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rdlasso: Regression discontinuity with high-dimensional data

Author

Listed:
  • Marianna Nitti

    (Università degli Studi di Roma “La Sapienza”)

  • Marco Ventura

    (Università degli Studi di Roma “La Sapienza”)

Abstract

We present the rdlasso command, which enables the inclusion of high-dimensional 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 automates covariate selection using lasso-based procedures, supports both sharp and fuzzy settings, and integrates seamlessly with rdrobust for bandwidth selection and inference. The command relies on Stata’s native implementation of lasso for high-dimensional covariate selection and on rdrobust for bandwidth selection, estimation, and inference, making the methodology both accessible to Stata users and computationally feasible for applied researchers.

Suggested Citation

  • Marianna Nitti & Marco Ventura, "undated". "rdlasso: Regression discontinuity with high-dimensional data," Italian Stata Conference 2026 05, Stata Users Group.
    • Handle: RePEc:boc:ital26:05
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