2025/05/12 by Matias D. Cattaneo, Rocio Titiunik, Cattaneo, Matias D. +3 · 1 voice · 1 citation
#stat.ME #econ.EM #stat.CO
paper · pdf · doi:10.48550/arxiv.2505.07989
Boundary Discontinuity (BD) designs are used in empirical research to learn about causal treatment effects along a continuous assignment boundary defined by a bivariate score. These designs are also known as multi-score regression discontinuity (RD) designs, and include geographic RD designs as a prominent example. This article introduces \pkgrd2d, a statistical software package for \proglangR, \proglangPython, and \proglangStata that implements local polynomial estimation and inference for BD designs using either the bivariate score or a univariate signed distance-to-boundary score. The software covers sharp and fuzzy BD designs, providing automatic bandwidth selection, robust bias-corrected pointwise inference, uniform confidence bands, cluster-robust inference with joint or separate fitting conventions, covariate-adjusted efficiency improvements, mass-point checks, and covariance regularization, among other features. We illustrate the package with an empirical application to Opportunity Zones, where eligibility has a strong first-stage effect on designation but no significant effects on early workplace-job growth.