rdrobust

Robust Local Polynomial Methods for RD Designs

The package rdrobust implements estimation, inference, and graphical procedures for Regression Discontinuity (RD) designs using local polynomial methods.

• rdrobust: point estimation and robust bias-corrected inference.
• rdbwselect: data-driven bandwidth selection for RD estimation and inference.
• rdplot: data-driven RD plots based on binned means and local polynomial fits.
• rdrobustplot: postestimation diagnostic plot for Stata.

Python Implementation

To install/update in Python type:

pip install rdrobust

• Help: PYPI repository.

• Replication: rdrobust illustration, rdplot illustration, senate data.

R Implementation

To install/update in R type:

install.packages('rdrobust')

• Help: R Manual, CRAN repository.

• Examples/data: rdrobust illustration, rdplot illustration, senate data.

Stata Implementation

To install/update in Stata type:

net install rdrobust, from(https://raw.githubusercontent.com/rdpackages/rdrobust/main/stata) replace

• Help: rdrobust, rdbwselect, rdplot, rdrobustplot.

• Replication: rdrobust illustration, rdplot illustration, new features illustration, senate data.

References

For overviews and introductions, see the rdpackages website.

Software and Implementation

• Calonico, Cattaneo and Titiunik (2014): Robust Data-Driven Inference in the Regression-Discontinuity Design. Stata Journal 14(4): 909-946.
• Calonico, Cattaneo and Titiunik (2015): rdrobust: An R Package for Robust Nonparametric Inference in Regression-Discontinuity Designs. R Journal 7(1): 38-51.
• Calonico, Cattaneo, Farrell and Titiunik (2017): rdrobust: Software for Regression Discontinuity Designs. Stata Journal 17(2): 372-404.

Technical and Methodological

• Calonico, Cattaneo and Titiunik (2014): Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs. Econometrica 82(6): 2295-2326. Supplemental Appendix.
• Calonico, Cattaneo and Titiunik (2015): Optimal Data-Driven Regression Discontinuity Plots. Journal of the American Statistical Association 110(512): 1753-1769. Supplemental Appendix.
• Calonico, Cattaneo and Farrell (2018): On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference. Journal of the American Statistical Association 113(522): 767-779. Supplemental Appendix.
• Calonico, Cattaneo, Farrell and Titiunik (2019): Regression Discontinuity Designs Using Covariates. Review of Economics and Statistics 101(3): 442-451. Supplemental Appendix.
• Calonico, Cattaneo and Farrell (2020): Optimal Bandwidth Choice for Robust Bias Corrected Inference in Regression Discontinuity Designs. Econometrics Journal 23(2): 192-210. Supplemental Appendix.
• Calonico, Cattaneo and Farrell (2022): Coverage Error Optimal Confidence Intervals for Local Polynomial Regression. Bernoulli 28(4): 2998-3022. Supplemental Appendix.

Funding

This work was supported in part by the National Science Foundation through grants SES-1357561, SES-1459931, SES-1947805, and SES-2019432.