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• W2030866772 abstract "Abstract This paper estimates an early warning system (EWS) for predicting systemic banking crises in a sample of low income countries in Sub-Saharan Africa. Since the average duration of crises in this sample of countries is longer than one year, the predictive performance of standard binomial logit models is likely to be hampered by the so-called crisis duration bias . The bias arises from the decision to either treat crisis years after the onset of a crisis as non-crisis years or remove them altogether from the model. To overcome this potential drawback, we propose a multinomial logit approach, which is shown to improve the predictive power of our EWS compared to the binomial logit model. Our results suggest that crisis events in low income countries are associated with low economic growth, drying up of banking system liquidity and widening of foreign exchange net open positions." @default.
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• W2030866772 date "2014-10-01" @default.
• W2030866772 modified "2023-10-13" @default.
• W2030866772 title "Early warning systems and systemic banking crises in low income countries: A multinomial logit approach" @default.
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• W2030866772 doi "https://doi.org/10.1016/j.jbankfin.2014.07.002" @default.
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