The multilayer structure of corporate networks

Jeude, J A van Lidth de; Aste, Tomaso; Caldarelli, Guido

doi:10.1088/1367-2630/ab022d

Cited by 19 publications

(5 citation statements)

References 30 publications

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“…In particular, we build a multiplex network consisting in a collection of M = 24 layers, one for each GICS sector. While all layers are composed of the same nodes (countries), the connections within each layer are based on the links between countries for the respective industry sector, preserving in this way the sectoral multi-layered nature of the country-to-country interactions [ 71 , 72 ].…”

Section: Methods and Resultsmentioning

confidence: 99%

The structural architecture of international industry networks in the global economy

et al. 2021

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Globalisation continuously produces novel economic relationships mediated by flows of goods, services, capital, and information between countries. The activity of multinational corporations (MNCs) has become a primary driver of globalisation, shaping these relationships through vast networks of firms and their subsidiaries. Extensive empirical research has suggested that globalisation is not a singular process, and that variation in the intensity of international economic interactions can be captured by ‘multiple globalisations’, however how this differs across industry sectors has remained unclear. This paper analyses how sectoral variation in the ‘structural architecture’ of international economic relations can be understood using a combination of social network analysis (SNA) measures based on firm-subsidiary ownership linkages. Applying an approach that combines network-level measures (Density, Clustering, Degree, Assortativity) in ways yet to be explored in the spatial networks literature, a typology of four idealised international network structures is presented to allow for comparison between sectors. All sectoral networks were found to be disassortative, indicating that international networks based on intraorganisational ties are characterised by a core-periphery structure, with professional services sectors such as Banks and Insurance being the most hierarchically differentiated. Retail sector networks, including Food & Staples Retailing, are the least clustered while the two most clustered networks—Materials and Capital Goods—have also the highest average degree, evidence of their extensive globalisations. Our findings suggest that the multiple globalisations characterising international economic interactions can be better understood through the ‘structural architecture’ of sectoral variation, which result from the advantages conferred by cross-border activity within each.

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Section: Methods and Resultsmentioning

confidence: 99%

The structural architecture of international industry networks in the global economy

et al. 2021

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“…The results show that just 0.61% of the top shareholders accumulate 80% of the control over the value of all firms in the network. In the study by Jeude, Aste, and Caldarelli (2019) conducted in February 2018, it is possible to note that the multiplex network of German and British corporations represent different types of corporate control relations: R&D alliances, board interlocking, ownership links, and mutual cross-shareholder. Among the results found by the authors is the relationship between corporate performance and the centrality of these firms in the multiplex network.…”

Section: Corporate Control and Networkmentioning

confidence: 99%

Corporate Ownership Network: The Hierarchical Capitalism in the Brazilian Context

2023

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Several studies have indicated a type of hierarchical capitalism in Latin America, characterized by the presence of multinational and state corporations, diversified multi-enterprise groups, low-skilled labor, and segmented labor markets. From the perspective of ownership networks, we explore who the owners of large Brazilian corporations are. These networks reveal actors and groups with prominent positions in the structure and ownership of companies. Thus, this article proposes to 1) describe the ownership network of the largest Brazilian corporations; 2) analyze the density, average degree, modularity, and the number of components connected in this network; 3) analyze measures of weighted degree centrality, intermediation, and eigenvector; 4) identify and analyze subgroups in the network, and 5) relate the configuration of the ownership network with hierarchical capitalism in the Brazilian context. The results point to prominent positions of financial shareholders, the Brazilian state (state-owned firms), and groups composed mostly of large multinationals, financial firms, families, and state-owned firms, confirming that the ownership structure is strongly linked to these players.

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“…Multiplex networks 76,77 provide a natural framework to describe such relationships and first empirical studies have shown that different layers are not structurally similar. Examples include: credit and liquidity exposures in the UK interbank market 78 , payments and exposures in the Mexican banking system 60 , the Mexican interbank market 79 , the Italian interbank market 80 , Colombian financial institutions and market infrastructures 81 , the EU derivatives market 28 , the UK interest rate, foreign exchange, and credit derivatives market 47 , corporate networks 82 . Several works have focused on financial contagion on multiplex networks, see Section 3.3.…”

Section: Multiplex and Higher-order Networkmentioning

confidence: 99%

The physics of financial networks

et al. 2021

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As the total value of the global financial market outgrew the value of the real economy, financial institutions created a global web of interactions that embodies systemic risks. Understanding these networks requires new theoretical approaches and new tools for quantitative analysis. Statistical physics contributed significantly to this challenge by developing new metrics and models for the study of financial network structure, dynamics, and stability and instability. In this Review, we introduce network representations originating from different financial relationships, including direct interactions such as loans, similarities such as co-ownership and higher-order relations such as contracts involving several parties (for example, credit default swaps) or multilayer connections (possibly extending to the real economy). We then review models of financial contagion capturing the diffusion and impact of shocks across each of these systems. We also discuss different notions of 'equilibrium' in economics and statistical physics, and how they lead to maximum entropy ensembles of graphs, providing tools for financial network inference and the identification of early-warning signals of system-wide instabilities.

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The multilayer structure of corporate networks

Cited by 19 publications

References 30 publications

The structural architecture of international industry networks in the global economy

The structural architecture of international industry networks in the global economy

Corporate Ownership Network: The Hierarchical Capitalism in the Brazilian Context

The physics of financial networks

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