In this paper we consider a strictly stationary time series generated by a nonlinear autoregression. We are concerned with the estimation of the parameter θ0which specifies the autoregression Two estimators are considered, namely. θnobtained by minimising the sum of squarcs of the sample prediction emets of a one step ahead predictor and θnobtained by minimising the sum of squares of the sample prediction errors of a multi-step ahead predictor. It is shown that θnis a better estimator of θ0than θn.