Based on the literature analysis, housing insecurity does not have a universally validated measure or scale that can be used across societies and contexts to measure housing insecurity. The literature on housing and housing insecurity is marred with individualised preferences of what individual researchers or organisations appropriate to measure housing insecurity. This paper takes the first step of proposing a scale of measuring housing insecurity that can be adopted for any context be it in developed countries or developing societies. The paper recognises the economic thinking that claims that the tools of mathematics are not always appropriate in the analysis of social reality (Lawson 2015) hence cognisance of the fact that functions and calculus are not always the best, this paper still makes use of mathematical calculations involving weights and still relies on the development of constructs that can be useful in explaining the reality of housing insecurity. We ask the question, to what extent is the ontology of housing so abstract that the numbers can be misleading? It is argued in this paper that the conception of reality and hence housing insecurity can still depend on the mathematical tools to understand the ontology of housing insecurity. Going deeper this paper does not claim to belong to the pluralism, or neoclassical thought, but as anticipated, devoid of that discourse and make use and hence benefit from both mainstream economic theory and aspects utilised by the pluralist school of thought and hence makes reference to the ontology of economics.
Abstract. The analysis of income at household level is highly important for understanding the poverty and for supporting the efforts to deal with poverty. Poverty measures can be calculated from a multitude of approaches. A common approach is to use household income and draw a minimum level of income required for a household to be considered above or below poverty. This paper looked at income at household level from a gender perspective and a marital status perspective in order to draw conclusions of the nature of household's characteristics that are associated with higher or lower income as a proxy for poverty. Based on data collected in a low income township in South Africa, the regression analysis was applied to investigate the differences between different marital statuses and gender and how they are associated with different levels of income. The regression results reveal that female headed households have, on average, lower incomes compared to male headed households, and also, that married heads of households have higher incomes compared to the single, divorced, and widowed. The widowed had the lowest average income.
JEL classification: I32
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