Further Results on the Weak Instruments Problem of the System GMM Estimator in Dynamic Panel Data Models

36 Pages Posted: 10 May 2017

See all articles by Kazuhiko Hayakawa

Kazuhiko Hayakawa

Hiroshima University

Meng Qi

Hiroshima University

Date Written: May 9, 2017

Abstract

In this paper, we investigate the weak instruments problem of the generalized method of moments (GMM) estimator for dynamic panel data models. Bun and Windmeijer (2010) demonstrate that the system GMM estimator combining models in first differences and levels suffers from the weak instruments problem when the variance ratio of the individual fixed effects to the errors is large, mainly because of the model in levels. In this paper, we alternatively consider first-difference and level models transformed by using the forward GLS transformation and demonstrate that this transformation yields a higher concentration parameter compared with the original models. This finding indicates that the proposed transformation yields stronger instruments despite the same first-differenced variables being used as instruments. 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 for the first-difference and level models and that the performance of the new system GMM estimator is reasonable even when the variance ratio is large.

Suggested Citation

Hayakawa, Kazuhiko and Qi, Meng, Further Results on the Weak Instruments Problem of the System GMM Estimator in Dynamic Panel Data Models (May 9, 2017). Available at SSRN: https://ssrn.com/abstract=2965281 or http://dx.doi.org/10.2139/ssrn.2965281

Kazuhiko Hayakawa (Contact Author)

Hiroshima University ( email )

Japan

Meng Qi

Hiroshima University ( email )

739-0046
Japan

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