Dataset Information

Loan maturity aggregation in interbank lending networks obscures mesoscale structure and economic functions.

ABSTRACT: Since the 2007-2009 financial crisis, substantial academic effort has been dedicated to improving our understanding of interbank lending networks (ILNs). Because of data limitations or by choice, the literature largely lacks multiple loan maturities. We employ a complete interbank loan contract dataset to investigate whether maturity details are informative of the network structure. Applying the layered stochastic block model of Peixoto (2015) and other tools from network science on a time series of bilateral loans with multiple maturity layers in the Russian ILN, we find that collapsing all such layers consistently obscures mesoscale structure. The optimal maturity granularity lies between completely collapsing and completely separating the maturity layers and depends on the development phase of the interbank market, with a more developed market requiring more layers for optimal description. Closer inspection of the inferred maturity bins associated with the optimal maturity granularity reveals specific economic functions, from liquidity intermediation to financing. Collapsing a network with multiple underlying maturity layers or extracting one such layer, common in economic research, is therefore not only an incomplete representation of the ILN's mesoscale structure, but also conceals existing economic functions. This holds important insights and opportunities for theoretical and empirical studies on interbank market functioning, contagion, stability, and on the desirable level of regulatory data disclosure.

SUBMITTER: Van Soom M

PROVIDER: S-EPMC6715684 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Loan maturity aggregation in interbank lending networks obscures mesoscale structure and economic functions.

Van Soom Marnix M van den Heuvel Milan M Ryckebusch Jan J Schoors Koen K

Scientific reports 20190829 1

Since the 2007-2009 financial crisis, substantial academic effort has been dedicated to improving our understanding of interbank lending networks (ILNs). Because of data limitations or by choice, the literature largely lacks multiple loan maturities. We employ a complete interbank loan contract dataset to investigate whether maturity details are informative of the network structure. Applying the layered stochastic block model of Peixoto (2015) and other tools from network science on a time serie ...[more]

PMID: 31467301

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Project description:BackgroundThe vision of learning healthcare systems (LHSs) is attractive as a more effective model for health care services, but achieving the vision is complex. There is limited literature describing the processes needed to construct such multicomponent systems or to assess development.MethodsWe used the concept of a capability maturity matrix to describe the maturation of necessary infrastructure and processes to create learning networks (LNs), multisite collaborative LHSs that use an actor-oriented network organizational architecture. We developed a network maturity grid (NMG) assessment tool by incorporating information from literature review, content theory from existing networks, and expert opinion to establish domains and components. We refined the maturity grid in response to feedback from network leadership teams. We followed NMG scores over time for nine LNs and plotted scores for each domain component with respect to SD for one participating network. We sought subjective feedback on the experience of applying the NMG to individual networks.ResultsLN leaders evaluated the scope, depth, and applicability of the NMG to their networks. Qualitative feedback from network leaders indicated that changes in NMG scores over time aligned with leaders' reports about growth in specific domains; changes in scores were consistent with network efforts to improve in various areas. Scores over time showed differences in maturation in the individual domains of each network. Scoring patterns, and SD for domain component scores, indicated consistency among LN leaders in some but not all aspects of network maturity. A case example from a participating network highlighted the value of the NMG in prompting strategic discussions about network development and demonstrated that the process of using the tool was itself valuable.ConclusionsThe capability maturity grid proposed here provides a framework to help those interested in creating Learning Health Networks plan and develop them over time.

Dataset Information

Loan maturity aggregation in interbank lending networks obscures mesoscale structure and economic functions.

Publications

Loan maturity aggregation in interbank lending networks obscures mesoscale structure and economic functions.

Similar Datasets

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