An Alternative Method of Estimation of SUR Model
American Journal of Theoretical and Applied Statistics
Volume 4, Issue 3, May 2015, Pages: 150-155
Received: Apr. 4, 2015; Accepted: Apr. 14, 2015; Published: Apr. 24, 2015
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Authors
Shohel Rana, Department of Mathematics and Natural Sciences, BRAC University, Dhaka, Bangladesh
Mohammad Mastak Al Amin, Department of Mathematics and Natural Sciences, BRAC University, Dhaka, Bangladesh
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Abstract
This paper proposed a transformed method of SUR model which provided unbiased estimation in case of two and three equations of high and low co-linearity for both small and large datasets. The generalized least squares (GLS) method for estimation of seemingly unrelated regression (SUR) model proposed by Zellner (1962), Srivastava and Giles (1987),provided higher MSE. Although the Ridge estimators proposed by Alkhamisi and Shukur (2008) provided smaller MSE in comparison with others, it was not unbiased in case of severe multicollinearity.This study showed that our proposed method typically provided unbiasedestimator with lower MSE and TMSE than traditional methods.
Keywords
SUR Model, GLS, MSE, TMSE
To cite this article
Shohel Rana, Mohammad Mastak Al Amin, An Alternative Method of Estimation of SUR Model, American Journal of Theoretical and Applied Statistics. Vol. 4, No. 3, 2015, pp. 150-155. doi: 10.11648/j.ajtas.20150403.20
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