Spatial poverty and inequality in South Africa: A municipality level analysis

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Show simple item record David, Anda Guilbert, Nathalie Hamaguchi, Nobuaki Higashi, Yudai Hino, Hiroyuki Leibbrandt, Murray Shifa, Muna 2018-01-16T10:43:23Z 2018-01-16T10:43:23Z 2018-01
dc.identifier.citation David, A., Guilbert, N., Hamaguchi, N., Higashi, Y., Hino, H., Leibbrandt M., Shifa, M. (2018). Spatial poverty and inequality in South Africa: A municipality level analysis. Cape Town: SALDRU, UCT. (SALDRU Working Paper Number 221).
dc.identifier.isbn 978-1-928281-82-5
dc.description.abstract Using the 2011 South African population census, we provide income and multidimensional poverty and inequality estimates at the municipal level. We go on to estimate a spatial econometric model to identify the correlates of poverty across municipalities in South Africa. Our results show that both income and multidimensional poverty and inequality vary significantly across municipalities in South Africa. In general, areas that are historically characterized by low economic and welfare outcomes still experience significantly higher poverty and deprivation levels. Using both global and local spatial autocorrelation measures we find significant and positive spatial dependence and clustering of regional development indicators. The situation of poverty is both spatially unequal and autocorrelated. Results from our spatial econometric analysis indicate negative and significant relations between the municipal poverty levels and local levels of education and economic activity (GDP per capita). Significant and positive relations are found between municipal poverty levels and local inequality levels, suggesting that municipalities with higher levels of inequality also have higher incidences of poverty. In contrast, natural geographic factors such as rainfall and temperature are not significantly related to municipal poverty. Accounting for both direct, intra-municipality effects as well as spillover effects of neighbouring municipalities is important. These spillover effects notably reduce the coefficient sizes suggested by non-spatial, OLS regressions. Most striking, the large negative coefficient that OLS attributes to residing within a historical homeland area is greatly reduced and even loses statistical significance in some spatial models. Clearly municipalities in homeland areas are particularly likely to be surrounded by very poor municipal neighbours and therefore subject to strong negative spillovers. That said, when interactions between this historical geographical variable and contemporary socio-economic deprivations are included, then homeland becomes statistically significant once more. This makes the important point that while, it is these socio-economic deprivations that are particularly important in explaining contemporary income poverty across the county, those who reside in these homeland areas remain especially badly off in terms of these deprivations. en_US
dc.description.sponsorship This paper is written as part of the “Social Cohesion, Inequality and Inclusive Development” partnership agreement between the French Development Agency, South African Office and the University of Cape Town. It is funded by the French Development Agency (AFD). We acknowledge very useful comments from AFD seminars in Pretoria and in Paris as well as from participants in the 4th DIAL Conference on Development Economics. en_US
dc.language.iso en en_US
dc.relation.ispartofseries Saldru Working Paper;221
dc.subject Poverty en_US
dc.subject Inequality en_US
dc.subject South Africa en_US
dc.title Spatial poverty and inequality in South Africa: A municipality level analysis en_US
dc.type Working Paper en_US

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