forecast performance of a model can potentially incur important policy costs. Commonly used statistical procedures, however … forecast breakdowns in small samples. We develop a procedure which aims at capturing the policy cost of missing a break. We use … can result from a break going undetected for too long. In so doing, we also explicitly study forecast errors as a …

likelihoods built from estimation errors). This paper sets a general context for this exercise, and describes some features of the … mean square error criterion. The forecast combinations generally lead to a reduction in forecast error, although over this …

conditions index, adds further forecast power, while third factors have a mixed effect on performance. The FCIs are used to …

This paper investigates the real-time forecast performance of the Bank of England's main DSGE model, COMPASS, before … COMPASS's relative forecast performance improves as the forecast horizon is extended (as does that of the Statistical Suite of …-model information and the method used to apply it are key determinants of DSGE model forecast accuracy …

Density forecast combinations are becoming increasingly popular as a means of improving forecast ‘accuracy', as … schemes. Sieve estimation is used to optimise the score of the generalised density combination where the combination weights … depend on the variable one is trying to forecast. Specific attention is paid to the use of piecewise linear weight functions …

We forecast CPI inflation in the United Kingdom up to one year ahead using a large set of monthly disaggregated CPI …, yielding gains in relative forecast accuracy of up to 70% at the one-year horizon. Our results suggests that the combination of … differences going beyond forecast accuracy …