The rd2d package provides R implementations of pointwise and uniform estimation and inference for Boundary Discontinuity Designs employing local polynomial methods.
The main functions are rd2d() and rdbw2d() for location-based methods, and rd2d.distance() and rdbw2d.distance() for distance-based methods. Both approaches support sharp and fuzzy designs. The distance-based methods target the level of the boundary average treatment effect curve using bivariate scores reduced to signed distance-based running variables.
Summary methods can also report weighted and largest boundary average treatment effects (WBATE and LBATE) when the fitted object stores the required covariance matrix, including intention-to-treat, first-stage, and fuzzy outputs.
To install/update in R type:
install.packages('rd2d')
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Help: R Manual, CRAN repository.
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Illustration: Simulation and estimation, Plots.
For overviews and introductions, see rdpackages website.
- Cattaneo, Titiunik and Yu (2025): rd2d: Causal Inference in Boundary Discontinuity Designs.
Working paper.
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Cattaneo, Titiunik and Yu (2026): Boundary Discontinuity Designs: Theory and Practice.
Advances in Economics and Econometrics: Thirteenth World Congress, eds. R. Griffith, Y. Gorodnichenko, M. Kandori and F. Molinari, Cambridge University Press, Vol. 1, Ch. 2, to appear, 2026. -
Cattaneo, Titiunik and Yu (2026): Estimation and Inference in Boundary Discontinuity Designs: Location-Based Methods.
Journal of the American Statistical Association, revise and resubmit.
Supplemental Appendix. -
Cattaneo, Titiunik and Yu (2026): Estimation and Inference in Boundary Discontinuity Designs: Distance-Based Methods.
Journal of Econometrics, revise and resubmit.
Supplemental Appendix. -
Cattaneo, Titiunik and Yu (2026): Estimation and Inference in Boundary Discontinuity Designs: Pooling-Based Methods.
Working paper.
Supplemental Appendix.
This work was supported in part by the National Science Foundation through grants SES-2019432, DMS-2210561, SES-2241575, and SES-2342226, and by the National Institute for Food and Agriculture through grant 2024-67023-42704.