New methods for forecasting inflation, applied to the US
Janine Aron () and
John Muellbauer ()
No 7877, CEPR Discussion Papers from C.E.P.R. Discussion Papers
Models for the twelve-month-ahead US rate of inflation, measured by the chain weighted consumer expenditure deflator, are estimated for 1974-99 and subsequent pseudo out-of-sample forecasting performance is examined. Alternative forecasting approaches for different information sets are compared with benchmark univariate autoregressive models, and substantial out-performance is demonstrated. Three key ingredients to the out-performance are: including equilibrium correction terms in relative prices; introducing non-linearities to proxy state dependence in the inflation process; and replacing the information criterion, commonly used in VARs to select lag length, with a ‘parsimonious longer lags’ (PLL) parameterisation. Forecast pooling or averaging also improves forecast performance.
Keywords: Error Correction Models; Evaluating Forecasts; Model Selection; Multivariate Time Series (search for similar items in EconPapers)
JEL-codes: C22 C51 C52 C53 E31 E37 E52 (search for similar items in EconPapers)
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Journal Article: New Methods for Forecasting Inflation, Applied to the US (2013)
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