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When Banks Punch Back: Macrofinancial Feedback Loops in Stress Tests

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  • Mr. Mario Catalan
  • Alexander W. Hoffmaister

Abstract

In the presence of adverse macroeconomic shocks, simultaneous capital losses in multiple banks can prompt them to contract their balance sheets. These bank responses generate externalities that propagate in the form of macro-financial feedback loops. This paper develops a credit response and externalities analysis model (CREAM) that integrates a disaggregated banking sector into an otherwise standard macroeconomic structural vector autoregressive model. It shows that accounting for macro-financial feedback loops can significantly affect macroeconomic outcomes and bank-specific stress tests results. The heterogeneity in bank lending responses matters: it determines how each bank fares under adverse conditions and the external effects that banks impose on each other and on economic activity. The model can thus be used to assess the contributions of individual banks to systemic risk along the time dimension.

Suggested Citation

  • Mr. Mario Catalan & Alexander W. Hoffmaister, 2020. "When Banks Punch Back: Macrofinancial Feedback Loops in Stress Tests," IMF Working Papers 2020/072, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:2020/072
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    Cited by:

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    3. Uquillas, Adriana & Tonato, Ronny, 2022. "Inter-portfolio credit risk contagion including macroeconomic and financial factors: A case study for Ecuador," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 299-320.
    4. Morell, Joe & Rice, Jonathan & Shaw, Frances, 2022. "A Framework for Macroprudential Stress Testing," Research Technical Papers 7/RT/22, Central Bank of Ireland.
    5. David Aikman & Daniel Beale & Adam Brinley-Codd & Anne-Caroline Hüser & Giovanni Covi & Caterina Lepore, 2023. "Macro-Prudential Stress Test Models: A Survey," IMF Working Papers 2023/173, International Monetary Fund.
    6. Darné, Olivier & Levy-Rueff, Guy & Pop, Adrian, 2024. "The calibration of initial shocks in bank stress test scenarios: An outlier detection based approach," Economic Modelling, Elsevier, vol. 136(C).
    7. Wang, Gang-Jin & Chen, Yan & Zhu, You & Xie, Chi, 2024. "Systemic risk prediction using machine learning: Does network connectedness help prediction?," International Review of Financial Analysis, Elsevier, vol. 93(C).

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    More about this item

    Keywords

    WP; balance sheet; bank; bank lending; lending rate; risk weight; real GDP; stress tests result; credit expansion; yield curve; bank capitalization ratios; loan portfolio; bank loss; bank externality; bank profit and loss; Loans; Bank credit; Capital adequacy requirements; Financial statements; Yield curve; Global; Stress tests; macroeconomic shocks; banking sector; modeling; vulnerability ranking; quasi-static behavior; funding cost; bank profit; aggregate bank result;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • G01 - Financial Economics - - General - - - Financial Crises
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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