Penalized Generalized Method of Moments with Many Weak Instrumental Variables
2017/03/28
研討會日期 : 2017-03-28
時間 : 15:00
主講人 : Professor Qingliang Fan
主持人 : Professor Yu-Chin Hsu
地點 : Conference Room B110
演講者簡介 : Professor Fan received his Ph.D. from North Carolina State University in 2012. He is currently an Assistant Professor at Wang Yanan Institute for Studies in Economics (WISE), Xiamen University. His research interests include Theoretical and applied econometrics, big data.
演講摘要 : This paper addresses the issue of statistical inference for instrumental variable models that are weakly identified. We propose a nuclear (Ky Fan) norm regularized two step GMM method with growing number of weak instrumental variables. In choosing the regularization parameter we adopt the Donald and Newey (1990) criterion which aims at minimization of the MSE. The main innovation of our paper is that we rely on the ‘blessing of dimensionality’, specifically, the many weak IVs are welcoming in the efficient estimation of structural parameters. And we use the penalized GMM method to control for the bias of many weak IV. We show the asymptotic property of our estimator which is consistent and asymptotic normal with optimal variance. We provide simulation results which demonstrate that our method performs favorably compared to other existing methods in finite sample. We also apply our method in the classic returns to education studies.
