Fixed effects in unconditional quantile regression
Nicolai T. Borgen ()
Additional contact information
Nicolai T. Borgen: University of Oslo
Stata Journal, 2016, vol. 16, issue 2, 403-415
Abstract:
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.
Keywords: xtrifreg; unconditional quantile regression; fixed effects (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (71)
Downloads: (external link)
http://www.stata-journal.com/article.html?article=st0438 link to article purchase
http://www.stata-journal.com/software/sj16-2/st0438/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:tsj:stataj:y:16:y:2016:i:2:p:403-415
Ordering information: This journal article can be ordered from
http://www.stata-journal.com/subscription.html
Access Statistics for this article
Stata Journal is currently edited by Nicholas J. Cox and Stephen P. Jenkins
More articles in Stata Journal from StataCorp LLC
Bibliographic data for series maintained by Christopher F. Baum () and Lisa Gilmore ().