Global estimates of growth–inequality–poverty (GIP) triangle: evidence from World Bank’s classification countries

This study extended the concept of ‘growth–inequality–poverty (GIP) triangle’ by using the principle component approach which allows us to composite different poverty and inequality indicators into one single index that contains most of the useful information from the original dataset. Using the idea of GIP triangle, this study examines the long-run relationship among weighted poverty index (which comprises headcount ratio, poverty gap and squared poverty gap); weighted inequality index (i.e., Watts Index, Gini Index and MLD Index) and average monthly per capita income in the designated 138 countries according to World Bank’s classification over a period of 2005–2010. The data set mainly contain countries’ unit record household survey at least one which is conducted between the countries during the sample period. The regression model encompassing the impact of economic growth and income inequality on poverty reflects that income inequality increases poverty while economic growth decreases poverty. It indicates that the impact of inequality in increasing poverty is a somewhat greater than that of growth in average income in reducing overall poverty in a sample countries. The other regression model encompassing the impact of economic growth and poverty on income inequality showed that the poverty itself is also likely to be a barrier for poverty reduction; and inequality seems to predict lower future growth rates. The final regression model depicting the impact of poverty and income inequality on mean income of the household suggests that poverty itself reduces mean income of the household while income inequality increases economic growth. The results are interesting and simply suggest that whenever social institutions malfunction, the incidence of damage would usually be distributed unevenly over the society’s members. Copyright Springer Science+Business Media Dordrecht 2014