Estimating dynamic games of oligopolistic competition: an experimental investigation

We evaluate standard assumptions in the estimation of dynamic oligopoly models with laboratory data. Using an entry/exit game, we estimate structural parameters under the assumption that the data are generated by a Markov-perfect equilibrium and subsequently predict counterfactual behavior. If behavior was collusive, however, the assumption would be violated and one would mispredict counterfactuals. The laboratory allows us to compare predicted behavior to true counterfactuals implemented as treatments. Our main finding is that prediction errors due to collusion are modest in size. We also document a different deviation from equilibrium behavior (inertia) that can lead to large prediction errors.