Bootstrap determination of the co-integration rank in VAR models
Bootstrap determination of the co-integration rank in VAR models
复制标题
VAR 模型中协整等级的 Bootstrap 确定
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
A. Taylor
中科院分区：
文献类型：
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作者：
Giuseppe Cavaliere;Anders Rahbek;A. Taylor
本文讨论了Johansen（1996）的似然比[LR]协整秩检验的一致自举实现和相关的顺序秩确定过程。利用在降秩零假设下得到的底层VAR模型的受限参数估计构造自举样本。提供了一个完整的渐近理论，它表明，与Swensen（2006）中的bootstrap过程不同，其中使用了VAR模型的无限制和受限估计的组合，所得的bootstrap数据为I(1)并且满足零协整秩，而不管真实秩。这确保了自举LR检验的渐近大小是正确的，并且自举序列过程选择小于真实秩的秩的概率收敛于零。蒙特卡罗证据表明，我们的引导程序在实践中工作得很好。
This paper discusses a consistent bootstrap implementation of the likelihood ratio [LR] co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The bootstrap samples are constructed using the restricted parameter estimates of the underlying VAR model which obtain under the reduced rank null hypothesis. A full asymptotic theory is provided which shows that, unlike the bootstrap procedure in Swensen (2006) where a combination of unrestricted and restricted estimates from the VAR model is used, the resulting bootstrap data are I(1) and satisfy the null co-integration rank, regardless of the true rank. This ensures that the bootstrap LR test is asymptotically correctly sized and that the probability that the bootstrap sequential procedure selects a rank smaller than the true rank converges to zero. Monte Carlo evidence suggests that our bootstrap procedures work very well in practice.