A Costly-information Foundation for Psychometric Curves

Abstract

We study a binary choice problem in which an agent chooses between two actions whose payoff depends on a continuous state. The agent chooses how much effort to invest in learning about the state. Equivalently, we can think of the state as the strength of a stimulus, with the agent exerting costly effort to be more responsive to it. Taking as given the Fisher information cost introduced by Hebert and Woodford (2021), we analyze the optimal state-dependent choice rule using a variational approach. The main result is that agents' optimal response is an S-shaped function of the state under mild conditions. This prediction is aligned with the widely documented psychometric curve response profile observed in the experimental literature in psychology and economics.