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zbMATH Open
Article . 2021
Data sources: zbMATH Open
Econometrica
Article . 2021 . Peer-reviewed
Data sources: Crossref
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Inference for Iterated GMM Under Misspecification

Inference for iterated GMM under misspecification
Authors: Hansen, BE; Lee, S;

Inference for Iterated GMM Under Misspecification

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).

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Australia
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Keywords

anzsrc-for: 3801 Applied Economics, anzsrc-for: 3803 Economic theory, 330, Estimation in multivariate analysis, 38 Economics, Analysis of variance and covariance (ANOVA), generalized method of moments, anzsrc-for: 1401 Economic Theory, misspecification, covariance matrix estimation, overidentification, 3801 Applied Economics, 3802 Econometrics, anzsrc-for: 1403 Econometrics, anzsrc-for: 38 Economics, Economic growth models, anzsrc-for: 1402 Applied Economics, Applications of statistics to economics, anzsrc-for: 3802 Econometrics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
33
Top 10%
Top 10%
Top 1%
Green