Local polynomial estimation, robust bias-corrected inference, and RD plots.
- Python
- R
- Stata
Regression Discontinuity 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
Estimation and inference for heterogeneous treatment effects in RD designs.
- Python
- 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.
- Python
- R
- Stata
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 and Titiunik (2026): Using Regression Discontinuity Approaches to Evaluate Threshold-Guided Interventions. Journal of the American Medical Association, 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
- 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.