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首页> 外文期刊>Journal of Econometrics >Analytical Evaluation of the Power of Tests for the Absence of Cointegration.
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Analytical Evaluation of the Power of Tests for the Absence of Cointegration.

机译:没有协整的检验能力的分析评估。

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This paper proposes a theoretical explanation for the common empirical results in which different tests for cointegration give different answers. Using local to unity parametrization, this paper analytically computes the power of four tests for the null of no cointegration: The ADF test on the residuals of the cointegration regression, Johansen's maximum eigenvalue test, the t-test on the Error Correction (EC) term, and Boswijk (1994) Wald test. The test statistics are shown to converge under a local alternative to random variables whose distributions are functions of Brownian Motions and Ornstein-Uhlenbeck processes and of a single nuisance parameter. The nuisance parameter is determined by the correlation at frequency zero of the errors in the cointegration relation with the shocks of the right-hand variables. I show that, when this correlation is high, system approaches, like the Johansen maximum eigenvalue or tests of the EC model, can exploit this correlation and significantly outperform single equation tests. Many of the varying results from applying different tests can be attributed to different values of this nuisance parameter.
机译:本文针对常见的经验结果提出了理论解释,其中不同的协整检验给出了不同的答案。本文使用局部到统一的参数化方法,分析了无协整零值的四种检验的功效:协整回归残差的ADF检验,Johansen最大特征值检验,误差校正(EC)项的t检验和Boswijk(1994)Wald检验。测试统计数据显示在局部变量下收敛于随机变量,该随机变量的分布是布朗运动和Ornstein-Uhlenbeck过程的函数以及单个扰动参数。干扰参数由协整关系中的误差在零频率处与右手变量的冲击的相关性确定。我证明了,当这种相关性很高时,系统方法(例如Johansen最大特征值或EC模型的测试)可以利用这种相关性,并且明显优于单方程测试。来自应用不同测试的许多不同结果可以归因于此讨厌参数的不同值。

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