Describing Location Shifts with One Class Support Vector Machines
MPRA Paper from University Library of Munich, Germany
The evolution of variables during location shifts (structural breaks) is of high interest to policy makers. I propose a novel approach to describe location shifts. I use two business surveys in the industry sector (faster soft indicators) to target the industrial production index (a slower hard indicator). Then I use One-Class Support Vector Machines on combinations of these two variables to identify if new observations act as ’novelties’ for the target variable, as observations coming from a diﬀerent distribution. In that case, one would expect the onset/end of a location shift. Moreover, that gives insights into what role animal spirit, as manifested in survey data, plays in equilibrium formation (location shifts).
Keywords: SVM; location shifts; novelites (search for similar items in EconPapers)
JEL-codes: C25 C5 C55 E65 (search for similar items in EconPapers)
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