Research on interbank networks and systemic importance is recognising that the web of exposures linking banks’ balance sheets is more complex than the single-layer-of-exposure approach suggests. Authors characterise the main features of the multiplex structure of the network of large European banks.
The recent ﬁnancial crisis brought to the fore the relevance of interconnectedness in general, and in particular in interbank markets. Of critical importance in this context is the identiﬁcation of the key players in the ﬁnancial network. While early contributions on the topic have focused on aggregated exposures, it is now increasingly recognised that the web of reciprocal exposures linking bank balance sheets is more intricate and complex. Interbank networks are better characterised as multiplex networks, featuring connections at multiple levels.
In the present paper, authors analyse the multiplex structure of the network of large European banks, making use of a detailed dataset presenting exposures partitioned according to maturity and instrument type.
They ﬁnd a high level of similarity between the diﬀerent layers (both by instrument and maturity), a core periphery structure which comprises a large core (relative to studies using country-speciﬁc datasets), and positively correlated multiplexity. The results suggest that an institution’s role in the channel of transmission is critical in determining the global importance of such institution, and that the notion of importance may not be related to its traditionally studied core-periphery role. Nevertheless, key forms of non-decomposable (across layers) centrality measures are resilient across layers, indicating that centrality at the layer-level can be robust to the absence of granular data availability.
Authors develop two measures of systemic importance suited to the case in which banks are connected through an arbitrary number of diﬀerent layers. This allows them to compute systemic importance indicators and decompose them into the contributions of the diﬀerent layers, providing a holistic analysis that truly incorporates the multiplex structure of the network (instead of doing separate analyses for the diﬀerent layers and the aggregate network) and is built directly from a consistent accounting representation of the system. Previous literature has justiﬁed the need to use granular data by noting that banks can rank diﬀerently in diﬀerent layers in terms of systemic importance and thereby the focus on a single layer can be misleading.
They conﬁrm that, even when centrality is persistent across layers, there is still important information to be obtained from granular data, in particular if one is able to decompose global systemic importance into layer-speciﬁc contributions. Nevertheless, they also show that when such granular data is not available, simple measures can be a good second best. Authors illustrate their measures with the dataset on exposures between large European banks, delving deeply into issues of interconnectedness across the various layers of an integrated accounting framework. The results suggest that their proposed measures can be useful tools for practical policy analysis.
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