Power calculations for regression-discontinuity designs

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

Research output: Contribution to journalArticlepeer-review

42 Scopus citations


In this article, we introduce two commands, rdpow and rdsampsi, that conduct power calculations and survey sample selection when using local polynomial estimation and inference methods in regression-discontinuity designs. rdpow conducts power calculations using modern robust bias-corrected local polynomial inference procedures and allows for new hypothetical sample sizes and bandwidth selections, among other features. rdsampsi uses power calculations to compute the minimum sample size required to achieve a desired level of power, given estimated or user-supplied bandwidths, biases, and variances. Together, these commands are useful when devising new experiments or surveys in regression-discontinuity designs, which will later be analyzed using modern local polynomial techniques for estimation, inference, and falsification. Because our commands use the communitycontributed (and R) package rdrobust for the underlying bandwidths, biases, and variances estimation, all the options currently available in rdrobust can also be used for power calculations and sample-size selection, including preintervention covariate adjustment, clustered sampling, and many bandwidth selectors. Finally, we also provide companion R functions with the same syntax and capabilities.

Original languageEnglish (US)
Article numberst0554
Pages (from-to)210-245
Number of pages36
JournalStata Journal
Issue number1
StatePublished - Mar 2019
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Mathematics (miscellaneous)


  • Local polynomial methods
  • Power calculations
  • Rdpow
  • Rdsampsi
  • Regression-discontinuity designs
  • St0554


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