Arbeitspapier
Asymptotic efficiency of semiparametric two-step GMM
In this note, we characterize the semiparametric efficiency bound for a class of semi- parametric models in which the unknown nuisance functions are identified via nonparametric conditional moment restrictions with possibly non-nested or over-lapping conditioning sets, and the finite dimensional parameters are potentially over-identified via uncondi tional moment restrictions involving the nuisance functions. We discover a surprising result that semiparametric two-step optimally weighted GMM estimators achieve the efficiency bound, where the nuisance functions could be estimated via any consistent non- parametric procedures in the first step. Regardless of whether the efficiency bound has a closed form expression or not, we provide easy-to-compute sieve based optimal weight matrices that lead to asymptotically efficient two-step GMM estimators.
- Sprache
-
Englisch
- Erschienen in
-
Series: cemmap working paper ; No. CWP31/12
- Klassifikation
-
Wirtschaft
Semiparametric and Nonparametric Methods: General
Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- Thema
-
Overlapping Information Sets
Semiparametric Efficiency
Two-Step GMM
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Chen, Xiaohong
Hahn, Jinyong
Liao, Zhipeng
- Ereignis
-
Veröffentlichung
- (wer)
-
Centre for Microdata Methods and Practice (cemmap)
- (wo)
-
London
- (wann)
-
2012
- DOI
-
doi:10.1920/wp.cem.2012.3112
- Handle
- Letzte Aktualisierung
-
20.09.2024, 08:22 MESZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Chen, Xiaohong
- Hahn, Jinyong
- Liao, Zhipeng
- Centre for Microdata Methods and Practice (cemmap)
Entstanden
- 2012
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