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rdrobust: Software for regression-discontinuity designs

Author

Listed:
  • Sebastian Calonico

    () (University of Miami)

  • Matias D. Cattaneo

    () (University of Michigan)

  • Max H. Farrell

    () (University of Chicago)

  • Roc ́ıo Titiunik

    () (University of Michigan)

Abstract

We describe a major upgrade to the Stata (and R) rdrobust package, which provides a wide array of estimation, inference, and falsification methods for the analysis and interpretation of regression-discontinuity designs. The main new features of this upgraded version are as follows: i) covariate-adjusted band- width selection, point estimation, and robust bias-corrected inference, ii) cluster– robust bandwidth selection, point estimation, and robust bias-corrected inference, iii) weighted global polynomial fits and pointwise confidence bands in regression- discontinuity plots, and iv) several new bandwidth selection methods, including different bandwidths for control and treatment groups, coverage error-rate optimal bandwidths, and optimal bandwidths for fuzzy designs. In addition, the upgraded package has superior performance because of several numerical and implementa- tion improvements. We also discuss issues of backward compatibility and provide a companion R package with the same syntax and capabilities.

Suggested Citation

  • Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Roc ́ıo Titiunik, 2017. "rdrobust: Software for regression-discontinuity designs," Stata Journal, StataCorp LP, vol. 17(2), pages 372-404, June.
  • Handle: RePEc:tsj:stataj:v:17:y:2017:i:2:p:372-404
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