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

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.

SUBMITTER: Diem C

PROVIDER: S-EPMC9092945 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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

Diem Christian C Borsos András A Reisch Tobias T Kertész János J Thurner Stefan S

Scientific reports 20220511 1

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 ...[more]

PMID: 35546595

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Project description:The digital transformation of firms plays an increasingly important role in the economy and society. However, limited access to data on firm-level digital intensity is an impediment to advancement of multiple research projects concerned with firm digitalization. To alleviate this challenge, this paper proposes a method for estimating firm-level digital intensity based on other more readily available firm-level data and reference data on digitalization, which is available on sector-level. The proposed method utilizes firm-level revenue breakdown by sector to estimate sector revenue-weighted digital intensity scores, which lead to classification of firms into low, medium and high digital intensity groups. The output from the proposed method can be directly used in research concerned with firm digitalization and investigating this multifaceted phenomenon. Results from the application of the proposed method to an illustrative sample of large US and non-US firms (2000 observations in total) indicate that firm-level digital intensity can be efficiently estimated for large samples using data commonly available to researchers. The key differences between the proposed method and alternative methods are:•Recognition of the fact that firms might participate in more than one sector or industry, which partially explains within-sector heterogeneity in firm-level digital intensity. We found that 67.8% of large US firms and 78.6% of large non-US firms were engaged in more than one industry.•Use of reference sector-level digital intensity scores, which allows for rapid update, application across geographies and time, as well as parallel calculation of multiple digital intensity scores for each reference data. Furthermore, use of reference data enables supplementation of firm-level data on digitalization.•Replicability of the method and reproducibility of the results through inclusion of the source code and availability of data through research and commercial databases.

Project description:BACKGROUND:Study of the medico economic impact of enhanced rehabilitation after surgery (ERAS), by comparing the cost of patient care with or without ERAS, both from the point of view of the hospitals and the Social Security Health Insurance Program. METHODS:Retrospective longitudinal study on matched data from March 1, 2019 to December 31, 2019. The data are extracted from the French prospective payment system. We studied 12 of the most commonly performed in ERAS business segments. The primary outcome was the reduction of the average length of hospital stay and its implications on production costs and excess capacity. We also studied the impact on hospital incomes and Social Security Insurance Program expenses. The potential gain in hospital days was computed by comparing the length of stay of ERAS and non-ERAS cases. The cost reduction was estimated using the mean number of avoidable days of hospitalization, and the mean cost of the stays obtained from the national cost study. Finally, we studied an approximation of the additional expense for the Social Security Health Insurance Program on costs standardized by applying public sector rates. RESULTS:The average length of stay reduction attributed to ERAS is 1.45 (CI 95% 1.42 to 1.48) day per stay, translating to a cost reduction for the hospitals of € 1060 (CI 95% 995 to 1125) per patient and a total of €65 million (CI 95% 61 to 69). At the same time, the additional expenses for the Social Security Insurance Program can conservatively be approximated to € 1.6 million, breaking into a € 2.2 million increase partially compensated by cost savings of € 0.6 million over subsequent stays for complications. Overall, for each percent of additional ERAS activity over the scope of the study, the marginal cost reduction for the hospitals can be estimated to € 1.8 million (CI 95% 1.7 million to 2.0 million). CONCLUSIONS:Associated with previously known clinical benefits for the patients, these convincing results in terms of economic gain strongly support expanding the adoption of ERAS.

Dataset Information

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

Publications

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

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