Inference on Structural Breaks using Information Criteria

Alastair Hall, Denise Osborn and Nikolaos D. Sakkas

Centre for Growth and Business Cycle Research Discussion Paper Series from Economics, The University of Manchester

Abstract: This paper investigates the usefulness of information criteria for inference on the number of structural breaks in a standard linear regression model. In particular, we propose a modified penalty function for such criteria based on theoretical arguments, which implies each break is equivalent to estimation of three individual regression coefficients. A Monte Carlo analysis compares information criteria to sequential testing, with the modified BIC and HQIC criteria performing well overall, for DGPs both without and with breaks. The methods are also used to examine changes in Euro area monetary policy between 1971 and 2007.

Pages: 33 pages
Date: 2012
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://hummedia.manchester.ac.uk/schools/soss/cgb ... apers/dpcgbcr173.pdf (application/pdf)

Related works:
Journal Article: Inference on Structural Breaks using Information Criteria (2013)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:man:cgbcrp:173

Access Statistics for this paper

More papers in Centre for Growth and Business Cycle Research Discussion Paper Series from Economics, The University of Manchester Contact information at EDIRC.
Bibliographic data for series maintained by Patrick Macnamara ().