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Local Randomization Methods for RD Designs

Project description

rdlocrand: Local Randomization Methods for RD Designs

Description

The regression discontinuity (RD) design is a popular quasi-experimental design for causal inference and policy evaluation. Under the local randomization approach, RD designs can be interpreted as randomized experiments inside a window around the cutoff. The rdlocrand package provides tools to analyze RD designs under local randomization:

  • rdrandinf to perform hypothesis testing using randomization inference.
  • rdwinselect to select a window around the cutoff in which randomization is likely to hold.
  • rdsensitivity to assess the sensitivity of the results to different window lengths and null hypotheses.
  • rdrbounds to construct Rosenbaum bounds for sensitivity to unobserved confounders.

For more details, and related Stata and R packages useful for the analysis of RD designs, visit https://rdpackages.github.io/.

Author

Matias Cattaneo, Princeton University. Email: cattaneo@princeton.edu

Rocio Titiunik, Princeton University. Email: titiunik@princeton.edu

Ricardo Masini, UC Davis. Email: rmasini@ucdavis.edu

Gonzalo Vazquez-Bare, UC Santa Barbara. Email: gvazquez@econ.ucsb.edu

Installation

To install/update use pip

pip install rdlocrand

Usage

from rdlocrand import rdrandinf, rdwinselect, rdsensitivity, rdrbounds

References

For overviews and introductions, see rdpackages website.



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