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Title: Mixed frequency models with MA components Authors:  Claudia Foroni - Deutsche Bundesbank (Germany) [presenting]
Massimiliano Marcellino - Bocconi University (Italy)
Dalibor Stevanovic - Universite du Quebec a Montreal (Canada)
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. 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, and the empirical applications confirm this ranking.