LEARNING TO BE IMPERFECT - THE ULTIMATUM GAME

This paper studies interactive learning processes that are subject to constant perturbations or ''noise.'' We argue that payoffs in the Ultimatum Game are such that responders are more apt to be ''noisy'' than are proposers and show that as a result the learning process readily leads to outcomes that are Nash equilibria but not subgame-perfect. We conclude that game theorists should not restrict attention to the subgame-perfect equilibrium when predicting laboratory behavior in the Ultimatum Game. (C) 1995 Academic Press, Inc.