IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2309.15983.html
   My bibliography  Save this paper

Causal Panel Analysis under Parallel Trends: Lessons from A Large Reanalysis Study

Author

Listed:
  • Albert Chiu
  • Xingchen Lan
  • Ziyi Liu
  • Yiqing Xu

Abstract

Two-way fixed effects (TWFE) models are widely used in political science to establish causality, but recent methodological discussions highlight their limitations under heterogeneous treatment effects (HTE) and violations of the parallel trends (PT) assumption. This growing literature has introduced new estimators and diagnostics, causing confusion among researchers about the reliability of existing results and best practices. To address these concerns, we replicated and reanalyzed 49 articles from leading journals using TWFE models for observational panel data with binary treatments. Using six HTE-robust estimators, diagnostic tests, and sensitivity analyses, we find: (i) HTE-robust estimators yield qualitatively similar but highly variable results; (ii) while a few studies show clear signs of PT violations, many lack evidence to support this assumption; and (iii) many studies are underpowered when accounting for HTE and potential PT violations. We emphasize the importance of strong research designs and rigorous validation of key identifying assumptions.

Suggested Citation

  • Albert Chiu & Xingchen Lan & Ziyi Liu & Yiqing Xu, 2023. "Causal Panel Analysis under Parallel Trends: Lessons from A Large Reanalysis Study," Papers 2309.15983, arXiv.org, revised Nov 2024.
    • Handle: RePEc:arx:papers:2309.15983
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2309.15983
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alexander Fouirnaies & Andrew B. Hall, 2018. "How Do Interest Groups Seek Access to Committees?," American Journal of Political Science, John Wiley & Sons, vol. 62(1), pages 132-147, January.
    2. Greg Distelhorst & Richard M. Locke, 2018. "Does Compliance Pay? Social Standards and Firm‐Level Trade," American Journal of Political Science, John Wiley & Sons, vol. 62(3), pages 695-711, July.
    3. Alberto Abadie & Susan Athey & Guido W Imbens & Jeffrey M Wooldridge, 2023. "When Should You Adjust Standard Errors for Clustering?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(1), pages 1-35.
    4. Jushan Bai & Serena Ng, 2021. "Matrix Completion, Counterfactuals, and Factor Analysis of Missing Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1746-1763, October.
    5. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    6. Paglayan, Agustina S., 2022. "Education or Indoctrination? The Violent Origins of Public School Systems in an Era of State-Building," American Political Science Review, Cambridge University Press, vol. 116(4), pages 1242-1257, November.
    7. Junyan Jiang, 2018. "Making Bureaucracy Work: Patronage Networks, Performance Incentives, and Economic Development in China," American Journal of Political Science, John Wiley & Sons, vol. 62(4), pages 982-999, October.
    8. Kirill Borusyak & Xavier Jaravel & Jann Spiess, 2024. "Revisiting Event-Study Designs: Robust and Efficient Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(6), pages 3253-3285.
    9. Jens Hainmueller & Dominik Hangartner, 2019. "Does Direct Democracy Hurt Immigrant Minorities? Evidence from Naturalization Decisions in Switzerland," American Journal of Political Science, John Wiley & Sons, vol. 63(3), pages 530-547, July.
    10. Dmitry Arkhangelsky & Guido W Imbens, 2022. "Doubly robust identification for causal panel data models [Sufficient statistics for unobserved heterogeneity in structural dynamic logit models]," The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 649-674.
    11. Callaway, Brantly & Karami, Sonia, 2023. "Treatment effects in interactive fixed effects models with a small number of time periods," Journal of Econometrics, Elsevier, vol. 233(1), pages 184-208.
    12. Alexander Fouirnaies, 2018. "When Are Agenda Setters Valuable?," American Journal of Political Science, John Wiley & Sons, vol. 62(1), pages 176-191, January.
    13. 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.
    14. Magaloni, Beatriz & Franco-Vivanco, Edgar & Melo, Vanessa, 2020. "Killing in the Slums: Social Order, Criminal Governance, and Police Violence in Rio de Janeiro," American Political Science Review, Cambridge University Press, vol. 114(2), pages 552-572, May.
    15. Lall, Ranjit, 2016. "How Multiple Imputation Makes a Difference," Political Analysis, Cambridge University Press, vol. 24(4), pages 414-433.
    16. Dmitry Arkhangelsky & Guido W. Imbens, 2019. "Doubly Robust Identification for Causal Panel Data Models," Papers 1909.09412, arXiv.org, revised Feb 2022.
    17. Martin Bisgaard & Rune Slothuus, 2018. "Partisan Elites as Culprits? How Party Cues Shape Partisan Perceptual Gaps," American Journal of Political Science, John Wiley & Sons, vol. 62(2), pages 456-469, April.
    18. Andrew J. Clarke, 2020. "Party Sub‐Brands and American Party Factions," American Journal of Political Science, John Wiley & Sons, vol. 64(3), pages 452-470, July.
    19. Andrew C. Eggers & Anthony Fowler & Jens Hainmueller & Andrew B. Hall & James M. Snyder, 2015. "On the Validity of the Regression Discontinuity Design for Estimating Electoral Effects: New Evidence from Over 40,000 Close Races," American Journal of Political Science, John Wiley & Sons, vol. 59(1), pages 259-274, January.
    20. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    21. Fouirnaies, Alexander & Hall, Andrew B., 2022. "How Do Electoral Incentives Affect Legislator Behavior? Evidence from U.S. State Legislatures," American Political Science Review, Cambridge University Press, vol. 116(2), pages 662-676, May.
    22. 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.
    23. Plümper, Thomas & Troeger, Vera E., 2019. "Not so Harmless After All: The Fixed-Effects Model," Political Analysis, Cambridge University Press, vol. 27(1), pages 21-45, January.
    24. Beck, Nathaniel & Katz, Jonathan N., 2001. "Throwing Out the Baby with the Bath Water: A Comment on Green, Kim, and Yoon," International Organization, Cambridge University Press, vol. 55(2), pages 487-495, April.
    25. Hainmueller, Jens & Mummolo, Jonathan & Xu, Yiqing, 2019. "How Much Should We Trust Estimates from Multiplicative Interaction Models? Simple Tools to Improve Empirical Practice," Political Analysis, Cambridge University Press, vol. 27(2), pages 163-192, April.
    26. Payson, Julia A., 2020. "The Partisan Logic of City Mobilization: Evidence from State Lobbying Disclosures," American Political Science Review, Cambridge University Press, vol. 114(3), pages 677-690, August.
    27. Baker, Andrew C. & Larcker, David F. & Wang, Charles C.Y., 2022. "How much should we trust staggered difference-in-differences estimates?," Journal of Financial Economics, Elsevier, vol. 144(2), pages 370-395.
    28. Trounstine, Jessica, 2020. "The Geography of Inequality: How Land Use Regulation Produces Segregation," American Political Science Review, Cambridge University Press, vol. 114(2), pages 443-455, May.
    29. Daniel Bischof & Markus Wagner, 2019. "Do Voters Polarize When Radical Parties Enter Parliament?," American Journal of Political Science, John Wiley & Sons, vol. 63(4), pages 888-904, October.
    30. Jonathan Roth, 2022. "Pretest with Caution: Event-Study Estimates after Testing for Parallel Trends," American Economic Review: Insights, American Economic Association, vol. 4(3), pages 305-322, September.
    31. Kosuke Imai & In Song Kim, 2019. "When Should We Use Unit Fixed Effects Regression Models for Causal Inference with Longitudinal Data?," American Journal of Political Science, John Wiley & Sons, vol. 63(2), pages 467-490, April.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Bogatyrev, Konstantin & Stoetzer, Lukas, 2024. "Synthetic Control Methods for Proportions," OSF Preprints brhd3, Center for Open Science.
    2. Ulbing, Philipp, 2024. "The Zero Lower Bound on Household Deposit Rates: Not As Binding As We Thought," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302353, Verein für Socialpolitik / German Economic Association.
    3. Rüttenauer, Tobias & Kapelle, Nicole, 2024. "Panel Data Analysis," SocArXiv 3mfzq, Center for Open Science.
    4. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Jun 2024.
    5. Strezhnev, Anton, 2024. "Group-specific linear trends and the triple-differences in time design," SocArXiv dg5ps, Center for Open Science.
    6. Weiss, Amanda, 2024. "How Much Should We Trust Modern Difference-in-Differences Estimates?," OSF Preprints bqmws, Center for Open Science.
    7. Tobias Ruttenauer & Ozan Aksoy, 2024. "When Can We Use Two-Way Fixed-Effects (TWFE): A Comparison of TWFE and Novel Dynamic Difference-in-Differences Estimators," Papers 2402.09928, arXiv.org, revised Apr 2024.

    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. Gregory Faletto, 2023. "Fused Extended Two-Way Fixed Effects for Difference-in-Differences With Staggered Adoptions," Papers 2312.05985, arXiv.org, revised Oct 2024.
    2. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Jun 2024.
    3. 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.
    4. Arold, W. Benjamin & Woessmann, Ludger & Zierow, Larissa, 2022. "Can Schools Change Religious Attitudes? Evidence from German State Reforms of Compulsory Religious Education," IZA Discussion Papers 14989, Institute of Labor Economics (IZA).
    5. Kamila Cygan-Rehm, 2022. "Lifetime Consequences of Lost Instructional Time in the Classroom: Evidence from Shortened School Years," CESifo Working Paper Series 9892, CESifo.
    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. Nilsen, Øivind A. & Raknerud, Arvid, 2024. "Dynamics of first-time patenting firms," Research Policy, Elsevier, vol. 53(8).
    8. Chen, Jidong & Shi, Xinzheng & Zhang, Ming-ang & Zhang, Sihan, 2024. "Centralization of environmental administration and air pollution: Evidence from China," Journal of Environmental Economics and Management, Elsevier, vol. 126(C).
    9. 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.
    10. Schoner, Florian & Mergele, Lukas & Zierow, Larissa, 2024. "Grading student behavior," Labour Economics, Elsevier, vol. 90(C).
    11. Matthias Breuer & Ed Dehaan, 2024. "Using and Interpreting Fixed Effects Models," Journal of Accounting Research, Wiley Blackwell, vol. 62(4), pages 1183-1226, September.
    12. repec:ags:aaea22:335779 is not listed on IDEAS
    13. Millar, Melanie I. & White, Roger M., 2024. "Do residential property assessed clean energy (PACE) financing programs affect local house price growth?," Journal of Environmental Economics and Management, Elsevier, vol. 124(C).
    14. Stefan Szymanski, 2023. "Anticipating the honeymoon: Event study estimation of new stadium effects in Major League Baseball using the imputation method," Economic Inquiry, Western Economic Association International, vol. 61(4), pages 1077-1102, October.
    15. Traviss Cassidy & Mark Dincecco & Ugo Antonio Troiano, 2024. "The Introduction of the Income Tax, Fiscal Capacity, and Migration: Evidence from US States," American Economic Journal: Economic Policy, American Economic Association, vol. 16(1), pages 359-393, February.
    16. Kihwan Bae & Edward Timmons, 2023. "Now You Can Take It with You: Effects of Occupational Credential Recognition on Labor Market Outcomes," Working Papers 23-03, Department of Economics, West Virginia University.
    17. Ruonan Xu & Luther Yap, 2024. "Clustering with Potential Multidimensionality: Inference and Practice," Papers 2411.13372, arXiv.org.
    18. Leek, Lauren Caroline & Bischl, Simeon, 2024. "How Central Bank Independence Shapes Monetary Policy Communication: A Large Language Model Application," SocArXiv yrhka, Center for Open Science.
    19. Büchler, Simon & Lutz, Elena, 2024. "Making housing affordable? The local effects of relaxing land-use regulation," Journal of Urban Economics, Elsevier, vol. 143(C).
    20. 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.
    21. Sarah Gust, 2024. "(Not) Going to School in Times of Climate Change: Natural Disasters and Student Achievement," ifo Working Paper Series 413, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.

    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:2309.15983. 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.