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

It is twenty-one years since South Africa’s democracy and the majority of South African households can still be classified as poor, despite the various interventions by Government to reduce poverty and inequality. The measurement used to determine the financial status of a household at a given point in time is its net equity in accordance with its Statement of Financial Position, calculated as its assets owned less liabilities owed. This study aimed to identify the selected significant factors that affect a South African household’s net equity value. In order to achieve the aim of this study, a heuristic model consisting of two components was developed. The first component considered which assets and liabilities should be included in determining a household’s net equity and how these assets and liabilities should be valued. The second component identified the selected factors that influence a household’s net equity. The heuristic model was applied to the empirical data using three phases. Firstly, the net equity value was calculated for each household. This was followed by an analysis of the selected factors that significantly influence household net equity. The last phase was performed to determine the effect of the identified selected factors in explaining the difference between households that have above average net equity values and those having below average values. The results of the study indicated that 11 selected factors significantly influence the net equity value in the South African household’s Statement of Financial Position. Seven of those factors significantly explain between 28,3 percent and 38,1 percent of the differences in the net equity value of a household when comparing the households with above average net equity value with those with below average values. This is useful information for policy makers in identifying the selected factors that will most significantly increase the net equity value of a household with a net equity value below the South African average. / Centre for Accounting Studies / M. Com. (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)

It is twenty-one years since South Africa’s democracy and the majority of South African households can still be classified as poor, despite the various interventions by Government to reduce poverty and inequality. The measurement used to determine the financial status of a household at a given point in time is its net equity in accordance with its Statement of Financial Position, calculated as its assets owned less liabilities owed. This study aimed to identify the selected significant factors that affect a South African household’s net equity value. In order to achieve the aim of this study, a heuristic model consisting of two components was developed. The first component considered which assets and liabilities should be included in determining a household’s net equity and how these assets and liabilities should be valued. The second component identified the selected factors that influence a household’s net equity. The heuristic model was applied to the empirical data using three phases. Firstly, the net equity value was calculated for each household. This was followed by an analysis of the selected factors that significantly influence household net equity. The last phase was performed to determine the effect of the identified selected factors in explaining the difference between households that have above average net equity values and those having below average values. The results of the study indicated that 11 selected factors significantly influence the net equity value in the South African household’s Statement of Financial Position. Seven of those factors significantly explain between 28,3 percent and 38,1 percent of the differences in the net equity value of a household when comparing the households with above average net equity value with those with below average values. This is useful information for policy makers in identifying the selected factors that will most significantly increase the net equity value of a household with a net equity value below the South African average. / Taxation / M. Phil. (Accounting Science)