RDDENSITY

The rddensity package provides Stata and R implementations of manipulation tests employing local polynomial density estimation methods. This method is useful for falsification of Regression Discontinuity Designs, as well as for testing for self-selection or sorting in other contexts. This implementation provides hypothesis tests and bandwidth selectors for manipulation testing.

This work was supported in part by the National Science Foundation through grants SES-1357561, SES-1459931, SES-1459967, SES-1947662, SES-1947805, and SES-2019432.

Website

https://rdpackages.github.io/rddensity

Queries and Requests

Please email: [email protected]

Major Upgrades

This package was first released in Spring 2017, and had one major upgrade in Summer 2020.

• Summer 2020 new features include: (i) speed improvements; (ii) improved integration with lpdensity; (iii) mass points in running variable adjustments; (iv) bandwidth selection adjustments for too few mass points in and/or overshooting of the support of the running variable; (v) density discontinuity plots with histogram and/or confidence bands; and (vi) binomial testing near cutoff as complementary discontinuity testing following results in rdlocrand methods (see references there for details).

Python Implementation

To install/update in Python type:

pip install rddensity

• Help: PyPI, Documentation
• Replication: Python script

R Implementation

To install/update in R type:

install.packages('rddensity')

• Help: R Manual, CRAN repository.

• Replication: R-script, rdplot illustration, senate data.

Stata Implementation

To install/update in Stata type:

net install rddensity, from(https://raw.githubusercontent.com/rdpackages/rddensity/master/stata) replace

• Help: rddensity, rdbwdensity.

• Replication: do-file, do-file plot, data-senate.

References

For overviews and introductions, see rdpackages website.

Software and Implementation

• Cattaneo, Jansson and Ma (2018): Manipulation Testing based on Density Discontinuity.
  Stata Journal 18(1): 234-261.

• Cattaneo, Jansson and Ma (2022): lpdensity: Local Polynomial Density Estimation and Inference.
  Journal of Statistical Software 101(2): 1-25.

Technical and Methodological

• Cattaneo, Jansson and Ma (2020): Simple Local Polynomial Density Estimators.
  Journal of the American Statistical Association 115(531): 1449-1455.
  Supplemental appendix.

• Cattaneo, Jansson and Ma (2022): Local Regression Distribution Estimators.
  Journal of Econometrics, forthcoming.
  Supplemental appendix.