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Dynamic spillover transmission in agricultural commodity markets: What has changed after the COVID-19 threat?

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  • Just, Małgorzata
  • Echaust, Krzysztof

Abstract

This paper applies the dynamic Diebold–Yilmaz and Baruník–Křehlík spillover indices to document a closer integration between agricultural commodity markets in the period when markets rebounded after the COVID-19 threat to the Russia–Ukraine​ war. We also identified the record return spillover transmission among agricultural commodities during a time of conflict and the strongest transmitters are wheat, maize and barley. The findings emphasise an increasing uncertainty to the global food market.

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  • Just, Małgorzata & Echaust, Krzysztof, 2022. "Dynamic spillover transmission in agricultural commodity markets: What has changed after the COVID-19 threat?," Economics Letters, Elsevier, vol. 217(C).
    • Handle: RePEc:eee:ecolet:v:217:y:2022:i:c:s0165176522002245
    DOI: 10.1016/j.econlet.2022.110671
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    References listed on IDEAS

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    Cited by:

    1. Barbara Będowska-Sójka & Agata Kliber & Laivi Laidroo, 2023. "Has the pandemic changed the relationships between fintechs and banks?," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(4), pages 15-33.
    2. Vítor João Pereira Domingues Martinho, 2022. "Impacts of the COVID-19 Pandemic and the Russia–Ukraine Conflict on Land Use across the World," Land, MDPI, vol. 11(10), pages 1-14, September.
    3. Pandey, Dharen Kumar & Lucey, Brian M. & Kumar, Satish, 2023. "Border disputes, conflicts, war, and financial markets research: A systematic review," Research in International Business and Finance, Elsevier, vol. 65(C).
    4. Florin Aliu & Jiří Kučera & Simona Hašková, 2023. "Agricultural Commodities in the Context of the Russia-Ukraine War: Evidence from Corn, Wheat, Barley, and Sunflower Oil," Forecasting, MDPI, vol. 5(1), pages 1-23, March.
    5. Khalfaoui, Rabeh & Shahzad, Umer & Ghaemi Asl, Mahdi & Ben Jabeur, Sami, 2023. "Investigating the spillovers between energy, food, and agricultural commodity markets: New insights from the quantile coherency approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 63-80.
    6. Kumar, Pawan & Singh, Vipul Kumar & Rao, Sandeep, 2023. "Does the substitution effect lead to feedback effect linkage between ethanol, crude oil, and soft agricultural commodities?," Energy Economics, Elsevier, vol. 119(C).
    7. Wei-Xing Zhou & Yun-Shi Dai & Kiet Tuan Duong & Peng-Fei Dai, 2023. "The impact of the Russia-Ukraine conflict on the extreme risk spillovers between agricultural futures and spots," Papers 2310.16850, arXiv.org.
    8. Umar, Muhammad & Riaz, Yasir & Yousaf, Imran, 2022. "Impact of Russian-Ukraine war on clean energy, conventional energy, and metal markets: Evidence from event study approach," Resources Policy, Elsevier, vol. 79(C).
    9. Feng, Yun & Yang, Jie & Huang, Qian, 2023. "Multiscale correlation analysis of Sino-US corn futures markets and the impact of international crude oil price: A new perspective from the multifractal method," Finance Research Letters, Elsevier, vol. 53(C).
    10. Tongshuai Qiao & Liyan Han, 2023. "COVID‐19 and tail risk contagion across commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(2), pages 242-272, February.
    11. Capitani, Daniel Henrique Dario & Gaio, Luiz Eduardo, 2023. "Volatility Transmissionin Agricultural Markets: Evidence from the Russia-Ukraine Conflict," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 11(2), April.
    12. Wu, You & Ren, Wenting & Wan, Jieru & Liu, Xiaoxue, 2023. "Time-frequency volatility connectedness between fossil energy and agricultural commodities: Comparing the COVID-19 pandemic with the Russia-Ukraine conflict," Finance Research Letters, Elsevier, vol. 55(PA).
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    14. Kristína Hudecová & Miroslava Rajčániová, 2023. "The impact of geopolitical risk on agricultural commodity prices," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 69(4), pages 129-139.

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    More about this item

    Keywords

    COVID-19; Russia–Ukraine war; Agricultural commodity; Spillover index;
    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
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness

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