Implements binscatter methods, including partition selection, point estimation, pointwise and uniform inference methods, and graphical procedures.
Binscatter provides a flexible, yet parsimonious way of visualizing and summarizing large data sets and has been a popular methodology in applied microeconomics and other social sciences. The binsreg package provides tools for statistical analysis using the binscatter methods developed in Cattaneo, Crump, Farrell and Feng (2024a), Cattaneo, Crump, Farrell and Feng (2024b) and Cattaneo, Crump, Farrell and Feng (2024c). binsreg implements binscatter least squares regression with robust inference and plots, including curve estimation, pointwise confidence intervals and uniform confidence band. binsqreg implements binscatter quantile regression with robust inference and plots, including curve estimation, pointwise confidence intervals and uniform conf idence band. binsglm implements binscatter generalized linear regression with robust inference and plots, including curve estimation, pointwise confidence intervals and uniform confidence band. binstest implements binscatter-based hypothesis testing procedures for parametric specifications of and shape restrictions on the unknown function of interest. binspwc implements hypothesis testing procedures for pairwise group comparison of binscatter estimators. binsregselect implements data-driven number of bins selectors for binscatter implementation using either quantile-spaced or evenly-spaced binning/partitioning. All the commands allow for covariate adjustment, smoothness restrictions, and clustering, among other features.
Matias D. Cattaneo (cattaneo@princeton.edu)
Richard K. Crump (richard.crump@ny.frb.org)
Max H. Farrell (maxhfarrell@ucsb.edu)
Yingjie Feng (fengyingjiepku@gmail.com)
Ricardo Masini (rmasini@princeton.edu)
https://nppackages.github.io/binsreg/
This package was first released in Winter 2019, and had one major upgrade in Summer 2021.
Summer 2021 new features include: (i) generalized linear models (logit, Probit, etc.) binscatter; (ii) quantile regression binscatter; (iii) new generic specification and shape restriction hypothesis testing function (now including Lp metrics); (iv) multi-group comparison of binscatter estimators; (v) generic point evaluation of covariate-adjusted binscatter; (vi) speed improvements and optimization. A complete list of upgrades can be found here.
To install/update use pip
pip install binsreg
from binsreg import binsregselect, binsreg, binsqreg, binsglm, binstest, binspwc
For overviews and introductions, see NP Packages website.
Cattaneo, Crump, Farrell and Feng (2024a): On Binscatter.
American Economic Review 114(5): 1488-1514.
Cattaneo, Crump, Farrell and Feng (2024b): Nonlinear Binscatter Methods.
Working paper.
FAQs
Implements binscatter methods, including partition selection, point estimation, pointwise and uniform inference methods, and graphical procedures.
We found that binsreg demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 3 open source maintainers collaborating on the project.
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