Bounded Rationality and Complexity in Individual Decision Problems

Theodoros Diasakos, University of California, Berkeley

Abstract

This paper develops a model of endogenous bounded rationality due to search costs arising from the complexity of the decision problem. The decision-maker is not required to know the entire structure of the problem when making choices. She can think ahead, through costly search, to reveal more details of the problem. The costs of search are not assumed exogenously, but inferred from revealed preferences through her choices. Thus, bounded rationality and its extent emerge endogenously: as problems become simpler or as the benefits of deeper search become larger relative to its costs, the choices more closely resemble those of a rational agent. For a fixed problem, the costs of search will vary across agents. This variation explains why the disparity between observed choices and those prescribed under rationality differs across decision-makers. Under additional assumptions, calibration of search costs suggests predictions and testable implications of the model. Through three applications,this approach of endogenous complexity costs is shown to be consistent with violations of timing independence in temporal framing problems, dynamic inconsistency and diversification bias in sequential versus simultaneous choice problems, and with plausible but contrasting risk attitudes across small- and large-stakes gambles.