Macroeconomic Forecasting With Mixed-Frequency Data
Michael Clements and
Ana Beatriz GalvÃ£o
Authors registered in the RePEc Author Service: Ana Beatriz Galvão ()
Journal of Business & Economic Statistics, 2008, vol. 26, 546-554
Many macroeconomic series, such as U.S. real output growth, are sampled quarterly, although potentially useful predictors are often observed at a higher frequency. We look at whether a mixed data-frequency sampling (MIDAS) approach can improve forecasts of output growth. The MIDAS specification used in the comparison uses a novel way of including an autoregressive term. We find that the use of monthly data on the current quarter leads to significant improvement in forecasting current and next quarter output growth, and that MIDAS is an effective way to exploit monthly data compared with alternative methods.
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