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How severe are the EBA macroeconomic scenarios for the Italian Economy? A joint probability approach

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  • Bonucchi, Manuel
  • Catalano, Michele

Abstract

Measures of the severity of macroeconomic scenarios have been widely used in the literature, but a consistent methodology for their calculation has not been developed yet. Against this background, we provide a general method for calculating the joint probability of observing a macroeconomic scenario, which can be applied to various structural models. By doing so, we can attach probabilities to scenarios produced with multidimensional economic models to compare their severity and plausibility. We apply our methodology to the 2016 and 2018 EBA stress test scenarios and also provide reverse stress test applications. Our results show that for the Italian economy, the 2016 and 2018 EBA scenarios are unlikely, especially the 2016 one. The reverse stress tests allow us to identify the key variables that affect our probabilities.

Suggested Citation

  • Bonucchi, Manuel & Catalano, Michele, 2022. "How severe are the EBA macroeconomic scenarios for the Italian Economy? A joint probability approach," Journal of International Money and Finance, Elsevier, vol. 129(C).
    • Handle: RePEc:eee:jimfin:v:129:y:2022:i:c:s0261560622001383
    DOI: 10.1016/j.jimonfin.2022.102735
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    References listed on IDEAS

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    1. Thomas Breuer & Martin Summer, 2018. "Systematic Systemic Stress Tests," Working Papers 225, Oesterreichische Nationalbank (Austrian Central Bank).
    2. Borio, Claudio & Drehmann, Mathias & Tsatsaronis, Kostas, 2014. "Stress-testing macro stress testing: Does it live up to expectations?," Journal of Financial Stability, Elsevier, vol. 12(C), pages 3-15.
    3. Kanas, Angelos & Molyneux, Philip, 2018. "Macro stress testing the U.S. banking system," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 54(C), pages 204-227.
    4. Paul Glasserman & Chulmin Kang & Wanmo Kang, 2015. "Stress scenario selection by empirical likelihood," Quantitative Finance, Taylor & Francis Journals, vol. 15(1), pages 25-41, January.
    5. Oriol Carreras & E Philip Davis & Ian Hurst & Iana Liadze & Rebecca Piggott & James Warren, 2018. "Implementing Macroprudential Policy in NiGEM," National Institute of Economic and Social Research (NIESR) Discussion Papers 490, National Institute of Economic and Social Research.
    6. Pritsker, Matthew, 2013. "Knightian uncertainty and interbank lending," Journal of Financial Intermediation, Elsevier, vol. 22(1), pages 85-105.
    7. Breuer, Thomas & Summer, Martin, 2020. "Systematic stress tests on public data," Journal of Banking & Finance, Elsevier, vol. 118(C).
    8. Thomas Breuer & Martin Jandacka & Klaus Rheinberger & Martin Summer, 2009. "How to Find Plausible, Severe and Useful Stress Scenarios," International Journal of Central Banking, International Journal of Central Banking, vol. 5(3), pages 205-224, September.
    9. Castrén, Olli & Dées, Stéphane & Zaher, Fadi, 2010. "Stress-testing euro area corporate default probabilities using a global macroeconomic model," Journal of Financial Stability, Elsevier, vol. 6(2), pages 64-78, June.
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    More about this item

    Keywords

    Multiple simultaneous equation models; Stress tests; Financial instability; Macroprudential; Joint probability;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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