Fixed effects in unconditional quantile regression

• Autores: Nicolai T. Borgen
• Localización: The Stata journal, ISSN 1536-867X, Vol. 16, Nº. 2, 2016, págs. 403-415
• Idioma: inglés
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• Resumen

  • Unconditional quantile regression has quickly become popular after being introduced by Firpo, Fortin, and Lemieux (2009, Econometrica 77: 953–973) and is easily implemented using the user-written command rifreg by the same authors. However, including high-dimensional fixed effects in rifreg is quite burdensome and sometimes even impossible. In this article, I show that when the number of fixed effects is large, the computational speed is massively increased by using xtreg rather than regress to fit the unconditional quantile regression models. I also introduce the xtrifreg command, which should be considered a supplement to rifreg. The xtrifreg command has many of the same features as rifreg but can be used to include a large number of fixed effects, to estimate cluster–robust standard errors, and to estimate cluster–bootstrapped standard errors.