论文标题
大型var的协整
Cointegration in large VARs
论文作者
论文摘要
本文分析了矢量自回旋过程中的协整（VAR），以均匀的坐标数量，$ n $和时间段的数量（$ t $）均大且订单相同时。我们提出了一种基于约翰森似然比测试的修改来检查订单$ 1 $的订单$ 1 $的方法。我们的程序比原始的Johansen测试及其有限的样本更正的优点是，我们的测试不会遭受过度拒绝的痛苦。这是通过针对矩阵特征值的新型渐近定理来实现的，该测试统计数据是按比例增长的$ n $和$ t $的制度。我们的理论发现得到了蒙特卡洛模拟和经验例证的支持。此外，我们发现了与方差多变量分析（MANOVA）的令人惊讶的联系，并解释了为什么它出现。
The paper analyses cointegration in vector autoregressive processes (VARs) for the cases when both the number of coordinates, $N$, and the number of time periods, $T$, are large and of the same order. We propose a way to examine a VAR of order $1$ for the presence of cointegration based on a modification of the Johansen likelihood ratio test. The advantage of our procedure over the original Johansen test and its finite sample corrections is that our test does not suffer from over-rejection. This is achieved through novel asymptotic theorems for eigenvalues of matrices in the test statistic in the regime of proportionally growing $N$ and $T$. Our theoretical findings are supported by Monte Carlo simulations and an empirical illustration. Moreover, we find a surprising connection with multivariate analysis of variance (MANOVA) and explain why it emerges.
