On the Distribution of Likelihood Ratio Test Statistics for Cointegration Rank
分析了高斯向量自回归模型中协整秩减少假设的似然比检验，发现通常的渐近分布存在较大规模扭曲，并利用局部渐近理论改进了分布近似。
Abstract This paper analyses the likelihood ratio test for the hypothesis of reduced cointegration rank in a Gaussian vector autoregressive model. The usual asymptotic distribution typically gives rather large size distortions. This is explained by the fact that the asymptotic distribution of the likelihood ratio test statistic varies across the parameter space. A much improved distribution approximation can be obtained using local asymptotic theory. The idea is discussed for some low dimensional examples.