A Generalized Method of Moments Estimator for Structural Vector Autoregressions Based on Higher Moments
提出一种利用数据高阶矩信息识别和估计结构向量自回归模型的广义矩方法，无需额外约束即可分析变量间的同期互动关系，并应用于经济活动、石油和股票价格的分析。
I propose a generalized method of moments estimator for structural vector autoregressions with independent and non-Gaussian shocks. The shocks are identified by exploiting information contained in higher moments of the data. Extending the standard identification approach, which relies on the covariance, to the coskewness and cokurtosis allows the simultaneous interaction to be identified and estimated without any further restrictions. I analyze the finite sample properties of the estimator and apply it to illustrate the simultaneous interaction between economic activity, oil, and stock prices. Supplementary materials for this article are available online.