IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v288y2024ics0360544223031535.html
   My bibliography  Save this article

Dynamic nonlinear effects of geopolitical risks on commodities: Fresh evidence from quantile methods

Author

Listed:
  • Mo, Bin
  • Nie, He
  • Zhao, Rongjie

Abstract

This paper examines the dynamic nonlinear effects of the Geopolitical Risk (GPR) on commodities using quantile methods. Our rolling window quantile estimations show that non-energy sectors, such as food and beverage, are not easily influenced by geopolitical events, while energy sectors can be easily affected. The recent COVID-19 pandemic has no strong effects on these relationships. Quantile-on-quantile results demonstrate that the magnitude of the co-movement of GPR and non-energy sectors is very small, whereas the magnitude of the co-movement of GPR associated with the energy sector is larger. Additionally, during bullish markets, GPR can exert positive effects on commodity markets. However, under other market conditions, negative effects are apparent. Finally, we use a nonparametric causality-in-quantiles test to provide fresh evidence of the explanatory power of GPR on commodity markets.

Suggested Citation

  • Mo, Bin & Nie, He & Zhao, Rongjie, 2024. "Dynamic nonlinear effects of geopolitical risks on commodities: Fresh evidence from quantile methods," Energy, Elsevier, vol. 288(C).
    • Handle: RePEc:eee:energy:v:288:y:2024:i:c:s0360544223031535
    DOI: 10.1016/j.energy.2023.129759
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223031535
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.129759?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Geopolitical risks; Commodity; Quantile-on-quantile; Causality-in-quantiles;
    All these keywords.

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:288:y:2024:i:c:s0360544223031535. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.