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Robust Inference with High-Dimensional Instruments

Qu Feng, Sombut Jaidee, Wenjie Wang

arXiv 30 Jun 2025 · Econometrics

arXiv:2506.23834 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We propose a weak-identification-robust test for linear instrumental variable (IV) regressions with high-dimensional instruments, whose number is allowed to exceed the sample size. In addition, our test is robust to general error dependence, such as network dependence and spatial dependence. The test statistic takes a self-normalized form and the asymptotic validity of the test is established by using random matrix theory. Simulation studies are conducted to assess the numerical performance of the test, confirming good size control and satisfactory testing power across a range of various error dependence structures.

Citation extraction

95
references
296
in-text mentions
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distinct cited
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self-citations
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main-text words

appendix boundary found by appendix_command · 65% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Feng, Q., S. Jaidee, G. Pan, and W. Zhu (2024) Robust testing in high dimensional linear models self0.7374350%
2Lee, D. S., J. McCrary, M. J. Moreira, and J. R. Porter (2022) Valid t-ratio inference for iv0.73732100%
Kleibergenunmatched citation key Kleibergen0.64441100%
4Newey, W. K. and F. Windmeijer (2009) Newey-Windmeijer(2009)Generalized method of moments with many weak moment conditions0.64441100%
5Andrews, I., J. H. Stock, and L. Sun (2019) Andrews-Stock-Sun(2019)Weak instruments in instrumental variables regression: Theory and practice0.64422100%
6Lim, D., W. Wang, and Y. Zhang (2024) A dimension-agnostic bootstrap anderson-rubin test for instrumental variable regressions0.64422100%
Carrasco and Tchuenteunmatched citation key Carrasco and Tchuente0.58531100%
Chaounmatched citation key Chao0.58531100%
9Chao, J. C., N. R. Swanson, J. A. Hausman, W. K. Newey, and T. Woute… (2012) Asymptotic distribution of jive in a heteroskedastic iv regression with many instruments0.58531100%
Guggenbergerunmatched citation key Guggenberger0.58531100%

Showing the top 10 of 240 scored citations. 4 of these could not be matched to a bibliography entry, so only the citation key is shown.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Inference in clustered IV models with many and weak instruments0.40511