Prior elicitation in multiple change-point models
By: Gary M. Koop and Simon M. Potter.
Contributors: Potter, Simon M.; Federal Reserve Bank of New York.
Series: Staff reports ;; no. 197; Staff reports (Federal Reserve Bank of New York : Online) ;; no. 197
Publisher: Federal Reserve Bank of New York
Published: 2004
Place of publication: [New York, N.Y.]
Language: eng
Format: Electronic resource
Subjects: Econometric models.
Description: "This paper discusses Bayesian inference in change-point models.  Current approaches place a possibly hierarchical prior over a known number of change points.  We show how two popular priors have some potentially undesirable properties, such as allocating excessive prior weight to change points near the end of the sample.  We discuss how these properties relate to imposing a fixed number of change points in the sample.  In our study, we develop a hierarchical approach that allows some change points to occur out of the sample.  We show that this prior has desirable properties and handles cases with unknown change points.  Our hierarchical approach can be shown to nest a wide variety of change-point models, from time-varying parameter models to those with few or no breaks.  Data-based learning about the parameter that controls this variety occurs because our prior is hierarchical"--Federal Reserve Bank of New York web site.
Notes: Includes bibliographical references.
Title from summary page as viewed on 1/10/2005.
Also available in print.
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Mode of access: World Wide Web.