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

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  • Caporin, Massimiliano
  • Costola, Michele

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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  • Caporin, Massimiliano & Costola, Michele, 2022. "Time-varying Granger causality tests in the energy markets: A study on the DCC-MGARCH Hong test," Energy Economics, Elsevier, vol. 111(C).
    • Handle: RePEc:eee:eneeco:v:111:y:2022:i:c:s0140988322002523
    DOI: 10.1016/j.eneco.2022.106088
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    Cited by:

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    More about this item

    Keywords

    Granger causality; Hong test; DCC-GARCH; Oil market; COVID-19;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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