A Highly Efficient Regression Estimator for Skewed And/Or Heavy-Tailed Distributed Errors

11 Pages Posted: 24 May 2017

See all articles by Lorenzo Ricci

Lorenzo Ricci

European Stability Mechanism; Université Libre de Bruxelles (ULB)

Vincenzo Verardi

FUNDP - University of Namur. CRED

Catherine Vermandele

Université Libre de Bruxelles (ULB)

Date Written: November 2016

Abstract

This paper proposes a simple maximum likelihood regression estimator that outperforms Least Squares in terms of efficiency and mean square error for a large number of skewed and/or heavy tailed error distributions.

Keywords: Skewed and heavy tailed regression; Tukey’s g and h distribution; Maximum approximated likelihood estimator

JEL Classification: C13, C16, G17

Suggested Citation

Ricci, Lorenzo and Verardi, Vincenzo and Vermandele, Catherine, A Highly Efficient Regression Estimator for Skewed And/Or Heavy-Tailed Distributed Errors (November 2016). European Stability Mechanism Working Paper No. 19. Available at SSRN: https://ssrn.com/abstract=2973098 or http://dx.doi.org/10.2139/ssrn.2973098

Lorenzo Ricci (Contact Author)

European Stability Mechanism ( email )

6a Circuit de la Foire Internationale
L-1347
Luxembourg

Université Libre de Bruxelles (ULB) ( email )

Ave. Franklin D Roosevelt, 50 - C.P. 114
Brussels, B-1050
Belgium

Vincenzo Verardi

FUNDP - University of Namur. CRED ( email )

8 Rempart de la Vierge
Namur, 5000
Belgium

Catherine Vermandele

Université Libre de Bruxelles (ULB) ( email )

CP 132 Av FD Roosevelt 50
Brussels, Brussels 1050
Belgium

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