Redundancy of Moment Conditions in Restricted GMM Estimation

Hailong Qian

Author information




Department of Economics, John Cook School of Business, Saint Louis University, St. Louis, MO 63108, USA

E-mail: qianh@slu.edu

Abstract




Using a novel approach to calculating the rank of the difference of two asymptotic variance matrices, The author derives the necessary and sufficient conditions for an extra set of moment conditions to be redundant given a set of moment conditions in GMM estimation with general nonlinear restrictions. The necessary and sufficient conditions derived in this paper include as a special case the redundancy of moment conditions for GMM estimation without restrictions that was first derived by Breusch et al. (1999). Therefore this paper advances the research on redundancy of moment conditions from unrestricted GMM estimation to a larger class of GMM estimation. To show their usefulness, the main results of the current paper are applied to instrumental variables estimation of linear regression models and the efficient estimation of seemingly unrelated regressions models, subject to restrictions.

 Keywords




GMM, restricted GMM estimation, moment conditions, redundancy of moment conditions, efficiency

Cite this article




Hailong Qian. Redundancy of Moment Conditions in Restricted GMM Estimation. Front. Econ. China, 2016, 11(3): 468‒497 https://doi.org/10.3868/s060-005-016-0025-7


About ISE | Contact ISE | Links | SUFE-IAR | SUFE
All Rights Reserved:2020 Institute for Advanced Research,
Shanghai University of Finance and Economics.777 Guoding Rd, Shanghai, PRC,200433