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.
Lingua originale | English |
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pagine (da-a) | 72-79 |
Numero di pagine | 8 |
Rivista | Regional Science and Urban Economics |
Volume | 70 |
DOI | |
Stato di pubblicazione | Pubblicato - 2018 |
Keywords
- Network dependence
- Spatial conditional dependence
- Systemic risk
- regional financial contagion