Arbeitspapier
Mixed frequency models with MA components
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 UMIDAS models (MIDAS-ARMA 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.
- Sprache
-
Englisch
- Erschienen in
-
Series: Document de travail ; No. 2017-10
- Klassifikation
-
Wirtschaft
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
Forecasting Models; Simulation Methods
- Thema
-
Temporal aggregation
MIDAS models
ARMA models
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Foroni, Claudia
Marcellino, Massimiliano
Stevanovic, Dalibor
- Ereignis
-
Veröffentlichung
- (wer)
-
Université du Québec à Montréal, École des sciences de la gestion (ESG UQAM), Département des sciences économiques
- (wo)
-
Montréal
- (wann)
-
2017
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Foroni, Claudia
- Marcellino, Massimiliano
- Stevanovic, Dalibor
- Université du Québec à Montréal, École des sciences de la gestion (ESG UQAM), Département des sciences économiques
Entstanden
- 2017
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