Doctoral Dissertation Research in Economics: Uncertainty Equivalents

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This award funds a series of choice experiments that test new methods for eliciting individual risk preferences. These methods have been developed from an innovative theory about how to model the way people make decisions in situations when certainty and uncertainty are combined. If the methods prove to have predictive power, this will be evidence in support of the new theory.The new theory starts with a general observation about widely observed behavior that does not fit the expected utility models widely used in the past by economists. The Allais paradox, prospect theory probability weighting, and small states risk aversion all arise in situations when certainty and uncertainty are combined. The key idea here is to model two different utility functions to represent preferences: a certainty function and an uncertainty function. The ways that actual behavior deviate from expected utility may be driven by differences between certain and uncertain utility.The award also funds an experiment on how markets for insurance are affected by possible ambiguity aversion.The broader impacts of this project include the interdisciplinary impact. A wide range of scientists from public health to political science are now using tools from behavioral economics. Policy makers are finding that this kind of decision modelling suggests new ways to reach policy goals in an effective way. If the new theory is supported by these experiments, it should be rapidly adopted by these communities.