Abstract
A decision‐analytic approach is taken to the problem of assessing the economic value of imperfect weather forecasts. Emphasis is placed on measures of the quality of such information and on the relationship between quality and economic value. The fallowing/planting problem for a spring wheat farmer is examined in detail as a specific application. It is assumed that the farmer's goal is to maximize the total expected discounted return over an infinite horizon, which places this problem within the general framework of Markov decision processes. By means of stochastic dynamic programming, the economic value to the farmer of currently available seasonal precipitation forecasts, as well as of hypothetical improvements in the quality of such forecasts, is estimated. Because the relationship between the quality and value of forecasts is highly nonlinear, the need to explicitly determine value‐of‐information estimates, rather than relying on quality as a surrogate for value, is made clear.

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