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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

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Bibliographic Info

Paper provided by International Food Policy Research Institute (IFPRI) in its series IFPRI discussion papers with number 843.

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Date of creation: 2008
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Handle: RePEc:fpr:ifprid:843

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Related research

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

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  1. Quirino Paris, 2001. "Multicollinearity and maximum entropy estimators," Economics Bulletin, AccessEcon, vol. 3(11), pages 1-9.
  2. Mabiso, Athur & Weatherspoon, Dave D., 2008. "Fuel and Food Tradeoffs: A Preliminary Analysis of South African Food Consumption Patterns," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6126, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  3. Mendelsohn, Robert & Nordhaus, William D & Shaw, Daigee, 1994. "The Impact of Global Warming on Agriculture: A Ricardian Analysis," American Economic Review, American Economic Association, vol. 84(4), pages 753-71, September.
  4. Lence, Sergio H. & Miller, Douglas, 1998. "Recovering Output-Specific Inputs from Aggregate Input Data: A Generalized Cross Entropy Approach," Staff General Research Papers 1305, Iowa State University, Department of Economics.
  5. Quirino Paris & Richard E. Howitt, 1998. "An Analysis of Ill-Posed Production Problems Using Maximum Entropy," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 124-138.
  6. Msangi, Siwa & Howitt, Richard E., 2006. "Estimating Disaggregate Production Functions: An Application to Northern Mexico," 2006 Annual meeting, July 23-26, Long Beach, CA 21080, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  7. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers 1488, Iowa State University, Department of Economics.
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