Heteroskedastic Structural Vector Autoregressions Identified via Long‐Run Restrictions
研究了在向量自回归模型中，如何利用变量间的协整结构提供的长期限制来检验异方差识别假设是否成立，并用美国数据发现1986年后基本面冲击对股价的影响更大。
ABSTRACT A central assumption for identifying structural shocks in vector autoregressive (VAR) models via heteroskedasticity is the time‐invariance of the impact effects of the shocks. It is shown how that assumption can be tested when long‐run restrictions based on the cointegration structure of the variables are available for identifying structural shocks. The importance of performing such tests is illustrated by investigating the impact of fundamental shocks on stock prices in the U.S. It is found that fundamental shocks post‐1986 have become more important than in the pre‐1986 period.