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...

Detection of structural change is a critical empirical activity, but continuous 'monitoring' of series, for structural changes in real time, raises well-known econometric issues that have been explored in a single series context. If multiple series co-break then it is possible that simultaneous...

In recent years there has been increasing interest in forecasting methods that utilise large datasets, driven partly by the recognition that policymaking institutions need to process large quantities of information. Factor analysis is one popular way of doing this. Forecast combination is...

Recently, there has been increasing interest in forecasting methods that utilise large datasets. We explore the possibility of forecasting with model averaging using the out-of-sample forecasting performance of various models in a frequentist setting, using the predictive likelihood. We apply...