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Time series forecasting under structural breaks

Author

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  • Skrobotov, Anton

    (RANEPA, Moscow, Russian Federation;)

Abstract

In this paper, we overview the forecasting methods in the presence of structural breaks. Methods for selecting a forecast window that includes the break date, weighted average methods of pre- and post-break estimators, and averaging-based methods are discussed. The considered methods are compared in terms of predictive power using Russian macroeconomic time series. The results demonstrate the superiority of forecasts that take into account the presence of break.

Suggested Citation

  • Skrobotov, Anton, 2024. "Time series forecasting under structural breaks," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 76, pages 120-139.
    • Handle: RePEc:ris:apltrx:0512
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    References listed on IDEAS

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    2. 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.
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    8. Tae‐Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting Under Structural Breaks Using Improved Weighted Estimation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1485-1501, December.
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    11. Skrobotov, Anton, 2021. "Structural breaks in cointegration models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 63, pages 117-141.
    12. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
    13. Stanislav Anatolyev & Victor Kitov, 2007. "Using All Observations when Forecasting under Structural Breaks," Finnish Economic Papers, Finnish Economic Association, vol. 20(2), pages 166-176, Autumn.
    14. Skrobotov, Anton (Скроботов, Антон), 2021. "Structural breaks in cointegration models [Структурные Сдвиги В Моделях Коинтеграции]," Working Papers w20220130, Russian Presidential Academy of National Economy and Public Administration.
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    More about this item

    Keywords

    time series; structural breaks; forecasting; optimal forecast; weighted estimator;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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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