Econometrica Vol. 89 No. 3 2021

Inference for Iterated GMM Under Misspecification

Bruce E. Hansen¹; Seojeong Lee²

¹ Department of Economics, University of Wisconsin. · ² School of Economics, University of New South Wales

Abstract

This paper develops inference methods for the iterated overidentified Generalized Method of Moments (GMM) estimator. We provide conditions for the existence of the iterated estimator and an asymptotic distribution theory, which allows for mild misspecification. Moment misspecification causes bias in conventional GMM variance estimators, which can lead to severely oversized hypothesis tests. We show how to consistently estimate the correct asymptotic variance matrix. Our simulation results show that our methods are properly sized under both correct specification and mild to moderate misspecification. We illustrate the method with an application to the model of Acemoglu, Johnson, Robinson, and Yared (2008).

DOI

10.3982/ecta16274

Volume

89

Issue

3

Pages

1419-1447

Language

en

Sources

bibtex:phds-export.bib openalex crossref

Cite

APA 7 MLA 9 Chicago (author–date) Harvard Elsevier Harvard (JFE, JBF…) The Accounting Review Academy of Management American Marketing Association INFORMS (Management Science) Copy citation Copied ✓