It is a privilege and pleasure to have the opportunity to present the inaugural presidential address of the Southern Agricultural Economics Association (SAEA). As I considered alternative topics which might be candidates for this presidential address, an intriguing question kept attracting my attention. Why are there regional agricultural economics associations and in particular why is there a Southern Agricultural Economics Association? What services does the SAEA provide to its membership that a national association such as the American Agricultural Economics Association does not provide? Or possibly it is not what services a regional association provides but how and in what kind of an environment the services are provided to members.

The following definition of biotechnology goes beyond the rather limiting concept of genetic engineering. Biotechnology is defined simply as those biological means used to develop processes and products employing organisms or their components.

Adoption of computerized decision analysis and computerized communications technology in many agricultural production and marketing situations will occur rapidly in the next decade. Computer hardware, such as microcomputers and large central processors, has become more reliable while costs have declined dramatically. Coupled with this has been the escalating costs of people and product transportation.

The cornerstone of the 1977 and 1981 Farm Bills for crops is a buffer stock-supply management program involving the farmer-owned reserve and acreage adjustment instruments. Among the several reasons normally cited for adopting this type program is price and income stability. However, recent swings in commodity prices, net farm income and government program costs have stimulated widespread interest in farm program redesign and modification in 1985.

Rural development research and extension activities directly impact approximately 100 million U.S. farm and nonfarm residents; whereas, commercial agricultural programs directly impact about 6 million farm residents (U.S. Department of Commerce, b). Based on this fact, it is difficult to understand why rural development research and extension programs are often listed last when priorities for funding are discussed.

Prior to the last decade, federal water-project construction programs dominated water policy. These programs continue, but at a reduced level of funding, and the nation now is denning a new agenda of water resources issues to include water quality management and water allocation. Economists engaged in studies of water resources policy, and who seek to influence the direction of policy through research, teaching, and extension will find these exciting times.

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.

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.

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.

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.