Insurance penetration and economic growth in Africa: Dynamic effects analysis using Bayesian TVP-VAR approach

Abstract

This paper examines the dynamic interactions between insurance and economic growth in eight African countries for the period of 1970-2013. Insurance demand is measured by insurance penetration which accounts for income differences across the sample countries. A Bayesian Time Varying Parameter Vector Auto regression (TVP-VAR) model with stochastic volatility is used to analyze the short run and the long run among the variables of interest. Using insurance penetration as a measure of insurance to economic growth, we find positive relationship for Egypt, while short-run negative and long-run positive effects are found for Kenya, Mauritius, and South Africa. On the contrary, negative effects are found for Algeria, Nigeria, Tunisia, and Zimbabwe. Implementation of sound financial reforms and wide insurance coverage are proposed recommendations for insurance development in the selected African countries.