Analyzing Urban Poverty A Summary of Methods and Approaches Judy Baker and Nina Schuler Abstract In recent years an extensive body of literature has emerged on the definition, measurement and analysis of poverty. Much of this literature focuses on analyzing poverty at the national level, or spatial disaggregation by general categories of urban or rural areas with adjustments made for regional price differentials. Yet for an individual city attempting to tackle the problems of urban poverty, this level of aggregation is not sufficient for answering specific questions such as where the poor are located in the city, whether there are differences between poor areas, if access to services varies by subgroup, whether specific programs are reaching the poorest, and how to design effective poverty reduction programs and policies. Answering these questions is critical, particularly for large, sprawling cities with highly diverse populations and growing problems of urban poverty. Understanding urban poverty presents a set of issues distinct from general poverty analysis and thus may require additional tools and techniques. This paper summarizes the main issues in conducting urban poverty analysis, with a focus on presenting a sample of case studies from urban areas that were implemented by a number of different agencies using a range of analytical approaches for studying urban poverty. Specific conclusions regarding design and analysis, data, timing, cost, and implementation issues are discussed. World Bank Policy Research Working Paper 3399, September 2004 The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org. *The authors would like to thank participants of the seminar in April 2004, the authors of the urban poverty studies referenced in the paper, and Richard Beardmore, André Herzog, Christine Kessides, Sunil Kumar, Mark Montgomery, Taimur Samad, and Stephanie Wilcock for their comments. 1 Introduction In recent years an extensive body of literature has emerged on the definition, measurement and analysis of poverty.1 Much of this literature focuses on analyzing poverty at the national level, or spatial disaggregation by general categories of urban or rural areas with adjustments made for regional price differentials. Yet for an individual city attempting to tackle the problems of urban poverty, this level of aggregation is not sufficient for answering specific questions such as where the poor are located in the city, whether there are differences between poor areas, if access to services varies by subgroup, whether specific programs are reaching the poorest, and how to design effective poverty reduction programs and policies. Answering these questions is critical, particularly for large, sprawling cities with highly diverse populations and growing problems of urban poverty.2 Understanding urban poverty presents a set of issues distinct from general poverty analysis and thus may require additional tools and techniques. This paper attempts to summarize the main issues in conducting urban poverty analysis, with a focus on presenting a sample of case studies from urban areas that were implemented by a number of different agencies, using a range of analytical approaches for studying urban poverty. A complementary document, The City Poverty Assessment: A Primer (Hentschel and Seshagir, 2000) provides a more in-depth discussion of specific types of analysis. Section I discusses the approaches to urban poverty analysis, Section II presents a summary of the case studies, and Section III concludes. SECTION I: URBAN POVERTY ANALYSIS 1. Designing Urban Poverty Studies For the purposes of this paper, urban poverty analysis (UPA) is defined as the process of gathering, analyzing, and presenting information on the extent, location, and conditions of poverty in a given city. This can then be used to generate a city poverty profile that policy makers, community members and academics can use in answering questions about urban poverty and to identify appropriate responses. It also provides a baseline from which changes in policies, investments and activities may be measured. As the conditions and quality of poverty are not static, a good city poverty profile should serve as a dynamic starting point for better understanding poverty problems and appropriate responses. While there is no single approach to conducting urban poverty assessments, there are some common good practices that may facilitate the process of thinking through the design of a city poverty profile, which are discussed below. a. Urban Context What issues are specific to urban poverty? 1For a summary and list of references, see Coudel, Hentschel, and Wodon, "Poverty Measurement and Analysis" in World Bank, 2002, A Sourcebook for Poverty Reduction Strategies, Chapter 1. Web link: http://www.worldbank.org/poverty/strategies/sourctoc.htm 2Urbanization is occurring rapidly, with estimates that the number of people living in urban areas will double to more than 5 billion between 1990 and 2025. With this increase, the number of poor in urban areas is also likely to rise. 2 While the dimensions of poverty are many, there is a subset of characteristics that are more pronounced for the poor in urban areas and may require specific analysis:3 commoditization (reliance on the cash economy); overcrowded living conditions (slums); environmental hazard (stemming from density and hazardous location of settlements, and exposure to multiple pollutants); social fragmentation (lack of community and inter-household mechanisms for social security, relative to those in rural areas); crime and violence; traffic accidents; and natural disasters. b. Definitions and Identification Who are the poor? What poverty indicators will be used in the city poverty profile? The application of quantitative poverty measures to a city should be viewed as the start of a city profile; distinguishing the poor from the non-poor (and the relative sizes of these groups), identifying their characteristics, facilitating the process of identifying the location of the poor, and highlighting groups that may be particularly vulnerable to poverty (i.e., female-headed households, migrants, youth, etc.). This basic data can be used to inform the selection of more in- depth qualitative measures. Box 1: Approaches to Measuring Urban Poverty Poverty is multidimensional, thus measuring it presents a number of challenges. Beyond low income, there is low human, social and financial capital. The most common approach to measuring poverty is quantitative, money-metric measures which use income or consumption to assess whether a household can afford to purchase a basic basket of goods at a given point in time. The basket ideally reflects local tastes, and adjusts for spatial price differentials across regions and urban or rural areas in a given country. Money-metric methods are widely used because they are objective, can be used as the basis for a range of socio-economic variables, and it is possible to adjust for differences between households, and intra- household inequalities. 3See Baharaoglu and Kessides, 2002, "Urban Poverty" in World Bank, 2002, A Sourcebook for Poverty Reduction Strategies, Chapter 16. 3 Despite these advantages, money-metric poverty measures have some shortcomings. Survey designs vary significantly between countries and over time, making comparability difficult. Some use income based measures, other consumption. Decisions about how to value housing, homegrown food, and how to account for household size and composition all affect poverty estimates. If not properly adjusted, monetary measures can underestimate urban poverty because they do not make allowance for the extra cost of urban living (housing, transport, and lack of opportunity to grow ones own food).4 Income or consumption measures also do not capture many of the dimensions of poverty. For example, in the urban context, the urban poor rely heavily on the cash economy thus making them more vulnerable to fluctuations in income, and there are severe environmental and health hazards due to crowded living conditions in urban slums, and no tenure security. Other aspects of poverty, both rural and urban, which are multidimensional relate to access to basic services such as water, sewage, health and education, and a safety net to mitigate hard times. Measuring urban poverty can be carried out using a number of approaches summarized below. Regardless of the methodology chosen, the data should ideally be comparable across cities, and allow for disaggregation at the intra-city level. This will capture vast differences between the poor in small towns and mega cities, or between urban slum areas within a given city. ˇ Income or Consumption Measures: Both are based on data that assess whether an individual or household can afford a basic basket of goods (typically food, housing water, clothing, transport, etc.). Consumption is generally considered to be a better measure than income because incomes tend to fluctuate over time, there are problems of under-reporting (particularly income derived from the private and informal sectors).5 Money metric measures can be adjusted to account for the higher cost of living in urban areas when measuring poverty. ˇ Unsatisfied Basic Needs Index: This approach defines a minimum threshold for several dimensions of poverty classifying those households who do not have access to these basic needs. They include characteristics such as literacy, school attendance, piped water, sewage, adequate housing, overcrowding, and some kind of caloric and protein requirement. If a household is deficient in one of the categories, they are classified as having unsatisfied basic needs. ˇ Asset Indicators: This has been used increasingly with the Demographic and Health Surveys (DHS), a standardized survey now administered in approximately 50 countries. A range of variables on the ownership of household assets are used to construct an indicator of households socio-economic status. These assets include: a car, refrigerator, television, dwelling characteristics (type of roof, flooring, toilet), and access to basic services including clean water and electricity.6 ˇ Vulnerability: This approach defines vulnerability as a dynamic concept referring to the risk that a household or individual will experience an episode of income or health poverty over time, and the probability of being exposed to a number of other risks (violence, crime, natural disasters, being pulled out of school). Vulnerability is measured by indicators that make it possible to assess a household's risk exposure over time through panel data. These indicators include measures of: physical assets, human capital, income diversification, links to networks, participation in the formal safety net, and access to credit markets. This kind of analysis can be quite complex, requiring a specially designed survey. 4Coudel, Hentschel, and Wodon,, in World Bank, 2002 5 Chen and Ravallion, 2000, "How did the World's Poorest Fare in the 1990s, Policy Research Working Paper, World Bank, Washington, D.C. Also see Annex 1: Case Summary 12 (Household Responses) 6 Falkingham, J. and C. Namazie, 2002, Measuring Health and Poverty: A review of approaches to identifying the poor, London, DFID Health Systems Resource Center, and Montgomery, M.R., M. Gragnaloti, K. Burke, and E. Paredes, Measuring Living Standards with Proxy Variables, Demography, 2000, 37(2): P. 155-74. 4 ˇ Participatory methods: This typically relies on qualitative approaches to capture aspects of urban poverty that may not be identified through pre-coded surveys. Through tools such as focus group discussions, case studies, and individual open-ended interviews, it is possible to determine the perceptions of poverty, identify priority needs and concerns, and gain insight on the effectiveness of programs and policies from the perspective of the beneficiaries. c. Location Where do the poor live? A city poverty profile is by definition a spatial tool, defining the extent and nature of poverty within a given area. Providing an accurate mapping of where the poor live and are concentrated within cities is an important input required for targeting appropriate responses. Spatial information on land use patterns, slum location, and physical location of facilities through Geographic Information Systems (GIS) are also critical inputs. In many cases, especially when the poor live in informal settlements, they may not be included in existing administrative data. d. Access and Accessibility How does the city (policies, environment, and infrastructure) mitigate or contribute to poverty? In providing its citizens with infrastructure (roads, transportation, water, electricity, etc.), education, health care, legal, political, and financial institutions, and employment opportunities, the city provides the tools that individuals use to generate their livelihoods and well-being. Illustrating the availability and accessibility of these municipal services to the poor, should be a key component of a city poverty profile. This can also identify areas that are particularly vulnerable to social exclusion due to the lack of services. e. Characteristics, Opportunity, and Constraints What is the nature of poverty? While income-based poverty measures provide a fair sense of which part of the population may have unmet needs and where they are located, these measures fail to capture the dynamic aspects of poverty, in terms of the cause and extent of deprivation, risk factors, and the coping strategies employed. This can include analyzing vulnerability, urban-rural linkages, and perceptions. Qualitative methods are often used for this kind of analysis. Box 2: A standard poverty profile for cities Any profile of urban poverty would be based on a set of core information as described below. Household surveys/census: In general this would include the following information disaggregated by income group (e.g. quintile): Location (within the city) Household size, structure Demographics Education levels Household expenditure patterns 5 Employment (status, occupation, hours worked) Housing characteristics (tenure status, physical condition) Access/quality/affordability to: infrastructure (water, sewage, energy); health care; education; social services. Administrative data: This would include data collected by various public agencies, ideally disaggregated by geographic areas within a city. Municipal spending by sector, location Infrastructure (roads, public standpipes, schools, hospitals) Health and nutritional status Education outcomes Crime and violence statistics 2. Using Urban Poverty Analysis To justify the expense (in time and resources) of conducting city level poverty research it is important to have a clear link between the information to be collected and the application of that information in city policies, programs, etc. A common pitfall in conducting research is a lack of clarity in objectives, resulting in the collection of unclear and sometimes useless information.7 a. Strategy Development In the process of balancing the dual objectives of providing quality of life and creating competitive cities, many local authorities are engaging in urban planning and city-wide strategy development activities. Urban poverty analysis can provide valuable inputs into the process of city strategy development. City Development Strategies (CDS), as supported by Cities Alliance8, back a `comprehensive analysis of key urban issues in a particular city, and help define strategic options and implementation alternatives.'9 Urban poverty analysis can facilitate the identification of `key urban issues' through quantitative measures of urban poverty, and qualitative measures of community priorities. Local Economic Development (LED)10 is a more economically driven city strategy tool that `offers local government, the private sector, the not- for-profit sectors and the local community the opportunity to work together to improve the local economy. It focuses on enhancing competitiveness, and thus increasing sustainable growth; and also on ensuring that the growth is inclusive.' Urban poverty analysis can also be used to highlight opportunities and constraints to economic opportunities (e.g. quantitative focus on employment structure, spatial location of workers, and qualitative analysis of household responses to poverty, labor-industry relations). 7 See Moser, C, Gatehouse, M. and H. Garcia, 1996, "Urban Poverty Research Sourcebook", UNDP/UNCHS (Habitat)/The World Bank, Working Paper No. 5. 8Refer to: http://www.citiesalliance.org/ 9See Annex 1 Case Summary 9 (Cali) 10Refer to: LED: A Primer (2003), World Bank. Available at: http://www.worldbank.org/urban/led/index.html 6 b. Service Delivery and City Budgeting Service delivery is a core function and often a central challenge for local authorities. The gap between the expectations of constituents and the capacity of municipalities to deliver is defined by a range of financial, political and management issues. Increasingly, local authorities are required to explore different approaches to service delivery, particularly in meeting the needs of the poor11. New approaches to service delivery also require new types of information. Urban poverty analysis can be an effective tool in gathering and analyzing information for the purposes of designing and implementing mechanisms for service delivery. Slum Upgrading12 Infrastructure Tenure, Land administration City budgeting c. Policy and Project Monitoring Without community buy-in and accountable implementation mechanisms, even the most enlightened of urban projects and service delivery mechanisms will fail. Monitoring the impact or effectiveness of a project over time can be a critical mechanism for both involving communities and learning from mistakes (and avoiding them in future projects). Integrating urban poverty analysis into World Bank urban projects may be useful both in designing projects (utilizing data findings) and in monitoring their impact. Often projects are designed to target specific groups, but without baseline data it is difficult to measure the impact of targeting measures, and to learn from successes or failures. Urban poverty analysis that uses available census and administrative data and specially designed surveys can provide an overview of the change in people's quality of life over time in areas such as income, assets, health outcomes, and education outcomes. This general picture can also be tailored to highlight the impacts of specific investments (slum upgrading, infrastructure investments etc.), to determine their quality, cost-effectiveness and possible replicability; and to provide a de facto baseline for any future actions and investments. In this way, urban poverty analysis is a valuable tool for urban policy development, providing both an input (specific local information) as well as a project output (a starting point for a project baseline). 11See World Development Report 2004, Making Services Work for the Poor. World Bank. http://econ.worldbank.org/wdr/wdr2004/text-30023/ 12This may include improving and/or installing basic infrastructure like water, sanitation, waste collection, access roads and footpaths, storm drainage, lighting, public telephones, etc. Upgrading also deals with regularizing security of land tenure and housing improvements, as well as improving access to social support programs (e.g. health, education) and municipal services (e.g. water, sanitation, waste collection, storm drainage, street lighting, paved footpaths, roads for emergency access). http://www.worldbank.org/urban/upgrading/index.html 7 Box 3: Poverty Mapping in Urban Areas: The Case of Brazil In response to a growing demand for disaggregated data, Brazil has in recent years been compiling and updating an Atlas of Human Development. The initiative, being supported by UNDP, is being implemented by two think tanks that have developed a set of human development indicators using census data for the past four decades. The indicators were based on 38 variables in five sectors; education (literacy and enrollment rates), health (life expectancy), housing (water supply and sewage facilities), income (inequality and population under the poverty line), and infant mortality. The most recent version of the Atlas has attempted to cover 3 large cities (Belo Horizonte, Rio de Janeiro and Recife) to look at poverty within cities. The data has been made widely available allowing researchers to further analyze information. It has been used for targeting social programs. It is also being used by members of the private sector, such as Telemar, a telecommunication provider which as used the Rio de Janeiro Neighborhood Atlas to market differentiated telephone services to poor areas within the city. Source: Experience with the Development and Use of Poverty Maps, Case Study Note for Brazil, in Henninger, N. and Snel, M. 3. Data for Urban Poverty Analysis The shape of any urban poverty analysis will be largely determined by the questions being asked by those designing the profile, the extent and quality of available data, and the amount of time and money that can be committed to the development of a profile. Within these parameters, there is a range of tools that can be employed to gather data for a city poverty profile. a. Population census The population census contains basic information about all citizens in a country. While usually only conducted once a decade, the census may provide valuable information about housing and basic service access, education levels, and employment. Since the census is by definition a counting of everyone, the data can be disaggregated to the city, municipal, and neighborhood level. While the data do not include indicators of income or consumption, proxies for welfare can be developed using access to basic services (e.g., UBN). In addition, a relatively new approach has been developed that combines census and household survey data to generate poverty and inequality measures at disaggregated levels. This approach is very powerful for urban poverty analysis.13 b. Administrative data Many local authorities collect significant amounts of information about their cities, but often that information is gathered and stored in ways that make them difficult to use or access. In developing a city poverty profile, existing administrative data can prove to be a rich resource of information. Such data may include: Information on location of facilities such as schools, hospitals, public standpipes, etc. Costs and expenditures by sector and function, 13See Elbers, Lanjouw and Lanjouw, 2002, Micro-Level Estimation of Poverty and Inequality, Econometrica, and http://econ.worldbank.org/programs/poverty/topic/14460/; also see video presentation of Poverty Mapping in Urban Areas, at http://info.worldbank.org/etools/bSPAN/presentationView.asp?EID=331&PID=655 8 Tax revenue by source, and Staffing statistics, etc. c. Household surveys Household surveys offer a more in-depth understanding of living conditions by expanding the amount of information gathered from households, but carefully limiting the number of households surveyed to create a representative sample of the population. Household surveys are used both nationally and at the city level. National household surveys that may provide insight into urban poverty include: 1. Employment Surveys: information in employment and unemployment patterns and fluctuations. These also include information on household income, housing features and household demographics. 2. Demographic and Health Surveys14: are designed specifically to explore the incidence of disease and use of health facilities. 3. Living Standard and Measurement Surveys15: collect household data that can be used to assess household welfare, to understand household behavior, and to evaluate the effect of various government policies on the living conditions of the population. LSMS surveys collect data on many dimensions of household well-being, including consumption, income, savings, employment, health, education, fertility, nutrition, housing and migration.16 At the city-level the following types of household surveys may be developed to explore particular issues. Service Satisfaction and Needs Surveys17: ask city residents in-depth questions about the quality of services they receive and their needs. These will likely be tailored to address specific services, and may be used to collect data over time. Multi-topic City Surveys18: are tailor made to city needs and may collect both qualitative and quantitative data. Quantitative data primarily includes household welfare (i.e. income, assets), service access, health service utilization, public transport use etc. Qualitative data may highlight service satisfaction and perception surveys. Developing a multi-topic city survey is likely the most comprehensive way to analyze the dynamics of urban poverty in a given city. d. Participatory assessments Participatory assessments go beyond household surveys to gather more qualitative data on individual and community perceptions. There are a range of tools19 that can be used in 14http://www.measuredhs.com/ 15http://www.worldbank.org/lsms/ 16 See Grosh, Margaret and Paul Glewwe, 2000, Designing Household Survey Questionnaires for Developing Countries: Lessons from Fifteen Years of Living Standard Measurement Study, Oxford University Press. 17For example Beneficiary Assessments and Report Cards. 18See Annex 1 Case Summary 10 (Cali) 19Many of the tools of participatory assessments fall under the rubric of `participatory rapid appraisal' or PRA. While many of these techniques originated within the study of rural poverty, they have been increasingly applied to the urban context. See Annex 1: Case Summaries 4, 7, & 8. 9 conducting participatory assessments, including focus groups, community meetings, community mapping, transect walks, and in-depth interviews. Participatory assessments may be used to facilitate the selection of indicators for household surveys and/or they may be used to explore particular issues that emerge through surveys in greater depth20. e. Geographic Information Systems (GIS) GIS data use geographic location as a reference for each database record and can be very powerful within cities for identifying spatial growth patterns, slum locations, access to public infrastructure, and land use patterns. This information can be combined with census and other data to determine the spatial dimensions of poverty and access within a city. SECTION II: CASE STUDIES 4. Urban Poverty Analysis in Practice Short summaries of a number of urban poverty studies have been included in Annex I (see Box 4), with an emphasis on the specifics of methodology and data rather than specific outcomes and analysis. The studies have been selected because they represent a number of approaches to urban poverty analysis and offer a range of geographic diversity. There are no clear `best practices' regarding urban poverty analysis as a city poverty profile is most fairly judged in relation to its study objectives. From the case studies, a number of examples have been highlighted for their strengths in particular elements of urban poverty analysis. Below is a listing of several key themes and the studies that cover them well. This is intended to serve as a summary list and does not reflect the depth and subtleties of the studies. The number in brackets refers to the case summary that can be found in Annex 1. 20See Annex 1 Case Summary 13 (Household Responses) 10 Box 4: CASE SUMMARIES in Annex 1 1. Assessment of Urban Poverty in Lesotho United Nations Development Programme (UNDP). Maseru, Lesotho. December 1997. 2. Core Welfare Indicators Questionnaire Survey (CWIQ): Lagos State Federal Office of Statistics. Abuja, Nigeria. July-August 1999. 3. Social Exclusion in Urban Uruguay World Bank (J. Baker). Montevido, Uruguay. 2001. 4. Urban Poverty and Violence in Jamaica World Bank. (Caroline Moser , Jeremy Holland) Kingston, Jamaica. 1997. 5. Brazil/ Rio de Janeiro: A City Study World Bank. Rio de Janeiro, Brazil. 1999. 6. Urban Livelihoods and Food and Nutrition Security in Greater Accra, Ghana International Food Policy Research Institute et al., 2000 (research data from 1996, 1997, 1998). 7. Poverty in Vientiane: A participatory poverty assessment GHK (Janelle Plummer and Nongnut Foppes-Ayamuang) Vientiane. Laos, January 2001. 8. Poverty in Ho Chi Minh City: results of participatory poverty assessments in three districts (1999) Save the Children (Tim Bond) Ho Chi Minh City, Vietnam. November 1999. 9. Ho Chi Minh City Participatory Poverty Assessment (2003) Poverty Task Force/ Save the Children (Trin Ho Ha Nghi, Huynh Thi Ngoc Tuyet, and Bill Todd) Ho Chi Minh City, Vietnam. July-August 2003. 10. Cali, Colombia: Toward a City Development Strategy World Bank. Cali, Colombia. 2002. 11. South Africa: Monitoring Service Delivery in Johannesburg World Bank (Vandana Chandra), Johannesburg, South Africa. 2002. 12. Action Research on Urban Poverty in Harare, Johannesburg and Luanda World Bank and CEFRE. Harare, Zimbabwe, Johannesburg, South Africa, and Luanda, Angola. 1999. 13. Household Responses to Poverty and Vulnerability: Vols. 1-4 The Urban Management Programme/ World Bank (Caroline Moser) Cisne Dos ( Guayaqil, Ecuador), Angyalfold (Budapest, Hungary), Commonwealth (Metro Manila, Philippines), Chawama (Lusaka, Zambia). 1996. 14. Crime and Local Inequality in South Africa Journal of Development Economics, G. Demombynes and B.Ozler (World Bank). Forthcoming, 2004. 15. Information Based Instruments for Improved Urban Management World Bank Policy Research Working Paper. (Deichman et al.). Bangalore, India 2003. 16. Urban Services Delivery and the Poor: The Case of Three Central American Cities The World Bank, San Salvador Metropolitan Area (El Salvador), Tegucigalpa (Honduras), Panama City and San Miguelito (Panama). June 2002. Developing a profile of City Poverty In several of the studies, the objective has been to develop an overview of the conditions, extent, implications, and activities relating to poverty within a particular city. These may be carried out to complement national poverty assessments or to provide input into city development strategies or specific urban projects/ investments. Complement national poverty assessments: (1) Lesotho; (2) Lagos; (3) Montevideo; (7) Vientiane, (9) Ho Chi Minh City (2003) Input into a City Development Strategy: (5) Rio de Janeiro; (10) Cali Input into a specific project: (4) Kingston; (7) Vientiane 11 Geographic and other Disaggregations of Poverty Although urban poverty analysis is implicitly spatial, it cannot be assumed that all studies focus on the geographic disaggregation of poverty. Within densely populated cities it becomes increasingly challenging to target services and attention at the poor who often live in close proximity to their better-off neighbors. Urban poverty analysis may also disaggregate data to examine households, social risk, violence and other characteristics of poverty. Geographic: (11) Johannesburg; (7) Vientiane; (15) Bangalore By Household: (6) Accra; (13) Household Responses Social exclusion: (3) Montevideo; (12) Harare/Johannesburg/Luanda Violence: (14) South Africa, (4) Kingston Tracking Urban Poverty over time For those working to address urban poverty, measuring the extent and characteristics of poverty over time is the only way to learn if/whether poverty alleviation policies have been appropriately designed and/or targeted. The analysis of poverty over time can also provide a local lens on the impacts of macroeconomic reforms. Using longitudinal data: (13) Household Responses Emphasizing the time-bound challenges /opportunities: (5) Rio de Janeiro Creating monitoring and information systems: (11) Johannesburg; (15) Bangalore Comparison over time: (8 & 9) Ho Chi Minh City (1999/ 2003) Understanding the dimensions and characteristics of living in poverty Traditionally the bulk of poverty analysis has been on rural areas, and so there is still much to be learned about the characteristics and strategies in response to urban poverty. An understanding of the specific characteristics and dimensions of urban poverty may lead to more equitable and cost-effective policies. Descriptive: (3) Montevideo; (4) Kingston; ( 6) Accra; (7) Vientiane; (8 & 9) Ho Chi Minh City (1999/ 2003); (12) Harare/Johannesburg/Luanda; (13) Household Responses Policy Oriented: (1) Lesotho; (3) Montevideo; (5) Rio de Janeiro; (9) Ho Chi Minh City (2003) Linking poverty measures to city finances (monitoring) Local authorities are increasingly challenged to meet the dual objectives of stimulating economic growth while ensuring adequate provision of services to inhabitants. Monitoring city expenditures to determine their effectiveness in meeting these objectives can be a useful exercise. (5) Rio de Janeiro; (8) Ho Chi Minh City (1999)*; (10) Cali; (11) Johannesburg *Not the intention of the study, but a potential use thereof. 12 Measuring the poverty impacts of programs and policies (evaluation) By evaluating programs or policies (that may or may not be explicitly targeted at the poor) to determine their impact on the poor and urban poverty, city officials, planners and policy makers can learn and respond to the reasons for particular successes and/or failures. (5) Rio de Janeiro; (7) Vientiane; (9) Ho Chi Minh City (2003); (11) Johannesburg; (15) Bangalore; (16) Central America Understanding specific urban issues Often the objective of an urban poverty analysis will be to focus on a particular segment of urban life and services--such as land, crime and violence, environmental issues, slums, or urban transport. In other cases the emphasis may be on working with communities to identify their priorities and concerns. Crime and Violence: (4) Kingston; (14) South Africa Food security: (6) Accra Prioritizing issues: (7) Vientiane; (8) Ho Chi Minh City (1999); (10) Cali Innovation Using available data in creative ways, or finding unique approaches to collecting data may make urban poverty analysis more cost effective and may also uncover unique findings. Working with available data (3) Montevideo; (5) Rio de Janeiro; (14) South Africa; Methods of data collection: (2) Lagos; (11) Johannesburg Analytical approaches: (4) Kingston; (6) Accra; (12) Harare/Johannesburg/Luanda; (13) Household Responses Integration of local partners In addition to providing valuable information about a city, the process of conducting an urban poverty analysis can also offer opportunities for training and partnership building. Local partners may include local universities, NGOs, neighborhood groups and youth and women's groups. Working with local partners (7) Vientiane, (8 & 9) Ho Chi Minh City (1999/2003), (10) Cali, (11) Johannesburg, (132) Household Responses, (15) Bangalore Good overall mix Many city poverty profiles are developed to address specific issues and target particular communities and neighborhoods. Conducting a comprehensive city-wide urban poverty analysis can be costly and time consuming and few cities have the resources available to do this. (1) Lesotho, (16) Central America Issues of local economic development Some city poverty profiles may be designed and used to examine issues relating to local economic development- highlighting areas of slow or rapid growth, tracking infrastructure investments, and highlighting areas of potential development. 13 (5) Rio de Janeiro; (7) Vientiane; (10) Cali BOX 4: Lesotho: A Narrative Case Summary In the Lesotho (1997) study, the objective of urban poverty analysis was to complement the existing and extensive work on poverty in Lesotho by illustrating (to policy makers) that urban poverty exists, and requires specific attention within national poverty alleviation strategies. Given that Lesotho is a predominantly rural contry, with only 20% of its population residing in urban areas, the majority of poverty assessments in recent years have largely ignored the unique features of urban poverty. Where poverty is predominantly rural, there is a clear need to illustrate not only that urban poverty exists, but that it requires different types of policy interventions. To meet these study objectives, the researchers were careful in selecting both the type of data they collect and the persons from whom the data were collected. By income comparison alone, the urban poor are generally better off than the rural poor. However, to illustrate the multidimensionality and relative nature of poverty, the study combines income characteristics with non-income characteristics (access to services) and qualitative perceptions of poverty. Within the broad category of urban poor, there are groups that have specific vulnerabilities that are not immediately apparent. To ensure that the stories of these vulnerable groups are told, the Lesotho study included a targeted sampling (most often by approaching respondents at their place of work) of seven pre- identified vulneable subgroups: female headed households, street children, informal traders, piece job workers, shebeen men and women (part of the beer brewing industry), construction workers and their families, and retrenched mineworkers and their families. While most of the vulnerability of the targeted respondents can be attributed to insecure employment--conceptions of poverty were shown to vary by category of interviewees (i.e. being out of school is the main indicator for street children, homelessness is the most important indicator for piece job workers, and lack of basic household needs as the primary indicator identified by household heads.) Using a questionnaire (see Annex 3) with some open-ended questions, the Lesotho study measures poverty through 3 methods, (i) income indicators (comparing these with a World Bank poverty line); (ii) non- income indicators (ranging from housing to community integration) and (iii) people's perception of poverty (interiew responses illustrated the relative understandings of poverty). Although the relatively small sample size used in the study does not allow for broad generalizations or comparisons, the mixture of targeted and untargeted qualitative and quantitative household surveys used in the study reveals some of the unique features of urban poverty: vulnerability due to commoditization, greater exposure to market conditions, erosion of community structures and greater `individualization' of poverty, vulnerability as a result of crime, a preponderance of female-headed households and greater exposure to environmental risks . While urban poverty analysis is important in its own right as a tool to identify and advocate for the needs of the urban poor, it can be of even greater value if placed within a larger context. In the case of Lesotho, a summary analysis of national level forces illustrates that the logical push towards urbanization that would follow from high rural poverty is in fact being mitigated by the labor migration to South Africa (particularly mining). The 40% of rural households that do not receive remittances are also the 40% that are below the rual poverty line, illustrating that remittances play a central role in mitigating rural-urban migration. By highlighting the vulnerability implicit in relying on remittances to mitigate rural poverty, the study presents a compelling case for why attention to urban poverty and by extension, development is relevant in forming sustainable national poverty alleviation strategies. 14 SECTION III: CONCLUSIONS 5. Some Lessons and Recommendations In this paper we have tried to pull together the various methods and approaches used to analyze urban poverty with an aim to provide some background and guidance to those interested in such work. The review is based on a number of existing urban poverty studies that have been carried out in a range of cities in developing countries. The emphasis was on the specifics of methodology and data rather than specific outcomes and analysis. The paper highlights key issues relating to urban poverty analysis to demonstrate how different approaches were used to address different issues (refer to Annex 1). Several general conclusions emerged from the review that would be useful to think about when designing a study of urban poverty as outlined below. Design and Analysis Defining and analyzing urban poverty can be complex as it has many dimensions. For this reason of complexity and by extension cost, most urban poverty studies will target only a particular aspect of urban poverty. When designing a study of urban poverty, it is useful to focus on what aspects specific to the urban poor that are of particular concern and they will affect the design and approach of the study. For example, to generate a poverty map or spatial poverty profile, a mapping of slums, or access to services, quantitative data collected through a census or household survey would be required. For focusing on issues of urban crime and violence and its link to poverty, supplementing quantitative data with a qualitative approach may be more appropriate. Several approaches may be combined to capture a more comprehensive analysis of urban poverty. One of the central challenges of urban poverty analysis is the lack of available disaggregated data. Many national level surveys are only representative at the urban or possibly city level. This level of aggregation, however, does not tell us much about poverty within a given city. This means that those who wish to understand and address urban poverty issues often need to undertake their own studies to access the information required. Most of the studies we reviewed carried out some kind of data collection that is representative at a disaggregated level within cities, as well as representative for subgroups in the population. This allowed for spatial analysis, which is critical for urban planning and for targeting poor areas. Once the approach has been defined, it is also important to ensure a clear link between the information collected and the application of that information in city policies and programs. The studies presented on Johannesburg and Bangalore have both been designed to support municipalities in using information and monitoring systems to perform their work more effectively. This objective has informed what type of data is collected, how it is collected and most importantly how it is analyzed and shared. Local capacity building has also been an objective in some studies (e.g. Johannesburg and Vientiane), and not only builds skills, but also contributes to future analysis and follow up in using the available information. Data When possible, it is advantageous to use existing data sources given the high cost of collecting data. This can include census data, facilities surveys, GIS, or over-sampling an ongoing household survey in urban areas. For example, in the study on Crime and Local Inequality in South Africa used existing census and household survey data to generate a poverty and inequality map, then linked this with existing crime data to focus on the linkage of crime and 15 inequality. In Montevideo, existing household surveys were used to analyze increases in local level inequality over time. This was then supplemented with qualitative data to study aspects of social exclusion that were thought to be linked to problems of increased inequality at the neighborhood level. A majority of the studies carried out some kind of household survey to meet the specific needs of the study. Appropriate sampling is a challenge to ensure that the data are representative, and that the sample is large enough to capture the group of interest (e.g. specific urban areas, etc.). When designing surveys, it is useful to think about sustainability for follow-up surveys if monitoring progress in poverty reduction is an objective, as well as cost-efficient methods. In this paper, we have suggested that urban poverty analysis is most valuable when targeted toward specific issues. Similarly, such analysis is also most effective when conducted in partnership (international and local) with local universities and academics and with the intention of sustaining capacity in city governments to replicate the exercise. Community level surveys can also provide a wealth of information for urban poverty analysis on services and facilities, particularly if the geographic unit is relatively small. Qualitative data can provide valuable local contextual information. For example, the qualitative poverty assessment in Vientiane illustrated the interdependence and informal cost-sharing for services between poor and non-poor households living in close proximity. Once the data have been collected, it is important to make this information (both the data sets as well as the analysis and reports) publicly available. Given the high cost that goes into data collection and the huge value it can provide for research, any initiative should make provisions for making the data available on a widespread basis to researchers and others, such as the Atlas of Human Development project in Brazil (see Box 3). Timing An important consideration in designing and conducting and urban poverty analysis is the issue of time. There are two elements to consider. First, given that cities are dynamic and ever changing environments, it is important to understand how the duration of the study itself (from design through data collection, analysis, and reporting) will impact on the findings. For example if a study is launched shortly after civil unrest or a natural disaster, the findings that are published 1-2 years later may no longer be relevant to policymakers and planners. Second, in designing and conducting surveys in urban areas, experience shows that respondents may have less time available for responding to questions and thus it is particularly important to keep interviews within a reasonable time frame. It is generally difficult to carry out a survey of more than one hour. In the Johannesburg Service Delivery study for example, the team had to review and revise their draft survey extensively to ensure that it could be completed in no more than 30 minutes. Time intensive surveys, while appearing comprehensive, may in fact produce poor quality data if respondents are not interested and annoyed by the process. Cost Rough cost estimates were available for a few of the studies carried out. The cost of data collection, both qualitative and quantitative, ranged from US$20,000 ­ US$60,000. This largely depended on sample size, length of the questionnaire, and local costs. Other costs would include staffing costs for technical expertise and data analysis, which can be significant if international experts are used. While it may appear difficult to justify the initial expense of conducting analytical work, the longer-term benefits of such an investment may prove very cost-effective. Urban poverty analysis may serve as the baseline of a project monitoring and evaluation program, 16 facilitate the most appropriate targeting of activities and funds to achieve project outcomes, and provide valuable input into a city's information monitoring system. Challenges in practice Several cases illustrate the various challenges of carrying out urban poverty analysis and how these challenges were overcome. Many of the challenges were related to sampling, data collection, and definitional issues during survey implementation. Few, if any, cases have achieved a sustainable mechanism for collecting consistent information over time that can then be used for monitoring and evaluating policies and programs. In Lesotho, for example, interviews were only conducted in selected low-income areas of three towns. Thus there was no city-wide data that could put the poverty analysis in the overall urban context. Within the low-income areas, however, households were randomly selected which did capture some differences in income levels. There was also concern, common to many other surveys, of a possible bias in sampling in that it is particularly difficult in urban areas (relative to rural) to find residents at home. Most surveys skip to another randomly selected household after 2-3 attempts to find someone at home. This may bias the results in capturing larger households (where it will be more likely to find someone at home), etc. If possible, follow up visits to the households should be scheduled at different times of the day. Finally, it is difficult to capture sub-groups in urban areas that may not have a fixed residence such as pavement dwellers, street children, informal traders, who are generally among the poor. Capturing these groups may require a specially designed instrument and approach. In Ho Chi Minh City (1999) and other city studies, interviewers found that specific definitions were sometimes confusing. For example the definition of what constitutes a household or a kitchen, and description of physical structure are sometimes perceived differently by households and interviewers and thus need to be defined explicitly. There is also an emerging literature on the definition of slums and tenure, particularly in the context of the Millennium Development Goals (UN HABITAT, Cities Alliance). Considerations for designing urban poverty analysis to meet project needs From the review of cases of urban poverty analysis carried out in a range of circumstances using a range of methods, a suggested check list of issues to consider has emerged as follows: What is the objective of carrying out the urban poverty assessment? What kind of information will be needed to meet the explicit objectives? Is the information needed already available and/or can it be derived from existing data? If the information is clearly not available, what resources are available for conducting an urban poverty assessment? (money, time, and staff) What types of instruments need to be developed and piloted for carrying the urban poverty assessment and for analyzing the findings? (surveys, questionnaires, data entry forms/computers, statistical software, etc.) 17 What methodological approaches are most appropriate? Primarily quantitative data (Multi-topic or Single-topic Household Survey), Primarily qualitative data (Urban Participatory Assessment), or a Community Level survey ? Are there opportunities for mixing quantitative and qualitative approaches ? Is sample data representative at a sufficiently disaggregated level to capture: intra-city poverty characteristics at the neighborhood, zone, municipality or district level; and subgroups in the population such as pavement dwellers and street children? Who will carry out the data collection and are there mechanisms to ensure sustainability? Are there issues to be raised in the urban poverty analysis that may be sensitive to community members, politicians, donors, etc? Is it possible to address these issues early on so that they will not threaten the outcome of the urban poverty assessment? Is capacity building an objective? If so, what can be built into the effort to ensure that local partners receive as much training and participation as possible? How will the analysis be linked to specific policy and projects? What are the mechanisms for making data widely available for planners and researchers? 18 REFERENCES Papers and Websites Baharaoglu and Kessides, 2002, "Urban Poverty" in World Bank, 2002, A Sourcebook for Poverty Reduction Strategies, Chapter 16. Chen and Ravallion, 2000, "How did the World's Poorest Fare in the 1990s," Policy Research Working Paper, World Bank, Washington, D.C. Cities Alliance, http://www.citiesalliance.org/ Coudel, Hentschel, and Wodon, 2002, "Poverty Measurement and Analysis" in World Bank, 2002, A Sourcebook for Poverty Reduction Strategies, Chapter 1. Demographic and Health Surveys, http://www.measuredhs.com/ Elbers, Lanjouw and Lanjouw, 2002, "Micro-Level Estimation of Poverty and Inequality", Econometrica, and http://econ.worldbank.org/programs/poverty/topic/14460/ also see video presentation of Poverty Mapping in Urban Areas, at http://info.worldbank.org/etools/bSPAN/presentationView.asp?EID=331&PID=655 Falkingham, J. and C. Namazie, 2002, Measuring Health and Poverty: A review of approaches to identifying the poor, London, DFID Health Systems Resource Center. GHK, 2001, "Literature Review Addressing Poverty through city development strategies" Research project of DFID. Grosh, Margaret and Paul Glewwe, 2000, Designing Household Survey Questionnaires for Developing Countries: Lessons from Fifteen Years of Living Standard Measurement Study, Oxford University Press (World Bank ISBN: 0-19-521595-8 SKU: 61595). Henninger, N. and Snel, M., Where are the Poor, Experiences with the Development and Use of Poverty Maps, 2002, World Resources Institute, Washington, DC. http://pdf.wri.org/wherepoor.pdf Hentschel, J. & R. Seshagir, 2000, "The City Poverty Assessment Primer," Prepared for the Urban Management Course, Poverty Group, The World Bank. Montgomery, M.R., M. Gragnaloti, K. Burke, and E. Paredes, 2000, Measuring Living Standards with Proxy Variables, Demography, 37(2): P. 155-74. Moser, C, Gatehouse, M. and H. Garcia, 1996, "Urban Poverty Research Sourcebook", UNDP/UNCHS (Habitat)/The World Bank, Working Paper No. 5. UNHABITAT, Cities Alliance, Background Papers 1-4 for Expert Meeting on Urban Indicators, Mimeo, Nairobi, 2002. World Bank Living Standards Measurement Study (LSMS), http://www.worldbank.org/lsms/ 19 World Bank, 2004, World Development Report 2004: Making Services Work for the Poor. http://econ.worldbank.org/wdr/wdr2004/text-30023/ World Bank, A Sourcebook for Poverty Reduction Strategies, Washington, DC, http://www.worldbank.org/poverty/strategies/sourctoc.htm World Bank Urban Poverty Site: www.worldbank.org/urban/poverty/index.html World Bank Urban Upgrading Site: http://www.worldbank.org/urban/upgrading/index.html Case Studies "Assessment of Urban Poverty in Lesotho", United Nations Development Programme (UNDP). Maseru, Lesotho. December, 1997. "Core Welfare Indicators Questionnaire Survey (CWIQ): Lagos State", Federal Office of Statistics. Abuja, Nigeria. July-August 1999. "Social Exclusion in Urban Uruguay", The World Bank (J. Baker). Montevido, Uruguay. 2001. "Urban Poverty and Violence in Jamaica", World Bank. (Caroline Moser , Jeremy Holland) Kingston, Jamaica. 1997. Brazil/ Rio de Janeiro: A City Study, World Bank. Rio de Janeiro, Brazil. 1999. "Urban Livelihoods and Food and Nutrition Security in Greater Accra, Ghana", International Food Policy Research Institute et al., 2000 (research data from 1996, 1997, 1998). "Poverty in Vientiane: A participatory poverty assessment", GHK (Janelle Plummer and Nongnut Foppes-Ayamuang), Vientiane. Laos. January, 2001. "Poverty in Ho Chi Minh City: results of participatory poverty assessments in three districts (1999)," Save the Children (Tim Bond) Ho Chi Minh City, Vietnam. November 1999. "Ho Chi Minh City Participatory Poverty Assessment (2003)," Poverty Task Force/ Save the Children (Trin Ho Ha Nghi, Huynh Thi Ngoc Tuyet and Bill Todd) Ho Chi Minh City, Vietnam. July-August 2003. Cali, Colombia: Toward a City Development Strategy, The World Bank. Cali, Colombia. 2002. "South Africa: Monitoring Service Delivery in Johannesburg", The World Bank (Vandana Chandra, Shashi Kolavalli and Bala Rajaratnam, Johannesburg, South Africa. 2002. Action Research on Urban Poverty in Harare, Johannesburg and Luanda, The World Bank and CEFRE. Harare, Zimbabwe, Johannesburg, South Africa, and Luanda, Angola. 1999. Household Responses to Poverty and Vulnerability: Vols. 1-4, The Urban Management Programme/ The World Bank (Caroline Moser) Cisne Dos ( Guayaqil, Ecuador), Angyalfold (Budapest, Hungary), Commonwealth (Metro Manila (The Phillipines), Chawama (Lusaka, Zambia). 1996-1997. 20 "Crime and Local Inequality in South Africa", Journal of Development Economics, G. Demombynes and B.Ozler (World Bank). Forthcoming, 2004. "Information Based Instruments for Improved Urban Management", World Bank Policy Research Working Paper. (Deichmann et al.). Bangalore, India, 2003. "Urban Services Delivery and the Poor: The Case of Three Central American Cities," The World Bank, San Salvador Metropolitan Area (El Salvador), Tegucigalpa (Honduras), Panama City and San Miguelito (Panama). June, 2002. 21 Annex 1. Case Summaries 1. Assessment of Urban Poverty in Lesotho United Nations Development Programme (UNDP). Maseru, Lesotho. December, 1997. FOCUS Key objective of focus for data collection and analysis Assess the level and status of urban poverty in Lesotho, place the findings of the assessment within the socio-economic realities facing Lesotho, and identify areas for intervention. DURATION October-April 1997 (6 weeks). INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. INSTRUMENTS: 5-Part Questionnaire (1. Household profile, non-income indicators, household expenditures, household income, 'perceptions of poverty' (open ended) Additional questions were added for 'vulnerable' groups. Data was coded then cleaned and analyzed with SPSS. METHODOLOGY: The study used the main questionnaire in untargeted interviews within determined geographic areas. Targeted interviews, that used the questionnaire but added additional questions, were conducted with pre-defined vulnerable groups (street vendors, casual wage laborers, street children, retrenched miners, street children and construction workers) IMPLEMENTATION: required 10 enumerators, and 6 weeks. DATA and SOURCES: Type of data used; sources Economic indicators: sources of income and mean annual earnings, average income of poor households, priority expenditures. Non-income indicators (i) Housing: household size and crowding, economic activities on garden plots. (ii) Access to basic services: water supply, electricity supply, sanitation, waste disposal, environmental pollution, health services, education, transportation. (iii) Additional non-income indicators: crime and safety; governance and legal issues, social/community integration. SOURCES: Multi-topic City Survey (primarily qualitative) EXISTING DATA: 1991 & 1994 Poverty Mapping Exercises. SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. 500 limited household interviews in selected sub-areas ('known to have sizeable low-income populations') of three areas: Maseru, Maputsoe and Mohale's Hoek. Of these, 366 (households), 91 (street vendors), 15 (street children), 15 (piece job workers), 10 (construction workers), 4 (retrenched miners). The household interviews were largely untargeted (and interviews were based only on geographic location in selected communities). The individual interviews were targeted to vulnerable groups (who were interviewed at their place of work). COSTS and FINANCING: Total costs for study; financing arrangements. Estimated $113,500 IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners COMMISIONED by: UNDP, IMPLEMENTED by: IHS (Mr. Paul Rabe), National University of Lesotho (Dr. Moeketsi Senaoana), Institute for Southern African Studies (Mrs. Matseliso Mapetla) 22 NOTES: see Box 5. By building upon existing data, the study increases its relevance through filling identified gaps in knowledge. In order to get a `well rounded' understanding of urban poverty it was useful to use a sampling mix that complemented geographic location with particular sub-groups. 23 2. Core Welfare Indicators Questionnaire Survey (CWIQ): Lagos State Federal Office of Statistics. Abuja, Nigeria. July-August 1999. FOCUS Key objective of focus for data collection and analysis To test the feasibility of a rapid survey methodology and instrument to collect data on basic human development indicators. While the Lagos study was intended as preparation for national survey, the findings were utilized as a management tool for local authorities. CONTEXT: Pilot study for proposed National General Household Survey. DURATION 12 days. July-August 1999. INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. METHODOLOGY: CWIQ is designed to gather information on human development indicators, measuring access, utilization and satisfaction with social services on a single visit to households. INSTRUMENTS: A short questionnaire is developed. During the interviews the respondents' answers are entered onto a bubble sheet. This sheet is fed, at regular intervals during the data collection phase, into an optical scanner, which loads the information into a database. The data collection and input process are thereby combined to allow for a rapid turnaround time. IMPLEMENTATION: 6 groups (of 4 enumerators, and 1 supervisor). Each group covered approx. 20 EA, and on average each EA conducted 4 Household interviews per day. Data collection in 12 days. DATA and SOURCES: Type of data used; sources DATA: 8 types of data were gathered: Demography of household members, Education of household members, Health of household members, Employment of household members, Household assets, Household Amenities, Poverty predictors, Child nutrition (through anthropomorphic measurement). SOURCES: Multi-Topic City Survey using CWIQ tools. SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. 5 zones of Lagos (each containing 20 enumeration areas). 1054 households interviews conducted. For each Enumerator Area (EA) 10 households were selected from a list of housing units compiled for the General Household Survey (a national project). COSTS and FINANCING: Total costs for study; financing arrangements. (Estimate) $20,000 IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners COMMISSIONED by: Federal Office of Statistics (with financial and technical assistance from the World Bank). NOTES The CWIQ approach allows for rapid collection and review of data, and may facilitate the ability of cities to collect and analyze data on a more frequent basis. This may be very useful as part of developing systems to monitor and evaluate programs and policies. However, this study also illustrates the challenges of identifying an appropriate sample size to make the data useful. In a city of 15 million, this presents an enormous challenge. 24 3. Social Exclusion in Urban Uruguay The World Bank, 2001. (J. Baker). Montevido, Uruguay. FOCUS Key objective of focus for data collection and analysis To analyze how spatial polarization may be linked to 'social exclusion'. To identify the characteristics of poverty among vulnerable groups. CONTEXT: Conducted as part of a national poverty assessment of Uruguay. DURATION 8 weeks. INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. METHODOLOGY: For qualitative analysis in 6 marginal urban neighborhoods: Focus groups (30), interviews with key informants (25), group interviews (8), direct and participatory observation, area history and trajectory, and social maps. For quantitative analysis: application of econometric analysis to existing data sets. IMPLEMENTATION: Five weeks for quantitative assessments. For qualitative assessment, 8 weeks (including planning and implementation). Research team consisted of international consultant and local team (20 in total). DATA and SOURCES: Type of data used; sources DATA: (i) Spatial Polarization: Application of econometric analysis to existing 1989-1996 census section (neighborhood cluster) data. (ii) Characteristics of Marginal Neighborhoods: qualitative measurement of employment, access to services and resources, access to social networks. The focus of both the qualitative and quantitative data was to better understand the characteristics of vulnerable groups. These were identified as Children in poverty, Inactive male youth (15-24), Teenage mothers, Female household heads with low income, Unemployed male adults, and Older (50+) women with low income. SOURCES: Combination of existing census data, and Participatory Assessments. SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. 6 neighborhoods selected by using recent census data to determine which areas had 'high risk' -- low levels of human and social capital variables (i.e. educational attainment, socioeconomic composition of household, percentage of single teenage mothers). COSTS and FINANCING: Total costs for study; financing arrangements. $30,000 (qualitative data collection and analysis), $10,000 (quantitative data analysis (data set already available). IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners COMMISIONED and IMPLEMENTED by: The World Bank, and local consultants (NGOs) NOTES This study highlights the need for disaggregated data for targeted policies. The findings illustrated that the poor in Montevido have become spatially polarized within the city and the effects of this polarization may not be apparent through aggregate data on income distribution. Uses a good mix of econometric and quantitative data to inform and build the case for the value-added of qualitative data. 25 4. Urban Poverty and Violence in Jamaica World Bank, 1997. (Caroline Moser , Jeremy Holland) Kingston, Jamaica FOCUS Key objective of focus for data collection and analysis To elicit and identify perceptions of four different aspects of violence. (i) Causes. (ii) The interrelationship of violence and poverty. (iii) The impact of violence on employment, the economic and social infrastructure, and local institutions. (iv) The perceived means by which governments , communities, households and individuals could work to reduce violence. CONTEXT: As part of an analysis for the implementation of a Social Investment Fund. DURATION September-October 1995. INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. METHODOLOGY: PUA (participatory urban appraisal) which includes use of focus groups, seasonality analysis, trend analysis, causal impact analysis (diagrams), solar system analysis, and other participatory methodologies. PUA is described as 'an iterative, flexible research approach that is appropriate for investigation of complex causal relationships (such as those that surround violence in Jamaica)' DATA and SOURCES: Type of data used; sources To capture the relationship between poverty, social institutions and violence, the researchers framed their data collection around the notion of vulnerability as a function of 5 assets. DATA: Measurement of Assets: Labor, Human Capital, Productive Assets, Household relations, and Social Capital. SOURCES: Participatory Urban Appraisal. SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. 5-communities within Kingston that exhibited different types of violence (determined by levels of drug activity, political affiliation, and economic circumstances.). Purposive sampling: identifies study communities considered representative of the issue under investigation- and uses in-depth investigation with a number of groups within the sample so as to be representative of the community. COSTS and FINANCING: Total costs for study; financing arrangements. Not Available IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners COMMISIONED and IMPLEMENTED by: The World Bank, NOTES Violence in Jamaica is a predominantly urban problem that affects the urban poor disproportionately. This study offers an example of an urban poverty assessment that disaggregates with reference to a particular facet of urban poverty. Uses a highly participatory methodology to understand and analyze the complex causal relationships related to urban violence. Focuses on understanding the relationships between the `assets' of the urban poor and the dynamic relationships between these assets and urban violence. A clear finding of the report was the linkage between high levels of violence and lack of work (labor asset) and vice versa. Another finding illustrated the cyclical nature of `area stigma' where high rates of violence make mobility within the community dangerous, thus resulting in reduced access to education (human capital) and lack of investment in communities (productive assets, social capital). 26 5. Brazil/ Rio de Janeiro: A City Study World Bank. Rio de Janeiro, Brazil, 1999. FOCUS Key objective of focus for data collection and analysis To examine the municipalities' expenditures and programs in light of new challenges (declining economic development and increasing vulnerability of the poor) facing the city. Using this analysis the report provides suggested priorities and action areas to make Rio a more competitive, fiscally sound and pro-poor city. Three core areas of analysis: (i) Examine whether programs and expenditures are reaching the poor. (ii) Determining what lessons can be learned from other cities implementing similar programs and, (iii) Assessing the fiscal and institutional resources available to the city. CONTEXT: This report was written in collaboration with Rio City's Secretariat of Strategic Affairs with the express purposes of implementing the 1996 Plano de Metas (which was designed to operationalize an earlier participatory municipal strategy). DURATION N/A INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. METHODOLOGY: This study is a comprehensive urban assessment, in which urban poverty is dealt with explicitly only in part. However the analysis of municipal programs and expenditures provides valuable insight into the quality and reach of services, and the examination of growth industries provides a useful discussion of job development as a poverty alleviation strategy. DATA and SOURCES: Type of data used; sources DATA: Using existing data sources, the paper provides an analysis of: Composition of city GDP (by sector), Extent/amount of federal transfers, Trade and industry performance, Characteristics of poor, Social program expenditures, Effectiveness of targeted social programs, and City revenues and transfers. SOURCES: Poverty data gathered from existing data: 1991 census, 1996 Household Survey (PNAD) and 1997 Living Standards Measurement Survey. SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. N/A COSTS and FINANCING: Total costs for study; financing arrangements. (Estimate) $30,000 of which approx. $15,000 for data analysis (mapping existing data with programs). IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners COMMISSIONED BY: The World Bank. IMPLEMENTATION: In collaboration with Rio Municipality- but intended as Bank recommendations. NOTES Comparisons with other developing/developed cities to help analyze trends in data (for ex. industry to service ratios in economically dynamic cities) provide a useful and realistic grounding for setting objectives. The data analysis illustrates that, contrary to popular and policy conception, the poor are NOT spatially concentrated in the favelas and that means-testing for effective targeting of social programs requires much better data on the characteristics and location of the urban poor in Rio. 27 6. Urban Livelihoods and Food and Nutrition Security in Greater Accra, Ghana International Food Policy Research Institute et al., 2000 (research data from 1996, 1997, 1998). FOCUS Key objective of focus for data collection and analysis To provide an understanding of the nature of urban poverty and the relationship between urban poverty and food insecurity (or malnutrition) in Accra. This report looks at both food insecurity and child nutritional status- seeking to determine how the strategies employed by the urban poor to secure their livelihoods affect the household's food security; the care of household members, especially children; and the resulting health and nutritional outcomes. CONTEXT: The study report is a compilation of two related and published studies (Ga Mashie Study Team: 1996, Accra Study Team: 1998.). DURATION January-April 1997 INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. METHODOLOGY: There were four project phases over 3 years. 1. Initial roundtable meetings and key informant interviews to determine 'information gaps', 2. Participatory rapid appraisal studies (1996) in 2 communities (one central, one peri-urban), 3. Qualitative city-wide household case studies (to facilitate in survey design and also develop descriptive case material). Focus group interviews were conducted around specific topics (coping strategies, livelihoods, household relations, etc.) 4. Integrated quantitative and qualitative Household survey (1998). In addition, analysis of data includes multivariate regression investigation of the determinants of child nutritional status. IMPLEMENTATION: Team of 25 enumerators conducted surveys in period between January-April 1997 (enumerators had undergone 8 weeks of training in preparation.) DATA and SOURCES: Type of data used; sources DATA: The analytical approach of the study focused on first examining urban livelihood strategies (income and expenditure) and then considering livelihood outcomes (household food availability, health and care practices, nutritional status, etc.) Data collected in this process included: Household demographics; Employment and self employment; Adaptive strategies; Credit, transfers and other incomes; Agriculture, livestock and fishing; Food habits and coping strategies; Food consumption and expenditure; Non-food expenditures; Health and care (regarding child-care); Hygiene (spot check), Anthropometry (to measure nutrition and health status of women and children). SOURCES: Multi-topic City Survey, Participatory Assessment, (with some reference to national Ghana Living Standards Survey GLSS). SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. 559 Household surveys in 16 enumerator areas (out of 879 EA in greater Accra region). That is 36HH/EA. This was intended to be representative cross-section of Accra, however because of the focus on food security the sample selected only HH where children under the age of 3 were present. Other than this, the sample survey was random (i.e. not targeted to only-poor neighborhoods/households.) COSTS and FINANCING: Total costs for study; financing arrangements. Not Available IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners IMPLEMENTATION: A collaboration between IFPRI, Noguchi Memorial Institute for Medical Research of the University of Ghana, and the World Health Organization. A companion report has been published by WHO: WHO Multi-country Study on Improving 28 Household food and Nutrition Security for the Vulnerable: Ghana. Achieving Urban Food and Nutrition Security for the Vulnerable in Greater Accra.2000.) NOTES This comprehensive study offers a very thorough examination of the complex causation relating to food insecurity- relating it to urban livelihoods and child-care. The study of the linkage between food security and child care is unique and required the development of an indicator to measure care and evaluate its impact on nutritional status in an urban environment. A key finding from the report is that 'all the variations in income in Accra, as well as health and nutrition outcomes, is explained by factors that vary at the household and individual levels and not by community-level effects'. This has valuable implications for policy. 29 7. Poverty in Vientiane: A participatory poverty assessment GHK (Janelle Plummer and Nongnut Foppes-Ayamuang) Vientiane, Laos. January 2001. FOCUS Key objective of focus for data collection and analysis To fill a perceived gap in knowledge about dimensions of urban poverty in Vientiane (national poverty assessment included only 2 households from Vientiane). As a qualitative assessment the objective of the study was to provide a `description of poverty in terms of what and why rather than how much and how many. It seeks to describe the nature of poverty, the livelihoods of different types of poor people and the different experiences of poverty.' CONTEXT: Conducted as part of an analysis for the planning process of a Vientiane Urban Infrastructure and Services Project (ADB). DURATION August-September 2003 INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. METHODOLOGY: a) Rapid Assessment: Because Lao does not have an official definition of poverty, it was necessary for the research team to conduct a rapid assessment to gather some information on where the poor may be concentrated within Vientiane. b) Training Local Team: An objective of the project was to build local capacity in conducting poverty assessments, so selection and training of a local team was an important element of the methodology. c) Conducting the Assessment: Various participatory methodologies were used, primarily Focus Group Discussions, Individual Discussions that were organized around semi- structured interviews, as well as Transect Walks (participatory mapping exercise). IMPLEMENTATION: 12 fieldworkers (largely from University of Vientiane), 3 team leaders (Department of Non Formal Education) and 2 co-advisors from PADETC. DATA and SOURCES: Type of data used; sources DATA: Interviews and focus groups used a list of questions to guide the data collection process, these included: Who are the poor (household characteristics)? Why are they poor (perceptions of poverty)? What are their problems (municipal services, employment, etc.)? What are the specific problems of vulnerable groups (female headed households, the elderly, etc.)? How do they cope on a daily basis (HH income & expenditure, coping mechanisms)? What forms of formal support are available (government programs, social networks, etc.)? What are service problems and needs of poor neighborhoods (water, sanitation, electricity, etc.)? Prioritization of service requirements in neighborhood area (community ranking of service needs). SOURCES: Participatory Assessment SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. The views of 744 households were obtained (through interviews, group discussions, etc.), in 8 villages (representing all 4 districts) within the urban area of Vientiane. COSTS and FINANCING: Total costs for study; financing arrangements. Not Available IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners COMMISSIONED as part of VUISP Project Preparation (Asian Development Bank). IMPLEMENTATION by GHK International, with support from a local NGO-- Participatory Development and Training Centre (PADETC) and the Ministry of Education. 30 NOTES Qualitative data is presented through a mix of charts and diagrams as well as narrative case studies--that present concepts such as social exclusion and vulnerability in a meaningful/tangible way. The data on respondent ranking of problems is disaggregated by gender and age illustrating the ways in which poverty is interpreted and felt differently by different segments of the population. In understanding the livelihood strategies of the poor, the assessment highlighted the interdependence between poor and non-poor households, offering valuable insight into service delivery policy, where targeting may fail to take into account of such relationships. 31 8. Poverty in Ho Chi Minh City: results of participatory poverty assessments in three districts (1999) Save the Children (Tim Bond) Ho Chi Minh City, Vietnam. November 1999. FOCUS Key objective of focus for data collection and analysis To understand poverty and its causes from the perspective of poor people, and to understand their priorities and perceptions of poverty alleviation (both through their own coping mechanisms as well as through government programs). CONTEXT: Developed in part to complement the quantitative household survey data from the Vietnam Living Standards Survey (1997/1998). This study was one of four such studies carried out in Vietnam (coordinated by the World Bank). DURATION April 1999. INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. METHODOLOGY: This report is the compilation of a number of participatory poverty assessments that were conducted using the following methods: 1. Collection of secondary data 2. Mapping of household units. 3. Household wealth ranking. 4. Household interviews based on questionnaires (70/ district) 5. Adult focus group discussions (used brainstorming, trend analysis, poverty tree, listing and ranking methods) 6. Group discussions with children (used listing, mapping, and drawing). 7. Individual interviews for case studies 8. Team meetings for enumerators to share experiences. IMPLEMENTATION: Three teams (one per district) consisting of 11 people. Team members represented a range of public sector and civil society organizations. All team members received 5 days of training. Data collection was conducted over a period of 3 weeks. DATA and SOURCES: Type of data used; sources DATA: The questionnaire and interviews aimed to collect the following types of qualitative data: Who are the poor? Why are they poor? Livelihood strategies and Coping mechanisms, Trends in poverty at community and household levels, Main concerns of the poor, and Participatory assessments of Anti-poverty strategies and institutions combating poverty. SOURCES: Participatory Poverty Assessment. SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. Conducted in 3 districts defined by the local authorities as "poor". a) 14 Adult focus groups (of 6-12 persons/district) to discuss open-ended questions on poverty. b) 34 children group discussions (in age groups of 6-10, 11-14, and 15-18). c) Household interviews (70/district) were selected on the basis of household wealth ranking exercise- with the objective of interviewing 40 'very poor', 15 'average', and 5 'better-off' households per district. COSTS and FINANCING: Total costs for study; financing arrangements. Not Available IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners COMMISSIONED BY: The World Bank. IMPLEMENTATION: Save the Children (coordinated the written report); assessments were carried out by a team of 50+ people including Ho Chi Minh City Hunger and Poverty Reduction (HEPR) board, district and ward 32 committees, the Social Development Research Centre, the Institute of Social Sciences in Ho Chi Minh City, the Youth Research Institute in Hanoi, the Open University (Ho Chi Minh City), Save the Children UK, Terre des Hommes and CARE International. NOTES: As a participatory assessment the study emphasizes the voice of those interviewed, capturing these in illustrative and informative narrative story boxes. Focus group discussions on Anti-poverty programs encouraged participants to identify and rank the services that were aware of and used (in some cases respondents were unfamiliar with and thus not using available services). This can be a useful monitoring tool for those implementing such programs. The study highlighted neighborhood specific poverty issues and emphasized through evidence and recommendations the need for local authorities to have greater autonomy over implementing local anti-poverty programs. 33 9. Ho Chi Minh City Participatory Poverty Assessment (2003) Poverty Task Force/ Save the Children (Trin Ho Ha Nghi, Huynh Thi Ngoc Tuyet and Bill Todd) Ho Chi Minh City, Vietnam. July-August 2003. FOCUS Key objective of focus for data collection and analysis To explore the grassroots perspectives on poverty trends and causes, and provide feedback on certain pro-poor policies initiated by the government, namely: (i) poverty reduction, (ii) grassroots democracy, (iii) public administration reform, and (iv) migration and urban issues. CONTEXT: This participatory poverty assessment (PPA) is one of a series of 12 PPA's that have been carried out by the Poverty Task Force in 2003 to provide a qualitative complement to the Vietnam Household Living Standards Survey, and to inform the Comprehensive Poverty Reduction and Growth Strategy (CPRGS) secretariat on the progress of implementation of the strategy (in place since 2002). This PPA builds upon the work done by Save the Children in 1999 (case study included) and follow up work done by the CPRGS Consultation in 2001. DURATION August 3 until August 16, 2003. Two weeks. INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. METHODOLOGY: (i) Wealth ranking (four in each ward), (ii) Focus Group discussions with adults, young people, and children (9 in each ward) (iii) Focus Group discussions with district authorities and small and medium sized enterprises (1 with each group in each district) (iv) Individual interviews (20 in total). IMPLEMENTATION: The PPA was conducted by 47 researchers with varied backgrounds including government organizations, mass organizations, academic institutions and led by Save the Children, UK. DATA and SOURCES: Type of data used; sources DATA: (i) Perceptions of causes and trends in poverty, poverty dynamics, employment and vulnerability, (ii) Progress in strengthening democracy at the grassroots level (with respect to Grassroots Democracy Decree), (iii) How the reform of public administration is taking place at local levels of government and (iv) migration in an urban context. All data is integrated into the narrative of the text with some charts highlighting perceptions of poverty and indicating disparities between official and community perceptions of effectiveness of local democratic participation measures. SOURCES: Participatory Poverty Assessment. SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. Conducted in 4 wards of 2 urbanizing districts: An Lac Township (pop: 47,920) and Tan Tao Commune (pop: 61,023) of Binh Chanh District (pop. 461,647) and Ward 4 (pop: 33,589) & Ward 5 (pop: 32,695) of District 8 (pop 538,547). Each of the wards are divided into cells, with an average of 150 cells per ward. The wards were selected on the basis of their rapid growth (ranging from 10- 60%) and their high proportion of migrants (ranging from 16-65%). In total, the study had the participation of 370 poor people. This is roughly one third of the 1,248 poor households that were defined by the government's Hunger Eradication and Poverty Reduction (HEPR) programme. In order to ensure the conclusions reached were reliable, valid and controlled biases the research term employed methods of cross-checking and triangulation 34 of data. COSTS and FINANCING: Total costs for study; financing arrangements. Approximately $25,000 IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners COMMISSIONED BY: (for all 12 PPAs) Poverty Task Force, Government of Vietnam with support from World Bank, ADB, AusAID, DFID, GTZ, JICA, SCUK and UNDP. IMPLEMENTATION: (for all 12 PPAs) Action Aid, Save the Children (UK), local NGOs and local research institutes including CRP, the Institute of Sociology (IOS), the Long An Primary Health Care Center, the Rural Development service Center (RDSC) and Vietnam Solutions. NOTES: In building on the reports of 1999 and 2001, this PPA identified the changing response by communities and local officials to the plight of poor migrants. Local officials recognize that poor migrants do not receive adequate access to social services, often pay considerably more (7-8 times) for basic services (water, electricity, etc.) and are among the most vulnerable. The study also illustrated how the influx of migrants were actually improving the conditions of non-migrant poor who were capitalizing on migrant need for accommodation and foodstuffs. The study offers a unique lens on the Grassroots Democracy Decree by comparing community responses to the responses of officials on how the participatory democracy measures are being implemented. The findings reveal that there are still considerable gaps in the effectiveness of the policies. The review of the Public Administration Reform (PAR) highlights some of the practical challenges of PAR, particularly in the area of housing and land (where it is suggested that additional decentralization would be most efficient). 35 10. Cali, Colombia: Toward a City Development Strategy The World Bank (Alexandra Ortiz) Cali, Colombia. 2002. FOCUS Key objective of focus for data collection and analysis To conduct a city-wide identification and prioritization of the city's main problems. To develop an analytical framework of the prioritized issues to feed into the city development strategy. While this paper provides insight into urban poverty in Cali (Ch. 4), it was not designed as an urban poverty assessment. CONTEXT: This report is intended as an information gathering advisory tool to the development of a World Bank funded, Cali- implemented City Development Strategy. DURATION (data collection by EPSOC) September 1999 INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. METHODOLOGY: There are two stages that have been documented. 1. City-wide identification and prioritization of problems: a participatory consultation with 147 participants. A six step process was used to allow participants to identify and prioritize challenges and propose approaches to addressing them. 2. In-depth research and analysis conducted for each of the 6 themes (in order community preference): (i) Economic reactivation (employment); (ii) Social development (poverty alleviation), (iii) Urban violence; (iv) Education; (v) Institutional modernization (governance, corruption); (vi) Spatial management (urban planning). DATA and SOURCES: Type of data used; sources DATA: Collected on the six core themes, as well as on basic poverty characteristics. SOURCES: Several papers and studies were commissioned for the study: These include (i) A review of national Household Survey (1994-1998), (ii) A review of poverty related studies by the Socioeconomic Research Center at Universidad del Valle (by CIDSE), (iii) An Institutional Map (by CIDSE), A small household survey to assess resettlement needs of a small community (by the Ashanty Youth Group), A paper on the Economic Prospects for Cali (by the firm Mision Siglo XXI). While the bulk of input into this report consisted of analysis of existing data, a Household Survey (1912 HH) was developed and conducted to assess satisfaction with municipal surveys (by EPSOC). This EPSOC survey will be described below. SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. 1,912 households that were representative of 5 different geographic areas and 6 socioeconomic strata. The Colombian statistical institute defines socioeconomic status as a function of `unsatisfied needs' (housing characteristics, etc) and is determined at the level of one square block of housing units. These strata are used for targeting subsidies. The survey gathered data on household income and included modules on Housing; Access to and satisfaction with basic services; Education and Health; the Labor market, Food security, Participation in city affairs, and Priorities of the population. COSTS and FINANCING: Total costs for study; financing arrangements. (Estimated) $50,000 for data collection, plus an additional $50,000 for analysis of papers and compilation of final report. 36 IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners COMMISSIONED BY: The World Bank to support the city of Cali. IMPLEMENTATION: Studies commissioned from a range of partners, but analysis conducted by the World Bank. NOTES When the income data from the household surveys (EPSOC) was compared to the socioeconomic strata it was found that the strata did not provide an adequate measure of poverty (there was considerable income heterogeneity within all of the strata) and highlighted a need to reconsider the use of strata as a means to targeting subsidy programs. As part of the household survey, respondents were asked to rank their priorities with regards to municipal services. Comparing these preferences with municipal expenditures provided a useful tool for policy makers. Similarly, when municipal expenditures mapped by geographic areas were compared with information on geographic concentrations of poverty and wealth it was noted that a disproportionate amount of expenditures went to better off areas. 37 11. South Africa: Monitoring Service Delivery in Johannesburg The World Bank (Vandana Chandra (Task Manager), Shashi Kolavalli and Bala Rajaratnam (Consultants), Johannesburg, South Africa. 2002 FOCUS Key objective of focus for data collection and analysis To pilot a simple and affordable survey that looks at how the status of service delivery changes on the ground, particularly in poorly served areas, and to integrate the generation and use of information with political processes to give voice to the city's poor residents. The long term outcome of this study would be the development and use (by service providers, policy makers and citizens) of a service delivery monitoring mechanism. CONTEXT: This study is part of a series of studies commissioned for the city of Johannesburg to look at issues of local economic development and service delivery. The City of Johannesburg has developed a number of strategic development plans- the most recent and far reaching being `Vision 2030'. DURATION Between mid August and end September 2001. INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. METHODOLOGY: Identify 'poorly served areas' or clusters (using 1996 Census data) with the same (poor) service delivery characteristics. Select survey sample. Develop questionnaire and conduct household survey using hand-held computers. INSTRUMENTS: The key innovation for this study was (1) cluster survey methodology for sampling; (2) the use of hand-held computers, or palm pilots that transferred data into Excel; (3) speed, affordability, accuracy and consistency in data analysis. The palm pilots made data collection easier (user-friendly interface), and more efficient (catching errors as they occur). Survey instruments were also integrated with GIS (Geographic Information Systems) data. A 30-minute survey was developed to collect information on access to basic services, household expenditure on services, household priorities, and educational/employment status of HH members. IMPLEMENTATION: 5100 households in 6 weeks by a team of 20 enumerators. DATA and SOURCES: Type of data used; sources DATA: Housing quality, Land, Toilets/sanitation, Water, Community priorities (regarding services), public infrastructure (telephones, waste removal, power supply, transport, health services, schools, police/ambulances/safety), Employment Status, and Payment for services/ Cost recovery. SOURCES: Multi-topic City Survey and Population Census (1996) SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. Cluster Survey methodology: After an initial assessment of the 1996 census data, it was determined that 921 enumerator areas, with 125, 409 households met the criteria of being 'poorly served' (in at least one of three services: water, sanitation and electricity). In the interest of keeping the survey to below 6000 households, only 20% of the poorly served EAs were surveyed, resulting in 5,100 household surveys carried out. Within the EA's, households were selected randomly and their ground location was identified on the GIS to enable production of detailed maps of how the status of service delivery on the ground changed between 1996 and 2001. COSTS and FINANCING: Total costs for study; financing arrangements. Background work, methodology preparation, survey costs including sampling, programming of PALMs: $59,000 Total (including data analysis and report writing): $79,000 38 IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners COMMISSIONED BY: The World Bank IMPLEMENTED BY: The World Bank with survey and GIS consultants; financial support was also provided by the Municipal Government of the City of Johannesburg. NOTES In aiming to generate an 'information system' that will be directly linked into the service delivery and governance systems requires consideration of (i) how the data links (or can be linked) with existing and forthcoming measurements (census, etc.) (ii) what incentives are needed and obstacles faced in creating an information system that is useful, cost-effective and transparent. The data collection instruments and the excel sheets that display the data were left with and shared among the relevant offices in the City of Johannesburg to facilitate next steps. 39 12. Action Research on Urban Poverty in Harare, Johannesburg and Luanda The World Bank and CEFRE. Harare, Zimbabwe, Johannesburg, South Africa, and Luanda, Angola. 1999. FOCUS Key objective of focus for data collection and analysis To measure the level of urban poverty, social exclusion and social initiative in Harare, Johannesburg and Luanda, and establish criteria to improve future urban poverty programs and projects. The action research aimed to answer questions on (i) the extent and depth of social exclusion in the 3 cities, (ii) the relationship between social exclusion and urban poverty, (iii) the impact (and the extent thereof in the 3 cities) that civil society (social initiative) has in promoting urban social development, and (iv) the positive influence that policy can have in supporting social initiative (and combating social exclusion) as part of poverty prevention. DURATION 13 months between July 1998- July 1999 INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. METHODOLOGY: Four phased project 1. Preparatory (literature review) studies and project design 2. Establishment of working networks and finalizing project design, 3. Field research (February- April 1999) 4. Data analysis and final report. Four main areas of inquiry: 1. Poverty [relied primarily on existing studies and data.] 2. Social Risks: defined as the elementary forces that drive the process of social exclusion [conducted key informant interviews with public administration officials, police force representatives, local leaders (trade unions/political parties/citizenship groups/religious), and health service professionals. 3. Social Initiative: defined as a measure of civil society's capacity to provide social protection to people.[conducted in-depth Interviews with leaders and representatives of civil society organizations.] 4. Policy: an analysis of urban policies with a focus on , policies against poverty, policies against social exclusion, and policies in support of social initiative. [conducted key informant interviews with city and national policy makers. INSTRUMENTS: Social exclusion Rapid Questionnaire (Q-RES), Social Initiative Rapid Questionnaire- etic (QRIS-ET), Social Initiative Questionnaire -emic (QRIS-EM), Questionnaire on Policies (QPOL) DATA and SOURCES: Type of data used; sources DATA: 1. Poverty. 2. Social Risks: measured with relation to: Habitat, Health, Employment: Intelligence, Crime, Gender, Family, Communication, Public Administration, Institutional disorder, Social Security. The social risk data was analyzed to determine localization (where risks are concentrated), specification by social groups (risk incidence among certain groups) and diachronization (risk factor trends in recent years) 3. Social Initiative. 4. Policies: Indices of Social Risk and Social Initiative were developed explicitly for this research. SOURCES: Single-Topic City Surveys, GIS SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. 1. Social Risks: 78 territorial units (28/Harare, 26/Luanda, and 24/Johannesburg). Key informant interviews: 580 (213/Johannesburg, 197/ Harare, 170/ Luanda) 2. Social Initiative Analysis: a) Key informant interviews (89/Johannesburg, 81/Harare, 78/Luanda). b) In-depth Interviews with leaders and representatives of civil society organizations. (30/city) 3. Policy: Key informant interviews (15/Harare, 8/Luanda, 8/ Johannesburg) 40 COSTS and FINANCING: Total costs for study; financing arrangements. Not Available. IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners COMMISIONED BY: The World Bank/IBRD IMPLEMENTED By: CEFRE with local teams from Habitat Angola (Angola), Community Agency for Social requirement (CASE, South Africa), Department for Rural and Urban Planning/ University of Zimbabwe (Zimbabwe). NOTES This research uses existing data to conduct poverty assessments, and supplements this information with new data (and methodologies) on more complex elements of poverty; 'social exclusion' and 'social initiative.' The paper provides some interesting geographic (by EA) mapping of social risk factors. 41 13. Household Responses to Poverty and Vulnerability: Vols. 1-4 The Urban Management Programme/ The World Bank (Caroline Moser) Cisne Dos ( Guayaqil, Ecuador), Angyalfold (Budapest, Hungary), Commonwealth (Metro Manila (The Phillipines), Chawama (Lusaka, Zambia). 1996-1997. (Also: Urban Poverty Research Sourcebook: Modules I&II, Caroline Moser et al. Urban Management Programme/World Bank. Sept.1996. FOCUS Key objective of focus for data collection and analysis The study explores how poor households in four very different cities respond to changes in economic circumstances and labor market conditions. There are four key elements to this; (i) To diagnose poverty trends within poor urban communities during crisis and economic reform. (ii) To identify how far both household and intra-household level factors diminish or increase the capacity to respond to conditions created by macroeconomic change and reform. (iii) To clarify the strategies by urban poor households and different members within them to reduce vulnerability and prevent increased impoverishment during the last decade. (iv) To identify critical poverty interventions to minimize welfare loss and ensure well-being during. DURATION 1996-1997 INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. METHODOLOGY: This study uses an analytical approach towards poverty and vulnerability that highlights the resilience of the urban poor. It suggests that the poor use their assets (defined in terms of labor, human capital, housing, household relations, and social capital) as a buffer against vulnerability. The study, in measuring household responses to adversity, focuses primarily on how the poor use their assets to mitigate negative impacts. There were three phases to the research process: 1. Contextual research (select target communities, longitudinal data extraction, background research, mapping of survey areas) 2. Research Surveys (develop and pilot surveys, identify sample and sub-sample, define coding procedures, collect data, data entry and cleaning) 3. Analysis and dissemination of results. INSTRUMENTS: Sample survey longitudinal rend data (1978-1992, with 42 comparative variables), Random Sample Survey, Community Level Survey, Sub-Sample Survey (semi- structured in-depth interview to provide a qualitative complement to the RSS. The SS Survey was conducted after the RSS and CLS.) A social policy paper and a macro-economic paper conducted in each of the sites was also used to address the key areas of inquiry. NOTE: The availability of longitudinal data was a requirement for site selection. DATA and SOURCES: Type of data used; sources DATA: All instruments (surveys and papers) addressed each of the areas of data collection with differing degrees of specificity and depth. The data collected included: Socioeconomic profile of the household, Access and reliability of household employment and income, Work patterns of household members and balancing gender roles, Access and reliability of facilities, Access and reliability of physical and social services. SOURCES: Multi-Topic City Surveys, Longitudinal Data (collected from a variety of sources) SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. In each of the research sites, the research community was selected on the basis of being a low-income settlement, as there being available longitudinal data that could facilitate comparative analysis between sites. Random Sample Survey (200 households/site: respondents predominantly women), Sub- Sample Survey (30 women/site from the sample survey) 42 COSTS and FINANCING: Total costs for study; financing arrangements. Not Available IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners COMMISSIONED BY: The World Bank IMPLEMENTED BY: The World Bank with field work facilitated by local women's NGOs. NOTES 7 volumes of reports were produced for this study, 4 case studies, 1 summary and 2 very useful modules on urban poverty research. These studies are unique in that they (i) take a micro-level approach that combines households and community level responses, (ii) have access to a long period of observation, and (iii) provide a comparative framework for analysis and comparison. There were 6 primary findings in the report. 1. A frequent response by poor households to declining real incomes is to mobilize additional labor-principally that of women, but also children. 2. The impact of reduction in public spending on social and economic infrastructure (in the 1980's and 1990's) was felt most severely by the poor who are unable to substitute public with private services. 3. Housing is an important productive asset that can cushion households against severe poverty, and land market regulation can either create opportunities to diversify its use or foreclose them. 4. Changes in household structure to strengthen family support networks are both a result of vulnerability and a strategy to reduce vulnerability. 5. Strategies to reduce household vulnerability often impose unequal burdens on household members- particularly women. 6. The pressure of economic crises can exert opposing forces on social capital- both strengthening it (as reciprocity networks are called into play), and eroding it (as households ability to cope deteriorates and community trust breaks down). 43 14. Crime and Local Inequality in South Africa Journal of Development Economics, G. Demombynes and B.Ozler (World Bank). Forthcoming, 2004. FOCUS Key objective of focus for data collection and analysis This is a piece of analytical work that uses existing local crime data to determine 1. the theoretical underpinnings of crime (comparing sociological vs. economic models) 2. how the relative position of a community among neighboring areas may be associated with crime, and 3. whether crime is particularly prevalent in areas with high racial inequality. DURATION N/A INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. METHODOLOGY: 1. Establish correlation between inequality and types of crime (across police jurisdictions) 2. Analyze data with respect to mean expenditure and income inequality (this correlates with sociological theories that suggest crime is a function of inequality) 3. Analyze data with respect to relative wealth between jurisdictions (to determine whether crime is influenced by the economic crime argument of cost-benefit) 4. Analyze data with respect to the relationship between crime and inequality with and between racial groups e) Conduct data analyses adjusting for under-reporting in crime DATA and SOURCES: Type of data used; sources DATA: a) Household Composition by police jurisdiction (race, education, primary occupation, housing characteristics, access to services) b) Property Crime and Violent Crime, c) Income Inequality and Racial Inequality. SOURCES: 1996 Population Census, 1996 South African Police Service Crime Data (Administrative data), 1995 October household Survey and Income and Expenditure Survey (used with the census to estimate mean per capita expenditure and per capita expenditure inequality.) SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. N/A COSTS and FINANCING: Total costs for study; financing arrangements. (Estimate for conducting a poverty map, which is the analytical basis for this type of study) $100,000 IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners N/A NOTES Application of careful analysis to existing administrative data can provide rich spatially disaggregated data. 44 15. Information Based Instruments for Improved Urban Management World Bank Policy Research Working Paper. (Deichmann et al.). Bangalore, India, 2003. FOCUS Key objective of focus for data collection and analysis To examine how public dissemination and use of spatially detailed data can help improve the quality of life in urban areas. (This largely an analytical paper that includes a description of data collection in Bangalore. While urban poverty was not the focus of this study, the data collection process and findings can provide useful lessons.) CONTEXT: This piece is part of a broader policy research program between the World Bank and Society for Development Studies. The Bangalore survey is the first of 4 anticipated surveys. NOTE: As of March 2004, similar data collection has been completed in Pune, Jaipur and Bhopal. DURATION 6-8 weeks (includes only survey and training, does not include data verification, analysis, and report production.) INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. METHODOLOGY: a) Focus groups with 4 different groups representing different types of settlements (squatter settlement, regularized slum, upper middle-class residential area, authorized revenue site) to facilitate the design of the household survey. b) Data collection using household survey. INSTRUMENT: Household survey designed by research teams, and then tested with focus groups (a). Survey consisted of 4 modules and was to last 1 hour. The survey team of 20 enumerators received 5 days of training, and were paired into 2 person teams for data collection. To facilitate geographic analysis of the data, survey teams utilized handheld GPS (global positioning systems) that provided spatial coordinates for each household surveyed. DATA and SOURCES: Type of data used; sources DATA: There were 4 modules used. These included, (i) Household information (characteristics of household members), (ii) Consumption and expenditures, (iii) Water supply (Survey design received input from the Bangalore Water Supply and Sanitation Board on local water sources (both formal and informal systems). The Water module included a `Willingness to Pay' Exercise that targeted the questions to reflect the reasonable amount that a household would pay to improve their water supply service (this required enumerators to tailor the questions based on specific criterion.) and (iv) Housing. SOURCES: Multi-topic City Household Survey SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. 2905HH (constituting a sample population of 13,453), distributed throughout 100 wards (proportionally). Because household listings for census (2001) were not available, electoral roles were used for the master sampling frame. COSTS and FINANCING: Total costs for study; financing arrangements. [The following costs are estimates based on similar surveys conducted in India as part of the research program: Survey design $40k; Development of Data Base $40k; Collaborator Travel & Fees Budget $35k, Total: $75k] IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners COMMISIONNED BY: The World Bank IMPLEMENTED BY: The World Bank Development Research Group and the Society for Development Studies (SDS). Bangalore Local Urban Observatory (BLUO) also involved. 45 NOTES The data collection exercise was framed by an understanding of why and how data can improve urban management (tax collection, service delivery, etc.). It also recognizes, however that for data to be put to use, training among relevant municipal staff is necessary. By not limiting the survey to a narrow population group (e.g. a slum survey) or a single topic, such surveys can provide a baseline for urban welfare analysis at the sub-city level and across sectors. The survey was designed so that the data (on at least household information and income and consumption modules) could be compared with past and future census data--adding to the collective data collection of the city and also so that it may be used in future studies to construct poverty maps. 46 16. Urban Services Delivery and the Poor: The Case of Three Central American Cities The World Bank, San Salvador Metropolitan Area (El Salvador), Tegucigalpa (Honduras), Panama City and San Miguelito (Panama). June 3, 2002. FOCUS Key objective of focus for data collection and analysis To describe and quantify the provisions of basic urban services to the poor in select Central American cities; and identify priority areas of government intervention. CONTEXT: While urbanization is a central feature in Central American cities, the relationship between increasing concentration of poor communities and service delivery has not been explicitly studied or documented. DURATION October- November 2000 (for collection of household surveys) INSTRUMENT and METHODOLOGY: Classify and describe instrument(s) used; methodology for implementation. METHODOLOGY: In addition to a 10 module Household Survey, this study also included the development and application of a welfare measure. As the purpose of the study was on service delivery rather than on poverty per se, the welfare measure was a crude estimate of aggregate consumption. This was preferred over income measures because of the difficulties in gathering objective income data. Each of the three City Studies is divided into 4 sections (i) an overview on urbanization and poverty; (ii) description of household and neighborhood characteristics; (iii) access to land and shelter; (iv) basic services and (v) transport. DATA and SOURCES: Type of data used; sources DATA: (i) Welfare Measure (ii) The household survey included 10 modules that gathered data on: household composition, housing/street observations, neighborhood conditions, housing conditions, water, sanitation and drainage, solid waste collection, electricity, transport ,expenses and consumption. SOURCES: (i) specialized household surveys tailored to this study (ii) interviews with selected agencies, communities, and enterprises; and (iii) a review of existing literature. SAMPLE SIZE, LOCATION and METHOD: Specify sample size and method for determining sample. Tegucigalpa (1,200 HH), Metropolitan San Salvador (1,426 HH), Panama City (2,411 observations drawn from the 1997 Living Standards Survey). The surveys (in Tegucigalpa and San Salvador) were based on stratified, multistage probability samples of households, with census segments serving as the primary sampling unit. The census segments are divided into 4 socio-economic strata. Random sampling from the primary sampling unit was weighted by the proportionate representation of each socio-economic strata in the population. COSTS and FINANCING: Total costs for study; financing arrangements. (Estimated) $276,000 (including the publishing and dissemination of reports) IMPLEMENTATION STRATEGY: Outline institutions responsible for implementation - local and international partners COMMISSIONED & IMPLEMENTATION: The World Bank NOTES This work is unique in offering a comparative analysis of three cities using consistent data collection methodology in each of the cities. 47 Annex 2. Useful Charts and Diagrams 2.1 Indicators and Data Sources From: J. Hentschel & R. Seshagir. (2000), "The City Poverty Assessment Primer," Prepared for the Urban Management Course, Poverty Group, The World Bank. Table 1: Indicators and Data Sources Indicator Data Source Income poverty indicators - Poverty rate (incidence, poverty gap, - National level household surveys (Living poverty severity; extreme poverty rate Standard Measurement Surveys, (incidence); income inequality measure Employment Surveys) if representative at city level; Multi-topic city survey Health and Education Outcome Indicators - Under-five mortality rate, infant mortality - Specialized national household surveys rate, maternal mortality rate, life such as DHS, or LSMS (if representative expectancy at city level) - Malnutrition rate of children - National levels (DHS, LSMS), Nutrition surveys, Height census - Literacy rate, years of schooling - Most surveys and most censuses Access Indicators - Water, electricity, sanitation, garbage - Various household surveys, population collection census, administrative data - School and health facility - Various household surveys, some population census, administrative data - Social programs (nutrition, social - Specialized household surveys (LSMS, assistance) multi-topic surveys, administrative data - Service satisfaction - Specialized city surveys (Service satisfaction and needs survey, multi-topic city survey) Non-Income Deprivation Indicators - Unemployment - National employment surveys, LSMS, multi-topic city surveys - Violence - Violence surveys (only certain types of violence can be measured), multi-topic city surveys, participatory appraisals - Child labor - National surveys, LSMS, multi-topic city survey - Discrimination - Participatory assessments, household surveys (not directly but through application of models) 48 2.2 Poverty Dimensions and Indicators From: Baharaoglu and Kessides, 2002, "Urban Poverty" in World Bank, 2002, A Sourcebook for Poverty Reduction Strategies, Chapter 16. 49 50 2.3 Urban Poverty Indicators From: Urban Poverty Research Sourcebook: Modules I&II, Caroline Moser et al. Urban Management Programme/World Bank. Sept. 1996. 51 52 53 54 55 56 Annex 3. Sample Questionnaire for Urban Poverty Assessment The following questionnaire is from: Assessment of Urban Poverty in Lesotho United Nations Development Programme (UNDP). Maseru, Lesotho. December, 1997. Questionnaire for Urban Poverty Assessment Town:_________________________ Sub-area:____________________________ Interviewer:____________ Date:__________ Questionnaire ID No:__________ Interviewee (HHD member interviewed):______ Category of Interviewee:________ PART 1: HOUSEHOLD PROFILE No.HHD Sex Age Rel. to Marita Years Place Occu- Months/Years Brings Mem- (1) (2) HHD l of of pation away from Incom bers Head Status School Res. (7) home e (3) (4) (5) (6) Months (9) Years 1(Head) 2 3 4 5 6 7 8 9 10 Codes: Sex (1): Age (2): Relation to HH Head (3): 1=Male Fill in age and use 0 for 1=Spouse/partner 2=Female those under 1 year old 2=Child 3=Grandchild 4=Relative 5=HH Head 6=Other Marital Status (4): Place of Usual Residence Type of Occupation 0=Unmarried (6): (7): 13=Seeking Work 1=Married 0=This HHD 0=Inactive 14=On Pension 2=Divorced/Separate 1=Another HHD in Same 1=Casual Labourer 15=Street Vendor d Village 2=House Work 16=Hawker 3=Widow(er) 2=Nearby Village 3=Miner 17=Health Worker 4=Cohabiting 3= Elsewhere in Lesotho 4=Other work in RSA 18=Sells Firewood 9=Unknown 4=RSA 5=Clerk 19=Taxi Driver 5=Other 6=Construction Work 20=Doctor/Healer 7=Government 21=Security/Guard Brings Income (9): 8=Teacher 22=Landlord/Landlad 1=Yes 9=Handicrafts y 2=No 10=Shop Worker 11=Mechanic 23=Other:_________ 12=School __ 99=Unknown 57 PART 2: NON-INCOME INDICATORS Code Indicator and measurement 2.1 House type: Rondavel: Malaene: Optak: Mokhukhu: Heisi: Room: Polata: Other: Specify:_____________________ 2.2 Number of rooms: (give number) 2.3 Rent house: Ownership of house: Don't know: 2.4 If you own your house, do you own the land? Don't know: Yes: n/a: No: 2.5 Rent amount: (if applicable, give figure) Don't know: n/a: 2.6 Quality of house G F P G=Good (observe) F=Fair P=Poor 2.7 Estimated size of plot of land (either by interviewer or respondent) (give number) 2.8 Economic activity on plot(s): (can check more than one box) Garden crops: Animals: Small business: No activity: n/a: Other: Specify:___________________ 2.9 Number of different garden crops: (give number) 2.10 Amount of litter on L M H L=Low property M=Medium (observe) H=High 2.11 What is the main method of disposal of your HHD waste and garbage? Dump it: Waste is picked up: Nothing: Bury it: n/a: Burn it: Don't know: 58 Code Indicator and measurement 2.12 Main source of water supply: Piped water directly to house: Bore hole: Outside tap (within yard, but outside Don't know: house): Other: Piped water to (public) collection Specify:___________________ point: 2.13 If water does not come directly to house, how long does it take to go to the water source (and back)? (give amount of time for return trip) n/a: 2.14 How long do you usually have to queue for water? (give time period) n/a: 2.15 When was water last cut off? (give time period) n/a: Don't know: 2.16 For how long was water cut off? (give time period) n/a: Don't know: 2.17 Do you have to pay for your water? If yes, how much? (give figure) n/a: Don't know: 2.18 Type of toilet: In-house toilet: Bucket latrine: Pit-latrine: Don't know: VIP latrine: Other: Specify:__________________ 2.19 Do you have to pay to use the toilet? Yes: No: n/a: If yes, how much? (give figure) 2.20 Is it a shared (public) toilet (for more than one HHD)? Yes: No: n/a: 59 Code Indicator and measurement 2.21 Is there evidence of sanitary pollution affecting the HHD or immediate neighbourhood? (observe) Yes: No: 2.22 Access to electricity supply? Yes: No: 2.23 Have you needed to use health services during the last 6 months? Yes: No: Don't know: 2.24 If so, what for? (list reasons) n/a: 2.25 What type of health services? (can check more than one box) Hospital: Doctor: Clinic: Don't know: Traditional healer: Other: Specify:______________________ 2.26 Are your children healthy? Yes: No: Don't know: n/a: Describe any problems 2.27 Have your children been to a doctor or clinic lately? Yes: No: Don't know: n/a: 2.28 Do you or your children go to school? Yes: No: Don't know: n/a: What kind of school? Specify 2.29 Does the school have adequate facilities and staff (such as teachers, desks, chairs, blackboards, lighting, books, etc)? Yes: No: Specify Don't know: n/a: 60 Code Indicator and measurement 2.30 Is it easy to get to school? Yes: No: Don't know: n/a: 2.31 Have any of your children dropped out of school? Yes: No: Don't know: n/a: 2.32 Why have they dropped out? Could not afford school fees : Child(ren) could not cope: Other: Don't know: n/a: 2.33 Do/did your children have suitable space to study and do their homework at home? (observe) Yes: No: n/a: 2.34 Do you need to use transportation regularly? Yes: No: 2.35 Do you have an alternative to public transportation? (can check more than one box) Walking: Own vehicle: Other vehicle: n/a: Other: Specify:________________________ 2.36 Where do you or your HHD members usually need to go when you use public transport? To visit relatives: (can check more than one box) To health centre: To work: To the rural areas: To school: n/a: To church: Other: To do groceries and shopping: Specify:_____________________ 2.37 Can you afford transportation? Yes: No: n/a: 61 Code Indicator and measurement 2.38 Are there any problems with transportation? (describe any problems) n/a: 2.39 Is your neighbourhood safe? Yes: No: Don't know: 2.40 Have you experienced crime/theft and/or other violence in last 6 months? Yes: No: 2.41 Are you informed about the responsibilities and representatives of local government (in Maseru: the Maseru City Council; in Mohale's Hoek and Maputsoe: town clerks) or the national government system? Yes: No: 2.42 Do you know what services you get from government? Yes: No: 2.43 Do you know about legal services (your basic rights)? Yes: No: 2.44 Where are you from originally? The city: The rural areas: 2.45 If originally from the rural areas: Do you travel back and forth to the rural areas often? Yes: No: n/a: 2.46 Where do your relatives live now? (can check more than one box) Same neighbourhood or town: Don't know: Different town: n/a: In the rural areas: Other: RSA: Specify:_______________________ _ 2.47 How often do you O N N O=Very often contact your O NO=Occasionally relatives? N=Rarely/never 2.48 Do you give O N N O=Very often assistance to your O NO=Occasionally relatives? N=Rarely/never 62 Code Indicator and measurement 2.49 If so, what kind of assistance? (can check more than one box) Economic assistance (money, gifts, food, etc.): Social assistance: Both: Other: n/a: 2.50 Do you receive O N N O=Very often assistance from your O NO=Occasionally relatives? N=Rarely/never 2.51 If so, what kind of assistance? (can check more than one box) Economic assistance (money, gifts, food, etc.): Social assistance: Both: Other: n/a: 2.52 Do you give O N N O=Very often assistance to the O NO=Occasionally community? N=Rarely/never 2.53 If so, what kind of assistance? (can check more than one box) Economic assistance (money, gifts, food, etc.): Social assistance: Both: Other: n/a: 2.54 Do you receive O N N O=Very often assistance from the O NO=Occasionally community? N=Rarely/never 2.55 If so, what kind of assistance? (can check more than one box) Economic assistance (money, gifts, food, etc.): Social assistance: Both: Other: n/a: 63 PART 3: MEASUREMENT ACCORDING TO POVERTY LINE 3.1 What was the expenditure of the HHD the previous week? Amount:_______________________________________ Can't remember: "Don't know" (doesn't want to say): Don't know (has no idea about HHD finance): n/a: Other: Specify:________________________ 3.2 What are usually the main items of expenditure? List in table below, unless: Can't remember: "Don't know" (doesn't want to say): Don't know (has no idea about HHD finance): n/a: Other: Specify:________________________ List in order of importance, not necessarily covering all items (1=most important; 2=less important, etc.) Where categories are of equal priority, they can be assigned the same number. Item Order Amount spent the previous week Food & Beverages Clothes & Footwear Rent Fuel & Power Water School Fees Education Other Transport Communications Furniture & Appliances Vehicle Recreation Toilet Other 64 PART 4: NET HOUSEHOLD INCOME Code Source of Income Average net amount Times yearly earned (after repaying costs) 4.1 Migrant Work of Men 4.2 Migrant Work of Women 4.3 Wage Work in Lesotho (Men) 4.4 Wage Work in Lesotho (Women) 4.5 Casual Work of Men 4.6 Casual Work of Women 4.7 Earnings from Shop/Café 4.8 Earnings from Construction/Carpentry 4.9 Earnings from Brewing 4.10 Earnings from Resale of Liquor or Beer 4.11 Earnings from Crops (Garden) 4.12 Earnings from Livestock 4.13 Earnings from Livestock Products 4.14 Earnings from Rental Income 4.15 Earnings from Private Practice at Home (Medical, etc.) 4.16 Earnings from Handicrafts 4.17 Earnings from Street Vending 4.18 Earnings from Hawking 4.19 Don't Know 4.20 Gifts (see below) Don't monetize! Explain below 4.21 Other:______________ 4.20: Gifts and receipts in kind (specify what and from whom): ________________________________________________________________________ ________________________________________________________________________ ________________________________________________________________________ ________________________________________________________________________ 65 PART 5: LISTING OF PERCEPTIONS OF POVERTY Let the respondents talk !! In case the respondent is shy or holding back, here is a basic checklist: 1. How do the respondents conceptualise their own situation? 2. What would they consider as "poverty"? 3. Are they "poor"? Are they "poor" most of the time (or does it depend on circumstances)? 4. What are the reasons for their poverty? 5. What could they do themselves to help improve their situation? 6. What could outside institutions do to help them (Government, private sector, churches, donors, NGOs, etc)? 7. Is life in the rural areas different? How so? 8. Do they consider their neighbourhood to be a poor area? Note their comments here: 66