Finite Sample Performance of Likelihood Ratio Tests for Cointegrating Ranks in Vector Autoregressions
Finite Sample Performance of Likelihood Ratio Tests for Cointegrating Ranks in Vector Autoregressions
复制标题
向量自回归中协整等级似然比检验的有限样本性能
DOI：
10.1017/s0266466600009956
复制
发表时间：
1995
影响因子：
0.8
通讯作者：
Hiro Y. Toda
中科院分区：
文献类型：
--
作者：
Hiro Y. Toda
本文通过蒙特卡罗模拟研究了 Johansen (1991, Econometrica 59, 1551–1580) 提出的协整等级似然比检验的有限样本属性。我们将模型转化为规范形式，以便在不失一般性的情况下很好地控制实验，然后进行全面的仿真研究。正如预期的那样，测试性能对过程的平稳根值非常敏感。我们还发现，测试性能在很大程度上取决于驱动过程的平稳和非平稳组件的创新之间的相关性。我们得出的结论是，100 个观测值不足以确保影响检验统计量分布的干扰参数值一致的合理良好性能。
This paper investigates through Monte Carlo simulation the finite sample properties of likelihood ratio tests for cointegrating ranks that were proposed by Johansen (1991, Econometrica 59, 1551–1580). We transform the model into a canonical form so that the experiment is well controlled without loss of generality and then conduct a comprehensive simulation study. As expected, the test performance is very sensitive to the value of the stationary root(s) of the process. We also find that the test performance depends crucially on the correlation between the innovations that drive the stationary and the nonstationary components of the process. We conclude that 100 observations are not sufficient to ensure reasonably good performance uniformly over the values of the nuisance parameters that affect the distributions of the test statistics.