Bayesian VARs with Large Panels
评估了不同规模贝叶斯向量自回归模型的预测和结构分析表现，发现基于上百个变量的模型在预测和货币政策冲击分析中表现良好。
This paper assesses the performance of Bayesian Vector Autoregression (BVAR) for models of different size. We consider standard specifications in the macroeconomic literature based on, respectively, three and eight variables and compare results with those obtained by larger models containing twenty or over one hundred conjunctural indicators. We first study forecasting accuracy and then perform a structural exercise focused on the effect of a monetary policy shock on the macroeconomy. Results show that BVARs estimated on the basis of hundred variables perform well in forecasting and are suitable for structural analysis.