Mixed Estimation In Seemingly Unrelated Regression Equation Model Some Finite Sample Properties Results

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.

REFERENCES

[1] Theil,H ., and A.S.Goldberger,"On Pure And Mixed Statistical Estimation In Economics" , international economics review ,vol.2,pp.65-78 , (1961).

[2] Theil,H,"On The Use Of Incomplete Prior Information In Regression Analysis",Journal of the American Statistical Association, Vol. 58, 401-414, .(1963).

[3] Nagar,A.L,and N.C.Kakwani, "The Bias And Moment Matrix Of A Mixed Regression Estimator ", Econometrica , vol. 32,pp.174-182, (1964).

[4] Nagar,A.L,and N.C.Kakwani,"Note On The Bias Of A Mixed Simultaneous Equation", International Economic Review, vol.7,No.1,pp 65-71, (1966).

[5] Zellner , A, "An Efficient Method Of Estimating Seemingly Unrelated Regression Equations And Tests For Aggregation Bias" , Journal of the American Statistical Association , vol.57,pp. 348-368., .(1962).

[6] _______, Estimators For Seemingly Unrelated Regression Equations:,"some exact finite sample results", Journal of the American Statistical Association ,vol. 58, pp.977-992, (1963)