Estimation of quantile regressions with fixed effects

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dc.contributor.authorFernando Rios-Avila
dc.contributor.authorAndrey Ramos
dc.contributor.authorGustavo Canavire-Bacarreza
dc.contributor.authorLeonardo Siles
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T20:06:31Z
dc.date.available2026-03-22T20:06:31Z
dc.date.issued2026
dc.description.abstractIn this article, we introduce two new commands, qregfe and qregplot , that are designed for fitting and visualizing quantile regression models with fixed effects. qregfe provides a unified syntax for implementing three panel-data estimators that are commonly used in empirical research: 1) the correlated random-effects specification of Abrevaya and Dahl (2008, Journal of Business and Economic Statistics 26: 379–397); 2) the two-step location-shift estimator of Canay (2011, Econometrics Journal 14: 368–386); and 3) the method of moments quantile regression approach of Machado and Santos Silva (2019, Journal of Econometrics 213: 145–173). The companion command qregplot produces coefficient–quantile plots, allowing researchers to visualize how the coefficients of each covariate change across the outcome conditional distribution.
dc.identifier.doi10.1177/1536867x261425793
dc.identifier.urihttps://doi.org/10.1177/1536867x261425793
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/80033
dc.language.isoen
dc.publisherSAGE Publishing
dc.relation.ispartofThe Stata Journal Promoting communications on statistics and Stata
dc.sourceUniversidad Privada Boliviana
dc.subjectEstimator
dc.subjectQuantile regression
dc.subjectCovariate
dc.subjectQuantile
dc.subjectEconometrics
dc.subjectMathematics
dc.subjectEstimation
dc.subjectStatistics
dc.subjectSyntax
dc.subjectRegression analysis
dc.titleEstimation of quantile regressions with fixed effects
dc.typearticle

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