Короткий опис (реферат):
Forecasting external public debt under conditions of uncertainty is important as it allows
the country to respond adequately to economic and financial challenges, promotes efficient
management of financial resources, formation of a stable financial policy and
ensures the country's external debt security, which are critical elements for ensuring
economic sustainability and sustainable development. The article's main purpose is to
critically analyze and apply existing time-series forecasting methodologies to determine
the future values of Ukraine's external public debt in conditions of uncertainty caused
by the still unresolved consequences of the COVID-19 pandemic and russia's invasion
and full-scale war in Ukraine. Using three forecasting methods, namely trendline extrapolation,
exponential smoothing, and autoregressive and moving average models,
the paper forecasts the volume of external public debt until 2029 and presents a graphical
representation of the debt dynamics from 2011 to 2029. The most pessimistic forecast
for the growth of external public debt was revealed when applying the method of
data extrapolation based on the trendline. A comparative analysis of the forecast values
for the three forecasting methods has revealed common trends in the growth of public
debt, as well as the key advantages and disadvantages inherent in each model. Importantly,
the article emphasizes the common risks identified in forecasting Ukraine's
external debt using time series analysis models, including the problem of achieving only
short-term forecasting accuracy and insufficient flexibility taking into account complex
and unexpected changes that may arise in conditions of uncertainty and economic instability.
The results of the study provide valuable information for policymakers and
stakeholders trying to navigate the complexities of managing external public debt under
uncertainty.
