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英文文献：Improved inference on cointegrating vectors in the presence of a near unit root using adjusted quantiles-改进的推论协整向量存在近单位根使用调整分位数
英文文献作者：Massimo Franchi,S?ren Johansen
英文文献摘要：
It is well known that inference on the cointegrating relations in a vector autoregression (CVAR) is difficult in the presence of a near unit root. The test for a given cointegration vector can have rejection probabilities under the null, which vary from the nominal size to more than 90%. This paper formulates a CVAR model allowing for many near unit roots and analyses the asymptotic properties of the Gaussian maximum likelihood estimator. Then a critical value adjustment suggested by McCloskey for the test on the cointegrating relations is implemented, and it is found by simulation that it eliminates size distortions and has reasonable power for moderate values of the near unit root parameter. The findings are illustrated with an analysis of a number of different bivariate DGPs.
众所周知，矢量自回归(CVAR)中协整关系的推断在近单位根存在的情况下是困难的。对给定协整向量的测试可以在null下有拒绝概率，从名义大小变化到超过90%。本文给出了一个允许许多近单位根的CVAR模型，并分析了高斯极大似然估计的渐近性质。然后采用McCloskey建议的临界值调整方法对协整关系进行检验，仿真结果表明，该方法消除了尺寸畸变，对近单位根参数的中等取值有较好的效果。研究结果通过对一些不同的双变量DGPs的分析来说明。
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