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Application of Markov-Switching MIDAS models to nowcasting of GDP and its components

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  • Ivan Stankevich

    (HSE University, Moscow, Russian Federation)

Abstract

The paper investigates the application of Markov-Switching MIDAS (Mixed Data Sampling) models to nowcasting of Russian GDP and its components. Different methods to get the resulting nowcast based on nowcasts under different regimes are proposed: weighted by regime probabilities, most probable regime, and perfectly predicted regime nowcasts. The model obtained is compared with standard econometric nowcasting models. Among all the models tested, Markov-Switching MIDAS model with perfectly predicted regime yields the best results for most of the series analyzed. MS MIDAS models without perfect regime foresight also perform better than standard MIDAS models and MFBVAR models for most of the series analyzed.

Suggested Citation

  • Ivan Stankevich, 2023. "Application of Markov-Switching MIDAS models to nowcasting of GDP and its components," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 70, pages 122-143.
    • Handle: RePEc:ris:apltrx:0474
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    References listed on IDEAS

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    Cited by:

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    2. Natalia Makeeva, 2025. "The impact of the official statistics revision on the accuracy of the Russian macroeconomic indicators nowcasting models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 79, pages 27-49.

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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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