Publication Type
Journal Article
Version
submittedVersion
Publication Date
1-2024
Abstract
We consider a linear combination of jackknife Anderson-Rubin (AR) and orthogonalized Lagrangian multiplier (LM) tests for inference in IV regressions with many weak instruments and heteroskedasticity. We choose the weight in the linear combination based on a decision-theoretic rule that is adaptive to the identification strength. Under both weak and strong identifications, the proposed linear combination test controls asymptotic size and is admissible. Under strong identification, we further show that our linear combination test is the uniformly most powerful test against local alternatives among all tests that are constructed based on the jackknife AR and LM tests only and invariant to sign changes.
Keywords
Many instruments, power, size, weak identification
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Econometrics
Volume
238
Issue
2
First Page
1
Last Page
20
ISSN
0304-4076
Identifier
10.1016/j.jeconom.2023.105602
Publisher
Elsevier
Citation
LIM, Dennis; WANG, Wenjie; and ZHANG, Yichong.
A conditional linear combination test with many weak instruments. (2024). Journal of Econometrics. 238, (2), 1-20.
Available at: https://ink.library.smu.edu.sg/soe_research/2618
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Additional URL
https://doi.org/10.1016/j.jeconom.2023.105602