In this paper, a Bayesian approach is suggested to compare unit root models with stationary autoregressive models when both the level and the error variance are subject to structural changes (known as breaks) of an unknown date. Ignoring structural breaks in the error variance may be responsible...

In this paper a Bayesian approach to unit root testing for panel data models is proposed based on the comparison of stationary autoregressive models with and without individual determinist trends, with their counterpart models with unit autoregressive roots. This is done under cross-sectional...