IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1809.03904.html
   My bibliography  Save this paper

Regression Discontinuity Designs Using Covariates

Author

Listed:
  • Sebastian Calonico
  • Matias D. Cattaneo
  • Max H. Farrell
  • Rocio Titiunik

Abstract

We study regression discontinuity designs when covariates are included in the estimation. We examine local polynomial estimators that include discrete or continuous covariates in an additive separable way, but without imposing any parametric restrictions on the underlying population regression functions. We recommend a covariate-adjustment approach that retains consistency under intuitive conditions, and characterize the potential for estimation and inference improvements. We also present new covariate-adjusted mean squared error expansions and robust bias-corrected inference procedures, with heteroskedasticity-consistent and cluster-robust standard errors. An empirical illustration and an extensive simulation study is presented. All methods are implemented in \texttt{R} and \texttt{Stata} software packages.

Suggested Citation

  • Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Rocio Titiunik, 2018. "Regression Discontinuity Designs Using Covariates," Papers 1809.03904, arXiv.org.
  • Handle: RePEc:arx:papers:1809.03904
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1809.03904
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Yoichi Arai & Hidehiko Ichimura, 2018. "Simultaneous selection of optimal bandwidths for the sharp regression discontinuity estimator," Quantitative Economics, Econometric Society, vol. 9(1), pages 441-482, March.
    2. Otávio Bartalotti & Quentin Brummet, 2017. "Regression Discontinuity Designs with Clustered Data," Advances in Econometrics, in: Matias D. Cattaneo & Juan Carlos Escanciano (ed.), Regression Discontinuity Designs, volume 38, pages 383-420, Emerald Publishing Ltd.
    3. A. Colin Cameron & Douglas L. Miller, 2015. "A Practitioner’s Guide to Cluster-Robust Inference," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 317-372.
    4. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, May.
    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. Andrés Elberg & Pedro M. Gardete & Rosario Macera & Carlos Noton, 2019. "Dynamic effects of price promotions: field evidence, consumer search, and supply-side implications," Quantitative Marketing and Economics (QME), Springer, vol. 17(1), pages 1-58, March.
    2. Andrew I. Friedson, 2018. "Medical Scribes as an Input in Health-Care Production: Evidence from a Randomized Experiment," American Journal of Health Economics, University of Chicago Press, vol. 4(4), pages 479-503, Fall.
    3. Knutsson, Daniel, 2020. "The Effect of Water Filtration on Cholera Mortality," Working Paper Series 1346, Research Institute of Industrial Economics.
    4. Simon Heß, 2017. "Randomization inference with Stata: A guide and software," Stata Journal, StataCorp LP, vol. 17(3), pages 630-651, September.
    5. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2021. "Cluster-Robust Inference: A Guide to Empirical Practice," Working Paper 1456, Economics Department, Queen's University.
    6. Benjamin L. Collier & Andrew F. Haughwout & Howard C. Kunreuther & Erwann O. Michel‐Kerjan, 2020. "Firms’ Management of Infrequent Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(6), pages 1329-1359, September.
    7. Hirschauer, Norbert & Grüner, Sven & Mußhoff, Oliver & Becker, Claudia & Jantsch, Antje, 2020. "Can p-values be meaningfully interpreted without random sampling?," EconStor Open Access Articles, ZBW - Leibniz Information Centre for Economics, pages 71-91.
    8. Cipullo, Davide & Reslow, André, 2019. "Biased Forecasts to Affect Voting Decisions? The Brexit Case," Working Paper Series 2019:4, Uppsala University, Department of Economics.
    9. Goenner, Cullen F, 2016. "The policy impact of new rules for loan participation on credit union returns," Journal of Banking & Finance, Elsevier, vol. 73(C), pages 198-210.
    10. Annalisa Caloffi & Marco Mariani & Alessandro Sterlacchini, 2016. "Evaluating Public Supports To The Investment Activities Of Business Firms: A Meta-Regression Analysis Of Italian Studies," Working Papers 0116, CREI Università degli Studi Roma Tre, revised 2016.
    11. Jeffrey Smith & Arthur Sweetman, 2016. "Viewpoint: Estimating the causal effects of policies and programs," Canadian Journal of Economics, Canadian Economics Association, vol. 49(3), pages 871-905, August.
    12. Dana Rotz & Paul Burkander & Mary Grider & Kenneth Fortson & Linda Molinari & Elias Sanchez-Eppler & Lindsay Cattell, "undated". "Providing Public Workforce Services to Job Seekers: 30-Month Impact Findings on the WIA Adult and Dislocated Worker Programs, Technical Supplement," Mathematica Policy Research Reports db04b33db50a4d45824da5a65, Mathematica Policy Research.
    13. B. James Deaton & Chad Lawley & Karthik Nadella, 2018. "Renters, landlords, and farmland stewardship," Agricultural Economics, International Association of Agricultural Economists, vol. 49(4), pages 521-531, July.
    14. Jan Stede, 2019. "Do Energy Efficiency Networks Save Energy? Evidence from German Plant-Level Data," Discussion Papers of DIW Berlin 1813, DIW Berlin, German Institute for Economic Research.
    15. MacKinnon, James G. & Webb, Matthew D., 2020. "Randomization inference for difference-in-differences with few treated clusters," Journal of Econometrics, Elsevier, vol. 218(2), pages 435-450.
    16. Dana Rotz & Paul Burkander & Kenneth Fortson & Sheena McConnell & Peter Schochet & Mary Grider & Linda Molinari & Elias Sanchez-Eppler, "undated". "Providing Public Workforce Services to Job Seekers: 15-Month Impact Findings on the WIA Adult and Dislocated Worker Programs (Technical Supplement)," Mathematica Policy Research Reports 1153336bee1c4a969d5341ef4, Mathematica Policy Research.
    17. Chiang, Harold D. & Hsu, Yu-Chin & Sasaki, Yuya, 2019. "Robust uniform inference for quantile treatment effects in regression discontinuity designs," Journal of Econometrics, Elsevier, vol. 211(2), pages 589-618.
    18. Ding, Peng, 2021. "The Frisch–Waugh–Lovell theorem for standard errors," Statistics & Probability Letters, Elsevier, vol. 168(C).
    19. He, Yang & Bartalotti, Otávio, 2019. "Wild Bootstrap for Fuzzy Regression Discontinuity Designs: Obtaining Robust Bias-Corrected Confidence Intervals," IZA Discussion Papers 12801, Institute of Labor Economics (IZA).
    20. Peng Ding, 2020. "The Frisch--Waugh--Lovell Theorem for Standard Errors," Papers 2009.06621, arXiv.org.

    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:1809.03904. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://arxiv.org/ .

    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 hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.