This paper considers the analysis of cointegrated time series using principal components methods. These methods have the advantage of neither requiring the normalisation imposed by the triangular eror correction model, nor the specification of a finite order vector autoregression.

This paper compares and generalizes some testing procedures for structural change in the context of cointegrated regression models.