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Implementing an Improved Test of Matrix Rank in Stata

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  • Qihui Chen
  • Zheng Fang
  • Xun Huang

Abstract

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.

Suggested Citation

  • Qihui Chen & Zheng Fang & Xun Huang, 2021. "Implementing an Improved Test of Matrix Rank in Stata," Papers 2108.00511, arXiv.org.
    • Handle: RePEc:arx:papers:2108.00511
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    References listed on IDEAS

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    1. Qihui Chen & Zheng Fang, 2018. "Improved Inference on the Rank of a Matrix," Papers 1812.02337, arXiv.org, revised Mar 2019.
    2. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    3. Kleibergen, Frank & Paap, Richard, 2006. "Generalized reduced rank tests using the singular value decomposition," Journal of Econometrics, Elsevier, vol. 133(1), pages 97-126, July.
    4. Qihui Chen & Zheng Fang, 2019. "Improved inference on the rank of a matrix," Quantitative Economics, Econometric Society, vol. 10(4), pages 1787-1824, November.
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