A statistical test for the optimality of deliberative time allocation


Whenever we make a choice, we also must decide how much time to spend making it. Many theories of decision making crucially assume that this deliberation perfectly balances the costs of time expenditure and the benefits of better decisions. However, might we “overthink” or “underthink” decisions? Here I propose and implement a method to precisely determine whether people are optimally spending their time on deliberation, accounting for individual preferences. The method consists of checking consistency of underlying preferences for time versus reward when incentives changes, which is a necessary condition for optimality. I measure choices and response times of human participants in motion-discrimination tasks, and find significant departures from optimality when task difficulty and monetary incentives are varied. I also assess a further implication of optimality which applies when the ease of decision making reflects the difference in value between options: as the amount of time already spent deliberating on a problem grows, the standard of confidence required to make a decision should fall. I conduct the first test of new theoretical results by Fudenberg et al. (2015) that characterize the decision rule in this setting. Model fits indicate that participants are sensitive to the information that elapsed time provides about the value of continued deliberation, especially once they have experience with the task. Thus principles of optimality help capture certain facets of deliberative behavior.

Last updated on 11/15/2017