Insurance Market Development and Income Inequality

Abstract

This study aims to empirically analyze the relationship between insurance market development and income inequality for 13 countries from 1980 to 2006. Specifically, we examine how country-level income distributions are related to one particular measure of insurance market development. Our proxies for insurance market development are total life insurance premiums (LP), and total non-life insurance premiums (NLP), which are used as independent variables. The dependent variable is the Gini coefficient (Gini, a common measure of income inequality). Granger causality tests and Generalized Method of Moments (GMM) methodologies were employed to analyze correlations between these variables. Granger causality tests were used to determine if the direction, if any, of the cause and effect relationships among these variables. The results of the Granger causality test indicate that LP affects the Gini coefficient while NLP is influenced by Gini in the total sample of countries. For the higher income economies, NLP is influenced by Gini, whereas both LP and Gini affect each other, and NLP affects Gini in the lower income group. Using the GMM methodology to perform a correlation analysis controls for endogeneity among independent variables, the results suggest that LP has negative (-) relationship with Gini for the total sample. Gini is also negatively (-) related with LP in the higher income economies. Thus, the evidence indicates that life insurance market development results in reduction of income inequality for the total sample of countries. Furthermore, income inequality is lessened as the life insurance market expands in the higher income economies. The empirical findings have some implication for insurance consumer well-being in high income countries.