On the Magnification of Small Biases in Decision-Making
42 Pages Posted: 25 Jun 2019 Last revised: 11 Sep 2019
Date Written: June 20, 2019
We analyze a setting in which an actor chooses between N ex ante identical options. She can exert effort to learn about the quality of each option, but can ultimately choose only one. There are up to N! unique optimal effort vectors, and each is asymmetric: a large amount of effort is expended learning about one arbitrarily chosen option, less on another, even less on a third, etc. This implies asymmetric likelihoods of each item being chosen. If the actor has an infinitesimal bias in favor of one option, then the actor selects an effort vector that maximizes the likelihood of her favored option being chosen. Small biases are magnified, sometimes enormously. We also show that a glass ceiling can arise, in which favored types are increasingly prevalent as one ascends the corporate ladder. These results have implications for portfolio selection (e.g., home bias, socially responsible investment funds), hiring (e.g., CEO choice, the glass ceiling), start-up funding, and a variety of other applications.
Keywords: choice, bias, portfolio selection, glass ceiling
JEL Classification: D83, D91, J71, G41
Suggested Citation: Suggested Citation