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Quantifying firm-level economic systemic risk from nation-wide supply networks.
Diem, Christian; Borsos, András; Reisch, Tobias; Kertész, János; Thurner, Stefan.
  • Diem C; Complexity Science Hub Vienna, Josefstädter Strasse 39, 1080, Vienna, Austria.
  • Borsos A; Institute for Finance, Banking and Insurance, Vienna University of Economics and Business, Welthandelsplatz 1, 1020, Vienna, Austria.
  • Reisch T; Complexity Science Hub Vienna, Josefstädter Strasse 39, 1080, Vienna, Austria.
  • Kertész J; Financial Systems Analysis, Central Bank of Hungary, Szabadság tér 9, Budapest, 1054, Hungary.
  • Thurner S; Department of Network and Data Science, Central European University, Quellenstrasse 51, 1100, Vienna, Austria.
Sci Rep ; 12(1): 7719, 2022 05 11.
Article in English | MEDLINE | ID: covidwho-1947421
ABSTRACT
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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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-022-11522-z

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-022-11522-z