This study concerns the evaluation of alternative pricing strategies involving options on feed grains futures contracts during the period of 1973-1986. To predict the option premiums that would have occurred at various points in this time period, the study did research on market premiums of options on corn futures contracts from March 1, 1985 until December 31, 1985. The research showed that market premiums conformed closely to the premiums estimated by Black model of options pricing. The generalized stochastic dominance with absolute risk aversion function intervals is applied in the study in order to evaluate the strategies. The results showed that under different risk preferences, (DARA and CARA), the commodity options strategies dominate the cash sale strategy, but do not dominate the hedging by selling futures contract strategy. Options may provide alternatives for feed grains producers and traders. Put (call) options provided protection from losses resulting from falling (raising) cash price and may somtimes raise average income/margin of feed grain producers and traders.

M.B.A. / A general increase in price elasticity on farming inputs as well as increasing pressure on South African subsidiaries of international companies makes it important for a well-planned pricing strategy. This is accentuated by the fact that pricing is normally done only once a year in seed companies in South Africa, and customers are unlikely to accept more frequent price changes. The aim of this study is to determine a suitable pricing strategy for hybrid maize seed for Monsanto in South Africa. The study has the following objectives: To determine through a literature study the factors influencing the decision to buy hybrid maize seed in South Africa. To determine the price range that producers would be willing to pay for typical hybrid maize seed products. To evaluate Mark-up Pricing, Target-Return Pricing, Perceived-Value Pricing, Value Pricing and Going-Rate Pricing and to determine the best method or combination of methods for the pricing of hybrid maize seed. To formulate a pricing strategy for hybrid maize seed for Monsanto in South Africa. Of the typical product characteristics, yield is the most important factor influencing the decision to buy a product. Products that are priced very high signal high quality to the customer. No significant price elasticity exists for low, medium or moderately high priced products. Grain quality and growth season length characteristics are of little importance in influencing the decision to buy a specific product. Customers want to have first-hand experience of a product, before being willing to buy a substantial amount of it. They need to confirm the potential of a new breakthrough product on their own farms and conditions, before buying it. The most important source of information is own experience, which consists of some form of farmer trial, followed by large plot trials conducted by seed companies. If an independent large plot set of trials is made available, it would be preferred over the large plot trials conducted by seed companies as a source of information to farmers. For products of average quality, farmers are willing to pay between R453.13 and R565.79, with an inelastic zone between R483.33 and R525.68 per unit of seed. For products of superior quality farmers are willing to pay between R555.56 and R686.36, with an inelastic zone between R591.67 and R652.27 per unit of seed. Monsanto employees generally underestimate the price customers are willing to pay for products of average quality, but there is a danger that they could overestimate the prices customers are willing to pay for products of superior quality. Sealed bid and negotiated pricing methods are not very suitable for pricing hybrid maize seed. Perceived-value pricing and going-rate pricing should be used for products of superior and average quality. For new breakthrough products, a market skimming approach should be followed and products should be priced very high, since an inflated price signals very high quality to customers. Monsanto needs more structured benchmarking with regards to competitor productions costs. A structured benchmarking approach for evaluating hybrid performance, pricing and market share is also discussed.

D.Litt. et Phil. / The objective of this dissertation was to investigate the ostensible structural deterioration of the socio-economic position of the South African maize producers since the start of the eighties as a consequence of the low and erratic rainfall, the relatively high cost of finance, the worsening terms of trade of the industry and the secular decline in the real price of maize on the world market. The constant pressure of the four factors on the profit position of the maize industry compelled producers to pay less attention to the maintenance of soil fertility, technology and the remuneration and training of their workers. The need to succumb to exploitative practices in order to survive became a strong feature of the industry since the late eighties when the potential for the further improvement of productivity by economising on fertilizer and other inputs and using capital assets such as tractors and harvesters more intensively had run its course. The South African maize producer is faced by an adverse production or cost function, mainly as a consequence of the very erratic climatic and poor soil, environment in which he is finding himself. The grain producing industries all over the world are still closely governed by soil and climatic conditions, compared to the meat, dairy, poultry and horticultural industries, which have increasingly assumed characteristics of manufacturing industry. Technological developments in the grain industries such as hybridisation and the advent of the modern fertilizers, weed and pest herbicides and the tractor and mechanical harvester did not free the industry from the constraints imposed on it by the poor South African soils and erratic weather patterns. The production of grain, especially maize, is still subject to the cost constraint imposed by the law of decreasing returns. Co-incidental to the difficult production function is the more pronounced tendency of production to fluctuate and the growing disparity between supply and demand, not only in the South African market, but globally. This behaviour as well 'as the price support measures, by especially the USA and the European Union, are responsible for the constant weakening of the terms of trade of the industry and the secular decline of the global real maize prize.

Maize is the most important cereal crop grown in South Africa. This crop is produced throughout the country under diverse conditions and in diverse environments. The study only focuses on technical efficiency because it is an important subject in developing agriculture where resources are limited, but high population growth is very common. In such a setting, increased output will depend more on efficiency improvements and assessing the scope for such efficiency improvements within the system is a crucial need. The objective of the study was to determine the level of technical efficiency and to identify the socio-economic and institutional characteristics as well as the entrepreneurial spirit that influence the technical efficiency of small-scale maize producers in the Tsolo magisterial district. Purposive and Snowball sampling techniques were used to collect primary data from 120 small-scale farmers. The stochastic frontier model was used to determine the level of technical efficiency. The Multivariate OLS was used to analyze the socio-economic factors and institutional characteristics that have influenced the technical efficiency of maize production. A similar linear regression model was used to estimate the influence of positive psychological capital and entrepreneurial spirit on the technical efficiency of maize production. The stochastic results revealed that small-scale farmers in Tsolo are technically efficient at 98 percent in maize production and experience increasing return to scale (1.37), which means that increase in the use of inputs, will as well increase their productivity and efficiency. The inefficiency model results indicated that age, years in farming, household size and extension contact significant and 3 variables, namely, as years in farming, extension contact and farm size are significant in the OLS model. Lastly the results of the linear regression indicated that, out of the 4 variables estimated in the entrepreneurial spirit, self-efficacy and resilience were significant with respect to its responsiveness to total maize output.

With many genetic traits discovered and many more in progress, it is imperative to the industry that firms (biotechnology companies) decide on the trait valuation and pricing. This includes more than one trait (also referred to as stacked traits) in a single variety of crop; the risk and uncertainty of expected returns associated with the development and release of a variety increases even more in case of stacked traits. The purpose of this thesis is to develop a model that can be used for the valuing and pricing of genetically modified (GM) traits that are random, sporadic, and non-persistent (e.g. drought tolerance, heat/cold stress) using the real option approach. The efficiency gain in case of occurrence of random event and expression of GM traits will be measured and used as a decision factor in determining the value of GM trait(s) at different phases of development. Risk premiums representing the value of GM trait to growers is calculated across risk averse attitudes. The return to labor and management (RTLM) provided by a GM trait is used to calculate the risk premiums when variation in parameters is allowed to be same as that reflected in historical data and gains from GM traits are realized. Monte Carlo simulation and stochastic efficiency with respect to a function (SERF) are used to estimate the certainty equivalents that decision makers would place on a risky alternative relative to a no risk investment. Certainty equivalents are estimated across a range of risk aversion coefficients and used to rank alternatives and determine where preferences among alternatives change while estimating risk premiums for the base case (no trait), drought tolerance, cold tolerance, NUB, and All traits (all traits combined into one as a stacked trait). Premiums provide perspective on the magnitude of differences in relative preferences among choices. The range of ARAC utilized was from 0.00 to 0.15 for all three crops. The risk premiums are treated as a potential source of revenue in the model as a technology fee charged by a biotech company. This thesis uses the Real Option methodology to evaluate GM traits as Option values at various stages of development. This approach helps managers decide the best possible option in making a certain decision today. It is also helpful in comparing different pathways (series of decisions) and thus better exploits the potential cash return in the future from investments made today (Figure D.1, Figure D.2). Three possible options to "continue", "wait", and "abandon" were modeled in this thesis. Such modeling determines the possible option values of GM traits at different stages of development depending on the kind of choices made at different points of time. This thesis shows that various GM traits that are out-of-money (OTM) at initial stages have increased probability of being in-the-money (ITM) at later stages of development. Sensitivities show that a share of potential technology fees and acreage of GM crops play a significant role in option values being ITM. Stacked traits provide a better chance of being ITM, thus the option to continue will be exercised by management. The option to wait causes reduction in option value. Among individual traits, drought tolerance has the greatest maximum option value in most cases. Therefore, if management has to choose the development of only one GM trait, it is most likely to choose to invest in the development of drought tolerance.