The effects of data uncertainty on real-time decision-making can be reduced by predicting early revisions to US GDP growth. We show that survey forecasts efficiently anticipate the first-revised estimate of GDP, but that forecasting models incorporating monthly economic indicators and daily...

"Bringing together the recent advances and innovative methods in macroeconomic forecasting, this erudite Handbook outlines how to forecast, including following world events such as the Covid-19 pandemic and the global financial crisis. With contributions from global experts, chapters explore the...

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...

We show how to improve the accuracy of real-time forecasts from models that include autoregressive terms by estimating the models on "lightly-revised" data instead of using data from the latest-available vintage. Forecast accuracy is improved by reorganizing the data vintages employed in the...