Small sample properties of the mixed regression estimator

In this paper, the small sample properties of the mixed regression estimator are examined when prior information may be biased and when the ration of the variance of the prior restriction errors to the variance of the sample errors is unknown. The mean square error of the mixed regression estimator is derived, and it is shown that the mixed regression estimator gets dominated by the ordinary least squares estimator in terms of the mean square error as the bias of prior information gets larger.