Estimating the impact of supply chain network contagion on financial stability

TL;DR

This paper quantifies how supply chain network contagion significantly amplifies financial risks and losses in the banking system, emphasizing the importance of including supply chain shocks in credit risk models for better financial stability assessment.

Contribution

It introduces a novel systemic risk index based on supply chain contagion, using comprehensive Hungarian firm data, highlighting the impact on financial stability and risk measurement.

Findings

Supply chain shocks can cause up to 16% of banking equity losses.

Contagion amplifies expected loss, VaR, and ES by factors of 4.3, 4.5, and 3.2.

A small fraction of firms carry substantial systemic risk.

Abstract

Realistic credit risk assessment, the estimation of losses from counterparty's failure, is central for the 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 do contribute to large financial losses. Based on a unique nation-wide micro-dataset, containing practically all supply chain relations of all Hungarian firms, together with their bank loans, we estimate how firm-failures affect the supply chain network, leading to potentially additional firm defaults and additional financial losses. Within a multi-layer network framework we define a financial systemic risk index (FSRI) for every firm, quantifying these expected financial losses caused by its own- and all the secondary defaulting loans caused by supply chain network (SCN) shock propagation. We find a small fraction of firms carrying substantial financial systemic risk, affecting up to 16% of the banking system's overall equity. These losses are predominantly caused by SCN contagion. For every bank we calculate the expected loss (EL), value at risk (VaR) and expected shortfall (ES), with and without accounting for SCN contagion. We find that SCN contagion amplifies the EL, VaR, and ES by a factor of 4.3, 4.5, and 3.2, respectively. These findings indicate that for a more complete picture of financial stability and realistic credit risk assessment, SCN contagion needs to be considered. This newly quantified contagion channel is of potential relevance for regulators' future systemic risk assessments.