This analysis investigates the predictive power of the most important leading indicators for the German economy, which are provided by the ifo Institute and IHS Markit. We conduct an out-of-sample, real-time forecast experiment for growth of gross domestic product and growth of gross value added...

This paper provides a detailed assessment of the real-time forecast accuracy of a wide range of vector autoregressive models (VAR) that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed-frequency time-varying...

This paper investigates the macroeconomic projections of the German government since the 1970s and compares it those of the Joint Economic Forecast, which is an in-dependent forecasting institution in Germany. Our results indicate that nominal GDP projections are upward biased for longer...

The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...

Using a novel dataset that contains qualitative firm survey data on sales forecasts as well as balance-sheet data on realized sales, we document that only major forecast errors are predictable and display autocorrelation. This result is a particular violation of the Full Information Rational...

We reformulate the Nordhaus test as a friction model where the large number of zero revisions are treated as censored, i.e., unknown values inside a small region of "imperceptibility." Using Blue Chip individual forecasts of U.S. real GDP growth, inflation, and unemployment over 1985-2020, we...