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  1. Article ; Online: Estimating the loss of economic predictability from aggregating firm-level production networks.

    Diem, Christian / Borsos, András / Reisch, Tobias / Kertész, János / Thurner, Stefan

    PNAS nexus

    2024  Volume 3, Issue 3, Page(s) pgae064

    Abstract: To estimate the reaction of economies to political interventions or external disturbances, input-output (IO) tables-constructed by aggregating data into industrial sectors-are extensively used. However, economic growth, robustness, and resilience ... ...

    Abstract To estimate the reaction of economies to political interventions or external disturbances, input-output (IO) tables-constructed by aggregating data into industrial sectors-are extensively used. However, economic growth, robustness, and resilience crucially depend on the detailed structure of nonaggregated firm-level production networks (FPNs). Due to nonavailability of data, little is known about how much aggregated sector-based and detailed firm-level-based model predictions differ. Using a nearly complete nationwide FPN, containing 243,399 Hungarian firms with 1,104,141 supplier-buyer relations, we self-consistently compare production losses on the aggregated industry-level production network (IPN) and the granular FPN. For this, we model the propagation of shocks of the same size on both, the IPN and FPN, where the latter captures relevant heterogeneities within industries. In a COVID-19 inspired scenario, we model the shock based on detailed firm-level data during the early pandemic. We find that using IPNs instead of FPNs leads to an underestimation of economic losses of up to 37%, demonstrating a natural limitation of industry-level IO models in predicting economic outcomes. We ascribe the large discrepancy to the significant heterogeneity of firms within industries: we find that firms within one sector only sell 23.5% to and buy 19.3% from the same industries on average, emphasizing the strong limitations of industrial sectors for representing the firms they include. Similar error levels are expected when estimating economic growth, CO
    Language English
    Publishing date 2024-02-17
    Publishing country England
    Document type Journal Article
    ISSN 2752-6542
    ISSN (online) 2752-6542
    DOI 10.1093/pnasnexus/pgae064
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Inequality in economic shock exposures across the global firm-level supply network.

    Chakraborty, Abhijit / Reisch, Tobias / Diem, Christian / Astudillo-Estévez, Pablo / Thurner, Stefan

    Nature communications

    2024  Volume 15, Issue 1, Page(s) 3348

    Abstract: For centuries, national economies have been engaging in international trade and production. The resulting international supply networks not only increase wealth for countries, but also allow for economic shocks to propagate across borders. Using global, ... ...

    Abstract For centuries, national economies have been engaging in international trade and production. The resulting international supply networks not only increase wealth for countries, but also allow for economic shocks to propagate across borders. Using global, firm-level supply network data, we estimate a country's exposure to direct and indirect economic losses caused by the failure of a company in another country. We show the network of international systemic risk-flows. We find that rich countries expose poor countries stronger to systemic risk than vice-versa. The risk is highly concentrated, however, higher risk levels are not compensated with a risk premium in GDP levels, nor higher GDP growth. Our findings put the often praised benefits for developing countries from globalized production in a new light, by relating them to risks involved in the production processes. Exposure risks present a new dimension of global inequality that most affects the poor in supply shock crises.
    Language English
    Publishing date 2024-04-18
    Publishing country England
    Document type Journal Article
    ZDB-ID 2553671-0
    ISSN 2041-1723 ; 2041-1723
    ISSN (online) 2041-1723
    ISSN 2041-1723
    DOI 10.1038/s41467-024-46126-w
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Quantifying firm-level economic systemic risk from nation-wide supply networks.

    Diem, Christian / Borsos, András / Reisch, Tobias / Kertész, János / Thurner, Stefan

    Scientific reports

    2022  Volume 12, Issue 1, Page(s) 7719

    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 ... ...

    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.
    MeSH term(s) COVID-19/epidemiology ; Humans
    Language English
    Publishing date 2022-05-11
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-022-11522-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Monitoring supply networks from mobile phone data for estimating the systemic risk of an economy.

    Reisch, Tobias / Heiler, Georg / Diem, Christian / Klimek, Peter / Thurner, Stefan

    Scientific reports

    2022  Volume 12, Issue 1, Page(s) 13347

    Abstract: Remarkably little is known about the structure, formation, and dynamics of supply- and production networks that form one foundation of society. Neither the resilience of these networks is known, nor do we have ways to systematically monitor their ongoing ...

    Abstract Remarkably little is known about the structure, formation, and dynamics of supply- and production networks that form one foundation of society. Neither the resilience of these networks is known, nor do we have ways to systematically monitor their ongoing change. Systemic risk contributions of individual companies were hitherto not quantifiable since data on supply networks on the firm-level do not exist with the exception of a very few countries. Here we use telecommunication meta data to reconstruct nationwide firm-level supply networks in almost real-time. We find the probability of observing a supply-link, given the existence of a strong communication-link between two companies, to be about 90%. The so reconstructed supply networks allow us to reliably quantify the systemic risk of individual companies and thus obtain an estimate for a country's economic resilience. We identify about 65 companies, from a broad range of company sizes and from 22 different industry sectors, that could potentially cause massive damages. The method can be used for objectively monitoring change in production processes which might become essential during the green transition.
    MeSH term(s) Cell Phone ; Data Collection ; Industry
    Language English
    Publishing date 2022-08-03
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-022-13104-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Book ; Online: Using firm-level production networks to identify decarbonization strategies that minimize social stress

    Stangl, Johannes / Borsos, András / Diem, Christian / Reisch, Tobias / Thurner, Stefan

    2023  

    Abstract: A rapid decarbonization of the economy requires a massive reconfiguration of its underlying production networks. To reduce emissions significantly, many firms need to change production processes, which has major impacts on practically all supply chains. ... ...

    Abstract A rapid decarbonization of the economy requires a massive reconfiguration of its underlying production networks. To reduce emissions significantly, many firms need to change production processes, which has major impacts on practically all supply chains. This restructuring process might cause considerable social distress, e.g. in the form of unemployment, if companies have to close down. Here, we use a unique dataset of the entire firm-level production network of a European economy and develop a network-theory-based measure to estimate the systemic social relevance of every single firm. It enables us to estimate the expected direct and indirect job losses in the supply chain triggered by every firm's default. For the largest CO2 emitting firms we link this measure of social relevance to their emissions. We identify firms with low social relevance and high emissions as potential decarbonization leverage points. We compare various decarbonization strategies by simultaneously capturing the social and environmental impact under the assumption that specific sets of firms would no longer produce. We find that a strategy based on the identified decarbonization leverage points could lead to a 20% reduction of CO2 emissions while putting 2% of jobs at risk. In contrast, targeting the largest emitters first, without considering their social relevance, results in 33% of jobs being at risk for comparable emission savings. Our results indicate that supply-chain sensitive CO2 taxation might reduce the social costs of the green transition considerably.
    Keywords Economics - General Economics ; Physics - Physics and Society
    Subject code 338
    Publishing date 2023-02-17
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Book ; Online: Inferring supply networks from mobile phone data to estimate the resilience of a national economy

    Reisch, Tobias / Heiler, Georg / Diem, Christian / Thurner, Stefan

    2021  

    Abstract: National economies rest on networks of millions of customer-supplier relations. Some companies -- in the case of their default -- can trigger significant cascades of shock in the supply-chain network and are thus systemically risky. Up to now, systemic ... ...

    Abstract National economies rest on networks of millions of customer-supplier relations. Some companies -- in the case of their default -- can trigger significant cascades of shock in the supply-chain network and are thus systemically risky. Up to now, systemic risk of individual companies was practically not quantifiable, due to the unavailability of firm-level transaction data. So far, economic shocks are typically studied in the framework of input-output analysis on the industry-level that can't relate risk to individual firms. Exact firm-level supply networks based on tax or payment data exist only for very few countries. Here we explore to what extent telecommunication data can be used as an inexpensive, easily available, and real-time alternative to reconstruct national supply networks on the firm-level. We find that the conditional probability of correctly identifying a true customer-supplier link -- given a communication link exists -- is about 90%. This quality level allows us to reliably estimate a systemic risk profile of an entire country that serves as a proxy for the resilience of its economy. In particular, we are able to identify the high systemic risk companies. We find that 65 firms have the potential to trigger large cascades of disruption in production chains that could cause severe damages in the economy. We verify that the topological features of the inter-firm communication network are highly similar to national production networks with exact firm-level interactions.

    Comment: 19 pages, 11 figures
    Keywords Economics - General Economics ; Physics - Physics and Society
    Subject code 338
    Publishing date 2021-10-11
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

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  7. Book ; Online: Quantifying firm-level economic systemic risk from nation-wide supply networks

    Diem, Christian / Borsos, András / Reisch, Tobias / Kertész, János / Thurner, Stefan

    2021  

    Abstract: Crises like COVID-19 or the Japanese earthquake in 2011 exposed the fragility of corporate supply networks. The production of goods and services is a highly interdependent process and can be severely impacted by the default of critical suppliers or ... ...

    Abstract Crises like COVID-19 or the Japanese earthquake in 2011 exposed the fragility of corporate supply networks. The production of goods and services is a highly interdependent process and can be severely impacted by the default of critical suppliers or customers. While knowing the impact of individual companies on national economies is a prerequisite for efficient risk management, the quantitative assessment of the involved economic systemic risks (ESR) is hitherto practically non-existent, mainly because of a lack of fine-grained data in combination with coherent methods. Based on a unique value added tax dataset we derive the detailed production network of an entire country and present a novel approach for computing the ESR of all individual firms. We demonstrate that a tiny fraction (0.035%) of companies has extraordinarily high systemic risk impacting about 23% of the national economic production should any of them default. Firm size alone cannot explain the ESR of individual companies; their position in the production networks does matter substantially. If companies are ranked according to their economic systemic risk index (ESRI), firms with a rank above a characteristic value have very similar ESRI values, while for the rest the rank distribution of ESRI decays slowly as a power-law; 99.8% of all companies have an impact on less than 1% of the economy. We show that the assessment of ESR is impossible with aggregate data as used in traditional Input-Output Economics. We discuss how simple policies of introducing supply chain redundancies can reduce ESR of some extremely risky companies.
    Keywords Economics - General Economics ; Computer Science - Social and Information Networks ; Physics - Physics and Society ; Quantitative Finance - Statistical Finance
    Subject code 338 ; 330
    Publishing date 2021-04-15
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

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  8. Article ; Online: Building an alliance to map global supply networks.

    Pichler, Anton / Diem, Christian / Brintrup, Alexandra / Lafond, François / Magerman, Glenn / Buiten, Gert / Choi, Thomas Y / Carvalho, Vasco M / Farmer, J Doyne / Thurner, Stefan

    Science (New York, N.Y.)

    2023  Volume 382, Issue 6668, Page(s) 270–272

    Abstract: New firm-level data can inform policy-making. ...

    Abstract New firm-level data can inform policy-making.
    Language English
    Publishing date 2023-10-19
    Publishing country United States
    Document type Journal Article
    ZDB-ID 128410-1
    ISSN 1095-9203 ; 0036-8075
    ISSN (online) 1095-9203
    ISSN 0036-8075
    DOI 10.1126/science.adi7521
    Database MEDical Literature Analysis and Retrieval System OnLINE

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