IDEAS home Printed from https://ideas.repec.org/a/cup/etheor/v33y2017i03p664-690_00.html
   My bibliography  Save this article

On Using Linear Quantile Regressions For Causal Inference

Author

Listed:
  • Kato, Ryutah
  • Sasaki, Yuya

Abstract

We show that the slope parameter of the linear quantile regression measures a weighted average of the local slopes of the conditional quantile function. Extending this result, we also show that the slope parameter measures a weighted average of the partial effects for a general structural function. Our results support the use of linear quantile regressions for causal inference in the presence of nonlinearity and multivariate unobserved heterogeneity. The same conclusion applies to linear regressions.

Suggested Citation

  • Kato, Ryutah & Sasaki, Yuya, 2017. "On Using Linear Quantile Regressions For Causal Inference," Econometric Theory, Cambridge University Press, vol. 33(3), pages 664-690, June.
    • Handle: RePEc:cup:etheor:v:33:y:2017:i:03:p:664-690_00
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S0266466616000177/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tymon S{l}oczy'nski, 2018. "Interpreting OLS Estimands When Treatment Effects Are Heterogeneous: Smaller Groups Get Larger Weights," Papers 1810.01576, arXiv.org, revised May 2020.
    2. Tymon Sloczynski, 2018. "A General Weighted Average Representation of the Ordinary and Two-Stage Least Squares Estimands," Working Papers 125, Brandeis University, Department of Economics and International Business School.
    3. Chiang, Harold D. & Sasaki, Yuya, 2019. "Causal inference by quantile regression kink designs," Journal of Econometrics, Elsevier, vol. 210(2), pages 405-433.
    4. Arie Beresteanu, 2016. "Quantile Regression with Interval Data," Working Paper 5991, Department of Economics, University of Pittsburgh.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cup:etheor:v:33:y:2017:i:03:p:664-690_00. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/ect .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.