Abstract
Biased estimation methods are more desirable than two stage least squares estimation for simultaneous equations models suffering from the problem of multicollinearity. This problem is also handled by using some prior information. Taking account of this knowledge, we recommend two stage modified ridge estimator. The new estimator can also be evaluated as an alternative to the previously proposed two stage ridge estimator. The widespread performance criterion, mean square error, is taken into consideration to compare the two stage modified ridge, two stage ridge and two stage least squares estimators. A real life data analysis is investigated to prove the theoretical results in practice. In addition, the intervals of the biasing parameter which provide the superiority of the two stage modified ridge estimator are determined with the help of figures. The researchers who deal with simultaneous systems with multicollinearity can opt for the two stage modified ridge estimator.
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