Munich Personal RePEc Archive

Describing Location Shifts with One Class Support Vector Machines

igescu, iulia (2020): Describing Location Shifts with One Class Support Vector Machines.

[img]
Preview
PDF
MPRA_paper_100984.pdf

Download (1MB) | Preview

Abstract

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).

Logo of the University Library LMU Munich
MPRA is a RePEc service hosted by
the University Library LMU Munich in Germany.