This paper considers forecast averaging when the same model is used but estimation is carried out over different estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or more structural breaks. It is shown that compared to...

We propose a new approach to deal with structural breaks in time series models. The key contribution is an alternative dynamic stochastic specification for the model parameters which describes potential breaks. After a break new parameter values are generated from a so-called baseline prior...

In this paper we evaluate the performance of several structural break tests under various DGPs. Concretely we look at size and power properties of CUSUM based, LM and Wald volatility break tests. In a simulation study we derive the properties of the tests under shifts in the unconditional and...

We propose a new approach to deal with structural breaks in time series models. The key contribution is an alternative dynamic stochastic specification for the model parameters which describes potential breaks. After a break new parameter values are generated from a so-called baseline prior...

Our aim in this article is to predict local airline market shares in the United States at the company level combining traditional economic indicators (at the national and local levels) with Google search engine requests. We resort both to simple econometric models and to more sophisticated...

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...

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...

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...

The Perron test is the most commonly applied procedure to test for a unit root in the presence of a structural break of unknown timing in the trend function. Deriving the Perron-type test regression from an unobserved component model, it is shown that the test regression in fact is nonlinear in...