This paper provides a novel approach to forecasting time series subject to discrete structural breaks. We propose a …

We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a …. Formulas for multistep, multiunit point and average forecasts are provided. An application to the problem of forecasting the … forecasting methods is also provided. …

forecasting procedure, based on component models, improves the forecasting accuracy of traditional methods. Component models … Monte Carlo out-of-sample experiment reveals that component models improve the forecasting accuracy of traditional methods …

In recent years there has been increasing interest in forecasting methods that utilise large datasets, driven partly by … weights. We consider the use of model averaging in forecasting UK inflation with a large dataset from this perspective. We …

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 …

, simulated annealing and genetic algorithms are considered. Both a Monte Carlo study and an empirical forecasting application to …

We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a … point and average forecasts are provided. An application to the problem of forecasting the growth rate of output and of … predicting turning points in the G-7 illustrates the approach. A comparison with alternative forecasting methods is also provided. …

variety of non-Gaussian alternatives including GARCH innovations. Our results are useful in many areas of forecasting and …

In Bayesian analysis of VAR-models, and especially in forecasting applications, the Minnesota prior of Litterman is … report on the forecasting performance of the different prior distributions considered in the paper. …