Root-NConsistent Estimation of a Panel Data Binary Response Model With Unknown Correlated Random Effects
提出一种面板数据二元响应模型的估计方法，对个体效应施加弱约束，估计量具有根号n一致性和渐近正态性，允许误差项异方差，且计算简单。模拟和实证表明其有用性。
In this article, we consider the estimation of a panel data binary response model with a weak restriction imposed on the individual specific effects. Our estimator is n$\sqrt{n}$-consistent and asymptotically normal under reasonable regularity conditions. Furthermore, we allow the error terms to be heteroscedastic over time. The proposed estimator has a closed form expression and thus is very easy to compute. Simulations and the empirical illustration demonstrate the usefulness of our proposed estimator.