IDEAS home Printed from https://ideas.repec.org/a/bpj/causin/v12y2024i1p21n1.html
   My bibliography  Save this article

Regression(s) discontinuity: Using bootstrap aggregation to yield estimates of RD treatment effects

Author

Listed:
  • Long Mark C.

    (School of Public Policy, University of California, Riverside, USA)

  • Rooklyn Jordan

    (Cascade Analysis, Ashland, Oregon, USA)

Abstract

Following Efron (2014), we propose an algorithm for estimating treatment effects for use by researchers employing a regression-discontinuity (RD) design. This algorithm generates a set of estimates of the treatment effect from bootstrapped samples, wherein the polynomial-selection algorithm developed by Pei, Lee, Card, and Weber (2021) is applied to each sample, the average of these RD treatment effect (RDTE) estimates is computed and serves as the overall estimate of the RDTE. Effectively, this procedure estimates a set of plausible RD estimates and weights the estimates by their likelihood of being the best estimate to form a weighted-average estimate. We discuss why this procedure may lower the estimate’s root mean squared error (RMSE). In simulation results, we show that this better performance is achieved, yielding up to a 5% reduction in RMSE relative to PLCW’s method and a 16% reduction in RMSE relative to Calonico, Cattaneo, and Titiunik’s (2014) method for bandwidth selection (with default settings).

Suggested Citation

  • Long Mark C. & Rooklyn Jordan, 2024. "Regression(s) discontinuity: Using bootstrap aggregation to yield estimates of RD treatment effects," Journal of Causal Inference, De Gruyter, vol. 12(1), pages 1-21, January.
    • Handle: RePEc:bpj:causin:v:12:y:2024:i:1:p:21:n:1
    DOI: 10.1515/jci-2022-0028
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/jci-2022-0028
    Download Restriction: no
    File URL: https://libkey.io/10.1515/jci-2022-0028?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. Bradley Efron, 2014. "Estimation and Accuracy After Model Selection," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 991-1007, September.
    2. Sebastian Calonico & Matias D. Cattaneo & Rocio Titiunik, 2014. "Robust data-driven inference in the regression-discontinuity design," Stata Journal, StataCorp LP, vol. 14(4), pages 909-946, December.
    3. Jens Ludwig & Douglas L. Miller, 2007. "Does Head Start Improve Children's Life Chances? Evidence from a Regression Discontinuity Design," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(1), pages 159-208.
    4. Sebastian Calonico & Matias D Cattaneo & Max H Farrell, 2020. "Optimal bandwidth choice for robust bias-corrected inference in regression discontinuity designs," The Econometrics Journal, Royal Economic Society, vol. 23(2), pages 192-210.
    5. Andrew Gelman & Guido Imbens, 2019. "Why High-Order Polynomials Should Not Be Used in Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 447-456, July.
    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. Pastore, Chiara & Jones, Andrew M., 2023. "Human capital consequences of missing out on a grammar school education," Economic Modelling, Elsevier, vol. 126(C).
    2. Mauricio Villamizar‐Villegas & Freddy A. Pinzon‐Puerto & Maria Alejandra Ruiz‐Sanchez, 2022. "A comprehensive history of regression discontinuity designs: An empirical survey of the last 60 years," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1130-1178, September.
    3. Peter Ganong & Simon Jäger, 2018. "A Permutation Test for the Regression Kink Design," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 494-504, April.
    4. Nicholas Barton & Tessa Bold & Justin Sandefur, 2017. "Measuring Rents from Public Employment: Regression Discontinuity Evidence from Kenya - Working Paper 457," Working Papers 457, Center for Global Development.
    5. Yang He & Otávio Bartalotti, 2020. "Wild bootstrap for fuzzy regression discontinuity designs: obtaining robust bias-corrected confidence intervals," The Econometrics Journal, Royal Economic Society, vol. 23(2), pages 211-231.
    6. Bold, Tessa & Barton, Nicholas & Sandefur, Justin, 2017. "Measuring Rents from Public Employment: Regression discontinuity evidence from Kenya," CEPR Discussion Papers 12105, C.E.P.R. Discussion Papers.
    7. Albanese, Giuseppe & Carrieri, Vincenzo & Speziali, Maria Maddalena, 2021. "Looking for a Star: Evaluating the Effect of the Cohesion Policy on Regional Well-Being," IZA Discussion Papers 14521, Institute of Labor Economics (IZA).
    8. Marinho Bertanha & Guido W. Imbens, 2020. "External Validity in Fuzzy Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(3), pages 593-612, July.
    9. Mohamed Ebeid & Umut Oguzoglu, 2023. "Short‐term effect of retirement on health: Evidence from nonparametric fuzzy regression discontinuity design," Health Economics, John Wiley & Sons, Ltd., vol. 32(6), pages 1323-1343, June.
    10. de Gendre, Alexandra & Lynch, John & Meunier, Aurélie & Pilkington, Rhiannon & Schurer, Stefanie, 2021. "Child Health and Parental Responses to an Unconditional Cash Transfer at Birth," IZA Discussion Papers 14693, Institute of Labor Economics (IZA).
    11. Mohamed Abouaziza, 2022. "Farmer constraints and relational contracts: evidence from agricultural value chains in East Africa," Economics PhD Theses 0122, Department of Economics, University of Sussex Business School.
    12. Meier, Pascal Flurin & Flepp, Raphael & Franck, Egon, 2023. "Replication: Do coaches stick with what barely worked? Evidence of outcome bias in sports," Journal of Economic Psychology, Elsevier, vol. 99(C).
    13. Shamsuddin, Mrittika & Acosta, Pablo A. & Schwengber, Rovane Battaglin & Fix, Jedediah & Pirani, Nikolas, 2022. "The Labor Market Impacts of Venezuelan Refugees and Migrants in Brazil," IZA Discussion Papers 15384, Institute of Labor Economics (IZA).
    14. Arteaga, Irma & Heflin, Colleen & Gable, Sara, 2016. "The impact of aging out of WIC on food security in households with children," Children and Youth Services Review, Elsevier, vol. 69(C), pages 82-96.
    15. Hasan, Rana & Jiang, Yi & Rafols, Radine Michelle, 2021. "Place-based preferential tax policy and industrial development: Evidence from India’s program on industrially backward districts," Journal of Development Economics, Elsevier, vol. 150(C).
    16. Richard Bluhm & Maxim Pinkovskiy, 2021. "The spread of COVID-19 and the BCG vaccine: A natural experiment in reunified Germany," The Econometrics Journal, Royal Economic Society, vol. 24(3), pages 353-376.
    17. Munari, Federico & Toschi, Laura, 2021. "The impact of public funding on science valorisation: an analysis of the ERC Proof-of-Concept Programme," Research Policy, Elsevier, vol. 50(6).
    18. Christina Korting & Carl Lieberman & Jordan Matsudaira & Zhuan Pei & Yi Shen, 2023. "Visual Inference and Graphical Representation in Regression Discontinuity Designs," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(3), pages 1977-2019.
    19. Feng, Li & Figlio, David & Sass, Tim, 2018. "School accountability and teacher mobility," Journal of Urban Economics, Elsevier, vol. 103(C), pages 1-17.
    20. Jonas Jessen & Daniel Kuehnle & Markus Wagner, 2021. "Is Voting Really Habit-Forming and Transformative? Long-Run Effects of Earlier Eligibility on Turnout and Political Involvement from the UK," Discussion Papers of DIW Berlin 1973, DIW Berlin, German Institute for Economic Research.

    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:bpj:causin:v:12:y:2024:i:1:p:21:n:1. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.