The binsreg package implements estimation, inference and graphical procedures using binscatter methods.

• binsreg: least squares binscatter regression with robust inference and plots.
• binsqreg: quantile binscatter regression with robust inference and plots.
• binsglm: generalized linear binscatter regression with robust inference and plots (R and Python).
• binslogit: logit binscatter estimation with robust inference and plots (Stata).
• binsprobit: probit binscatter estimation with robust inference and plots (Stata).
• binstest: binscatter-based tests for parametric specifications and shape restrictions.
• binspwc: binscatter-based pairwise group comparison tests.
• binsregselect: data-driven selection of the number of bins for binscatter estimation.

To install/update in Python type:

pip install binsreg

• Help: PyPI repository.

• Replication: py-script, plot illustration, data.

To install/update in R type:

install.packages('binsreg')

• Help: R Manual, CRAN repository.

• Replication: R-script, plot illustration, data.

To install/update in Stata type:

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

• Help: binsreg, binslogit, binsprobit, binsqreg, binstest, binspwc, binsregselect.

• Replication files: do-file, plot illustration, data, speed test.

• Cattaneo, Crump, Farrell and Feng (2025): Binscatter Regressions.
  Stata Journal 25(1): 3-50.

• Cattaneo, Crump, Farrell and Feng (2024): On Binscatter.
  American Economic Review 114(5): 1488-1514.
  Supplemental Appendix

• Cattaneo, Crump, Farrell and Feng (2026): Nonlinear Binscatter Methods.
  Review of Economics and Statistics, revise and resubmit.
  Supplemental Appendix

This work was supported in part by the National Science Foundation through grants SES-1947805, SES-2019432, and SES-2241575.