Estimating dynamic games of oligopolistic competition: an experimental investigation
用实验室数据评估动态寡头模型的标准估计方法，发现如果行为是合谋的，假设马尔可夫完美均衡会导致预测偏差，但偏差幅度较小；同时发现惯性行为可能造成较大预测误差。
Abstract 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.