An approximated exponentially tilted empirical likelihood estimator of moment condition models
提出一种近似指数倾斜经验似然估计量，通过二阶近似避免嵌套优化，计算简单，且与经验似然估计量二阶渐近等价，在模型误设下仍n收敛。
.This study proposes an approximated estimator for moment condition models. Our estimator approximates the exponentially tilted empirical likelihood (ETEL) estimator in Schennach (2007) by using a second-order approximation of implied probabilities (IPs) for the exponential tilting (ET). The resulting approximated ETEL estimator generates positive IPs. As the nested optimization of ETEL and EL is avoided, it is computationally simple. It is second-order asymptotically equivalent to the EL estimator. In particular, it has the same O(n−1) bias as EL. It also has the same O(n−2) variance as EL. Like ET and ETEL estimators, it is n convergent under model misspecification, while the EL estimator may not be.