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Climate affects crop production decisions and outcomes in agriculture. From very short-term decisions about which crops to grow, when to plant or harvest a field, to longer-term decisions about farm investments, climate can positively or negatively affect agricultural systems. Although the general effects of climate change on agriculture are broadly understood, there are limited studies that model the relationship between specific crops and climate variables. The study uses the Autoregressive Distributed Lag (ARDL) model to analyze the sensitivity of maize yield to climate variables, fertilizer use and other non-climate variables. This paper uses annual time-series data of 47 observations spanning from 1970 to 2016. The results reveal that rainfall and temperature are important maize yield drivers in South Africa. However, if excessive, they will produce negative effects. The findings of this analysis are relevant for designing long-term interventions to mitigate the effects of climate change on maize production.

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The study used the Autoregressive Distributed Lag-Error Correction Model (ARDL-ECM) approach to estimate the responsiveness of South African maize and sorghum producers to price risk, price incentives and non-price incentives. The price risk variable was incorporated in the supply models to examine its impact on maize and sorghum production decisions. The study used annual historical time series data of 49 observations for the period 1970 to 2018 was used in the analysis. The empirical results reveal that maize and sorghum producers' response to own price is reasonably low. The study further shows that both maize and sorghum crops demonstrate a high speed of adjustment to the long-run equilibrium, which means that in the event of a shock to the system, grain output will quickly re-establish itself at a faster rate. The findings underscore the relevance of price risk in determining production output in South Africa.

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