We derive necessary and sufficient conditions under which the parameters of the model are identical to those of the true system which is supposed to be linear and of finite dimension. These conditions are that the cross-correlations between the output error and the input as well as the model output should be asymptotically null in a finite horizon. This horizon may be used as a minimum necessary test horizon in model validation.