Financial and Risk Management Assistance: Decision Support for Agriculture

Article excerpt

The Financial and Risk Management (FARM) Assistance program created by Texas Cooperative Extension is a strategic analysis service offered to farmers and ranchers in Texas. The program serves as an example of large-scale, focused programming by extension agencies, as well as the implementation of technical stochastic simulation methods for use on the farm.

Key Words: decision information, decision support system, extension programming, farm level analysis, outreach, simulation

JEL Classifications: Q16, Q12, C15, D83

An important aspect of the agricultural economics profession is the connection of research and outreach. The land-grant system itself was designed to ensure that the information from innovative research flows to the general public. The common model is for extension agencies to disseminate relevant information developed or learned through research. Outreach occurs through many other channels, and most often it is the information or the newly discovered answer that is shared with the agricultural community. It is less common, however, for agricultural producers to be given access to the actual research methods or analytical tools used in the profession.

Applying research methods to specific individual problems or situations is what commonly happens when private companies fund research projects or hire research consultants. In this sense, applied research is very common, but tailoring a research method to a specific problem or application is time consuming and expensive. When the work is concluded, the resulting model is often so specific that it has few other applications. Delivering applied research tools and capacity to the general public is less common because creating a single model or tool that is flexible enough to handle the variety and uniqueness of many applications is difficult at best.

Texas Cooperative Extension has developed a program that delivers powerful analytical capacity to the hands of farmers and ranchers in Texas. The program known as Financial And Risk Management (FARM) Assistance is founded in stochastic farm-level research methods. Developed as an outreach program, the complex research tool is made available to any Texas producer.

Research Foundation

The FARM Assistance program is technically a 10-year pro forma financial analysis that incorporates the research methods of stochastic simulation. Stochastic simulation has long been an effective tool in investment analysis. Reutlinger (1970) describes the benefits of stochastic simulation in analyzing risky investment projects and goes on to provide several case examples of how the World Bank has used simulation risk analysis to aid in projectfunding decisions. Pouliquen (1970) discusses the technical concepts of risk analysis. He explains the importance of correlation to the overall risk assessment of an investment and describes the trade-off between model complexity and the value of isolating individual sources of risk.

In essence, FARM Assistance is a decision support system (DSS). The foundation of decision support and decision theory covers a broad spectrum of literature. FARM Assistance as a DSS addresses the decision steps of formulating and evaluating business alternatives. A survey of business managers conducted by Nutt (2000) focused on the evaluation of strategic alternatives. An interesting finding was that managers spent the most time, effort, and resources on the evaluation step in the decision-making process. A DSS like FARM Assistance can simplify the evaluation step for farm managers, increasing the likelihood that they will use more formal and accurate evaluations of alternative strategies.

Backus, Eidman, and Dijkhuizen (1997) point out the problems in production agriculture that can be viewed as a call for development of systems similar to FARM Assistance. They explain that farmers typically spend insufficient time and effort forming and evaluating alternative plans, often because they lack the confidence to do so accurately. …