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  • 标题:Government debt forecasting based on the Arima model
  • 本地全文:下载
  • 作者:Fedir Zhuravka ; Hanna Filatova ; John O. Aiyedogbon
  • 期刊名称:Public and Municipal Finance
  • 印刷版ISSN:2222-1867
  • 电子版ISSN:2222-1875
  • 出版年度:2020
  • 卷号:8
  • 期号:1
  • 页码:120-127
  • DOI:10.21511/pmf.08(1).2019.11
  • 出版社:LLC "CPC "Business Perspectives"
  • 摘要:The paper explores theoretical and practical aspects of forecasting the government debt in Ukraine. A visual analysis of changes in the amount of government debt was conducted, which has made it possible to conclude about the deepening of the debt crisis in the country. The autoregressive integrated moving average (ARIMA) is considered as the basic forecasting model; besides, the model work and its diagnostics are estimated. The EViews software package illustrates the procedure for forecasting the Ukrainian government debt for the ARIMA model: the series for stationarity was tested, the time series of monthly government debt was converted into stationary by making a number of transformations and determining model parameters; as a result, the most optimal specification for the ARIMA model was chosen.Based on the simulated time series, it is concluded that ARIMA tools can be used to predict the government debt values.
  • 关键词:debt; debt sustainability; modeling; time series analysis; Ukraine
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