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Are systemic banking crises in developed and developing countries predictable?

Listed author(s):
  • Hamdaoui, Mekki
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    This paper contributes to the empirical literature on early warning systems of banking crises using a new methodology accounting for model uncertainty. We introduce new variables measuring exposure and connectivity of the domestic banking sector to international financial markets. We show that a multinomial logit model based on Bayesian Model Averaging is favored to conventional multinomial and binary models highlighting what is called by Bussiere and Fratzsher (2006) “post-crisis bias”. We show that the application of the multinomial logit model, which distinguishes between more than two states and uses Bayesian Model Averaging, is a valid way to solve this problem and leads to a substantial improvement in the ability to predict banking crises. The empirical results show that for a set of 49 developing and developed countries, the model would have correctly predicted the vast majority of crises.

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    File URL: http://www.sciencedirect.com/science/article/pii/S1042444X1630069X
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    Article provided by Elsevier in its journal Journal of Multinational Financial Management.

    Volume (Year): 37-38 (2016)
    Issue (Month): ()
    Pages: 114-138

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    Handle: RePEc:eee:mulfin:v:37-38:y:2016:i::p:114-138
    DOI: 10.1016/j.mulfin.2016.09.002
    Contact details of provider: Web page: http://www.elsevier.com/locate/mulfin

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