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TF-MIDAS: a new mixed-frequency model to forecast macroeconomic variables

Nicolás Bonino-Gayoso and Alfredo Garcia-Hiernaux

MPRA Paper from University Library of Munich, Germany

Abstract: This paper tackles the mixed-frequency modeling problem from a new perspective. Instead of drawing upon the common distributed lag polynomial model, we use a transfer function representation to develop a new type of models, named TF-MIDAS. We derive the theoretical TF-MIDAS implied by the high-frequency VARMA family models and as a function of the aggregation scheme (flow and stock). This exact correspondence leads to potential gains in terms of nowcasting and forecasting performance against the current alternatives. A Monte Carlo simulation exercise confirms that TF-MIDAS beats UMIDAS models in terms of out-of-sample nowcasting performance for several data generating high-frequency processes.

Keywords: Mixed-Frequency models; TF-MIDAS; U-MIDAS; Nowcasting; Forecasting (search for similar items in EconPapers)
JEL-codes: C18 C51 C53 (search for similar items in EconPapers)
Date: 2019-03-30
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-ore
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https://mpra.ub.uni-muenchen.de/93366/1/MPRA_paper_93366.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/94475/1/MPRA_paper_93366.pdf revised version (application/pdf)

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