IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2007.04267.html
   My bibliography  Save this paper

Difference-in-Differences Estimators of Intertemporal Treatment Effects

Author

Listed:
  • Cl'ement de Chaisemartin
  • Xavier D'Haultfoeuille

Abstract

We study treatment-effect estimation using panel data. The treatment may be non-binary, non-absorbing, and the outcome may be affected by treatment lags. We make a parallel-trends assumption, and propose event-study estimators of the effect of being exposed to a weakly higher treatment dose for $\ell$ periods. We also propose normalized estimators, that estimate a weighted average of the effects of the current treatment and its lags. We also analyze commonly-used two-way-fixed-effects regressions. Unlike our estimators, they can be biased in the presence of heterogeneous treatment effects. A local-projection version of those regressions is biased even with homogeneous effects.

Suggested Citation

  • Cl'ement de Chaisemartin & Xavier D'Haultfoeuille, 2020. "Difference-in-Differences Estimators of Intertemporal Treatment Effects," Papers 2007.04267, arXiv.org, revised Nov 2023.
    • Handle: RePEc:arx:papers:2007.04267
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2007.04267
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Cl'ement de Chaisemartin & Xavier D'Haultfoeuille & F'elix Pasquier & Gonzalo Vazquez-Bare, 2022. "Difference-in-Differences Estimators for Treatments Continuously Distributed at Every Period," Papers 2201.06898, arXiv.org, revised Dec 2023.
    2. Dave Donaldson, 2018. "Railroads of the Raj: Estimating the Impact of Transportation Infrastructure," American Economic Review, American Economic Association, vol. 108(4-5), pages 899-934, April.
    3. Juan Carlos Suárez Serrato & Owen Zidar, 2016. "Who Benefits from State Corporate Tax Cuts? A Local Labor Markets Approach with Heterogeneous Firms," American Economic Review, American Economic Association, vol. 106(9), pages 2582-2624, September.
    4. Clemens Fuest & Andreas Peichl & Sebastian Siegloch, 2018. "Do Higher Corporate Taxes Reduce Wages? Micro Evidence from Germany," American Economic Review, American Economic Association, vol. 108(2), pages 393-418, February.
    5. 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.
    6. Thiemo Fetzer, 2019. "Did Austerity Cause Brexit?," American Economic Review, American Economic Association, vol. 109(11), pages 3849-3886, November.
    7. Kurt Schmidheiny & Sebastian Siegloch, 2023. "On event studies and distributed‐lags in two‐way fixed effects models: Identification, equivalence, and generalization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 695-713, August.
    8. Robin Burgess & Remi Jedwab & Edward Miguel & Ameet Morjaria & Gerard Padró i Miquel, 2015. "The Value of Democracy: Evidence from Road Building in Kenya," American Economic Review, American Economic Association, vol. 105(6), pages 1817-1851, June.
    9. Kyle Handley & Nuno Limão, 2018. "Policy Uncertainty, Trade, and Welfare: Theory and Evidence for China and the United States," World Scientific Book Chapters, in: Policy Externalities and International Trade Agreements, chapter 5, pages 123-175, World Scientific Publishing Co. Pte. Ltd..
    10. Rebecca Diamond & Tim McQuade & Franklin Qian, 2019. "The Effects of Rent Control Expansion on Tenants, Landlords, and Inequality: Evidence from San Francisco," American Economic Review, American Economic Association, vol. 109(9), pages 3365-3394, September.
    11. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods and an Application on the Minimum Wage and Employment," DETU Working Papers 1804, Department of Economics, Temple University.
    12. Kilian Huber, 2018. "Disentangling the Effects of a Banking Crisis: Evidence from German Firms and Counties," American Economic Review, American Economic Association, vol. 108(3), pages 868-898, March.
    13. Athey, Susan & Imbens, Guido W., 2022. "Design-based analysis in Difference-In-Differences settings with staggered adoption," Journal of Econometrics, Elsevier, vol. 226(1), pages 62-79.
    14. Brad Hershbein & Lisa B. Kahn, 2018. "Do Recessions Accelerate Routine-Biased Technological Change? Evidence from Vacancy Postings," American Economic Review, American Economic Association, vol. 108(7), pages 1737-1772, July.
    15. 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.
    16. 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.
    17. Justin R. Pierce & Peter K. Schott, 2016. "The Surprisingly Swift Decline of US Manufacturing Employment," American Economic Review, American Economic Association, vol. 106(7), pages 1632-1662, July.
    18. Heather Antecol & Kelly Bedard & Jenna Stearns, 2018. "Equal but Inequitable: Who Benefits from Gender-Neutral Tenure Clock Stopping Policies?," American Economic Review, American Economic Association, vol. 108(9), pages 2420-2441, September.
    19. David H. Autor, 2003. "Outsourcing at Will: The Contribution of Unjust Dismissal Doctrine to the Growth of Employment Outsourcing," Journal of Labor Economics, University of Chicago Press, vol. 21(1), pages 1-42, January.
    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. Kurt Schmidheiny & Sebastian Siegloch, 2023. "On event studies and distributed‐lags in two‐way fixed effects models: Identification, equivalence, and generalization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 695-713, August.
    2. Lichter, Andreas & Loeffler, Max & Isphording, Ingo E. & Nguyen, Thu-Van & Poege, Felix & Siegloch, Sebastian, 2021. "Profit Taxation, R&D Spending, and Innovation," IZA Discussion Papers 14830, Institute of Labor Economics (IZA).
    3. Sebastian Siegloch & Nils Wehrhöfer & Tobias Etzel, 2022. "Spillover, Efficiency and Equity Effects of Regional Firm Subsidies," ECONtribute Discussion Papers Series 210, University of Bonn and University of Cologne, Germany.
    4. Jin, Zhangfeng & Zhang, Junsen, 2023. "Access to local citizenship and internal migration in a developing country: Evidence from a Hukou reform in China," Journal of Comparative Economics, Elsevier, vol. 51(1), pages 181-215.
    5. Damian Clarke & Kathya Tapia-Schythe, 2021. "Implementing the panel event study," Stata Journal, StataCorp LP, vol. 21(4), pages 853-884, December.
    6. 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.
    7. Katarzyna Bilicka & Evgeniya Dubinina & Petr Janský, 2022. "Fiscal consequences of corporate tax avoidance," WIDER Working Paper Series wp-2022-97, World Institute for Development Economic Research (UNU-WIDER).
    8. Rösner, Anja & Haucap, Justus & Heimeshoff, Ulrich, 2020. "The impact of consumer protection in the digital age: Evidence from the European Union," International Journal of Industrial Organization, Elsevier, vol. 73(C).
    9. Bruno Ferman, 2023. "Inference in difference‐in‐differences: How much should we trust in independent clusters?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 358-369, April.
    10. 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.
    11. Howes, Cooper, 2022. "Why does structural change accelerate in recessions? The credit reallocation channel," Journal of Financial Economics, Elsevier, vol. 144(3), pages 933-952.
    12. Clément de Chaisemartin & Xavier D’Haultfœuille, 2023. "Two-way fixed effects and differences-in-differences with heterogeneous treatment effects: a survey," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 1-30.
    13. Kurt Schmidheiny & Sebastian Siegloch, 2019. "On Event Study Designs and Distributed-Lag Models: Equivalence, Generalization and Practical Implications," CESifo Working Paper Series 7481, CESifo.
    14. Yadav, Anil & McHale, John & O'Neill, Stephen, 2023. "How does co-authoring with a star affect scientists' productivity? Evidence from small open economies," Research Policy, Elsevier, vol. 52(1).
    15. Mac Clay, Pablo & Börner, Jan & Sellare, Jorge, 2023. "Institutional and macroeconomic stability mediate the effect of auctions on renewable energy capacity," Energy Policy, Elsevier, vol. 180(C).
    16. Rik Chakraborti & Gavin Roberts, 2023. "How price-gouging regulation undermined COVID-19 mitigation: county-level evidence of unintended consequences," Public Choice, Springer, vol. 196(1), pages 51-83, July.
    17. Han, Sukjin, 2021. "Identification in nonparametric models for dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 132-147.
    18. Blesse, Sebastian & Diegmann, André, 2022. "The place-based effects of police stations on crime: Evidence from station closures," Journal of Public Economics, Elsevier, vol. 207(C).
    19. Maclean, J. Catherine & Pichler, Stefan & Ziebarth, Nicolas R., 2020. "Mandated Sick Pay: Coverage, Utilization, and Welfare Effects," IZA Discussion Papers 13132, Institute of Labor Economics (IZA).
    20. Xin Nie & Jianxian Wu & Han Wang & Weijuan Li & Chengdao Huang & Lihua Li, 2022. "Contributing to carbon peak: Estimating the causal impact of eco‐industrial parks on low‐carbon development in China," Journal of Industrial Ecology, Yale University, vol. 26(4), pages 1578-1593, August.

    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    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:2007.04267. 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.