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

Ivan Stankevich

Applied Econometrics, 2023, vol. 70, 122-143

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.

Keywords: nowcasting; Russian GDP; forecasting; Markov-Switching models; MIDAS models. (search for similar items in EconPapers)
JEL-codes: C53 E37 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:ris:apltrx:0474

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