Choosing Between Different Time‐Varying Volatility Models for Structural Vector Autoregressive Analysis
研究了在结构向量自回归分析中，如何通过信息准则和异方差检验来选择时变波动模型，发现使用选择准则能显著降低脉冲响应估计的均方误差，而异方差检验仅能判断波动是否存在。
Abstract The performance of information criteria and tests for residual heteroscedasticity for choosing between different models for time‐varying volatility in the context of structural vector autoregressive analysis is investigated. Although it can be difficult to find the true volatility model with the selection criteria, using them is recommended because they can reduce the mean squared error of impulse response estimates substantially relative to a model that is chosen arbitrarily based on the personal preferences of a researcher. Heteroscedasticity tests are found to be useful tools for deciding whether time‐varying volatility is present but do not discriminate well between different types of volatility changes. The selection methods are illustrated by specifying a model for the global market for crude oil.