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Сравнительный Анализ Прогнозных Моделей Российского Ввп В Условиях Наличия Структурных Сдвигов
[Comparative analysis of the forecasting models for Russia’s GDP under the structural breaks]

Author

Listed:
  • Fokin, Nikita
  • Haritonova, Marina

Abstract

In this paper we compare two types of models for forecasting Russia’s GDP under the structural breaks. We consider models that allow breaks in a deterministic trend, in which the dates of structural breaks set exogenously, and more flexible class of models – with a stochastic trend. We show that models with a stochastic trend demonstrate the best result in GDP growth rates forecasting for a year ahead. For shorter horizons, the best forecasting model is the error correction model with a break in the deterministic trend in the GDP level.

Suggested Citation

  • Fokin, Nikita & Haritonova, Marina, 2020. "Сравнительный Анализ Прогнозных Моделей Российского Ввп В Условиях Наличия Структурных Сдвигов [Comparative analysis of the forecasting models for Russia’s GDP under the structural breaks]," MPRA Paper 103412, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:103412
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    References listed on IDEAS

    as
    1. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    2. Alquist, Ron & Kilian, Lutz & Vigfusson, Robert J., 2013. "Forecasting the Price of Oil," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 427-507, Elsevier.
    3. Andrey Polbin, 2021. "Multivariate unobserved component model for an oil-exporting economy: the case of Russia," Applied Economics Letters, Taylor & Francis Journals, vol. 28(8), pages 681-685, May.
    4. Hadi Salehi Esfahani & Kamiar Mohaddes & M. Hashem Pesaran, 2014. "An Empirical Growth Model For Major Oil Exporters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 1-21, January.
    5. International Monetary Fund, 2010. "Estimating Potential Output with a Multivariate Filter," IMF Working Papers 2010/285, International Monetary Fund.
    6. Peter K. Clark, 1987. "The Cyclical Component of U. S. Economic Activity," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(4), pages 797-814.
    7. Fokin, Nikita & Polbin, Andrey, 2019. "A Bivariate Forecasting Model For Russian GDP Under Structural Changes In Monetary Policy and Long-Term Growth," MPRA Paper 95306, University Library of Munich, Germany, revised Apr 2019.
    8. Kuboniwa, Masaaki, 2014. "A comparative analysis of the impact of oil prices on oil-rich emerging economies in the Pacific Rim," Journal of Comparative Economics, Elsevier, vol. 42(2), pages 328-339.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    forecasting; real GDP; structural breaks; long-term growth rate; oil prices; Russian economy;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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