Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/171826
Authors: 
Castle, Jennifer L.
Doornik, Jurgen A.
Hendry, David F.
Pretis, Felix
Year of Publication: 
2015
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 3 [Year:] 2015 [Issue:] 2 [Pages:] 240-264
Abstract: 
To capture location shifts in the context of model selection, we propose selecting significant step indicators from a saturating set added to the union of all of the candidate variables. The null retention frequency and approximate non-centrality of a selection test are derived using a "split-half" analysis, the simplest specialization of a multiple-path block-search algorithm. Monte Carlo simulations, extended to sequential reduction, confirm the accuracy of nominal significance levels under the null and show retentions when location shifts occur, improving the non-null retention frequency compared to the corresponding impulse-indicator saturation (IIS)-based method and the lasso.
Subjects: 
structural breaks
model selection
Monte Carlo
indicator saturation
Autometrics
JEL: 
C51
C22
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/4.0/
Document Type: 
Article
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