Recentered influence functions in Stata: Methods for analyzing the determinants of poverty and inequality

Recentered influence functions (RIFs) are statistical tools popularized by Firpo, Fortin, and Lemieux (2009) for analyzing unconditional partial effects on quantiles in a regression analysis framework (unconditional quantile regressions). The flexibility and simplicity of these tools has opened the possibility of extending the analysis to other distributional statistics using linear regressions or decomposition approaches. In this paper, I introduce three Stata 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 to implement Oaxaca-Blinder type decomposition analysis (RIF decompositions).