Forecasting and turning point predictions in a Bayesian panel VAR model
提出在面板贝叶斯VAR模型中进行变量预测和转折点预测的方法，模型考虑了截面依赖和参数时变，并提供了层次先验和明尼苏达型先验下的后验分布公式，最后以G-7国家产出增长率预测为例展示了方法。
We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a flexible model that accounts for both interdependencies in the cross section and time variations in the parameters. Posterior distributions for the parameters are obtained for hierarchical and for Minnesota-type priors. Formulas for multistep, multiunit 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.