Ahoy the Good Hope?: some bearings and signals in Seldom-Navigated Waters - on inequality in South Africa's Coloured and African population

Previous studies have decomposed South African income inequality into inequality between and within the population groups defined by the apartheid regime's racial classification system. While a substantial fraction of total inequality can be attributed to differences in mean income levels between those population groups, the level of inequality within the racial groups has been found to contribute more to total inequality. Yet few investigations have attempted to elucidate inequality within these population groups. This study therefore explores the extent to which inequality in a joint sample of African and coloured individuals can be attributed specific labour-market related characteristics of their households or household heads. The analyses apply the Theil-L measure of inequality to the distribution of a consumption bundle in a household survey data set from 1995. The education level of household heads is the strongest single explanatory factor, followed by households' main income sources. The race, age categories, or gender of household heads do not account for large fractions of inequality in this sample

Integration into the South African Core Economy: Household Level Covariates

The aim of this paper is to further improve the understanding of income generation among the formerly underprivileged and often impoverished majority of households in South Africa. This study uses household survey data for the analysis of households' integration into the South African core economy. The emerging picture of household income generation is one that disputes common perceptions of the multitude of means by which African households are assumed to generate their income. The majority of households rely to a large extent on one income source and one income earner. Verbal contextual information and descriptive statistics justify the estimation of separate multinomial logit models for urban and non-urban households with the probabilities for having either of five main income source categories as outcomes. Results from the regression analyses indicate that prominent covariates of low core-economy integration are earners who are female, either old or young earners of working-age, who have low levels of education. A non-urban household's location in either a former 'homeland' or in an agriculturally or commercially developed area yields disparate implications for the main income source probabilities. The study also finds associations between main income sources and households' demographic compositions which are compatible with findings in previous research on both private transfer behaviour and endogenous household formation in South Africa.

Homing in on the Core - Households Incomes, Income Sources and Geography in South Africa

The focus of this study is on household income generation among previously disadvantaged households in South Africa. Households' income sources are divided into categories that reflect differing extents of association with the core economy

Integration into the South African Core Economy: Household Level Covariates

The aim of this paper is to further improve the understanding of income generation among the formerly underprivileged and often impoverished majority of households in South Africa. This study uses household survey data for the analysis of households' integration into the South African core economy. The emerging picture of household income generation is one that disputes common perceptions of the multitude of means by which African households are assumed to generate their income. The majority of households rely to a large extent on one income source and one income earner. Verbal contextual information and descriptive statistics justify the estimation of separate multinomial logit models for urban and non-urban households with the probabilities for having either of five main income source categories as outcomes. Results from the regression analyses indicate that prominent covariates of low core-economy integration are earners who are female, either old or young earners of working-age, who have low levels of education. A non-urban household's location in either a former 'homeland' or in an agriculturally or commercially developed area yields disparate implications for the main income source probabilities. The study also finds associations between main income sources and households' demographic compositions which are compatible with findings in previous research on both private transfer behaviour and endogenous household formation in South Africa.The author notes that while any defects or shortcomings in this work are entirely his own responsibility, thanks goes to Arne Bigsten, Lennart Flood, Stefan Klasen, Murray Leibbrandt, Laura Poswell, Donald Storrie, and Ali Tasiran for valuable comments to previous versions of this work. The financial provision for this research by the Swedish International Development Cooperation Agency (Sida) is thankfully acknowledged. The author would also like to thank the Centre for Social Science Research at the University of Cape Town for hosting the author while conducting the research for this work

Integration into the South African Core Economy: Household Level Covariates

The aim of this paper is to further improve the understanding of income generation among the formerly underprivileged and often impoverished majority of households in South Africa. This study uses household survey data for the analysis of households' integration into the South African core economy. The emerging picture of household income generation is one that disputes common perceptions of the multitude of means by which African households are assumed to generate their income. The majority of households rely to a large extent on one income source and one income earner. Verbal contextual information and descriptive statistics justify the estimation of separate multinomial logit models for urban and non-urban households with the probabilities for having either of five main income source categories as outcomes. Results from the regression analyses indicate that prominent covariates of low core-economy integration are earners who are female, either old or young earners of working-age, who have low levels of education. A non-urban household's location in either a former 'homeland' or in an agriculturally or commercially developed area yields disparate implications for the main income source probabilities. The study also finds associations between main income sources and households' demographic compositions which are compatible with findings in previous research on both private transfer behaviour and endogenous household formation in South Africa.The author notes that while any defects or shortcomings in this work are entirely his own responsibility, thanks goes to Arne Bigsten, Lennart Flood, Stefan Klasen, Murray Leibbrandt, Laura Poswell, Donald Storrie, and Ali Tasiran for valuable comments to previous versions of this work. The financial provision for this research by the Swedish International Development Cooperation Agency (Sida) is thankfully acknowledged. The author would also like to thank the Centre for Social Science Research at the University of Cape Town for hosting the author while conducting the research for this work

Homing in on the Core – Households Incomes, Income Sources and Geography in South Africa

The focus of this study is on household income generation among previously disadvantaged households in South Africa. Previous research has found that poverty among South African households was associated with the extent to which workers and their dependants were integrated into the South African core economy. This study investigates whether a similar conception can be ascertained in multivariate regression analysis. Households’ income sources are divided into categories that reflect differing extents of association with the core economy. Ensuing further justification by results from descriptive analyses, the income source categories are utilised as explanatory variables to investigate whether inter-household variation in income sources can explain variation in income levels. For the latter purposes, the results from the estimation of three reduced form models are compared. All three models have households’ log-income levels as dependent variables and share a set of household characteristics as explanatory variables. Two of the models are two-stage specifications that use provincial locations in the construction of instruments for income source categories. The third specification contains no income source variables but includes provincial locations as explanatory variables. The results show that, as compared to the specification with provincial locations, income sources can be incorporated as explanatory variables into multivariate regression analyses without considerable loss of explanatory power. Controls for endogeneity must however be applied. The partial impacts from income sources are statistically significant and their signs are in accordance with expectations. For some income sources the magnitudes of the impacts are not in correspondence with what may be expected from the descriptive analysis. The latter results suggest that households in different main income source categories also differ systematically in their demographic and educational endowments. When assimilated with results from the descriptive analyses, the estimated partial impacts from the different provinces support this interpretation.South Africa: log-income levels, household income, multivariate regression analyses