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Substantiation Of The Public Debt Sustainability Using Kalman Filter

Author

Listed:
  • Bolos Marcel

    (University of Oradea, Faculty of Economics)

  • Otgon Cristian

    (University of Oradea, Faculty of Economics)

  • Pop Razvan

    (University of Oradea, Faculty of Economics)

Abstract

Global economic conditions have pushed many countries into the delicate situation of contracting foreign loans, leading overnight at alarming volumes of public debt. The need for control and relevant analysis for the sustainability of a country\'s public debt has led us to use the Kalman filter in predicting future values of the key indicators of public debt. The development of a mathematical model of analysis for public services and the budget deficit was necessary to objectively assess the level of the public debt sustainability.Knowing future values of the public debt or the future evolutions of the revenues for the operational budget, offers the posibility of a better handling of the operational expenditures and finally a better balance for the public budget deficit.Using the mathematical mechanism of Kalman filters implemented in Matlab programming language, we generated the estimated future values of the proposed model proposed and key indicators, the results confirming the fears of a low public debt sustainability for Romania.We predicted the future values for the debt service, the public external debt and the operational public revenues,expenditures and deficit, and compared them, to obtain an image of the future evolution and position of the sustainability of the public debt. The work in this paper is an innovative one for the public science sector, and the results obtained are promising for future researches. The values estimated by the Kalman filter are an orientation for the future public policies, and indicate a rather stable but negative evolution for the public debt service. The sustainability of the public debt depends on the decisions taken for the correction of the estimated values, in changing the negative evolution of the budgetary indicators into a positive one.Taking all this into consideration we will conclude that the mathematical mecanism of the Kalman filters offers valuable informations for Government and future research should be oriented to develop it's returned results.

Suggested Citation

  • Bolos Marcel & Otgon Cristian & Pop Razvan, 2011. "Substantiation Of The Public Debt Sustainability Using Kalman Filter," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pages 323-334, December.
    • Handle: RePEc:ora:journl:v:1:y:2011:i:2:p:323-334
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    References listed on IDEAS

    as
    1. Barro, Robert J, 1989. "The Ricardian Approach to Budget Deficits," Journal of Economic Perspectives, American Economic Association, vol. 3(2), pages 37-54, Spring.
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    3. Aleksander Aristovnik, 2008. "Short-Term Determinants of Current Account Deficits: Evidence from Eastern Europe and the Former Soviet Union," Eastern European Economics, Taylor & Francis Journals, vol. 46(1), pages 24-42, January.
    4. Aizenman, Joshua & Sun, Yi, 2010. "Globalization and the sustainability of large current account imbalances: Size matters," Journal of Macroeconomics, Elsevier, vol. 32(1), pages 35-44, March.
    5. Mr. Nigel A Chalk, 1998. "Fiscal Sustainability with Non-Renewable Resources," IMF Working Papers 1998/026, International Monetary Fund.
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    More about this item

    Keywords

    Kalman filter; debt; sustainability; deficit; prediction;
    All these keywords.

    JEL classification:

    • H63 - Public Economics - - National Budget, Deficit, and Debt - - - Debt; Debt Management; Sovereign Debt
    • H68 - Public Economics - - National Budget, Deficit, and Debt - - - Forecasts of Budgets, Deficits, and Debt
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

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