Investigating the optimization of the white maize spread/price

Abstract

The agricultural sector contributes significantly to job creation in South Africa. However, the area under maize production has decreased in the past years whilst the consumption increased. The increase in demand has put pressure on maize farmers to increase their yields per hectare. Furthermore, the continued decrease in land allocated for maize production will ultimately threaten food security and lead to an increase in maize prices. Trading firms sell the March/July white maize spread each year. The money received from selling the March/July white maize spread pays for the interest and storage costs associated with carrying white maize from March to the end of June. The difference between the price at which the spread is sold and the full carrying costs associated with carrying white maize from March to the end of June is paid by the trading firm. Eventually, the lower the price at which the spread is sold, the higher the amount the trading firm must pay to carry white maize from March to the end of June. This study serves as a tool for trading firms to better predict the best price to sell the March/July white maize spread to relieve pressure from their cashflow. It will also ensure that maize meal is affordable to the final consumer at a competitive price because the cost that trading firms incur from getting maize from the farm to the miller will be minimised. The aim of the study was to determine the best price to sell the March/July white maize spread under the prevailing circumstances and conditions at the time. The study followed the positivist paradigm and the quantitative approach. The study design used was longitudinal in nature. The study population was the crop estimates committee reports released from 1999 to date. The sample of the population that was used in this study was the crop estimates committee reports from 2009 to 2020. Purposive sampling was used to determine the sample size, resulting in ten units of analysis being utilised. Each unit of analysis was the final report of the crop estimates committee. Data on supply and demand estimates of white maize was obtained from SAGIS and data on white maize prices was obtained from Thomson Reuters. This study made use of a regression analysis to determine what the price of the March/July white maize spread will be given a certain amount of white maize ending/opening stock, R/$ exchange rate and the stock to use ratio. The study found that the optimal price of the March/July white maize spread is associated with an opening stock of more than 1 362 000 tons, a R/$ exchange rate of less than R12.09 and a stock to use ratio of more than 22%. In reality these variables may vary. A model derived from a regression analysis of the March/July 2017 white maize spread was suggested to determine the optimal price of the March/July white maize spread taking all these variables into account.