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Forecasting US inflation by Bayesian model averaging

✍ Scribed by Jonathan H. Wright

Publisher
John Wiley and Sons
Year
2009
Tongue
English
Weight
372 KB
Volume
28
Category
Article
ISSN
0277-6693

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✦ Synopsis

Abstract

Recent empirical work has considered the prediction of inflation by combining the information in a large number of time series. One such method that has been found to give consistently good results consists of simple equal‐weighted averaging of the forecasts from a large number of different models, each of which is a linear regression relating inflation to a single predictor and a lagged dependent variable. In this paper, I consider using Bayesian model averaging for pseudo out‐of‐sample prediction of US inflation, and find that it generally gives more accurate forecasts than simple equal‐weighted averaging. This superior performance is consistent across subsamples and a number of inflation measures. Copyright © 2008 John Wiley & Sons, Ltd.

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