Time-Varying Granger Causality Tests for Applications in Global Crude Oil Markets: A Study on the DCC-MGARCH Hong Test

M. Caporin, Michele Costola
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Abstract

Analysing causality among oil prices and, in general, among financial and economic variables is of central relevance in applied economics studies. The recent contribution of Lu et al. (2014) proposes a novel test for causality— the DCC-MGARCH Hong test. We show that the critical values of the test statistic must be evaluated through simulations, thereby challenging the evidence in papers adopting the DCC-MGARCH Hong test. We also note that rolling Hong tests represent a more viable solution in the presence of short-lived causality periods.
时变格兰杰因果检验在全球原油市场中的应用:DCC-MGARCH Hong检验的研究
在应用经济学研究中,分析油价之间的因果关系,以及总体上分析金融和经济变量之间的因果关系,具有核心意义。Lu et al.(2014)最近的贡献提出了一种新的因果关系检验——DCC-MGARCH Hong检验。我们表明检验统计量的临界值必须通过模拟来评估,从而挑战采用DCC-MGARCH Hong检验的论文中的证据。我们还注意到,滚动Hong检验在存在短暂因果期的情况下是一种更可行的解决方案。
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