This dissertation presents three essays. The first essay finds that the household risky ratio, the ratio of high risk assets over low risk assets directly owned by households, is a strong negative predictor of the equity premium on the US stock market. The predictability is robust to definition of the asset classes, first versus second half of sample, and the finite-sample bias of Stambaugh (1999). The predictability is stronger than, and not subsumed by popular predictors like price-earnings ratios, yield spread, equity share of issues, or consumption-wealth ratios. The main predictive power is decomposed into three similar parts: 1) the household tilt of risky assets, which is novel and generally orthogonal to known predictors; 2) a valuation ratio component; and 3) an issuance component of high risk versus low risk assets. / Economics

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)

This study aims at investigating household food accessibility categories (food insecure, vulnerable, marginal and food secure) of rural households in Sekhukhune district of Limpopo province. The study is based on five wards in Mamone village in the Limpopo province of South Africa. Ten households from each ward were randomly selected for the study. Structured questionnaires administered by enumerators were used to collect information from household heads. In all 50 household heads constitutes the sample size for the study. Data was collected from 20 August 2007 to 25 August 2007. Responses in the questionnaires were tabulated, coded and processed using Statistical Package for Social Sciences (SPSS) programme. Based on comprehensive food security and vulnerability analysis the study showed that over 70 per cent of the sampled households were food insecure. Lack of education, income sources, water source, and infrastructure were some of the important factors contributing to food insecurity. The government should also give special attention to policy measures that guide towards the provision of household assets. It is recommended that special attention be given to measures that will provide the necessary factors that negatively affect household food security and vulnerability. / Agriculture, Animal Health and Human Ecology / M.A. (Human Ecology)

This study aims at investigating household food accessibility categories (food insecure, vulnerable, marginal and food secure) of rural households in Sekhukhune district of Limpopo province. The study is based on five wards in Mamone village in the Limpopo province of South Africa. Ten households from each ward were randomly selected for the study. Structured questionnaires administered by enumerators were used to collect information from household heads. In all 50 household heads constitutes the sample size for the study. Data was collected from 20 August 2007 to 25 August 2007. Responses in the questionnaires were tabulated, coded and processed using Statistical Package for Social Sciences (SPSS) programme. Based on comprehensive food security and vulnerability analysis the study showed that over 70 per cent of the sampled households were food insecure. Lack of education, income sources, water source, and infrastructure were some of the important factors contributing to food insecurity. The government should also give special attention to policy measures that guide towards the provision of household assets. It is recommended that special attention be given to measures that will provide the necessary factors that negatively affect household food security and vulnerability. / Agriculture, Animal Health and Human Ecology / M.A. (Human Ecology)