Determinants of life and funeral insurance penetration and density in South Africa
Thesis (MPhil Development Finance)--Stellenbosch University, 2015.
ENGLISH ABSTRACT: As the life and funeral insurance premiums have increased significantly between 2001 and 2013 in South Africa, it was important to assess the determinants, macroeconomic or demographic, that influenced this trajectory. Although there is significant literature and empirical findings on the determinants of life insurance demand, there are few studies that have explored the determinants of microinsurance in general or funeral insurance in South Africa. In our research, we were also interested to find whether the determinants of life insurance penetration and density were similar to those of funeral insurance penetration and whether macroeconomic factors had a greater influence than demographic factors on the demand for life and funeral insurance. The factors used in the data analysis were identified through a review of previous empirical studies, after which they were collected from various sources and prepared for analysis. We assessed descriptive statistics to determine the nature of all variables and basic relationship between them. Then we performed multiple linear regression analysis using an Ordinary Least Squares Estimation (OLS) in other to ascertain the main factors that drove the increase in life and funeral insurance. Finally, we conducted Johansen cointegration and Granger causality in order to determine whether a causal relationship between income and life insurance existed. Although we expected income per capita to be a significant determinant across all dependent variables, it was not as strong as envisioned. It was only significant and positive for the life and funeral insurance density models. This was the same result for life expectancy at birth. The young age dependency ratio had a positive effect on life insurance consumption but not on funeral insurance consumption. Unemployment had a negative effect on funeral insurance consumption but it was interesting to note that the level of grants or social welfare provided had a positive impact on funeral insurance penetration. This was in contrast to life insurance penetration where a negative impact was observed. We found that demographic factors had a larger explanatory power than macroeconomic factors but that a combination of both types of factors resulted in more optimal regression models. Finally we found that a unidirectional causal relationship between income and life insurance penetration and density existed running from life insurance penetration and density to income with no feedback effects.
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