Information and statistical support for monitoring budget security in conditions of economic instability

Abstract

The article considers the issues of improving the methodology of statistical monitoring of budgetary security of Ukraine in conditions of macroeconomic instability caused by both internal and external factors. The relevance of the study is due to the need for timely identification of threats to the fiscal stability of the state in the context of a full-scale war, a significant increase in public debt, inflationary pressure and currency volatility. Reliable and integrated statistical information is a key resource for informed decision-making and the development of strategic forecasts. The purpose of the study is to substantiate a comprehensive approach to building a system of information and statistical monitoring of budget security. Methods. The work uses an indicative approach to selecting a set of relevant indicators (budget deficit, debt burden, structure of tax revenues, level of tax autonomy, volume of intergovernmental transfers, etc.). To analyze the dynamics of the index, time series and correlation-regression analysis were used to identify the impact of macroeconomic factors (GDP, inflation, public debt, unemployment, hryvnia exchange rate) on the level of budgetary security. Results. The integral index of budgetary security of Ukraine for the period 2010–2023 ranged from 0.3 to 0.6, which indicates a low or medium level of stability of the budgetary system. The highest level (about 0.6) was observed in 2020, the lowest (about 0.3) in 2015 and 2022. The correlation-regression model showed that GDP growth contributes to the growth of the index, while inflation, debt burden, unemployment, and hryvnia devaluation have a negative effect. Conclusions. The proposed statistical monitoring methodology, based on the integral index and statistical methods, can be integrated into the information systems of government bodies to improve the efficiency of financial resource management and timely response to risks. Further research should be directed towards the development of software tools for real-time monitoring and improvement of forecasting methods taking into account external threats.