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.
Time-varying Granger causality tests in the energy markets: A study on the DCC-MGARCH Hong test
Caporin M.
;
2022
Abstract
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.
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