A Stochastic Production Function Analysis of Maize Hybrids and Yield Variability in Drought-Prone Areas of Kenya

Abstract

Abstract The importance of maize as a staple food and source of cash for smallholder farmers in drought prone areas of Sub-Saharan Africa, and the threat of greater climatic variability, have led recently to considerable investment in maize breeding for water-use efficiency. Kenya is a target country for this research. Although trial data suggest that improved genetic materials in the research pipeline may increase mean yields and reduce yield variability, relatively little has been documented concerning the variability of maize yields on smallholder farms in Kenya. This research serves as a baseline by testing the effect of current maize hybrids on the mean, variance, and skewness of yields with a stochastic production function applied to survey data collected by Tegemeo Institute during the 2006-7 cropping season. We find that, relative to other maize types, hybrids enhance mean yields, although there is scant evidence of their effect on the variance of yields. Perhaps more importantly, hybrids reduce the exposure of smallholders to extremely low yields, pulling maize yields toward the mean. Additional research is required to confirm these findings using longitudinal data and rainfall data.