#STATA LOCAL SOFTWARE#
#STATA LOCAL CODE#

Journal of the American Statistical Association 110(512): 1753-1769.Д¬alonico, Cattaneo and Farrell (2018): On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference.

#STATA LOCAL SOFTWARE#

Software and ImplementationД¬alonico, Cattaneo and Titiunik (2014): Robust Data-Driven Inference in the Regression-Discontinuity Design.Д¬alonico, Cattaneo and Titiunik (2015): rdrobust: An R Package for Robust Nonparametric Inference in Regression-Discontinuity Designs.Д¬alonico, Cattaneo, Farrell and Titiunik (2017): rdrobust: Software for Regression Discontinuity Designs.Д¬alonico, Cattaneo and Titiunik (2014): Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs.Д¬alonico, Cattaneo and Titiunik (2015): Optimal Data-Driven Regression Discontinuity Plots. ReferencesДЇor overviews and introductions, see rdpackages website.

#STATA LOCAL CODE#

Replication: do-file, rdplot illustration, senate data.ДЇor source code and related files, visit rdrobust repository. Winter 2020 new features include: (i) discrete running variable checks and adjustments (ii) bandwidth selection adjustments for too few mass points in and/or overshooting of the support of the running variable (iii) RD Plots with additional covariates plotted at their mean (previously the package set additional covariates at zero) (iv) automatic removal of co-linear additional covariates (v) turn on/off standardization of variables (which may lead to small numerical/rounding discrepancies with prior versions) and (vi) rdplot output using ggplot2 in R. This package was first released in Spring 2014, and had two major upgrades in Fall 2016 and in Winter 2020.ДЇall 2016 new features include: (i) major speed improvements (ii) covariate-adjusted bandwidth selection, point estimation, and robust inference (iii) cluster-robust bandwidth selection, point estimation, and robust inference (iv) weighted global polynomial fits and pointwise confidence bands for RD plots and (v) several new bandwidths selectors (e.g., different bandwidths for control and treatment groups, coverage error optimal bandwidths, and optimal bandwidths for fuzzy designs). This work was supported in part by the National Science Foundation through grants SES-1357561, SES-1459931, SES-1947805 and SES-2019432. It provides point estimators, confidence intervals estimators, bandwidth selectors, automatic RD plots, and many other features. The rdrobust package provides Python, R and Stata implementations of statistical inference and graphical procedures for Regression Discontinuity designs employing local polynomial and partitioning methods.

Stata local