In this paper we develop a new model that incorporates inflation expectations and can be used for the structural analysis of inflation, as well as for forecasting. In this latter connection, we specifically look into the usefulness of real-time survey data for inflation projections. We contribute to the literature in two ways. First, our model extracts the inflation trend and its cycle, which is linked to real economic activity, by exploiting a much larger information set than typically seen in this class of models and without the need to resort to Bayesian techniques. The reason is that we use variables reflecting inflation expectations from consumers and firms under the assumption that they are consistent with the expectations derived from the model. Thus, our approach represents an alternative way to shrink the model parameters and to restrict the future evolution of the factors. Second, the inflation expectations that we use are derived from the qualitative questions on expected price developments in both the consumer and the business surveys. This latter source, in particular, is mostly neglected in the empirical literature. Our empirical results suggest that overall, inflation expectations in surveys provide useful information for inflation forecasts. In particular for the most recent period, models that include survey expectations on prices tend to outperform similar models that do not, both for Belgium and the euro area. Furthermore, we find that the business survey, i.e. the survey replies by the price-setters themselves, contributes most to these forecast improvements.