Аnalysis of public debt based on long time series, trends and forecasts

Abstract

The size and impact of public debt on economic and social processes is a very relevant issue today. The crisis caused by the coronavirus epidemic has caused a significant increase in public debt not only in Hungary, but also in the whole world. It can be said that the central issue of economic policy today is how to get out of this situation, what tools are needed to return at least to the pre-crisis level of public debt on a fair basis. The purpose of our research is to analyze public debt as a share of GDP in Hungary based on long time series, establish trends and make a forecast. The share of public debt in GDP is one of the most important macroeconomic indicators. This is justified not only by its role in the analysis of economic processes (risk, economic growth, investments, money and capital markets), but also by its constitutional-financial-legal assessment. The ratio of public debt to GDP is an important indicator for the long-term stability of economic processes in the state. The relevance of the analysis of public debt based on analytical trends is enhanced by the economic shock caused by the COVID epidemic, which was an unpredictable factor, and the situation formed by the epidemic deviates significantly from the stable trends of economic processes in previous years.For the study, secondary data were used, which were evaluated using trend analysis. Statistical smoothing of the time series of public debt as a share of GDP was tested at a statistically acceptable level using a quadratic polynomial trend. Modeling was performed using linear and logarithmic trend functions, in both cases a less favorable fit of the function was obtained than in the case of an exponential trend. The obtained short-term forecast indicates a gradual decrease in the state debt indicator, which is confirmed by expert conclusions.