Empirical evidence suggests that many macroeconomic and financial time series are subject to occasional structural breaks. In this paper we present analytical results quantifying the effects of such breaks on the correlation between the forecast and the realization and on the ability to forecast...

Autoregressive models are used routinely in forecasting and often lead to better performance than more complicated models. However, empirical evidence is also suggesting that the autoregressive representations of many macroeconomic and financial time series are likely to be subject to structural...

This paper provides a novel approach to forecasting time series subject to discrete structural breaks. We propose a Bayesian estimation and prediction procedure that allows for the possibility of new breaks over the forecast horizon, taking account of the size and duration of past breaks (if...

A structural break is viewed as a permanent change in the parameter vector of a model. Using taxonomies of all sources of forecast errors for both conditional mean and conditional variance processes, we consider the impacts of breaks and their relevance in forecasting models: (a) where the...

Empirical evidence suggests that many macroeconomic and financial time-series are subject to occasional structural breaks. In this paper we present analytical results quantifying the effects of such breaks on the correlation between the forecast and the realisation, and on the ability to...

Autoregressive models are used routinely in forecasting and often lead to better performance than more complicated models. However, empirical evidence is also suggesting that the autoregressive representations of many macroeconomic and financial time series are likely to be subject to structural...

Present value calculations require predictions of cash flows both at near and distant future points in time. Such predictions are generally surrounded by considerable uncertainty and may critically depend on assumptions about parameter values as well as the form and stability of the data...

This paper provides a novel approach to forecasting time series subject to discrete structural breaks. We propose a Bayesian estimation and prediction procedure that allows for the possibility of new breaks over the forecast horizon, taking account of the size and duration of past breaks (if...

Present value calculations require predictions of cash flows both at near and distant future points in time. Such predictions are generally surrounded by considerable uncertainty and may critically depend on assumptions about parameter values as well as the form and stability of the data...

This paper provides a novel approach to forecasting time series subject to discrete structural breaks. We propose a Bayesian estimation and prediction procedure that allows for the possibility of new breaks over the forecast horizon, taking account of the size and duration of past breaks (if...