Most macroeconomic data are uncertain—they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper...

This paper aims to provide a brief and relatively non-technical overview of state-of-the-art forecasting with large data sets. We classify existing methods into four groups depending on whether data sets are used wholly or partly, whether a single model or multiple models are used and whether a...

The Bank of England has constructed a 'suite of statistical forecasting models' (the 'Suite') providing judgement-free statistical forecasts of inflation and output growth as inputs into the forecasting process, and to offer measures of relevant news in the data. The Suite focuses on combining...

We extend the standard approach to Bayesian forecast combination by forming the weights for the model averaged forecast from the predictive likelihood rather than the standard marginal likelihood. The use of predictive measures of fit offers greater protection against in-sample overfitting when...

We extend the standard approach to Bayesian forecast combination by forming the weights for the model averaged forecast from the predictive likelihood rather than the standard marginal likelihood. The use of predictive measures of fit offers greater protection against in-sample overfitting and...