Journal article
Enhanced power enhancements for testing many moment equalities: beyond the 2- and ∞-norm
- Abstract:
- Tests based on the 2- and $\infty$-norm have received considerable attention in high-dimensional testing problems, as they are powerful against dense and sparse alternatives, respectively. The power enhancement principle of Fan et al.\ (2015) combines these two norms to construct improved tests that are powerful against both types of alternatives. In the context of testing whether a candidate parameter satisfies a large number of moment equalities, we construct tests that harness the strength of all $p$-norms with $p \in [2, \infty]$. As a result, these tests are consistent against strictly more alternatives than any test based on a single $p$-norm. In particular, our tests are consistent against more alternatives than tests based on the 2- and $\infty$-norm, which is what most implementations of the power enhancement principle target. We illustrate our general results in the linear instrumental variable model with many instruments, for which we also provide numerical results and an empirical illustration.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
-
-
(Preview, Accepted manuscript, pdf, 578.4KB, Terms of use)
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- Publisher copy:
- 10.1080/01621459.2025.2591282
Authors
+ European Research Council
More from this funder
- Funder identifier:
- https://ror.org/0472cxd90
- Grant:
- 101124535
+ UK Research and Innovation
More from this funder
- Funder identifier:
- https://ror.org/001aqnf71
- Grant:
- EP/Z002222/1
- Publisher:
- Taylor & Francis
- Journal:
- Journal of the American Statistical Association More from this journal
- Publication date:
- 2025-12-05
- Acceptance date:
- 2025-11-12
- DOI:
- EISSN:
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1537-274X
- ISSN:
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0162-1459
- Language:
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English
- Keywords:
- Pubs id:
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2325723
- Local pid:
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pubs:2325723
- Deposit date:
-
2025-11-13
- ARK identifier:
Terms of use
- Copyright holder:
- Kocka and Preinerstorfer
- Copyright date:
- 2025
- Rights statement:
- © 2025 The Author(s). Published with license by Taylor and Francis Group, LLC This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
- Licence:
- CC Attribution (CC BY)
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