Macroeconomic risk assessments play an important role in the forecasts of manyinstitutions. However, to the best of our knowledge their performance has notbeen investigated yet. In this work, we study the Bank of England’s risk forecastsfor inflation. We find that these forecasts do not...

In this papaer, we put DSGE forecasts in competition with factor forecasts. We focus on these two models since they represent nicely the two opposing forecasting philosophies. The DSGE model on the one hand has a strong theoretical economic background; the factor model on the other hand is mainly...

This paper investigates the impact of news media information on improving short-term GDP growth forecasts by analyzing a large and unique corpus of 12.4 million news articles spanning from 1991 to 2018. We extract business cycle-related sentiment from each article using an annotated dataset from...

We propose a prior for VAR models that exploits the panel structure of macroeconomic time series while also providing shrinkage towards zero to address overfitting concerns. The prior is flexible as it detects shared dynamics of individual variables across endogenously determined groups of...

A reflection on the lackluster growth over the decade since the Global Financial Crisis has renewed interest in preventative measures for a long-standing problem. Advances in machine learning algorithms during this period present promising forecasting solutions. In this context, the paper...

This paper describes a dynamic factor model for the Maltese economy. The model mainly serves as a tool to timely provide the Central Bank of Malta with nowcasts as well as short-term forecasts of the growth rate of the real gross domestic product, which in turn are used as an input in the...

The purpose of this paper is to compare the accuracy of the three types of models: Autoregressive Integrated Moving Average (ARIMA) models, Holt-Winters models and Neural Network Auto-Regressive (NNAR) models in forcasting the Harmonized Index of Consumer Prices (HICP) for the countries of...

Forecast models with large cross-sections are often subject to overparameterization leading to unstable parameter estimates and hence inaccurate forecasts. Recent articlessuggest that a large Bayesian vector autoregression (BVAR) with sufficient prior information dominates competing approaches....

Over the past 10 years dynamic stochastic general equilibrium (DSGE) models have become an important tool in quantitative macroeconomics. However, DSGE models were not considered as a forecasting tool until very recently. The objective of this paper is twofold. First, we compare the forecasting...

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...