Mixed frequency models with MA components

Arbeitspapier

Temporal aggregation in general introduces a moving average (MA) component in the aggregated model. A similar feature emerges when not all but only a few variables are aggregated, which generates a mixed frequency model. The MA component is generally neglected, likely to preserve the possibility of OLS estimation, but the consequences have never been properly studied in the mixed frequency context. In this paper, we show, analytically, in Monte Carlo simulations and in a forecasting application on U.S. macroeconomic variables, the relevance of considering the MA component in mixed-frequency MIDAS and Unrestricted-MIDAS models (MIDASARMA and UMIDAS-ARMA). Specifically, the simulation results indicate that the short-term forecasting performance of MIDAS-ARMA and UMIDAS-ARMA is better than that of, respectively, MIDAS and UMIDAS. The empirical applications on nowcasting U.S. GDP growth, investment growth and GDP deflator inflation confirm this ranking. Moreover, in both simulation and empirical results, MIDAS-ARMA is better than UMIDAS-ARMA.

Angaben zum Objekt

• ISBN: 978-3-95729-425-8
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Bundesbank Discussion Paper ; No. 02/2018

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications ; Forecasting Models; Simulation Methods
• Thema: temporal aggregation ; MIDAS models ; ARMA models

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Foroni, Claudia ; Marcellino, Massimiliano ; Stevanović, Dalibor
• Ereignis: Veröffentlichung
• (wer): Deutsche Bundesbank
• (wo): Frankfurt a. M.
• (wann): 2018

Weitere Informationen

• Handle: http://hdl.handle.net/10419/174890
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ