The analysis of causality among oil prices and, in general, between financial and economic variables is of central relevance in applied economic studies. The recent contribution of Lu et al. (2014) proposes a new causality test, the DCC-MGARCH Hong test. We show that the critical values of the test statistic should be evaluated through simulations to avoid potential Type I errors. We also note that rolling Hong tests represent a more viable solution in the presence of short-lived causality periods.

中文翻译：

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能源市场中的时变格兰杰因果检验：关于 D​​CC-MGARCH Hong 检验的研究

石油价格之间的因果关系分析，一般来说，金融和经济变量之间的因果关系分析在应用经济学研究中具有核心意义。Lu 等人最近的贡献。(2014) 提出了一种新的因果关系检验，即 DCC-MGARCH Hong 检验。我们表明，应通过模拟评估测试统计量的临界值，以避免潜在的 I 类错误。我们还注意到，在存在短暂因果期的情况下，滚动 Hong 检验代表了一种更可行的解决方案。