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Executive Summary
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This study forms part of a four-country research programme funded by DfID. The overall goal is to develop methods of measuring and analysing poverty and modelling the impact of change at household level.
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The aim of the Swaziland study was to test the use of individual household economy methods in an area of high HIV/AIDS prevalence; to identify the main factors affecting income levels in HIV affected and non affected households and to
explore possible uses of household economy methods in programme design and monitoring.
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The study was conducted in a Highvelt, maize producing community, about 40 km from the capital city, Mbabane.
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Household economy methods were used to describe and quantify the components of household income and expenditure, including food production and employment. The assessment covered the entire community.
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Detailed demographic information was collected for all household members, including providers of remittance income. The presence of orphans1 in a household was used as a proxy for HIV/AIDS2. 35% of all households fall into this HIV/AIDS affected category. Orphans make up 11% of the total population.
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Comparisons were made between the income and standard of living of households across the study population. These were based on comparisons of disposable income i.e. income remaining after the household had met its food requirements. A minimum standard of living was established, including basic needs and primary school costs; the standard was designed to be consistent with international Millennium Development Goals (MDGs). 25 households (23%) fell below the minimum standard of living.
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An estimate was made of the impact of HIV/AIDS, changes in agricultural production and other shocks on household economy and living standards.
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Overall, total community disposable income appears to have fallen by around 8.3% due to HIV/AIDS, although the figure is higher in directly affected households. Agricultural production is characterised by low yields and low use of farm inputs. Low
input use among wealthier households appears to be linked to variability of returns (due to climatic risks, pests etc). With the exception of retrenchment in the South African mining industry and loss of job security in local forestry work, the pattern of
employment is relatively stable.
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Across the population as a whole, a higher proportion of poorer non HIV affected children are out of school than HIV affected children. This can be explained by selective targeting of orphans for assistance with school fees3.
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Analysis of the characteristics of the poorest 25 households showed that 54% had either suffered a death within the last 5 years which was likely to be AIDS related and/or accepted an orphan from outside the household. Of the 10 households in this
group that had suffered an AIDS death the simulation showed that at least 5 would previously have been in a much higher income group.
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Irrespective of HIV status, households in the very poor group have less access to land, higher levels of unemployment and more low paid employment. However, across the group as a whole, there is no single 'cause' of poverty.
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This study provides quantitative information that could be used to guide policy and to estimate the actual investment costs of raising living standards. Interventions that reduce household costs (e.g. school fees) and increase production (e.g. farm
input subsidies) would help many poor households. However, the causes of poverty vary considerably, and individual case work is also needed to match assistance to household needs and capacities.
Footnotes:
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Orphans are defined locally (and in this study) as children who have lost one or both parents.
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The cause of death was not known definitively; however, adult HIV prevalence in this area is estimated at 38% so it is reasonable to assume that a large number of ‘prime age’ adult deaths resulting in orphans can be attributed to HIV/AIDS. 2001 figures for Swaziland show that 15% of all children who are orphans ( total = 59,000 in total, of which 35,000 (59%) have lost parents due to AIDS. These figures are projected to rise by 2010 to 22%, 87,000 and 82% respectively (UNICEF 2003, Africa's orphaned generations, New York).
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Due to the current availability of targeted educational support for orphans, it is not possible to draw
meaningful comparisons with enrolment rates of HIV affected children in other countries (eg 'Contrasing primary school outcomes of paternal and maternal orphans in Manicaland,Zimbabwe.' Nyamukapa C and Gregson S 2003)
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