TY - JOUR
T1 - Power calculations for regression-discontinuity designs
AU - Cattaneo, Matias D.
AU - Titiunik, Rocío
AU - Vazquez-Bare, Gonzalo
N1 - Funding Information:
This article and commands were motivated by impact evaluation work conducted at the Philippine Institute for Development Studies, Manila, Philippines, in the summers of 2014 and 2016, which were sponsored by the Asian Development Bank. We thank these institutions for their hospitality and support. We also thank an anonymous reviewer, Sebastian Calonico, David Drukker, Xinwei Ma, David Mckenzie, Aniceto Orbeta, and participants at short courses and workshops at the Abdul Latif Jameel Poverty Action Lab, the Asian Development Bank, the Inter-American Development Bank, and the Georgetown Center for Econometric Practice for useful questions, comments, and suggestions that improved this project. The authors gratefully acknowledge financial support from the National Science Foundation through grant SES-1357561.
Publisher Copyright:
© 2019 StataCorp LLC.
PY - 2019/3
Y1 - 2019/3
N2 - 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.
AB - 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.
KW - Local polynomial methods
KW - Power calculations
KW - Rdpow
KW - Rdsampsi
KW - Regression-discontinuity designs
KW - St0554
UR - http://www.scopus.com/inward/record.url?scp=85067822707&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067822707&partnerID=8YFLogxK
U2 - 10.1177/1536867X19830919
DO - 10.1177/1536867X19830919
M3 - Article
AN - SCOPUS:85067822707
SN - 1536-867X
VL - 19
SP - 210
EP - 245
JO - Stata Journal
JF - Stata Journal
IS - 1
M1 - st0554
ER -