Steady State Learning and the Code of Hammurabi

The code of Hammurabi specified a “trial by surviving in the river” as a way of deciding whether an accusation was true. This system is puzzling for two reasons. First, it is based on a superstition: We do not believe that the guilty are any more likely to drown than the innocent. Second, if people can be easily persuaded to hold a superstitious belief, why such an elaborate mechanism? Why not simply assert that those who are guilty will be struck dead by lightning? We attack these puzzles from the perspective of the theory of learning in games. We give a partial characterization of patiently stable outcomes that arise as the limit of steady states with rational learning as players become more patient. These “subgame-confirmed Nash equilibria” have self-confirming beliefs at certain information sets reachable by a single deviation. We analyze this refinement and use it as a tool to study the broader issue of the survival of superstition. According to this theory Hammurabi had it exactly right: his law uses the greatest amount of superstition consistent with patient rational learning.