PRIOR ELICITATION IN MULTIPLE CHANGE‐POINT MODELS* |
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| Authors: | Gary Koop Simon M. Potter |
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| Affiliation: | 1. University of Strathclyde, UK;2. Federal Reserve Bank of New York, U.S.A.;3. We would like to thank seminar participants at the Federal Reserve Bank of St. Louis and University of Kansas. The views expressed in this article are ours and do not necessarily reflect the views of the Federal Reserve Bank of New York or the Federal Reserve System. Gary Koop is a Fellow of the Rimini Center for Economic Analysis. Please address correspondence to: Gary Koop, Department of Economics, University of Strathclyde, Sir William Duncan Building, 130 Rottenrow, Glasgow G4 0GE, Scotland, UK. E‐mail: . |
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| Abstract: | This article discusses Bayesian inference in change‐point models. The main existing approaches treat all change‐points equally, a priori, using either a Uniform prior or an informative hierarchical prior. Both approaches assume a known number of change‐points. Some undesirable properties of these approaches are discussed. We develop a new Uniform prior that allows some of the change‐points to occur out of sample. This prior has desirable properties, can be interpreted as “noninformative,” and treats the number of change‐points as unknown. Artificial and real data exercises show how these different priors can have a substantial impact on estimation and prediction. |
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