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...

We build a time varying DSGE model with financial frictions in order to evaluate changes in the responses of the macroeconomy to financial friction shocks. Using US data, we find that the transmission of the financial friction shock to economic variables, such as output growth, has not changed...