In this paper we investigate the impact of publication lags on forecast quality. Specifically, using a set of 285 economic series, we provide a concise measure of the forecast inefficiencies associated with series that are subject to a delay in their publication. This inefficiency is measured with respect to a variety of models and found to be statistically significant under certain conditions. These conditions include the persistence of the series, and the model used to generate the forecasts. Regarding the latter, we provide some evidence to suggest that recently proposed models based on real-time predictor variables tend to deliver lower levels of forecast inefficiency.