Qu Feng, Sombut Jaidee, Wenjie Wang
arXiv 30 Jun 2025 · Econometrics
arXiv:2506.23834 · PDF · DOI · OpenAlex · Extracted main text
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.
appendix boundary found by appendix_command · 65% of the source is main text. Read the extracted text to check this.
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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Feng, Q., S. Jaidee, G. Pan, and W. Zhu (2024) Robust testing in high dimensional linear models self | 0.737 | 4 | 3 | 50% |
| 2 | Lee, D. S., J. McCrary, M. J. Moreira, and J. R. Porter (2022) Valid t-ratio inference for iv | 0.737 | 3 | 2 | 100% |
| 3 | Newey, W. K. and F. Windmeijer (2009) Newey-Windmeijer(2009)Generalized method of moments with many weak moment conditions | 0.644 | 4 | 1 | 100% |
| 4 | Andrews, I., J. H. Stock, and L. Sun (2019) Andrews-Stock-Sun(2019)Weak instruments in instrumental variables regression: Theory and practice | 0.644 | 2 | 2 | 100% |
| 5 | Lim, D., W. Wang, and Y. Zhang (2024) A dimension-agnostic bootstrap anderson-rubin test for instrumental variable regressions | 0.644 | 2 | 2 | 100% |
| 6 | Chao, 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 instruments | 0.585 | 3 | 1 | 100% |
| 7 | Hausman, J. A., W. K. Newey, T. Woutersen, J. C. Chao, and N. R. Swa… (2012) Instrumental variable estimation with heteroskedasticity and many instruments | 0.585 | 3 | 1 | 100% |
| 8 | Mikusheva, A. and L. Sun (2022) Inference with many weak instruments | 0.585 | 3 | 1 | 100% |
| 9 | Anatolyev, S. and N. Gospodinov (2011) Specification testing in models with many instruments | 0.585 | 3 | 1 | 100% |
| 10 | Belloni, A., D. Chen, V. Chernozhukov, and C. Hansen (2012) Sparse models and methods for optimal instruments with an application to eminent domain | 0.585 | 3 | 1 | 100% |
Showing the top 10 of 95 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Inference in clustered IV models with many and weak instruments | 0.405 | 1 | 1 |