Monitoring Systemic Risk Based on Dynamic Thresholds
AbstractSuccessful implementation of macroprudential policy is contingent on the ability to identify and estimate systemic risk in real time. In this paper, systemic risk is defined as the conditional probability of a systemic banking crisis and this conditional probability is modeled in a fixed effect binary response model framework. The model structure is dynamic and is designed for monitoring as the systemic risk forecasts only depend on data that are available in real time. Several risk factors are identified and it is hereby shown that the level of systemic risk contains a predictable component which varies through time. Furthermore, it is shown how the systemic risk forecasts map into crisis signals and how policy thresholds are derived in this framework. Finally, in an out-of-sample exercise, it is shown that the systemic risk estimates provided reliable early warning signals ahead of the recent financial crisis for several economies.
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Bibliographic InfoPaper provided by International Monetary Fund in its series IMF Working Papers with number 12/159.
Date of creation: 01 Jun 2012
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-08-23 (All new papers)
- NEP-BAN-2012-08-23 (Banking)
- NEP-RMG-2012-08-23 (Risk Management)
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