Gini regressions and heteroskedasticity

Arthur Charpentier, Ndéné Ka, Stéphane Mussard and Oumar Hamady Ndiaye

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.

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Year of publication:	2019
Authors:	Charpentier, Arthur ; Ka, Ndéné ; Mussard, Stéphane ; Ndiaye, Oumar Hamady
Published in:	Econometrics : open access journal. - Basel : MDPI, ISSN 2225-1146, ZDB-ID 2717594-7. - Vol. 7.2019, 1/4, p. 1-16
Subject:	Gini \| heteroskedasticity \| jackknife \| U-statistics \| Heteroskedastizität \| Heteroscedasticity \| Schätztheorie \| Estimation theory \| Gini-Koeffizient \| Gini coefficient \| Regressionsanalyse \| Regression analysis

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Type of publication:	Article
Type of publication (narrower categories):	Aufsatz in Zeitschrift ; Article in journal
Language:	English
Other identifiers:	10.3390/econometrics7010004 [DOI] hdl:10419/247504 [Handle]
Classification:	C14 - Semiparametric and Nonparametric Methods ; C3 - Econometric Methods: Multiple/Simultaneous Equation Models
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012025711