Inference in Regression Discontinuity Designs under Local Randomization

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Synthetic Control Method: Inference, Sensitivity Analysis and Confidence Sets (2018, methodology): “Cattaneo et al. (2016) exemplify one way to apply similar tools to a regression discontinuity design.”
Regression Discontinuity Designs (2021, unknown): “A formalization of the Multiple-Cutoff RD design was given in Cattaneo et al. (2016), and a practical discussion can be found in Section 4 in Cattaneo, Idrobo and Titiunik (2024).”
Breaking Ties: Regression Discontinuity Design Meets Market Design (2019, background): “Each school ranks these proposals, first by priority then by tie-breaker within priority groups, provi(8)The connection between continuity of running variable distributions and conditional expectation functions is noted by Dong (2018) and Arai et al.”
A Practical Introduction to Regression Discontinuity Designs (2019, methodology): “The accompanying package rdlocrand, which is presented and illustrated by Cattaneo, Titiunik, and Vazquez-Bare (2016), implements the local randomization methods discussed in the second Element.”
Power calculations for regression-discontinuity designs (2019, background): “See Cattaneo, Titiunik, and Vazquez-Bare (2016) for an introduction to the commands rdrandinf, rdwinselect, rdsensitivity, and rdrbounds for implementing randomization-based inference methods for RD designs under a local randomization assumption.”