Abstract
The study was carried out to examine asset ownership and income as determinants of household poverty in South Africa. The specific objectives were to determine the poverty status of the households and, investigate the influence of asset ownership and income on household poverty in South Africa. Secondary data was sourced from the National Income Dynamics Study (NIDS) 2014/2015 data. A sample size of 9619 households was selected for this study. The poverty status of the households was determined using the poverty line. The poverty line was calculated as two-third of the mean-per-capita household expenditure. Households with expenditure above the poverty line were considered to be “non-poor” and those with expenditure below the poverty line were considered “poor”. For the purpose of this study, assets were divided into monetary and non-monetary assets. Binary logistic technique was further used to analyse the influence of ownership of monetary and non-monetary assets, household income, household size (as a control variable), and provincial locations on the household poverty status. An investigation into the assets owned by households indicated that real estate assets, business assets, vehicle assets, financial assets, superannuation assets, livestock assets and possessions, were assets owned by South African households. The results showed that 59.49% of South African households experience poverty, particularly in Kwazulu-Natal, Eastern Cape and Limpopo provinces. The results of the logistic regression further revealed that ownership of non-monetary assets, income and household size had a positive influence on the household poverty status. The Western Cape, Northern Cape, Free State, and Gauteng provinces had high probability for improving the household poverty status, while Kwazulu-Natal province showed a negative influence on the poverty status. It was recommended that policies should focus on income redistribution through employment generation, which will lead to enhanced income. This can, in turn, be used to acquire assets, especially in the most affected provinces like Kwazulu-Natal, Eastern Cape and Limpopo province.
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