A Gini estimator for regression with autocorrelated errors-Reference-Cited by-同舟云学术

A Gini estimator for regression with autocorrelated errors

Published:2022-03-24 Issue:1 Volume:27 Page:83-95
ISSN:1558-3708
Container-title:Studies in Nonlinear Dynamics & Econometrics
language:en
Short-container-title:

Author:

Ka Ndéné¹^ORCID,Mussard Stéphane²

Affiliation:

1. Gredt, Université Alioune Diop de Bambey , BP 30 , Bambey , Senegal

2. CHROME, UNIV. NIMES , Nimes , France

Abstract

Abstract The widely used Prais–Winsten technique for estimating parameters of linear regression model with serial correlation is sensitive to outliers. In this paper, an alternative method based on Gini mean difference (GMD) is proposed. A Monte Carlo simulation is used to show that the Gini estimator is more robust than the general least squares one when the data are contaminated by outliers.

Publisher

Walter de Gruyter GmbH

Subject

Economics and Econometrics,Social Sciences (miscellaneous),Analysis,General Medicine

Link

https://www.degruyter.com/document/doi/10.1515/snde-2020-0134/pdf

Reference21 articles.

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