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...

We identify financial stress regimes using a model that explicitly links financial variables with the macroeconomy. The financial stress regimes are identified using a large unbalanced panel of financial variables with an embedded method for variable selection and, empirically, are strongly...

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...