03623nam 2200613Ia 450 991046248450332120200520144314.01-4755-8973-51-4755-3725-5(CKB)2670000000234724(EBL)1606807(SSID)ssj0000942928(PQKBManifestationID)11521454(PQKBTitleCode)TC0000942928(PQKBWorkID)10975124(PQKB)11787625(MiAaPQ)EBC1606807(Au-PeEL)EBL1606807(CaPaEBR)ebr10590656(OCoLC)796653585(EXLCZ)99267000000023472420111102d2012 uy 0engur|n|---|||||txtccrMonitoring systemic risk based on dynamic thresholds[electronic resource] /prepared by Kasper Lund-JensenWashington International Monetary Fund20121 online resource (37 p.)IMF working paper ;12/159Description based upon print version of record.1-4755-0457-8 1-4755-6546-1 Includes bibliographical references.Cover; 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 Threshold4. 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), 1970-20109. Systemic Banking Crises DatesIII. Systemic Banking Crises Dates; ReferencesSuccessful 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 wIMF Working PapersFinancial risk managementRisk managementElectronic books.Financial risk management.Risk management.Lund-Jensen Kasper985995International Monetary Fund.MiAaPQMiAaPQMiAaPQBOOK9910462484503321Monitoring systemic risk based on dynamic thresholds2253709UNINA