The conditional volatility in the daily spot prices of the crops traded on the South African Futures Exchange (yellow maize, white maize, wheat, sunflower seed and soybeans) is determined. The volatility in the prices of white maize, yellow maize and sunflower seed have been found to vary over time, suggesting the use of the GARCH approach in these cases. Using the GARCH approach, the conditional standard deviation is the measure of volatility, and distinguishes between the predictable and unpredictable elements in the price process. This leaves only the stochastic component and is hence a more accurate measure of the actual risk associated with the price of the crop. The volatility in the prices of wheat and soybeans was found to be constant over time; hence the standard error of the ARIMA process was used as the measure of volatility in the prices of these two crops. When comparing the medians of the conditional standard deviations in the prices of white maize, yellow maize and sunflower seed to the constant volatilities of wheat and soybeans, the price of white maize was found to be the most volatile, followed by yellow maize, sunflower seed, soybeans, and wheat respectively. These results suggest that the more risk-averse farmers will more likely produce wheat, sunflower seed and to a lesser extent soybeans, while maize producers are expected to utilise forward pricing methods, especially put options, at a high level to manage the higher volatility.

Increasing productive water use in agriculture is seen as paramount to meet future food demand with limited water supplies. The main objective of this paper is to gain a better understanding of the interrelated linkages between crop water productivity (CWP) and applied water productivity (AWP) as affected by irrigation management decisions in order to assess the impact of economic decision making on CWP and AWP under area-limiting and water-limiting conditions. A daily soil water balance mathematical programming model that explicitly models the impact of technology choice and stochastic weather on water use efficiency was used to study the interactions. The assumption is made that a rational decision maker will allocate water to maximize expected profits. The results showed that CWP is, to a large extent, unresponsive to increasing irrigation water applications, especially when water applications are approaching maximum potential crop yields. The difference between optimal crop yields for the area-limiting and water-limiting scenarios is small, which shows that the portion of water production function that is relevant for economic decision making is small and falls within the unresponsive range of CWP changes. Profit maximizing decision makers will not try to maximize CWP or AWP since these objectives will result in profit losses.

Logistic regression is employed to analyse the factors which influence the decision of whether or not the respondent used forward pricing methods during the 2004/05 maize production season. Forward pricing methods include cash forward contracting and hedging with futures contracts and/or options, through the South African Futures Exchange (SAFEX). Based on the results, the use of forward pricing is associated with lower levels of risk aversion and higher levels of human capital. Factor analysis is employed to reduce the dimensionality of the personal reasons which help to interpret the underlying, common factor of the personal reasons why farmers are reluctant to use forward pricing methods. Three factors were extracted and were labelled “Lack of capacity", “Distrust of the market", and “Bad experiences”. The results from the factor analysis confirm the finding that farmers need higher levels of human capital to use forward pricing methods and that farmers do not believe that the forward pricing market is effective. Education should furthermore, focus more on the practical application of alternative forward pricing methods and not purely on the benefits of the use of forward pricing methods.