Finite Sample Performance of Robust Bayesian Regression

33 Pages Posted: 13 Nov 1997

See all articles by Michael Smith

Michael Smith

UNSW Australia Business School, School of Economics

Simon J. Sheather

Texas A&M University

Robert Kohn

University of New South Wales - School of Economics and School of Banking and Finance

Date Written: April 24, 1996

Abstract

The finite sample performance of a number of linear regression estimators is investigated in a variety of parametric settings involving outliers. A Bayesian approach is shown to have good overall comparative performance. It is then shown how the same Bayesian methodology can be easily extended to robust nonparametric regression. The Bayesian analysis is carried out using the Gibbs sampler.

JEL Classification: C11

Suggested Citation

Smith, Michael and Sheather, Simon J. and Kohn, Robert, Finite Sample Performance of Robust Bayesian Regression (April 24, 1996). Available at SSRN: https://ssrn.com/abstract=41540 or http://dx.doi.org/10.2139/ssrn.41540

Michael Smith

UNSW Australia Business School, School of Economics

High Street
Sydney, NSW 2052
Australia
+61 2 9385 3365 (Ext. 3365) (Phone)
+61 2 9313 6337 (Fax)

Simon J. Sheather (Contact Author)

Texas A&M University ( email )

Langford Building A
798 Ross St.
College Station, TX 77843-3137
United States

Robert Kohn

University of New South Wales - School of Economics and School of Banking and Finance ( email )

Australian School of Business
Sydney NSW 2052, ACT 2600
Australia
+61 2 9385 2150 (Phone)

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