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QCM: Stata module to implement quantile control method (QCM) via Random Forest

Author

Listed:
  • Guanpeng Yan

    (Shandong University of Finance and Economics)

  • Qiang Chen

    (Shandong University)

Programming Language

Stata

Abstract

qcm implements quantile control method (QCM) via random forest (Chen, Xiao and Yao, 2023), which provides confidence intervals for treatment effects in panel data with a single treated unit using quantile random forest (Meinshausen, 2006). As a nonparametric ensemble learning, QCM is suitable for high-dimensional data, and robust to heteroskedasticity, autocorrelation and model misspecification. Simulations in Chen, Xiao and Yao (2023) show that for 95% nominal confidence level, the empirical coverage rate can reach above 90% if the number of pretreatment periods is 30 or larger. qcm also supports placebo tests using fake treatment units and/or fake treatment time as alternative methods for inference and robustness check.

Suggested Citation

  • Guanpeng Yan & Qiang Chen, 2023. "QCM: Stata module to implement quantile control method (QCM) via Random Forest," Statistical Software Components S459270, Boston College Department of Economics, revised 23 Nov 2023.
    • Handle: RePEc:boc:bocode:s459270
    Note: This module should be installed from within Stata by typing "ssc install qcm". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
    as

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    File URL: http://fmwww.bc.edu/repec/bocode/q/qcm.ado
    File Function: program code
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    File URL: http://fmwww.bc.edu/repec/bocode/q/qcm.sthlp
    File Function: help file
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    File URL: http://fmwww.bc.edu/repec/bocode/l/lqcm.mlib
    File Function: Mata object code
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    File URL: http://fmwww.bc.edu/repec/bocode/g/growth.dta
    File Function: supplementary data file
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    File URL: http://fmwww.bc.edu/repec/bocode/c/carbontaxgr.dta
    File Function: supplementary data file
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