GLOBAL WELL-BEING AND ECONOMIC INEQUALITY

Abstract

The objective of this paper is to find the efficiency of computational methods, namely multinomial logistic regression (MLR) in predicting four classes of human development index (HDI) for 98 world countries for year 2018. In this paper we apply MLR to study the impact of GDP per capita, Net Income Gini index, Wealth Gini index and poverty rate on Human Development Index, for 98 world countries. The MLR model emphasized the nonlinear relationship between economic inequality (measured by GINI indices and poverty rate) and HDI. The logistic regression model achieved 92,9% accuracy and R-square values over 90%. The results of our research have generated a series of suggestions for the future that can be considered by both international organizations and state governments.