Spatial Change in the Concentration of Multidimensional Poverty in Gauteng, South Africa: Evidence from Quality of Life Survey Data

Abstract

The multidimensional poverty index (MPI) is generally credited for better capturing the various components of poverty. Where such indexes have a spatial component, opportunity arises for analyzing changes in the spatial concentration of multidimensional poverty over given periods across space. Using current available MPI data for Gauteng province, South Africa, we apply spatial statistical analysis techniques to measure the degree of spatial concentration, spread and orientation of poverty across the various wards. Results reveal distinct variations in concentration, spatial spread and orientation of poverty across the province. These results open up possibilities of spatially targeted state interventions for reducing poverty.

Contextualizing multidimensional poverty in urban India

“…multidimensional poverty in Taiwan (Chen et al, 2019). Spatial analyses have been integrated into the estimation of multidimensional poverty and studies suggest significant clustering of multidimensional poverty indices in South Africa and China (Katumba et al, 2019;Li et al, 2019). Child mortality and malnutrition are significant contributors to urban poverty while overlapping deprivations in education and decent infrastructure characterize rural poverty (Aguilar & Sumner, 2020).…”

Spatio-temporal patterns and changes in environmental attitudes and place attachment in Gauteng, South Africa

“…Being less affluent may lead to residents caring less about their environment and sense of "place" and caring more about satisfying their own day-to-day economic needs. Cheruiyot, Wray, and Katumba (2015) and Katumba, Cheruiyot, and Mushongera (2019) found a similar socio-spatial pattern in their examination of levels of dissatisfaction with local government in Gauteng with residents in the periphery exhibiting greater levels of dissatisfaction with local government than residents located in the more central parts of the province. The researchers argued that a core and peripheral divide exists in the spatial distribution of these attributes.…”

“…The result was the creation of so-called "townships". It is the historical neglect of these township communities in terms of the provision of public services, resources and infrastructure which researchers have argued has given rise to an increase in dissatisfaction with government (Cheruiyot, Wray, and Katumba 2015;Katumba, Cheruiyot, and Mushongera 2019). In this context, socio-economic impoverishment, and concentrated disadvantage has colluded to create ecologically isolated and stereotyped communities.…”

“…Second, generalizations have been made on the socio-economic status of wards (poor/affluent), even though no measures of affluence were conducted in this analysis. Our reference to the socio-economic wealth of wards in Gauteng is based on previous research (see Peberdy, Harrison, and Dinath 2017;Katumba, Cheruiyot, and Mushongera 2019) as well as prior experience of having resided and visited these wards on numerous occasions over the past three decades. Finally, different respondents were interviewed during each iteration of the survey; therefore, the respondents do not reflect specific individuals' views over the period under consideration but rather the general attitudes and feelings of people who reside in the same locality.…”

“…In South Africa, Cheruiyot, Wray, and Katumba (2015) used spatial error modeling to investigate levels of dissatisfaction with the performance of local government in Gauteng province while Katumba, Cheruiyot, and Mushongera (2019) also used a number of geospatial techniques to examine poverty in the same province. Both studies found significant spatial clustering in the level of dissatisfaction with the performance of local government and poverty levels, respectively, with the former study also identifying a number of spatial predictors of the level of local dissatisfaction.…”