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

This is the authors' abstract. We don't add key points for this paper.

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.