It is as important to measure the degree of risk involved as it is to measure the probable return from an investment project. The expected returns from such a project are usually calculated from a unique set of parameters whose values are the [`]best guessed estimates' available at the time of making the projection. Risk analysis involves the selection of the range of possible values for each major variable and an estimation of the probability of each value occurring. In the computations used in this paper the choice of values is made by Monte Carlo simulation. As agricultural problems are involved, care has been taken of the linkage effects between variables and of the dependence of one year's results on the outcome of the previous year. The dynamic nature of the problem and the iterative calculations involved in Monte Carlo techniques favour a computer-based model. The paper is concerned with the application of this approach to rangeland livestock projections.
Journal articles from the Grassland Society of Southern Africa (GSSA) African Journal of Range and Forage Science as well as related articles and reports from throughout the southern African region.