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 analyze the relationship between uncertainty and economic growth expectations in Mexico through the Growth at Risk methodology. Our analysis consists of two stages: first, we estimate a quantile regression of annual output growth conditional on lagged values of a measure of macroeconomic...

We specify an empirical model of US inflation which has the dynamics of wage and price setting at its core. In the dynamic wage equation an equilibrium-correction term connects the wage level to industrial prosperity indicators. In that way, the role of wage setting in the dynamics of the...

Obgleich es zahlreiche Institutionen gibt, die das deutsche Bruttoinlandsprodukt vorhersagen, mangelt es aktuell an sogenannten "Nowcasting"-Modellen, deren Prognosegüte mit jedem neu verfügbaren, das deutsche Bruttoinlandsprodukt beeinflussenden Datenpunkt verbessert wird. In der folgenden...

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...

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...

We document whether a simple, univariate model for quarterly GDP growth is able to deliver forecasts of yearly GDP growth in a crisis period like the Covid19 pandemic, which may serve cross-checking forecasts obtained from elaborate and expert models used by forecasting institutions. We include...

This paper presents a framework for quantifying uncertainty around point forecasts for GDP, inflation and house prices in Norway. The framework combines quantile regressions using a broad set of uncertainty indicators with a skewed t-distribution, allowing for time-variation and asymmetry in the...

This paper exploits daily infrared images taken from satellites to track economic activity in advanced and emerging countries. We first develop a framework to read, clean, and exploit satellite images. Our algorithm uses the laws of physics (Planck's law) and machine learning to detect the heat...