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Recentered influence functions (RIFs) in Stata: RIF regression and RIF decomposition

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  • Fernando Rios-Avila

    (Levy Economics Institute of Bard College)

Abstract

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 (un- conditional quantile regressions). The flexibility and simplicity of these tools have opened the possibility to extend the analysis to other distributional statistics us- ing 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).

Suggested Citation

  • Fernando Rios-Avila, 2020. "Recentered influence functions (RIFs) in Stata: RIF regression and RIF decomposition," Stata Journal, StataCorp LP, vol. 20(1), pages 51-94, March.
    • Handle: RePEc:tsj:stataj:v:20:y:2020:i:1:p:51-94
    DOI: 10.1177/1536867X20909690
    Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj20-1/st0588/
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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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