Uncertainty in economic models of climate-change impacts

Uncertainty is poorly represented in existing studies of climate-change impacts. Methods that have been used to characterize uncertainty in the literature are described and the limitations of each discussed. It is found that two broad characterizations are useful. A large number of studies are based on several specific scenarios or attempt to randomize selected variables in their deterministic economic models. Other studies describe individual or collective reaction to risk. The first category falls short of an adequate representation of uncertainty by focusing primarily on a few values of variables included to capture variability. The second group of studies tend to focus more on behavior than impacts. What is needed are Monte Carlo type simulations where randomness is apparent in a series of independent draws from a distribution suitably adjusted for climate change. Some of the benefits of improvements in the characterization of uncertainty are discussed.