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Analysis of Regression Discontinuity Designs with Multiple Cutoffs or Multiple Scores

Matias D. Cattaneo, Rocio Titiunik, Gonzalo Vazquez-Bare

arXiv 16 Dec 2019 · Statistics — Computation · publishedThe Stata Journal Promoting communications on statistics and Stata (2020) · 13 citations (OpenAlex)

arXiv:1912.07346 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We introduce the Stata (and R) package rdmulti, which includes three commands (rdmc, rdmcplot, rdms) for analyzing Regression Discontinuity (RD) designs with multiple cutoffs or multiple scores. The command rdmc applies to non-cumulative and cumulative multi-cutoff RD settings. It calculates pooled and cutoff-specific RD treatment effects, and provides robust bias-corrected inference procedures. Post estimation and inference is allowed. The command rdmcplot offers RD plots for multi-cutoff settings. Finally, the command rdms concerns multi-score settings, covering in particular cumulative cutoffs and two running variables contexts. It also calculates pooled and cutoff-specific RD treatment effects, provides robust bias-corrected inference procedures, and allows for post-estimation estimation and inference. These commands employ the Stata (and R) package rdrobust for plotting, estimation, and inference. Companion R functions with the same syntax and capabilities are provided.

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27
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Cattaneo, M. D., L. Keele, R. Titiunik, and G. Vazquez-Bare (2016) Interpreting Regression Discontinuity Designs with Multiple Cutoffs self0.87452100%
2Cattaneo, M. D., N. Idrobo, and R. Titiunik (2020) A Practical Introduction to Regression Discontinuity Designs: Extensions self0.81142100%
3Cattaneo, M. D., L. Keele, R. Titiunik, and G. Vazquez-Bare (2021) Extrapolating Treatment Effects in Multi-Cutoff Regression Discontinuity Designs self0.81142100%
4Calonico, S., M. D. Cattaneo, M. H. Farrell, and R. Titiunik (2017) rdrobust: Software for Regression Discontinuity Designs self0.73732100%
5Calonico, S., M. D. Cattaneo, and R. Titiunik (2014) Robust Data-Driven Inference in the Regression-Discontinuity Design self0.73732100%
6Calonico, S., M. D. Cattaneo, and R. Titiunik (2015) rdrobust: An R Package for Robust Nonparametric Inference in Regression-Discontinuity Designs self0.73732100%
7Keele, L. J., and R. Titiunik (2015) Geographic Boundaries as Regression Discontinuities0.73732100%
8Cattaneo, M. D., N. Idrobo, and R. Titiunik (2019) A Practical Introduction to Regression Discontinuity Designs: Foundations self0.64422100%
9Brollo, F., T. Nannicini, R. Perotti, and G. Tabellini (2013) The Political Resource Curse0.40511100%
10Calonico, S., M. D. Cattaneo, M. H. Farrell, and R. Titiunik (2019) Regression Discontinuity Designs Using Covariates self0.40511100%

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1Local-Polynomial Estimation for Multivariate Regression Discontinuity Designs0.64422
2Boundary estimation in the regression-discontinuity design: Evidence for a merit- and need-based financial aid program0.64422
3Breaking Ties: Regression Discontinuity DesignMeets Market Design0.40511
4A Practical Introduction to Regression Discontinuity Designs: Extensions0.40511
5rdhte: Conditional Average Treatment Effects in RD Designs0.40511