Learning and Noisy Equilibrium Behavior in an Experimental Study of Imperfect Price Competition

We consider a duopoly pricing game with a unique Bertrand-Nash equilibrium. The high-price firm has a nonvanishing market share, however, and intuition suggests that observed prices may be positively related to this market share. This relationship is implied by a model in which players make noisy (logit) best responses to expected payoff differences. The resulting logit equilibrium model was used to design an experiment in which the high-price firm's market share varies. The model accurately predicts the final-period price averages. A naive learning model predicts the observed differences in the time paths of average prices