Comparative Learning Dynamics*

We study economic environments in which agents make choices on the basis of relative performance criteria and call the associated class of dynamic adjustment rules comparative dynamics. We distinguish two classes of learning behavior: learning from the population experience (imitative dynamics) and learning only from one's own experience (introspective dynamics). Paradoxically, for a broad class of models, comparing stochastically stable states across dynamics, agent payoffs are lower for imitative than introspective dynamics—mimicking best practice in the population is counterproductive.