Estimating the supply response of maize in South Africa

Abstract

Maize is the most important crop in South Africa, being both the major feed grain for livestock and the primary staple food crop for the majority of the South African population. Furthermore, the maize industry contributes substantially to employment, manufacturing, foreign exchange and food security. The importance of maize in contributing to national growth is critical; this makes it meaningful to investigate the nature of maize farmers’ production decisions. This study quantifies the supply response of maize farmers to price and non-price factors in South Africa using econometric techniques. The non-price factors considered in this study are rainfall, technology and market policy. A modified Nerlovian partial adjustment model was applied on historical time series data spanning from 1980-2012 to estimate the supply response of maize in South Africa. To deal with the expected problems associated with time series data the study adopted several diagnostic tests. Results indicate a short-run supply elasticity of 0.49 and a long-run supply elasticity of 0.65, signifying that maize farmers are less sensitive to price changes. The results confirm that non-price factors seem to have more effect on maize supply in South Africa. These findings coincide with those obtained in supply response studies for field crops conducted in other developing African countries. The study also showed that non-price factors such as, rainfall, technology and market policies have a positive impact on maize production. Given the findings, the study recommends policies that focus more on non-price factors as a means of stabilising maize production. The study also recommends that Industry stakeholders and policymakers should find means to integrate the significant relationships between non-price factors and production output into future decisions and marketing policies to safeguard a healthy, growing and sustainable maize industry in South Africa. Key words: Maize supply response, Nerlovian partial adjustment model, price factors, non-price factors.