Descriptive Modeling of Systemic Banking Crises

  • Dragan Gamberger
  • Dražen Lučanin
  • Tomislav Šmuc
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7569)


The topic of the work is detection of connections between occurrences of systemic banking crises and values of socio-economic indicators in time frames of three years before outburst of crises. For this task we have used the list of banking crises in the period 1976-2007 prepared by the International Monetary Fund that we have connected with publically available Word Bank data. For the analysis a machine learning methodology based on subgroup discovery has been used. The main result is that demographic indicators have been detected as most relevant. At first place this is the indicator of percentage of total population that is in the age group 15-64 years. This indicator is present in both developed models and presents a condition related to a high number of crises outbursts. In the first model this indicator is connected with the indicator of annual percentage of money and quasi money growth while in the second model it is connected with the indicator of life expectancy for male population. For the analysis especially interesting is the second model because it includes decreasing or very low positive trend in active population in a period before the onset of the crises. The importance of the result is in the fact that such situations may be expected in the near future in many developed and developing economies.


Systemic Banking Systemic Risk Negative Case Active Population Money Growth 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dragan Gamberger
    • 1
  • Dražen Lučanin
    • 1
  • Tomislav Šmuc
    • 1
  1. 1.Rudjer Bošković InstituteZagrebCroatia

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