Averaging GMM Estimator Robust to Misspecification
2016/12/20
研討會日期 : 2016-12-20
時間 : 14:30
主講人 : Professor Xu Cheng
主持人 : Professor Chu-An Liu
地點 : Conference Room B110
演講者簡介 : Prof. Cheng received her Ph.D. in Economics from Yale University in 2010. She is currently an Associate Professor at University of Pennsylvania. Her research fields are Econometric Theory and Applied Econometrics.
演講摘要 : This paper studies the averaging GMM estimator that combines a conservative GMM estimator based on valid moment conditions and an aggressive GMM estimator based on both valid and possibly misspecified moment conditions, where the weight is the sample analog of an infeasible optimal weight. We establish asymptotic theory on uniform approximation of the upper and lower bounds of the finite-sample risk difference between two estimators, which is used to show that the averaging estimator uniformly dominates the conservative estimator by reducing the risk under any degree of misspecification. Extending seminal results on the James-Stein estimator, the uniform dominance is established in non-Gaussian semiparametric nonlinear models. The simulation results support our theoretical findings. The proposed averaging estimator is applied to estimate the human capital production function in a life-cycle labor supply model.
