The Value of Frost Forecasting: A Bayesian Appraisal

Abstract

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.

Factors affecting the value of environmental predictions to the energy sector

“…The latter decision problem is also described by several governmental bodies in (Danish Ministry of Transport, 2006;WMO Secretariat, 2007;NAV Canada, 2002). Early papers applying a classical decision science approach include (Baquet et al, 1976), who quantified the value of frost forecasts to orchard operators deciding whether or not to run heaters. A more general theoretical framework for this valuation problem was provided by (Hilton, 1981) while (Kite-Powell 2005) applied the theory to an ocean environmental data application.…”

Decision‐maker expectations and the value of climate prediction information: conceptual considerations and preliminary evidence

“…These studies have generally employed the decision theory approach (Arrow, 1962;Simon, 1975) as their underlying paradigm, and have focussed on either short-term weather forecasts (e.g., Lave, 1963;Baquet et al, 1976) or longer-term climate predictions (e.g., Winkler et al, 1983;Mjelde et al , 1988). In general, these analyses examine characteristics of the forecasts (e.g., accuracy, lead time, reliability) necessary for climate predictions to have economic value (Winkler et al, 1983;Brown et al, 1986;Katz et al, 1982;Doll, 1971;Lave, 1963;Mjelde et al, 1988;Mazzocco, 1989).…”

Managerial evaluation of exogenous forecast sources

“…Alternately, the track record may be voluminous enough to estimate the relative frequency of all possible forecast-state pairs. This is the approach Baquet et al (1976) take in analyzing for fruit growers a large number of temperature forecasts in a short interval about 32°F. This paper concerns the managerial evaluation of exogenous forecast sources when the initial data are insufficient to allow the use of a relative frequency approach to assess the required probability distributions.…”