Content area
Abstract
The boiling wheat economy in the recent two or three years has raised public and the agricultural policy makers' concerns about the design and administration of wheat programs. A number of methods have been developed in the last decade to assist in the assessment and evaluation of alternative policies. Some of these emanate from the work of both electrical engineers and economists on "optimal control theory."
Two important functions of any control program are to provide a "learning basis" and to control the target system. Sometimes they are not compatible. The learning aspect is often used as a criterion to distinguish the quality feature of diverse control methods. For example, there is no active learning capacity in the open-loop policy design. Only accidental learning is found in the open-loop feedback control design. Policies that mix the learning and control functions are variously called active learning, dual control laws, or actively adaptive control systems. Although the actively adaptive schemes are useful methods for dealing with anticipated future events, they tend to be conservative in some applications where the future is uncertain. The imbalance and uncertainty of demand and supply in the recent wheat economy have compounded the problems of future farm program design. However, adaptive control theory assisted with decision tree analysis enables development of better decision strategies for policy makers under certain environments.
The optimal control solution chosen in 1983 for the planning horizon of 1984 and 1985 under uncertainty was a "set" idea instead of a single value. The results suggest that a flexible farm program design is a credible alternative because it would provide administrators with a greater range of choice for solving the price instability problem, thus making operation of the farm program more efficient.
