An empirical study involving derivations of farmers' utility functions and the accuracy of these functions in predicting practical decisions is here reported. Three models of utility estimation which were used are compared as to their predictive accuracy and usefulness under field conditions. The study tests the hypothesis that maximizing expected utility, as a criterion of decision, is superior to maximizing expected monetary value. Utility functions are derived for two points in time in order to test the hypothesis that, if utility functions are to serve as a guide to the decision maker, they must be derived at each point in time at which decisions are made. Implications for decision-making research and for practical farm decision making are indicated. 0< We are indebted to John L. Dillon for helpful comments.

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The economic value of frost forecasts is estimated under various assumptions concerning prior information, accuracy of forecasts, and the shape of the orchard operator's utility functions. The frost protection decision process is simulated in the context of Bayesian decision making under uncertainty. The averaged seasonal values estimated per day per acre were $@@‐@@5.39 for frost forecasts provided by the U.S. Weather Service, $@@‐@@8.57 for perfect frost forecasts, $@@‐@@4.73 for profit maximizers, and $@@‐@@191.39 for completely ignorant decision makers. The methodology used has general application to determination of economic value of information under conditions of uncertainty.

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Agricultural sector analyses for purposes of agricultural policy evaluation and planning in developing countries are generally conducted in a partial equilibrium framework without regard to agricultural‐nonagricultural interactions. A relatively simple simulation model built on an input‐output framework is developed which, in combination with an agricultural sector analysis, enables interactions in the product markets and labor market to be considered. The model is illustrated through linkage with an agricultural simulation model to evaluate alternative agricultural policies in Nigeria. The model also has potential for use with other formal and informal sector analysis techniques.

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1 If at some future date there were a change in external circumstances, e.g., prices or technology, then a new decision situation would arise for which new policy variables would be selected. This implies a comparative-statics approach.A. N. HALTER i8 professor of agricultural economics, Oregon State University.