Mixed Estimation In Seemingly Unrelated Regression Equation Model Some Finite Sample Properties Results
Ghazal. A. Ghazal, Salwa.A.Hegazy
Keywords: mixed seemingly unrelated regression model, moment matrix, Nagar's expansion, prior information
Abstract: in (1964) Nagar and Kakwani analysis the results of the first and second moment that proposed by Theil and Goldberger (1961) ,derive the bias estimators and second moment matrix of mixed model estimators consider with the order of magnitude criteria ,derived biased estimators to order that refer to big (O) in probability where begin the number of observations. In this paper we derive mixed seemingly unrelated regression equations (SURE) by combining the prior information and sample information in a single model, derive the bias estimator to order and the moment matrix to order by using the methodology of Nagar's expansion for the moment of estimator. the bias has been derived conceder the normality distribution assumption of the random disturbances.
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