The behavior of the probability limits of differentk-class estimators under specification error is examined. Despite the fact that the probability limits are different when errors are not zero, it is shown that there exists no case in which either of the two leading estimators is uniformly more robust than the other if the criterion is any positive semi-definite quadratic form in the inconsistencies.