2015
DOI: 10.11648/j.ajtas.20150403.20
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An Alternative Method of Estimation of SUR Model

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 … Show more

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Cited by 2 publications
(1 citation statement)
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“…Consequently, the use of only ordinary least squares regression could result in biased findings and erratic results as ordinary least squares regression ignores time-invariant unobserved individual effects and endogeneity (Flannery & Hankins 2013;Maddala & Lahiri 2009). Generalised least squares regression estimates unknown parameters in a linear regression model that can be applied when the variances of the observations are unequal or when there is a certain level of correlation between variables (Rana & Al Amin 2015). The introduction of a lagged effect in the dependent variable significantly reduced the endogeneity of the dataset.…”
Section: Data and Analysis Methodsmentioning
confidence: 99%
“…Consequently, the use of only ordinary least squares regression could result in biased findings and erratic results as ordinary least squares regression ignores time-invariant unobserved individual effects and endogeneity (Flannery & Hankins 2013;Maddala & Lahiri 2009). Generalised least squares regression estimates unknown parameters in a linear regression model that can be applied when the variances of the observations are unequal or when there is a certain level of correlation between variables (Rana & Al Amin 2015). The introduction of a lagged effect in the dependent variable significantly reduced the endogeneity of the dataset.…”
Section: Data and Analysis Methodsmentioning
confidence: 99%