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GMM with nearly-weak identification

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Bertille, Antoine and Renault, Eric (2021) GMM with nearly-weak identification. Econometrics and Statistics . doi:10.1016/j.ecosta.2021.10.010 (In Press)

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Official URL: https://doi.org/10.1016/j.ecosta.2021.10.010

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Abstract

A unified framework for the asymptotic distributional theory of GMM with nearly-weak instruments is provided. It generalizes a previously proposed framework in two main directions: first, by allowing instruments’ weakness to be less severe in the sense that some GMM estimators remain consistent, while featuring low precision; and second, by relaxing the so-called ”separability assumption” and considering generalized versions of local-to-zero asymptotics without partitioning a priori the vector of parameters in two subvectors converging at different rates. It is shown how to define directions in the parameter space whose estimators come with different rates of convergence characterized by the Moore-Penrose inverse of the Jacobian matrix of the moments. Furthermore, regularity conditions are provided to ensure standard asymptotic inference for these estimated directions.

Item Type: Journal Article
Subjects: H Social Sciences > HB Economic Theory
Q Science > QA Mathematics
Divisions: Faculty of Social Sciences > Economics
Library of Congress Subject Headings (LCSH): Moments method (Statistics), Asymptotic distribution (Probability theory), Estimation theory
Journal or Publication Title: Econometrics and Statistics
Publisher: Elsevier
ISSN: 2452-3062
Official Date: 2021
Dates:
DateEvent
2021Published
11 November 2021Available
16 October 2021Accepted
DOI: 10.1016/j.ecosta.2021.10.010
Status: Peer Reviewed
Publication Status: In Press
Access rights to Published version: Restricted or Subscription Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
UNSPECIFIEDSocial Sciences and Humanities Research Council of Canadahttp://dx.doi.org/10.13039/501100000155
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