We investigate the impact of reputation in a laboratory experiment. We do so by varying whether the past choices of a long-run player are observable by the short-run players. Our framework allows for reputation to have either a beneficial or a harmful effect on the long-run player. We find that reputation is seldom harmful and its beneficial effects are not as strong as theory suggests. When reputational concerns are at odds with other-regarding preferences, we find the latter overwhelm the former. (JEL C91, D12, D82, D83, Z13)

This paper considers learning rules for environments in which little prior and feedback information is available to the decision maker. Two properties of such learning rules are studied: absolute expediency and monotonicity. Both require that some aspect of the decision maker's performance improves from the current period to the next. The paper provides some necessary, and some sufficient conditions for these properties. It turns out that there is a large variety of learning rules that have the properties. However, all learning rules that have these properties are related to the replicator dynamics of evolutionary game theory. For the case in which there are only two actions, it is shown that one of the absolutely expedient learning rules dominates all others.