Article Dans Une Revue Studies in Nonlinear Dynamics & Econometrics Année : 2023

A Gini estimator for regression with autocorrelated errors

Résumé

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.

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Dates et versions

hal-04849798 , version 1 (19-12-2024)

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Citer

Ndéné Ka, Stéphane Mussard. A Gini estimator for regression with autocorrelated errors. Studies in Nonlinear Dynamics & Econometrics, 2023, 27 (1), pp.83-95. ⟨10.1515/snde-2020-0134⟩. ⟨hal-04849798⟩

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