Estimating the impact of supply chain network contagion on financial stability

IF 6.1 2区 经济学 Q1 BUSINESS, FINANCE
Zlata Tabachová , Christian Diem , András Borsos , Csaba Burger , Stefan Thurner
{"title":"Estimating the impact of supply chain network contagion on financial stability","authors":"Zlata Tabachová ,&nbsp;Christian Diem ,&nbsp;András Borsos ,&nbsp;Csaba Burger ,&nbsp;Stefan Thurner","doi":"10.1016/j.jfs.2024.101336","DOIUrl":null,"url":null,"abstract":"<div><div>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 <em>selected</em> 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.</div></div>","PeriodicalId":48027,"journal":{"name":"Journal of Financial Stability","volume":"75 ","pages":"Article 101336"},"PeriodicalIF":6.1000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Financial Stability","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1572308924001219","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0

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.
估算供应链网络传染对金融稳定的影响
现实的信用风险评估,即估算债务人倒闭造成的损失,是维护金融稳定的核心。信用风险模型侧重于借款人的财务状况,对实体经济,特别是供应链的其他风险考虑甚少。最近的大流行病、地缘政治动荡和自然灾害表明,供应链冲击可造成足以威胁金融稳定的巨大金融损失。基于一个独特的全国性微观数据集(其中包含匈牙利所有企业的几乎所有供应链关系及其银行贷款),我们开发了一个多层次冲击传播框架,以估算企业受到的经济冲击如何在供应链网络(SCN)中产生连锁反应,从而导致企业遭受额外的财务损失、更多的贷款违约,进而给银行的股本缓冲带来损失。首先,我们估算了单个企业的金融系统性风险,量化了由供应链网络传染引起的企业自身和所有次级违约贷款造成的预期金融损失。我们发现,有一小部分企业会带来巨大的金融系统性风险,影响银行系统整体权益的 22%(假设违约损失为 100%)。这些损失主要是由 SCN 感染造成的。其次,我们计算了每家银行的预期损失(EL)、风险价值(VaR)和预期亏空(ES),包括 SCN 感染和无 SCN 感染的情况。我们发现,SCN-contagion 将 EL、VaR 和 ES 分别放大了 5.2、6.7 和 4.4 倍。第三,我们展示了如何利用新框架来评估实体经济大幅冲击对金融稳定的风险。我们模拟了 2020 年初由企业级就业数据校准的 COVID-19 激发的冲击所造成的金融损失。我们的模拟结果表明,如果不采取任何干预措施,整个系统的银行股本将遭受 6% 的损失。该框架可用于设计和测试有针对性的政策干预措施,例如,以最佳方式为企业提供足够的流动性支持,以避免其违约。通过向选定的流动性不足(但有偿付能力)的企业提供总额为银行总股本 0.5%的额外流动性支持,可将损失从银行总股本的 6%降至 1%。这些研究结果表明,为了更全面地反映金融稳定性和进行现实的信贷风险评估,需要考虑 SCN 传染。这一现在可以量化的传染渠道对监管机构未来的系统性风险评估具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
7.70
自引率
9.30%
发文量
78
审稿时长
34 days
期刊介绍: The Journal of Financial Stability provides an international forum for rigorous theoretical and empirical macro and micro economic and financial analysis of the causes, management, resolution and preventions of financial crises, including banking, securities market, payments and currency crises. The primary focus is on applied research that would be useful in affecting public policy with respect to financial stability. Thus, the Journal seeks to promote interaction among researchers, policy-makers and practitioners to identify potential risks to financial stability and develop means for preventing, mitigating or managing these risks both within and across countries.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信