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 …

additionally extract information on the volatility of the series to be predicted, since volatility is forecast-relevant under non … forecast, we employ an information criterion tailored to the relevant loss. Using a large monthly data set for the US economy … use of estimation under the relevant loss is effective. Using an additional volatility proxy as predictor and conducting …

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 …

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 …