This paper examines the predictive power of weather for electricity prices in day-ahead markets in real time. We find that next-day weather forecasts improve the forecast accuracy of day-ahead electricity prices substantially, suggesting that weather forecasts can price the weather premium....

We argue that the next generation of macro modellers at Inflation Targeting central banks should adapt a methodology from the weather forecasting literature known as `ensemble modelling'. In this approach, uncertainty about model specifications (e.g., initial conditions, parameters, and boundary...

We propose a novel Bayesian model combination approach where the combination weights depend on the past forecasting performance of the individual models entering the combination through a utility-based objective function. We use this approach in the context of stock return predictability and...

We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...

A long strand of literature has shown that the world has become more global. Yet, the recent Great Global Recession turned out to be hard to predict, with forecasters across the world committing large forecast errors. We examine whether knowledge of in-sample co-movement across countries could...

We introduce a Bayesian approach to predictive density calibration and combination that accounts for parameter uncertainty and model set incompleteness through the use of random calibration functionals and random combination weights. Building on the work of Ranjan and Gneiting (2010) and...

We estimate demand, supply, monetary, investment and financial shocks in a VAR identified with a minimum set of sign restrictions on US data. We find that financial shocks are major drivers of fluctuations in output, stock prices and investment but have a limited effect on inflation. In a second...

This paper presents the MATLAB package DeCo (density combination) which is based on the paper by Billio, Casarin, Ravazzolo, and van Dijk (2013) where a constructive Bayesian approach is presented for combining predictive densities originating from different models or other sources of...

This paper analyzes the sovereign risk contagion using CDS spreads for the major euro area countries. Using several econometric approaches (non linear regression, quantile regression and Bayesian quantile with heteroskedasticity) we show that propagation of shocks in Europe's CDS's has been...

Interactions between the eurozone and US booms and busts and among major eurozone economies are analyzed by introducing a panel Markov-switching VAR model well suitable for a multi-country cyclical analysis. The model accommodates changes in low and high data frequencies and endogenous...