This paper proposes strategies to detect time reversibility in stationary stochastic processes by using the properties of mixed causal and noncausal models. It shows that they can also be used for non-stationary processes when the trend component is computed with the Hodrick-Prescott filter...

This paper proposes concepts and methods to investigate whether the bubble patterns observed in individual time series are common among them. Having established the conditions under which common bubbles are present within the class of mixed causal-noncausal vector autoregressive models, we...

We are interested in determining the number of common trends and common cycles in the output of a set of Latin American countries. In order to work with homogeneous and reasonably good series however, we should rely on annual data. Consequently, the number of variables is relatively large...