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Long-run exclusion and the determination of cointegrating rank: Monte Carlo evidence

机译:长期排除和协整等级的确定:蒙特卡洛证据

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摘要

This note investigates long-run exclusion in a cointegrated vector autoregressive (VAR) model from the viewpoint of finite-sample statistical inference. Monte Carlo experiments show that, in various circumstances, a mis-specified partial VAR model, which is justified by the existence of a long-run excluded variable, can lead to better finite-sample inference for cointegrating rank than a fully specified VAR model. Implications of long-run exclusion for econometric modelling are then considered based on the Monte Carlo study.
机译:本文从有限样本统计推断的角度研究了协整向量自回归(VAR)模型中的长期排除。蒙特卡洛实验表明,在各种情况下,错误指定的部分VAR模型(​​通过长期排除变量的存在是合理的)可以比完全指定的VAR模型导致更好的用于协整秩的有限样本推论。然后根据蒙特卡洛研究,考虑长期排除对计量经济模型的影响。

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