State debt assessment and forecasting: time series analysis

  • 227 Views
  • 55 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

One of the pressing problems in the modern development of the world financial system is an excessive increase in state debt, which has many negative consequences for the financial system of any country. At the same time, special attention should be paid to developing an effective state debt management system based on its forecast values. The paper is aimed at determining the level of persistence and forecasting future values of state debt in the short term using time series analysis, i.e., an ARIMA model. The study covers the time series of Ukraine’s state debt data for the period from December 2004 to November 2020. A visual analysis of the dynamics of state debt led to the conclusion about the unstable debt situation in Ukraine and a significant increase in debt over the past six years. Using the Hurst exponent, the paper provides the calculated value of the level of persistence in time series data. Based on the obtained indicator, a conclusion was made on the confirmation of expediency to use autoregressive models for predicting future dynamics of Ukraine’s state debt. Using the EViews software, the procedure for forecasting Ukraine’s state debt by utilizing the ARIMA model was illustrated, i.e., the series was tested for stationarity, the time series of monthly state debt data were converted to stationary, the model parameters were determined and, as a result, the most optimal specification of the ARIMA model was selected.

view full abstract hide full abstract
    • Figure 1. Time series graph of the State Debt of Ukraine 2004–2020, UAH mln
    • Figure 2. Monthly growth rates of Ukraine’s state debt for 2004–2020, %
    • Figure 3. Annual growth rates of Ukraine’s State Debt for 2004–2020, %
    • Figure 4. Time series graph of the State Debt of Ukraine 2004–2020, USD ths.
    • Figure 5. The State Debt of Ukraine 2004–2020 сorrelogram, USD ths.
    • Figure 6. Сorrelogram of the State Debt of Ukraine 2004–2020 in first differences
    • Figure 7. Forecasted amount of Ukraine’s state debt, USD bln
    • Table 1. Results of testing time series for stationarity in first differences
    • Conceptualization
      Fedir Zhuravka, Petr Šuleř
    • Project administration
      Fedir Zhuravka
    • Supervision
      Fedir Zhuravka, Petr Šuleř
    • Validation
      Fedir Zhuravka
    • Writing – review & editing
      Fedir Zhuravka, Hanna Filatova
    • Data curation
      Hanna Filatova
    • Formal Analysis
      Hanna Filatova, Tomasz Wołowiec
    • Methodology
      Hanna Filatova, Petr Šuleř
    • Resources
      Hanna Filatova, Petr Šuleř, Tomasz Wołowiec
    • Software
      Hanna Filatova, Tomasz Wołowiec
    • Visualization
      Hanna Filatova
    • Writing – original draft
      Hanna Filatova