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Quantifying firm-level economic systemic risk from nation-wide supply networks

Crises like COVID-19 exposed the fragility of highly interdependent corporate supply networks and the complex production processes depending on them. However, a quantitative assessment of individual companies’ impact on the networks’ overall production is hitherto non-existent. Based on a unique val...

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Autores principales: Diem, Christian, Borsos, András, Reisch, Tobias, Kertész, János, Thurner, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9092945/
https://www.ncbi.nlm.nih.gov/pubmed/35546595
http://dx.doi.org/10.1038/s41598-022-11522-z
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author Diem, Christian
Borsos, András
Reisch, Tobias
Kertész, János
Thurner, Stefan
author_facet Diem, Christian
Borsos, András
Reisch, Tobias
Kertész, János
Thurner, Stefan
author_sort Diem, Christian
collection PubMed
description Crises like COVID-19 exposed the fragility of highly interdependent corporate supply networks and the complex production processes depending on them. However, a quantitative assessment of individual companies’ impact on the networks’ overall production is hitherto non-existent. Based on a unique value added tax dataset, we construct the firm-level production network of an entire country at an unprecedented granularity and present a novel approach for computing the economic systemic risk (ESR) of all firms within the network. We demonstrate that 0.035% of companies have extraordinarily high ESR, impacting about 23% of the national economic production should any of them default. Firm size cannot explain the ESR of individual companies; their position in the production networks matters substantially. A reliable assessment of ESR seems impossible with aggregated data traditionally used in Input-Output Economics. Our findings indicate that ESR of some extremely risky companies can be reduced by introducing supply chain redundancies and changes in the network topology.
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spelling pubmed-90929452022-05-12 Quantifying firm-level economic systemic risk from nation-wide supply networks Diem, Christian Borsos, András Reisch, Tobias Kertész, János Thurner, Stefan Sci Rep Article Crises like COVID-19 exposed the fragility of highly interdependent corporate supply networks and the complex production processes depending on them. However, a quantitative assessment of individual companies’ impact on the networks’ overall production is hitherto non-existent. Based on a unique value added tax dataset, we construct the firm-level production network of an entire country at an unprecedented granularity and present a novel approach for computing the economic systemic risk (ESR) of all firms within the network. We demonstrate that 0.035% of companies have extraordinarily high ESR, impacting about 23% of the national economic production should any of them default. Firm size cannot explain the ESR of individual companies; their position in the production networks matters substantially. A reliable assessment of ESR seems impossible with aggregated data traditionally used in Input-Output Economics. Our findings indicate that ESR of some extremely risky companies can be reduced by introducing supply chain redundancies and changes in the network topology. Nature Publishing Group UK 2022-05-11 /pmc/articles/PMC9092945/ /pubmed/35546595 http://dx.doi.org/10.1038/s41598-022-11522-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Diem, Christian
Borsos, András
Reisch, Tobias
Kertész, János
Thurner, Stefan
Quantifying firm-level economic systemic risk from nation-wide supply networks
title Quantifying firm-level economic systemic risk from nation-wide supply networks
title_full Quantifying firm-level economic systemic risk from nation-wide supply networks
title_fullStr Quantifying firm-level economic systemic risk from nation-wide supply networks
title_full_unstemmed Quantifying firm-level economic systemic risk from nation-wide supply networks
title_short Quantifying firm-level economic systemic risk from nation-wide supply networks
title_sort quantifying firm-level economic systemic risk from nation-wide supply networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9092945/
https://www.ncbi.nlm.nih.gov/pubmed/35546595
http://dx.doi.org/10.1038/s41598-022-11522-z
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