{
  "title": "Systemic Risk Modeling: How Theory Can Meet Statistics",
  "publication": "IMF Working Papers, March 13, 2020",
  "sourceUrl": "https://www.imf.org/en/publications/wp/issues/2020/03/13/systemic-risk-modeling-how-theory-can-meet-statistics-49244",
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  "summary": "We propose a framework to link empirical models of systemic risk to theoretical network/ general equilibrium models used to understand the channels of transmission of systemic risk.",
  "sections": [
    {
      "heading": "Main contribution",
      "content": "- Proposes a framework to link empirical models of systemic risk to theoretical network/general equilibrium models used to understand channels of transmission of systemic risk.\n- Uses empirical “cross-sectional\" moments to re-calibrate a theoretical model and estimate the importance of a “Minsky\" cycle of optimism in driving systemic risk."
    },
    {
      "heading": "Theoretical model components",
      "content": "- Allows for systemic risk arising from:\n  - interbank counterparty risk,\n  - common asset exposures / fire sales,\n  - a “Minsky\" cycle of optimism."
    },
    {
      "heading": "Empirical model and methodology",
      "content": "- Uses stock market and CDS spreads data to:\n  - estimate a multivariate density of equity returns,\n  - compute the expected equity return for each bank, conditional on a bad macro-outcome.\n- The empirical “cross-sectional\" moments derived from these estimates are used to re-calibrate the theoretical model."
    },
    {
      "heading": "Key findings and focal estimation objective",
      "content": "- The framework is designed to estimate the importance of the Minsky cycle of optimism in driving systemic risk by reconciling empirical cross-sectional moments with theoretical model implications.\n\n---\n\n Content in this bundle\n\n- Working Paper\n  - Working Paper (Markdown version){rel=\"alternate\" type=\"text/markdown\"}\n  - Working Paper (PDF){rel=\"external\" type=\"application/pdf\"}\n\n---\n\nSource: https://www.imf.org/en/publications/wp/issues/2020/03/13/systemic-risk-modeling-how-theory-can-meet-statistics-49244"
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    "Authors: Raphael A Espinoza, Miguel A. Segoviano, Ji Yan",
    "Published: March 13, 2020",
    "Series: IMF Working Papers",
    "DOI: https://doi.org/10.5089/9781513536170.001",
    "Proposes a framework to link empirical models of systemic risk to theoretical network/general equilibrium models used to understand channels of transmission of systemic risk.",
    "Uses empirical “cross-sectional\" moments to re-calibrate a theoretical model and estimate the importance of a “Minsky\" cycle of optimism in driving systemic risk.",
    "Allows for systemic risk arising from:",
    "Uses stock market and CDS spreads data to:",
    "The empirical “cross-sectional\" moments derived from these estimates are used to re-calibrate the theoretical model.",
    "The framework is designed to estimate the importance of the Minsky cycle of optimism in driving systemic risk by reconciling empirical cross-sectional moments with theoretical model implications.",
    "**Working Paper**"
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