| dc.description.abstract | The dissertation comprises three empirical analyses focusing on the origins of South African households’ income sources. The income sources are categorized to reflect the households’ varying extent of economic core sector integration. All three chapters contain analyses of household survey data from 1995 and focus on the African and coloured population.
Chapter 1
explores the extent to which inequality in a sample 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. 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.
Chapter 2
utilizes the income source categories to investigate whether these can contribute to explain inter-household variation in income sources can explain variation in income levels. 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 as 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. The results also suggest that households in different main income source categories differ systematically in their demographic and educational endowments.
In Chapter 3
the sample is restricted to the African and coloured households that have a main income source. The analyses aim to identify household level characteristics that are associated with differing extents of core sector integration. Two separate multinomial logit models are estimated, for urban and non-urban households respectively. The output from the analysis is utilized to compute the probabilities for a household having a main income source from either one of five categories. The results indicate that prominent covariates of low core-economy integration are earners of income with low levels of education, of female gender, and of either old or of young of working-age. A non-urban household’s location in either a former “homeland” or in an agriculturally or commercially developed area also 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 endogenous household formation in South Africa.
Doubtlessly, varying extents of core-sector integration is very much an inter-racial phenomenon in South Africa. However, the analyses show that such integration varies considerably also within the previously disadvantaged population segment in South Africa. There, the varying integration displays impacts on household welfare that are separable from other characteristics, but is a mechanism which appears in part determined by household or individual earner characteristics.
Other studies emphasize the importance of employment creation as a policy objective to combat South Africa’s many challenges. The results here support the dire need for more employment, since the worst-off households often rely on non-labour income sources. However, even if employment would increase in South Africa’s core economy within the foreseeable future, no guarantee exists that the currently most marginalized households would be integrated. For the latter to eventuate, demand for labour would have to extend into remote areas and encompass low-skilled, largely female, and young labour that may not currently afford to market their services. Geographically targeted efforts that upgrade the skills of the young and facilitate their access to the labour market are thus also favoured by the results of these studies. | swe |
