In this paper we investigate the asymptotic properties of various estimators of autocorrelation parameter of an ARMA(1,1) model when uncertain non–sample prior information on the moving average component is available. In particular we study the preliminary test and the shrinkage estimators of the autocorrelation parameter and we compare their efficiency with respect to the maximum likelihood estimator designated as the unrestricted estimator. It is shown that near the prior information on MA–parameter, both preliminary test and shrinkage estimators are superior to the MLE while they lose their superiority as the MA–parameter moves away from the prior information although preliminary test estimator gains its efficiency to some extent but the shrinkage estimator attains its lower bound of its efficiency.