IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2501.14405.html
   My bibliography  Save this paper

Triple Instrumented Difference-in-Differences

Author

Listed:
  • Sho Miyaji

Abstract

In this paper, we formalize a triple instrumented difference-in-differences (DID-IV). In this design, a triple Wald-DID estimand, which divides the difference-in-difference-in-differences (DDD) estimand of the outcome by the DDD estimand of the treatment, captures the local average treatment effect on the treated. The identifying assumptions mainly comprise a monotonicity assumption, and the common acceleration assumptions in the treatment and the outcome. We extend the canonical triple DID-IV design to staggered instrument cases. We also describe the estimation and inference in this design in practice.

Suggested Citation

  • Sho Miyaji, 2025. "Triple Instrumented Difference-in-Differences," Papers 2501.14405, arXiv.org.
    • Handle: RePEc:arx:papers:2501.14405
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2501.14405
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Adam Isen & Maya Rossin-Slater & W. Reed Walker, 2017. "Every Breath You Take—Every Dollar You’ll Make: The Long-Term Consequences of the Clean Air Act of 1970," Journal of Political Economy, University of Chicago Press, vol. 125(3), pages 848-902.
    2. Esther Duflo, 2001. "Schooling and Labor Market Consequences of School Construction in Indonesia: Evidence from an Unusual Policy Experiment," American Economic Review, American Economic Association, vol. 91(4), pages 795-813, September.
    3. Imai, Kosuke & Kim, In Song, 2021. "On the Use of Two-Way Fixed Effects Regression Models for Causal Inference with Panel Data," Political Analysis, Cambridge University Press, vol. 29(3), pages 405-415, July.
    4. Olivier Deschênes & Michael Greenstone & Joseph S. Shapiro, 2017. "Defensive Investments and the Demand for Air Quality: Evidence from the NOx Budget Program," American Economic Review, American Economic Association, vol. 107(10), pages 2958-2989, October.
    5. Sun, Liyang & Abraham, Sarah, 2021. "Estimating dynamic treatment effects in event studies with heterogeneous treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 175-199.
    6. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
    7. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, 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. Sho Miyaji, 2024. "Instrumented Difference-in-Differences with Heterogeneous Treatment Effects," Papers 2405.12083, arXiv.org, revised Jan 2025.
    2. Sho Miyaji, 2024. "Instrumented Difference-in-Differences with Heterogeneous Treatment Effects," Discussion Paper Series DP2024-22, Research Institute for Economics & Business Administration, Kobe University.
    3. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    4. Sho Miyaji, 2024. "Two-way fixed effects instrumental variable regressions in staggered DID-IV designs," Papers 2405.16467, arXiv.org.
    5. Dahis, Ricardo & Szerman, Christiane, 2024. "Decentralizing Development: Evidence from Government Splits," Research Department working papers 2297, CAF Development Bank Of Latinamerica.
    6. Arne Henningsen & Guy Low & David Wuepper & Tobias Dalhaus & Hugo Storm & Dagim Belay & Stefan Hirsch, 2024. "Estimating Causal Effects with Observational Data: Guidelines for Agricultural and Applied Economists," IFRO Working Paper 2024/03, University of Copenhagen, Department of Food and Resource Economics.
    7. Han, Sukjin, 2021. "Identification in nonparametric models for dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 132-147.
    8. Ashesh Rambachan & Jonathan Roth, 2020. "Design-Based Uncertainty for Quasi-Experiments," Papers 2008.00602, arXiv.org, revised Oct 2024.
    9. Wen, Jiayi & Huang, Haili, 2024. "Parental health penalty on adult children’s employment: Gender differences and long-term consequences," Journal of Health Economics, Elsevier, vol. 95(C).
    10. Clément de Chaisemartin & Xavier D'Haultfœuille, 2020. "Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects," American Economic Review, American Economic Association, vol. 110(9), pages 2964-2996, September.
    11. Francis Wong, 2024. "Taxing Homeowners Who Won’t Borrow," CESifo Working Paper Series 11185, CESifo.
    12. Hannah Klauber & Felix Holub & Nicolas Koch & Nico Pestel & Nolan Ritter & Alexander Rohlf, 2024. "Killing Prescriptions Softly: Low Emission Zones and Child Health from Birth to School," American Economic Journal: Economic Policy, American Economic Association, vol. 16(2), pages 220-248, May.
    13. Cl'ement de Chaisemartin & Xavier D'Haultf{oe}uille, 2021. "Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey," Papers 2112.04565, arXiv.org, revised Jun 2022.
    14. Eli Ben‐Michael & Avi Feller & Jesse Rothstein, 2022. "Synthetic controls with staggered adoption," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(2), pages 351-381, April.
    15. Lin, Weifen & Tong, Xinyue & Hu, Yao & Wang, Hui, 2024. "The flow of industrial lifeblood: The impact of the West-to-East oil transportation project on enterprise performance of China," Energy Economics, Elsevier, vol. 129(C).
    16. Pengju Zhang & Ling Zhu, 2021. "Does the ACA Medicaid Expansion Affect Hospitals’ Financial Performance?," Public Finance Review, , vol. 49(6), pages 779-814, November.
    17. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Jun 2024.
    18. Hiroko OKUDAIRA & Miho TAKIZAWA & Kenta YAMANOUCHI, 2022. "Does Employee Downsizing Work? Evidence from Product Innovation at Manufacturing Plants," Discussion papers 22015, Research Institute of Economy, Trade and Industry (RIETI).
    19. Brick, Kerri & De Martino, Samantha & Visser, Martine, 2023. "Behavioural nudges for water conservation in unequal settings: Experimental evidence from Cape Town," Journal of Environmental Economics and Management, Elsevier, vol. 121(C).
    20. Roth, Jonathan & Sant’Anna, Pedro H.C. & Bilinski, Alyssa & Poe, John, 2023. "What’s trending in difference-in-differences? A synthesis of the recent econometrics literature," Journal of Econometrics, Elsevier, vol. 235(2), pages 2218-2244.

    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:2501.14405. 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.