There is a consensus that the best way to forecast customer churn is by statistical methods. It is, however, unclear when which statistical method is more appropriate. This study aims to provide a set of guidelines to data scientists and researchers who are interested in optimizing statistical...

We nowcast and forecast Austrian economic activity, namely real gross domestic product (GDP), consumption and investment, which are available at a quarterly frequency. While nowcasting uses data up to (and including) the quarter to be predicted, forecasting uses only data up to the previous...

This paper describes the set of Bayesian vector autoregression (BVAR) models that Banco de España uses to project GDP growth rates and to simulate macrofinancial risk scenarios for Brazil and Mexico. The toolkit consists of large benchmark models to produce baseline projections and various...

We propose an easy-to-implement framework for combining quantile forecasts, applied to forecasting GDP growth. Using quantile regressions, our combination scheme assigns weights to individual forecasts from different indicators based on quantile scores. Previous studies suggest distributional...

The study investigates the existence and extent of information rigidity in inflation forecasts among 25 developed and 18 developing economies during 2002-2017 period utilizing a survey data set never explored before on this issue. In general, the study finds some evidence of information...

This report projects the inflows and outflows of the EU budget for the next five years in accordance with Article 247(1)(c) of the Financial Regulation. This fourth edition forecasts the revenue and expenditure stemming from the Multiannual Financial Framework (MFF) 2021-2027 and...

This methodological report explains the data sources and methods used by the Joint Research Centre (JRC) to compile the dataset on structural small and medium-sized enterprises (SMEs) indicators in the annual SME Performance Review, and commissioned by the Directorate General for Internal...

Dynamic factor models (DFMs), which assume the existence of a small number of unobserved underlying factors common to a large number of variables, are very popular among empirical macroeconomists. Factors can be extracted using either nonparametric principal components or parametric Kalman...

We analyse the performance of financial market variables in nowcasting Finnish quarterly GDP growth. In particular, we assess if prediction accuracy is affected by the sampling frequency of the financial variables. Therefore, we apply MIDAS models that allow us to nowcast quarterly GDP growth...