Cow-calf production and marketing decisions in East Texas : application of risk constrained linear programming and statistical decision theory

Abstract

Beef cattle production is the most important agricultural enterprise in Texas. Much of the state's land resources are devoted to the production of forage for raising calves and feed grains for fattening them. Yet, as in many other agricultural activities, annual profits for both ranchers and feeders are highly variable. This study concentrates on decisionmaking under uncertainty at the ranch level. Variability in ranch profits is due largely to seasonal and annual fluctuations in calf prices and forage yields. Specific objectives addressed are: (a) to determine alternative sets of efficient ranch plans consisting of profitable forage combinations, cow herd sizes and levels of integration for individual cow-calf producers in three areas of East Texas; (b) to estimate effects of calving season and cow fertility level on profitability; (c) to evaluate the effect of decisionmakers' risk-return preferences on selection of the optimal ranch organization from alternative efficient plans; (d) to develop calf price and forage yield forecasting models; (e) to determine profitable annual calf marketing strategies in response to price and forage forecasts; (f) to estimate the value of the forecasting information. Hazell's risk-constrained linear programming model is adapted to accomplish objectives (a) and (b) for an agricultural enterprise in which both an intermediate product (forage) and final product (beef) are produced. The model is specified to maximize expected net income subject to constraints on resources and the mean absolute deviation in net returns. The latter constraint is parametrically altered in order to derive a linear approximation to an E-V frontier of efficient ranch plans. Optimal long-run ranch plans are then identified using alternative lexicographic (risk-return) utility functions..