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Does the default pecking order impact systemic risk? Evidence from Brazilian data

Michel Alexandre, Thiago Silva, Krzysztof Michalak and Francisco Aparecido Rodrigues

European Journal of Operational Research, 2023, vol. 309, issue 3, 1379-1391

Abstract: The DebtRank approach is a popular metric used to estimate systemic risk in network models. It assumes that the loss distribution of a distressed debtor among its creditors follows a pro-rata fashion, proportional to the loan granted to the debtor. However, the banking literature documents that the loss distribution can be heterogeneous across different creditors. In this study, we extend the DebtRank framework assuming a heterogeneous pattern of the loss distribution, inspired by the default pecking order. Grounded on the empirical literature, we assume distressed debtors employ some criterion (equity, equity-to-assets ratio, out-degree, or loan extended) to rank the creditors they are willing to default on first. Applying this framework to an extensive Brazilian data set, we find that the systemic risk is sensitive to the heuristic adopted for the default pecking order, with the pro-rata pattern serving as a lower bound. We can interpret this result in light of the dual role of financial networks, which can serve as a conduit for both risk-sharing and shock propagation. DPO may affect the balance between these two effects. We find empirical evidence corroborating this hypothesis by assessing the role of interconnectedness (as measured by the network density) in driving systemic risk. When losses are mostly transmitted to the more fragile creditors, the density positively affects systemic risk. In this instance, the financial network serves primarily as a channel for shock propagation rather than risk-sharing.

Keywords: Finance; Systemic risk; Default pecking order; Complex networks (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1016/j.ejor.2023.01.043

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