Economics at your fingertips  

Robust covariance estimation for quantile regression

João Santos Silva ()

United Kingdom Stata Users' Group Meetings 2015 from Stata Users Group

Abstract: Quantile regression is increasingly used by practitioners, but there are still some misconceptions about how difficult it is to obtain valid standard errors in this context. In this presentation I discuss the estimation of the covariance matrix of the quantile regression estimator, focusing special attention on the case where the regression errors may be heteroskedastic and/or “clustered”. Specification tests to detect heteroskedasticity and intra-cluster correlation are discussed, and small simulation studies illustrate the finite sample performance of the tests and of the covariance matrix estimators. The presentation concludes with a brief description of qreg2, which is a wrapper for qreg that implements all the methods discussed in the presentation.

New Economics Papers: this item is included in nep-ecm
Date: 2015-09-16
References: Add references at CitEc
Citations: Track citations by RSS feed

Downloads: (external link) presentation slides (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:

Access Statistics for this paper

More papers in United Kingdom Stata Users' Group Meetings 2015 from Stata Users Group Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().

Page updated 2019-08-20
Handle: RePEc:boc:usug15:10