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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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    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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