This paper estimates a simple univariate model of expectation or opinion formation in continuous time adapting a 'canonical' stochastic model of collective opinion dynamics (Weidlich and Haag, 1983; Lux, 1995, 2007). This framework is applied to a selected data set on survey-based expectations from the rich EU business and consumer survey database for twelve European countries. The model parameters are estimated through maximum likelihood and numerical solution of the transient probability density functions for the resulting stochastic process. The model's performance is assessed with respect to its out-of-sample forecasting capacity relative to univariate time series models of the ARMA(p; q) and ARFIMA(p; d; q) varieties. These tests speak for a slight superiority of the canonical opinion dynamics model over the alternatives in the majority of cases.