Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/62816 
Year of Publication: 
2004
Series/Report no.: 
Working Paper No. 514
Publisher: 
Queen Mary University of London, Department of Economics, London
Abstract: 
In this paper, a Bayesian approach is suggested to compare unit root models with stationary models when both the level and the error variance are subject to structural changes (known as breaks) of an unknown date. The paper utilizes analytic and Monte Carlo integration techniques for calculating the marginal likelihood of the models under consideration, in order to compute the posterior model probabilities. The performance of the method is assessed by simulation experiments. Some empirical applications of the method are conducted with the aim to investigate if it can detect structural breaks in financial series, with changes in the error variance.
Subjects: 
Bayesian inference, Model comparison, Autoregressive models, Unit roots, Structural breaks
JEL: 
C11
C22
G10
Document Type: 
Working Paper

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