Monitoring systemic risk based on dynamic thresholds /
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 bina...
Clasificación: | Libro Electrónico |
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Autor principal: | |
Formato: | Electrónico eBook |
Idioma: | Inglés |
Publicado: |
[Washington, D.C.] :
International Monetary Fund,
©2012.
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Colección: | IMF working paper ;
WP/12/159. |
Temas: | |
Acceso en línea: | Texto completo |
Tabla de Contenidos:
- 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.