Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US output growth and inflation

Michael Peter Clements and Ana Beatriz Galvão ()

The Warwick Economics Research Paper Series (TWERPS) from University of Warwick, Department of Economics

Abstract: Although many macroeconomic series such as US real output growth are sampled quarterly, many potentially useful predictors are observed at a higher frequency. We look at whether a recently developed mixed data-frequency sampling (MIDAS) approach can improve forecasts of output growth and inflation. We carry out a number of related real-time forecast comparisons using various indicators as explanatory variables. We find that MIDAS model forecasts of output growth are more accurate at horizons less than one quarter using coincident indicators ; that MIDAS models are an effective way of combining information from multiple indicators ; and that the forecast accuracy of the unemployment-rate Phillips curve for inflation is enhanced using the MIDAS approach.

Keywords: Data frequency; multiple predictors; combination; real-time forecasting (search for similar items in EconPapers)
JEL-codes: C51 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-ets, nep-for and nep-mac
Date: 2006
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Persistent link: http://EconPapers.repec.org/RePEc:wrk:warwec:773

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