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Recentered Influence Functions (RIF) in Stata: RIF-Regression and RIF-Decomposition

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  • Fernando Rios-Avila

    (Levy Economics Institute)

Abstract

Recentered Influence Functions (RIF) are statistical tools that have been popularized by Firpo, Fortin, and Lemieux (2009) for analyzing unconditional partial effects (UPE) on quantiles in a regression analysis framework (Unconditional Quantile Regressions). The flexibility and simplicity of this tool, however, has opened the possibility to extend 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 Recentered Influence Functions 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 which is used for the implementation of Oaxaca-Blinder type decomposition analysis.

Suggested Citation

  • Fernando Rios-Avila, 2019. "Recentered Influence Functions (RIF) in Stata: RIF-Regression and RIF-Decomposition," 2019 Stata Conference 22, Stata Users Group.
    • Handle: RePEc:boc:scon19:22
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    References listed on IDEAS

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    1. Heckley, Gawain & Gerdtham, Ulf-G. & Kjellsson, Gustav, 2016. "A general method for decomposing the causes of socioeconomic inequality in health," Journal of Health Economics, Elsevier, vol. 48(C), pages 89-106.
    2. Fernando Rios-Avila, 2019. "Recentered Influence Functions in Stata: Methods for Analyzing the Determinants of Poverty and Inequality," Economics Working Paper Archive wp_927, Levy Economics Institute.
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