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Flexible and fast estimation of quantile treatment effects: The rqr and rqrplot commands

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  • Andreas Haupt

    (Karlsruhe Institute of Technology)

  • Øyvind Wiborg

    (University of Oslo)

  • Nicolai T. Borgen

    (University of Oslo)

Abstract

Using quantile regression models to estimate quantile treatment effects is becoming increasingly popular. This presentation introduces the rqr command, which can be used to estimate residualized quantile regression (RQR) coefficients and the rqrplot postestimation command, which can be used to effortlessly plot the coefficients. The main advantages of the rqr command compared with other Stata commands that estimate (unconditional) quantile treatment effects are that it can include high-dimensional fixed effects and that it is considerably faster than the other commands.

Suggested Citation

  • Andreas Haupt & Øyvind Wiborg & Nicolai T. Borgen, 2022. "Flexible and fast estimation of quantile treatment effects: The rqr and rqrplot commands," Swiss Stata Conference 2022 04, Stata Users Group.
    • Handle: RePEc:boc:csug22:04
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    File URL: http://repec.org/csug2022/Haupt-Bern2022-rqr.pdf
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