Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/174890
Authors: 
Foroni, Claudia
Marcellino, Massimiliano
Stevanović, Dalibor
Year of Publication: 
2018
Series/Report no.: 
Bundesbank Discussion Paper 02/2018
Abstract: 
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.
Subjects: 
temporal aggregation
MIDAS models
ARMA models
JEL: 
E37
C53
ISBN: 
978-3-95729-425-8
Document Type: 
Working Paper
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