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What predicts financial (in)stability? A Bayesian approach

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  • Eidenberger, Judith
  • Neudorfer, Benjamin
  • Sigmund, Michael
  • Stein, Ingrid

Abstract

This paper contributes to the literature on early warning indicators by applying a Bayesian model averaging approach. Our analysis, based on Austrian data, is carried out in two steps: First, we construct a quarterly financial stress index (AFSI) quantifying the level of stress in the Austrian financial system. Second, we examine the predictive power of various indicators, as measured by their ability to forecast the AFSI. Our approach allows us to investigate a large number of indicators. The results show that excessive credit growth and high returns of banks' stocks are the best early warning indicators. Unstable funding (as measured by the loan to deposit ratio) also has a high predictive power.

Suggested Citation

  • Eidenberger, Judith & Neudorfer, Benjamin & Sigmund, Michael & Stein, Ingrid, 2014. "What predicts financial (in)stability? A Bayesian approach," Discussion Papers 36/2014, Deutsche Bundesbank.
    • Handle: RePEc:zbw:bubdps:362014
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    3. David Orrell, 2017. "A Quantum Theory of Money and Value, Part 2: The Uncertainty Principle," Economic Thought, World Economics Association, vol. 6(2), pages 14-26, September.
    4. Polat, Onur & Ozkan, Ibrahim, 2019. "Transmission mechanisms of financial stress into economic activity in Turkey," Journal of Policy Modeling, Elsevier, vol. 41(2), pages 395-415.

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    More about this item

    Keywords

    financial crisis; early warning indicators; government policy and regulation; financial stress index;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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