This paper presents a conceptual framework, known as systems development, for designing, selecting, and evaluating information systems. Techniques are developed that aid farm managers in choosing an accounting system. Six farmers took part in case studies testing the selection techniques. The participating farmers exhibited great diversity in the preferred design of their accounting systems and the manner in which they desired reports to be presented. This diversity suggests that system selection is an important aspect of implementing an accounting system.

A multiperiod programming model was used to simulate the effects of lower marginal income tax rates, the soil and water conservation deduction, and the cash tax accounting option on firm growth for a “representative” farm operating in the Alabama Black Belt region. Results show the lowered marginal income tax rates associated with the Economic Recovery Tax Act (ERTA) of 1981 provide a positive growth stimulus to the modeled firm as measured by accumulated net worth over a 10-year planning horizon. The soil and water conservation deduction in general provides greater tax relief to the modeled firm than either the ERTA income tax rate changes or the cash tax accounting provision. Important complementary and substitute relationships were found to exist between marginal income tax rates and the various tax provisions studied, implying care must be exercised when attempting to evaluate the impact on farm firms of changes in tax policy.

Cyclical fluctuations in prices and production have long characterized the United States hog industry. Recent evidence suggests that the length of the hog cycle has changed. In order to determine whether the change in cycle length is statistically significant, the bootstrap technique is employed to derive confidence intervals for point estimates of the hog cycle. Application of the bootstrap technique to time series models is discussed and empirical results are presented. It is concluded that the hog cycle is undergoing rather complicated changes based on cycle lengths that are calculated to be statistically different from zero.

A characteristics model, which assumes goods generate a common set of attributes but no unique attribute, is described. The model yielded two equations which were estimated. One was a set of hedonic price equations in which the price paid for each food purchased was a function of imputed attribute prices. This set of equations was estimated at the household level. Nutrient demand equations were estimated across households. Imputed prices, income, and household characteristics including location, size, education, age distribution, and race affected nutrient demand levels.

A linear programming algorithm is used to estimate the parameters of a wheat storage decision model. This approach allows objective functions other than minimization of error squared to be used. It is demonstrated that by using a profit maximization objective function, an improved wheat storage decision model can be developed.

Cumulative probability distributions of income for management scenarios involving four preharvest marketing strategies are subjected to stochastic dominance analysis to determine risk-efficient sets of strategies for different groups of farmers in North Florida. Results indicate that farmers should behave differently in their choice of marketing strategies according to their risk attitudes. Highly risk-averse farmers should prefer some forward contracting while low risk-averse and risk-loving farmers should prefer cash sales at harvest. Use of the futures markets leads to both higher income and greater risk than forward contracting but lower income and risk than cash sales.

Basic features of a microcomputer package, BCDP, which is an auto-tutorial designed to teach the Simplex algorithm are described. The package may be used to augment lecture and text materials in introductory linear programming courses or as a review for advanced math programming courses. Preliminary evaluations of the effectiveness of the program to augment classroom instruction are very positive.

Vector-autoregressive-moving-average (VARMA) modeling was used to identify distributed lag relationships among farm tractor derived demand variables and to provide a basis for formally testing the hypothesis that the price of new tractor horsepower is exogeneous to its quantity demanded. Similar causality tests were used for a number of other explanatory variables, including the interest rate, price of diesel fuel, and price of used tractors. Results indicate that several lagged variables are significant causal factors and that the dynamic nature of the demand structure cannot be ignored when explaining tractor demand.