Disposable Income and Life Insurance Demand in Sub-Sahara Africa

This study examines the effect of disposable income on life insurance demand in Sub- Saharan Africa by taking a sample of 15 selected African countries in the Sub-Sahara region. To achieve this, we selected various countries of our interest that have consistently published their data between 1995 and 2016. The specific objectives are to determine the relative effect of per capita income, as well as major macroeconomic factors and preferences on life insurance demand in the sample countries. A sample of fifteen (15) selected African countries in the Sub-Saharan region formed the sample of this study, this was to ensure adequate observation for statistical testing. We adopted a panel (balanced) data analysis to identify the possible country’s specific type of disposable income and how it affects life insurance demand. To this end, we conducted the unit root test analysis to check the level of data stationarity in the specified models. Fixed and random effects panel data techniques were conducted as well as the Hausman test which formed basis for selecting the preferred model between fixed and random effects models. Our results indicate that inflation and real interest rate both exert negative effect on life insurance demand in Sub-Saharan Africa, while gross domestic product per capita shows positive significant impact on life insurance demand in Sub-Saharan Africa. We therefore recommend that efficient management of gross domestic product per capita leading to increased disposable income is crucial if Sub-Saharan is to sustain growth in life insurance demand. The specific objectives are to determine the relative effect of per capita income, as well as major macroeconomic factors, preferences and life insurance demand in the sampled countries. It is argued in this study that the key macroeconomic factors driving demand for life insurance in the case of Sub-Saharan Africa is disposable income captured by GDPPC. Using annual data covering the period 1990 – 2011 (22 years), the study applies the panel data estimation and analytic methodology, which allows for endogenization of individual country characteristics in the analysis. The modeling adopted in this study categorizes all the necessary macroeconomic factors in the study that seek to explain both insurance penetration and insurance density for the sampled countries, which are Nigeria, South Africa, Namibia, Cameroon, Ghana, Cote d’Ivoire, Sudan, Kenya, Uganda, Mozambique, Togo, Benin, Senegal, Cape Verde and Zambia. Analyses and tests were carried out using location.