Computationally efficient identification of dynamic errors-in-variables model is considered in this paper. The instrumental variable (IV) method is computationally efficient but it suffers from poor small-sample properties of the estimated parameters. The method presented in this work uses the prefiltered data. The input-output data is passed through a pair of user defined prefilters and the output data from the prefilters is subjected to a least-squares like algorithm. Compared to the IV approach, the proposed method shows a significant improvement in the small-sample properties of the MA parameter estimates, without any increase in the computational load.