Estimating the impact of supply chain network contagion on financial stability

Realistic credit risk assessment, the estimation of losses due to a debtors failure, is central for maintaining financial stability. Credit risk models focus on the financial conditions of borrowers and only marginally consider other risks from the real economy, supply chains in particular. Recent pandemics, geopolitical instabilities, and natural disasters demonstrated that supply chain shocks can contribute to financial losses large enough to threaten financial stability. Based on a unique nation-wide micro-dataset, containing practically all supply chain relations of all Hungarian firms, together with their bank loans, we develop a multi-layer shock propagation framework to estimate how economic shocks to firms cascade in the supply chain network (SCN), leading to additional financial losses to firms, additional defaults of loans and, hence, losses to banks’ equity buffers. First, we estimate the financial systemic risk of individual firms, by quantifying the expected financial losses caused by a firm’s own- and all the secondary defaulting loans caused by supply chain network contagion. We find a small fraction of firms carrying substantial financial systemic risk, affecting up to 22% of the banking system’s overall equity (assuming a loss given default of 100%). These losses are predominantly caused by SCN-contagion. Second, we calculate for every bank the expected loss (EL), value at risk (VaR) and expected shortfall (ES), with and without SCN-contagion. We find that SCN-contagion amplifies EL, VaR, and ES by a factor of 5.2, 6.7 and 4.4, respectively. Third, we showcase how the new framework can be used to assess the risks of a large real economy shock for financial stability. We simulate the financial losses from a COVID-19 inspired shock calibrated from firm-level employment data in the beginning of 2020. Our simulations show that without any interventions, system-wide bank equity would suffer losses of 6%. The framework can be used to design and test targeted policy interventions, e.g., optimally providing firms with enough liquidity-support to avert their default. By supporting selected illiquid (yet solvent) firms with additional liquidity totalling 0.5% of overall bank equity, the losses can be reduced from 6% to 1% of overall bank equity. These findings indicate that for a more complete picture of financial stability and realistic credit risk assessment, SCN contagion needs to be considered. This now quantifiable contagion channel is of relevance for future systemic risk assessments of regulators.

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Publication Details

Journal
Journal of Financial Stability
Published
2024-10-18
DOI
https://doi.org/10.1016/j.jfs.2024.101336
Citations
15
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
8.32

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article

Estimating the impact of supply chain network contagion on financial stability

Csaba Burger, Stefan Thurner, Christian Diem, András Borsos et al.
15 citations
Journal of Financial Stability
Supply Chain Resilience and Risk Management
8.32
article

Estimating the impact of supply chain network contagion on financial stability

Csaba Burger, Stefan Thurner, Christian Diem, András Borsos, Zlata Tabachová
article en
15 citations

Abstract

Realistic credit risk assessment, the estimation of losses due to a debtors failure, is central for maintaining financial stability. Credit risk models focus on the financial conditions of borrowers and only marginally consider other risks from the real economy, supply chains in particular. Recent pandemics, geopolitical instabilities, and natural disasters demonstrated that supply chain shocks can contribute to financial losses large enough to threaten financial stability. Based on a unique nation-wide micro-dataset, containing practically all supply chain relations of all Hungarian firms, together with their bank loans, we develop a multi-layer shock propagation framework to estimate how economic shocks to firms cascade in the supply chain network (SCN), leading to additional financial losses to firms, additional defaults of loans and, hence, losses to banks’ equity buffers. First, we estimate the financial systemic risk of individual firms, by quantifying the expected financial losses caused by a firm’s own- and all the secondary defaulting loans caused by supply chain network contagion. We find a small fraction of firms carrying substantial financial systemic risk, affecting up to 22% of the banking system’s overall equity (assuming a loss given default of 100%). These losses are predominantly caused by SCN-contagion. Second, we calculate for every bank the expected loss (EL), value at risk (VaR) and expected shortfall (ES), with and without SCN-contagion. We find that SCN-contagion amplifies EL, VaR, and ES by a factor of 5.2, 6.7 and 4.4, respectively. Third, we showcase how the new framework can be used to assess the risks of a large real economy shock for financial stability. We simulate the financial losses from a COVID-19 inspired shock calibrated from firm-level employment data in the beginning of 2020. Our simulations show that without any interventions, system-wide bank equity would suffer losses of 6%. The framework can be used to design and test targeted policy interventions, e.g., optimally providing firms with enough liquidity-support to avert their default. By supporting selected illiquid (yet solvent) firms with additional liquidity totalling 0.5% of overall bank equity, the losses can be reduced from 6% to 1% of overall bank equity. These findings indicate that for a more complete picture of financial stability and realistic credit risk assessment, SCN contagion needs to be considered. This now quantifiable contagion channel is of relevance for future systemic risk assessments of regulators.

Journal of Financial StabilityVol. 75
Vienna University of Economics and Business (AT), Santa Fe Institute (US), Hungarian National Bank (HU), Complexity Science Hub (AT), Medical University of Vienna (AT)
Bundesministerium für Klimaschutz, Umwelt, Energie, Mobilität, Innovation und Technologie, Oesterreichische Nationalbank
Openalex Percentile: Top 3%
Supply Chain Resilience and Risk Management
8.32
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