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Anticipating the bust: a new cyclical systemic risk indicator to assess the likelihood and severity of financial crises

Author

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  • Lang, Jan Hannes
  • Izzo, Cosimo
  • Fahr, Stephan
  • Ruzicka, Josef

Abstract

This paper presents a tractable, transparent and broad-based domestic cyclical systemic risk indicator (d-SRI) that captures risks stemming from domestic credit, real estate markets, asset prices, and external imbalances. The d-SRI increases on average several years before the onset of systemic financial crises, and its early warning properties for euro area countries are superior to those of the total credit-to-GDP gap. In addition, the level of the d-SRI around the start of financial crises is highly correlated with measures of subsequent crisis severity, such as GDP declines. Model estimates suggest that the d-SRI has significant predictive power for large declines in real GDP growth three to four years down the line, as it precedes shifts in the entire distribution of future real GDP growth and especially of its left tail. The d-SRI therefore provides useful information about both the probability and the likely cost of systemic financial crises many years in advance. Given its timely signals, the d-SRI is a useful analytical tool for macroprudential policymakers. JEL Classification: G01, G17, C22, C54

Suggested Citation

  • Lang, Jan Hannes & Izzo, Cosimo & Fahr, Stephan & Ruzicka, Josef, 2019. "Anticipating the bust: a new cyclical systemic risk indicator to assess the likelihood and severity of financial crises," Occasional Paper Series 219, European Central Bank.
  • Handle: RePEc:ecb:ecbops:2019219
    Note: 2731285
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    References listed on IDEAS

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    More about this item

    Keywords

    early warning models; financial crises; GDP at risk; local projections; quantile regressions; systemic risk;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling

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