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Spillover dynamics for systemic risk measurement using spatial financial time series models

Francisco Blasques (), Siem Jan Koopman, Andre Lucas and Julia Schaumburg

VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy from Verein für Socialpolitik / German Economic Association

Abstract: A new model for time-varying spatial dependencies is introduced. It forms an extension to the popular spatial lag model and can be estimated conveniently by maximum likelihood. The spatial dependence parameter is assumed to follow a generalized autoregressive score (GAS) process. The theoretical properties of the model are established and its satisfactory finite sample performance is shown in a small simulation study. In an empirical application, spatial dependencies between nine European sovereign CDS spreads are estimated for the time period from November 2008 until October 2013. The empirical model features a spatial weights matrix constructed from cross-border lending data and regressors including country-specific and Europe-wide risk factors. The estimation results indicate a high, time-varying degree of spatial spillovers in the spread data. A spatial GAS model with t-distributed errors provides the best fit. There is evidence for a downturn in spatial dependence after the Greek default in winter 2012, which can be explained economically by a change in bank regulation.

JEL-codes: C23 C58 G15 (search for similar items in EconPapers)
Date: 2014
New Economics Papers: this item is included in nep-ecm, nep-rmg and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Related works:
Journal Article: Spillover dynamics for systemic risk measurement using spatial financial time series models (2016) Downloads
Working Paper: Spillover Dynamics for Systemic Risk Measurement using Spatial Financial Time Series Models (2014) Downloads
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