Vector Autoregressions and Reality
质疑无约束向量自回归中方差分解和脉冲响应函数的统计显著性，提出用正态近似和自助重采样两种方法计算置信区间，并用Sims的例子说明其重要性。
This article questions the statistical significance of variance decompositions and impulse response functions for unrestricted vector autoregressions. It suggests that previous authors have failed to provide confidence intervals for variance decompositions and impulse response functions. Two methods of computing such confidence intervals are developed: first, using a normal approximation; second, using bootstrapped resampling. An example from Sims's work is used to illustrate the importance of computing these confidence intervals. In this example, the 95% confidence intervals for variance decompositions span up to 66 percentage points at the usual forecasting horizon.