This paper aims to demonstrate that the data revision process affects the persistence of gross domestic product shocks. Results will contribute to the debate between unit root and linear models.

We consider the problem of unobserved components in time series from a Bayesian non-parametric perspective. The identification conditions are treated as unknown and analyzed in a probabilistic framework. In particular, informative prior distributions force the spectral decomposition to be in an...

This paper aims to demonstrate that the data revision process affects the persistence of gross domestic product shocks. Results will contribute to the debate between unit root and linear models.