rdrobust-package: Robust Data-Driven Statistical Inference in RD Designs

In rdrobust: Robust Data-Driven Statistical Inference in Regression-Discontinuity Designs

Robust Data-Driven Statistical Inference in RD Designs

Description

Regression-discontinuity (RD) designs are quasi-experimental research designs popular in social, behavioral and natural sciences. The RD design is usually employed to study the (local) causal effect of a treatment, intervention or policy. This package provides tools for data-driven graphical and analytical statistical inference in RD designs: rdrobust to construct local-polynomial point estimators and robust confidence intervals for average treatment effects at the cutoff in Sharp, Fuzzy and Kink RD settings, rdbwselect to perform bandwidth selection for the different procedures implemented, and rdplot to conduct exploratory data analysis (RD plots).

Details

Package:	rdrobust
Type:	Package
Version:	2.2
Date:	2023-11-03
License:	GPL-2

Function for statistical inference: rdrobust
Function for bandwidths selection: rdbwselect
Function for exploratory data analysis (RD plots): rdplot

Author(s)

Sebastian Calonico, Columbia University, New York, NY. [e-mail].

Matias D. Cattaneo, Princeton University, Princeton, NJ. [e-mail].

Max H. Farrell, University of California, Santa Barbara, CA. [e-mail].

Rocio Titiunik, Princeton University, Princeton, NJ. [e-mail].

rdrobust documentation built on Nov. 4, 2023, 1:07 a.m.