We introduce the \texttt{Stata} package \textsf{Binsreg}, which implements the binscatter methods developed in \citet*{Cattaneo-Crump-Farrell-Feng_2021_Binscatter}. The package includes seven commands: \texttt{binsreg}, \texttt{binslogit}, \texttt{binsprobit}, \texttt{binsqreg}, \texttt{binstest}, \texttt{binspwc}, and \texttt{binsregselect}. The first four commands implement point estimation and uncertainly quantification (confidence intervals and confidence bands) for canonical and extended least squares binscatter regression (\texttt{binsreg}) as well as generalized nonlinear binscatter regression (\texttt{binslogit} for Logit regression, \texttt{binsprobit} for Probit regression, \texttt{binsqreg} for quantile regression). These commands also offer binned scatter plots, allowing for one- and multi-sample settings. The next two commands focus on pointwise and uniform inference: \texttt{binstest} implements hypothesis testing procedures for parametric specification and for nonparametric shape restrictions of the unknown regression function, while \texttt{binspwc} implements multi-group pairwise statistical comparisons. These two commands cover both least squares as well as generalized nonlinear binscatter methods. All our methods allow for multi-sample analysis, which is useful when studying treatment effect heterogeneity in randomized and observational studies. Finally, the command \texttt{binsregselect} implements data-driven number of bins selectors for binscatter methods using either quantile-spaced or evenly-spaced binning/partitioning. All the commands allow for covariate adjustment, smoothness restrictions, weighting and clustering, among many other features. Companion \texttt{Python} and \texttt{R} packages with similar syntax and capabilities are also available.
翻译:我们引入了 & textt{ Stata} 套件 { textt{ binspret},\ textt{ trickr{ binsreg}, 执行在\ citet} Cattarneo- Crum- Farrell- Feng_ 2021_ Binscatter} 中开发的 binshall 方法。 这个套件包括七个命令 :\ textt{ binsret},\ textt{ binspret},\ texttt{ bindress} right{ binsest},\ textt{binsterrickright}, 和\ textttralt{ brickrickrice} 。 前四个命令执行点估算和不确定的量化方法( 信任间隔和信任带) 最小的回归(\ texttrestread), 以及非线性 bentbent binsteft bill 回归回归回归的回归(\ tracks) 。