Recent rises in macroeconomic volatility have prompted the introduction of quantile vector autoregression (QVAR) models to forecast macroeconomic risk. This paper provides an extensive evaluation of the predictive performance of QVAR models in a pseudo-out-of-sample experiment spanning 112...

This paper focuses on identifying useful indicators for nowcasting GDP in Sweden. We analyze 35 monthly indicators spanning the period from 1993 to 2023. Additionally, we evaluate the group-wise performance of these indicators. The analysis is conducted using mixed-data sampling (MIDAS) and...

The German economy is stuck in a difficult position as it faces both slow growth as well as structural change. The continuing lack of orders in manufacturing, increasing international competition, and sluggish development in industry-related services are now affecting the labor market and...

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...

This special topic investigates the extent to which selling price expectations (SPE) from the harmonised EU programme of business surveys contain leading information for forecasting short-term developments in the Harmonised Index of Consumer Prices (HICP). The analysis is based on a...

Following a prolonged and broad-based stagnation, the EU economy resumed growth in the first quarter of this year. As projected in spring, the expansion continued at a subdued, yet steady, pace throughout the second and third quarters, amidst further abating inflationary pressures. The...

We introduce a frequency-domain forecast combination method that leverages time- and frequencydependent predictability to enhance forecast accuracy. By decomposing both the target variables (equity premium and real GDP growth) and predictor variables into distinct frequency components, this...

This paper investigates nowcasting Growth-at-Risk (GaR) using consensus forecasts from the Survey of Professional Forecasters (SPF) in the US. Incorporating SPF consensus forecasts into the conditional mean of an AR-GARCH type model significantly enhances nowcasting accuracy for GaR and the...

In this study, we analyzed the forecasting and nowcasting performance of a generalized regression neural network (GRNN). We provide evidence from Monte Carlo simulations for the relative forecast performance of GRNN depending on the data-generating process. We show that GRNN outperforms an...

The crisis periods of the past decades have highlighted the difficulty of forecasting economic indicators due to increased non-linearity and rapidly changing dynamics. To address this challenge, we introduce the Transform-Sparsify-Forecast (TSF) framework. The TSF framework first applies...

We develop a novel methodology to quantify forecasts based on qualitative survey data. The methodology is generally applicable when quantitative information is available on the realization of the forecasted variable, for example from firm balance sheets. The method can be applied to a wide range...

The German economy will likely contract in the first quarter of 2024 due to still heightened inflation and weak demand, which was already weighing on German economic output in 2023. Inflation, which is falling in both Germany and the euro area overall, is expected to return close to the European...

We forecast recessions in Canada using an autoregressive (AR) probit model. In this model, the presence of the lagged latent variable, which captures the autocorrelation in the recession binary variable, results in an intractable likelihood with a high dimensional integral. Therefore, we employ...

Economic policies are generally formulated on the basis of data available in real time, which might subsequently be revised. Implicitly, the possibility of data revisions creates an element of uncertainty around the very same data driving policy decisions. Given that such uncertainty could be...