Quantile Regression in the Presence of Sample Selection

Martin Huber and Blaise Melly ()

No 1109, Economics Working Paper Series from University of St. Gallen, School of Economics and Political Science

Abstract: Most sample selection models assume that the errors are independent of the regressors. Under this assumption, all quantile and mean functions are parallel, which implies that quantile estimators cannot reveal any (per definition non-existing) heterogeneity. However, quantile estimators are useful for testing the independence assumption, because they are consistent under the null hypothesis. We propose tests for this crucial restriction that are based on the entire conditional quantile regression process after correcting for sample selection bias. Monte Carlo simulations demonstrate that they are powerful and two empirical illustrations indicate that violations of this assumption are likely to be ubiquitous in labor economics.

Keywords: Sample selection; quantile regression; independence; test (search for similar items in EconPapers)
JEL-codes: C12 C13 C14 C21 (search for similar items in EconPapers)
Pages: 33 pages
Date: 2011-03
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (29)

Downloads: (external link)
http://ux-tauri.unisg.ch/RePEc/usg/econwp/EWP-1109.pdf (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:usg:econwp:2011:09

Access Statistics for this paper

More papers in Economics Working Paper Series from University of St. Gallen, School of Economics and Political Science Contact information at EDIRC.
Bibliographic data for series maintained by ().