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Impact of Climate Change, Weather Extremes, and Price Risk on Global Food Supply

Author

Listed:
  • Mekbib G. Haile

    (Center for Development Research, Bonn University)

  • Tesfamicheal Wossen

    (International Institute of Tropical Agriculture (IITA))

  • Kindie Tesfaye

    (International Maize and Wheat Improvement Center (CIMMYT))

  • Joachim von Braun

    (Center for Development Research, Bonn University)

Abstract

We analyze the determinants of global crop production for maize, wheat, rice, and soybeans over the period 1961–2013. Using seasonal production data and price change and price volatility information at country level, as well as future climate data from 32 global circulation models, we project that climate change could reduce global crop production by 9% in the 2030s and by 23% in the 2050s. Climate change leads to 1–3% higher annual fluctuations of global crop production over the next four decades. We find strong, positive and statistically significant supply response to changing prices for all four crops. However, output price volatility, which signals risk to producers, reduces the supply of these key global agricultural staple crops—especially for wheat and maize. We find that climate change has significant adverse effects on production of the world’s key staple crops. Especially, weather extremes— in terms of shocks in both temperature and precipitation— during crop growing months have detrimental impacts on the production of the abovementioned food crops. Weather extremes also exacerbate the year-to-year fluctuations of food availability, and thus may further increase price volatility with its adverse impacts on production and poor consumers. Combating climate change using both mitigation and adaptation technologies is therefore crucial for global production and hence food security.

Suggested Citation

  • Mekbib G. Haile & Tesfamicheal Wossen & Kindie Tesfaye & Joachim von Braun, 2017. "Impact of Climate Change, Weather Extremes, and Price Risk on Global Food Supply," Economics of Disasters and Climate Change, Springer, vol. 1(1), pages 55-75, June.
  • Handle: RePEc:spr:ediscc:v:1:y:2017:i:1:d:10.1007_s41885-017-0005-2
    DOI: 10.1007/s41885-017-0005-2
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    3. Liang, Chen & Zhu, Minghao & Lee, Peter K.C. & Cheng, T.C.E. & Yeung, Andy C.L., 2024. "Combating extreme weather through operations management: Evidence from a natural experiment in China," International Journal of Production Economics, Elsevier, vol. 267(C).
    4. Oscar Zapata, 2018. "Turning to God in Tough Times? Human Versus Material Losses from Climate Disasters in Canada," Economics of Disasters and Climate Change, Springer, vol. 2(3), pages 259-281, October.
    5. Ilan Noy & Shunsuke Managi & Stephane Hallegatte, 2018. "Economics of Disasters and Climate Change – The Journal’s First Year," Economics of Disasters and Climate Change, Springer, vol. 2(1), pages 1-3, April.
    6. Hongbo Liu & Shuanglu Liang, 2019. "The Nexus between Energy Consumption, Biodiversity, and Economic Growth in Lancang-Mekong Cooperation (LMC): Evidence from Cointegration and Granger Causality Tests," IJERPH, MDPI, vol. 16(18), pages 1-15, September.
    7. Chen, Bowen & Villoria, Nelson B., 2018. "Food Price Variability and Import Dependence: A Country Panel Analysis," 2018 Annual Meeting, August 5-7, Washington, D.C. 274285, Agricultural and Applied Economics Association.
    8. Ole Boysen & Kirsten Boysen-Urban & Alan Matthews, 2021. "Alternative EU CAP Tools for Stabilising Farm Incomes in the Era of Climate Change," Working Papers 202103, Geary Institute, University College Dublin.
    9. Suresh, Kanesh & Khanal, Uttam & Wilson, Clevo & Managi, Shunsuke & Quayle, Annette & Santhirakumar, Samithamby, 2021. "An economic analysis of agricultural adaptation to climate change impacts in Sri Lanka: An endogenous switching regression analysis," Land Use Policy, Elsevier, vol. 109(C).
    10. Mariam Diallo & Fleur Wouterse, 2023. "Agricultural development promises more growth and less poverty in Africa: Modelling the potential impact of implementing the Comprehensive Africa Agriculture Development Programme in six countries," Development Policy Review, Overseas Development Institute, vol. 41(3), May.
    11. Roberto Louis Forestal & Shih-Ming Pi, 2021. "Using Artificial Neural networks and Optimal Scaling Model to Forecast Agriculture Commodity Price: An Ecological-economic Approach," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(3), pages 1-3.
    12. Sukcharoen, Kunlapath & Golden, Bill & Vestal, Mallory & Guerrero, Bridget, 2020. "Do crop price expectations matter? An analysis of groundwater pumping decisions in Western Kansas," Agricultural Water Management, Elsevier, vol. 231(C).

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