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Climate variability and maize yield in South Africa: Results from GME and MELE methods

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  • Akpalu, Wisdom
  • Hassan, Rashid M.
  • Ringler, Claudia

Abstract

"This paper investigates the impact of climate variability on maize yield in the Limpopo Basin of South Africa using the Generalized Maximum Entropy (GME) estimator and Maximum Entropy Leuven Estimator (MELE). Precipitation and temperature were used as proxies for climate variability, which were combined with traditional inputs variables (i.e., labor, fertilizer, seed, and irrigation). We found that the MELE fits the data better than the GME. In addition, increased precipitation, increased temperature, and irrigation have a positive impact on yield. Furthermore, results of the MELE show that the impact of precipitation on maize yield is stronger than that of temperature, meaning that the impact of climate variability on maize yield could be negative if the change increases temperature but reduces precipitation at the same rate and simultaneously. Moreover, the impact of irrigation on yield is positive but with a lower elasticity coefficient than that of precipitation, which supposes that irrigation may only partially mitigate the impact of reduced precipitation on yield. " from authors' abstract

Suggested Citation

  • Akpalu, Wisdom & Hassan, Rashid M. & Ringler, Claudia, 2008. "Climate variability and maize yield in South Africa: Results from GME and MELE methods," IFPRI discussion papers 843, International Food Policy Research Institute (IFPRI).
    • Handle: RePEc:fpr:ifprid:843
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    References listed on IDEAS

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    Cited by:

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    2. Phiri, Innocent Pangapanga, 2011. "Modelling farmers’ choice of adaptation strategies towards climatic and weather variability: Empirical evidence from Chikhwawa district, Southern Malawi," Research Theses 134489, Collaborative Masters Program in Agricultural and Applied Economics.
    3. Parajuli, P.B. & Jayakody, P. & Sassenrath, G.F. & Ouyang, Y., 2016. "Assessing the impacts of climate change and tillage practices on stream flow, crop and sediment yields from the Mississippi River Basin," Agricultural Water Management, Elsevier, vol. 168(C), pages 112-124.
    4. Pangapanga, Phiriinnocent & Thangalimodzi, Lucy Tembo, 2012. "Participation in pro poor agro based enterprises in Malawi: do households’ poverty levels change automatically?," MPRA Paper 39446, University Library of Munich, Germany.
    5. Robert Becker Pickson & Ge He & Elliot Boateng, 2022. "Impacts of climate change on rice production: evidence from 30 Chinese provinces," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 3907-3925, March.
    6. Arunrat, Noppol & Pumijumnong, Nathsuda & Hatano, Ryusuke, 2018. "Predicting local-scale impact of climate change on rice yield and soil organic carbon sequestration: A case study in Roi Et Province, Northeast Thailand," Agricultural Systems, Elsevier, vol. 164(C), pages 58-70.
    7. Jonathan P. Sheppard & Rafael Bohn Reckziegel & Lars Borrass & Paxie W. Chirwa & Claudio J. Cuaranhua & Sibylle K Hassler & Svenja Hoffmeister & Florian Kestel & Rebekka Maier & Mirko Mälicke & Christ, 2020. "Agroforestry: An Appropriate and Sustainable Response to a Changing Climate in Southern Africa?," Sustainability, MDPI, vol. 12(17), pages 1-32, August.

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    Keywords

    Yield function; maize; Generalized maximum entropy; Maximum entropy Leuven estimator; Climate variability; Climate change;
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