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Valid Two-Step Identification-Robust Confidence Sets for GMM
- Source :
- MIT Press
- Publication Year :
- 2018
-
Abstract
- In models with potentially weak identification, researchers often decide whether to report a robust confidence set based on an initial assessment of model identification. Two-step procedures of this sort can generate large coverage distortions for reported confidence sets, and existing procedures for controlling these distortions are quite limited. This paper introduces a generally applicable approach to detecting weak identification and constructing two-step confidence sets in GMM. This approach controls coverage distortions under weak identification and indicates strong identification, with probability tending to 1 when the model is well identified.
Details
- Database :
- OAIster
- Journal :
- MIT Press
- Notes :
- application/pdf
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1351762921
- Document Type :
- Electronic Resource