IDEAS home Printed from https://ideas.repec.org/p/fip/fedgfe/2025-91.html

Parallel Trends Forest: Data-Driven Control Sample Selection in Difference-in-Differences

Author

Listed:

Abstract

This paper introduces parallel trends forest, a novel approach to selecting optimal control samples when using difference-in-differences (DiD) in a relatively long panel data with little randomization in treatment assignment. Our method uses machine learning techniques to find control units that best meet the parallel trends assumption. We demonstrate that our approach outperforms existing methods, particularly with noisy, granular data. Applying the parallel trends forest to analyze the impact of post-trade transparency in corporate bond markets, we find that it produces more robust estimates compared to traditional two-way fixed effects models. Our results suggest that the effect of transparency on bond turnover is small and not statistically significant when allowing for constrained deviations from parallel trends. This method offers researchers a powerful tool for conducting more reliable DiD analyses in complex, real-world settings.

Suggested Citation

  • Yesol Huh & Matthew Kling, 2025. "Parallel Trends Forest: Data-Driven Control Sample Selection in Difference-in-Differences," Finance and Economics Discussion Series 2025-091, Board of Governors of the Federal Reserve System (U.S.).
    • Handle: RePEc:fip:fedgfe:2025-91
    DOI: 10.17016/FEDS.2025.091
    as

    Download full text from publisher

    File URL: https://www.federalreserve.gov/econres/feds/files/2025091pap.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.17016/FEDS.2025.091?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. Stefan Wager & Susan Athey, 2018. "Estimation and Inference of Heterogeneous Treatment Effects using Random Forests," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(523), pages 1228-1242, July.
    2. Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2021. "Synthetic Difference-in-Differences," American Economic Review, American Economic Association, vol. 111(12), pages 4088-4118, December.
    3. Susan Athey & Mohsen Bayati & Nikolay Doudchenko & Guido Imbens & Khashayar Khosravi, 2021. "Matrix Completion Methods for Causal Panel Data Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1716-1730, October.
    4. Ashesh Rambachan & Jonathan Roth, 2023. "A More Credible Approach to Parallel Trends," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(5), pages 2555-2591.
    5. Alberto Abadie & Javier Gardeazabal, 2003. "The Economic Costs of Conflict: A Case Study of the Basque Country," American Economic Review, American Economic Association, vol. 93(1), pages 113-132, March.
    6. Andrew Baker & Brantly Callaway & Scott Cunningham & Andrew Goodman-Bacon & Pedro H. C. Sant'Anna, 2025. "Difference-in-Differences Designs: A Practitioner's Guide," Papers 2503.13323, arXiv.org, revised Jun 2025.
    7. Hendrik Bessembinder & William Maxwell, 2008. "Markets: Transparency and the Corporate Bond Market," Journal of Economic Perspectives, American Economic Association, vol. 22(2), pages 217-234, Spring.
    8. Guojun He & Shaoda Wang, 2017. "Do College Graduates Serving as Village Officials Help Rural China?," American Economic Journal: Applied Economics, American Economic Association, vol. 9(4), pages 186-215, October.
    9. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    10. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    11. 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.
    12. Amy K. Edwards & Lawrence E. Harris & Michael S. Piwowar, 2007. "Corporate Bond Market Transaction Costs and Transparency," Journal of Finance, American Finance Association, vol. 62(3), pages 1421-1451, June.
    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. 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.
    2. Christian Alemán-Pericón & Alexander Ludwig & Christopher Busch & Raül Santaeulàlia-Llopis, 2022. "A Stage-Based Identification of Policy Effects," Working Papers 1369, Barcelona School of Economics.
    3. Jordi J. Teixidó & F. Javier Palencia-González & José M. Labeaga & Xavier Labandeira, 2024. "Carbon Leakage from Fuel Taxes: Evidence from a Natural Experiment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(12), pages 3235-3270, December.
    4. Porreca, Zachary, 2022. "Synthetic difference-in-differences estimation with staggered treatment timing," Economics Letters, Elsevier, vol. 220(C).
    5. Robert Messerle & Jonas Schreyögg, 2024. "Country-level effects of diagnosis-related groups: evidence from Germany’s comprehensive reform of hospital payments," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 25(6), pages 1013-1030, August.
    6. Sandro Heiniger, 2024. "Data-driven model selection within the matrix completion method for causal panel data models," Papers 2402.01069, arXiv.org.
    7. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Jun 2024.
    8. 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.
    9. Kishore, Prabhat & Roy, Devesh & Birthal, Pratap S. & Srivastava, Shivendra Kumar, 2024. "Regulation and Policy Response to Groundwater Preservation in India," Policy Papers 345044, ICAR National Institute of Agricultural Economics and Policy Research (NIAP).
    10. repec:ags:icar24:345044 is not listed on IDEAS
    11. Nicolaj N. Mühlbach, 2020. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," CREATES Research Papers 2020-04, Department of Economics and Business Economics, Aarhus University.
    12. Dennis Shen & Peng Ding & Jasjeet Sekhon & Bin Yu, 2022. "Same Root Different Leaves: Time Series and Cross-Sectional Methods in Panel Data," Papers 2207.14481, arXiv.org, revised Oct 2022.
    13. Zhentao Shi & Jin Xi & Haitian Xie, 2025. "A Synthetic Business Cycle Approach to Counterfactual Analysis with Nonstationary Macroeconomic Data," Papers 2505.22388, arXiv.org.
    14. Di, Wenhua & Pattison, Nathaniel, 2023. "Industry Specialization and Small Business Lending," Journal of Banking & Finance, Elsevier, vol. 149(C).
    15. Mark Kattenberg & Bas Scheer & Jurre Thiel, 2023. "Causal forests with fixed effects for treatment effect heterogeneity in difference-in-differences," CPB Discussion Paper 452, CPB Netherlands Bureau for Economic Policy Analysis.
    16. Susan Athey & Guido Imbens & Zhaonan Qu & Davide Viviano, 2025. "Triply Robust Panel Estimators," Papers 2508.21536, arXiv.org, revised Feb 2026.
    17. Goeyvaerts, Geert, 2023. "Reconstructing cities: Stimulating redevelopment through the tax code," Regional Science and Urban Economics, Elsevier, vol. 99(C).
    18. David Gilchrist & Thomas Emery & Nuno Garoupa & Rok Spruk, 2023. "Synthetic Control Method: A tool for comparative case studies in economic history," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 409-445, April.
    19. Miteva, Daniela A. & Ellis, Edward A. & Ellis, Peter W. & Sills, Erin O. & Griscom, Bronson W. & Rodriguez-Ward, Dawn & Naples, Colette & Uematsu, Claire, 2025. "Community sawmills can save forests: Forest regrowth and avoided deforestation due to vertical integration of wood production in Mexican community forests," Ecological Economics, Elsevier, vol. 236(C).
    20. Florian Gunsilius, 2020. "Distributional synthetic controls," Papers 2001.06118, arXiv.org, revised Dec 2021.
    21. Lee, Siha & Liu, Sitian, 2024. "Fertility incentives in Canada: A cohort analysis," CLEF Working Paper Series 75, Canadian Labour Economics Forum (CLEF), University of Waterloo.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • 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
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:fip:fedgfe:2025-91. 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: Ryan Wolfslayer ; Keisha Fournillier (email available below). General contact details of provider: https://edirc.repec.org/data/frbgvus.html .

    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.