NPROBUST

The nprobust package provides R and Stata implementations of bandwidth selection, point estimation and inference procedures for nonparametric kernel-based density and local polynomial methods.

This work was supported by the National Science Foundation through grant SES-1459931 and SES-1947805.

Website

https://nppackages.github.io/nprobust

Queries and Requests

Please email: [email protected]

R Implementation

To install/update in R type:

install.packages('nprobust')

• Help: R Manual, CRAN repository.

• Replication: R-script, nprobust_data.

Stata Implementation

To install/update in Stata type:

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

• Help: kdrobust, kdbwselect, lprobust, lpbwselect.

• Replication: do-file, nprobust_data.

References

Software and Implementation

• Calonico, Cattaneo and Farrell (2019): nprobust: Nonparametric Kernel-Based Estimation and Robust Bias-Corrected Inference.
  Journal of Statistical Software 91(8): 1-33.

Technical and Methodological

• Calonico, Cattaneo and Farrell (2018): On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference.
  Journal of the American Statistical Association 113(522): 767-779.
  Supplemental Appendix.

• Calonico, Cattaneo and Farrell (2022): Coverage Error Optimal Confidence Intervals for Local Polynomial Regression.
  Bernoulli 28(4): 2998-3022.
  Supplemental Appendix.