Priors for Unit Root Models

Joseph B. Kadane, Ngai Hang Chan and Lara J. Wolfson


In the recent debate about unit roots, part of the discussion now centers on what prior is correct to use. From the perspective of subjective Bayesians, this question seems ill posed. To the extent that the likelihood is sharply peaked, the prior will not matter much. To the extent that the likelihood is flat, the posterior depends principally on the prior. A special consideration in unit roots models is that the spaces , and have very different economic implications. A better way to asses the role of the prior is to study its connections with these implications through prior elicitations.

In each of the intervals, a conjugate prior (i.e. normal-inverse gamma) is fit to the elicited opinion of an expert. Since the likelihood in each interval is normal, the posterior is of the same form as the prior (i.e. piece-wise normal-inverse gamma), so this family of priors is closed under sampling.

A modification of existing methods for the normal linear model permits elicitation of this expanded family of prior distributions. An example elicitation of a macro-economist is discussed.

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