Average inflation in the euro area has remained relatively stable since the onset of the current economic and financial crisis. Given the extent and length of the crisis, this observation might seem surprising in that it suggests that the traditional cyclical behaviour of inflation has weakened...

This paper develops an efficient approach to model and forecast time-series data with an unknown number of change-points. Using a conjugate prior and conditional on time-invariant parameters, the predictive density and the posterior distribution of the change-points have closed forms. The...

This paper builds on a simple unified representation of shrinkage Bayes estimators based on hierarchical Normal-Gamma priors. Various popular penalized least squares estimators for shrinkage and selection in regression models can be recovered using this single hierarchical Bayes formulation....

This paper builds on a simple unified representation of shrinkage Bayes estimators based on hierarchical Normal-Gamma priors. Various popular penalized least squares estimators for shrinkage and selection in regression models can be recovered using this single hierarchical Bayes formulation....

This paper presents a bridge model for short-run (one or two quarters ahead) forecasting of Italian GDP, relying on industrial production and survey indicators as key variables that can help in providing a real-time first GDP estimate. For a one- to two-year horizon, it formulates and estimates...

We estimate a medium scale DSGE model for the Euro Area to gain intuition on the importance of Limited Asset Market Participation (LAMP). Our results suggest that LAMP is sizeable (39% of households over the 1993-2012 sample) and important to understand EMU business cycle, especially, in the...

The predictive likelihood is of particular relevance in a Bayesian setting when the purpose is to rank models in a forecast comparison exercise. This paper discusses how the predictive likelihood can be estimated for any subset of the observable variables in linear Gaussian state-space models...

This paper presents the Matlab package DeCo (Density Combination) which is based on the paper by Billio et al. (2013) where a constructive Bayesian approach is presented for combining predictive densities originating from different models or other sources of information. The combination weights...

Changing time series properties of US inflation and economic activity, measured as marginal costs, are modeled within a set of extended Phillips Curve (PC) models. It is shown that mechanical removal or modeling of simple low frequency movements in the data may yield poor predictive results...

Forecast models with large cross-sections are often subject to overparameterization leading to unstable parameter estimates and hence inaccurate forecasts. Recent articlessuggest that a large Bayesian vector autoregression (BVAR) with sufficient prior information dominates competing approaches....