Nonparametric and Semiparametric Methods

Software packages for nonparametric and semiparametric smoothing methods. Replication files and illustration codes employing these packages are also available.

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

Software available in R and Stata

• nprobust: estimation and inference using kernel density and local polynomial regression methods.
• lpdensity: estimation and inference using local polynomial distribution/density regression methods.
• binsreg: partition selection, point estimation, pointwise and uniform inference, and graphical procedures using binscatter methods.

Software available in R

• lspartition: estimation and inference using partitioning-based least squares methods, including B-splines, wavelet and piecewise polynomial regression estimators.

Replication

Replication files and illustration code are available in the replication page.

Contributors

• Sebastian Calonico, Columbia University.
• Matias D. Cattaneo, Princeton University.
• Richard K. Crump, Federal Reserve Bank of New York.
• Max H. Farrell, University of Chicago.
• Yingjie Feng, Princeton University
• Michael Jansson, UC Berkeley and CREATES.
• Xinwei Ma, UC San Diego.