Valuing climate forecasts for midwestern grain producers
Mazzocco, Michael Anthony
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https://hdl.handle.net/2142/22274
Description
Title
Valuing climate forecasts for midwestern grain producers
Author(s)
Mazzocco, Michael Anthony
Issue Date
1989
Doctoral Committee Chair(s)
Sonka, Steven T.
Department of Study
Agricultural and Consumer Economics
Discipline
Agricultural and Consumer Economics
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Economics, Agricultural
Language
eng
Abstract
Climate effects on corn and soybean production on two representative midwestern grain farms are incorporated into production function estimates by using physiologic crop growth simulation models over fourteen years of weather data and different combinations of management decisions. Model producers are assumed to maximize a net return function. Using dynamic programming, the value of the net return functions and the associated optimal crop decisions are identified for different prior climate expectations and different designs of climate forecasts.
Climate forecasts are shown to have more value in east central Illinois than in central Iowa. Much of this value relates to adjusting the amount and timing of nitrogen application for corn production. Climate forecasts are shown to have value in crop selection when the price relationship between corn and soybeans is in a competitive range. Forecasts with more discrete outcome categories have more value than those with fewer categories, although slight decreases in the accuracy of the less detailed forecasts do not detract from their value. Management decisions included in the soybean production functions do not exhibit sufficient flexibility or responsiveness to climate for soybean climate forecasts to have value.
Ambiguity theory is used as an alternative to risk theory to develop different assumptions on the decision maker's prior information. The different assumptions on prior information are shown to strongly impact the value of information.
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