The South African Reserve Bank presents an annual balance sheet for the South African household sector constructed from macro-economic data estimates. Broad asset and liability classes are presented which can be disaggregated with the use of micro-level data obtained directly from households. At the time of the study, however, micro-level data on the different asset and liability classes accumulated by households was not available. The main objective of the study was to disaggregate and measure the asset and liability base of South African households in metropolitan and non-metropolitan areas using micro-level data. The study used a mixed methodological approach, consisting of both qualitative and quantitative data and was conducted in three phases. In the first phase, a comprehensive literature review was conducted on the recognition and measurement of household assets and liabilities. Economic theories that explain asset and liability accumulation were reviewed and international surveys on household net wealth measurement scrutinised. A heuristic model of a financial position section for the South African household sector was developed. In the second and qualitative phase, online and face-to-face focus group deliberations were conducted with experts in the field of household finance to ensure that the newly developed financial position section would robustly recognise and measure all possible household asset and liability classes. In the third and quantitative phase, the financial position section was included in an omnibus survey and data was collected from a representative sample of 2 606 households in South Africa. The weighted data was segmented in terms of metropolitan and non-metropolitan areas and presented as statements of financial position based on the classification, recognition and measurement principles of “The Conceptual Framework for Financial Reporting 2010”. Composition analyses presented a secondary objective, namely to explore the effect of identified independent demographic variables on asset and liability accumulation. Multivariate analysis of variance (MANOVA) identified meaningful interaction effects for (1) age, income and area; (2) income and age; (3) education, income and age; and (4) education and income on asset accumulation and an age and income interaction effect on liability accumulation. The study contributes to the body of knowledge on the contemporaneous effect of age, income, education and area of residence on household asset and liability accumulation and provides information on South African household net wealth not yet available. The disaggregated asset and liability base will assist policy makers both at micro- and macro-economic level with the overview and management of South African household net wealth. / Business Management / D. Accounting Science

The South African Reserve Bank presents an annual balance sheet for the South African household sector constructed from macro-economic data estimates. Broad asset and liability classes are presented which can be disaggregated with the use of micro-level data obtained directly from households. At the time of the study, however, micro-level data on the different asset and liability classes accumulated by households was not available. The main objective of the study was to disaggregate and measure the asset and liability base of South African households in metropolitan and non-metropolitan areas using micro-level data. The study used a mixed methodological approach, consisting of both qualitative and quantitative data and was conducted in three phases. In the first phase, a comprehensive literature review was conducted on the recognition and measurement of household assets and liabilities. Economic theories that explain asset and liability accumulation were reviewed and international surveys on household net wealth measurement scrutinised. A heuristic model of a financial position section for the South African household sector was developed. In the second and qualitative phase, online and face-to-face focus group deliberations were conducted with experts in the field of household finance to ensure that the newly developed financial position section would robustly recognise and measure all possible household asset and liability classes. In the third and quantitative phase, the financial position section was included in an omnibus survey and data was collected from a representative sample of 2 606 households in South Africa. The weighted data was segmented in terms of metropolitan and non-metropolitan areas and presented as statements of financial position based on the classification, recognition and measurement principles of “The Conceptual Framework for Financial Reporting 2010”. Composition analyses presented a secondary objective, namely to explore the effect of identified independent demographic variables on asset and liability accumulation. Multivariate analysis of variance (MANOVA) identified meaningful interaction effects for (1) age, income and area; (2) income and age; (3) education, income and age; and (4) education and income on asset accumulation and an age and income interaction effect on liability accumulation. The study contributes to the body of knowledge on the contemporaneous effect of age, income, education and area of residence on household asset and liability accumulation and provides information on South African household net wealth not yet available. The disaggregated asset and liability base will assist policy makers both at micro- and macro-economic level with the overview and management of South African household net wealth. / Business Management / D. Com. (Accounting Science)

South Africans carry high debt levels and many deal with the threat of over-indebtedness. In particular, the debt situation of the youth is of utmost concern. This study was undertaken to gain an understanding of how the liability usage of households fluctuates over the life course. The main objective was to identify and describe how debt is accumulated by young South Africans and how household characteristics and events may be related to the uptake of household liabilities. This study conducted a comprehensive literature review culminating with the development of a heuristic model that identified variables that may affect household debt uptake. Quantitative statistical analysis techniques were employed on secondary data acquired from the South African Audience Research Foundation’s All Media and Products Survey for the years 1999 until 2013. The findings identified that household debt follows a familiar life cycle pattern. A number of independent variables were shown to affect household debt uptake. Furthermore, certain of these variables are related to the trajectories of the life course. / Taxation / M. Acc. Sci.