Matias D. Cattaneo, Richard K. Crump, Max H. Farrell, Yingjie Feng
arXiv 25 Feb 2019 · Econometrics · publishedThe Stata Journal Promoting communications on statistics and Stata (2025) · 23 citations (OpenAlex)
arXiv:1902.09615 · PDF · DOI · OpenAlex · Extracted main text
We introduce the package Binsreg, which implements the binscatter methods developed by Cattaneo, Crump, Farrell, and Feng (2024b,a). The package includes seven commands: binsreg, binslogit, binsprobit, binsqreg, binstest, binspwc, and binsregselect. The first four commands implement binscatter plotting, point estimation, and uncertainty quantification (confidence intervals and confidence bands) for least squares linear binscatter regression (binsreg) and for nonlinear binscatter regression (binslogit for Logit regression, binsprobit for Probit regression, and binsqreg for quantile regression). The next two commands focus on pointwise and uniform inference: binstest implements hypothesis testing procedures for parametric specifications and for nonparametric shape restrictions of the unknown regression function, while binspwc implements multi-group pairwise statistical comparisons. Finally, the command binsregselect implements data-driven number of bins selectors. The commands offer binned scatter plots, and allow for covariate adjustment, weighting, clustering, and multi-sample analysis, which is useful when studying treatment effect heterogeneity in randomized and observational studies, among many other features.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | width30.25006ptheight2.62222ptdepth-2.25222pt (2024) On Binscatter | 1.000 | 5 | 4 | 100% |
| 2 | Cattaneo, M. D., R. K. Crump, M. H. Farrell, and Y. Feng (2024) bNonlinear Binscatter Methods self | 0.843 | 3 | 3 | 100% |
| 3 | Caceres, M (2024) Stata Module Mauricio https://github.com/mcaceresb/stata-gtools | 0.644 | 2 | 2 | 100% |
| 4 | Correia, S., and N. Constantine (2024) Stata Module reghdfe https://github.com/sergiocorreia/reghdfe | 0.644 | 2 | 2 | 100% |
| 5 | Calonico, S., M. D. Cattaneo, and M. H. Farrell (2018) On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference self | 0.405 | 1 | 1 | 100% |
| 6 | width30.25006ptheight2.62222ptdepth-2.25222pt (2022) Coverage Error Optimal Confidence Intervals for Local Polynomial Regression | 0.405 | 1 | 1 | 100% |
| 7 | Calonico, S., M. D. Cattaneo, and R. Titiunik (2014) Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs self | 0.405 | 1 | 1 | 100% |
| 8 | Cattaneo, M. D., R. K. Crump, M. H. Farrell, and E. Schaumburg (2020) Characteristic-Sorted Portfolios: Estimation and Inference self | 0.405 | 1 | 1 | 100% |
| 9 | Cattaneo, M. D., M. H. Farrell, and Y. Feng (2020) Large sample properties of partitioning-based series estimators self | 0.405 | 1 | 1 | 100% |
| 10 | Droste, M (2019) Stata Module Binscatter2 https://github.com/mdroste/stata-binscatter2/ | 0.405 | 1 | 1 | 100% |
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