Affiliation:
1. University of Miami Miami, FL
2. University of Michigan Ann Arbor, MI
3. University of Chicago Chicago, IL
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 bandwidth 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 implementation improvements. We also discuss issues of backward compatibility and provide a companion R package with the same syntax and capabilities.
Subject
Mathematics (miscellaneous)
Reference22 articles.
1. Estimation of the Conditional Variance in Paired Experiments
2. Regression Discontinuity Designs with Clustered Data
3. CalonicoS., CattaneoM. D., and FarrellM. H. 2016a. Coverage error optimal confidence intervals for regression discontinuity designs. Working Paper, University of Michigan. http://www-personal.umich.edu/∼cattaneo/papers/Calonico-Cattaneo-Farrell_2016_wp.pdf.
4. CalonicoS., CattaneoM. D., FarrellM. H., and TitiunikR. 2016b. Regression discontinuity designs using covariates. Working Paper, University of Michigan. http://www-personal.umich.edu/∼cattaneo/papers/Calonico-Cattaneo-Farrell-Titiunik_2016_wp.pdf.
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