Structural Vector Autoregressions With Nonnormal Residuals
指出在结构向量自回归模型中，当识别约束不足时，可利用混合正态分布等分布假设来识别结构冲击，并用美国和欧洲利率数据验证了该方法。
Abstract In structural vector autoregressive (SVAR) modeling, sometimes the identifying restrictions are insufficient for a unique specification of all shocks. In this paper it is pointed out that specific distributional assumptions can help in identifying the structural shocks. In particular, a mixture of normal distributions is considered as a possible model that can be used in this context. Our model setup enables us to test restrictions which are just-identifying in a standard SVAR framework. The results are illustrated using a U.S. macro data set and a system of U.S. and European interest rates. Keywords: : CointegrationImpulse responsesMixed normal distributionVector autoregressive processVector error correction model