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No 69:
On the Least Absolute Deviations Method for Ridge Estimation of SURE Models

Zangin Zeebari and Ghazi Shukur ()

Abstract: This paper examines the application of the Least Absolute Deviations (LAD) method for ridge-type parameter estimation of Seemingly Unrelated Regression Equations (SURE) models. The methodology is aimed to deal with the SURE models with non-Gaussian error terms and highly collinear predictors in each equation. Some biasing parameters used in the literature are taken and the efficiency of both Least Squares (LS) ridge estimation and the LAD ridge estimation of the SURE models, through the Mean Squared Error (MSE) of parameter estimators, is evaluated.

Keywords: SURE Models; LAD Estimation; Ridge Regression; Efficiency; Robustness; (follow links to similar papers)

JEL-Codes: C15; C30; C31; (follow links to similar papers)

20 pages, October 24, 2012

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