Development of the Indicative System for Assessing GDP Per Capita Using Cumulative Indices, Including Human Capital

Viktor Dmitrievich Orekhov, Olga Sergeevna Prichina, Aliya Shavkatovna Gizyatova, Alla V. Blinnikova and Olesya G. Kukharenko

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