Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US output growth and inflation
Michael Clements and
Ana Galvão ()
No 269743, Economic Research Papers 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: Agricultural and Food Policy; Research Methods/ Statistical Methods (search for similar items in EconPapers)
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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:ags:uwarer:269743
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