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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 ISSN 2452-3062. (In Press)
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Official URL: https://doi.org/10.1016/j.ecosta.2021.10.010
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 | ||||||||
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| Subjects: | H Social Sciences > HB Economic Theory Q Science > QA Mathematics |
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| 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: |
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| DOI: | 10.1016/j.ecosta.2021.10.010 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | In Press | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| Date of first compliant deposit: | 19 October 2021 | ||||||||
| Date of first compliant Open Access: | 11 November 2022 | ||||||||
| RIOXX Funder/Project Grant: |
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