Alternative Over-identifying Restriction Tests in the GMM Estimation of Panel Data Models

78 Pages Posted: 15 Apr 2013 Last revised: 29 Jul 2018

Date Written: June 20, 2018

Abstract

A new over-identifying restriction test in the generalized method of moments (GMM) estimation of panel data models is proposed. In contrast to the conventional over-identifying restriction test, where the sample covariance matrix of the moment conditions is used in the weighting matrix, the proposed test uses a block diagonal weighting matrix constructed from the efficient optimal weighting matrix. It is shown that the proposed test statistic asymptotically follows the weighted sum of the chi-square distribution with one degree of freedom. A detailed local power analysis is provided for dynamic panel data models, and it is demonstrated that the new test has a comparable power to the conventional J test in many cases. The Monte Carlo simulations reveal that the proposed test has a substantially better size property than the conventional test does.

Keywords: panel data; GMM; over-identification test; system of equations

Suggested Citation

Hayakawa, Kazuhiko, Alternative Over-identifying Restriction Tests in the GMM Estimation of Panel Data Models (June 20, 2018). Available at SSRN: https://ssrn.com/abstract=2250624 or http://dx.doi.org/10.2139/ssrn.2250624

Kazuhiko Hayakawa (Contact Author)

Hiroshima University ( email )

Japan

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