Abstract
This paper examines the effect of rainfall, temperature, and drought on sorghum, millets, wheat, and maize crops in Africa. Spatial Bayesian propensity score modeling (BSPSM) analysis is used to estimate means for specific geographic populations using spatial Bayesian models. The results show that rising temperatures and drought have a negative impact on the yield of these crops, thus compromising food security and livelihoods of African populations. Adverse effects include decreased productivity, increased crop losses, and altered grain quality. In light of this challenge, it is important to take adaptive measures to mitigate the effects of rising temperatures. Recommended measures include the adoption of resilient agricultural practices, such as the use of heat-adapted seeds, efficient irrigation, and the establishment of agroforestry systems. In addition, risk management strategies such as crop insurance and crop diversification are essential to improve farmers’ resilience to climate change.
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The datasets used during the current study are available from the corresponding or first author on reasonable request.
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K.S.: introduction, concept-building, data. M.B.J.: literature review, analysis, supervision. A.G.: literature review, methods, editing, discussion, conclusion, and implications.
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Ghazouani, A., Ben Jebli, M. & Shahzad, K. Natural Disaster and Food Security in African Countries: Evidence from an Experimental Bayesian Spatial Model. J Knowl Econ (2024). https://doi.org/10.1007/s13132-023-01713-y
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DOI: https://doi.org/10.1007/s13132-023-01713-y