Revising Beliefs In Nonidentified Models

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Revising Beliefs In Nonidentified Models

Author Info

Poirier, Dale J.

Abstract

A Bayesian analysis of a nonidentified model is always possible if a proper prior on all the parameters is specified. There is, however, no Bayesian free lunch. The price is that there exist quantities about which the data are uninformative, i.e., their marginal prior and posterior distributions are identical. In the case of improper priors the analysis is problematic resulting posteriors can be improper. This study investigates both proper and improper cases through a series of examples.

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Publisher Info
Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 14 (1998)
Issue (Month): 04 (August)
Pages: 483-509
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:cup:etheor:v:14:y:1998:i:04:p:483-509_14

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