Predicting the role of socio-economic indices for the Human Development Index based on a multivariate regression model

Social and economic indicators of countries at the global level can reveal both weak and strong achievements concerning specific countries on a wide range of indices. The purpose of the present study was to investigate the correlations between social and economic indicators and the Human Development Index (HDI), a summary composite measure of a country's average wellbeing. Secondary analysis was conducted between April and July 2022. Six variables of the HDI (i.e., the Gini Coefficient Index [GCI], Multidimensional Poverty Index [MPI], Research and Development Percentage Index of gross domestic product [R&D], infant mortality rate (IMR), and Gender Development Index [GDI]) were investigated across 189 countries in six continents. Data were analyzed using a multivariate regression model. The average HDI in the countries of the world was equal to 0.72 (SD ± 0.14), with the highest HDI score in Europe (0.87 ± 0.06; p < .001). Europe also had the highest R&D (1.34 [SD ± 1.02]; p < .001) and GDI indicators (0.98 [SD ± 0.02]; p < .001). Africa had the highest infant mortality (41.62 [SD ± 18.93]; p < .001) and highest MPI (0.230 [SD ± 0.166]; p < .001). America had the highest GCI (44.10 [SD ± 6.27]; p < .001). Findings indicated that countries with a higher HDI had better social and economic indicators (p < .001). There was a correlation between all selected indices with the HDI. The highest (negative) correlation was observed between IMR and HDI (r = − 0.885). The multivariate regression model showed IMR and the MPI were significant predictors of HDI and explained 84.7% of variance. The two country indicators of IMR and MPI are good predictors of a country’s HDI.