The goal of the study is to develop the indicative system for assessing GDP per capita (result), depending on changes in the indices describing both human capital and a wide range of alternative institutional development factors at the international level (potential reasons) using an exploratory forecast. A generalized correlation formula of combining ten global indices into the optimal predictor CP1 has been developed based on regression modeling, which provides a GDP per capita (GDP/C) forecast with a low coefficient of determination equal to 3 % for 12 largest economies and an average of 8 % for five samples from the largest countries by GDP (6, 12, 24, 48, and 72). The generalized correlation formula for the regression dependence, which allows finding the value of GDP/C from the predictor CP1, is as follows: GDP/C = 139∙CP13.75. The degree of influence of the indices included in the predictor CP1 and determining the value of GDP/C has been revealed. The main influence is exerted by the indices describing the development of human capital: Human Capital Index and Mean Years of Schooling (44 %), as well as the World Happiness Index (24 %) and Legatum Prosperity Index (19 %). The use of regression modeling has allowed to identify potential causes that were not taken into account by the existing global indices, but had significant impact on the GDP/C value. The result of the study is an optimized system of indices, which predicts GDP/C with a high coefficient of determination.
Volume 12 | 05-Special Issue
Pages: 1139-1152
DOI: 10.5373/JARDCS/V12SP5/20201867