Revealed Indifference: Using Response Times to Infer Preferences

Revealed preference is the dominant approach for inferring preferences, but it relies on discrete, stochastic choices. The choice process also produces response times (RTs) which are continuous and can often be observed in the absence of informative choice outcomes. Moreover, there is a consistent relationship between RTs and strength-of-preference, namely that people make slower decisions as they approach indifference. This relationship arises from optimal solutions to sequential information sampling problems. Here, we investigate several ways in which this relationship can be used to infer preferences when choice outcomes are uninformative or unavailable. We show that RTs from a single binary-choice problem are enough to usefully rank people according to their degree of loss aversion. Using a large number of choice problems, we are further able to recover individual utility-function parameters from RTs alone (no choice outcomes) in three different choice domains. Finally, we are able to use long RTs to predict which choices are inconsistent with a subject’s utility function and likely to later be reversed. These results provide a proof of concept for a novel “method of revealed indifference”.