Estimation of the economic value of irrigation water is complicated by a lack of data on the price or marginal cost of water. Through econometric estimation of an aggregate total value product function, this paper obtains marginal irrigation water value estimates for the Middle Atlantic region. Additionally, the impact of temperature and soil conditions on aggregate production within the region is estimated. Ridge regression and covariance analysis are employed to deal with problems of multicollinearity and simultaneous equation bias, respectively. Estimates indicate a substantial and growing return to irrigation within the region.

Payment arrangements among members of a cooperative play a critical role in the performance of the cooperative. The impact of three payment systems is assessed for Florida sugarcane cooperatives through a bi-level programming model which incorporates both individual and collective behavior.

The role of cognitive science as presented by Black offers an in-depth treatment of the current agricultural information processing and interpretation revolution and the contributions of other disciplines, ranging from engineering and psychology, finance and medicine, to the science of decisionmaking in agriculture. Certainly, many farm management economists will find the issues of information reception, styles of thinking, systems science approaches, biological pathways in modeling, psychological types, and other cognitive science issues raised in this session to be important and useful in the context of both basic and applied research. Agricultural economists are again reminded of the need to integrate approaches across models, the payoff to alternative degrees of approximating reality and the usefulness of a better balance in the portfolio of microcomputer activities.

Simulation has become a standard methodology in agricultural economics with models being used in all aspects of the profession. Johnson and Rausser identify two major types of production simulation models in their recent survey of the topic—firm and process models. Firm models, especially those concerned with growth, are most prominent in the agricultural economics literature. However, Johnson and Rausser also review some application of process models, which emphasize specific types of firm decisions. Biophysical simulation models are a specific form of these models concerned with the interaction of weather, soil, and/or biological processes in agricultural production and/or environmental loadings. In the recent agricultural economics literature, these models often are identified as bio-economic simulators. However, similar models are being utilized to evaluate erosion. Since erosion is largely a physical process, biophysical simulation seems more appropriate for the general classification of models considered in this paper.

A dynamic model of daily cash and futures prices for cotton was developed using time series analysis. The time series model was included in a recursive Monte Carlo simulation model. Validation of the model was performed with a stochastic, dynamic simulation of the estimated model over the observation period 1975-1982 and with a static, deterministic out-of-sample forecast from December 9, 1981 through March 9, 1982. The model was then used to incorporate futures trading strategies into a policy simulation model.

Scherer's industrial organization model is modified to characterize the grain marketing system. The modified model identifies the important relationships between economic characteristics and the type of grain facilities found in three states; Alabama, Illinois, and Ohio. Multivariate linear discriminant analysis is used to identify the important basic supply, demand, and transportation variables within and among these states. It is concluded that the structural differences among selected grain marketing regions can be explained by regional differences in basic supply, demand, and transportation variables. The findings suggest that Scherer's industrial organization model can be adapted to explain the diverse structure of the grain marketing system in selected states.

Development and commercialization of technologies that utilize on-farm energy sources are beset by uncertainty. Producer gas, a technology that allows wood to be converted to a gaseous fuel which can power internal combustion engines, is evaluated for irrigation systems using simulation modeling and stochastic efficiency analysis. For many market conditions, producer gas stochastically dominates diesel fuel for powering a center pivot irrigation system in terms of lower cost. Commercial potential exists, but experience with pilot installations is required to further reduce uncertainty.

In the absence of agricultural policy, the behavior of the agricultural sector is dictated by market forces. Any agricultural policy, other than one of “hands off—let the market forces rule,” is dependent upon programmatic tools which in one way or another attempt to interfere or modify behavior of the sector. If it is government's objective to design and implement a set of programs which will distort market behavior so as to achieve policy goals with minimum negative side effects, it is essential that policymakers understand the kind of market environment within which the U.S. farm sector exists and how this market is likely to behave, given alternative interferences.

In this study, both the Rotterdam model and the double logarithmic model were used to estimate the demand parameters for fruit beverages. The results show that: (1) under the conditions of block-independence and predetermined price changes, the Slutsky matrix for fruit beverages is symmetric and negative definite; (2) own-price elasticity estimates from both models are about the same; and (3) income elasticity estimates and cross-product relationships from the two models are not compatible.

This paper describes a microcomputer software package, IO/EAM: An Input-Output Economic Assessment Model, which was developed at the University of Georgia through a joint extension-research effort. The package is a menudriven, user friendly program that is designed to be used by county extension agents, researchers, and other extension personnel to estimate the economic impact of changes in county economies. The program employs an input-output model that provides users with a locally based, easily updated source of economic intelligence. Use of input-output techniques allows users to estimate the impact of changes in county economies on an industry-by-industry basis and to account for the interdependencies among these industries in a county.

An economically efficient allocation of resources maximizes consumer and producer surpluses. It can be shown that under perfectly competitive conditions, an efficient allocation of resources will evolve. It may be the global welfare optimum, but for a given set of conditions, consumer and producer surpluses can be maximized.

An economic threshold of agricultural pest management is derived. Results provide a method for researchers to use in making improved pest control recommendations to farmers without farm level decisionmaking. An empirical illustration for lesion nematode management in irrigated corn is given and directions for further research are indicated.

The risk effects of irrigation scheduling in a sub-humid climate have been well documented recently using approximations of the variance of net returns. A method to determine the exact variance of net returns assuming only multivariant normality is presented. The approximation technique in contrast to the method presented in this research was shown to have a non-uniform effect on the variance of net returns of each schedule.

Agricultural economists have recently been attracted to procedures suggested by Granger and others which allow observed data to reveal causal relationships. Results of this study indicate that “causality” tests can be ambiguous in identifying behavioral relationships between agricultural price variables. Caution is suggested when using such procedures for model choice.

The majority of decisions concerning investment and allocation of public funds for agricultural research, extension, and teaching (RET) are made at the state-level, while most of the quantitative RET evaluations are made on a national basis. This paper illustrates an approach for conducting a disaggregated state-level evaluation of agricultural research, extension, and teaching. Ridge regression is employed to handle multicollinearity problems.