Methods are described for the appropriate use of data obtained and analysed in real time to represent the output gap. The methods employ cointegrating VAR techniques to model real-time measures and realizations of output series jointly. The model is used to mitigate the impact of data revisions; to generate appropriate forecasts that can deliver economically meaningful output trends and that can take into account the end-of-sample problems encountered in measuring these trends; and to calculate probability forecasts that convey in a clear way the uncertainties associated with the gap measures. The methods are applied to data for the United States 1965q4–2004q4, and the improvements over standard methods are illustrated
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