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Finite Sample Modifications of the Granger Non Causality Test in Cointegrated Vector Autoregressions

机译:协整矢量自回归中的Granger非因果关系检验的有限样本修改

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摘要

This article deals with the Granger non causality test in cointegrated vector autoregressive processes. We propose a new testing procedure that yields an asymptotically standard distribution and performs well in small samples by combining the standard Wald test and the generalized inverse procedure. We also propose a few simple modifications to the test statistics in order to help our procedure perform better in finite samples. Monte Carlo simulations show that our procedure works better than the conventional approach.
机译:本文讨论了协整向量自回归过程中的Granger非因果关系检验。通过结合标准Wald检验和广义逆过程,我们提出了一种新的检验程序,该程序产生渐近的标准分布并在小样本中表现良好。我们还建议对测试统计信息进行一些简单的修改,以帮助我们的程序在有限的样本中更好地执行。蒙特卡洛模拟显示,我们的程序比常规方法效果更好。

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