A canonical model is described which reflects the real time informational context of decision-making. Comparisons are drawn with ‘conventional’ models that incorrectly omit market-informed insights on future macroeconomic conditions and inappropriately incorporate information that was not available at the time. It is argued that conventional models are misspecified and misinterpret news. However, neither diagnostic tests applied to the conventional models nor typical impulse response analysis will be able to expose these deficiencies clearly. This is demonstrated through an analysis of quarterly US data 1968q4-2006q1. However, estimated real time models considerably improve out-of- sample forecasting performance, provide more accurate ‘nowcasts’ of the current state of the macroeconomy and provide more timely indicators of the business cycle. The point is illustrated through an analysis of the US recessions of 1990q3—1991q2 and 2001q1— 2001q4.