Climate variability and maize yield in the Limpopo region of South Africa: Results from GME and MELE methods

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 input variables (i.e. labour, fertilizer, seed and irrigation). Based on pseudo R-squared, we found that the GME fits the data better than MELE. In addition, increased precipitation, increased temperature and irrigation have a positive impact on yield. Furthermore, the results of the GME show that the impact of precipitation on maize yield is weaker than that of temperature. However, the impact of climate variability on maize yield could be negative if it increases temperature marginally but reduces precipitation to a very large extent simultaneously. Moreover, the impact of irrigation on yield is positive and with a higher elasticity coefficient than that of precipitation, which supposes that the present system of irrigation could mitigate the impact of reduced precipitation on yield.