DP7877 New methods for forecasting inflation, applied to the US.

Author(s): Janine Aron, John Muellbauer
Publication Date: June 2010
Keyword(s): Error Correction Models, Evaluating Forecasts, Model Selection, Multivariate Time Series
JEL(s): C22, C51, C52, C53, E31, E37, E52
Programme Areas: International Macroeconomics
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=7877

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.