This award funds research in economic theory. The project seeks to advance how economists study individuals who must make decisions when the environment and possible outcomes are uncertain. People often appear to avoid these kinds of situations, preferring to safe and well-understood options over choices that seem risky, uncertain, or ambiguous in their benefits. Understanding how risk and ambiguity affect choices is important not only for predicting a host of individual decisions, such as saving, investment, education, and job selection. This kind of economic theory is also important assessing the impact of different policies, technological changes, or other economic factors on the economy. Not surprisingly, ambiguity aversion and pessimistic attitudes towards risk have played an ever-increasing role in applications to macroeconomics and finance. The research effort will address a gap in our current economic theory. It will provide a better model of how individuals make use of new information about risky and ambiguous situations. The model will also help us understand how attitudes towards risk and ambiguity compare across individuals. Finally, the new theory may offer sharper predictions. The team will use an approach based on evolution and adaptation to build this new theory. The project could develop new tools for use by business managers and policymakers, who often must form accurate predictions of how customers, employees, citizens, and other individuals will behave in risky situations.

While there is now an abundance of research providing decision-theoretic foundations to models of ambiguity and risk aversion, much less is known about how evolution might select between competing models and approaches. This project will advance basic theory regarding risk and ambiguity by providing an evolutionary foundation for a new model, the adaptive model, that imposes significant structure on ambiguity and risk aversion. Important features will be that preferences should be dynamically consistent, even at the cost of consequentialism, and that different ambiguity preferences go hand in hand with departures from expected utility theory in the context of risk. Depending on how effectively individuals of a genotype can adapt the expression of their phenotype, the adaptive model can nest variants of several prominent models in the literature as special cases. This will permit the evaluation of these models based on a new set of primitive assumptions and will extend the general insights about the structure of preferences under uncertainty and their updating to applications of those models in the contexts of finance, macro and policy choice. The project will also help strengthen the interdisciplinary bridge between the fields of decision theory and evolutionary biology.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Division of Social and Economic Sciences (SES)
Type
Standard Grant (Standard)
Application #
1851664
Program Officer
Nancy Lutz
Project Start
Project End
Budget Start
2019-07-15
Budget End
2022-06-30
Support Year
Fiscal Year
2018
Total Cost
$404,913
Indirect Cost
Name
Duke University
Department
Type
DUNS #
City
Durham
State
NC
Country
United States
Zip Code
27705