Abstract:

Influential theories of the decision making process hold that a choice is made once the cumulative weight of noisily sampled information reaches a desired level. While these theories were originally motivated as optimal solutions to statistical problems, the extent to which people optimally spend time deliberating is less well explored. I conduct an experimental test of optimality in a setting where the speed of information processing reflects the difference in value between options. In this case, spending a long time without having arrived at a conclusion signals that the problem is both hard and low-value, so the confidence level required to trigger a decision should decline over time. I find that a recently developed theory of the optimal time-varying threshold improves model fit by accurately predicting observed truncation of response time tails. Principles of optimality may thus help account for patterns of choice and response time that characterize the process of deliberation.