Identification and estimation of entry games under symmetry of unobservables

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.