This award funds research in economic theory that develops a model of economic decisions that takes into account bounded rationality. The PI will replace the usual maximizing behavior assumed in standard economics with an alternative assumption of "sparse maximizing". This results in a model that is tractable to compute while reflecting basic psychological forces governing limited attention. The PI then goes on to use this starting assumption in a variety of microeconomic models. This includes deriving demand curves, determining the outcome of simple exchange economies, and analyzing dynamic choices such as consumption over the life cycle.
Specifically, the PI proposes a sparse max operation which generalizes the traditional max operator used in economics. The agent builds a simplified model of the world which is sparse, considering only the variables of first-order importance. Her stylized mental model and her resulting choices both derive from constrained optimization. The framework yields a behavioral version of many pillars of economics, including the basic theory of consumer demand and competitive equilibrium. The sparse max extends to dynamic contexts via spare dynamic programming, a behavioral version of traditional dynamic programming.
The framework allows for the exploration of a number of concrete issues, such as inattention to some variables like the interest rate, myopia, inertia in portfolio choice, and inattention to rare events. The framework gives us a new way to assess which parts of basic economics are robust to the assumption of perfect maximization.
The project contributes to broader societal goals by developing a new approach that may help policymakers better predict the effects of their actions on the economy.
