Investigation of Factors Determining Lithuanian Public Debt to Foreign Countries

Abstract Research purpose. The study aims to examine which indicators influence the amount of Lithuanian public debt to foreign countries. Design / Methodology / Approach. First of all, in order to find out what could be preliminary indicators influencing the public debt, a comprehensive literature review has been done. This was implemented with the main goal of finding out the influencing independent variables, which were used for the next calculation. Successively was the selection procedure of the appropriate methodology for solving similar tasks. The pairwise and multivariate regression analyses have been carried out with the collected data. Findings. Empirical research has shown that all independent variables are significant and can be used for pairwise regression analysis. After doing this, the authors found that no regression equation could be completed with no variable, which means that none of the variables affects the dependent variable (altogether). A multivariate regression analysis was also performed to check the impact of the selected variables on public debt. The regression equation was succeeded only when the criterion “population” had been eliminated. The results show that GDP, the unemployment rate, inflation and the minimum wage (in composition) may have an impact on the government’s external debt. Originality / Value / Practical implications. Due to the emergency (pandemic) situation, the Lithuanian state borrowed a considerable amount of money from the European Commission - last year, it was planned to borrow 2.7 billion according to the initial budget, but due to the situation, the debt was increased by 5.1 billion Euros. The concept of reasoning the amount of public debt to foreign countries is valuable not only in the concept of the COVID pandemic. This empirical research analyses the critical substances which affect the public debt based on factual statistics, correlation analysis and pairwise and multivariate regression.