Local polynomial estimation, robust bias-corrected inference, and RD plots.
- Python
- R
- Stata
Robust RD Methods
RD Packages collects maintained software for estimation, inference, visualization, power analysis, density testing, local randomization, heterogeneous effects, boundary designs, and multi-cutoff or multi-score regression discontinuity designs.
Packages
Package names link directly to GitHub. The old package pages on this site now redirect to those repositories so documentation does not drift.
Estimation and inference for heterogeneous treatment effects in RD designs.
- R
- Stata
Finite-sample and large-sample analysis using local randomization methods.
- Python
- R
- Stata
Manipulation testing with local polynomial density estimation at the cutoff.
- Python
- R
- Stata
Power, sample size, and minimum detectable effects calculations for RD studies.
- Python
- R
- Stata
Estimation and inference for geographic and other boundary discontinuity designs.
- R
Methods for RD designs with multiple cutoffs, multiple scores, extrapolation, and RD plots.
- Python
- R
- Stata
Replication Files
Examples, paper replications, and companion code are collected on the replication page.
References
Selected overview articles, practical introductions, and related references for RD methods and applications.
- Cattaneo and Titiunik (2022): Regression Discontinuity Designs. Annual Review of Economics 14: 821-851.
- Cattaneo, Idrobo and Titiunik (2020): A Practical Introduction to Regression Discontinuity Designs: Foundations. Cambridge Elements: Quantitative and Computational Methods for Social Science, Cambridge University Press. Erratum.
- Cattaneo, Idrobo and Titiunik (2024): A Practical Introduction to Regression Discontinuity Designs: Extensions. Cambridge Elements: Quantitative and Computational Methods for Social Science, Cambridge University Press.
- Cattaneo, Titiunik and Yu (2026): Boundary Discontinuity Designs: Theory and Practice. Advances in Economics and Econometrics: Thirteenth World Congress, Cambridge University Press, Vol. 1, Ch. 2, to appear.
- Cattaneo, Keele and Titiunik (2023): A Guide to Regression Discontinuity Designs in Medical Applications. Statistics in Medicine 42(24): 4484-4513.
- Cattaneo, Titiunik and Vazquez-Bare (2020): The Regression Discontinuity Design. Handbook of Research Methods in Political Science and International Relations, Sage Publications, Ch. 44, pp. 835-857.
- Cattaneo, Titiunik and Vazquez-Bare (2017): Comparing Inference Approaches for RD Designs: A Reexamination of the Effect of Head Start on Child Mortality. Journal of Policy Analysis and Management 36(3): 643-681.
- Cattaneo and Titiunik (2024): Comment: Protocols for Observational Studies: An Application to Regression Discontinuity Designs. Statistical Science 39(4): 560-565.
- Cattaneo and Vazquez-Bare (2016): The Choice of Neighborhood in Regression Discontinuity Designs. Observational Studies 2: 134-146.
Contributors
Researchers and developers contributing to the RD Packages software family.
- Sebastian CalonicoUC Davis
- Matias D. CattaneoPrinceton University
- Rajita ChandakUniversity of Wisconsin-Madison
- Nicolas IdroboUniversity of Pennsylvania
- Max H. FarrellUC Santa Barbara
- Michael JanssonUC Berkeley
- Xinwei MaUC San Diego
- Ricardo MasiniUC Davis
- Filippo PalombaPrinceton University
- Rocio TitiunikPrinceton University
- Gonzalo Vazquez-BareUC Santa Barbara
- Ruiqi (Rae) YuPrinceton University
Funding
This work was supported in part by the National Science Foundation, the National Institutes of Health, and the National Institute for Food and Agriculture.