Inference for Iterated GMM Under Misspecification

S-Tier
Journal: Econometrica
Year: 2021
Volume: 89
Issue: 3
Pages: 1419-1447

Authors (2)

Bruce E. Hansen (not in RePEc) Seojeong Lee (Seoul National University)

Score contribution per author:

4.022 = (α=2.01 / 2 authors) × 4.0x S-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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).

Technical Details

RePEc Handle
repec:wly:emetrp:v:89:y:2021:i:3:p:1419-1447
Journal Field
General
Author Count
2
Added to Database
2026-01-25