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Impact of climate risk shocks on global food and agricultural markets: A multiscale and tail connectedness analysis

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  • Khalfaoui, Rabeh
  • Goodell, John W.
  • Mefteh-Wali, Salma
  • Chishti, Muhammad Zubair
  • Gozgor, Giray

Abstract

We examine the time-frequency nexus between climate change, agricultural and food markets over normal and extreme market conditions by employing advanced methods such as quantile cross-spectral analysis and wavelet quantile correlation. To identify how climate change affects food and agricultural market price returns, we examine daily data from January 1, 2019, to May 9, 2022, using two climate change proxies: European CO2 emissions and MSCI World Climate Paris Aligned Net indices, four global food market indices, and four agricultural commodities. Our results reveal significant insights into the impact of CO2 emissions and environmental policy on these markets, emphasizing the nuanced nature of these effects across different market conditions and time frames. The results suggest that, in the long run, environmental policies contribute positively to agricultural and food markets, while the impact of CO2 emissions manifests as predominantly negative. This research provides valuable contributions to understanding the intricate dynamics between climate change, environmental policies, and the financial aspects of food and agricultural markets.

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  • Khalfaoui, Rabeh & Goodell, John W. & Mefteh-Wali, Salma & Chishti, Muhammad Zubair & Gozgor, Giray, 2024. "Impact of climate risk shocks on global food and agricultural markets: A multiscale and tail connectedness analysis," International Review of Financial Analysis, Elsevier, vol. 93(C).
    • Handle: RePEc:eee:finana:v:93:y:2024:i:c:s1057521924001388
    DOI: 10.1016/j.irfa.2024.103206
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    2. Bai, Jiaming & Li, Rui & Jiang, Yu & Zhang, Jiarui & Li, Dayong & Cai, Zelin & Zhang, Zhi, 2024. "Efficient agricultural water research under elevated global carbon dioxide concentration – Based on bibliometric analysis," Agricultural Water Management, Elsevier, vol. 299(C).
    3. Xuewei Zhou & Zisheng Ouyang & Rangan Gupta & Qiang Ji, 2024. "Time-Varying Multilayer Networks Analysis of Frequency Connectedness in Commodity Futures Markets," Working Papers 202422, University of Pretoria, Department of Economics.
    4. Yan-Hong Yang & Ying-Hui Shao & Wei-Xing Zhou, 2024. "Contemporaneous and lagged spillovers across crude oil, carbon emission allowance, climate change, and agriculture futures markets: Evidence from the $R^2$ decomposed connectedness approach," Papers 2408.09669, arXiv.org.

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