, cannot be used to compare data among cities or to compare city data to country data.
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