Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/62824 
Year of Publication: 
2006
Series/Report no.: 
Working Paper No. 567
Publisher: 
Queen Mary University of London, Department of Economics, London
Abstract: 
Recently, there has been increasing interest in forecasting methods that utilise large datasets. 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.
Subjects: 
Forecasting, Inflation, Bayesian model averaging, Akaike criterion, Forecast combining
JEL: 
C11
C15
C53
Document Type: 
Working Paper

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