Recentered influence functions (RIFs) are statistical tools popularized by Firpo, Fortin, and Lemieux (2009, Econometrica 77: 953–973) for analyzing unconditional partial effects on quantiles in a regression analysis framework (unconditional quantile regressions). The flexibility and simplicity of these tools have opened the possibility to extend the analysis to other distributional statistics using linear regressions or decomposition approaches. In this article, I introduce one function and two commands to facilitate the use of RIFs in the analysis of outcome distributions: rifvar() is an egen extension used to create RIFs for a large set of distributional statistics, rifhdreg facilitates the estimation of RIF regressions enabling the use of high-dimensional fixed effects, and oaxaca_rif implements Oaxaca–Blinder decomposition analysis (RIF decompositions).

最近的影响函数（RIF）是Firpo，Fortin和Lemieux（2009，Econometrica 77：953–973）普及的统计工具，用于在回归分析框架中分析对分位数的无条件局部影响（无条件分位数回归）。这些工具的灵活性和简单性为使用线性回归或分解方法将分析扩展到其他分布统计数据提供了可能性。在本文中，我介绍了一个函数和两个命令来促进在结果分布分析中使用RIF：rifvar（）是一个egen扩展，用于为大量的分布统计（rifhdreg）创建RIF便于估计RIF回归，从而可以使用高维固定效应，而oaxaca_rif实现了Oaxaca-Blinder分解分析（RIF分解）。