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Gini Regressions and Heteroskedasticity

Arthur Charpentier (), Ndéné Ka (), Stéphane Mussard () and Oumar Hamady Ndiaye ()
Additional contact information
Arthur Charpentier: Centre de Recherche en Economie et Management (CREM), Université de Rennes, 35000 Rennes, France
Ndéné Ka: Département D’économie, Université Alioune Diop de Bambey, Bambey BP 30, Senegal
Oumar Hamady Ndiaye: Chrome , Université de Nîmes, 30000 Nîmes, France

Econometrics, 2019, vol. 7, issue 1, 1-16

Abstract: We propose an Aitken estimator for Gini regression. The suggested A -Gini estimator is proven to be a U -statistics. Monte Carlo simulations are provided to deal with heteroskedasticity and to make some comparisons between the generalized least squares and the Gini regression. A Gini-White test is proposed and shows that a better power is obtained compared with the usual White test when outlying observations contaminate the data.

Keywords: Gini; heteroskedasticity; jackknife; U -statistics (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2019
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