In this paper we introduce a non-parametric estimation method for a large Vector Autoregression (VAR) with time-varying parameters. The estimators and their asymptotic distributions are available in closed form. This makes the method computationally efficient and capable of handling information...

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...

Detection of structural change is a critical empirical activity, but continuous 'monitoring' of time series for structural changes in real time raises well-known econometric issues. These have been explored in a univariate context. If multiple series co-break, as may be plausible, then it is...

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...

We examine how to forecast after a recent break. We consider monitoring for change and then combining forecasts from models that do and do not use data before the change; and robust methods, namely rolling regressions, forecast averaging over different windows and exponentially weighted moving...

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...