Macroeconomic data are subject to revision over time as later vintages are released, yet the usual way of generating real-time out-of-sample forecasts from models effectively makes no allowance for this form of data uncertainty. We analyse a simple method which has been used in the context of...

Using U.S. real-time data, we show that changes in the unemployment rate unexplained by Okun's Law have significant predictive power for GDP data revisions. A positive (negative) error in Okun's Law in real time implies that GDP will be later revised to show less (more) growth than initially...

It is difficult to choose the best model for forecasting real per capita GDP for a particular country or group of countries. This study suggests potential gains from combining time series and growth-regression-based approaches to forecasting.Kraay and Monokroussos consider two alternative...

We estimate a Markow-switching dynamic factor model with three states based on six leading business cycle indicators for Germany preselected from a broader set using the Elastic Net soft-thresholding rule. The three states represent expansions, normal recessions and severe recessions. We show...

This paper contributes to the large debate regarding the impact of oil price changes on U.S. GDP growth. Firstly, it replicates empirical findings of prominent studies and finds that the proposed oil price measures have a dissipating effect with recent data up to 2016Q4. Secondly, it re-examines...