Monitoring systemic risk based on dynamic thresholds [[electronic resource] /] / prepared by Kasper Lund-Jensen

• Autore: Lund-Jensen Kasper
• Pubblicazione: Washington, : International Monetary Fund, 2012
• Descrizione fisica: 1 online resource (37 p.)
• Soggetto topico: Financial risk management; Risk management
• Soggetto genere / forma: Electronic books.
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: 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 Threshold ; 4. 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 ; 9. Systemic Banking Crises DatesIII. Systemic Banking Crises Dates; References
• Sommario/riassunto: Successful 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
• Titolo autorizzato: Monitoring systemic risk based on dynamic thresholds
• ISBN: 1-4755-8973-5; 1-4755-3725-5
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910462484503321
• Lo trovi qui: Univ. Federico II
• Serie: IMF Working Papers