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. …

Carlo simulation. These distributions are wider than those of AR(1) models with normal distributed error terms. As the drift …-out probability. Empirically approaches accounting for seasonality by dummies and using differenced series, as well as forecasting …

models for forecasting, although this proved to be problem- atic due to estimation and identification issues. Hybrid DSGE … the EU debt crisis. The results of this study can be useful in conducting monetary policy analysis and macro-forecasting …

monetary policy analysis and macro-forecasting with the use of advanced Bayesian methods. …

models for forecasting, although this proved to be problematic due to estimation and identi.cation issues. Hybrid DSGE models … results of this study can be useful in conducting monetary policy analysis and macro-forecasting in the Euro area. …

Forecasting based on random intercepts models requires imputation of the individual permanent effects to the simulated … individuals. When these individuals enter the simulation with a history of past outcomes this involves sampling from conditional …