Quantile Granger causality in the presence of instability

IF 9.9 3区 经济学 Q1 ECONOMICS
Alexander Mayer , Dominik Wied , Victor Troster
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引用次数: 0

Abstract

We propose a new framework for assessing Granger causality in quantiles in unstable environments, for a fixed quantile or over a continuum of quantile levels. Our proposed test statistics are consistent against fixed alternatives, they have nontrivial power against local alternatives, and they are pivotal in certain important special cases. In addition, we show the validity of a bootstrap procedure when asymptotic distributions depend on nuisance parameters. Monte Carlo simulations reveal that the proposed test statistics have correct empirical size and high power, even in absence of structural breaks. Moreover, a procedure providing additional insight into the timing of Granger causal regimes based on our new tests is proposed. Finally, an empirical application in energy economics highlights the applicability of our method as the new tests provide stronger evidence of Granger causality.
存在不稳定性的量子格兰杰因果关系
我们提出了一个新的框架来评估不稳定环境中分位数的格兰杰因果关系,用于固定分位数或连续的分位数水平。我们提出的测试统计对于固定的替代是一致的,它们对于局部的替代具有重要的力量,并且它们在某些重要的特殊情况下是关键的。此外,我们还证明了当渐近分布依赖于干扰参数时,一个自举过程的有效性。蒙特卡罗模拟表明,即使在没有结构断裂的情况下,所提出的测试统计量也具有正确的经验大小和高功率。此外,一个程序提供额外的洞察格兰杰因果制度的时间基于我们的新测试提出。最后,在能源经济学中的实证应用突出了我们方法的适用性,因为新的检验提供了更有力的格兰杰因果关系证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Econometrics
Journal of Econometrics 社会科学-数学跨学科应用
CiteScore
8.60
自引率
1.60%
发文量
220
审稿时长
3-8 weeks
期刊介绍: The Journal of Econometrics serves as an outlet for important, high quality, new research in both theoretical and applied econometrics. The scope of the Journal includes papers dealing with identification, estimation, testing, decision, and prediction issues encountered in economic research. Classical Bayesian statistics, and machine learning methods, are decidedly within the range of the Journal''s interests. The Annals of Econometrics is a supplement to the Journal of Econometrics.
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