On uniform asymptotic risk of averaging GMM estimators

Artikel

This paper studies the averaging GMM estimator that combines a conservative GMM estimator based on valid moment conditions and an aggressive GMM estimator based on both valid and possibly misspecified moment conditions, where the weight is the sample analog of an infeasible optimal weight. We establish asymptotic theory on uniform approximation of the upper and lower bounds of the finite-sample truncated risk difference between any two estimators, which is used to compare the averaging GMM estimator and the conservative GMM estimator. Under some sufficient conditions, we show that the asymptotic lower bound of the truncated risk difference between the averaging estimator and the conservative estimator is strictly less than zero, while the asymptotic upper bound is zero uniformly over any degree of misspecification. The results apply to quadratic loss functions. This uniform asymptotic dominance is established in non-Gaussian semiparametric nonlinear models.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: Quantitative Economics ; ISSN: 1759-7331 ; Volume: 10 ; Year: 2019 ; Issue: 3 ; Pages: 931-979 ; New Haven, CT: The Econometric Society

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Estimation: General ; Multiple or Simultaneous Equation Models: Instrumental Variables (IV) Estimation ; Model Evaluation, Validation, and Selection
• Thema: Asymptotic risk ; finite-sample risk ; generalized shrinkage estimator ; GMM ; misspecification ; model averaging ; nonstandard estimator ; uniform approximation

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Cheng, Xu ; Liao, Zhipeng ; Shi, Ruoyao
• Ereignis: Veröffentlichung
• (wer): The Econometric Society
• (wo): New Haven, CT
• (wann): 2019

Weitere Informationen

• DOI: doi:10.3982/QE711
• Handle: http://hdl.handle.net/10419/217160
• Letzte Aktualisierung: 10.03.2025, 11:42 MEZ