Evaluation of mixed frequency approaches for tracking near-term economic developments in North Macedonia
Gani Ramadani (),
Magdalena Petrovska () and
Vesna Bucevska ()
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Magdalena Petrovska: National Bank of the Republic of North Macedonia
Vesna Bucevska: Faculty of Economics, Ss Cyril and Methodius University
No 2021-03, Working Papers from National Bank of the Republic of North Macedonia
Aggregate demand forecasting, also known as nowcasting when it applies to current quarter assessment, is of notable interest to policy makers. This paper concentrates on the empirical methods dealing with mixed-frequency data. In particular, it focuses on the MIDAS approach and its later extension, the Bayesian MF-VAR. The two strategies are evaluated in terms of their accuracy to nowcast Macedonian GDP growth, using same monthly frequency data set. The results of this study indicate that the MIDAS regressions demonstrate comparable forecasting performance to that of MF-VAR model. Moreover, it is interesting to note that the two approaches are reciprocal, since in general, their combined forecast demonstrates clear superiority in predicting business cycle turning points. Additionally, the MF-VAR model showed higher precision in times of increased uncertainty.
Keywords: MF-VAR; Bayesian estimation; MIDAS; Forecast pooling; Forecast evaluation (search for similar items in EconPapers)
JEL-codes: C53 E37 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-mac and nep-tra
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Persistent link: https://EconPapers.repec.org/RePEc:mae:wpaper:2021-03
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