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

Author

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  • Borgen, Nicolai T.
  • Haupt, Andreas
  • Wiborg, Øyvind N.

Abstract

Using quantile regression models to estimate quantile treatment effects is becoming increasingly popular. This paper introduces the rqr command that can be used to estimate residualized quantile regression (RQR) coefficients and the rqrplot postestimation command that can be used to effortless plot the coefficients. The main advantages of the rqr command compared to 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

  • Borgen, Nicolai T. & Haupt, Andreas & Wiborg, Øyvind N., 2021. "Flexible and fast estimation of quantile treatment effects: The rqr and rqrplot commands," SocArXiv 4vquh, Center for Open Science.
    • Handle: RePEc:osf:socarx:4vquh
    DOI: 10.31219/osf.io/4vquh
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    References listed on IDEAS

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    1. Sergio Firpo, 2007. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 75(1), pages 259-276, January.
    2. Matteo Bottai & Nicola Orsini, 2019. "qmodel: A command for fitting parametric quantile models," Stata Journal, StataCorp LLC, vol. 19(2), pages 261-293, June.
    3. Victor Chernozhukov & Iván Fernández-Val & Blaise Melly, 2022. "Fast algorithms for the quantile regression process," Empirical Economics, Springer, vol. 62(1), pages 7-33, January.
    4. Markus Frolich & Blaise Melly, 2010. "Estimation of quantile treatment effects with Stata," Stata Journal, StataCorp LLC, vol. 10(3), pages 423-457, September.
    5. Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 73(1), pages 245-261, January.
    6. Card, David, 1996. "The Effect of Unions on the Structure of Wages: A Longitudinal Analysis," Econometrica, Econometric Society, vol. 64(4), pages 957-979, July.
    7. Borgen, Nicolai T. & Haupt, Andreas & Wiborg, Øyvind N., 2021. "A New Framework for Estimation of Unconditional Quantile Treatment Effects: The Residualized Quantile Regression (RQR) Model," SocArXiv 42gcb, Center for Open Science.
    8. Nicolai T. Borgen, 2016. "Fixed effects in unconditional quantile regression," Stata Journal, StataCorp LLC, vol. 16(2), pages 403-415, June.
    9. Fortin, Nicole & Lemieux, Thomas & Firpo, Sergio, 2011. "Decomposition Methods in Economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 1, pages 1-102, Elsevier.
    10. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    11. Kaplan, David M. & Sun, Yixiao, 2017. "Smoothed Estimating Equations For Instrumental Variables Quantile Regression," Econometric Theory, Cambridge University Press, vol. 33(1), pages 105-157, February.
    12. Fernando Rios-Avila, 2020. "Recentered influence functions (RIFs) in Stata: RIF regression and RIF decomposition," Stata Journal, StataCorp LLC, vol. 20(1), pages 51-94, March.
    13. David Powell, 2020. "Quantile Treatment Effects in the Presence of Covariates," The Review of Economics and Statistics, MIT Press, vol. 102(5), pages 994-1005, December.
    14. Machado, Jose A.F. & Silva, J. M. C. Santos, 2005. "Quantiles for Counts," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1226-1237, December.
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