Cities and Poverty Research Indicators Working Group 7 November 2002 Isandla Institute PDG Project Structure Recognizing and understanding Recording and monitoring Responding and intervening Poverty Alleviation Isandla Institute PDG Recognising Urban Poverty Urban Growth SA reflects global and regional trends in urban population growth The big picture is of consistent growth Within this there are different patterns in the rate, location and population that are growing Isandla Institute PDG Urban growth - race Urban Population by Race, 1911-1996
14,000,000 12,000,000 Population 10,000,000 8,000,000 Africans Whites Coloureds 6,000,000 Indians 4,000,000 2,000,000 1910 1920 1930 1940 1950 1960 1970 1980 1990 Years Isandla Institute PDG Urban growth - gender
African Urban Population by Gender, 1911-1996 8,000,000 7,000,000 6,000,000 Population 5,000,000 Men Women 4,000,000 3,000,000 2,000,000 1,000,000 1910 1920 1930 1940 1950 1960 1970 1980 1990 Years Isandla Institute PDG Urban growth - location Population of Metropolitan Centres, 1875-1996
8000000 7000000 6000000 Population 5000000 Greater Johannesburg Greater Cape Town 4000000 Greater Durban Port Elizabeth 3000000 2000000 1000000 0 1875 1895 1915 1935 1955 1975 1995 Years Isandla Institute PDG Urbanisation of poverty Three main reasons for the urbanisation of
poverty The natural growth of the poor population within cities Growing urban inequality Poor people moving to cities Isandla Institute PDG Who are the urban poor in SA If there is a typical face of poverty in South Africa then this picture is no longer only a rural women engaged in subsistence agricultural production. It is an HIV child living in an environmentally degraded informal settlement in a rapidly growing city - without services who is subjected to organised and household violence and is vulnerable to global economic and political trends. FS Mufamadi, Minister For Provincial and Local Government, SACN Launch 7 October 2002 Isandla Institute PDG Who are the urban poor in SA? Total Urban Population, by Race 1996 95-99 Years Indian Men Coloured Men White Men African Men Indian Women Coloured W omen White Women African Women 90-94 Years
85-89 Years 80-84 Years 75-79 Years 70-74 Years 65-69 Years 60-64 Years 55-59 Years 50-54 Years 45-49 Years 40-44 Years 35-39 Years 30-34 Years 25-29 Years 20-24 Years 15-19 Years 10-14 Years 5-9 Years 0-4 Years -1300000 -800000 -300000 200000 700000 1200000 Population Isandla Institute PDG Who are the urban poor in SA? 1996 City Population by Race 3,000,000 2,750,000 2,500,000 2,250,000 Indian/Asian 2,000,000
Coloured Population 1,750,000 White African/Black 1,500,000 1,250,000 1,000,000 750,000 500,000 250,000 0 Joburg East Rand Isandla Institute Pretoria Durban Pieter- maritzburg Cape Town Port Elizabeth Buffalo City Mangaung PDG Poverty definition Poverty is more than a lack of income. Poverty exists when an individual or a households access to income, jobs and/or infrastructure is inadequate or sufficiently unequal to prohibit full access to opportunities in society. The condition of poverty is caused by a combination of social, economic, spatial, environmental and political factors.
Isandla Institute PDG Poverty definition Energy Energy Crime Crime Health Health Unemployment Unemployment Literacy Literacy Water Water Income Income Disability Disability Poverty Poverty Housing Housing Gender Gender Transport Transport Waste Waste Isandla Institute Environmental EnvironmentalHealth Health Gini
Gini CDI CDI PDG Recording and monitoring poverty Choose the appropriate indicators of urban poverty Select the correct scale Monitor vulnerable groups Identify sectoral weaknesses Use up-to-date, reliable data Isandla Institute PDG Choose the right indicator Isandla Institute PDG Select the right scale Isandla Institute PDG Identify vulnerable groups Dwelling type by race in Cape Town 80% 70% 60% 50% 40% 30% 20% Total population African population 10% 0%
g g g g lli n ll i n l li n ll i n e e e e w w w w D al D al D yard D ard m m y r r k k o c c Fo Inf l Ba l Ba a a m m r For Info Isandla Institute PDG Making complex data useful
Must be understood by all stakeholders Must be flexible - accommodate new data and refinement Must interface with other data e.g. budget, provincial data, community priorities etc. Must be authoritative - locally and internationally and internally and externally Isandla Institute PDG The City Development Index P M B /M s u n d u ziS ta n d a rdo fL iv in gIn d e xC D I A llC itie sS ta n d a rdo
fL iv in gIn d e xC D I 6 .3 0 C D I= 5 1 0 0 .0 0 9 .6 C D I= 3 1 0 0 .0 8 0 .0 0 8 0 .0 C ityP ro d u ct= 1
1 .0 6 0 .0 6 0 .0 0 In fra stru ctu re=4 9 .3 4 0 .0 P ro d u ct= 5 6 .3 0 2 0 .0 0 2 0 .0 0 .0 0
0 .0 E d u ca tio n= 5 4 .0 W a ste= 4 9 .0 4 .7 H e a lth= 3 Isandla Institute In fra stru ctu re=6 1 .9 2 4 0 .0 0 E d u ca tio n=
W a ste= 7 5 .8 9 5 6 .0 0 H e a lth= 3 5 .1 3 PDG Customising the CDI for SA CDI AVAILABLE DATA PRODUCT (Gross Geographical Product (GGP)) We used Mean Household Income (Census 1996) normalised to 100 as a substitute for GGP. Isandla Institute REASONABLE DATA WISH LIST
GGP figures are available, but have not been calculated for all the cities. COMMENT ON SOUTH AFRICAN RELEVANCE The product figure fails to capture the other dimensions of growth for example investment, competitiveness, exports, tourism, employment, building plans passed, car sales, house prices, local inflation, skills etc. PDG Customising the CDI for SA CDI AVAILABLE DATA EDUCATION (Literacy x 25 + combined enrolment) In the absence of city enrolment figures we used only literacy (9 years) (literacy x50). Isandla Institute REASONABLE DATA WISH LIST Enrolment figures are available in the Provinces, but have not been calculated for at the city or sub city scale.
COMMENT ON SOUTH AFRICAN RELEVANCE Given the nature of formal employment in cities it may also be appropriate to measure levels of tertiary education. PDG Customising the CDI for SA CDI AVAILABLE DATA HEALTH Life expectancy 25 x50/60 +32 Child mortality x50 /31.92 We used provincial estimates of infant mortality instead of child mortality Isandla Institute REASONABLE DATA WISH LIST Child mortality figures are available from the ante natal surveys, but are not calibrated at the city scale. Life expectancy has not been calibrated at the city scale COMMENT ON SOUTH AFRICAN RELEVANCE
Recognising that there is a danger of double counting, it is important that HIV/Aids and TB figures are reflected in the health index. Similarly, the impact on mortality and health services of the high transport accident figures means that this data could also be used. PDG Customising the CDI for SA CDI AVAILABLE DATA INFRASTUCTURE Water connection x25 Sewerage connection x25 Electricity x25 Telephone x25 Census 1996 data was used define levels Isandla Institute REASONABLE DATA WISH LIST City data may be more up to date than the census. COMMENT ON SOUTH AFRICAN RELEVANCE Service levels may need to be adjusted. Given the housing backlog and the ongoing demands associated with urban growth we felt housing should be included but that only informal
backyard shacks and informal settlements should be defined as inadequate to recognise rental housing as an important urban shelter choice. PDG Customising the CDI for SA CDI AVAILABLE DATA WASTE Wastewater treated x50 + formal solid waste disposal Formal solid waste disposal (Census 1996) Isandla Institute REASONABLE DATA WISH LIST Data on waste water treated is available from the cities. COMMENT ON SOUTH AFRICAN RELEVANCE The focus of this brown agenda indicator could be expanded to recognise air pollutants, possibly using a proxy health indicator such as upper respiratory tract infections. PDG Gaps in the CDI Does not capture all dimensions of poverty Infrastructure heavy
Not all locally specific poverty dynamics are addressed - e.g. segregation Key aspects of city development are not included Isandla Institute PDG Introducing SAPIC South African Poverty Indicator (SAPIC) SAPIC 100 80 A poverty adjusted CDI 60 Safety and Security 40 20 0 Social and economic exclusion Good governance Spatial integration Isandla Institute PDG SAPIC and budget SAPIC and Budget Indicator SAPIC 100 80 A poverty adjusted CDI 60 40 Safety and Security
20 0 Social and economic exclusion Good governance Spatial integration Budget indicator Isandla Institute SAPIC PDG Introducing SAPIC SAPIC (Possible indicators) SAFETY AND SECURITY Black male victims between 16 and 30 who are homicide victims. Police per 10000 population Juvenile offenders per 10000 population Proportion of alcohol/drug related crimes. DATA WISH LIST AND DATA ISSUES City and sub city scale collation of crime, prison, and medical data. The weighting and formation of the index needs to balance issues of access to justice, negative impacts of crime and violence and the dependence on criminal livelihoods within poor communities. Figures on crimes against women and children are not included in this part of the SAPIC as they are used as proxy indicators of social exclusion. Isandla Institute
RELEVANCE TO POVERTY IN SOUTH AFRICAN CITIES Although all South Africans are negatively affected by crime, the poor bare the brunt of the violence and social dislocation of crime. Crime in South African cities, especially among poor communities, is closely associated with drug and alcohol trade and abuse. Unchecked criminality as a livelihood strategy among poor households may threaten overall city governance and public safety. PDG Introducing SAPIC SAPIC (Possible indicators) GOOD GOVERNACE Project viability financial indicators, Institutional transformation, Participatory IDP, etc DATA WISH LIST AND DATA ISSUES These indicators draw from the Department of Provincial and Local Governments (DPLGs) Key Performance Indicators (KPIs). They are collected at a municipal scale intended for reporting to national government. The proposed indicators would not be appropriate for sub city application, for instance in an IDP, where alternatives should be proposed. Isandla Institute RELEVANCE TO POVERTY IN SOUTH AFRICAN CITIES Although all citizens benefit from sound financial
practice, transparent government and effective participatory processes, the poor are most likely to gain from democratic and good governance. They are also most likely to suffer from municipal fiscal crisis and corruption. Without democracy and participatory forums their voices cannot be heard on how the city should be run. Despite its prominence in the pro-poor literature good city governance is not an area where there has been much work on urban indicators and we have therefore adopted some of DPLGs general KPIs for local government. PDG Introducing SAPIC SAPIC (Possible indicators) SPATIAL INTEGRATION Affordability of commuter fares x25 Accessibility to public transport x25 Door to door journey times x 25 Proportion of the population stranded without access to transport x25 DATA WISH LIST AND DATA ISSUES Transport is used as a proxy indicator for spatial isolation and exclusion. Collection of the data at the city (and sub city) scale is required for the inclusion of the indicator as proposed. Elements of the index overlap with the CDI and there is an ambiguity over the definition of secure tenure with a possible over emphasis on ownership over rental. Slums Index: % households without tenure % households without water % households without sanitation and other services % households without permanent structures
Isandla Institute RELEVANCE TO POVERTY IN SOUTH AFRICAN CITIES The legacy of apartheid planning and the high cost of well located land for new subsidy based housing development means that the urban poor in South African are located on the periphery, far from jobs and subject to expensive travel. Extensive subsidies currently maintain this pattern of race and class segregation and mitigate against the integration of cities in line with urban reconstruction policy frameworks that are designed to enhance the opportunities of the poor. There are some questions around the appropriateness of the UN Slums Index. PDG Introducing SAPIC SAPIC (Possible indicators) DATA WISH LIST AND DATA ISSUES SOCIAL AND ECONOMIC EXCLUSION RDI (Racial Development Index) = HDI of Africans as a proportion of that of the population as a whole. GDI (Gender Development Index) Rape Gini coefficient for Africans Reported child abuse per 10000 of population Unemployment (extended definition)
The HDI is a globally accepted index of well being. HDI (Human Development Index) indicators include longevity, education and income these can all be extracted from the South African census at the city and sub city scale and calculated using the apartheid race classification of African as a proxy for racist exclusion. The UNs GDI (Gender Development Index) uses the same variables as the HDI but measures the performance of women relative to that of men. It is used here as a proxy indicator of gender discrimination. RELEVANCE TO POVERTY IN SOUTH AFRICAN CITIES Key lines of exclusion and marginality in South Africa include racism, sexism, language discrimination and xenophobia. Although rape and child abuse figures are notoriously underreported, they are collected and can be used to reflect fear and vulnerability. Gini coefficients measure inequality traditionally in income. The use of the African Gini is designed to show that race is no longer a reliable predictor of poverty, as there is increasingly extreme inequality within race groups. Similar measures could be made of any race group. Isandla Institute PDG Introducing SAPIC SAPIC (Possible indicators) POVERTY ADJUSTED CDI CDI for Africans CDI for residents of informal backyards and informal settlements CDI for the lowest income quintile
DATA WISH LIST AND DATA ISSUES Not all variables of the CDI can be adjusted for race or for housing type and income quintile. But the infrastructure, waste, health and education variables can be disaggregated in this way and if income rather than GGP is used for the product Census 1996 can be used to calculate the poverty adjusted CDI. Isandla Institute RELEVANCE TO POVERTY IN SOUTH AFRICAN CITIES The CDI is a solid general measure of poverty, but it measures average performance and, especially in highly unequal contexts such as South African cities, fails to reflect the position of the poorest of the poor. By running the CDI for Africans (the population most negatively impacted by apartheid); the lowest income quintile and those in informal settlements (the housing and infrastructure poorest) we establish a general idea of development from the perspective of the poor of the city. PDG Calculating quality of life indices Contents 1 Human poverty index 2 Human development Index 3 Gender - related development index 4
Gini coefficient 5 Poverty line 6 Cities development index 7 Poverty gap index Isandla Institute PDG Inequality indicators - Gini coefficients (Jhb - Africans) No. of Individuals 0 Income groups (R) Lorenz Curve 5,776 None 27,992 R1-2400 79,617 R2401-6000 90% 161,417 R6001-12000 80%
373 R360001 or more 100% 50% 40% 0% 20% 40% 60% 80% 100% 582983 Gini coefficient Isandla Institute 0.46 PDG Gender-related Development Index Gender - related Development Index Indicators Measures Population share Percent share of total population Longevity life expectancy at birth Knowledge
Adult literacy Combined first, second and third level gross enrolment ration Decent standard of living Adjusted real GDP per capita % share of the econ active population Data (male) Data (female) Population share 0.49 0.51 Longevity 76.70 82.80 Adult literacy 99.00 99.00 79.00 Combined first, second and third level gross enrolment ration 0.59 % share of economically active population 77.00 Ratio of female non agri wage to male non agri wage Adjusted real GDP per capita Longevity Ratio of female non-agri wage
to male non agri wage 0.41 0.75 0.75 6231.00 6231.00 Max (male) Min (male) Max (female) Min (female) 76.7 22.5 82.8 27.5 0 0 100 100 0 0 100 100 Combined first, second and third level gross enrolment ration Adult literacy Index Longevity Adult literacy 0.913
0.920 Decent standard of living 0.885 GDI Isandla Institute 0.906 PDG Poverty lines (eThekweni) Poverty Lines Number Percent None Income groups (R) None Poverty Lines 73,909 13% R1-2400 Below 2400 per annum 21,283 4% R2401-6000 Below 6000 per annum 60,144 11%
R6001-12000 Below 12000 per annum 65,149 11% R12001-18000 Below 18000 per annum 66,788 12% R18001-30000 Below 30000 per annum 73,494 13% R30001-42000 Below 42000 per annum 45,081 8% R42001-54000 Below 54000 per annum 35,654 6% R54001-72000 Below 72000 per annum 39,284 7%
R72001-96000 Below 96000 per annum 27,611 5% R96001-132000 Below 132000 per annum 28,756 5% R132001-192000 Below 192000 per annum 18,179 3% R192001-360000 Below 360000 per annum 11,591 2% R360001 or more Select poverty line 3,030 1% 569953 100% Poverty lines Distribution below the Poverty Line
One of the easiest ways to establish who the poor are is to establish the percentage 25% of people who are living below the 20% poverty line. 15% povety lines are a rough measure of 10% identifying the poor. However poverty lines are the easiest measure to 5% determine poverty. 0% None Below 2400 p.a. Below 6000 p.a. Below 12000 p.a. Below 18000 p.a. Below 18000 p.a. % and No. of people below the poverty line
Isandla Institute 50.40% 287,273 50.4 percent of people are living below the poverty line PDG Project Structure Recognizing and understanding Recording and monitoring Responding and intervening Poverty Alleviation Isandla Institute PDG Responding and intervening Service delivery and poverty Pro-poor sector support Land-use planning transport and poverty HIV/Aids and poverty SACN Group Finance and restructuring LED Transport HIV group
Indicator Group City Development Strategies Focus of intervention Environment and poverty Isandla Institute PDG Conclusion Further information from the project is available on www.sacities.net Recognising and understanding poverty South African commitments to sustainable urban development, Different approaches to addressing urban poverty, The dynamics of urban growth in global, regional and national patterns of poverty, The urbanisation of poverty, Key definitions, Web Sources on urban poverty Isandla Institute Recording and monitoring poverty Census-based Profiles of SACN members data by city and sector, Composite indicators including: - City Development Index, - Gini coefficients,
- Gender Development Index - Human Development Index - Poverty Lines - Poverty Gaps Responding to poverty and intervening Urban development and HIV/Aids Pro-poor local economic development a sectoral approach Environment and poverty relief Transportation, spatial planning and poverty alleviation Pro-poor service delivery affordability and willingnessto-pay South African Poverty Index for Cities Proposal PDG
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