Quantifying the Uncertainty around Break Dates in Step-Indicator Saturation
Quantifying the uncertainty around structural breaks is crucial to attribute breaks to potential causes. Step-Indicator saturation (SIS, see Castle et al 2015) allows for the detection of structural breaks using model selection, however, little is known about the uncertainty around the timing of detected breaks. Here we quantify the uncertainty around break dates in models selected using SIS, to help when attributing detected breaks to events. Relying on congruence of designed models in general-to-specific model selection, we use the approximate normal distribution of the error terms to compute the probability of the underlying break falling in any specified interval around a detected break. This allows us to compute approximate probabilities of the date of the true break indicator coinciding with the date of the estimated break indicator, as a function of the estimated break magnitude and error variance. This enables hypothesis tests on break dates - an invaluable feature when attributing detected shifts to known events, from shocks in economics, to policy interventions in climate change. Analytical results show that a two standard deviation shift precisely coincides with the correct date approximately 64% of the time, with an approximate 95% confidence interval of plus/minus 3 periods. Monte Carlo simulations confirm the approximate confidence intervals for the break date in SIS. We demonstrate our method for breaks in UK NOX emissions time series using the R-package `gets'
Year of publication: |
[2023]
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Authors: | Hendry, David F. ; Pretis, Felix |
Publisher: |
[S.l.] : SSRN |
Saved in:
freely available
Extent: | 1 Online-Ressource (24 p) |
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Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments April 11, 2023 erstellt |
Other identifiers: | 10.2139/ssrn.4416619 [DOI] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10014357742
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