This award funds research in economic decision theory. There are four distinct projects. Each seeks to develop new methods for incorporating aspects of human behavior into formal mathematical models of decision making.

The first project builds on previous work by other scholars (Kreps-Porteous and Epstein-Zin) that developed recursive utility models. This project models the premium that an individual with preferences represented by this kind of utility function would pay for the early resolution of uncertainty; in other words, what fraction of his income would the individual be willing to give up in order to learn his future consumption levels? This premium can be used as a criterion for the choice of parameter values in recursive utility models.

The second project studies boundedly optimizing decision amkers operating in otherwise standard competitive financial markets with standard preferences. The new theory yields a number of predictions: limited market participation, ex post consumption heterogeneity, and high volatility of asset prices as compared to the fundamentals.

Project Three provides a novel axiomatization of quasi-hyperbolic discounting. This model of preferences over time is increasingly widely used in applications of behavioral economics. The proposed axiomatization and the implied method of parameter measurement are useful for experimental work. These methods make it possible to elicit short run discount factors independent of utility functions. The goal is to develop a method that will eliminate experimental confounds that are unavoidable with current methods.

Project Four studies a model of individual decisions makers who do not fully recognize the extent to which their future choices disregard their current preferences. The project proposes a method of eliciting such inaccurate beliefs about the future. The goal is to explain such behavior by studying how these failures of learning can persist in the long run.

Models of dynamic decisions are key to understanding many economic phenomena, such as savings, investment, taxation, and growth. This research will improve the toolbox available to model these phenomena. The result will be new methods to analyze the effects of economic behavior and economic policy. The methods will be useful not just to economists but also to decision theorists and financial scholars.

Agency
National Science Foundation (NSF)
Institute
Division of Social and Economic Sciences (SES)
Type
Standard Grant (Standard)
Application #
1123729
Program Officer
Nancy A. Lutz
Project Start
Project End
Budget Start
2011-08-01
Budget End
2014-07-31
Support Year
Fiscal Year
2011
Total Cost
$272,935
Indirect Cost
Name
Harvard University
Department
Type
DUNS #
City
Cambridge
State
MA
Country
United States
Zip Code
02138