A Doubly Corrected Robust Variance Estimator for Linear GMM

Hwang, Jungbin and Kang, David and Lee, Seojeong (2020) A Doubly Corrected Robust Variance Estimator for Linear GMM. Journal of Econometrics. ISSN 0304-4076 (In Press)

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Abstract

We propose a new finite sample corrected variance estimator for the linear generalized method of moments (GMM) including the one-step, two-step, and iterated estimators. Our formula also corrects the over-identification bias in variance estimation on top of the commonly used finite sample correction of Windmeijer (2005), which corrects the bias from estimating the efficient weight matrix, so is doubly corrected. An important feature of the proposed double correction is that it automatically provides robustness to misspecification of the moment condition. In contrast, the conventional variance estimator and the Windmeijer correction are inconsistent under misspecification. That is, the double correction formula proposed in this paper provides a convenient way to obtain improved inference under correct specification and robustness against misspecification at the same time.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Econometrics
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2604
Subjects:
ID Code:
148276
Deposited By:
Deposited On:
16 Oct 2020 10:05
Refereed?:
Yes
Published?:
In Press
Last Modified:
20 Oct 2020 11:15