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Modeling inter-country spatial financial interactions with Graphical Lasso: An application to sovereign co-risk evaluation

Giuseppe Arbia (), Riccardo Bramante, Silvia Facchinetti and Diego Zappa

Regional Science and Urban Economics, 2018, vol. 70, issue C, 72-79

Abstract: We propose a model to extract significant risk spatial interactions between countries adopting the Graphical Lasso algorithm, used in graph theory to sort out spurious conditional correlations. In this context, the major issue is the definition of the penalization parameter. We propose a search algorithm aimed at the best separation of the variables (expressed in terms of conditional dependence) given an a priori desired partition. The case study focuses on Credit Default Swap (CDS) returns over the period 2009–2017. The proposed algorithm is used to estimate the spatial systemic risk relationship between Peripheral and Core Countries in the Euro Area.

Keywords: Regional financial contagion; Spatial conditional dependence; Systemic risk; Network dependence (search for similar items in EconPapers)
JEL-codes: C13 C51 C61 G01 (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eee:regeco:v:70:y:2018:i:c:p:72-79

DOI: 10.1016/j.regsciurbeco.2018.02.006

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