We show that financial variables contribute to the forecast of GDP growth during the Great Recession, providing additional insights on both first and higher moments of the GDP growth distribution. If a recession is due to an unforeseen shock (such as the Covid-19 recession), financial variables...

We show that financial variables contribute to the forecast of GDP growth during the Great Recession, providing additional insights on both first and higher moments of the GDP growth distribution. If a recession is due to an unforeseen shock (such as the Covid-19 recession), financial variables...

This paper proposes a simple technical approach for the analytical derivation of Point-in-Time PD (probability of default) forecasts, with minimal data requirements. The inputs required are the current and future Through-the-Cycle PDs of the obligors, their last known default rates, and a...

The focus of this paper is the evaluation of a very popular method for potential output estimation and medium-term forecasting? the production function approach?in terms of predictive performance. For this purpose, a forecast evaluation for the three to five years ahead predictions of GDP growth...

The focus of this paper is the evaluation of a very popular method for potential output estimation and medium-term forecasting - the production function approach - in terms of predictive performance. For this purpose, a forecast evaluation for the three to five years ahead predictions of GDP...

We document whether a simple, univariate model for quarterly GDP growth is able to deliver forecasts in a crisis period like the Covid-19 pandemic, which may serve cross-checking forecasts obtained from elaborate and expert models used by forecasting institutions. We include shocks to the log...

In this paper, we compare two fundamentally different judgmental demand forecasting approaches used to estimate demand and their corresponding demand distributions. In the first approach, parameters are obtained from a linear regression and maximum likelihood estimation (MLE) based on team...

The number of short-time workers from January to April 2020 is used to now- and forecast quarterly GDP growth. We purge the monthly log level series from the systematic component to extract unexpected changes or shocks to log short-time workers. These monthly shocks are included in a univariate...

The number of employees historically filed and registered from January to April 2020 for short-time compensation is used to obtain a nowcast for GDP growth in the first quarter and an outlook until the third quarter 2021. We purge the monthly log level series from the systematic component to...