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Shifting horizons: assessing macro trends before, during, and following systemic banking crises

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  • Schudel, Willem

Abstract

This paper assesses the trends of some main macroeconomic and macro-financial variables across different time horizons related to systemic banking crises. Specifically, by gradually shifting the observation horizon of the same statistical model across time, it observes how these variables are associated with banking crises in the past, present and future. The associations vary considerably when shifting horizons. Domestic house price growth increases the probability of observing a crisis in the future, but its effect disappears when moving closer to a crisis. The inverse holds true for the effect of the global credit gap, while global credit growth consistently and significantly increases the probability of a future banking crisis. Also, banking crises seem to be spatially correlated in the very short run. In all, the results can help policy makers by shedding light on the temporal horizon of the variables they monitor in addition to evaluating their predictive power. JEL Classification: C23, C51, E43, E51, G01

Suggested Citation

  • Schudel, Willem, 2015. "Shifting horizons: assessing macro trends before, during, and following systemic banking crises," Working Paper Series 1766, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:20151766
    Note: 1985704
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    Cited by:

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    2. Markus Behn & Carsten Detken & Tuomas Peltonen & Willem Schudel, 2017. "Predicting Vulnerabilities in the EU Banking Sector: The Role of Global and Domestic Factors," International Journal of Central Banking, International Journal of Central Banking, vol. 13(4), pages 147-189, December.
    3. Dieckelmann, Daniel, 2020. "Cross-border lending and the international transmission of banking crises," Discussion Papers 2020/13, Free University Berlin, School of Business & Economics.

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    More about this item

    Keywords

    banking crisis; binary time series cross section data; credit; time horizons;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
    • G01 - Financial Economics - - General - - - Financial Crises

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