Time-varying Granger causality tests in the energy markets: A study on the DCC-MGARCH Hong test

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...

Full description

Saved in:
Bibliographic Details
Published inEnergy economics Vol. 111; p. 106088
Main Authors Caporin, Massimiliano, Costola, Michele
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.07.2022
Subjects
COVID-19
DCC-GARCH
Granger causality
Hong test
Oil market
COVID-19
Q43
C10
C32
C13
Oil market
Q47
C58
Hong test
DCC-GARCH
Granger causality
Online AccessGet full text

Cover

More Information
Summary: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. •We investigate the DCC-MGARCH Hong test proposed by Lu et al. (2014)•We show that the critical values of the test statistic should be evaluated through simulations•Standard critical values expose the DCC-MGARCH test to Type I errors•Rolling Hong test is a more viable option in the presence of short-lived causality periods•The extended analysis includes also natural gas and the outbreak of the COVID-19 pandemic
ISSN:0140-9883
1873-6181
DOI:10.1016/j.eneco.2022.106088