MODELING GDP DYNAMICS USING REGRESSION ANALYSIS OF PANEL DATA
The article considers an approach to the analysis of macroeconomic indicators using panel regression analysis. Models of dynamics of GDP per capita in three groups of countries differing in the level of economic development in the period after the collapse of the USSR are obtained. The share of exports in GDP, the trade balance per capita, and the level of Worldwide Governance Indicators were chosen as predictors. There was made an attempt to substantiate the difference in the dynamics of these indicators. An assessment of the quality and a criterion for choosing possible models for panel data (pooling model, fixed effect, random effects model) are given. The difference in actual and model values for the selected models for some countries of the selected groups is demonstrated.