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: <code><a href="/link/rdrobust?package=rdrobust&version=0.70" rd-options="" data-mini-rdoc="rdrobust::rdrobust">rdrobust</a></code> to construct local-polynomial point estimators and robust confidence intervals for average treatment effects at the cutoff in Sharp, Fuzzy and Kink RD settings, <code><a href="/link/rdbwselect?package=rdrobust&version=0.70" rd-options="" data-mini-rdoc="rdrobust::rdbwselect">rdbwselect</a></code> to perform bandwidth selection for the different procedures implemented, and <code><a href="/link/rdplot?package=rdrobust&version=0.70" rd-options="" data-mini-rdoc="rdrobust::rdplot">rdplot</a></code> to conduct exploratory data analysis (RD plots).

rdrobust-package

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).

Sebastian Calonico

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rdrobust-package: Robust data-driven statistical inference in RD designs

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