rd2d: Causal Inference in Boundary Discontinuity Designs

Matias Cattaneo, Rocio Titiunik and Ruiqi Rae Yu

Papers from arXiv.org

Abstract: Boundary discontinuity designs -- also known as Multi-Score Regression Discontinuity (RD) designs, with Geographic RD designs as a prominent example -- are often used in empirical research to learn about causal treatment effects along a continuous assignment boundary defined by a bivariate score. This article introduces the R package rd2d, which implements and extends the methodological results developed in Cattaneo, Titiunik and Yu (2025) for boundary discontinuity designs. The package employs local polynomial estimation and inference using either the bivariate score or a univariate distance-to-boundary metric. It features novel data-driven bandwidth selection procedures, and offers both pointwise and uniform estimation and inference along the assignment boundary. The numerical performance of the package is demonstrated through a simulation study.

Date: 2025-05, Revised 2025-06
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/2505.07989 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2505.07989

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().