IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2310.18504.html
   My bibliography  Save this paper

Doubly Robust Identification of Causal Effects of a Continuous Treatment using Discrete Instruments

Author

Listed:
  • Yingying Dong
  • Ying-Ying Lee

Abstract

Many empirical applications estimate causal effects of a continuous endogenous variable (treatment) using a binary instrument. Estimation is typically done through linear 2SLS. This approach requires a mean treatment change and causal interpretation requires the LATE-type monotonicity in the first stage. An alternative approach is to explore distributional changes in the treatment, where the first-stage restriction is treatment rank similarity. We propose causal estimands that are doubly robust in that they are valid under either of these two restrictions. We apply the doubly robust estimation to estimate the impacts of sleep on well-being. Our new estimates corroborate the usual 2SLS estimates.

Suggested Citation

  • Yingying Dong & Ying-Ying Lee, 2023. "Doubly Robust Identification of Causal Effects of a Continuous Treatment using Discrete Instruments," Papers 2310.18504, arXiv.org, revised Feb 2024.
    • Handle: RePEc:arx:papers:2310.18504
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2310.18504
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Joshua Angrist & Victor Chernozhukov & Iván Fernández-Val, 2006. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," Econometrica, Econometric Society, vol. 74(2), pages 539-563, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kato, Kengo & F. Galvao, Antonio & Montes-Rojas, Gabriel V., 2012. "Asymptotics for panel quantile regression models with individual effects," Journal of Econometrics, Elsevier, vol. 170(1), pages 76-91.
    2. repec:hal:wpspec:info:hdl:2441/5rkqqmvrn4tl22s9mc4b6ga2g is not listed on IDEAS
    3. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    4. Manuel Arellano & Stéphane Bonhomme, 2017. "Quantile Selection Models With an Application to Understanding Changes in Wage Inequality," Econometrica, Econometric Society, vol. 85, pages 1-28, January.
    5. Michal Franta, 2023. "The Application of Multiple-Output Quantile Regression on the US Financial Cycle," Working Papers 2023/2, Czech National Bank.
    6. Chunbei Wang & Le Wang, 2011. "Language Skills and the Earnings Distribution Among Child Immigrants," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 50(2), pages 297-322, April.
    7. Chesher, Andrew, 2017. "Understanding the effect of measurement error on quantile regressions," Journal of Econometrics, Elsevier, vol. 200(2), pages 223-237.
    8. Alexandre Belloni & Victor Chernozhukov, 2011. "High Dimensional Sparse Econometric Models: An Introduction," Papers 1106.5242, arXiv.org, revised Sep 2011.
    9. Ion Zgreaban, Irina, 2013. "Education in Romania - How much is it Worth?," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 149-163, March.
    10. Fong, Wai Mun, 2013. "Footprints in the market: Hedge funds and the carry trade," Journal of International Money and Finance, Elsevier, vol. 33(C), pages 41-59.
    11. Victor Chernozhukov & Iván Fernández-Val & Blaise Melly & Kaspar Wüthrich, 2020. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(529), pages 123-137, January.
    12. Grimpe, Christoph & Kaiser, Ulrich & Sofka, Wolfgang, 2018. "Innovating for the Better? The Role of Advocacy Group Work Experience for Employee Pay," IZA Discussion Papers 11649, Institute of Labor Economics (IZA).
    13. Shabbar Jaffry & Yaseen Ghulam & Vyoma Shah, 2007. "Returns to Education in Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 46(4), pages 833-852.
    14. Marilena Furno, 2011. "Goodness of Fit and Misspecification in Quantile Regressions," Journal of Educational and Behavioral Statistics, , vol. 36(1), pages 105-131, February.
    15. WenWu Wang & Ping Yu, 2023. "Nonequivalence of two least-absolute-deviation estimators for mediation effects," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(1), pages 370-387, March.
    16. Leonid Kogan & Dimitris Papanikolaou & Lawrence D. W. Schmidt & Jae Song, 2020. "Technological Innovation and Labor Income Risk," NBER Working Papers 26964, National Bureau of Economic Research, Inc.
    17. Chen, Xirong & Li, Degui & Li, Qi & Li, Zheng, 2019. "Nonparametric estimation of conditional quantile functions in the presence of irrelevant covariates," Journal of Econometrics, Elsevier, vol. 212(2), pages 433-450.
    18. Wiji Arulampalam & Alison Booth & Mark Bryan, 2010. "Are there asymmetries in the effects of training on the conditional male wage distribution?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 23(1), pages 251-272, January.
    19. Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
    20. Katarzyna Burzynska & Olle Berggren, 2015. "The Impact of Social Beliefs on Microfinance Performance," Journal of International Development, John Wiley & Sons, Ltd., vol. 27(7), pages 1074-1097, October.
    21. Schlueter, Tobias & Sievers, Soenke & Hartmann-Wendels, Thomas, 2015. "Bank funding stability, pricing strategies and the guidance of depositors," Journal of Banking & Finance, Elsevier, vol. 51(C), pages 43-61.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2310.18504. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.