A Gini estimator for regression with autocorrelated errors

Ka Ndéné () and Stéphane Mussard
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Ka Ndéné: Gredt, Université Alioune Diop de Bambey, BP 30, Bambey, Senegal

Studies in Nonlinear Dynamics & Econometrics, 2023, vol. 27, issue 1, 83-95

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.

Keywords: autocorrelation; Gini; U-statistics (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1515/snde-2020-0134

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