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...

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...

We compare the Bank of England's Inflation Report quarterly forecasts for growth and inflation to real-time benchmark forecasts. The results reveal the well-known difficulty of forecasting in a stable macroeconomic environment, and the Inflation Report forecasts of GDP growth are generally...

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 consider time series forecasting in the presence of ongoing structural change where both the time series dependence and the nature of the structural change are unknown. Methods that downweight older data, such as rolling regressions, forecast averaging over different windows and exponentially...