Global Inequality in Life Expectancies: What Role Does Income Inequality Play?

Context: Life expectancy best helps to capture the health and well-being of a population. However, wide differences are seen in life expectancies across different countries and at different points of time. Research objective: This study examines trends in global inequalities in Life Expectancy at birth between countries from 1960 to 2017, and studies how income inequality affects inequality in life expectancy. Data and methodology: Life expectancy at birth is the main variable under study. We have also used data on GDP per capita at purchasing power parity, Health Expenditure per capita and Government Expenditure on health per capita. Six measures of inequality have been used, primary being the Gini coefficient. We have divided the countries into four groups according to the World Bank Classification Scheme, and have used graphs, choropleth maps and Moran’s I for statistical analysis. The causal relationship between inequality in Life Expectancy and per capita GDP is examined using reduced form regression models. Findings: The life expectancy at birth shows a steadily rising trend. The choropleth maps indicate considerable spatial variations in life expectancy, which are stable over time. There is a decline in the global inequality in life expectancy over time. Moreover, the decomposition analysis for the Gini coefficient shows that in any year, the between groups inequality is more important than the within groups inequality. This is corroborated by the decomposition of Gini over time. We infer from the devised regression models that there is a positive association between per capita income inequality and inequality in life expectancy. The regressions point out evidence that inequality in lifespan and inequality in per capita income can be explained in terms of inequality in health expenditure.