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Comparing early warning systems for banking crises

Author: Dilruba Karim
Institution: University of Essex
Type of case study: Research

About the research

Despite the extensive literature on prediction of banking crises by Early Warning Systems (EWS), their practical use by policy makers is limited, even in the international financial institutions. This is a paradox since the changing nature of banking risks as more economies liberalise and develop their financial systems, as well as ongoing innovation, makes the use of EWS for informing policies aimed at preventing crises more necessary than ever. In this context, we assess the logit and signal extraction EWS for banking crises on a comprehensive common dataset. We suggest that logit is the most appropriate approach for global EWS and signal extraction for country specific EWS. Furthermore it is important to consider the policy maker’s objectives when designing predictive models and setting related thresholds since there is a sharp trade-off between correctly calling crises and false alarms.

Aims and objectives

To use readily available macroeconomic, financial and institutional data for developing models for banking crisis prediction which can be replicated by institutions in other International Financial Institutions (IFI) member countries. By using international macrodata for over a hundred countries covering a period from 1979-2003 we were able to examine which variables are associated with systemic banking crises. Based on the results, we constructed a model to generate predictions on the likelihood of future banking crises.

Methodology

We developed econometric models using statistical software and IMF and World Bank data to generate probabilities of banking crises in various countries. Method used was multivariate logit and signal extraction. The inputs used were both macroeconomic variables (a combination of IFS and WDI data) as well as financial variables to reflect the evolution of money and credit (IFS data). These variables have been utilised in previous banking crisis literature but access to the data allowed us to expand the data set in terms of countries covered and the time frame.

Results

Policy recommendations: the multivariate logit method is more appropriate than signal extraction for designing international models of banking crisis prediction. These logit models can be used to generate probabilities of banking crises occurring in future with significant reliability which would enable policy makers to intervene to avert crisis materialisation.

Publications

Davis, E. P. and Karim, D. (2008) ‘Comparing early warning systems for banking crises’, Journal of Financial Stability, 4(2), pp. 89-120. doi: 10.1016/j.jfs.2007.12.004 Retrieved 11 September 2013 from http://www.sciencedirect.com/science/article/pii/S1572308908000144