Having a correct assessment of current business cycle conditions is one of the major challenges for monetary policy conduct. Given that GDP figures are available with a significant delay central banks are increasingly using Nowcasting as a useful tool for having an immediate perception of...

We analyze how modeling international dependencies improves forecasts for the global economy based on a Bayesian GVAR with SSVS prior and stochastic volatility. To analyze the source of performance gains, we decompose the predictive joint density into its marginals and a copula term capturing...

Based on German business cycle forecast reports covering 10 German institutions for the period 1993-2017, the paper analyses the information content of German forecasters' narratives for German business cycle forecasts. The paper applies textual analysis to convert qualitative text data into...

The primary goal of this paper is to describe several models that are currently used at the National Bank of the Republic of Macedonia (NBRM) for short-term forecasting of inflation - Autoregressive integrated moving average models (aggregated and disaggregated approach), three equation...

The Eurosystem/ECB staff macroeconomic projection exercises constitute an important input to the ECB's monetary policy. This work marks a thorough analysis of the Eurosystem/ECB projection errors by looking at criteria of optimality and rationality using techniques widely employed in the applied...

We provide a novel methodology for estimating time-varying weights in linear prediction pools, which we call dynamic pools, and use it to investigate the relative forecasting performance of dynamic stochastic general equilibrium (DSGE) models, with and without financial frictions, for output...

In this paper we develop a small open economy model explaining the joint determination of output, inflation, interest rates, unemployment and the exchange rate in a multi-country framework. Our model - the Halle Economic Projection Model (HEPM) - is closely related to studies recently published...

We provide a novel methodology for estimating time-varying weights in linear prediction pools, which we call dynamic pools, and use it to investigate the relative forecasting performance of dynamic stochastic general equilibrium (DSGE) models, with and without financial frictions, for output...