Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US output growth and inflation
Michael Clements and
Ana Galvão ()
The Warwick Economics Research Paper Series (TWERPS) from University of Warwick, Department of Economics
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
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Working Paper: Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US output growth and inflation (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:wrk:warwec:773
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