The sovereign rating is a qualitative assessment of the reliability of the borrower that informs investors investing in financial assets about important indicators such as government debt, its development and the overall state and future prospects for development of its economy. The main research goal is to test the significance of the individual macroeconomic indicators in determining the sovereign rating and to determine which of them has the most influence by using a multiple linear regression and correlation analysis based on ordinary least squares (OLS). We used an original method of multicollinearity measurement as share of tightness of the system including and excluding the dependent variable.

Credit ratings are based on Standard & Poor's, Moody's ratings are drawn from Moody's Investors service. When selecting countries, the population criterion was used. Macroeconomc indicators are used to calculate the rating using the World Bank Indicators data, which consists of 1519 indicators. The first hypothesis assumes that the following are the most important indicators for determining the state rating: government debt in total to GDP, GDP per capita, GDP growth rate, unemployment rate and inflation. Other indicators such as x₁ government debt to GDP x₂ unemployment rate and x₄ growth rate of GDP have not been confirmed as significant indicators influencing the ratings. However, the main benefit of this theses is also the creation of regression equations to estimate the rating of a particular state in the given year, or the rating of a particular state in a time series. The high value of the aggregate correlation coefficient was impaired by absolute multi-collinearity. In one instance, the aggregate correlation coefficient did not exceed 80% when multi-collinearity was below 20%. Rating grades cannot be explained solely by economic characteristics, but are also influenced by political or strategic factors.