The post-crisis environment has posed important challenges to standard forecasting models. In this paper, we exploit several combinations of a large-scale DSGE structural model with standard reduced-form methods such as (B)VAR (i.e. DSGE-VAR and Augmented-(B)VARDSGE methods) and assess their use...

The model presented here is an estimated medium-scale model for the United States (US) economy developed to forecast and analyse policy issues for the US. The model is specified to track the deviation of the medium-run developments from the balanced-growth-path via an estimated CES production...

Time-varying parameter (TVP) models have the potential to be over-parameterized, particularly when the number of variables in the model is large. Global-local priors are increasingly used to induce shrinkage in such models. But the estimates produced by these priors can still have appreciable...

This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using additive regression trees. We argue that regression tree models are ideally suited for macroeconomic nowcasting in the face of extreme observations, for instance those produced...

This paper uses forecasts from the European Central Bank's Survey of Professional Forecasters to investigate the relationship between inflation and inflation expectations in the euro area. We use theoretical structures based on the New Keynesian and Neoclassical Phillips curves to inform our...

The balance sheet adjustment in the household sector was a prominent feature of the Great Recession that is widely believed to have held back the cyclical recovery of the US economy. A key question for the US outlook is therefore whether household deleveraging has ended or whether further...