Estimating the impact of supply chain network contagion on financial stability
基于匈牙利企业供应链与银行贷款的微观数据，构建多层冲击传播框架，量化供应链网络传染对银行股权损失的放大效应，并模拟新冠疫情冲击下政策干预的效果。
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.