Research Output per year

### Abstract

This paper discusses Bayesian inference in change-point models. Existing approaches involve placing a (possibly hierarchical) prior over a known number of change-points. We show how two popular priors have some potentially undesirable properties (e.g. allocating excessive
prior weight to change-points near the end of the sample) and discuss how these properties relate to imposing a fixed number of changepoints in-sample. We develop a new hierarchical approach which allows some of of change-points to occur out-of sample. We show that this prior has desirable properties and handles the case where the
number of change-points is unknown. Our hierarchical approach can be shown to nest a wide variety of change-point models, from timevarying parameter models to those with few (or no) breaks. Since our prior is hierarchical, data-based learning about the parameter which
controls this variety occurs.

Original language | English |
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Place of Publication | Leicester |

Number of pages | 29 |

Publication status | Published - Sep 2004 |

### Publication series

Name | Department of Economics Working Papers |
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Publisher | University of Leicester |

Volume | 04/26 |

### Keywords

- bayesian inference
- change-point models
- change-points
- statistics
- economics

## Research Output

- 1 Article

## Prior elicitation in multiple change-point models

Koop, G. M. & Potter, S., Aug 2009, In : International Economic Review. 50, 3, p. 751-772 21 p.Research output: Contribution to journal › Article

17
Citations
(Scopus)

## Cite this

Koop, G., & Potter, S. M. (2004).

*Prior elicitation in multiple change-point models*. (Department of Economics Working Papers; Vol. 04/26).