This study investigates usefulness of business tendency surveys in industrial sector for out-of-sample prediction of growth of industrial production in Russia. A special attention is paid to performance of survey-augmented models during the recent Great Recession 2008/2009. Using the real-time...

Forecasting real economic activity poses a considerable challenge not only due to hard-to-predict events like the current financial crisis but also due to the fact that targeted variables often undergo significant revisions after their first publication. In this paper we report the results of a...

We compare forecasts from different adaptive learning algorithms and calibrations applied to US real-time data on inflation and growth. We find that the Least Squares with constant gains adjusted to match (past) survey forecasts provides the best overall performance both in terms of forecasting...

We investigate whether the KOF Barometer–a leading indicator regularly released by the KOF Swiss Economic Institute–can be useful for short-term out-of-sample prediction of year-on-year quarterly real GDP growth rates in Switzerland. We find that the KOF Barometer appears to be useful for...

This study presents a model that delivers more accurate forecasts of the revised rather initial estimates of the quarterly GDP growth rate in Switzerland during the period of the recent financial crisis. The key explanation to our findings is that our model, capitalizing on the information...

We investigate the information content of business tendency surveys for key macroeconomic variables in Switzerland. To summarise the information of a large data set of sectoral business tendency surveys we extract a small number of common factors by a principal components estimator. The...