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 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 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...

La littérature sur l'instabilité macroéconomique couvre un champ extrêmement vaste qui se révèle par le spectre très large de mesures utilisées pour appréhender ce phénomène. Le choix de la mesure de l'instabilité macroéconomique apparait généralement peu discuté sous le...

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...

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...

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...