EconPapers    
Economics at your fingertips  
 

Gini-PLS Regressions

Stéphane Mussard () and Fattouma Souissi-Benrejab
Additional contact information
Fattouma Souissi-Benrejab: LAMETA, Universite Montpellier I

Authors registered in the RePEc Author Service: Fattouma SOUISSI BENREJAB

Cahiers de recherche from Departement d'Economique de l'École de gestion à l'Université de Sherbrooke

Abstract: Data contamination and excessive correlations between regressors (multicollinear- ity) constitute a standard and major problem in econometrics. Two techniques en- able solving these problems, in separate ways: the Gini regression for the former, and the PLS (partial least squares) regression for the latter. Gini-PLS regressions are proposed in order to treat extreme values and multicollinearity simultaneously.

Keywords: Gini covariance; Gini Regression; Gini-PLS Regressions; PLS Regression. (search for similar items in EconPapers)
JEL-codes: C3 C8 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2015-02, Revised 2017-01
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://gredi.recherche.usherbrooke.ca/wpapers/GREDI-1702.pdf (application/pdf)

Related works:
Journal Article: Gini-PLS Regressions (2019) Downloads
Working Paper: Gini-PLS Regressions (2015) Downloads
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:shr:wpaper:17-02

Access Statistics for this paper

More papers in Cahiers de recherche from Departement d'Economique de l'École de gestion à l'Université de Sherbrooke Contact information at EDIRC.
Bibliographic data for series maintained by Jean-François Rouillard ().

 
Page updated 2022-10-01
Handle: RePEc:shr:wpaper:17-02