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rdlasso: Regression Discontinuity with High-Dimensional Data

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  • Marianna Nitti
  • Marco Ventura

Abstract

We present a command, rdlasso, which allows the inclusion of highdimensional covariates in Regression Discontinuity Design (RDD) settings. This command is based on the paper "Inference in Regression Discontinuity Designs with High-Dimensional Covariates" by Kreiss and Rothe (2023). The command allows for the inclusion of high-dimensional covariates in RDD for sharp and fuzzy cases, making the methodology methodology accessible to Stata users and also automating the covariate selection procedure.

Suggested Citation

  • Marianna Nitti & Marco Ventura, 2025. "rdlasso: Regression Discontinuity with High-Dimensional Data," Working Papers in Public Economics 265, Department of Economics and Law, Sapienza University of Roma.
    • Handle: RePEc:sap:wpaper:wp265
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    References listed on IDEAS

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    1. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018. "Double/debiased machine learning for treatment and structural parameters," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
    2. Timothy B Armstrong & Michal Kolesár, 2018. "A Simple Adjustment for Bandwidth Snooping," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(2), pages 732-765.
    3. 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.
    4. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "Inference on Treatment Effects after Selection among High-Dimensional Controlsâ€," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(2), pages 608-650.
    5. 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.
    6. Erik Meyersson, 2014. "Islamic Rule and the Empowerment of the Poor and Pious," Econometrica, Econometric Society, vol. 82(1), pages 229-269, January.
    7. Matias D. Cattaneo & Nicolas Idrobo & Rocio Titiunik, 2019. "A Practical Introduction to Regression Discontinuity Designs: Foundations," Papers 1911.09511, arXiv.org.
    8. Claudia Noack & Tomasz Olma & Christoph Rothe, 2021. "Flexible Covariate Adjustments in Regression Discontinuity Designs," Papers 2107.07942, arXiv.org, revised Apr 2025.
    9. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Roc ́ıo Titiunik, 2017. "rdrobust: Software for regression-discontinuity designs," Stata Journal, StataCorp LLC, vol. 17(2), pages 372-404, June.
    10. Alexander Kreiss & Christoph Rothe, 2023. "Inference in regression discontinuity designs with high-dimensional covariates," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 105-123.
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    Keywords

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    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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