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We propose a fast and consistent procedure to detect unit roots based on subspace methods. It has three distinctive features. First, the same method can be applied to single or multiple time series. Second, it employs a flexible family of information criteria, whose loss functions can be adapted to the statistical properties of the data. Last, it does not require the specification of a model for the analysed series. In addition, we provide a subspace-based consistent estimator for the cointegrating rank and the cointegrating matrix. Simulation exercises show that these procedures have good finite sample properties.