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The impact of the Russia-Ukraine conflict on the extreme risk spillovers between agricultural futures and spots

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  • Zhou, Wei-Xing
  • Dai, Yun-Shi
  • Duong, Kiet Tuan
  • Dai, Peng-Fei

Abstract

The ongoing Russia-Ukraine conflict between two major agricultural powers has posed significant threats and challenges to the global food system and world food security. Focusing on the impact of the conflict on the global agricultural market, we propose a new analytical framework for tail dependence, and combine the Copula-CoVaR method with the ARMA-GARCH-skewed Student-t model to examine the tail dependence structure and extreme risk spillover between agricultural futures and spots over the pre- and post-outbreak periods. Our results indicate that the tail dependence structures in the futures-spot markets of soybean, maize, wheat, and rice have all reacted to the Russia-Ukraine conflict. Furthermore, the outbreak of the conflict has intensified risks of the four agricultural markets in varying degrees, with the wheat market being affected the most. Additionally, all the agricultural futures markets exhibit significant downside and upside risk spillovers to their corresponding spot markets before and after the outbreak of the conflict, whereas the strengths of these extreme risk spillover effects demonstrate significant asymmetries at the directional (downside versus upside) and temporal (pre-outbreak versus post-outbreak) levels.

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  • Zhou, Wei-Xing & Dai, Yun-Shi & Duong, Kiet Tuan & Dai, Peng-Fei, 2024. "The impact of the Russia-Ukraine conflict on the extreme risk spillovers between agricultural futures and spots," Journal of Economic Behavior & Organization, Elsevier, vol. 217(C), pages 91-111.
  • Handle: RePEc:eee:jeborg:v:217:y:2024:i:c:p:91-111
    DOI: 10.1016/j.jebo.2023.11.004
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    1. Yun-Shi Dai & Peng-Fei Dai & Wei-Xing Zhou, 2024. "The impact of geopolitical risk on the international agricultural market: Empirical analysis based on the GJR-GARCH-MIDAS model," Papers 2404.01641, arXiv.org.

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    More about this item

    Keywords

    Agricultural futures and spots; Russia-Ukraine conflict; Tail dependence; Risk spillover; Copula-CoVaR; Asymmetric impact;
    All these keywords.

    JEL classification:

    • 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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance

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