Generalized Recentered Influence Function Regressions
This paper suggests a generalization of covariate shifts to study distributional impacts on inequality and distributional measures. It builds on the recentered influence function (RIF) regression method, originally designed for location shifts in covariates, and extends it to general policy interventions, such as location–scale or asymmetric interventions. Numerical simulations for the Gini, Theil, and Atkinson indexes demonstrate strong performance across a myriad of cases and distributional measures. An empirical application examining changes in Mincerian equations is presented to illustrate the method.
Authors
- Javier Alejo (ORCID: https://orcid.org/0000-0003-0681-7137)
- Julián Martínez-Iriarte (ORCID: https://orcid.org/0000-0003-2639-3909)
- Antonio F. Galvao (ORCID: https://orcid.org/0000-0003-4406-4041)
Institutions
- Consejo Nacional de Investigaciones Científicas y Técnicas (AR)
- Universidad de la República de Uruguay (UY)
- University of California, Santa Cruz (US)
- Universidad de Buenos Aires (AR)
- Michigan State University (US)
Publication Details
- Journal
- Econometrics
- Published
- 2025-04-17
- DOI
- https://doi.org/10.3390/econometrics13020019
- Citations
- 2
- Primary Topic
- Statistical Methods and Inference
- Type
- article
- Field-Weighted Citation Impact
- 5.26