We apply the geographically weighted regression to investigate spatial variability (nonstationarity) in the relationships between municipal operating expenditure (in total and for a separate component thereof) and the determinants of this expenditure, in South Africa. The empirical findings indicate that some of these relationships are spatially varying for the period under consideration. The global model (i.e., least square regression) cannot take account of the unequal environment in which South African municipalities operate. One implication of our findings is that a “one‐size‐fits‐all” approach in the design of policies targeting municipal finances may not be appropriate for municipalities in South Africa, and indeed in other contexts in which such heterogeneity is found. Instead, policy formulation should explicitly consider relevant differences in local conditions.

This paper investigates the relationship between household income and the share of food expenditure in South Africa using clustered household income and socio-economic data published in the National Dynamics Income Study. To achieve this objective and because of the clustered nature of the data, a multilevel linear model, in particular, the random intercept model, was employed as a suitable method of investigation. Fixed effect methods were also used to compare results. The results confirmed that the share of household food expenditure is inversely related to household income in a district. This finding is consistent with Engel’s law, such that an increase in household income is related to a decrease in the proportion allocated to food items by a typical household within a district. It was found that the relationship between household income and food expenditure does not vary across districts. The finding also pointed out that the district context matters because the district’s average household income significantly explains the share of food expenditure at the household level.

The main objective of this paper is to examine the relationship between two types of property‐related crime and some socio‐economic, demographic and deterrence factors. It employs the conditional autoregressive specification to account for spatial autocorrelation that characterises property‐related crime data, which are aggregated up to the level of municipality. First, the analysis confirms the presence of spatial autocorrelation in the data, which means that neighbouring municipalities exhibit similar levels of property crime rates. In addition, and most importantly, empirical findings show that internal migration, youth and education are important predictors of property‐related crime across municipalities in South Africa for the period under consideration.

This paper examined the role of male partners in modern contraceptive use by women across clusters in South Africa. Its main objective was threefold. First, the present paper sought to test whether South African married women’s modern contraceptive use is related to the influence of their husbands or male partners. Second, it examined whether modern contraceptive use is similar within clusters. Third, it tested whether group effects are spatially dependent among neighbouring clusters. It used the recent Demographic and Health Survey for South Africa as the data source to carry out the empirical analysis. On the one hand, the results confirm a positive and significant relationship between South African married women’s modern contraceptive use with their partners’ secondary education level, irrespective of the cluster in which they reside. On the other hand, the hypothesis that spatial dependence of random effects is not confirmed, leading to the conclusion that space only matters when it comes to spatial heterogeneity or group effects.

This paper examines the relationship between the education level of household heads and households' energy-saving practices at the micro-level in South Africa. It uses the community survey of 2016 as data source. Multilevel logistic models are estimated to account for similari-ties between households in same municipalities. The results point to a significant and positive relationship between the education level of household heads and households' energy-saving practices. One can therefore infer that a household whose head is educated is more likely to have light bulbs, switch off lights in the house when not in use, and switch off appliances at the wall (not with remotes) when not in use than households whose heads have no education. Therefore, education offers a tool to incentivise households to save electricity, which will also contribute indirectly to the effort of addressing the challenges of climate change, amongst oth-ers.