Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/212314 
Erscheinungsjahr: 
2015
Schriftenreihe/Nr.: 
Bank of Finland Research Discussion Papers No. 6/2015
Verlag: 
Bank of Finland, Helsinki
Zusammenfassung: 
This paper presents first steps toward robust early-warning models. We conduct a horse race of conventional statistical methods and more recent machine learning methods. As early-warning models based upon one approach are oftentimes built in isolation of other methods, the exercise is of high relevance for assessing the relative performance of a wide variety of methods. Further, we test various ensemble approaches to aggregating the information products of the built early-warning models, providing a more robust basis for measuring country-level vulnerabilities. Finally, we provide approaches to estimating model uncertainty in early-warning exercises, particularly model performance uncertainty and model output uncertainty. The approaches put forward in this paper are shown with Europe as a playground.
JEL: 
E44
F30
G01
G15
C43
Persistent Identifier der Erstveröffentlichung: 
ISBN: 
978-952-323-027-9
Dokumentart: 
Working Paper

Datei(en):
Datei
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