Time series estimation of the dynamic effects of disaster-type shocks
Time series estimation of the dynamic effects of disaster-type shocks
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DOI：
10.1016/j.jeconom.2022.02.009
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发表时间：
2021-07
影响因子：
6.3
通讯作者：
R. Davis;Serena Ng
中科院分区：
文献类型：
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作者：
R. Davis;Serena Ng
本文在原始冲击相互独立的假设下，给出了svar的三个结果。首先，提出了一个将具有无限方差的灾害型变量纳入SVAR的框架。我们证明了SVAR的最小二乘估计是一致的，但具有非标准渐近性。其次，将灾害冲击识别为峰度最大的分量。利用对无穷方差具有鲁棒性的估计器恢复相互独立的分量。第三，提出了对Choleski分解预白化残差的独立性检验，以检验对SVAR施加的限制。该测试可以应用于数据是否有肥尾或细尾，以及是否准确识别模型。我们考虑了三个申请。首先，独立性检验用于阐明关于不确定性在经济波动中的作用的相互矛盾的证据。在第二种情况下，灾害冲击显示出主要由反馈动态产生的短期经济影响。第三个研究使用该框架研究新冠疫情后经济冲击的动态影响。
This paper provides three results for SVARs under the assumption that the primitive shocks are mutually independent. First, a framework is proposed to accommodate a disaster-type variable with infinite variance into a SVAR. We show that the least squares estimates of the SVAR are consistent but have non-standard asymptotics. Second, the disaster shock is identified as the component with the largest kurtosis. An estimator that is robust to infinite variance is used to recover the mutually independent components. Third, an independence test on the residuals pre-whitened by the Choleski decomposition is proposed to test the restrictions imposed on a SVAR. The test can be applied whether the data have fat or thin tails, and to over as well as exactly identified models. Three applications are considered. In the first, the independence test is used to shed light on the conflicting evidence regarding the role of uncertainty in economic fluctuations. In the second, disaster shocks are shown to have short term economic impact arising mostly from feedback dynamics. The third uses the framework to study the dynamic effects of economic shocks post-covid.