Rubas et al. (2006) presented a discussion on four methodologies economists use to model the decision-making process: decision theory, general equilibrium modeling, game theory, and mechanism design theory and suggested that climate forecast issues are ripe for more innovative and rigorous studies that can lead to theoretical advances in the economics of information as well as advances in climate sciences.
The most widely used form of decision theory assumes that preferences among risky alternatives can be described by maximizing net payoffs. The value of climate forecasts is the expected difference between the net payoffs when the forecasts are used to make optimal decisions, and the net payoffs when decisions are made optimally using only prior knowledge.
Game theory recognizes that the choices of individuals are interlinked. Unlike decision theory, in game theory, researchers must account for interactions between decision-makers and the combined effect their decisions may have on each other's payoffs.
General equilibrium modeling attempts to account for all decision-makers, all possible decisions, and their impacts on the market prices of all relevant commodities. Studies have used general equilibrium concepts to develop simpler partial equilibrium models, sector models, and trade models of particular crops to examine the effects of climate forecast use (Chen and McCarl 2000; Chen et al. 2002).
Decision theory, game theory, and general equilibrium modeling vary in the number of decision-makers and decisions modeled, but all assume that the rules of the process are fixed. In mechanism design, the rules players operate under become part of the process. In climate forecast applications, the goal is to find the set of market and institutional rules that maximize the net benefits associated with climate forecast use.
Rubas et al. (2006) explained that decision-making using climate forecasts has generally been treated by the social sciences as an applied issue and not as an issue that can be used to advance theory. She argued that combining research on technology adoption, climate forecasts, and the economics of information would allow researchers to combine cutting-edge issues from different disciplines. Economic thinking applied to climate applications has already: (a) contributed to our understanding of how to incorporate uncertain information into decision-making, (b) proven to be a good bridge between the physical and social sciences and decision-makers, by translating climate-sensitive biophysical information into viable resource allocation choices, and (c) revealed the conditions under which decision-makers can benefit from climate information.
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