43027 Authorized THE WORLD BANK GROUP WASHINGTON, D.C. UP-4 Disclosure URBAN PAPERS JANUARY 2008 Public Authorized Disclosure Public Urban Poverty in Ethiopia A Multi-faceted and Spatial Perspective Authorized Elisa Muzzini Disclosure Public Authorized Disclosure Public URBAN SECTOR BOARD Urban Poverty in Ethiopia A Multi-faceted and Spatial Perspective Elisa Muzzini THE WORLD BANK URBAN SECTOR Washington, D.C. BOARD © 2008 The International Bank for Reconstruction and Development/The World Bank 1818 H Street NW Washington, DC 20433 Telephone 202-473-1000 Internet www/worldbank.org The findings, interpretations, and conclusions expressed here are those of the author and do not necessarily reflect the views of the Board of Executive Directors of the World Bank or the governments they represent. To order additional copies of this publication, please send an e-mail to the Urban Help Desk, urbanhelp@worldbank.org Urban publications are available on-line at http://www.worldbank.org/urban/. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE iii TABLE OF CONTENTS Acknowledgements .................................................................................................vii Abstract .................................................................................................................ix I. INTRODUCTION ............................................................................................... 1 II. HOW ARE THE URBAN POPULATION AND THE URBAN POOR SPATIALLY DISTRIBUTED?................................................................................................. 3 A. Spatial Distribution of the Urban Population................................................ 4 B. Spatial Distribution of Urban Poverty ......................................................... 7 III. NARROWING DOWN THE FOCUS: NEIGHBORHOOD POVERTY ................................. 8 A. Intra-City Spatial Distribution of Poverty: why it matters and how to measure it .................................................................................................... 8 B. "Being poor in a poor area": is income poverty spatially concentrated?..........10 C. Slum settlements: are people living in slum-like conditions spatially concentrated?...............................................................................................12 D. Income Poor and People living in Slum-like Conditions: to what extent is there overlap? ..............................................................................................17 E. Conclusions ..........................................................................................18 IV. LIVING CONDITIONS: URBAN ADVANTAGE AND URBAN INEQUALITY......................20 V. URBAN POVERTY: A DEMOGRAPHIC PROFILE.......................................................29 VI. URBAN POVERTY AND EDUCATIONAL ATTAINMENT ..............................................34 VII. COPING WITH VULNERABILITY: INCOME DIVERSIFICATION AND SAFETY NETS........41 A. Urban Poverty and Income Diversification .................................................41 B. Urban Poverty and Safety Nets ................................................................45 VIII. URBAN POVERTY AND EXPENDITURE PATTERNS: ARE BASIC SERVICES AFFORDABLE FOR THE POOR?...........................................................................53 IX. CONCLUSIONS................................................................................................59 References.............................................................................................................63 LIST OF TABLES Table 1. Population living in Slum-like Conditions - Indicators........................................14 Table 2. Spatial Connotation of Urban Poverty ­ Main Findings ......................................19 Table 3. Urban Poverty and Living Conditions ­ Main Findings .......................................28 Table 4. The "Urban" Household................................................................................30 Table 5. Demographic Profile of Urban Poverty ­ Main Findings......................................34 Table 6. Urban Poverty and Educational Attainment ­ Main Findings...............................40 Table 7. Urban Poverty and Income Diversification - Main Findings.................................44 Table 8. Urban Poverty and Safety Nets ­ Main Findings...............................................52 Table 9. Urban Poverty and Expenditure Patterns ­ Main Findings..................................58 URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE iv LIST OF FIGURES Figure 1. Ethiopian Urban Population, by Size of Urban Center (2006) ............................. 5 Figure 2. Ethiopian Urban Centers (Number), by Size of Urban Center (2006)................... 5 Figure 3. Urban Population and Urban Poverty Distribution, by Locality............................ 7 Figure 4. Urban Poverty Incidence, by Locality ............................................................. 8 Figure 5. Percentage of the Poor Living in High-Poverty Neighborhoods, by Definition of High-Poverty Neighborhood...........................................................................12 Figure 6. Percentage of High-Poverty Neighborhoods, by Locality...................................12 Figure 7. Percentage of Population living in Slum-like Conditions, Strict versus Relaxed Definition .......................................................................................................14 Figure 8. Clusters Classified as Slum Settlements (Percent of Total) ...............................16 Figure 9. Share of Population in Slum-like Conditions Living in Slum Settlements, by Definition of Slum Settlement............................................................................16 Figure 10. Overlay between People living in Slum-like Conditions and Urban Poor (Percentage of Ethiopian Urban Population).........................................................17 Figure 11. Urban Population with Access to Improved Water Supply (%), by Quintile and Locality....................................................................................................21 Figure 12. Urban Population with Access to Improved Sanitation (%), by Quintile and Locality ..........................................................................................................22 Figure 13. Urban Population with Access to Electricity (%), by Quintile and Locality.........23 Figure 14. Urban Population with Access to Waste Disposal Vehicles/Containers (%), by Quintile and Locality ....................................................................................24 Figure 15. Urban Population Living in an Overcrowded Space (%), by Quintile and Locality ..........................................................................................................25 Figure 16. Urban Population with Land and Housing Ownership (%), by Quintile and Locality ..........................................................................................................26 Figure 17. Household Composition ­ Poor versus Non-Poor Households ..........................31 Figure 18. Female Headed Households ­ Demographic Profile........................................33 Figure 19. Education Profile: Head of Household, Years of Schooling, by Locality..............37 Figure 20. Education Profile: Adult Females, Years of Schooling ­ by Locality...................37 Figure 21. Education Profile: Adult Males, Years of Schooling ­ by Locality ......................38 Figure 22. Education Profile: Female Heads, Years of Schooling ­ by Locality...................39 Figure 23. Main Source of Income, by Locality.............................................................42 Figure 24. Percentage of the Population Receiving Transfers, by Locality.........................48 Figure 25. Percentage of the Population Receiving Transfers, Poor versus non-Poor, by Locality ..........................................................................................................48 Figure 26. Per Capita Transfer (Birr), by Locality .........................................................49 Figure 27. Per Capita Transfer (Birr), Poor versus non-Poor, by Locality..........................49 URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE v Figure 28. Percentage of the Population Receiving Transfers, Poor FHH versus Poor MHH, by Locality .............................................................................................50 Figure 29. Per Capita Transfer (Birr), Poor FHH versus Poor MHH, by Locality ..................50 Figure 30. Food Expenditure, Share of Total Expenditure, by Locality ............................53 Figure 31. Water Expenditure, Share of Total Expenditure, by Locality...........................54 Figure 32. Electricity Expenditure, Share of Total Expenditure, by Locality......................55 Figure 33. Expenditure on Health and Medical Care, Share of Total Expenditure, by Locality ..........................................................................................................56 Figure 34. Education Expenditure, Share of Total Expenditure, by Locality.......................57 LIST OF BOXES Box 1. Methodological Approach, and Definition of Poverty Line ...................................... 3 Box 2. Land Management System and Housing Markets in Ethiopia--A Snapshot..............26 Box 3. The Profile of Migrants in Urban Ethiopia...........................................................31 Box 4. Returns to Education in Urban Ethiopia.............................................................36 URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE vii ACKNOWLEDGEMENTS The author would like to thank World Bank staff members Rumana Huque, Caterina Ruggeri Laderchi, Vivien Foster and Judy Baker for guidance, insightful discussions and comments. This paper--a product of the Urban Unit, Sustainable Development Department in the East/South Africa Region--is part of a larger effort in the department to study the challenges of urbanization in Ethiopia and its implications for growth and poverty alleviation. The author may be contacted at emuzzini@worldbank.org. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE ix ABSTRACT The study provides an overview of the multi-faceted and spatial dimensions of urban poverty in Ethiopia drawing on the 1999 household survey data. First, the study observes urban poverty through a "spatial lens" by segmenting the urban space based on population size and assessing "intra-urban" spatial patterns of poverty. Second, the profile of urban poverty is broadened to encompass selected non-monetary indicators of living standards. The results suggest limited intra-urban spatial concentration of monetary and non-monetary poverty in line with the prevailing view that Ethiopian urban centers display integrated residential structures where the poor live side-by-side with the non-poor. However, 75 percent of the urban population suffers from some form of non-monetary deprivation with respect to their living conditions, lacking either access to improved water supply or sanitation or living in overcrowded spaces. Major towns perform better than small/medium towns with respect to access to improved water supply and electricity; yet, they are not spared from challenges. First, overcrowding and lack of tenure security are pressing issues in major towns, and are highly correlated with urban poverty. Second, major towns fare as badly as small/medium towns as far as access to improved sanitation is concerned. A peculiar feature of the demographic profile of urban families is the high percentage of female-led families, which represent a remarkable 33 percent of the urban population. The high percentage of female-led families with dependents and the low education attainment of female heads raise particular concerns over the income-generating opportunities available to female headed households. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE I. INTRODUCTION The primary objective of this study is to provide a better understanding of the spatial connotation and heterogeneous profile of urban poverty in Ethiopia. The study is motivated by the growing awareness among Ethiopian government agencies of the challenges associated with urban development and urban poverty. The recently released Plan for Accelerated and Sustained Development to End Poverty (PASDEP) emphasizes that urban development is going to play a more central role in the next phase of Ethiopia's development, and in PASDEP itself, that it has been in the past. The growing concern on urban poverty is cited as one of the reasons behind the mounting interest on urban development.1 Urban poverty has a strong spatial connotation. While poverty has been studied and documented in Ethiopia to a great extent, the existing poverty literature seldom provides an urban perspective of poverty or, when it does so, it merely studies urban poverty relatively to rural poverty.2 The dichotomy between the urban and rural space is however too coarse to depict the complex reality of urbanization, and its associated poverty outcomes. The urban and rural space intersect at so many levels that it is difficult to demarcate the boundaries between them. The concept of urban spectrum is therefore more suited to describe the gradations to be found within the urban space. Lying somewhere in the continuum between urban and rural, small towns tend for example to have their own distinct urban profile. PASDEP recognizes the spatial differentiation which characterizes the urban space, emphasizing the need to adopt a geographically-differentiated strategy to foster urban development. In particular, PASDEP identifies the development of small towns as a key area of intervention to strengthen urban-rural linkages.3 ... and it is multi-faceted. Monetary poverty is only one among several measures of deprivation. Decent living conditions, access to basic services, a minimum level of educational attainment and adequate safety nets are equally important measures of human well-being. Over-reliance on the monetary dimension of poverty may risk under-estimating the true extent of poverty in the urban context, where living conditions can be made harsher by diseconomies of agglomeration, such as congestion, environmental degradation and crime, theft and disorder. On the contrary, a good understanding of the non-monetary dimensions of poverty can provide policy-makers with more entry points for anti-poverty interventions. Monetary poverty can for example be addressed by tackling non-monetary aspects of poverty, such as improvements in housing quality and better access to basic services. Urban poverty is observed through a `spatial lens'. This study examines the urban space from two different spatial perspectives. First, the urban space is segmented based on the population size of the urban centers: urban settlements are classified as major towns if they have more than 100,000 inhabitants. All other urban settlements with population below the 100,000 threshold are classified as small and medium towns.4 Based on the 5 1See PASDEP, p. 161. PASDEP is Ethiopia's second PRSP. 2See, for example, Bigsten et al (2003), Taddesse and Shimeles (2000) and Gebremedhin (2006). 3The Small Towns Development Program will focus on the provision of basic infrastructure services, digital mapping and support services to 600 small towns. 4The population estimates are based on the 2005 Labor Force Survey. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 2 100,000 cut-off point, there are seven major urban centers in the Ethiopian urban landscape: Mekele, Gonder, Awasa, Dire Dawa, Addis Ababa, Bahir Dar and Adama. Second, the focus is then narrowed down to the neighborhood level to study "intra-urban" spatial patterns of poverty and assess the extent to which urban poverty is spatially concentrated within urban centers. The profile of urban poverty is broadened to encompass selected non-monetary indicators of living standards. This study adopts a broad definition of poverty. First, the study assesses the incidence of non-monetary deprivation with respect to urban living conditions and discusses the overlap between monetary poverty and non-monetary deprivation. Second, the study assesses how the income poor fare with respect to selected non-monetary indicators of well-being--namely livability, education attainment, income diversification, access to safety nets and affordability of basic services. It also characterizes the demographic profile of poor households to identify specific vulnerabilities associated with household size and composition (e.g., the incidence of female-headed households). Drawing on the framework outlined above, this study addresses the following questions: · How is the urban population and urban poverty spatially distributed across the urban spectrum? · To what extent are monetary poverty and non-monetary deprivation (associated to living conditions) spatially concentrated within urban centers? · How do the urban poor fare with respect to access to basic services and living conditions, relatively to the rural poor? Where do small and medium towns position themselves in the urban-rural continuum in terms of provision of basic services? · How does the demographic profile of urban poverty change across the urban spectrum? · Is there a clear urban advantage with respect to educational attainment? How are small and medium towns faring with respect to educational outcomes relatively to major towns? · To what extent the urban population, and the urban poor in particular, have access to different risk management options compared to the rural population? Are safety nets effective in lessening the vulnerability associated with urban poverty? · How do the expenditure choices of the urban poor differ from non-poor expenditure patterns for basic services (e.g., health, education)? The study is structured as follows: Section II analyses the spatial distribution of urbanization and urban poverty; Section III explores the within-urban spatial distribution of monetary and non-monetary deprivation; Section IV delves into the linkages between monetary poverty and living conditions, documenting how the urban population, and in particular the urban poor, fare with respect to access to basic services and housing quality; Section V contrasts the demographic profile of the urban and rural population, and highlights the distinguishing features of urban poor households; Section VI explores the correlation between urban poverty and education outcomes across the urban spectrum; Section VII discusses the effectiveness of income diversification and safety nets as urban livelihood strategies to cope with vulnerability; Section VIII discusses the expenditure choice of the poor for selected basic services; finally, Section IX summarizes the main findings of this study. The methodology and data used for the study are described in Box 1. 5 It is not possible to further disaggregate towns below 100,000 as the sample is not representative at the level of small towns. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 3 Box 1. Methodological Approach, and Definition of Poverty Line The study mainly draws on the 1999 Household, Income, Consumption and Expenditure Survey (HICES) and the accompanying Welfare Monitoring Survey (WMS). The results from the 1999 round of nationally representative surveys are complemented by secondary quantitative and qualitative information on urban poverty. The Government of Ethiopia is currently undertaking a new round of the HICES and WMS for the year 2004/05. Unfortunately, the insights from the 2004/05 surveys were not available in time for this study, because the survey datasets were not fully compiled and did not allow the identification of the poor. In line with the 2005 Poverty Assessment conducted by the World Bank, this study adopts multiple poverty lines (one for each of the 32 zones that the Ethiopia Central Statistical Authority (CSA) uses for sampling of households) to allow for variations in consumption baskets across geographic areas (World Bank 2005). In other words, geographic variation in the poverty line allows for the possibility that households living in different locations consume different baskets of goods, for a given level of wealth, because of different preferences and tastes and relative price differences. This implies that different poverty lines are set in urban and rural areas to account for urban-rural disparities in the cost of necessities. The main rationale for allowing different poverty lines between urban and rural areas is to minimize the risk of under-estimating urban poverty, a risk that occur when one poverty line is set for the country as a whole based on a national basket of goods. Nationwide non-food allowance may indeed be insufficient to cover basic urban necessities as urban environments are highly monetized economies (i.e., they rely on cash transactions significantly more than rural centers). For example, the urban poor who have to rely on street vendors to a significant extent for their basic water needs may end up spending significantly more for water than those connected to piped water supply. (See, for example, Satterthwaite 2004). In line with the 2005 Poverty Assessment, the lower bound of the full poverty line, which accounts for both food and non-food basic needs, is used throughout the study. Household income is approximated by total consumption per adult equivalent with imputed rent, excluding energy expenditures given the intricacies involved in imputing expenditure related to wood and dung collection, which is the most common fuel source in rural Ethiopia. (World Bank 2005). All household variables, unless otherwise stated, are population weighted. For simplicity, those with per capita consumption below the region-specific poverty rate are defined as income poor, and "income" and "consumption" are used interchangeably in the study. The urban codes for 1999 HICES provided by the CSA made possible the identification of major towns in the 1999 HICES/WMS. In this study, major towns are defined as towns with population above 100,000 inhabitants (based on 2005 Labor Force Survey population estimates). All other towns with population below the threshold are classified as small and medium. Each town is identified by a sequence of five codes, namely a zone, wereda, town, keftegna, kebele and enumeration area code. It is not possible to distinguish between small and medium towns as the survey is not representative at the level of small and medium towns. The quintiles for urban, small towns and major towns are calculated based on the entire population (ie. each quintile represents 20 percent of the country population). Quintiles for Addis Ababa are calculated based on the population in Addis Ababa only (i.e., each quintile represents 20 percent of Addis population), given that applying the quintiles of the population as a whole to Addis population would result in a very low number of observations in the Addis two lowest quintiles. Source: World Bank (2005). II. HOW ARE THE URBAN POPULATION AND THE URBAN POOR SPATIALLY DISTRIBUTED? This Section analyses the spatial distribution of the urban population and urban poverty. It first sets the context by presenting the main trends that characterize the urban transition in URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 4 Ethiopia. It then analyzes the recent trends in urban poverty and assesses the extent to which urban poverty is spatially concentrated in a given segment of the urban spectrum. A. Spatial Distribution of the Urban Population Ethiopia is urbanizing fast, but from a low base. While Ethiopia has a high rate of urbanization (estimated at 4.4 percent per year), the level of urbanization is still very low. Only 16 percent of the total population is estimated to live in urban areas as of 2006, against 13 percent in 1999 (CSA 2006). The urban population is expected to reach 22 million people by 2020, based on the 4.4 estimated annual growth rate (PASDEP 2006). However, cautious is needed in interpreting the estimates, which are derived by projecting 1994 population census data and thus likely to underestimate the true level of urbanization. There is significant variation is the size distribution of urban centers in Ethiopia. Based on Ethiopia politico-administrative classification, "urban" includes all "localities with 2,000 or more inhabitants" as well as (i) all administrative capitals (regional, zonal and wereda capitals), (ii) settlements with urban dwellers' associations which are not administrative capitals and (iii) all other settlements whose inhabitants are primarily not engaged in non-agricultural activities (World Bank 2006). Based on the 2006 size distribution of urban centers, 39 percent of the urban population lives in the twelve largest urban centers (with more than 100,000 inhabitants), 27 percent live in 101 urban centers with population between 20,000 and 100, 0000 and the remaining 34 percent resides in 820 urban centers with less than 20,000 inhabitants (see Figure 1 and Figure 2). The statistics need however to be interpreted with caution, given that the last census was conducted in 1994. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 5 Figure 1. Ethiopian Urban Population, by Size of Urban Center (2006) [up to 2,000] 2% [2,000 to 4,999] 9% [Above 200,000] 30% [5,000 to 19,999] 23% [100,000 to 200,000] 9% [50,000 to 99,000] [20,000 to 49,999] 8% 19% Note: The label indicates the population range of the urban centers and the percentage of urban population living in those urban centers. For example, 2 percent of the urban population lives in urban centers with less than 2,000 inhabitants. Source: CSA 2006. Figure 2. Ethiopian Urban Centers (Number), by Size of Urban Center (2006) [50,000 to 99,000], [100,000 to 200,000], 14 8 [20,000 to 49,999], [Above 200,000] , 4 79 [up to 2,000], 171 [5,000 to 19,999], 310 [2,000 to 4,999], 339 Note: The label indicates the population range of the urban centers and the number of urban centers falling in that population range. For example, there are 171 urban centers with less than 2,000 inhabitants. Source: CSA 2006. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 6 For analytical purposes, towns with more than 100,000 inhabitants are classified as major towns. Based on the 2005 Labor Force Survey population estimates, there are seven major towns with population above 100,000, in urban Ethiopia: Mekele, Gonder, Awasa, Dire Dawa, Addis Ababa, Bahir Dar and Adama.6 All other towns with population below the threshold are classified as small/medium towns. Given the large number of urban centers with population below 100,000 inhabitants, a further breakdown of the urban space would be warranted to capture differences between small and medium towns. However, this is not possible with the available data, as the household survey is not representative at the level of small towns. Among major towns, Addis Ababa plays a dominant role. 35 percent of the urban population live in the seven major urban centers in Ethiopia. Among them, the primacy of Addis Ababa emerges starkly, with 25 percent of the urban population living in the capital city. PASDEP emphasizes the "overwhelming weight of Addis Ababa in the urban picture in Ethiopia": Addis Ababa, with an estimated population of 3 million people, is 14 times bigger than Dire Dawa, the second largest city in the country. To reflect Addis Ababa's dominant role in the urban scene and to capture differences in the urban profile between the capital city and other major towns, separate statistics for Addis Ababa are presented throughout this study. ... but 65 percent of the urban population lives in small/medium towns. As a result, small/medium town growth is likely to become a significant contributor to urbanization in Ethiopia (see Figure 3). This finding is consistent with global evidence pointing to small cities as the engine of urbanization in developing countries: cities with less than one million inhabitants are expected to house 60 percent of the developing-country urban population by 2015 (National Research Council 2003). Likewise, Kessides (2005) finds that the urban landscape in Africa is not dominated by very large cities. On the contrary, the urban population is widely dispersed across mainly small settlements, with 52 percent of the urban Africans living in settlements with less than 200,000 inhabitants. 6The urban codes for 1999 HICES provided by the Central Statistical Authority (CSA) made possible the identification of these towns in the 1999 HICES/WMS. Each town is identified by a series of codes, which consists of a concatenation of zone, wereda, town, keftegna, kebele and enumeration areas codes. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 7 Figure 3. Urban Population and Urban Poverty Distribution, by Locality 100% Addis , 25% Major Addis , 22% Major towns, 80% towns, 35% 31% 60% 40% Small/medium Small/medium towns, 65% towns, 69% 20% 0% Urban population Urban poor Note: Major towns, defined as towns with more than 100,000 inhabitants, include Mekele, Gonder, Awasa, Dire Dawa, Addis Ababa, Bahir Dar and Adama. B. Spatial Distribution of Urban Poverty The latest trends indicate that urban poverty may be harder to fight than rural poverty. Based on the Ministry of Finance and Economic Development (MoFED)'s estimates, urban poverty increased by 4 percentage points (from 33 to 37 percent) over the period 1995-99, while rural poverty declined by two percentage points (from 47 to 45 percent) over the same period. Findings from the 2004 round of nationally representative household survey reported in PASDEP corroborate the view that urban poverty may be more difficult to curb than rural poverty: over the period 1999-2004 urban poverty saw only a slight reduction (from 37 to 35 percent) while rural poverty declined significantly from 45 to 39 percent.7 Deepening urban poverty is accompanied by rising urban inequality. "The Gini coefficient paints Ethiopia as an equal, but equally poor society" (World Bank 2005a, emphasis added). The image of Ethiopia as an equally poor society may however fail to capture the evolving urban reality. PASDEP reports no significant change in rural inequality, but rising level of urban inequality, with an increase in the Gini coefficient from 0.34 to 0.38 over the period 1995 to 1999 and again to 0.44 in 2004 in urban areas (PASDEP 2006). Urban poverty is slightly more spatially concentrated in small/medium towns than in major towns. Comparing the distribution of the urban population with the distribution of urban poverty can shed some light on whether urban poverty is spatially concentrated in any specific segment of the urban spectrum. The lower bound of the full poverty line ("the lower poverty line") as calculated in the 2005 World Bank Poverty Assessment is used as a poverty threshold throughout the study, resulting into 46 percent of the urban population 7 The Plan for Accelerated and Sustained Development to End Poverty (PASDEP) is Ethiopia second PRSP. A full- fledged poverty report from MoFED was not available at the time this study was conducted. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 8 being poor in 1999 (see also Box 1).8 The analysis suggests a slightly higher concentration of urban poverty in small/medium towns: 69 percent of the urban poor live in small/medium towns, compared to 65 percent of the urban population. The remaining 31 percent of the urban poor live in major towns, which represent 35 percent of the total population. The incidence of urban poverty is also higher in small/medium towns (50 percent) than in major towns (41 percent), as shown in Figure 4. Figure 4. Urban Poverty Incidence, by Locality 100% 80% 60% 46% 50% 41% 41% 40% 20% 0% Urban Small/medium Major towns Addis towns Note: Poverty rates are calculated based on the lower bound of the full poverty line in line with the 2005 World Bank poverty assessment. III. NARROWING DOWN THE FOCUS: NEIGHBORHOOD POVERTY This Section explores the within-urban spatial dimension of poverty: the poverty of neighborhoods. The Section first discusses why it is important to assess the intra-urban spatial distribution of poverty and how to measure it. Drawing on the 1999 HICES/WMS, the empirical evidence on the spatial distribution of urban poverty is then presented and its implications for poverty reduction are discussed. A. Intra-City Spatial Distribution of Poverty: why it matters and how to measure it International experience tells that it is worse to be income-poor in a poor neighborhood. Two different within-urban spatial patterns in income poverty can be identified. The first is a pattern of urban poverty concentration, which "refers to the confinement of the poor to a subset of neighborhood locations", which are disconnected from the urban fabric (Greene 1991). Poverty concentration implies urban segregation, and the consequent proliferation of multiple cities in one city. The second is a pattern of poverty dispersion, where the income poor are scattered across the urban space. Understanding towards which urbanization pattern Ethiopia is heading is essential for tailoring anti-poverty programs to the urban context. While income poverty can be thought as economic distance from the better off, urban segregation implies a physical distance and often also translates 8See World Bank (2005), p. 14. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 9 into social distance from the better off urban population. Hence, urban segregation makes 9 urban poverty harder to fight by compounding the negative effects arising from monetary poverty with the negative effects associated with physical and social segregation. For example, the residential location of the poor, by means of neighborhood-effects, does play a role in driving labor market outcomes through several channels. First, urban segregation can lead to higher unemployment rates for the urban poor by making it more difficult for demand and supply of low-skilled jobs to match, as the urban poor often have a restricted spatial range for job search and mobility (van Golde 1998). Second, the concentration of low-income consumers in one particular area is unlikely to sustain a vibrant business climate which could promote local employment opportunities and upward mobility (da Fonseca Freitosa and Wissman 2006). On the same vein, Atkinson and Kintrea (2001) find that it is worse to be poor in a poor area in Britain, in particular with regard to employment outcomes. Drawing on surveys for Glasgow and Edinburgh, the authors find that the percentage of people working outside their neighborhoods is lower, while unemployment is higher, in deprived neighborhoods than in mixed neighborhoods. .... and that neighborhood living standards matter. The second part of this Section deals with non-monetary deprivation associated with living conditions. This form of non- monetary deprivation finds its physical manifestation in slum settlements. UN-Habitat defines a slum settlement as a contiguous settlement whose inhabitants lack access to basic services (first and foremost improved water supply and sanitation) and live in unfit and overcrowded housing structures with no security of tenure (UN-Habitat 2002). The element of contiguity is a defining feature of slum settlements, as the proximity of people living in dismal conditions generates the negative externalities which characterize the life of slum dwellers. For example, it is the spatial concentration of people with no access to improved water supply and sanitation that puts people in slum settlements at higher risks of communicable diseases than the rest of the urban population (see Montgomery and Hewett--2004- for an application to Nairobi slums). A distinction needs to be made between people living in slum-like conditions and slum settlements. The literature often fails to account for the element of contiguity in the definition of slum settlements, especially in countries where GIS mapping techniques are not available. When the contiguity aspect is neglected, what is measured is not the incidence of slum settlements but rather the incidence of people living in slum-like conditions. In this study, a clear distinction is made between people living in slum-like conditions and slum settlements. People living in slum-like conditions are defined as dwellers suffering from some form of non-monetary deprivation associated with their living conditions. The actual forms of non-monetary deprivation may vary from country to country, but generally include lack of access to basic services, such as improved water and sanitation, overcrowding, poor structure of housing and no security of tenure. On the other hand, slum settlements arise when people living in slum-like conditions are geographically concentrated. Keeping the two concepts distinct is essential for policy making. Improving livability is a much more difficult task in slum settlements, where the poor bear not only the cost derived from lack of adequate services but also those associated with physical and social isolation as well as negative health externalities, than in mixed areas, where people living in slum-like conditions settle side-by-side with wealthier parts of the urban society. 9 The opposite relationship may however not hold true. For example, India's Caste System has been presented as an extreme case where strong social distance can prevail despite the spatial proximity among the different social groups (da Fonseca Freitosa and Wissman 2006). URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 10 There is often the misconception that income poverty and non-monetary deprivation coexist in a given space. To what extent income poverty and non-monetary deprivation associated with living conditions overlap is an empirical question to be validated on the ground. In some instances, dismal living conditions may not be associated with low levels of income; for example, an increase in household income is ineffective in securing a healthy environment for households living in slum settlements, where dwellers are exposed to negative externalities. Baud et al (2006) find for example that poverty and slum settlements do not overlap in Delhi, as slums are concentrated in the heart of the city, while poverty is more prevalent in the outskirts of the Corporation area. The extent to which monetary and non-monetary poverty overlap has relevant implications for designing anti- poverty and slum upgrading programs. When dismal living conditions and monetary poverty coexist, multiple entry points are needed to achieve the twin objectives to lifting people out of poverty and guaranteeing them minimum standards of living. On the other hand, income- enhancing interventions may not be the key entry point where slum settlements do not constitute hotspots of poverty. There is a rationale for public intervention to counter the negative externalities associated with spatial concentration in poverty. Concentration in monetary poverty can lead to bad outcomes such as social segregation and inefficient labor markets which impact on the urban society as a whole. Similarly, concentration of non-monetary deprivation generates negative externalities for all neighboring residents. The government has a range of measures available to promote a more cohesive urban society, both directly through slum upgrading programs and indirectly through land management and housing policies. In this context, policy-makers need to be conscious of the impact that urban policies can have on spatial segregation if urbanization is to be steered towards more sustainable outcomes. B. "Being poor in a poor area": is income poverty spatially concentrated? Evidence points to limited intra-urban spatial concentration in monetary poverty.10 A spatial analysis is conducted to assess the intra-urban spatial concentration in monetary poverty. The proportion of the poor living in clusters or neighborhoods with high poverty rates, usually above 20-50 percent, is conventionally adopted as a measure of poverty concentration.11 If a relatively high proportion of the urban poor reside in clusters with high poverty rates, then poverty is considered highly concentrated (see, for example, Greene 1991 and Jargowsky and Bane 1990). Enumeration areas are used as a proxy for clusters; hence, each enumeration area corresponds to a cluster unit for this exercise. The cluster is identified as a high-poverty neighborhood if the poverty rate in the cluster is 50 percent or higher; if the poverty rate is below 50 percent, the cluster is defined as a mixed-income neighborhood. In the case of Ethiopia, the spatial analysis does not point to high spatial concentration in monetary poverty: 43 percent of the urban poor live in high-poverty neighborhoods, which represent 28 percent of the total sampled neighborhoods (see Figure 6). Major towns show lower spatial concentration in income poverty than small/medium towns. There is variation in the spatial concentration of income-poverty across the urban space (see Figure 5). The percentage of the poor living in high-poverty 10Monetary and income poverty are used interchangeably in the study. 11In poverty mapping, researchers have used different cut-off levels for different countries of the world. For example, Woldemariam and Mohammed (2003) used a head-count ratio of 33 percent to define the least poor areas for Ethiopia, but for Malawi a higher proportion was used (49 percent). URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 11 settlements ranges from 31 percent in major towns to 48 percent in small/medium towns.12 In Addis Ababa, the percentage of the poor concentrated in high-poverty neighborhoods is even lower, amounting to 28 percent of the total. A similar trend is found when comparing the percentage of high-poverty neighborhoods across the urban spectrum: 33 and 20 percent of the enumeration areas are classified as high-poverty neighborhoods in small/medium and major towns, respectively. A sensitivity analysis is conducted to test the robustness of the results to changes in the cut-off point for high-poverty neighborhoods (assumed equal to 50 percent in the baseline scenario). Figure 5 shows how income poverty concentration is affected by changes in the underlying definition of high-poverty neighborhoods. Poverty concentration drops significantly as the definition of high-poverty neighborhoods is made more stringent. For example, only 10 percent of the poor is found to live in high-poverty neighborhoods, when the cut-off point is 70 percent--i.e., enumeration areas are defined as high-poverty neighborhoods if 70 percent of the residents are poor. In addition, the sensitivity analysis corroborates the findings that urban poverty is systematically more concentrated in small/medium towns than in major towns. The difference in concentration across the urban spectrum is more pronounced when the cut-off point is between 40 and 50 percent. While the analysis sheds some light on poverty concentration, it is far from providing a complete picture of the spatial distribution of income poverty. In particular, the analysis ignores the concentration effects which derive from the spatial organization of the enumeration areas themselves. Everything being equal, poverty concentration, and the risk of social segregation, is higher when high-poverty neighborhoods are all contiguous to each other rather than dispersed all over the city. Only GIS mapping techniques, which are currently not applicable to urban Ethiopia, could shed light on whether urban poverty settlements are themselves clustered or dispersed. 12Assuming a cut off point of 50 percent for the definition of high-poverty neighborhoods. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 12 Figure 5. Percentage of the Poor Living in High-Poverty Neighborhoods, by Definition of High-Poverty Neighborhood 100 90 80 Urban Small/medium towns 70 Large towns Poor Addis Ababa 60 the ofe 50 centag 40 Per 30 20 10 0 10 20 30 40 50 60 70 80 90 100 Cut-off Point for Definition of High-Poverty Neighborhood Figure 6. Percentage of High-Poverty Neighborhoods, by Locality 100% 80% 60% 40% 28% 33% 20% 19% 20% 0% Urban Small/medium Major towns Addis towns C. Slum settlements: are people living in slum-like conditions spatially concentrated? The literature differs on the percentage of slum dwellers in Ethiopia. The available literature suggests that slum dwellers range between 70 and 100 percent of the urban URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 13 population. Based on the UN-Habitat Global Observatory Database, the percentage of slum population in urban areas amounts to an astonishing 99.4 percent.13 According to the MDG assessment on slum dwellers, the disparities in estimates can be related to the fact "due to indigenous creation, the country does not exhibit the clear cut dualism in residential structure that is common among cities of colonial origin" (GoE 2004 and Olima 2001). The broad range of estimates may also be partially related to the fact that the literature often fails to recognize the difference between living in slum-like conditions and living in slum settlements (see Section A). This may be particularly the case in Ethiopia, where the contiguity aspects of slum settlements is difficult to capture in the absence of GIS mapping techniques. This Section makes a clear distinction between the two concepts, by assessing the extent to which people living in slum-like conditions are geographically concentrated in slum settlements. People living in slum-like conditions are defined based on three core livability indicators: access to improved water supply, access to improved sanitation and over-crowding. The internationally accepted UN-Habitat definition of people living in slum- like conditions is based on the following indicators: access to water supply, access to sanitation, overcrowding, security of tenure and housing quality (UN-Habitat 2003). While the UN-Habitat definition is often used in international benchmarking, international definitions may not always be operationally relevant at the country level. The UN-Habitat definition is therefore adjusted to reflect data availability and local conditions in the Ethiopian context. In this study, people living in slum-like conditions are defined based on three robust indicators which show sufficient intra-urban variability: access to water supply, access to sanitation and overcrowding. Structure of housing is not included among the indicators as it does not show enough variation to function as a screening variable: the majority of the urban population live in dwellings with similar structural features, in terms of both roof and wall material (81 percent of the urban population live in dwellings built of wood and mud and roofed with corrugated iron sheets or grass).14 Security of tenure is excluded from the definition because the indicator on house/land ownership derived from the survey is not refined enough to capture the complexity of the concept (see also Box 2). Two different operational definitions of people living in slum-like conditions are adopted in this study. People living in slum-like conditions in strict sense are defined as those suffering from multiple forms of non-monetary deprivation, namely as (i) not having access to improved water supply, (ii) not having access to improved sanitation and (iii) living in an overcrowded space. People living in slum-like conditions in a relaxed sense are defined as those failing to meet at least one of the three above forms of deprivation (see Table 1 below).15 When interpreting the results, one has however to keep in mind that information on access to water and sanitation is incomplete as the indicators do not account for quality of service provision, non-monetary costs (such as time traveled to fetch water) and affordability of service provision.16 13 See http://ww2.unhabitat.org/programmes/guo/documents/Table1.pdf 14 In addition, 90 percent of the urban population lives in dwellings roofed with corrugated iron sheets, 82 percent in dwelling built of wood and mud. 15 Sensitivity analysis has been conducted to check the robustness of the results to changes in the definition of people living in slum-like conditions. The results are available from the author. 16 Distance to point of supply indicators are not refined enough to capture intra-urban differences, so they could not be included in the core slum dwellers indicator. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 14 Table 1. Population living in Slum-like Conditions - Indicators Variable Definition No access to improved water supply Un-improved water sources include out of compound shared taps and unprotected well No access to improved sanitation Un-improved sanitation options include field/forest, bucket and shared pit latrines Overcrowding More than two people occupying a room The percentage of the population living in slum-like conditions varies to a significant extent according to the definition adopted. When the strict definition is adopted, the population living in slum-like conditions is estimated at 12 percent, with no significant difference across the urban space. When the relaxed definition is adopted, the percentage of population living in slum-like conditions escalates to 75 percent. The share of population living in slum-like conditions is relatively higher in small/medium towns (79 percent) than in major towns (68 percent) and the difference is statistically significant.17 This implies that 75 percent of the urban population suffers from some forms of non- monetary deprivation in living conditions, while only a small percentage suffers from multiple forms of deprivation. Figure 7. Percentage of Population living in Slum-like Conditions, Strict versus Relaxed Definition 100% Strict definition Relaxed definition 79% 80% 75% 68% 66% 60% 40% 20% 12% 11% 14% 13% 0% Urban Small/medium Major towns Addis towns Fifty-nine percent of the clusters are slum settlements, and slum settlements are more prevalent in small towns than in major towns. As mentioned above, for the purpose of this analysis slum settlements are defined by the spatial concentration of people living in slum-like conditions. An assessment of spatial concentration is conducted to estimate the extent to which slum settlements are an issue in urban Ethiopia. For analytical purposes, an enumeration area is defined as a slum settlement if at least 80 percent of its residents live in slum-like conditions based on the "relaxed" definition - i.e., they lack 17When the stringent definition of slum is adopted, the proportion of slum dwellers is slightly higher in major towns than in small towns, hinting that deep deprivation is relatively more common in major urban settings. However, the difference is not statistically significant based on 95 percent confidence interval. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 15 access to improved water supply or sanitation or they live in overcrowded dwellings.18 A higher cut-off point than the one used for the analysis of monetary poverty is chosen to reflect the very high incidence of people living in slum-like conditions in urban Ethiopia based on the relaxed definition.19 The analysis shows that 59 percent of enumeration areas are classified as slum settlements, i.e., in 59 percent of the enumeration areas at least 80 percent of the population has some basic needs unmet with respect to their living conditions (see Figure 9). A significant difference is found in the prevalence of slum settlements across the urban spectrum: 66 percent of the enumeration areas are classified as slum settlements in small/medium towns, compared to 47 percent in major towns. There is no evidence of significant spatial concentration among those living in slum-like conditions, but concentration is higher in small/medium towns. 70 percent of people living in slum-like conditions are estimated to reside in slum settlements, which represent 59 percent of the geographic urban space. The percentage is higher in small/medium towns (75 percent) than in major towns (60 percent), suggesting a more concentrated spatial distribution of people living in slum-like conditions in small/medium towns, compared to major towns. More stringent definitions of slum settlements results in a significant drop in spatial concentration. A sensitivity analysis is conducted to check the robustness of the findings to changes in the cut-off point for the definition of slum settlements (see Figure 9). There is a noticeable drop in spatial concentration when the cut-off point is increased above 80 percent. The percentage of people living in slum-like conditions that are found to reside in slum settlements drops from 70 percent to 42 percent when the cut-off point increases from 80 to 90 percent. The sensitivity analysis also corroborates the finding that slum settlements are more prevalent in small/medium towns than in major towns, as the differential between small/medium towns and major towns in the degree of spatial concentration of people living in slum-like conditions widens when the cut-off point increases from 70 to 90 percent. The results are interesting on two grounds: first, they show that people living in slum-like conditions tend to be scattered across urban centers; second, they indicate that income poverty and slum-like conditions have a similar rather dispersed pattern of spatial distribution in urban Ethiopia. 18For the purpose of the exercise, the less stringent definition of slum dwellers is applied, given the relatively low percentage of urban population meeting the strict slum definition criteria. 19Each enumeration area corresponds to a cluster unit for this exercise. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 16 Figure 8. Clusters Classified as Slum Settlements (Percent of Total) 100% 80% 66% 59% 60% 47% 44% 40% 20% 0% Urban Small/medium Major towns Addis towns Figure 9. Share of Population in Slum-like Conditions Living in Slum Settlements, by Definition of Slum Settlement 100 90 80 70 dwellers 60 m slu ofe 50 Urban 40 Small/medium towns Large towns Percentag 30 Addis Ababa 20 10 0 10 20 30 40 50 60 70 80 90 100 Cut-off Point for Definition of Slum-like Conditions URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 17 D. Income Poor and People living in Slum-like Conditions: to what extent is there overlap? The 1999 HICES/WMS suggests that monetary poverty and inadequate living conditions are distinct challenges, although significant overlap does exist. Only 52 of the people living in slum-like conditions are income poor based on the relaxed definition of people living in slum-like conditions.20 The overlap between the two groups is slightly more significant in small/medium towns than in major towns: 55 and 47 percent of people living in slum-like conditions are income poor in small/medium and major towns, respectively. On the other hand, a large share of the income poor suffers from non- monetary deprivation in living conditions: two-thirds of the urban poor live in slum settlements when the relaxed definition of people living in slum-like conditions is adopted.21 Looking at the overlap between high-poverty and slum settlements yield similar results, indicating that only 36 percent of slum settlements are high-poverty neighborhoods while 74 percent of high-poverty neighborhoods are slum settlements. Overall, the results indicate that that non-monetary deprivation in living conditions is significantly more widespread than monetary poverty. 39 percent of the Ethiopian urban population live in slum-like conditions and also suffers from monetary poverty. However, an additional 36 percent of the urban population lives in slum-like conditions without being income poor signaling that non-monetary deprivation associated with living conditions affects a much larger share of the urban population than monetary poverty (see Figure 10). Figure 10. Overlay between People living in Slum-like Conditions and Urban Poor (Percentage of Ethiopian Urban Population) Urban Poor (46%) 7% 39% 36% People living in slum-like conditions (75%) Note: The diagrams are based on the relaxed definition of people living in slum-like conditions. 20 When the strict definition of people living in slum-like conditions is adopted, the percentage of people living in slum-like conditions that are income poor increases from 52 to 72 percent. 21 19 percent of the urban poor suffer from deep non-monetary deprivation, based on the strict definition of people living in slum-like conditions. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 18 E. Conclusions Overall the analysis does not raise specific concerns with regard to the degree of spatial distribution of poverty, in particular in major towns. The results are consistent with the prevailing view that even cities as large as Addis Ababa display very integrated residential structures where the poor live side-by-side with the non-poor (see GoE 2004). Similarly, ENDA-Ethiopia (1999) finds that: A characteristic feature of Addis Ababa is that rich and poor live together without segregation. Slums are found in well-to-do areas, while wealthy residences and high buildings are standing in the midst of slum areas. The results, while far from being conclusive, provide some reflections on the importance of exploring the intra-urban spatial dimension of income poverty and non-monetary deprivation. The potential economic and social impacts of more concentrated poverty in small/medium towns compared to major towns are worth further investigation, in particular with respect to labor market outcomes. A more spatial concentrated distribution of poverty may make it more difficult for demand and supply of low-skilled labor to match in small/medium towns, compared to major towns. On the other hand, the negative effects of a more spatially concentrated pattern of poverty could be partially mitigated by the higher dynamism of labor markets in small/medium towns, relatively to major towns. Small/medium towns indeed exhibit a lower level of unemployment compared to major towns for all age groups: in small/medium towns, employment rates for 20-24 year old persons are for example 10 percentage points higher than in major towns (57 percent vs. 47 percent). (World Bank 2006). A word of caution is finally needed in interpreting the results, not only because GIS techniques are unavailable to corroborate the findings but also because the 1999 data may fail to capture the latest trends in the intra-urban spatial distribution of poverty. The relatively optimistic picture depicted by the 1999 data may have well been to some extent reversed by the rapid urbanization that has characterized Ethiopia over the last six years. The main findings of this Section are summarized in Table 2. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 19 Table 2. Spatial Connotation of Urban Poverty ­ Main Findings Urban Small/medium towns versus major towns Income · Slightly less than half (43%) of the urban · The percentage of the income poor living in high-poverty settlements poverty poor live in high-poverty neighborhoods, range from 31% in major towns to 48% in small/medium towns. In which represent 28% of the total sampled Addis Ababa, the percentage of the income poor concentrated in neighborhoods. high-poverty neighborhoods is even lower, amounting to 28% of the total. · 33% and 20% of the enumeration areas are classified as high- poverty neighborhoods in small/medium and major towns, respectively. People living· The percentage of the population living in · The percentage of population living in slum-like conditions is in slum-like slum-like conditions ranges from 12% to relatively higher in small/medium towns (79%) than in major towns conditions / 75%, depending on whether the strict or (68%) and the difference is statistically significant. slum relaxed definition is adopted, respectively. · 75% of people living in slum-like conditions reside in slum settlements · 70% of people living in slum-like conditions settlements in small/medium towns, compared to 60% in major live in slum settlements, which represent towns. 59% of the enumeration areas (when the · 66% of the enumeration areas are classified as slum settlements in relaxed definition is adopted). small/medium towns, compared to 47% in major towns. Overlap · Half of the people living in slum-like between conditions are income-poor, while 2/3 of the income poor urban poor live in slum-like conditions (when and people the relaxed definition is adopted) living in · 39 percent of the Ethiopian urban population slum-like live in slum like conditions without being conditions income poor. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 20 IV. LIVING CONDITIONS: URBAN ADVANTAGE AND URBAN INEQUALITY The available evidence paints a dismal picture with regard to living conditions in urban Ethiopia: two-third of the urban population suffer from some form of non-monetary deprivation related to their living conditions (i.e., they either lack access to improved water supply, access to improved sanitation or live in overcrowded dwellings). In light of this evidence, there is the need to delve further into the linkages between income poverty and specific indicators of living conditions. More specifically, this Section focuses on access to improved water supply, access to improved sanitation, access to electricity, solid waste management, overcrowding and security of tenure. The objective of this Section is to document the urban advantage relatively to rural areas with respect to access to basic services, the variation in living conditions across the urban spectrum and the level of intra- urban inequality in access to services. Access to improved water supply Access to improved water supply in urban areas is low, but significantly higher than in rural areas. Only 45 percent of the urban population has access to improved water supply, based on the 1999 HICES/WMS data. The remaining 55 percent relies on un- improved sources of water supply, namely public standpipes or unprotected wells (see Figure 11). On the other hand, urban areas fare significantly better than rural areas, where access to improved water supply is as low as 2 percent. The WHO/UNICEF Joint Monitoring Program (JMP) estimates a higher access rate to improved water supply in both urban and rural Ethiopia: in 2002, 81 percent of the Ethiopian urban population is estimated to have access to improved water supply, against 11 percent of the rural population (see WHO/UNICEF 2004). The discrepancy in access is likely to be related to a definitional issue given that the JMP model classifies public standpipes as an improved source of water supply, while in this study, out-of-compound share taps are classified as an un-improved source of water supply. The difference may also reflect the difficulty of empirically testing the standard definition of improved water supply, in a context where shared water connection is the norm. International comparisons, based on JMP data, shows that urban access to water supply in Ethiopia (81 percent) is in line with Sub-Saharan African average (estimated at 80 percent), while rural access (11 percent) falls significantly behind Sub- Saharan African average (42 percent). Major towns perform significantly better than small/medium towns with regard to access to improved water supply. 32 percent of the urban population in small/medium towns does have access to improved water supply, against 59 percent of the urban population in major towns. For a given quintile of the income distribution, the gap between small/medium towns and major towns is broadly constant (ranging from 20 percent for the poorest quintile to 26 percent for the wealthiest quintile), suggesting that the lower standard of service in small/medium towns cannot be attributed solely to a poverty issue, but it is most likely an issue of overall availability. Small/medium towns are likely to be on average more expensive to serve than major towns, due to their lower density of population and remoteness; the higher unit cost of supply can partially explain the lower access and quality of service in small/medium towns relatively to major urban centers. Still, inequality across urban quintiles is high. In addition to the overall low rate of service provision, there is significant inequality in access to improved water supply across quintiles. 25 percent of the urban population in the poorest quintile relies on improved sources of water supply, against 58 of percent of the wealthiest quintile. The degree of inequality in access to improved water supply is broadly similar across the urban spectrum. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 21 Figure 11. Urban Population with Access to Improved Water Supply (%), by Quintile and Locality22 100 80 70 60 55 51 58 41 44 40 38 38 32 36 33 25 27 23 18 20 0 1 2 3 4 5 Major towns Small/medium towns Urban Access to improved sanitation Access to improved sanitation in urban settings is low by international standards. Based on the 1999 HICES/WMS data, half of the urban population has no access to improved sanitation, relying instead on shared pit latrines, field or buckets as a sanitation option. Urban coverage is however significantly higher than rural coverage, estimated at 8 percent. While the coverage estimate from the 1999 HICES/WMS is consistent with GoE estimates, the JMP reports urban access to improved sanitation at only 19 percent in 2002 (against 4 percent in rural areas) (GoE 2005). Based on JMP data, access to improved sanitation in both urban and rural Ethiopia falls significantly behind the Sub-Saharan African average, estimated at 53 and 28 percent respectively. Access to improved sanitation appears to be an equally pressing issue across the urban spectrum, in contrast to access to improved water supply, which is significantly lower in small/medium towns, relatively to major towns (see Figure 12). ... and there is evidence of inequality in access across quintiles. Adding to the poor record of access in urban areas, evidence shows that the poor fare worse than the non- poor, across the urban spectrum. Considering the entire urban spectrum, only 35 percent of the poorest quintile has access to improved sanitation, against 57 percent of the wealthiest quintile. Caution is however needed in interpreting the results, given that the access variable does not capture differences in the quality of service, such as in the number of people sharing pit latrines. Lack of information on quality of service constrain our ability to grasp the severity (in particular the health and environmental impacts) associated with lack of improved sanitation. 22 Based on the following WMS survey question: "What is the main source of drinking water? (1) Taps inside the house; (2) Taps in compound private; (3) Taps in compound shared; (4) Taps outside the compound shared; (5) Protected well/spring; (6) Unprotected well/spring; (7) River, lake or pond". Options (1), (2), (3) and (5) are considered improved sources of water supply. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 22 Figure 12. Urban Population with Access to Improved Sanitation (%), by Quintile and Locality23 100 80 60 55 59 56 57 41 44 45 44 44 45 52 44 40 44 34 35 20 0 1 2 3 4 5 Major towns Small/medium towns Urban Access to Electricity Access to electricity is mostly an issue of overall availability, and does not depend on level of income. There is a striking difference in the percentage of the population with access to electricity as a lighting source across the urban spectrum. Access to shared electricity connections appear to be the norm in major towns and Addis Ababa, where virtually the entire population is covered by the grid. On the other hand, only 58 percent of the urban population is small/medium towns has access to electricity. As in the case of water supply, the low uptake may be related to availability constraints, which may be associated to the high unit cost of supply which generally characterizes small/medium urban centers based on international experience. It is also worth noting that urban areas, with an average access rate of 28 percent, fare significantly better than rural areas, where there is virtually no access to electricity. Small/medium towns show some degree of inequality in access across quintiles. While access to electricity is merely an issue of overall availability, there is some evidence of inequality, in particular in small/medium towns where the poor are affected more than the non-poor by lack of electricity access: 41 percent of the poorest quintile does have access to electricity, against 69 percent of the population in the wealthiest quintile (see Figure 13). 23 Based on the following WMS survey question: "What type of toilet facility does the household use? (1) Flush toilet/Private; (2) Flush toilet/Shared; (3) Pit latrine/Private; (4) Pit latrine/Shared; (5) Container (from hh items); (6) Field/Forest; (7) Other." Options (1), (2) and (3) are considered improved sanitation in this study. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 23 Figure 13. Urban Population with Access to Electricity (%), by Quintile and Locality24 100 94 95 97 96 97 81 80 73 69 65 65 61 60 53 54 51 41 40 20 0 1 2 3 4 Major towns Small/medium towns Urban5 Solid waste management Access to water disposal vehicles is not related to level of income, and is worse in small/medium towns, relatively to major towns. The environmental footprint associated with inadequate waste management is an urban feature, as rural dwellers have means of disposing waste with limited impact on the environment. The percentage of the population with access to waste disposal vehicles/containers is strikingly low across the urban spectrum, ranging from 7 percent in small/medium towns to 38 percent in major towns to 42 percent in Addis Ababa. There is no significant difference in access to waste disposal vehicles/containers between the poor and the non-poor, suggesting that waste management results mainly from the failure by the urban municipalities to deliver the service. The results suggest that the environmental externalities associated with waste management are high, especially in small/medium towns, where almost the entire urban population does not have access to environmentally safe waste disposal and collection (see Figure 14). 24 Based on the following WMS survey question: "What is the main source of lighting fuel? (1) Kerosene; (2) Electricity; (3) Fire wood; (4) Candle; (5) Others". URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 24 Figure 14. Urban Population with Access to Waste Disposal Vehicles/Containers (%), by Quintile and Locality25 100 80 60 42 38 40 34 34 31 24 20 17 10 14 13 11 3 6 5 6 0 1 2 3 4 5 Major towns Small/medium towns Urban Overcrowding In urban areas, overcrowding is highly correlated with level of income. In line with UN-Habitat definition, overcrowding is defined as occupancy rate above 2 persons per room (UN-Habitat 2002). The percentage of the population in the poorest quintile that lives in an overcrowded space is 59 percent, compared to only 18 percent of the population in the wealthiest quintile, suggesting that overcrowding is a more pressing issue among the urban poor, relatively to the rest of the urban population.26 Overcrowding is more severe in major towns than in small/medium towns. While major towns fare significantly better than small/medium towns in terms of access to basic services, the opposite is true with regard to overcrowding: 65 percent of the poorest quintile in major towns live in overcrowded dwellings against 57 percent of the poorest quintile small/medium towns. The high level of overcrowding in major towns is however not surprising given the housing backlog and lack of low income housing options which characterize major cities in Ethiopia (see World Bank 2005d) (see Figure 15). 25Based on the following WMS survey question: "What type of waste disposal facility does the household use? (1) Use waste disposal vehicle/container; (2) Use dug-outs; (3) Just throw away; (4) Use as fertilizer; (5) Burning the waste, (6) Other". 26A comparison of level of overcrowding between urban and rural areas cannot be conducted given that the indicator does not control for the size of the room and different structure of the dwelling. Our indicator would classify as overcrowding situations where households tend to live together in an open space. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 25 Figure 15. Urban Population Living in an Overcrowded Space (%), by Quintile and Locality 100 80 65 59 60 57 54 48 45 44 37 40 34 36 26 20 18 20 20 16 0 1 2 3 4 5 Urban Major towns Small/medium towns Note: Overcrowding is defined as more than two persons per room. Security of tenure Security of tenure is a more pressing issue in major towns than in small/medium towns. On average, 62 percent of the urban population is reported to have de facto ownership of land and housing. The average masks significant variation across the urban spectrum: 49 percent of the urban population in major towns has land and housing ownership, against 69 percent of the urban population in small/medium towns. A major caveat however applies, as ownership is at best an imperfect indicator of security of tenure, whose complexity is difficult to capture in one indicator (see UN-Habitat 2002). The correlation between security of tenure and land and housing ownership is particularly weak in the context of the Ethiopian land management and housing system, where land titling in 1999 was based on one-year renewable permits and no formal legal titles to housing existed (see also Box 2). Hence, even those households reporting to have ownership of land and housing may in fact have no or very limited security of tenure. Security of tenure is related to level of income in major towns only. While in small/medium towns there is no significant difference in security of tenure across quintiles, the gap is much more pronounced in major towns. Only 28 percent of the population in the poorest quintile reported to own land and housing, against 54 percent of the wealthiest quintile. A similar gap is found across quintiles for Addis Ababa. However, as mentioned above the reliability of the answers should be taken into account in interpreting the results (see Figure 16). URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 26 Figure 16. Urban Population with Land and Housing Ownership (%), by Quintile and Locality27 100 80 72 70 73 64 67 64 65 60 63 54 61 55 45 46 49 40 28 20 0 1 2 3 4 5 Major towns Small/medium towns Urban Box 2. Land Management System and Housing Markets in Ethiopia--A Snapshot Private land ownership was outlawed in Ethiopia under the Land Reform Bill of March 1975 passed during the Dergue regime, in favor of collective use of land under local Kebele Councils. Housing was nationalized, and all "surplus" houses, i.e., all houses other than those being used as primary residences by the owners were acquired by the government. The prevailing annual permit system, which was also inherited from the Dergue regime, grants only one-year rights for land and requires an annual renewal. Payments for "permit" land are very low and set up administratively, without any connection to market value of land. Waitlists for low-priced residential rents are endless and growing. Land is not mortgagable, despite the fact that the federal land lease law allows using lease land as a collateral (Kaganova 2005). In 2002, a new urban land lease system was designed to supersede the existing permit land system. While the uptake of the land lease system varies across cities, implementation of the lease system faces multiple challenges. For example, it is administratively very difficult to manage, because lease payments are due upfront and interests have to be paid on the outstanding amounts. In addition, the lease system is not yet very attractive and there is no voluntary conversion of permit rights into leases (Kaganova 2005). Ethiopia's concept of legal titles to property is only limited to land. There have never been titles for the housing unit per se: de facto ownership of a housing structure exists, but there is no formal title to the built property, which is one reason why banks and lending agencies have so far been unwilling to accept the "house" as collateral for a loan (World Bank 2005d). 27Based on the following two WMS survey questions: "Does any member of household (including the head of hh) own dwellings or buildings?" and "Does any member of the household own any land holding?". URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 27 Conclusions Empirical evidence points to a clear urban advantage with respect to access to basic services and high variation in living conditions across the urban space. There is a remarkable urban-rural gap in access to improved water supply, improved sanitation and electricity.28 However, the urban-rural gap hides considerable diversity within the urban spectrum. On one hand, small/medium towns fare distinctively worse than major towns as far as access to improved water supply, electricity and solid waste management is concerned. On the other hand, major towns are not spared by challenges: both security of tenure and overcrowding appear to be more pressing issues in major towns, compared to small/medium towns. Inadequate access to improved sanitation is as severe in major towns than in small/medium towns. The urban advantage is accompanied by high intra-urban inequality. The poorest quintile fares remarkably worse than the wealthiest quintile across all access indicators. The highest level of inequality is found with respect to access to improved water supply. In addition, both overcrowding and security of tenure are affecting more the poor than the non-poor. The main findings of this Section are summarized in Table 3. 28 The urban advantage relatively to rural areas is defined with respect to access to basic services only. A comparison between urban and rural areas with respect to security of tenure, overcrowding and waste management is not conducted given that security of tenure and waste management are almost exclusively an urban challenge, while the overcrowding indicator cannot be compared between urban and rural areas because of difference in dwelling structures. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 28 Table 3. Urban Poverty and Living Conditions ­ Main Findings Urban Urban versus Rural Poor versus non-poor Small/medium towns versus major towns Access to improved · Access to improved · Inequality is high: 25% of the · Major towns perform significantly better than water water supply is higher poorest quintile has access, small/medium towns: 32% of the urban in urban (45%) than compared to 58% of the wealthiest population in small/medium towns has rural areas (2%). quintile. access, compared to 59% in major towns. Access to improved · Urban coverage · The poor fare worse than the non- · No significant difference sanitation (50%) is higher than poor: 35% of the poorest quintile rural coverage (8%). has access, compared to 57% of the wealthiest quintile. Access to electricity · There is a striking · Access to electricity is mainly an · Access to electricity is the norm in major difference between issue of overall availability. There is towns and Addis Ababa, while only 58% of urban (28%) and however some inequality especially the urban population in small/medium towns rural access (0.1%). in small/medium towns, where 41% does have access. of the poorest quintile does have access to electricity, against 69% of the population in the wealthiest quintile. Solid waste management - · Access to water disposal vehicles is · The percentage of the population with access not related to level of income. to waste disposal vehicles/containers is strikingly low across the urban spectrum, ranging from 7% in small/medium towns to 38% in major towns to 42% in Addis Ababa. Overcrowding - · Overcrowding is highly correlated · Overcrowding is more severe in major towns with level of income. 59% of the than in small/medium towns. poorest quintile lives in an over- · 65% of the poorest quintile in major towns crowded space, compared to only 18 live in overcrowded dwellings against 57% of % percent of the wealthiest quintile. the poorest quintile small/medium towns Security of tenure - · Security of tenure is correlated to · Security of tenure is a more pressing issue in level of income in major towns only, major towns than in small/medium towns: where 28% of the population in the 49% of the urban population in major towns poorest quintile has ownership, has land and housing ownership, against against 54 % of the wealthiest only 69% of the urban population in quintile. small/medium towns. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 29 V. URBAN POVERTY: A DEMOGRAPHIC PROFILE Understanding the demographic profile of urban poverty is critical to target policy interventions effectively to the needs of the poor. The demographic profile of urban poverty impacts on the livelihood strategies of the poor and their capacity to lift themselves out of poverty. For example, urban female headed households (FHHs) may have access to a different, and often more limited, range of income-earning opportunities than male-headed households (MHHs), while lack of access to child day care may impair the ability of FHHs with infants to be active in the labor market. This Section first compares and contrasts the demographic profile of the urban and rural household, it then focuses on comparing the composition of the poor and non-poor households within the urban context, and finally presents the demographic profile of FHHs. The Urban Household Household size is on average the same in urban and rural areas, but in major towns households are larger than in small/medium towns. Households have on average 6 members in both rural and urban areas. Household size increases as we move across the urban spectrum from small/medium towns to major towns: the average household size is 5.7 and 6.3 in small/medium and major towns respectively, and the difference in size is statistically significant. Urban households are characterized by lower dependency ratios than rural households.29 The average number of children is slightly lower in urban settings (1.6 per family), than in rural settings (1.8 per rural family). Likewise, the average number of infants per family is lower in urban areas (0.8) than in rural areas (1.2) (see Table 4). On average, 13 percent of household members are infants in urban areas against 21 percent in rural areas. This finding is consistent with evidence of higher fertility rates in rural than urban areas, as reported in PASDEP. The ratio of adult females is significantly higher in urban than rural households. Adult females are more numerous in urban than rural families: the ratio of females to males is 56 percent for urban households and 51 percent for rural ones (see Table 4). This finding may be associated with the (albeit scant) evidence of rural-to-urban migratory flows. The 2004 Participatory Poverty Assessment suggests that, following life events such as widowhood and divorce, women tend to migrate to urban areas, where they find a less constraining environment and better employment opportunities than in rural areas (MoFED 2004). There are differences in household size and composition across the urban spectrum. As mentioned above, households tend to be larger in major towns than in small/medium towns: the average household size is 5.7 in small/medium towns and 6.3 in major towns. In addition, in major towns households are characterized by a higher number of adults (3.9) and a lower dependency ratio (0.8) that in small/medium towns, where on average there are 2.9 adults per family and a dependency ratio of 1.2. The larger household size in major towns, compared to small/medium towns, may be related to a shortage of affordable urban housing options, obliging different generations to live under the same shelter. The differential my also be related to step migration, as migrants often opt to move first from rural areas to nearby small/medium towns, and subsequently move to major 29 The dependency ratio is defined as number of children, infants and elderly divided by the number of adults (excluding elderly). URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 30 towns once they are comfortable enough to make the next move. Although evidence on step migration in Ethiopia is scarce, there is broad consensus that small/medium towns are playing the role of intermediate base for long-distance migrants (see World Bank 2006 and Box 3). Table 4. The "Urban" Household HH Infants Children Adults Elderly Ratio of Dependency Size females ratio Rural 5.9 1.2 1.8 2.6 0.2 51 1.4 Urban 5.9 0.8 1.6 3.2 0.3 56 1.0 Small/medium towns 5.7 0.9 1.7 2.9 0.3 56 1.2 Major towns 6.3 0.6 1.5 3.9 0.3 56 0.8 Addis 6.4 0.6 1.5 4.1 0.3 56 0.7 Note: Infants: [0-5], Children [6-14]; Adults [15-59], Elderly [60+]. The Urban Poor Household In the urban context, the poor household is on average larger and with a higher dependency ratio than the non-poor household. Significant differences are found between the urban poor and the non-poor with regard to the household composition. The urban poor household is on average larger (6.6 members) than the non-poor household (5.4 members). The dependency ratio is also higher in poor families, translating in a higher number of infants and children (see Figure 17). Size and composition of poor households differ across the urban spectrum. Mirroring the variation in household size and composition between small/medium and major towns, the composition of poor households is also remarkably different across the urban spectrum. In major towns poor households tend to be larger in size and to have a higher number of adult members and a lower number of children than poor households in small/medium towns (see Figure 17). URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 31 Figure 17. Household Composition ­ Poor versus Non-Poor Households Infants Children Adult male Adult female Elderly 8 7 0.3 0.3 6 0.3 1.9 2.3 5 0.3 1.7 4 1.8 1.6 1.4 2.0 3 1.3 2 2.0 2.0 1.3 1.9 1 0.9 1.0 0 0.7 0.7 Non poor Poor Small/medium towns - Major towns - Poor Poor Box 3. The Profile of Migrants in Urban Ethiopia According to the 2005 most recent national data an estimated 18 percent of the Ethiopian population lived in a different area than where they were born, and 6 percent had moved over the last 4 years up to 2005. The share of migrants of rural origin is high in Ethiopia: almost 70 percent of migrants are from rural origin, compared with less than 39 percent for the rest of Sub-Saharan Africa. Migrants tend to be young and concentrated in the most productive age groups. About half of the migrants are aged less than 19, while women migrants are more likely to be found in the age group 15-25. Migrants have low level of education, but they are on average more educated than non- migrants. Gender plays a role in determining the reasons behind the decision to migrate. Female reasons to migrate are generally related to marriage arrangement and dissolution. Work-related reasons are instead more prevalent among men. Reasons related to distress migration, such as displacement, war, drought are equally likely for men and women. Source: World Bank (2006), Vol II., Background Papers. Time to Move on? Internal Migration in Ethiopia and its Labor Market Implications. Female-headed Households The proportion of female headed household (FHH) is high in Ethiopia, compared to international standards. Ethiopia has the fifth highest percentage of female-headed households among the 22 African countries for which such data is available (see Kodama 2006). Nationwide, 19 percent of the households is female-headed. The high prevalence of female-led families is rooted in the historical and cultural roots of Ethiopia. For example, Meehan (2004) finds that the high prevalence of FHH in Tigray (30 percent of the population) is related to the loss of male combatants in both the civil war that ended in 1991 and the more recent Ethio-Eritrean conflict, a traditionally high age gap between wives URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 32 and husbands, leading to a high number of widows compared to widowers, and migration patterns, resulting in de facto FHH even where legal marriage still exists. Urban areas have a strikingly higher proportion of FHH than rural areas: 33 percent of the urban families are female-headed with no significant variation across the urban spectrum, against 17 percent of rural families. The percentage is high, compared to the 13 percent for urban Ivory Coast in 1988 (Grootaert et al. 1997) and the 33 percent for Mauritania (Coulombe and McKay 1996). Drawing on data from the Amhara region, Kodama (2006) points to the local socio-economic conditions pushing female heads to migrate to urban areas as one explanatory factor for the very high percentage of female heads in urban areas, compared to rural areas. Once a woman residing in rural areas becomes the family head, she is unlikely to be able to sustain herself unless she can get access to land and be allowed to put it to productive use. The ability of a woman to access land is very low in the Ethiopian context, where there is shortage of land and restrictions to both access and use of land by women (e.g., inheritance laws).30 Those female heads who are not able to access land have often no choice but to migrate to urban areas. The proportion of urban FHH with dependents and widow-led families is high. In urban areas, FHHs with one dependent represent 29 percent of the total urban population, and FHHs with one dependent infant constitutes 14 percent of the urban population. In addition, widow-led families represent a remarkable 15 percent of the urban population (see Figure 18). No notable difference in the proportion of widow-led households and FHHs is found between the poor and the non-poor. A modest but statistically significant difference however emerges in the proportion of female heads with three dependents, which is slightly higher among the poor (16 percent) than the non-poor (12 percent). The high percentage of female heads with one dependent infant raises concerns with regard to the female heads' ability to be active in the labor market, especially for those female heads that don't have access or cannot afford day care. This suggests that expanding access to affordable infant and child day care could be extremely effective in expanding the income-generating opportunities of a significant proportion of the urban population. Female heads tend to be older, based on life expectancy. With an average age of 44, female heads tend to be relatively older, based on a life expectancy at birth of 42 years. The majority of female heads (respectively 44 and 39 percent in urban and rural areas) falls into the 31-45 age range; and a significant number of female heads (28 and 27 percent respectively in urban and rural settings) falls into the 46-60 age range. Similarly, comparing 1994 Ethiopian census and the 2000 Ethiopian Demographic Health Survey, Angeli and Salvini (2005) find that the proportion of FHHs is higher the older the age of the head. When considering households heads in the 50+ age range, half of family heads are women, and the highest percentage of FHHs is found when the head of the household is 60+. 30Upon divorce, women are only entitled to take their movable property. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 33 Figure 18. Female Headed Households ­ Demographic Profile 40 33 33 35 31 29 30 25 20 17 16 15 16 17 16 14 15 12 9 9 10 8 8 9 5 3 0 Rural Urban Urban poor At least 1 dependent At least 3 dependents Widow Divorced/Separated At least 1 infant Fem head Conclusions Based on the 1999 HICES/WMS, urban households have a different demographic profile than rural households, as they tend to have a lower number of dependents and more adult females than rural households. Evidence also points to variations in the demographic profile of households across the urban spectrum: in major towns, urban households are larger, and have a higher number of adult members than in small/medium towns, suggesting that in major towns a shortage of affordable urban housing options may oblige different generations to live under the same shelter. Poor households are as expected found to be larger in size and with more dependents than non-poor households. Perhaps, the most striking result is related to the extremely high percentage of female-headed households in urban settings (33 percent), compared to rural areas (17 percent). The high percentage of FHHs with dependents (19 percent), in particular dependent infants (14 percent), raises concerns with regard to the income-generating opportunities available to female heads with limited or no access to child day care. The main findings of this Section are summarized in Table 5. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 34 Table 5. Demographic Profile of Urban Poverty ­ Main Findings Urban Urban versus Rural Poor versus non- Small/medium towns poor versus major towns Household · Household size (6 members) is · Poor households · Households are larger in size on average the same in urban (6.6) are larger major towns (6.3), and rural areas. than non-poor compared to small/medium households (5.4). towns (5.7). Household · Urban households have less · The dependency · Households in major towns composition children and infants than rural ratio is higher in are characterized by a households. poor families than higher number of adults and · The ratio of adult females is in non-poor ones. a lower dependency ratio higher in urban than rural than households in households. small/medium towns. The differential applies to both poor and non-poor. FHHs · 33 percent of urban families · No significant · No significant difference. are female-headed, compared difference. to 17 percent of rural families. · In urban areas, FHHs with one dependent represent 29 percent of urban families; FHHs with one dependent infant represent 14 percent of urban families. VI. URBAN POVERTY AND EDUCATIONAL ATTAINMENT Human capital formation is not only valuable on its own but also instrumental to economic growth and poverty reduction (see Box 4). For example, the education of the head of the household influences the way the household relates to the labor market and thus the income-earning opportunities of the household. This Section characterizes first the education profile of the urban population to then focus on the urban poor and FHHs. Urban-rural disparities are strikingly evident in terms of human capital formation. The 1999 HICES/WMS data show that the urban population draws on a larger stock of human capital than the rural population. On average, household heads have only one year of education in rural areas, compared to five years of education in urban areas (see Figure 19). A similar gap exists in the educational attainment of adult males and females across the urban-rural spectrum: on average, adult females have virtually no education in rural areas, while they have on average four years of schooling in urban areas (see Figure 20 and Figure 21). The striking difference in educational attainment between urban and rural areas is consistent with evidence of tighter supply-side bottlenecks in rural areas, resulting in high teacher-pupils ratios and limited availability of classrooms (World Bank 2005b). According to a World Bank study on Ethiopia, the education of the head of the household has implications for child enrollment in both urban and rural areas. Better educated heads of URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 35 households are more likely to have children enrolled in primary schools: for every additional year of educational attainment of the household head, the probability that a child is enrolled in school increases by 0.8 percentage points in urban areas and by 1.1 percentage points in rural areas (World Bank 2005a). The correlation could be related to the fact that uneducated parents underestimate the returns to education (see Box 4). Supply-side constrains coupled with low parental education in rural areas translates into much lower enrollments rates in rural areas, relatively to urban areas, and may contribute to the rural- urban divide in human capital formation. For example, 90 percent of urban children ever enroll in grade 1, compared to 45 percent of rural children. Once in school, rural children survive to grade 4 at about 72 percent the rate of urban children, but their survival rate to grade 8 is only 25 percent as high (World Bank 2005b). There is a significant difference in educational outcomes between small/medium and major towns. The gap in terms of years of schooling between small/medium towns and major towns is on average two years for both adult males and females. The gap is slightly less pronounced for heads of households, whose average schooling is 4.4 years in small/medium towns compared with 5.7 in major towns. The same differential is found for both poor and non-poor groups. ... but small/medium towns perform remarkably better than rural areas with regard to human capital formation. Small/medium towns are much closer to major urban centers than rural settings in terms of education attainment. As an example, heads of households have on average four years of education in small/medium towns, against a rural average of one year. In small/medium towns, the education of family heads in the poorest quintile is two years, above the educational attainment of the wealthiest quintile in rural families (1.6 years) (see Figure 19) Within urban inequality in educational attainment is significant. In urban areas, a marked difference in educational attainment emerges between the urban poor and the non- poor. The number of years of education of household heads is double for the non-poor (six years) than for the poor (three years). The gap in terms of adult education is also high, averaging two years for both adult females and males. The gap between the poor and the non-poor in much less pronounced in rural areas: for example, non-poor heads have on average one year of schooling, compared to 0.5 years for poor heads. A recently completed World Bank study on Ethiopia indicates that even such a minimal difference in educational attainment can translate into higher private returns to education when the level of education is below grade 4. This result does however not hold in urban areas, at least in the capital city, where returns from non-formal and grade 1-4 education are not statistically different than the returns from being illiterate. Hence, the results suggest that minimal education may be enough to make a difference in earnings in rural areas, but not in urban areas (World Bank 2006 and Box 4). The inequality in educational attainment between the poorest and the wealthiest quintiles is more marked in major towns. The gap in education outcomes is more prominent in major towns and Addis Ababa, where the differential in years of education between the poorest and wealthiest quintile is 5.2 and 6.7 years respectively, than in small/medium towns, where the differential is 4.4. There is an urban gender bias in human capital formation. There are large disparities in educational outcomes between adult females and males for a given quintile in urban areas. The bias in terms of female education is found across the urban spectrum, among the poor as well as the non-poor, suggesting that the gender bias is unlikely to be only related URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 36 to level of income (see Figure 20 and Figure 21). In other words, a poor woman is as likely to be less educated than a man than a non-poor woman, as the gap in terms of years of schooling between females and males is two years both for the poor and the non-poor. The results are consistent with the existing literature: a World Bank study finds that girls who reside in rural areas are 11.6 percentage points less likely to be enrolled in school than boys, everything else being equal; in urban areas, girls are still 4.3 percentage points less likely to be enrolled in school than boys (World Bank 2005). Box 4. Returns to Education in Urban Ethiopia The poverty reduction impact of education in urban areas cannot be over-emphasized. Bigsten et all (2003) find that education is an important factor in the determination of the longer-term welfare of households, but more so in urban than in rural areas Unlike in rural areas, in urban areas education of the household head and wife significantly affect both probabilities of moving out of and falling into poverty. For instance, households with heads or wives that had completed primary education had 12 and 22 percent, respectively, higher chance of getting out of poverty, and an 8 and 7 percent lower probability of falling into poverty. Households where the head, or wife, had completed primary education had respectively, a 23 and 18 percent better chance of remaining non-poor; conversely, they had 9 and 10 percent less chance of being ``chronically'' poor. All four coefficients on the primary education of the head and wife are highly significant, unlike for rural areas. Similarly, Kronlid (2001) finds that the returns to education in urban Ethiopia are high compared to international evidence, especially for higher education. Drawing from the three waves of the Ethiopian urban socio-economic survey for the years 1994, 1995 and 1997, the author estimates returns to education in terms of the effect of main income earner's education on log of per adult monthly income of the household, and finds returns of 13 percent, 28 percent, 37 percent and 153 percent respectively for primary, secondary, post-secondary and tertiary education. Again, parental education is found to play a significant role in enhancing household welfare, by increasing the probability of child enrollment into school. Delving more on the returns to education for different grade level, the private returns are found to follow a U-shape, in which they are highest at the lowest levels of educational attainment as well as at the top end (World Bank 2005b). Differences are found however in the patterns of returns in urban and rural: for Grades 1-4, the rural returns are much higher than those in urban areas; but they also drop off much more precipitously than in urban areas as the level of education rises, falling to only 8 percent a year for Grades 9-12, compared with a reasonably high 12 percent in urban areas (World Bank 2005b). On the other hand, World Bank 2006 finds a linear relationship between average returns to education and educational level in urban areas. Taking the illiterates as the reference group, the impact of education on earnings ranges from 28 percent for those with non-formal education to 90 percent for the highest skilled. Interestingly, differences in returns also emerge when splitting the sample between Addis and other urban areas. In other urban areas, returns to education are significant and higher than in Addis for all levels of education--for example, returns to grade 5-8 are 32 percent in Addis and 49 percent elsewhere. On the other hand, returns from non-formal and grade 1-4 education are not statistically different from illiterate in the capital, suggesting that minimal education may not be sufficient to compete in more dynamic urban labor markets (World Bank 2006). URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 37 Figure 19. Education Profile: Head of Household, Years of Schooling, by Locality 8 7 7 7 6 Poor 6 6 Non-Poor 6 6 5 Average 5 4 4 3 4 3 3 3 2 1 1 0.5 1 0 Rural Urban Small/medium Major towns Addis towns Figure 20. Education Profile: Adult Females, Years of Schooling ­ by Locality 8 7 Poor 6 Non-Poor 5 5 5 Average 5 4 4 4 5 4 4 4 3 3 3 2 2 1 0.2 0.4 0.4 0 Rural Urban Small/medium Major towns Addis towns URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 38 Figure 21. Education Profile: Adult Males, Years of Schooling ­ by Locality 8 8 8 7 7 Poor 6 7 Non-Poor 7 6 6 6 5 Average 5 5 5 4 4 3 2 2 1 1 1 0 Rural Urban Small/medium Major towns Addis towns Urban female heads have much lower educational attainment than male heads. In urban areas female heads fare worse than male heads with regard to educational outcomes, with on average half the number of years of schooling than male heads, across the urban spectrum. The differential in years of schooling between female and male heads is another expression of the gender bias. However, there is no significant gap in the number of years of schooling between female adults that are part of FHH and female adults that are part of MHH (see also Angeli and Salvini 2005). In addition, a female head is not found to have a statistically significant impact in the modeling of the probability of primary school enrolment and completion for the years 1996 and 2002. These results suggest that a child raised in FHHs is as likely as a child raised in a MHH to be enrolled and complete primary school (see World Bank 2005, p. 205). Poor female heads less years of schooling than poor male heads. Poor female heads are a particularly vulnerable group with regard to human capital formation, as they suffer from the gender bias as much as from the vulnerability derived from income poverty. Urban poor female heads have on average one year of schooling, against an average of four years of schooling for poor male heads. The educational attainment of poor female heads is comparable to the average rural level of education, and thus strikingly below the urban average. Hence, female-led families stand to benefit the most from increase in education: Kronid (2001) finds that 40 percent of the urban Ethiopian households are female-led, yet 58 percent of the household heads with no education are female-led. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 39 Figure 22. Education Profile: Female Heads, Years of Schooling ­ by Locality 8 7 7 7 6 6 6 5 5 5 4 4 3 3 4 3 3 2 1 1 2 2 2 1 0.0 0.2 1.0 0 0.2 Rural Urban Small/medium Major towns Addis towns FHH Poor FHH Non Poor MHH FHH Conclusions Empirical evidence from the 1999 HICES/WMS finds a significant gap between urban and rural areas in terms of educational attainment. The urban advantage masks however significant intra-urban inequality: small/medium towns dwellers have on average two years less of schooling than major towns dwellers; across the urban spectrum the poor fare significantly worse the non-poor (e.g., non-poor heads have on average six years of schooling, compared to three years for poor heads). There is also evidence of a significant urban gender bias with regard to years of schooling. Poor female heads appear to be a particularly vulnerable group, with significant less years of education than poor male heads. The main findings of this Section are summarized in Table 6. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 40 Table 6. Urban Poverty and Educational Attainment ­ Main Findings Urban Urban versus Rural Poor versus non-poor Small/medium towns Female versus male versus major towns heads Educational · On average, household · Non-poor heads have on · The gap in terms of · Female heads have on attainment heads have only one average six years of schooling, years of schooling average half the (years of year of education in compared to three years for between small/medium number of years of schooling) rural areas, compared poor heads. towns and major towns schooling than male to five years of · The education gap between is on average two years heads, across the education in urban the poor and the non-poor for both adult males and urban spectrum. areas. averages two years for both females. · Urban poor female · A similar gap exists in adult females and males. heads have on the educational · The gap in education outcome average one year of attainment of adult between the poorest and schooling, against an males and females: on wealthiest quintile is more average of four years average, adult females prominent in major towns of schooling for poor have virtually no (5.2) and Addis Ababa (6.7), male heads. education in rural than in small/medium towns · The educational areas, while they have (4.4). attainment of poor on average four years female heads is of schooling in urban comparable to the areas. average rural level of · As far as the education education, and thus of the heads of strikingly below the household is urban average. concerned, the gap between the wealthiest and the poorest quintile is only one year in rural areas, compared to five years in urban areas. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 41 VII. COPING WITH VULNERABILITY: INCOME DIVERSIFICATION AND SAFETY NETS The livelihood strategies of the poor are markedly different in urban and rural contexts; even within the broad urban spectrum, the poor may resort to different livelihood strategies than the non-poor as a way of adapting to the opportunities and risks of the local environment. While capturing urban-rural differences in livelihood strategies is beyond the scope of this study, some light can be shed on how the local environment affects the livelihoods of the poor by documenting spatial differences in income diversification strategies and safety nets. Income diversification can be considered a form of risk management strategy, as households with a more diversified income base are better able to withstand the welfare impact of income shocks. Safety nets are also an essential part of any risk management strategy as they help counter the vulnerability that derives from urban poverty. A. Urban Poverty and Income Diversification An important aspect of the livelihoods of the urban poor is their degree of income diversification. Given the wider set of employment opportunities and the greater reliance on cash income which characterizes the urban environment, the urban poor may be able to diversify their income portfolios more than the rural poor, and thereby shield themselves against the vulnerability that comes with increased reliance on the market. This stylized fact about the urban life is confirmed by empirical evidence from the 1999 HICES/WMS. Urban dwellers are more income-diversified than rural dwellers. The 1999 HICES/WMS shows that agriculture is the base of the rural economy: 74 percent of rural inhabitants rely on agriculture as their primary source of income. As expected, urban dwellers are more income-diversified than rural dwellers: 37 percent of the urban population relies on wage-income for sustenance, 34 percent on self-employment and 22 percent on other source of income. The comparable figures for the rural population are 3.0, 4.6 and 18.4 percent, respectively (see Figure 23).31 A relatively high percent of urban dwellers rely on agriculture as their primary source of income. Urban agriculture plays an important role in defining urban livelihoods, especially in peri-urban areas, and constitutes the main source of income for as much as 7 percent of the urban population. Furthermore, an additional 30 percent of urban dwellers derives part of their income from agricultural activities. ... but the role of urban agriculture as a main source of income varies across the urban spectrum. Urban agriculture plays a minimal role in major towns (only 1 percent of the population relies on agriculture as their main source of income), and a much bigger role in small/medium towns, where 10 percent of the population relies for their subsistence on agriculture. It is worth noting that the results are likely to underestimate the overall role that urban agriculture plays in the livelihood strategies of the urban population, because the available classification of income sources is too coarse to capture inter-sectoral linkages. For example, while only a small fraction of the urban population in small/medium towns derives their income directly from agriculture, much of the non-agricultural employment in smaller urban centers may be in agro-processing industries or services, and thus indirectly related to agricultural activities. 31Results are derived from Question 20 in the WMS survey: What is the main source of income of the households? URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 42 Reliance on agriculture drops drastically from rural areas to small/medium towns. Strikingly, the percentage of the population relying on agriculture as their main source of income drops from 74 percent in rural areas to 10 percent in small/medium towns. On the other hand, 41 percent of the population in small/medium towns still derives some income from agriculture activities, against only 9 percent of the urban population in major towns. Urban dwellers in small/medium and major towns differ in their income diversification profile. The main difference in the income base between dwellers in small/medium and major urban centers is related to the relative weight of self-employment and wage income. Reliance on wage income as the main source of sustenance is more common in large urban centers (53 percent) than in small/medium towns (28 percent). On the other hand, small/medium town dwellers rely relatively more on self-employment (39 percent) as their main source of income than major town dwellers (24 percent) (see Figure 23). Figure 23. Main Source of Income, by Locality Sources of Income - Rural Sources of Income - Urban 7.1% 18.4% 22.4% 3.0% 4.6% 33.6% 74.0% 36.9% Agriculture Self-employment Wage Other Agriculture Self-employment Wage Other Sources of Income - Small/medium Sources of Income - Major Towns Towns 10.3% 1.2% 22.9% 21.4% 24.4% 38.6% 28.2% 53.0% Agriculture Self-employment Wage Other Agriculture Self-employment Wage Other Income source is more a function of location than level of income, but there is some variation in the composition of income between the poor and the non-poor. When controlling for the size of urban settlements, no significant difference is found in the pattern of income diversification between the poor and the non-poor: the poorest quintile of URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 43 the population appear to be as diversified in its income base as the wealthiest quintile. There is however evidence of some variation in income composition between the poorest and wealthiest quintiles. The poorest quintile relies relatively less on wage (31 percent) and more on self-employment (38 percent) as its main source of income than the wealthiest quintile (43 percent and 31 percent, respectively). This pattern is found in both small/medium and major towns. The urban poor in small/medium towns have a different pattern of income diversification than the urban poor in major towns. Wage as the main source of sustenance is more prevalent among the poorest quintile in major towns (52 percent) than in small/medium towns (25 percent). The opposite trend is found with respect to other income sources, which are more common as the main source of income among the poorest quintile in small/medium towns (26 percent) than in major towns (11 percent). The poorest quintile in Addis Ababa has a pattern of income diversification in line with the poorest quintile in major towns. In urban areas, FHHs rely slightly more on other sources of income, and less on wage income, than the average population. For example, 28 percent of the FHHs in the poorest quintile draws on other sources of income for their sustenance, against 23 percent of the urban poorest quintile. On the other hand, 26 percent of the FHHs in the poorest quintile relies on wage income compared to 31 percent of the urban population in the poorest quintile. This pattern is found across quintiles. This may indicate that female heads may have less access to formal employment opportunities than the average, as also suggested by their disadvantage in term of human capital formation. Conclusions This Section finds that, as expected, urban dwellers are more income-diversified than rural dwellers. Evidence also shows that income composition is affected much more by location than level of income, as no significant difference is found in the level of income diversification across quintiles. On the other hand, some variations emerge in the income composition across quintiles: overall, the poorest tend to rely more on self-employment and less on wage than the wealthiest as their main source of income. Table 7 summarizes the main findings of this Section on urban poverty and income diversification. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 44 Table 7. Urban Poverty and Income Diversification - Main Findings Urban Urban versus Rural Poor versus non-poor Small/medium towns versus FHHs versus major towns average urban Income profile · Urban dwellers are · In urban areas, the poorest · Reliance on wage as main · In urban areas, more income- quintile relies relatively less source of income is more FHHs rely slightly diversified than on wage employment (31%) common in major towns more on other rural dwellers. as the main source of (53%) than in small/medium sources of income, income than the wealthiest towns (28%). and less on wage quintile (43%). · Small/medium towns income, than the · In urban areas, the poorest dwellers rely relatively more average. quintile relies more on self- on self-employment (39%) employment (38%) than the than major towns dwellers wealthiest quintile (31%). (24%). · Wage is more prevalent among the poorest quintile in major towns (52%) than in small/medium towns (25%). Reliance on · 74% in rural areas, · 10% in small/medium · 10% in small/medium · In line with urban agriculture against 7% in towns, compared to 1% in towns, compared to 1% in average. urban areas. major towns. major towns. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 45 B. Urban Poverty and Safety Nets The urban poor are generally highly vulnerable to shocks, as informal safety nets easily break down in the urban space, where crime, theft and disorder combined with social segregation may expose the urban poor to high risk. Vulnerability is thus central to the lives of the urban poor and calls for measures to mitigate the impact of shocks as well as enhance the poor's capacity to respond to them. Comparing the risk management options available to the urban poor is well beyond the scope of this study; nevertheless, the 1999 HICES/WMS data can shed some light on the relative effectiveness of different types of safety nets in reaching the urban poor. Reliance on transfers is often the most critical safety net for the poor. The objective of this Section is to assess the effectiveness of different types of transfers in reaching the urban poor. For analytical purposes, four different types of transfers are identified, based on the source of the transfer: private transfers, public cash transfers, transfers from NGOs and transfers from abroad (remittances). The data does now allow distinguishing between different sources of transfers from abroad. To capture the effectiveness of the transfers in reaching the poor, the poverty status is defined based on the pre-transfer expenditure distribution. In essence, for the purpose of this exercise the poor are defined as those whose pre-transfer expenditure is below the poverty line. As discussed in Box 2, the poverty line is set at a different level in each region to allow for the possibility that households living in different locations consume different baskets of goods at different prices, for a given level of wealth.32 Private transfers Private transfers are larger in size in urban areas than in rural areas, although coverage is similar. Overall, the 1999 HICES/WMS data suggests that private transfers represent an important safety net in both urban and rural areas: 54 percent of the urban population received private transfers, compared to 50 percent of the rural population.33 However, substantial differences characterize the value of the transfers received in urban and rural areas. The per capita median transfer is significantly higher in urban areas (Birr 37) than in rural areas (Birr 16).34 Similarly, the urban poor receive a median transfer of Birr 47, which is more than the double than the private transfer received by the rural poor (Birr 19).35 In urban areas, the poor benefit more from private transfers than the non-poor. In urban areas, a higher percentage of the poor (60 percent) receive private transfers, compared to the non-poor (48 percent), and the difference is statistically significant. In addition, the urban poor receive a median transfer of Birr 47 per capita, significantly above the amount received by the urban non-poor (Birr 26) (see Figure 27).36 Measured as a percentage of per capita expenditure, private transfers represent a significant higher share of total expenditure for the poor (5.4 percent) than for the non-poor (1 percent). 32Considering the post-transfer expenditure distribution may lead to underestimating the effectiveness of the transfer system, as those who were able to make it out of poverty because of the transfer system would be erroneously classified as non-poor. 33In rural areas, however, non-cash mechanisms might be more prevalent, such as oxen and labor sharing. 34Median transfer size is calculated based on the number of people actually receiving the transfer. 35The percentage of the poor reached by private transfer is 51 and 56 percent respectively in urban and rural areas (although the difference is not significant based on a 95 percent confidence interval). 36Median transfer size is calculated based on the number of people actually receiving the transfer. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 46 Public cash transfers Public cash transfers are less prevalent in urban than rural areas, although comparable in size. Particularly relevant for poverty reduction is the distribution of public cash transfers. Cash transfers are less prevalent in urban than in rural areas: 8 percent of the urban population receives public transfers, against 12 percent of the rural population. The differential is more pronounced between the urban and the rural poor: 10 percent of the urban poor receive public transfers, against 21 percent of the rural poor, and the difference is statistically significant. On the other hand, public transfers are comparable in size between urban and rural areas: the median per capita transfer amounts to Birr 36 and 38 in urban and rural areas, respectively; similarly, the urban and rural poor reached by public cash transfers receive on average the same per capita transfer value, equal to Birr 47 per capita. Targeting of public cash transfers to the urban poor is imperfect at best, and worse in Addis Ababa, compared to small/medium towns. Only 10 percent of the urban poor are reached by public cash transfers. In addition, there is a considerable amount of leakage as 6 percent of the non-poor are recipients of public cash transfers. In terms of value of transfers received, the evidence is mixed: overall, the urban poor benefiting from cash transfers receive a larger per capita transfer (Birr 47) than the non-poor (Birr 20). This result masks however significant differences across the urban spectrum. In small/medium towns, the poor receive a significantly higher per capita transfer (Birr 56) than the non-poor (Birr 20). The opposite is however true in Addis Ababa, where the non-poor benefiting from public cash transfers receive a per capita public cash transfer of Birr 53, almost the double than the transfer received by the poor (Birr 21). Public cash transfers are more prevalent and higher in value in small/medium towns than in major towns. There are significant differences within the urban spectrum in the distribution of public cash transfers. Small/medium towns appear to have more of a rural character with respect to the distribution of public transfers: 13 percent of the poor in small/medium towns receive public transfers, compared to only 4 percent of the poor in major towns. In addition, in small/medium towns the poor reached by public cash transfers receive on average Birr 56 per capita, which is more than the double of the amount received by the poor in major towns and Addis Ababa (Birr 24 and Birr 21 per capita respectively). Transfers from NGOs Per capita NGOs transfers are significantly larger in urban areas than rural areas, although coverage is similar. NGO transfers show a pattern similar to private transfers: in terms of coverage, both transfers do not show any specific bias in favor of urban areas; in terms of transfer value, they both tend to benefit relatively more the urban population than the rural population. NGOs transfers are as likely to reach the urban as the rural population: transfers from NGOs are received by 8 percent of the population in both urban and rural settings, and by 12 and 11 percent of the urban and rural poor, respectively. The urban population benefiting from NGO transfers receives however larger per capita amounts (Birr 50) than the rural population (Birr 13). Similarly, the urban poor receive on average Birr 53, more than double the amount received by the rural poor (Birr 17).37 In urban areas, the poor are more likely to receive NGO transfers than the non- poor, but receive on average the same transfer value. Within urban areas, 12 percent of the poor receive transfers from NGOs, compared to 6 percent of the non-poor. On the 37Median transfer size is calculated based on the number of people actually receiving the transfer. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 47 other hand, there is no significant difference in the per capita transfer value between the poor (Birr 53) and the non-poor (Birr 47) across the urban spectrum (see Figure 27).38 The average per capita NGO transfer is larger in small/medium towns than in major towns. On average, small/medium towns dwellers reached by NGOs transfers benefit from larger per capita transfers (Birr 68) than major towns dwellers (Birr 22). The incidence of the transfer is also slightly higher in small/medium towns (10 percent) than in major towns (7 percent). Remittances from abroad Remittances from abroad reach a minimal part of the population, and mostly urban dwellers in major towns. Only one percent of the rural population receives transfers from abroad, compared to 3 percent of the urban population. Within the urban population, the poor are as likely as the non-poor to benefit from remittances from abroad. The percentage of the urban population benefiting from remittances is significantly higher in major towns (6 percent) than in small/medium towns, where only 2 percent of the population receives remittances. In major towns, including Addis Ababa, the non-poor benefiting from remittances receive larger per capita transfers (Birr 574) than the poor (Birr 442). Transfers to female-headed families Among the urban poor, FHHs are more likely to receive private transfers than MHHs. 73 percent of the poor FHHs receive private transfers against 52 percent of the poor MHHs. This may reflect the fact that urban FHHs are more vulnerable and therefore need more support from relatives left behind in rural areas to sustain themselves. No significant difference between FHHs and MHHs is however found with respect to the coverage of the other transfers (see Figure 28). Poor FHHs in small/medium towns benefit more from transfers than poor FHHs in major towns. Poor FHHs in small/medium towns are more likely to receive transfers than poor FHHs in major towns. 75 percent of poor FHHs in small/medium towns receive private transfers, compared to 68 percent of poor FHHs in major towns. Similarly, 14 percent of poor FHHs in small/medium towns receive NGO transfers, against 8 percent in major towns. In addition, in small/medium towns poor FHHs receive larger per capita transfers (Birr 102) from NGOs than poor FHHs in major towns (Birr 21) (see Figure 29).39 There is no difference in the value of private and public cash transfers received by FHHs in small/medium towns and major towns. 38Median transfer size is calculated based on the number of people actually receiving the transfer. 39Median transfer size is calculated based on the number of people actually receiving the transfer. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 48 Figure 24. Percentage of the Population Receiving Transfers, by Locality 60% 55% 54% 52% 53% 50% 50% 40% 30% 20% 12% 10%10% 10% 8% 8% 8% 7% 8% 6% 5% 6% 4% 3% 1% 2% 0% Rural Urban Small/medium towns Major towns Addis Transfer from Abroad Transfer from other households Transfer from government Transfer from NGO Figure 25. Percentage of the Population Receiving Transfers, Poor versus non-Poor, by Locality 70% 60% 61% 60% 57% 57% 54% 50% 48% 48% 48% 47% 49% 40% 30% 21% 20% 11% 12% 13%13% 10% 8% 9% 10% 7% 6% 7% 6% 7% 5% 8%6% 6% 5% 6% 5% 5%7% 3% 3% 4% 5%6% 4% 1% 2% 0% Poor Non-poor Poor Non-poor Poor Non-poor Poor Non-poor Poor Non-poor Rural Urban Small/medium towns Major towns Addis Transfer from Abroad Transfer from other households Transfer from government Transfer from NGO URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 49 Figure 26. Per Capita Transfer (Birr), by Locality 180 160 140 120 68 100 50 rr Bi 80 22 21 60 13 25 36 45 26 40 38 48 20 45 37 33 16 - Rural Urban Small/medium towns Major towns Addis Private transfers Public cash transfers Transfers from NGOs Note: The stack bar of the charts does not represent the total value of per capita monthly transfer, as some people may receive one type of transfer but not the other. Figure 27. Per Capita Transfer (Birr), Poor versus non-Poor, by Locality 180 160 140 64 120 53 100 rriB 23 17 23 80 77 17 47 46 56 21 26 21 60 53 12 24 40 47 20 32 20 54 54 20 47 41 37 19 26 33 24 15 0 Poor Non-poor Poor Non-poor Poor Non-poor Poor Non-poor Poor Non-poor Rural Urban Small/medium towns Major towns Addis Private transfers Public cash transfers Transfers from NGOs Note: The stack bar of the charts does not represent the total value of per capita monthly transfer, as some people may receive one type of transfer but not the other. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 50 Figure 28. Percentage of the Population Receiving Transfers, Poor FHH versus Poor MHH, by Locality 80% 75% 73% 70% 68% 69% 60% 52% 53% 51% 51% 50% 40% 30% 20% 12% 15% 14% 12% 11% 12%13% 9% 10% 7% 8% 8% 8% 4% 4% 4% 4% 4% 4%4% 2% 2% 3% 4% 1% 0% FHH MHH FHH MHH FHH MHH FHH MHH Urban Small/medium towns Major towns Addis Transfer from Abroad Transfer from other households Transfer from government Transfer from NGO Figure 29. Per Capita Transfer (Birr), Poor FHH versus Poor MHH, by Locality 350 300 250 83 102 21 24 200 r Bir 66 150 72 100 202 32 31 23 135 50 114 37 47 32 30 29 37 - Poor FHH Poor MHH Poor FHH Poor MHH Poor FHH Poor MHH Urban Small/medium towns Major towns Transfer from other households Transfer from government Transfer from NGO Note: as different households receive different types of different transfers; the stack bar of the charts does not represent the total value of household monthly transfer. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 51 Conclusions The rural poor benefit more from public cash transfers than the urban poor, while the urban poor rely more on private transfers and transfers from NGOs. Public cash transfers are more prevalent in rural than urban areas (although comparable in size): 21 percent of the rural poor receive public cash transfers, compared to 10 percent of the urban poor. On the other hand, the urban poor rely more on private transfers than the rural poor: 60 percent of the urban poor benefit from private transfers, against 54 percent of the rural poor; the urban poor also receive significantly larger per capita median private transfers than the rural poor (Birr 47 and 19, respectively). The urban poor also benefit more from NGO transfers: the per capita median transfer from NGOs is significantly larger in urban than rural areas (although coverage is similar). Overall, the volume of transfers flowing to urban areas is significantly larger than the volume flowing to rural areas. Overall, urban areas receive a significantly larger volume of transfers than rural areas despite the fact that the total public cash transfer to rural areas is almost twice as much the overall transfer to urban areas. The smaller volume of public cash transfers flowing to urban areas is more than compensated by the volume of private transfers entering urban areas, which is more than threefold the volume flowing to rural areas. Similarly, total NGO transfers to urban areas are almost three times larger the transfer to rural areas. Location matters: the urban poor in small/medium towns have better access to safety nets than the urban poor in major towns. The urban poor in small/medium towns are more likely to receive public cash transfers (13 percent), private transfers (61 percent) and NGO transfers (13 percent) than the urban poor in major towns (where percentage are respectively 4, 57 and 8 percent). On the other hand, the per capita median transfer does not differ significantly across the urban spectrum, with the only exception of transfers from NGO, whose median value is larger for small/medium towns poor (Birr 64) than for major towns poor (Birr 21).40 While the urban poor in small/medium towns are less likely to receive remittances from abroad (1 percent) than the urban poor in major towns (3 percent), the coverage and the size of this transfer among the poor is so limited that it is unlikely to make any significant difference in the welfare of the poor in both small/medium and major towns. There is more leakage to the non-poor in major towns than in small/medium towns. Overall, the proportion of the urban poor receiving public cash and NGO transfers is higher than the proportion of the urban non-poor. However, the overall urban trend hides significant differences within the urban spectrum, as leakage appears to be lower in small/medium towns, compared to major towns. In small/medium towns, 13 percent of the poor are reached by public cash transfers, against 7 percent of the non-poor. In major towns, only 4 percent of the poor are reached by public cash transfers against 5 percent of the non-poor. In major towns, transfers from NGOs are slightly more pro-poor than public transfers: 8 percent of the poor in major towns benefit from NGO transfers against 6 percent of the non-poor. Still, leakage is lower in small/medium towns, where 13 percent of the poor are reached by NGO transfers, against 6 percent of the non-poor. The main findings of this Section are summarized in Table 8. 40Transfer value is calculated conditional on receiving the transfer. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 52 Table 8. Urban Poverty and Safety Nets ­ Main Findings Urban Urban versus Rural Poor versus non-poor Small/medium towns versus Poor FHHs versus major towns poor MHHs Private · No significant difference in · The poor are more likely to · No significant difference in · Among the urban transfers coverage. receive private transfers coverage (55% in poor, FHHs are · Per capita private transfers (60%) than the non-poor small/medium and 52% in more likely to are significantly larger in (54%). major town). receive private urban areas (Birr 37) than in · In urban areas, the poor · Per capita transfers are transfers than rural areas (Birr 16). receive larger per capita slightly larger in major towns MHHs. transfers (Birr 47) than the (Birr 48) than small/medium · Poor FHHs in non-poor (Birr 26). towns (Birr 33). small/medium towns are more Public cash· Public cash transfers are less · Targeting of public cash · Public cash transfers are more likely to receive transfers prevalent in urban (8%) transfers to the urban poor is prevalent in small/medium transfers than than rural areas (12%). imperfect at best: 10% of the towns than in major towns. poor FHHs in · Size is comparable. poor versus 6% of the non- · Per capita public cash transfers major towns. poor receive the transfer. are larger in size in · In small/medium · Average transfer value is small/medium towns (Birr 45) towns poor FHHs larger for the poor (Birr 47) than in major towns (Birr 48). receive larger per than for the non-poor (Birr capita NGO 26). However the opposite is transfers than true in Addis Ababa. poor FHHs in NGO transfer· No significant difference in · In urban areas, the poor are · Coverage is similar: 10 major towns. coverage. more like to receive transfers percent in small/medium · Per capita NGOs transfers (12%) than the non-poor towns and 7 percent in major are significantly larger in (6%). towns. urban areas (Birr 50) than · Size is comparable. · Transfer value is larger in rural areas (Birr 13). small/medium towns than in major towns. Remittances · Only one percent of the rural · Within the urban population, · Incidence is higher in major population receives transfers the poor are as likely as the towns (6 percent) than in from abroad, compared to 3 non-poor to benefit from small/medium towns (2 percent of the urban remittances from abroad. percent). population. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 53 VIII.URBAN POVERTY AND EXPENDITURE PATTERNS: ARE BASIC SERVICES AFFORDABLE FOR THE POOR? Comparing the budget shares of the poor against the urban average can shed light on whether the poor can afford consumption of basic services and whether inequalities arise with regard to service provision. The results need however to be interpreted with caution, given that budget shares only tell one side of the story. Low budget shares may mask under-provision of essential services rather than being a true indicator of affordability. With this caveat in mind, this Section compares the budget shares of the poor for food and essential services (i.e., water, electricity, medical and health care and education) against average budget shares across the urban spectrum. Budget shares are computed as a percentage of total expenditure. In line with Engel's law, food budget shares are highest in rural areas, and among the poor. The share of expenditure for food products is expected to decline as income increases based on Engel's law, according to which consumers increase their expenditures for food products (in percent terms) less than their increases in income. Empirical evidence from the 1999 HICES/WMS is consistent with Engel's law. As shown in Figure 30 below, food budget shares are relatively higher in rural areas (72 percent) than in urban areas (51 percent), reflecting the fact that average rural household expenditure is below urban expenditure. In addition, average food shares decline from small/medium towns (53 percent) to major towns (48 percent) to Addis Ababa (47 percent). As expected, the poor spend a higher share of their total expenditure on food than the average population in both rural and urban areas. Figure 30. Food Expenditure, Share of Total Expenditure, by Locality 100% 80% 80% 73% 67% 69% 69% 66% 60% 51% 53% 48% 47% 40% 20% 0% Average Poor Average Poor Average Poor Average Poor Average Poor Rural Urban Small/medium Major towns Addis towns Water expenditure represents a heavier burden for the urban poor, compared to the urban average. As shown in Figure 31, the urban poor spend a higher share of their URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 54 budget (2.0 percent) for water than the urban average (1.4 percent), despite being significantly under-served (see Section IV). The inequality between the poor and the non- poor is more prominent in the urban context, than in rural areas, where the poor spend only 0.3 percentage point more than the average for water. Although the current budget shares are below 5 percent and thus considered affordable by international standards, the current level of spending raises concern in the Ethiopian context, in light of the low access to improved water supply and the low quality of service provision.41 On average, budget shares are higher in small/medium towns than in major towns. In small/medium towns, water charges represent 1.7 percent of total expenditure, slightly above the budget share in major towns (1.1 percent). Similarly, the urban poor tend to spend more for water services (as percentage of total expenditure) in small/medium towns (2.2 percent), where service coverage is lower, than in major towns (1.6 percent). Figure 31. Water Expenditure, Share of Total Expenditure, by Locality 8% 7% 6% 5% 4% 3% 2.0% 2.0% 2.2% 2% 1.7% 1.7% 1.4% 1.6% 1.4% 1.1% 1.0% 1% 0% Average Poor Average Poor Average Poor Average Poor Average Poor Rural Urban Small/medium Major towns Addis towns Budget shares for electricity are higher in urban areas, especially in major towns. While lower budget shares in rural areas (1.5 percent), compared to urban areas (3.2 percent) simply reflect an extremely low level of rural electrification, significant differences in spending patterns also emerge within the urban space (see also Section IV). On average, electricity budget shares are slightly lower in small/medium towns (2.7 percent) than in major towns (3.3 percent) and in Addis Ababa (3.6 percent). The difference reflects the fact that electrification rate is drastically lower in small/medium towns (58 percent), compared to major towns, where access to electricity is almost universal. 41In terms of budget shares, the rural population appears to spend slightly more on water services than the urban population. This is mainly to be attributed to the fact that average total expenditure is significantly lower in rural areas, relatively to urban areas. Water charges are on the other hand slightly higher in urban areas than in rural areas. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 55 The poor spend more on electricity as a share of total expenditure than the average, especially in major towns. The budget share for the poor is 3.7 percent, compared to 3.2 percent for the urban average. The differential is much more pronounced in major towns, where the poor spend 4.5 percent of their overall expenditure for electricity against an urban average of 3.3 percent. In addition, the poor spends a strikingly higher share of their budget for electricity in major towns (4.5 percent) and Addis Ababa (5 percent) than in small/medium towns (2.6 percent). While the difference may partially reflect the higher access rate in major towns, compared to small/medium towns, it also suggests that affordability constraints may arise where availability constraints are not binding. Figure 32. Electricity Expenditure, Share of Total Expenditure, by Locality 8% 7% 6% 5.0% 5% 4.5% 4% 3.7% 3.6% 3.2% 3.3% 3% 2.7% 2.6% 2% 1.5% 1.1% 1% 0% Average Poor Average Poor Average Poor Average Poor Average Poor Rural Urban Small/medium Major towns Addis towns On average, household health expenditure is low, with no significant difference between the poor and the non-poor. Household expenditure on medical and health care is generally low, averaging 1.2 percent and 0.8 percent of total expenditure in urban and rural areas, respectively.42 In urban areas, the poor spend significantly less (1.0 percent) than the average (1.6 percent) as a percentage of total expenditure, suggesting a lower than average utilization of health services by the poor. In addition, no significant difference in budget share is found between the urban and the rural poor, indicating that the urban advantage with respect to access to better health services may often fail to materialize, at least for the poor. These findings are consistent with the concerns raised by a recent World Bank study on health and poverty outcomes in Ethiopia (World Bank 2005c). The study finds evidence of very low health care expenditure (as a share of non-food expenditure) and high inequalities in access to health services across income quintiles. 42Health expenditure includes pharmaceutical products and herbicides and medical expenses on governmental health stations. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 56 Figure 33. Expenditure on Health and Medical Care, Share of Total Expenditure, by Locality 8% 7% 6% 5% 4% 3% 2% 1.6% 1.5% 1.6% 1.6% 1.2% 1.0% 1.2% 1% 0.8% 0.9% 0.7% 0% Average Poor Average Poor Average Poor Average Poor Average Poor Rural Urban Small/medium Major towns Addis towns Education expenditure is higher in major towns than in small towns. Significant variation is found in the patterns of education expenditure between urban and rural areas. As expected, budget shares for education are significantly lower in rural areas (1.6 percent) than in urban areas (5.5 percent), reflecting a lower educational attainment in rural areas, relatively to urban areas (see Section VI). Within the urban space, budget shares are higher in major towns (4.0 percent) than in small/medium towns (1.6 percent), in line with the lower investment on education by small/medium town dwellers. The urban poor spend less on education (2.7 percent) than the urban average (2.3 percent) as a share of their total expenditure. On the other hand, when measured as a share of non-food expenditure, education expenditure becomes a relatively heavier burden for the urban poor than the urban average: in major towns, the poor spend 11 percent of their non-food expenditure on education, compared to an average budget share of 8 percent. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 57 Figure 34. Education Expenditure, Share of Total Expenditure, by Locality 8% 7% 6% 5% 4.5% 4.0% 4% 3.5% 3.2% 3% 2.7% 2.3% 2% 1.6% 1.8% 1% 0.4% 0.6% 0% Average Poor Average Poor Average Poor Average Poor Average Poor Rural Urban Small/medium Major towns Addis towns Conclusions The empirical evidence shows that urban dwellers spend significantly more (as a share of their total expenditure) than rural dwellers for basic services such as electricity, education and slightly more for health services. On the other hand, they spend as much as rural dwellers water services. The urban poor tend to spend a higher share of their budget than the average for water and electricity. On the other hand, the urban poor spend less for essential services such as health and education than the average, suggesting that the poor may fail to fully benefit from the urban advantage with respect to access to health facilities and education. Interesting findings emerge by comparing expenditure patterns in small/medium towns and major towns. Small/medium towns dwellers tend to spend a higher share of their budget for water than major towns dwellers. On the other hand, major towns dwellers spend more as a share of their budget for electricity and education than small/medium towns dwellers. No significant differences in spending patterns between small/medium towns and major towns emerges with respect to health care services. The main findings of this Section are summarized in Table 9. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 58 Table 9. Urban Poverty and Expenditure Patterns ­ Main Findings Urban Urban versus Rural Poor versus non-poor Small/medium towns versus major towns Water · Budget shares are slightly higher · The urban poor spend a · In small/medium towns, water in rural (1.7%) than in urban higher share of their budget expenditure represent 1.7% of total areas (1.4%). (2.0%) for water than the expenditure, slightly above the budget · However, in absolute terms urban average (1.4%), share in major towns (1.1%). charges are higher in urban than despite being significantly · Budget shares for the poor are 2.2% rural areas. under-served. and 1.6% in small/medium and major towns, respectively. Electricity · Budget shares are lower in rural · The budget share for the · Electricity budget shares are slightly areas (1.5%) compared to urban urban poor is 3.7%, lower in small/medium towns (2.7%) areas (3.2%). compared to 3.2% for the than in major towns (3.3%) and in urban average. Addis Ababa (3.6%). · The differential is much · The poor spends a strikingly higher more pronounced in major share of their budget for electricity in towns, where the poor spend major towns (4.5%) and Addis Ababa 4.5% of their overall (5%) than in small/medium towns expenditure for electricity (2.6%). (against an urban average of 3.3%). Health · Budget shares are comparable and · In urban areas, the poor · No significant difference. low in both urban (0.8%) and spend significantly less rural areas (1.2%). (1.0%) than the average · No significant difference in budget (1.6%). share between the urban and rural poor. Education · Budget shares for education are · The urban poor tend to · Budget shares are on average higher in significantly lower in rural areas spend a lower share of their major towns (4.0%) than in (1.6%) than in urban areas budget for education (2.3%) small/medium towns (1.6%). (5.5%). than the urban average (2.7%). URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 59 IX. CONCLUSIONS Evidence suggests that there is not a single profile of poverty in urban Ethiopia. Instead, urban poverty is multi-faceted and spatially differentiated. Even a coarse segmentation of the urban spectrum based on population size is sufficient to capture significant variation in the profile of urban poverty across the urban spectrum. Spatial patterns of urbanization and urban poverty Small/medium towns play a key role in shaping urbanization patterns in Ethiopia. The lion's share of urbanization in Ethiopia is likely to originate from small/medium towns, where 65 percent of the urban population resides. While the attention paid to primary cities is justified in light of their contribution to economic growth, evidence suggests that small/medium towns in Ethiopia cannot be overlooked and deserve more policy attention going forward. Urban poverty is slightly more prominent in small/medium towns than in major towns. Poverty rate in small/medium towns is 50 percent, against 41 percent in major towns.43 In addition, the share of the urban poor in small/medium towns is above the share of the urban population: 69 percent of the urban poor live in small/medium towns, which accounts for 65 percent of the urban population. Evidence points to limited within urban spatial concentration of monetary and non-monetary deprivation. Ethiopian towns do not exhibit a high degree of spatial concentration with respect to both monetary and non-monetary dimensions of deprivation. The results are consistent with the prevailing view that urban centers in Ethiopia display very integrated residential structures where the poor live side-by-side with the non-poor. This pattern can potentially have positive implications with regard to job market outcomes for the urban poor. On the other hand, spatial concentration of both monetary and non- monetary deprivation is slightly more evident in small/medium towns, relatively to major towns. Hence, the evidence suggests that the poor in small/medium towns, representing 69 percent of the urban poor, may be at a higher risk of facing the economic and social disadvantages that are associated with physical and social segregation than the poor in major towns. Urban poverty and living conditions Urban centers fare significantly better than rural areas with respect to basic service provision. Still, urban centers are significantly under-served. Evidence points to a significant urban advantage as far access to basic services is concerned. Urban areas fare distinctively better than rural areas with regard to basic MDG indicators, such as access to improved water supply and improved sanitation. Still, 75 percent of the urban population suffers from some form of non-monetary deprivation with respect to their living conditions, lacking either access to improved water supply or improved sanitation or living in overcrowded spaces. There is significant variation in living standards across the urban spectrum. While lack of tenure security and overcrowding are relatively more pressing issues in major towns, access to improved water supply and waste management are more prominent concerns in 43Based on the lower bound of the full poverty line ("the lower poverty line") as calculated in the 2005 World Bank Poverty Assessment. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 60 small/medium towns. Access to improved sanitation features as a challenge across the urban spectrum. Among the forms of deprivation that disproportionately affect the poor are access to improved water, access to electricity--in small/medium towns only--overcrowding, and lack of tenure security--in major towns only. The demographic profile of the urban poor The urban poor have a distinct demographic profile. Urban poor households tend to be larger than non-poor households and to have a higher number of dependents. Differences in the demographic profile of households are found between small/medium and major towns: urban poor families in major towns are larger than in small/medium towns and feature a high number of adults. The larger size of households in major towns, compared to small/medium towns, may be in part related to the limited housing options available in major urban centers which may oblige different generations to live under the same roof. Urban poverty and female-led families Urban female-led families, a strikingly high percentage of the urban population, are a vulnerable group in particular with respect to human capital formation. Female-led families represent a remarkable 33 percent of the urban population. While the share of the poor among FHHs is in line with the urban average, FHHs are a markedly vulnerable and heterogeneous group that deserves specific policy attention: FHHs with at least one dependent and widow-led households represent 29 percent and 15 percent of the urban population, respectively. Urban FHHs are particularly disadvantaged with respect to educational attainment: female heads have on average half the number of years of schooling than male heads, across the urban spectrum. Obviously, the disadvantages are compounded for poor urban female heads: they have one year of schooling on average, compared to three years of schooling for the average poor head of household. The educational attainment of poor urban female heads is comparable to the average rural level of education, and thus strikingly below the urban average. Poor FHH in small/medium towns benefit more from safety nets than poor FHHs in major towns. Among the urban poor, FHHs are more likely to receive private transfers than MHHs: 68 percent of poor FHHs receive private transfers against 50 percent of poor MHH, Poor FHHs in small/medium towns benefit to some extent more from safety nets than poor FHHs in major towns. 71 percent of poor FHHs receive private transfers in small/medium towns, against 60 percent in major towns. Similarly, 14 percent receive NGO transfers in small/medium towns, against 9 percent in major towns, and the value received is on average higher. These findings suggest that strengthening safety nets for poor FHHs in major towns is likely to yield a significant poverty reducing impact. Urban poverty and educational attainment Educational attainment is markedly higher in urban areas than in rural areas. However, intra-urban inequality is high, especially in major towns. The urban population draws on a larger stock of human capital than the rural population. On one hand, the urban poor are as expected better educated than the rural poor. On the other hand, in relative terms the urban poor have a distinct disadvantage in terms of educational attainment than the urban non-poor. Inequality in human capital formation is particularly evident in major towns and Addis Ababa, where the differential in years of education between the poorest and the wealthiest quintile is 5.2 and 6.7 years, respectively. The results are particularly worrisome as a wide gap in human capital formation is likely to fuel URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 61 inequality within urban centers and reinforce the educational divide between the poor and the non-poor, given the significant positive impact that parental education is found to play on child enrolment. Urban poverty and risk management Income diversification is mainly a function of the urban-rural divide, rather than level of income. Urban dwellers have a much more diversified income base, compared to rural dwellers. Within the urban spectrum, small/medium towns and major town dwellers differ in their income diversification profile with respect to the relative weight of self- employment and wage income: as expected self-employment is more common in small/medium towns, while wage income is more prevalent in major towns. No major difference is found in the pattern of income diversification across quintiles, when controlling for the size of the urban settlement, suggesting that the local environment affects the patterns of income diversification more than wealth. Overall, urban areas receive a larger volume of transfers than rural areas. However, the poor may not be those benefiting the most from the transfers. Urban areas receive remarkably higher flows of private transfers than rural areas. Per capita NGO transfers are also significantly larger in urban than rural areas. The larger volume of private flows more than compensate for the fact that public cash transfers are remarkably more prevalent in rural areas than in urban areas. The re-distributional impact of the transfers within urban areas is however unclear. While the poor tend to benefit the most from private transfers, there is considerable leakage in the distribution of public cash transfers. This is especially the case in Addis Ababa, where the non-poor receive a significantly higher per capita public transfer than the poor. Within the urban spectrum, the poor in major towns have the least access to safety nets. The urban poor in major towns are less likely to receive transfers from the government, other households and NGOs than the urban poor in small/medium towns. In major towns, the urban poor reached by the transfers receive smaller per capita median transfers than the urban poor in small/medium towns. In addition, leakage to the non-poor is more pronounced than in small/medium towns. Urban poverty and expenditure patterns When availability constraints are not binding, affordability constraints emerge. Affordability concerns emerge with respect to the utilization of basic services such as education and electricity by the urban poor. On the other hand, the poor exhibit relatively low budget shares for water (albeit significantly above average), providing supporting evidence that availability is the major constraint to water consumption among the poor. In urban areas, the low budget share for health services of poor households, compared to the average share, is likely to be associated with low utilization by the poor of health facilities. In addition, the lack of significant difference in budget shares between the urban and the rural poor may suggest that the urban poor fail to reap the benefits of urban access to health service provision. Summing it up: the multi-faceted nature of urban poverty In many respects, small/medium towns have an urban character. With respect to human capital formation, the pattern of income diversification and access to basic services, small/medium towns are distinctly urban, performing significantly better than rural areas. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 62 By the same token, the urban poor in small/medium towns have a distinct `urban' profile: they are better educated, have a more diversified income base and better access to basic services (such as water and sanitation) than the rural poor. On the other hand, small/medium towns have a different poverty profile than major towns. Small/medium towns still have a long way to catch up with the level of service provision in major towns. Only 32 percent of the urban population in small/medium towns does have access to improved water supply, compared to 59 percent of the urban population in major towns. The environmental externalities associated with waste management are more acute in small/medium towns, where almost the entire urban population does not have access to environmentally safe waste disposal and collection, against 62 percent of the population in major towns. Access to shared electricity connections is the norm in major towns and Addis Ababa, with virtually the entire population is covered by the grid. On the other hand, only 58 percent of the urban population is small/medium towns have electricity access. There is also a significant difference in educational outcomes between small/medium and major towns: the gap between small/medium towns and major towns in terms of years of schooling is on average two years for both adult males and females. ... but major towns are not spared from poverty challenges. While performing better than small/medium towns in many respects, major towns still face enormous challenges in fighting urban poverty. First, overcrowding and lack of tenure security are pressing issues, and are highly correlated with urban poverty. Second, basic urban service provision, such as access to improved water supply and waste management, is better in major towns than in small/medium towns, but far from being satisfactory. Third, major towns fare as badly as small/medium towns with regard to access to improved sanitation. As the urban poor are more affected than the non-poor by inadequate service provision, these urban challenges takes on a strong poverty connotation. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 63 REFERENCES Angeli, Aurora and Silvana Salvini (2005). Family Structure, gender of the Household Head and Child Opportunities in Addis Ababa, in 25th International Population Conference, Paris, Iussp. Aredo, Dejene (2005). Migrant Remittances, Shocks, and Poverty in Urban Ethiopia: An Analysis of Micro level Panel Data. Addis Ababa University. Atkinson, Rowland and Kintrea, Keith (2001). Disentangling Area Effects: Evidence from Deprived and Non-deprived Neighbourhoods. Urban Studies, Vol. 38, No. 12, 2277­ 2298. Baud, ISA, K, Pfeffer, N. Sridharan and N. Nainan (2006). Matching Knowledge to Urban Governance: Mapping Deprivations in the three Indian mega-cities. Mimeo. Bigsten, Arne, Bereket Kebede, Abebe Shimeles and Mekonnen Taddesse (2003). Growth and Poverty Reduction in Ethiopia: Evidence from Household Panel Surveys, World Development Vol. 31, No. 1, pp. 87­106. Birke, Yami (1999). Solid Waste Management in Ethiopia, Integrated Development for Water Supply and Sanitation, 25th WEDC Conference. Addis Ababa. Central Statistical Office (2006). Statistical Abstract, January 2007. Addis Ababa. Coulombe, Harold, and Andrew McKay (1996). `Modeling Determinants of Poverty in Mauritania'. World Development, 24 (6): 1015-31. Da Fonseca Feitosa, Flávia and Wissmann, Anna (2006). Social-mix policy approaches to urban segregation in Europe and the United States. Zentrum für Entwicklungsforschung Center for Development Research, Universität Bonn. ENDA-Ethiopia (1999). The Cycle of Waste in Addis Ababa. Mimeo. Gebremedhin, Tesfaye Alemayehu (2006). The Analysis of Urban Poverty in Ethiopia. The University of Sydney. Grootaert, Christiaan (1997). The Determinants of Poverty in Côte d'Ivoire in the 1980s. Journal of African Economies, 6 (2): 169-96. Greene, Richard (1991). Poverty Concentration Measures and the Urban Underclass. Economic Geography, Vol. 67, No. 3, July, pp 240-252. Government of Ethiopia (2005). Sanitation Millennium Development Goals Needs Assessment. Addis Ababa. Government of Ethiopia (2004). Urban Sector Millennium Development Goals Needs Assessment: Improving the Lives of Slum Dwellers. Addis Ababa, December. Jargowsky, Paul A. and Mary Jo Bane (1990). Ghetto Poverty: Basic Questions in Inner-City Poverty in the United States. Edited by L. E. Lynn and M. G. H. McGeary, Washington DC: National Academic Press. Kaganova, Olga (2005). Establishing More Efficient and Effective Land Management. The Urban Institute. Mimeo. Kessides, Christine (2005). The Urban Transition in Sub-Saharan Africa: Implications for Economic Growth and Poverty Reduction. Africa Region Working Paper Series N. 97. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 64 Kodama, Yuka (2006). Poverty Analysis of Ethiopian Females in the Amhara Region: Utilizing BMI as an Indicator of Poverty. Institute of Developing Economies. Discussion Paper No. 80. Kronlid, Karin (2001). Household Welfare and Education in Urban Ethiopia. World Institute for Development Economics Research. Discussion Paper No. 2001/144. Meehan, Fiona (2004). Female Headed Households in Tigray, Ethiopia. A Study Review. DCG Report No. 35. Ministry of Finance and Economic Development (2006). Ethiopia: Building on Progress: A Plan for Accelerated and Sustained Development to End Poverty (PASDEP). Addis Ababa. September. Ministry of Finance and Economic Development (2005). Ethiopia: Participatory Poverty Assessment 2004-05. Addis Ababa. October. Montgomery, Mark and Paul C. Hewett (2004). Urban Poverty and Health in Developing Countries: Household and Neighborhood Effects. Mimeo. National Research Council (2003). Cities Transformed ­ Demographic Change and its Implication in the Developing World. Washington, DC. Olima, Washington H.A. (2001). The Dynamics and Implications of Sustaining Urban Spatial Segregation in Kenya: Experiences from Nairobi Metropolis. Lincoln Institute of Land Policy Conference Paper. Satterthwaite, David (2004). The under-estimation of urban poverty in low and middle- income nations, IIED Working Paper on Poverty Reduction in Urban Areas. Taddesse, Mekonnen and Abebe Shimeles (2000). Comparison of Welfare and Poverty: an Application of Stochastic Dominance Testing to Ethiopian Household Data. in Shimeles, Kebede and Bigsten "Poverty, Income Distribution and Labor Markets in Ethiopia": Addis Ababa University. UN-Habitat (2003). Slums of the World: The Face of Urban Poverty in the New Millennium?. Working Paper. UN-Habitat (2002). Secure Tenure, Slums and Global Sample of Cities. Expert Group Meeting on Urban Indicators. Nairobi, Kenya. Van Golde, Jacco (1998). Spatial Segmentation of Large Urban Labour markets: Cultures of Segregation Among the Urban Poor?. Paper presented at the 38th European Conference of the Regional Science Association. Vienna. Woldermariam, Elizabeth and Liama Mohammed (2003). Poverty Mapping in Selected African Countries. Addis Ababa, Ethiopia: Economic Commission for Africa and World Bank, April. WHO/UNICEF (2004). Meeting the MDG drinking-water and sanitation target: A mid-term assessment of progress. World Bank (2006). Urban Labour Markets in Ethiopia: Challenges and Prospects. Washington, DC. World Bank (2005a). Well-Being and Poverty in Ethiopia. Washington, DC. World Bank (2005b). Education in Ethiopia ­ Strengthening the Foundation for Sustainable Progress. Washington, DC. URBAN POVERTY IN ETHIOPIA: A MULTI-FACETED AND SPATIAL PERSPECTIVE 65 World Bank (2005c). A Country Status Report on Health and Poverty. June. Washington, DC. World Bank (2005d). Housing in Addis Ababa: Background Paper. Mimeo.