Qihui Chen, Zheng Fang, Xun Huang
arXiv 1 Aug 2021 · Econometrics
arXiv:2108.00511 · PDF · DOI · OpenAlex · Extracted main text
We develop a Stata command, bootranktest, for implementing the matrix rank test of Chen and Fang (2019) in linear instrumental variable regression models. Existing rank tests employ critical values that may be too small, and hence may not even be first order valid in the sense that they may fail to control the Type I error. By appealing to the bootstrap, they devise a test that overcomes the deficiency of existing tests. The command bootranktest implements the two-step version of their test, and also the analytic version if chosen. The command also accommodates data with temporal and cluster dependence.
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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 | Chen, Q., and Z. Fang (2019) Improved Inference on the Rank of a Matrix self | 1.000 | 10 | 3 | 100% |
| 2 | Kleibergen, F., and R. Paap (2006) Generalized Reduced Rank Tests Using the Singular Value Decomposition | 1.000 | 5 | 3 | 100% |
| 3 | Robin, J.-M., and R. J. Smith (2000) Tests of Rank | 0.737 | 3 | 2 | 100% |
| 4 | Cameron, A. C., J. B. Gelbach, and D. L. Miller (2008) Bootstrap-based improvements for inference with clustered errors | 0.405 | 1 | 1 | 100% |
| 5 | Kleibergen, F., M. Schaffer, and F. Windmeijer (2020) RANKTEST: Stata module to test the rank of a matrix | 0.405 | 1 | 1 | 100% |
| 6 | Kunsch, H. R (1989) The Jackknife and the Bootstrap for General Stationary Observations | 0.405 | 1 | 1 | 100% |
| 7 | Wu, C. F. J (1986) Jackknife, Bootstrap and Other Resampling Methods in Regression Analysis | 0.405 | 1 | 1 | 100% |
Showing the top 7 of 7 scored citations.