Model selection when there are multiple breaks

Jennifer Castle, Jurgen Doornik and David Hendry

Journal of Econometrics, 2012, vol. 169, issue 2, 239-246

Abstract: We consider model selection facing uncertainty over the choice of variables and the occurrence and timing of multiple location shifts. General-to-simple selection is extended by adding an impulse indicator for every observation to the set of candidate regressors: see Johansen and Nielsen (2009). We apply that approach to a fat-tailed distribution, and to processes with breaks: Monte Carlo experiments show its capability of detecting up to 20 shifts in 100 observations, while jointly selecting variables. An illustration to US real interest rates compares impulse-indicator saturation with the procedure in Bai and Perron (1998).

Keywords: Impulse-indicator saturation; Location shifts; Model selection; Autometrics (search for similar items in EconPapers)
JEL-codes: C22 C52 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (76)

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Working Paper: Model Selection when there are Multiple Breaks (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:169:y:2012:i:2:p:239-246

DOI: 10.1016/j.jeconom.2012.01.026

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