Forecasting using predictive likelihood model averaging

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.

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Year of publication:	2006
Authors:	Kapetanios, George ; Labhard, Vincent ; Price, Simon
Publisher:	London : Queen Mary University of London, Department of Economics
Subject:	Forecasting, Inflation, Bayesian model averaging, Akaike criterion, Forecast combining

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Series:	Working Paper ; 567
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	517657643 [GVK] hdl:10419/62824 [Handle]
Classification:	C11 - Bayesian Analysis ; C15 - Statistical Simulation Methods; Monte Carlo Methods ; C53 - Forecasting and Other Model Applications
Source:	EconStor

Persistent link: https://www.econbiz.de/10010284123