THE SAMPLING PERFORMANCE OF INEQUALITY RESTRICTED AND PRE-TEST ESTIMATORS IN A MIS-SPECIFIED LINEAR MODEL

The literature on the sampling properties of the inequality restricted and pre-test estimators typically assumes a properly specified model and focuses on the estimation of the regression coefficient vector. In this paper, we derive and evaluate the risk functions of these estimators for both the prediction vector and the disturbance variance in a model which is mis-specified through the exclusion of relevant regressors. The results suggest that unrestricted estimation is generally preferable to pre-testing or naively imposing restrictions.