Generalized Method of Moments with Grouped Heterogeneous Validity of Moment Conditions in Panel Data Models
报告人： Zhan Gao（University of Southern California）
时间：2024-09-26 15:10-17:00
地点：Zoom Meeting ID: 936 5315 7690 Passcode：123456
Abstract:
This paper provides a unified framework for the selection of valid moment conditions and detection of latent group structure based on the moment condition validity in general nonlinear generalized method of moments (GMM) panel data models, which can accommodate a diverging number of moment conditions and group-specific heterogeneous validity of moment conditions across agents. The proposed method integrates the pairwise adaptive fused Lasso and the adaptive Lasso regularization into the GMM estimation. The estimator is shown to be consistent and achieve classification and moment selection consistency simultaneously. The asymptotic distribution of a post-regularization estimator is derived, and its oracle properties are established. The finite-sample performance of the proposed method is evaluated through a Monte Carlo simulation experiment. The method is applied to empirically investigate the impact of the agricultural productivity shocks on rural-to-urban migration in China.
About the Speaker:
I am a Ph.D. candidate in economics at University of Southern California. Before coming to LA, I obtained M.Phil. in Economics and B.Sc. in Mathematics from the Chinese University of Hong Kong. My research interests are mainly in econometrics.
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