Pre-Test Estimation in a Regression Model with a Misspecified Covariance Matrix

We consider the effects of incorrectly assuming a scalar error covariance matrix in a linear regression model in the context of a pre-test for linear restrictions on the coefficients. Because of this misspecification the (true) size and power of the pre-test may differ from their assumed values, distorting the pre-test estimator risk function towards that of one or other of its component estimators. The restricted and pre-test estimators may dominate the unrestricted estimator over a larger, or smaller, part of the parameter space, compared to the case with a correctly specified model.


Issue Date:
Nov 11 1991
Publication Type:
Working or Discussion Paper
Language:
English
Total Pages:
27
Series Statement:
9115




 Record created 2017-09-13, last modified 2017-09-13

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