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100   $a20111102d2012      uy             0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aMonitoring systemic risk based on dynamic thresholds$b[electronic resource] /$fprepared by Kasper Lund-Jensen
210   $aWashington $cInternational Monetary Fund$d2012
215   $a1 online resource (37 p.)
225 0 $aIMF working paper ;$v12/159
300   $aDescription based upon print version of record.
311   $a1-4755-0457-8 
311   $a1-4755-6546-1 
320   $aIncludes bibliographical references.
327   $aCover; Contents; I. Introduction; II. Related Literature; III. Econometric Methodology and Model Specification; A. Model Specification; Figures; 1. Binary Response Model Structure; Tables; 1. Countries in Data Sample; 2. Systemic Banking Crises, 1970-2010; IV. Estimation Results; 3. Standardized Marginal Effects; 4. Systemic Risk Factors; 2. Systemic Risk Factors based on Dynamic Logit Model, 1970-2010; V. Monitoring Systemic Risk; A. The Signal Extraction Approach; 3. Signal Classification; B. Crisis signals based on binary response model; 5. Optimal Threshold
327   $a4. Monitoring Systemic Risk, 1970-2010C. Risk Factor Thresholds; 6. Systemic Risk Estimates and Crisis Signals; 7. Credit-to-GDP Growth Threshold; D. Out-of-Sample Analysis; 5. Monitoring Systemic Risk - Out-of-Sample Analysis: 2001-2010; VI. Concluding Remarks; 8. Systemic Risk Estimates for the United States; Appendices; I. Data Sources and Description; 6. Systemic Risk Factors (1/2), 1970-2010; II. Binary Response Model Estimation Results; 7. Systemic Risk Factors (2/2), 1970-2010; 8. Systemic Risk Factors based on Dynamic Logit Model (Credit-to-GDP Growth), 1970-2010
327   $a9. Systemic Banking Crises DatesIII. Systemic Banking Crises Dates; References
330   $aSuccessful implementation of macroprudential policy is contingent on the ability to identify and estimate systemic risk in real time. In this paper, systemic risk is defined as the conditional probability of a systemic banking crisis and this conditional probability is modeled in a fixed effect binary response model framework. The model structure is dynamic and is designed for monitoring as the systemic risk forecasts only depend on data that are available in real time. Several risk factors are identified and it is hereby shown that the level of systemic risk contains a predictable component w
410  0$aIMF Working Papers
606   $aFinancial risk management
606   $aRisk management
608   $aElectronic books.
615  0$aFinancial risk management.
615  0$aRisk management.
700   $aLund-Jensen$b Kasper$0985995
712 02$aInternational Monetary Fund.
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910462484503321
996   $aMonitoring systemic risk based on dynamic thresholds$92253709
997   $aUNINA