Identification and estimation of entry games under symmetry of unobservables
针对完全信息两玩家进入博弈，提出基于不可观测变量对称性的新识别与估计方法，无需均衡选择或参数分布假设，估计量具有根号n一致性，并提供了对称性检验。蒙特卡洛模拟和折扣零售商进入博弈的应用表明方法有效。
Summary This paper provides a new point identification and estimation method for two-player entry games with complete information, based on symmetry of unobservables. Neither equilibrium selection nor parametric distributional assumptions are required. In addition, a weaker support condition is used relative to the existing literature. Unlike other semiparametric estimators, the estimator proposed here is $\sqrt{n}$-consistent. A test of the required symmetry condition is provided. Monte Carlo evidence shows that the estimator performs well with moderate sample sizes, and is robust to unimodal and multimodal error distributions. The estimator is applied to an entry game of discount retailers. The results suggest that researchers should apply the normality assumption with caution.