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Forecasting using predictive likelihood model averaging

Authors
Publisher
Elsevier B.V.
Publication Date
Volume
91
Issue
3
Identifiers
DOI: 10.1016/j.econlet.2005.12.017
Keywords
  • Forecasting
  • Inflation
  • Bayesian Model Averaging
  • Akaike Criterion
  • Forecast Combining
Disciplines
  • Mathematics

Abstract

Abstract Recently, there has been increasing interest in forecasting methods that utilise large data sets. We explore the possibility of forecasting with model averaging using the out-of-sample forecasting performance of various models in a frequentist setting, using the predictive likelihood. We apply our method to forecasting UK inflation and find that the new method performs well; in some respects it outperforms other averaging methods.

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