Flexible and fast estimation of quantile treatment effects: The rqr and rqrplot commands

Nicolai T. Borgen, Andreas Haupt and Øyvind Wiborg
Additional contact information
Nicolai T. Borgen: University of Oslo
Andreas Haupt: Karlsruhe Institute of Technology
Øyvind Wiborg: University of Oslo

Northern European Stata Conference 2022 from Stata Users Group

Abstract: Using quantile regression models to estimate quantile treatment effects is becoming increasingly popular. This presentation introduces the rqr command, which can be used to estimate residualized quantile regression (RQR) coe

Date: 2022-10-12
References: Add references at CitEc
Citations:

Downloads: (external link)
http://repec.org/neur2022/Northern_Europe22_Pinzon.pdf presentation materials (application/pdf)

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:boc:neur22:06

Access Statistics for this paper

More papers in Northern European Stata Conference 2022 from Stata Users Group Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().