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Further Results on the Weak Instruments Problem of the System GMM Estimator in Dynamic Panel Data Models
Author(s) -
Hayakawa Kazuhiko,
Qi Meng
Publication year - 2020
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/obes.12336
Subject(s) - estimator , generalized method of moments , transformation (genetics) , mixture model , complement (music) , monte carlo method , panel data , econometrics , mathematics , computer science , statistics , biochemistry , chemistry , complementation , gene , phenotype
In this paper, we investigate the weak instruments problem of the generalized method of moments (GMM) estimator for dynamic panel data models. Specifically, we complement Bun and Windmeijer (2010) by considering the alternative first‐difference and level models transformed by the forward GLS transformation. We demonstrate that this transformation yields a higher concentration parameter compared with the original models. This indicates that the proposed transformation yields stronger instruments even though the instruments used are identical. The Monte Carlo simulation results show that the system GMM estimator for the transformed model, called the forward system GMM estimator , performs better than the conventional system GMM estimator.