Structural Correlations in the Italian Overnight Money Market: An Analysis Based on Network Configuration Models

Luu, Duc Thi; Lux, Thomas; Yanovski, Boyan

doi:10.3390/e19060259

Cited by 4 publications

(2 citation statements)

References 45 publications

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“…Even the clustering coefficients, which are often used to analyse the clustering behaviours in complex networks (e.g. see Luu et al (2017) and the literature therein), can explain the third order of the structural correlations among three nodes alone. In contrast, the communicability is able to catch richer information of the direct as well as indirect pathways associated with different orders of the interconnectednesses between nodes.…”

Section: Multilayer Communicabilitymentioning

confidence: 99%

The multilayer architecture of the global input-output network and its properties

Grassi¹,

Bartesaghi²,

Clemente³

et al. 2021

Preprint

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We analyse the multilayer architecture of the global input-output network using sectoral trade data (WIOD, 2016 release). With a focus on the mesoscale structure and related properties, we find that the multilayer analysis that takes into consideration the splitting into industry-based layers is able to catch more peculiar relationships between countries that cannot be detected from the analysis of the single-layer aggregated network. We can identify several large international communities in which some countries trade more intensively in some specific layers. However, interestingly, our results show that these clusters can restructure and evolve over time. In general, not only their internal composition changes, but the centrality rankings of the members inside are also reordered, with the diminishing role of industries from some countries and the growing importance of those from some other countries. These changes in the large international clusters may reflect the outcomes and the dynamics of cooperation as well as competition among industries and among countries in the global input-output network.

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Section: Multilayer Communicabilitymentioning

confidence: 99%

The multilayer architecture of the global input-output network and its properties

Grassi¹,

Bartesaghi²,

Clemente³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Whenever dealing with the models defined within the ERG formalism, this further implies that the structure of the real network Ĝ, proxied by the quantity X, is completely explained by the (topological information encoded into the) imposed constraints. By contrast, if |z| > z th the observed value X( Ĝ) lies outside the chosen confidence interval: the structure of the observed network determining X is not completely explained by the specific constraints imposed, and further model specifications should be used (i.e., additional or more complex constraints) [58,126].…”

Section: Testing Higher-order Patterns Reconstructionmentioning

confidence: 99%

Reconstruction methods for networks: The case of economic and financial systems

et al. 2018

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The study of social, economic and biological systems is often (when not always) limited by the partial information about the structure of the underlying networks. An example of paramount importance is provided by financial systems: information on the interconnections between financial institutions is privacy-protected, dramatically reducing the possibility of correctly estimating crucial systemic properties such as the resilience to the propagation of shocks. The need to compensate for the scarcity of data, while optimally employing the available information, has led to the birth of a research field known as network reconstruction. Since the latter has benefited from the contribution of researchers working in disciplines as different as mathematics, physics and economics, the results achieved so far are still scattered across heterogeneous publications. Most importantly, a systematic comparison of the network reconstruction methods proposed up to now is currently missing. This review aims at providing a unifying framework to present all these studies, mainly focusing on their application to economic and financial networks. 7The problem of missing information. After an initial activity aimed at determining the structure of real-world networks by measuring standard topological quantities, a more theoretical activity was started, aiming at both defining new quantities and devising proper models to explain observations [45,44,52,53,54]. Given the complexity that can arise even from a simple mathematical model based upon graphs, researchers have recently focused on the development of a topological theory: loosely speaking, topological quantities are employed to define statistical models, rather than reproduced from microscopic dynamical rules [55,56,57,58,59].Unfortunately, when moving to the validation of such models a common problem arises: very often, the data available on the real network are either incomplete or imprecise (or both). This problem is particularly evident in the case of economic and financial networks: in this case, data collection suffers from the problem of partial accounting and the presence of disclosure requirements. In order to illustrate the importance of such an issue, let us think of a bipartite, financial network whose node sets represent investors and the investments they do. Although the knowledge of the whole network structure could help regulators to take immediate countermeasures to stop the propagation of financial distress, this information is seldom available (the knowledge of the whole network of investments would pose immense problems of privacy), thus hindering the possibility of providing a realistic estimate of the extent of the contagion. As confirmed by the analysis of the various papers reported in this review, the incompleteness of network instances seems to be unavoidable [60,61]: since addressing the problem of estimating the resilience of financial networks cannot be addressed without knowing the structural details of national and cross-countries interbank networks, inf...

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The multilayer architecture of the global input-output network and its properties

Grassi¹,

Bartesaghi²,

Clemente³

et al. 2022

Journal of Economic Behavior & Organization

View full text Add to dashboard Cite

Structural Correlations in the Italian Overnight Money Market: An Analysis Based on Network Configuration Models

Cited by 4 publications

References 45 publications

The multilayer architecture of the global input-output network and its properties

The multilayer architecture of the global input-output network and its properties

Reconstruction methods for networks: The case of economic and financial systems

The multilayer architecture of the global input-output network and its properties

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