ECONOMETRIC MODELING OF ECONOMIC GROWTH FACTORS BASED ON PANEL DATA

Abstract

Economic growth is a key indicator of a country's development and a subject of research in macroeconomics. The study of factors affecting the level of GDP per capita allows developing effective economic policy strategies and improving the well-being of the population. Modern methods of econometric analysis, in particular panel methods, allow obtaining data on both time trends and individual characteristics of individual countries. This is especially important when comparing countries with very different socio-economic and political conditions. The article examines the factors of economic growth based on econometric modeling of panel data for 18 countries for the period 2002–2020. GDP per capita was chosen as the effective indicator, and the main explanatory variables are indicators of foreign economic activity (the share of exports in GDP and the trade balance per capita) and the quality of public administration institutions (Worldwide Governance Indicators). To take into account the individual characteristics of countries, panel models with fixed and random effects were used. The selection of the most adequate model specification was carried out using the Wald, Breusch–Pagan and Hausman tests.

The results show that indicators of the quality of public administration and the effectiveness of foreign economic activity are statistically significant determinants of GDP per capita, but their impact varies across groups of countries. The study emphasizes the importance of combining economic and institutional factors to ensure sustainable economic growth. The methods used demonstrate the advantages of panel data analysis for increasing the accuracy of estimates and taking into account latent, country-specific factors.