Large Bayesian vector auto regressions
证明，通过贝叶斯收缩方法处理大型向量自回归模型，能提升小型货币VAR的预测表现，并产生可信的脉冲响应，适用于结构分析。
Abstract This paper shows that vector auto regression (VAR) with Bayesian shrinkage is an appropriate tool for large dynamic models. We build on the results of De Mol and co‐workers (2008) and show that, when the degree of shrinkage is set in relation to the cross‐sectional dimension, the forecasting performance of small monetary VARs can be improved by adding additional macroeconomic variables and sectoral information. In addition, we show that large VARs with shrinkage produce credible impulse responses and are suitable for structural analysis. Copyright © 2009 John Wiley & Sons, Ltd.