IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2110.08410.html
   My bibliography  Save this paper

Covariate Adjustment in Regression Discontinuity Designs

Author

Listed:
  • Matias D. Cattaneo
  • Luke Keele
  • Rocio Titiunik

Abstract

The Regression Discontinuity (RD) design is a widely used non-experimental method for causal inference and program evaluation. While its canonical formulation only requires a score and an outcome variable, it is common in empirical work to encounter RD analyses where additional variables are used for adjustment. This practice has led to misconceptions about the role of covariate adjustment in RD analysis, from both methodological and empirical perspectives. In this chapter, we review the different roles of covariate adjustment in RD designs, and offer methodological guidance for its correct use.

Suggested Citation

  • Matias D. Cattaneo & Luke Keele & Rocio Titiunik, 2021. "Covariate Adjustment in Regression Discontinuity Designs," Papers 2110.08410, arXiv.org, revised Aug 2022.
    • Handle: RePEc:arx:papers:2110.08410
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2110.08410
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Keele, Luke J. & Titiunik, Rocío, 2015. "Geographic Boundaries as Regression Discontinuities," Political Analysis, Cambridge University Press, vol. 23(1), pages 127-155, January.
    2. Davezies, Laurent & Le Barbanchon, Thomas, 2017. "Regression discontinuity design with continuous measurement error in the running variable," Journal of Econometrics, Elsevier, vol. 200(2), pages 260-281.
    3. Markus Frölich & Martin Huber, 2019. "Including Covariates in the Regression Discontinuity Design," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 736-748, October.
    4. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Rocío Titiunik, 2019. "Regression Discontinuity Designs Using Covariates," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 442-451, July.
    5. Bertanha, Marinho, 2020. "Regression discontinuity design with many thresholds," Journal of Econometrics, Elsevier, vol. 218(1), pages 216-241.
    6. Sebastian Calonico & Matias D. Cattaneo & Rocio Titiunik, 2014. "Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs," Econometrica, Econometric Society, vol. 82, pages 2295-2326, November.
    7. Sebastian Calonico & Matias D Cattaneo & Max H Farrell, 2020. "Optimal bandwidth choice for robust bias-corrected inference in regression discontinuity designs [Econometric methods for program evaluation]," The Econometrics Journal, Royal Economic Society, vol. 23(2), pages 192-210.
    8. Otávio Bartalotti & Quentin Brummet & Steven Dieterle, 2021. "A Correction for Regression Discontinuity Designs With Group-Specific Mismeasurement of the Running Variable," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 833-848, July.
    9. Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
    10. Myung Hwan Seo & Yoichi Arai & Taisuke Otsu, 2021. "Regression Discontinuity Design with Potentially Many Covariates," Working Paper Series no142, Institute of Economic Research, Seoul National University.
    11. Burt S. Barnow & Matias D. Cattaneo & Rocío Titiunik & Gonzalo Vazquez‐Bare, 2017. "Comparing Inference Approaches for RD Designs: A Reexamination of the Effect of Head Start on Child Mortality," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 36(3), pages 643-681, June.
    12. Guido Imbens & Karthik Kalyanaraman, 2012. "Optimal Bandwidth Choice for the Regression Discontinuity Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 933-959.
    13. Joshua D. Angrist & Miikka Rokkanen, 2015. "Wanna Get Away? Regression Discontinuity Estimation of Exam School Effects Away From the Cutoff," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1331-1344, December.
    14. Hsu, Yu-Chin & Shen, Shu, 2019. "Testing treatment effect heterogeneity in regression discontinuity designs," Journal of Econometrics, Elsevier, vol. 208(2), pages 468-486.
    15. Hahn, Jinyong & Todd, Petra & Van der Klaauw, Wilbert, 2001. "Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design," Econometrica, Econometric Society, vol. 69(1), pages 201-209, January.
    16. Zhuan Pei & Yi Shen, 2017. "The Devil is in the Tails: Regression Discontinuity Design with Measurement Error in the Assignment Variable," Advances in Econometrics, in: Regression Discontinuity Designs, volume 38, pages 455-502, Emerald Group Publishing Limited.
    17. Rebecca A. Maynard & Kenneth A. Couch & Coady Wing & Thomas D. Cook, 2013. "Strengthening The Regression Discontinuity Design Using Additional Design Elements: A Within‐Study Comparison," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 32(4), pages 853-877, September.
    18. Geneletti, Sara & O'Keeffe, Aidan G. & Sharples, Linda D. & Richardson, Sylvia & Baio, Gianluca, 2015. "Bayesian regression discontinuity designs: incorporating clinical knowledge in the causal analysis of primary care data," LSE Research Online Documents on Economics 65600, London School of Economics and Political Science, LSE Library.
    19. Rosenbaum, Paul R., 2010. "Design Sensitivity and Efficiency in Observational Studies," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 692-702.
    20. Veronica Grembi & Tommaso Nannicini & Ugo Troiano, 2016. "Do Fiscal Rules Matter?," American Economic Journal: Applied Economics, American Economic Association, vol. 8(3), pages 1-30, July.
    21. Otávio Bartalotti & Quentin Brummet, 2017. "Regression Discontinuity Designs with Clustered Data," Advances in Econometrics, in: Regression Discontinuity Designs, volume 38, pages 383-420, Emerald Group Publishing Limited.
    22. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881.
    23. Siddhartha Chib & Liana Jacobi, 2016. "Bayesian Fuzzy Regression Discontinuity Analysis and Returns to Compulsory Schooling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 1026-1047, September.
    24. 'Agoston Reguly, 2021. "Heterogeneous Treatment Effects in Regression Discontinuity Designs," Papers 2106.11640, arXiv.org, revised Oct 2021.
    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. Fontana, Nicola & Nannicini, Tommaso & Tabellini, Guido, 2023. "Historical roots of political extremism: The effects of Nazi occupation of Italy," Journal of Comparative Economics, Elsevier, vol. 51(3), pages 723-743.
    2. Fürstenau, Elisabeth & Gohl, Niklas & Haan, Peter & Weinhardt, Felix, 2023. "Working life and human capital investment: Causal evidence from a pension reform," Labour Economics, Elsevier, vol. 84(C).
    3. Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
    4. Mari, Gabriele, 2023. "Less for more? Cuts to child benefits, family adjustments, and long-run child outcomes in larger families," SocArXiv e3n82, Center for Open Science.
    5. Junquera, Álvaro F., 2024. "More money, more effect? Employment effects of job search programs in Veneto," SocArXiv rjshu, Center for Open Science.
    6. Geloso, Vincent & Kufenko, Vadim & Arsenault-Morin, Alex P., 2023. "The lesser shades of labor coercion: The impact of seigneurial tenure in nineteenth-century Quebec," Journal of Development Economics, Elsevier, vol. 163(C).
    7. Bragança, Arthur & Dahis, Ricardo, 2022. "Cutting special interests by the roots: Evidence from the Brazilian Amazon," Journal of Public Economics, Elsevier, vol. 215(C).
    8. de Bruijn, Ernst-Jan & Vethaak, Heike & Koning, Pierre & Knoef, Marike, 2023. "Debt Relief for the Financially Vulnerable: Impact on Employment, Welfare Receipt, and Mental Health," IZA Discussion Papers 16336, Institute of Labor Economics (IZA).
    9. Rivers, Nicholas & Woerman, Matt & Yassin, Kareman, 2023. "Yellow Vests, Pessimistic Beliefs, and Carbon Tax Aversion (2022): A Comment," I4R Discussion Paper Series 58, The Institute for Replication (I4R).
    10. Ruiqi Rich Zhu & Cheng He & Yu Jeffrey Hu, 2023. "The Effect of Product Recommendations on Online Investor Behaviors," Papers 2303.14263, arXiv.org, revised Nov 2023.
    11. Han, Luyi & Pan, Yuxuan & Goetz, Stephan J. & Rupasingha, Anil, 2023. "Impact of Community Reinvestment Act on Minority and Female Employment Growth," 2023 Annual Meeting, July 23-25, Washington D.C. 335703, Agricultural and Applied Economics Association.
    12. Ayad, Fayssal, 2023. "Mapping the path forward: A prospective model of natural resource depletion and sustainable development," Resources Policy, Elsevier, vol. 85(PA).
    13. Penney, Jeffrey & Lehrer, Steven F. & Bernal, Gloria L. & Reyes, Luis Carlos, 2023. "Do opportunities for low-income students at top colleges promote academic success? Evidence from Colombia's Ser Pilo Paga program," CLEF Working Paper Series 64, Canadian Labour Economics Forum (CLEF), University of Waterloo.
    14. Haitian Xie, 2022. "Nonlinear and Nonseparable Structural Functions in Fuzzy Regression Discontinuity Designs," Papers 2204.08168, arXiv.org, revised Jul 2022.

    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. Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
    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. Yu‐Chin Hsu & Shu Shen, 2021. "Testing monotonicity of conditional treatment effects under regression discontinuity designs," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 346-366, April.
    4. Blaise Melly & Rafael Lalive, 2020. "Estimation, Inference, and Interpretation in the Regression Discontinuity Design," Diskussionsschriften dp2016, Universitaet Bern, Departement Volkswirtschaft.
    5. Yoichi Arai & Yu‐Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2022. "Testing identifying assumptions in fuzzy regression discontinuity designs," Quantitative Economics, Econometric Society, vol. 13(1), pages 1-28, January.
    6. Yang He & Otávio Bartalotti, 2020. "Wild bootstrap for fuzzy regression discontinuity designs: obtaining robust bias-corrected confidence intervals [Using Maimonides’ rule to estimate the effect of class size on scholastic achievemen," The Econometrics Journal, Royal Economic Society, vol. 23(2), pages 211-231.
    7. Matias D. Cattaneo & Luke Keele & Rocio Titiunik, 2023. "A Guide to Regression Discontinuity Designs in Medical Applications," Papers 2302.07413, arXiv.org, revised May 2023.
    8. Masayuki Sawada & Takuya Ishihara & Daisuke Kurisu & Yasumasa Matsuda, 2024. "Local-Polynomial Estimation for Multivariate Regression Discontinuity Designs," Papers 2402.08941, arXiv.org.
    9. Atı̇la Abdulkadı̇roğlu & Joshua D. Angrist & Yusuke Narita & Parag Pathak, 2022. "Breaking Ties: Regression Discontinuity Design Meets Market Design," Econometrica, Econometric Society, vol. 90(1), pages 117-151, January.
    10. 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.
    11. Crespo Cristian, 2020. "Beyond Manipulation: Administrative Sorting in Regression Discontinuity Designs," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 164-181, January.
    12. Babii, Andrii & Kumar, Rohit, 2023. "Isotonic regression discontinuity designs," Journal of Econometrics, Elsevier, vol. 234(2), pages 371-393.
    13. Matias D. Cattaneo & Luke Keele & Rocío Titiunik & Gonzalo Vazquez-Bare, 2021. "Extrapolating Treatment Effects in Multi-Cutoff Regression Discontinuity Designs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1941-1952, October.
    14. Yusuke Narita & Kohei Yata, 2021. "Algorithm is Experiment: Machine Learning, Market Design, and Policy Eligibility Rules," Working Papers 2021-022, Human Capital and Economic Opportunity Working Group.
    15. Myung Hwan Seo & Yoichi Arai & Taisuke Otsu, 2021. "Regression Discontinuity Design with Potentially Many Covariates," Working Paper Series no142, Institute of Economic Research, Seoul National University.
    16. Jin-young Choi & Myoung-jae Lee, 2017. "Regression discontinuity: review with extensions," Statistical Papers, Springer, vol. 58(4), pages 1217-1246, December.
    17. Crespo Cristian, 2020. "Beyond Manipulation: Administrative Sorting in Regression Discontinuity Designs," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 164-181, January.
    18. Dean Eckles & Nikolaos Ignatiadis & Stefan Wager & Han Wu, 2020. "Noise-Induced Randomization in Regression Discontinuity Designs," Papers 2004.09458, arXiv.org, revised Nov 2023.
    19. David Wuepper & Robert Finger, 2023. "Regression discontinuity designs in agricultural and environmental economics," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(1), pages 1-28.
    20. Sebastian Calonico & Matias D Cattaneo & Max H Farrell, 2020. "Optimal bandwidth choice for robust bias-corrected inference in regression discontinuity designs [Econometric methods for program evaluation]," The Econometrics Journal, Royal Economic Society, vol. 23(2), pages 192-210.

    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:2110.08410. 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.