Robust Estimation of Multiple Regression Model with Non-normal Error: Symmetric Distribution

Wing-Keung Wong and Guorui Bian

No 09/05, Monash Economics Working Papers from Monash University, Department of Economics

Abstract: In this paper, we develop the modified maximum likelihood (MML) estimators for the multiple regression coefficients in linear model with the underlying distribution assumed to be symmetric, one of Student's t family. We obtain the closed form of the estimators and derive their asymptotic properties. In addition, we demonstrate that the MML estimators are more appropriate to estimate the parameters in the Capital Asset Pricing Model by comparing its performance with that of least squares estimators (LSE) on the monthly returns of US portfolios. Our empirical study reveals that the MML estimators are more efficient than the LSE in terms of relative efficiency of one-step-ahead forecast mean square error for small samples.

Keywords: Maximum likelihood estimators; Modified maximum likelihood estimators; Student's t family; Capital Asset Pricing Model; Robustness. (search for similar items in EconPapers)
JEL-codes: C1 C2 G1 (search for similar items in EconPapers)
Pages: 18 pages
Date: 2005-06-01
New Economics Papers: this item is included in nep-ecm
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