Structural Estimation of Time-Varying Spillovers: An Application to International Credit Risk Transmission

Lukas Boeckelmann and Arthur Stalla-Bourdillon

Working papers from Banque de France

Abstract: We propose a novel approach to quantify spillovers on financial markets based on a structural version of the Diebold-Yilmaz framework. Key to our approach is a SVAR-GARCH model that is statistically identified by heteroskedasticity, economically identified by maximum shock contribution and that allows for time-varying forecast error variance decompositions. We analyze credit risk spillovers between EZ sovereign and bank CDS. Methodologically, we find the model to better match economic narratives compared with common spillover approaches and to be more reactive than models relying on rolling window estimations. We find, on average, spillovers to explain 37% of the variation in our sample, amid a strong variation of the latter over time.

Keywords: CDS; spillover; sovereign debt; systemic risk; SVAR; identification by heteroskedasticity (search for similar items in EconPapers)
JEL-codes: C58 G01 G18 G21 (search for similar items in EconPapers)
Pages: 61 pages
Date: 2021
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-ore and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://publications.banque-france.fr/sites/defaul ... /documents/wp798.pdf

Related works:
Working Paper: Structural Estimation of Time-Varying Spillovers:an Application to International Credit Risk Transmission (2021)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bfr:banfra:798

Access Statistics for this paper

More papers in Working papers from Banque de France Banque de France 31 Rue Croix des Petits Champs LABOLOG - 49-1404 75049 PARIS. Contact information at EDIRC.
Bibliographic data for series maintained by Michael brassart ().