This paper considers the estimation of dynamic causal effects using a proxy structural vector-autoregressive model with possibly nonstationary regressors. We provide general conditions under which the asymptotic normal approximation remains valid. In this case, the asymptotic variance depends on the persistence property of each series. We further provide a consistent asymptotic covariance matrix estimator that requires neither knowledge of the presistence properties of the variables nor pretests for nonstationarity. The proposed consistent covariance matrix estimator is robust and is easy to implement in practice. When all regressors are indeed stationary, the method becomes the same as the standard procedure.

本文考虑使用具有可能非平稳回归变量的代理结构向量自回归模型来估计动态因果效应。我们提供了渐近正态近似保持有效的一般条件。在这种情况下，渐近方差取决于每个序列的持久性。我们进一步提供了一个一致的渐近协方差矩阵估计器，它既不需要了解变量的存在性，也不需要对非平稳性进行预测试。所提出的一致协方差矩阵估计器是稳健的并且在实践中易于实现。当所有的回归量都确实静止时，该方法与标准程序相同。