Many macroeconomic series such as US real output growth are sampled quarterly, although potentially useful predictors are often observed at a higher frequency. We look at whether a mixed data-frequency sampling (MIDAS) approach can improve forecasts of output growth. The MIDAS approach is...

Quantile forecasts are central to risk management decisions because of the widespread use of Value-at-Risk. A quantile forecast is the product of two factors: the model used to forecast volatility, and the method of computing quantiles from the volatility forecasts. In this paper we calculate...

The recent literature suggests that first announcements of real output growth in the US have predictive power for the future course of the economy. We show that this need not point to a behavioural relationship, whereby agents respond to the announcement, but may instead simply be a by-product...

We find that model estimates of the term structure of ex ante or perceived macro uncertainty are more in line with realized uncertainty than survey respondents’ perceptions for both inflation and output growth. Survey estimates contain short-term vari- ation in short-horizon uncertainty which...

Vintage-based vector autoregressive models of a single macroeconomic variable are shown to be a useful vehicle for obtaining forecasts of different maturities of future and past observations, including estimates of post-revision values. The forecasting performance of models which include...

We show how to improve the accuracy of real-time forecasts from models that include au-toregressive 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...