We compare real-time density forecasts for the euro area using three DSGE models. The benchmark is the Smets-Wouters model and its forecasts of real GDP growth and inflation are compared with those from two extensions. The first adds financial frictions and expands the observables to include a...

A New Keynesian DSGE model with non-Ricardian households is estimated for the Portuguese economy and the stability of the model’s prediction (posterior distributions, impulse responses, and sources of fluctuations in endogenous variables) tested under different assumptions on non-Ricardian...

We propose a class of prior distributions that discipline the long-run predictions of vector autoregressions (VARs). These priors can be naturally elicited using economic theory, which provides guidance on the joint dynamics of macroeconomic time series in the long run. Our priors for the long...

The prominent role of monetary policy in the U.S. interwar depression has been conventional wisdom since Friedman and Schwartz [1963]. This paper presents evidence on both the surprise and the systematic components of monetary policy between 1929 and 1933. Doubts surrounding GDP estimates for...

Bayesian predictive synthesis is a flexible method of combining density predictions. The flexibility comes from the ability to choose an arbitrary synthesis function to combine predictions. I study the choice of synthesis function when combining large numbers of predictions-a common occurrence...

We propose a multicountry quantile factor augmeneted vector autoregression (QFAVAR) to model heterogeneities both across countries and across characteristics of the distributions of macroeconomic time series. The presence of quantile factors allows for summarizing these two heterogeneities in a...

This paper presents a weekly GDP indicator for Switzerland, which addresses the limitations of existing economic activity indicators using alternative high-frequency data created in the wake of the COVID-19 pandemic. The indicator is obtained from a Bayesian mixed-frequency dynamic factor model...

We propose an unobserved components model with stochastic volatility and structural shocks to explore the relevant factors that influence trend inflation in the USA. Using structural shocks that incorporate a broad set of information for the US economy, we find that four structural shocks have...

In this paper we investigate whether the forecast of the HICP components (indirect approach) improves upon the forecast of overall HICP (direct approach) and whether the aggregation of country forecasts improves upon the forecast of the euro-area as a whole, considering the four largest euro...

In this paper we review the methodology of forecasting with log-linearised DSGE models using Bayesian methods. We focus on the estimation of their predictive distributions, with special attention being paid to the mean and the covariance matrix of h-step ahead forecasts. In the empirical...