Testing, Estimation in GMM and CUE with Nearly-Weak Identification

DOI10.1080/07474930903451599zbMath1187.62040OpenAlexW2084801034WikidataQ57441269 ScholiaQ57441269MaRDI QIDQ3564824

Mehmet Caner

Publication date: 26 May 2010

Published in: Econometric Reviews (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/07474930903451599

zbMATH Keywords

rate of convergenceempirical processtriangular central limit theorem

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Asymptotic distribution theory in statistics (62E20) Hypothesis testing in multivariate analysis (62H15) Central limit and other weak theorems (60F05) Asymptotic properties of parametric tests (62F05)

Related Items (13)

On the behaviour of the GMM estimator in persistent dynamic panel data models with unrestricted initial conditions ⋮ Weak Instrumental Variables Models for Longitudinal Data ⋮ Asymptotic F tests under possibly weak identification ⋮ Estimation and inference in adaptive learning models with slowly decreasing gains ⋮ Conditional moment models under semi-strong identification ⋮ Testing identification strength ⋮ Robust inference in nonlinear models with mixed identification strength ⋮ Efficient minimum distance estimation with multiple rates of convergence ⋮ Maximum likelihood estimation and uniform inference with sporadic identification failure ⋮ On the performance of block-bootstrap continuously updated GMM for a class of non-linear conditional moment models. Moving block bootstrap inference under weak identification ⋮ Near exogeneity and weak identification in generalized empirical likelihood estimators: many moment asymptotics ⋮ Editors' introduction ⋮ Finite sample properties of the GMM Anderson–Rubin test

Cites Work

• Large Sample Properties of Generalized Method of Moments Estimators
• Boundedly pivotal structural change tests in continuous updating GMM with strong, weak identification and completely unidentified cases
• Testing for weak identification in possibly nonlinear models
• Discontinuities of weak instrument limiting distributions.
• Weak convergence and empirical processes. With applications to statistics
• Efficient GMM with nearly-weak instruments
• LASSO-TYPE GMM ESTIMATOR
• GMM with Weak Identification
• Estimation of the Parameters of a Single Equation in a Complete System of Stochastic Equations

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