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...

This study evaluates forecasting performance of a large-scale factor model developed in Siliverstovs and Kholodilin (2012) in a genuine ex ante forecasting exercise. We perform our forecast of GDP growth in Switzerland in real time using real-time data vintages collected at weekly frequency....

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...

The paper evaluates the quality of the German national accounting data (GDP and its use-side components) as measured by the magnitude and dispersion of the forecast/revision errors. It is demonstrated that government consumption series are the least reliable, whereas real GDP and real private...

In this paper, we investigate whether the Google search activity can help in nowcasting the year-on-year growth rates of monthly US private consumption using a real-time data set. The Google-based forecasts are compared to those based on a benchmark AR(1) model and the models including the...

The paper evaluates the quality of the German national accounting data (GDP and its use-side components) as measured by the magnitude and dispersion of the forecast/revision errors. It is demonstrated that government consumption series are the least reliable, whereas real GDP and real private...

In this paper we extend the targeted-regressor approach suggested in Bai and Ng (2008) for variables sampled at the same frequency to mixed-frequency data. Our MIDASSO approach is a combination of the unrestricted MIxed-frequency DAta-Sampling approach (U-MIDAS) (see Foroni et al., 2015; Castle et...

In this paper we suggest an approach to comparison of models' forecasting performance in unstable environments. Our approach is based on combination of the Cumulated Sum of Squared Forecast Error Differential (CSSFED) suggested earlier in Welch and Goyal (2008) and the Bayesian change point...