This paper proposes an econometric framework for nowcasting the monetary policy stance and decisions of the European … main drivers of the ECB's reaction function at every point in time. In out-of-sample nowcasting experiments, the model …

This paper assesses the forecasting performance of various variable reduction and variable selection methods. A small … and a large set of wisely chosen variables are used in forecasting the industrial production growth for four Euro Area …

We provide a versatile nowcasting toolbox that supports three model classes (dynamic factor models, large Bayesian VAR … simplifying two key tasks: creating new nowcasting models and improving the policy analysis. For model creation, the toolbox … nowcasting model for global GDP growth. Overall, the toolbox aims at facilitating creation, evaluation, and deployment of …

performs favourably compared to the Eurosystem/ECB staff macroeconomic projections, (iv) forecasting performance deteriorates …

. Nevertheless, their forecasting properties are still barely explored. We fill this gap by comparing the quality of real … priors from a DSGE model. We show that the analyzed DSGE model is relatively successful in forecasting the US economy in the … accurate short-term forecasts for interest rates. Conditional on experts' now casts, however, the forecasting power of the DSGE …

across different horizons and real-time datasets. To further improve performances when forecasting with machine learning, we …

We define nowcasting as the prediction of the present, the very near future and the very recent past. Crucial in this … collected at low frequency and published with long delays. Until recently, nowcasting had received very little attention by the … basis of simple models. We argue that the nowcasting process goes beyond the simple production of an early estimate as it …

forecasting power of these models for the Japanese economy. In this paper, we aim at assessing the relative performance of factor …. For most of the components, we report that factor models yield lower forecasting errors than a simple AR process or an … improvements in terms of forecasting accuracy are found for more volatile periods, such as the recent financial crisis. However …