GMM inference when the number of moment conditions in large

DOI10.1016/S0304-4076(99)00014-7zbMath0941.62077WikidataQ127293311 ScholiaQ127293311MaRDI QIDQ1808550

José A. F. Machado, Roger W. Koenker

Publication date: 13 August 2000

Published in: Journal of Econometrics (Search for Journal in Brave)

zbMATH Keywords

asymptotic expansiongeneralized method of momentsGMM

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Estimation in multivariate analysis (62H12) Asymptotic distribution theory in statistics (62E20) Linear regression; mixed models (62J05)

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Cites Work

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• A central limit theorem applicable to robust regression estimators
• Multivariate regression models for panel data
• Asymptotic behavior of M-estimators of p regression parameters when \(p^ 2/n\) is large. I. Consistency
• Asymptotic behavior of M estimators of p regression parameters when \(p^ 2/n\) is large. II: Normal approximation
• Approximation of least squares regression on nested subspaces
• Asymptotics with increasing dimension for robust regression with applications to the bootstrap
• The Falstaff estimator
• Convergence rate of sieve estimates
• Efficient estimation of panel data models with sequential moment restrictions
• Asymptotic efficiency in estimation with conditional moment restrictions
• Robust regression: Asymptotics, conjectures and Monte Carlo
• Approximation Theorems of Mathematical Statistics
• Asymptotic Normality of Series Estimators for Nonparametric and Semiparametric Regression Models
• Efficient Instrumental Variables Estimation of Nonlinear Models
• More Efficient Estimation in the Presence of Heteroscedasticity of Unknown Form
• Generalized Instrumental Variables Estimation of Nonlinear Rational Expectations Models
• Inference Concerning the Number of Factors in a Multivariate Nonparametric Relationship
• Consistent Specification Testing Via Nonparametric Series Regression
• Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations
• Robust Statistics