Near Observational Equivalence and Unit Root Processes: Formal Concepts and Implications

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Abstract
A number of recent papers have discussed the fact that difference stationary and trend stationary processes are nearly observationally equivalent. The meaning of this fact, however, remains clouded. This paper defines near observational equivalence and derives several implications of the notion for classical and Bayesian unit root inference. For example, unless restrictions are imposed on the general difference and trend stationary models, the exact size of any consistent unit root test rises to one with sample size. Bayesian posteriors regarding unit roots are arbitrary in the sense that given any prior, there are other priors that agree with the first regarding empirical outcomes, but that imply arbitrarily different unit root posteriors.

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