Detecting global financial crises over history: A multivariate nonlinear denoising strategy

Cécile Bastidon (), Patrice Abry (), Pierre Borgnat (), Pablo Jensen, Antoine Parent and Barbara Pascal ()
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Pierre Borgnat: Phys-ENS - Laboratoire de Physique de l'ENS Lyon - ENS de Lyon - École normale supérieure de Lyon - Université de Lyon - Université de Lyon - CNRS - Centre National de la Recherche Scientifique
Pablo Jensen: Phys-ENS - Laboratoire de Physique de l'ENS Lyon - ENS de Lyon - École normale supérieure de Lyon - Université de Lyon - Université de Lyon - CNRS - Centre National de la Recherche Scientifique
Barbara Pascal: LS2N - Laboratoire des Sciences du Numérique de Nantes - Inria - Institut National de Recherche en Informatique et en Automatique - CNRS - Centre National de la Recherche Scientifique - IMT Atlantique - IMT Atlantique - IMT - Institut Mines-Télécom [Paris] - Nantes Univ - ECN - NANTES UNIVERSITÉ - École Centrale de Nantes - Nantes Univ - Nantes Université - Nantes univ - UFR ST - Nantes université - UFR des Sciences et des Techniques - Nantes Université - pôle Sciences et technologie - Nantes Univ - Nantes Université

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Abstract: We propose a 3-step original model-based crisis datation method. The steps consist in 1/ choosing the informational content of the multivariate signal; 2/ segmenting it using a multivariate piecewise linear denoising model from signal theory; 3/ filtering of events identified by the segmentation. Applied to a database of 32 advanced and emerging countries over the period 1960 to today, the method detects all major crises from the expert based reference literature. In addition, it allows to draw a typology based on the strictly global vs. regional systemic diffusion of crises, their effect on global uncertainty.

Date: 2022-07-25
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Published in World Economic History Conference Paris, Jul 2022, Paris, France

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04926362

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