Improving real-time estimates of output gaps and inflation trends with multiple-vintage models

Real-time estimates of output gaps and inflation trends differ from the values that are obtained using data available long after the event. Part of the problem is that the data on which the real-time estimates are based is subsequently revised. We show that vector-autoregressive models of data vintages provide forecasts of post-revision values of future observations and of already-released observations capable of improving real-time output gap and inflation trend estimates. Our findings indicate that annual revisions to output and inflation data are in part predictable based on their past vintages.