Predicting Human Cooperation in the Prisoner’s Dilemma Using Case-based Decision Theory

In this paper we show Case-based Decision Theory (Gilboa and Schmeidler, 1995) can explain the aggregate dynamics of cooperation in the repeated Prisoner’s Dilemma, as observed in the experiments performed by Camera and Casari (2009). Moreover, we find CBDT provides a better fit to the dynamics of cooperation than does the existing Probit model, which is the first time such a result has been found. We also find that humans aspire to a payoff above the mutual defection outcome but below the mutual cooperation outcome, which suggests they hope, but are not confident, that cooperation can be achieved; and we find that cognitive capacity, and not memory storage space, is the more significant constraint on human problem-solving in this context. This is the first empirical test of Case-based Decision Theory in a strategic, dynamic, and multi-agent experiment. This provides a different frame of reference to view the results of cooperation in the iterated prisoner’s dilemma that incorporates past experience as well as beliefs of future payoffs. JEL codes: D01, D83, C63, C72, C88