Modelling errors are often the limiting factor in identification problems. Therefore, it is important to qualify their impact on the estimated plant model parameters (θ) over cap (Z), where Z stands for the data. This paper qualifies the influence of model errors and disturbing noise level on: (i) the asymptotic value theta(*) (estimate for an infinite amount of data) of (θ) over cap (Z), and (ii) the asymptotic (amount of data going to infinity) covariance matrix Cov((θ) over cap (Z)) of (θ) over cap (Z). The theory is elaborated on a time- and frequency-domain estimator.