IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v79y2023i2p592-596.html

Discussion on “Instrumented difference‐in‐differences” by Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy & Dylan S. Small

Author

Listed:
  • Hyunseung Kang

Abstract

We reinterpret the instrumented difference‐in‐differences (iDID) under a linear instrumental variables (IV) model. Under the linear IV model, we show why iDID is a clear improvement over two existing methods, difference‐in‐differences (DID) and a cross‐sectional, IV analysis. We also re‐express some of the assumptions of iDID using familiar, regression‐based identification assumptions. We conclude with a method inspired by the linear IV model that can potentially remedy the weak identification problem in iDID.

Suggested Citation

  • Hyunseung Kang, 2023. "Discussion on “Instrumented difference‐in‐differences” by Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy & Dylan S. Small," Biometrics, The International Biometric Society, vol. 79(2), pages 592-596, June.
    • Handle: RePEc:bla:biomet:v:79:y:2023:i:2:p:592-596
    DOI: 10.1111/biom.13784
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/biom.13784
    Download Restriction: no
    File URL: https://libkey.io/10.1111/biom.13784?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hyunseung Kang & Anru Zhang & T. Tony Cai & Dylan S. Small, 2016. "Instrumental Variables Estimation With Some Invalid Instruments and its Application to Mendelian Randomization," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(513), pages 132-144, March.
    2. Moreira, Marcelo J., 2009. "Tests with correct size when instruments can be arbitrarily weak," Journal of Econometrics, Elsevier, vol. 152(2), pages 131-140, October.
    3. Zijian Guo & Hyunseung Kang & T. Tony Cai & Dylan S. Small, 2018. "Confidence intervals for causal effects with invalid instruments by using two‐stage hard thresholding with voting," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(4), pages 793-815, September.
    4. Jean-Marie Dufour, 1997. "Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models," Econometrica, Econometric Society, vol. 65(6), pages 1365-1388, November.
    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. Sheng Wang & Hyunseung Kang, 2022. "Weak‐instrument robust tests in two‐sample summary‐data Mendelian randomization," Biometrics, The International Biometric Society, vol. 78(4), pages 1699-1713, December.
    2. Nicolas Apfel, 2019. "Relaxing the Exclusion Restriction in Shift-Share Instrumental Variable Estimation," Papers 1907.00222, arXiv.org, revised Jul 2022.
    3. Frank Windmeijer & Xiaoran Liang & Fernando P. Hartwig & Jack Bowden, 2021. "The confidence interval method for selecting valid instrumental variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 752-776, September.
    4. Joe Hirschberg & Jenny Lye, 2017. "Alternative Graphical Representations of the Confidence Intervals for the Structural Coefficient from Exactly Identified Two-Stage Least Squares," Department of Economics - Working Papers Series 2026, The University of Melbourne.
    5. Qingliang Fan & Zijian Guo & Ziwei Mei, 2022. "A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates," Papers 2205.00171, arXiv.org, revised May 2024.
    6. Russell Davidson & James G. MacKinnon, 2014. "Bootstrap Confidence Sets with Weak Instruments," Econometric Reviews, Taylor & Francis Journals, vol. 33(5-6), pages 651-675, August.
    7. Bekker, Paul A. & Lawford, Steve, 2008. "Symmetry-based inference in an instrumental variable setting," Journal of Econometrics, Elsevier, vol. 142(1), pages 28-49, January.
    8. Xiaoran Liang & Eleanor Sanderson & Frank Windmeijer, 2022. "Selecting Valid Instrumental Variables in Linear Models with Multiple Exposure Variables: Adaptive Lasso and the Median-of-Medians Estimator," Papers 2208.05278, arXiv.org.
    9. Donald W.K. Andrews & James H. Stock, 2005. "Inference with Weak Instruments," NBER Technical Working Papers 0313, National Bureau of Economic Research, Inc.
    10. Han Zhang & Jing Qin & Sonja I. Berndt & Demetrius Albanes & Lu Deng & Mitchell H. Gail & Kai Yu, 2020. "On Mendelian randomization analysis of case‐control study," Biometrics, The International Biometric Society, vol. 76(2), pages 380-391, June.
    11. Nicolas Apfel & Helmut Farbmacher & Rebecca Groh & Martin Huber & Henrika Langen, 2022. "Detecting Grouped Local Average Treatment Effects and Selecting True Instruments," Papers 2207.04481, arXiv.org, revised Oct 2023.
    12. Gregor Steiner & Jeremie Houssineau & Mark F. J. Steel, 2025. "Possibilistic Instrumental Variable Regression," Papers 2511.16029, arXiv.org, revised Jan 2026.
    13. Qingliang Fan & Yaqian Wu, 2020. "Endogenous Treatment Effect Estimation with some Invalid and Irrelevant Instruments," Papers 2006.14998, arXiv.org.
    14. Nathan Canen & Shantanu Chadha, 2026. "Empirical Challenges with Peers-of-Peers Instruments in the Linear-In-Means Model," Papers 2602.24215, arXiv.org.
    15. Ying Zhou, 2025. "Causal Inference with Secondary Outcomes," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 17(1), pages 3-16, April.
    16. Chao, John & Swanson, Norman R., 2007. "Alternative approximations of the bias and MSE of the IV estimator under weak identification with an application to bias correction," Journal of Econometrics, Elsevier, vol. 137(2), pages 515-555, April.
    17. Antoine, Bertille & Renault, Eric, 2020. "Testing identification strength," Journal of Econometrics, Elsevier, vol. 218(2), pages 271-293.
    18. Firmin Doko Tchatoka, 2015. "On bootstrap validity for specification tests with weak instruments," Econometrics Journal, Royal Economic Society, vol. 18(1), pages 137-146, February.
    19. Hongwei Shi & Xinyu Zhang & Xu Guo & Baihua He & Chenyang Wang, 2025. "Testing overidentifying restrictions on high-dimensional instruments and covariates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 77(2), pages 331-352, April.
    20. David S. Lee & Justin McCrary & Marcelo J. Moreira & Jack Porter, 2022. "Valid t-Ratio Inference for IV," American Economic Review, American Economic Association, vol. 112(10), pages 3260-3290, October.

    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:bla:biomet:v:79:y:2023:i:2:p:592-596. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.