Fully Modified Vector Autoregressive Inference in Partially Nonstationary Models
Fully Modified Vector Autoregressive Inference in Partially Nonstationary Models
复制标题
部分非平稳模型中的完全修改向量自回归推理
DOI：
10.1080/01621459.1998.10473730
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发表时间：
1998
影响因子：
3.7
通讯作者：
Carmela Quintos
中科院分区：
文献类型：
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作者：
Carmela Quintos
摘要秩的似然比（LR）检验是检验多变量时间序列间协整关系个数的常用方法。部分非平稳模型中LR检验的分布是非标准的，并且在存在非iid误差和误指定滞后的情况下包含讨厌的参数。相比之下，我表明，在较少的限制性假设的错误，完全修改（FM）的向量自回归（VAR）秩检验有一个卡方分布的空协整，但退化的空无协整，不像它的LR对应，这是很好地定义为两个空值。事实证明，通过外生I（0）变量增加VAR可以解决退化问题。该方法也可用于检验格兰杰因果关系，实际上是Toda-Yamamoto用附加滞后I（1）变量扩充VAR方法的推广。不像LR测试的排名或户田山本的因果关系的测试，FM测试不需要…
Abstract The likelihood ratio (LR) test for ranks is commonly used to test for the number of cointegrating relationships among multivariate time series. The distribution of the LR test in partially nonstationary models is nonstandard and contains nuisance parameters in the presence of non-iid errors and misspecified lags. In contrast, I show that under less-restrictive assumptions on the errors, the fully modified (FM) vector autoregressive (VAR) rank test has a chi-squared distribution for the null of cointegration but is degenerate for the null of no cointegration, unlike its LR counterpart, which is well defined for both nulls. It turns out that augmenting the VAR by an exogenous I(0) variable solves the degeneracy problem. The procedure can also be applied to testing for Granger causality and is in fact a generalization of Toda-Yamamoto's procedure of augmenting the VAR with additional lagged I(1) variables. Unlike the LR test for ranks or Toda-Yamamoto's test for causality, the FM tests do not requir...
影响因子：
6.1
作者：
PERRON, P
通讯作者：
PERRON, P