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- W3120656018 abstract "In 2018 a process change in the industry sector initiated at the “center” (West Europe) induced internal spillover effects at the end of the value chain (Romania) and propagated further affecting the “center” with a lag. Classical econometrics deals poorly with circular change. Support Vector Machines (SVM) can deal with that. As it can quantify small movements in “animal spirit” (coming from survey data) as novelties, that way it can monitor equilibrium changes (location shifts) ahead of hard indicators (industrial production index). This is a positive side of “animal spirit.” Confronted with a Rare Event, an unexpected change like that of the Virus Crisis in 2020, the same survey data produce outliers. “Animal spirit” shows its negative side as irrational behavior." @default.
- W3120656018 created "2021-01-18" @default.
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- W3120656018 date "2020-01-01" @default.
- W3120656018 modified "2023-09-24" @default.
- W3120656018 title "The Role of Animal Spirit in Monitoring Location Shifts with SVM:Novelties Versus Outliers" @default.
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- W3120656018 doi "https://doi.org/10.1007/978-3-030-64583-0_8" @default.
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