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

61 Pages Posted: 21 Apr 2021

Date Written: December 2020

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 SVARGARCH 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

JEL Classification: C58, G01, G18, G21

Suggested Citation

Lukas, Boeckelmann and Stalla-Bourdillon, Arthur, Structural Estimation of Time-Varying Spillovers: an Application to International Credit Risk Transmission (December 2020). Banque de France Working Paper No. 798, Available at SSRN: https://ssrn.com/abstract=3827913 or http://dx.doi.org/10.2139/ssrn.3827913

Boeckelmann Lukas (Contact Author)

Banque de France ( email )

Paris
France

Arthur Stalla-Bourdillon

Banque de France

Paris
France

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