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Modeling structure and credit risk of the economy: a multilayer bank-firm network approach

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  • Soumen Majhi
  • Anna Mancini
  • Giulio Cimini

Abstract

Assessing the resilience of the economy requires accounting for its intrinsic multi-layer nature, by assessing for instance how disruptions at the firm level spread through the production network and propagate to the banking sector. Methods exist to measure the reverberation of shocks over the multilayer network of supply-customer relations among firms, corporate loans of banks and their interbank market exposures. However, empirical network data are often privacy protected and thus inaccessible to researchers and regulators. In this work we develop an unified framework, combining state-of-the art techniques to reconstruct the whole multilayer structure of the economy from balance sheet information of banks and firms, as well as dynamics of shock propagation from the inter-firm to the interbank layers. We showcase application of our methodology using data of the Italian economy. We identify the most systemically important firms and industries, as well as the most vulnerable banks, further assessing the determinants of systemic risk -- obtaining results coherent with the empirical literature on network contagion. Overall, our framework allows performing detailed network-based stress tests on a digital twin of the economy, without requiring detailed network information that is difficult to acquire.

Suggested Citation

  • Soumen Majhi & Anna Mancini & Giulio Cimini, 2026. "Modeling structure and credit risk of the economy: a multilayer bank-firm network approach," Papers 2603.09854, arXiv.org.
  • Handle: RePEc:arx:papers:2603.09854
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    References listed on IDEAS

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    1. Andras Borsos & Bence Mero, 2020. "Shock Propagation in the Banking System with Real Economy Feedback," MNB Working Papers 2020/6, Magyar Nemzeti Bank (Central Bank of Hungary).
    2. Massimiliano Fessina & Giulio Cimini & Tiziano Squartini & Pablo Astudillo-Est'evez & Stefan Thurner & Diego Garlaschelli, 2024. "Inferring firm-level supply chain networks with realistic systemic risk from industry sector-level data," Papers 2408.02467, arXiv.org.
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