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Robust Inference with High-Dimensional Instruments

Author

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  • Qu Feng
  • Sombut Jaidee
  • Wenjie Wang

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.

Suggested Citation

  • Qu Feng & Sombut Jaidee & Wenjie Wang, 2025. "Robust Inference with High-Dimensional Instruments," Papers 2506.23834, arXiv.org.
    • Handle: RePEc:arx:papers:2506.23834
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    File URL: http://arxiv.org/pdf/2506.23834
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