## _wp04153 - References

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### I. INTRODUCTION
- High incidence of financial instability since the late 1990s has driven development of quantitative methods to assess financial sector robustness, exposures and vulnerability to shocks.
- Quantitative methodologies reviewed: indicators of financial sector soundness, early warning systems, sensitivity analysis and extreme scenarios (“stress tests”), and financial forecasting.
- These techniques are used alongside expert judgment and institutional/legal analysis; they do not replace qualitative assessment.
- Surveys and guides cited as foundational: BIS (2001); Evans and others (2000); Blaschke, Jones, Majnoni and Peria (2001); Sundararajan and others (2002); IMF draft guide for FSIs (IMF, 2003a).

### II. USE OF FINANCIAL SOUNDNESS INDICATORS (FSIs)
- Purpose: capture macroprudential vulnerabilities via macroeconomic and prudential indicators (including CAMELS ratios, interbank exposures, external contagion measures).
- Practical use:
  - Aggregate FSI analysis is judgmental, complemented by institution-level FSI analysis where feasible.
  - Benchmarks/norms remain developing; data comparability via IMF draft manual is a first step.
  - Peer group comparisons recommended where number of banks permits; focus on systemically important banks when concentration is high.
- Signaling and aggregation methods:
  - Scoring and threshold models: Caprio (1998); Kaminsky, Lizondo and Reinhart (1998); Goldstein, Kaminsky and Reinhart (2000); Edison (2000).
  - Weighted combinations and summary indices are used by IMF, Bank of England, and private sector risk providers.
- Statistical early-warning models:
  - Probit/logit/discriminant approaches estimate probability of financial failure from FSIs and macro variables (examples include Demirgüç-Künt and Detragiache (1998); Gonzalez-Hermosillo (1999); Mulder, Perrelli and Rocha (2001); Bussiere and Fratzscher (2002); Worrell, Cherebin and Polius-Mounsey (2001); Polius and Sahely (2003)).
  - Limitations: unsatisfactory out-of-sample forecasting power; single-country models constrained by limited crisis observations; promising alternative is institution-level failure models to infer systemic risk.
- Volatility forecasting:
  - Market volatility proposed as an FSI (Morales and Schumacher, 2003); empirical results mixed due to data frequency and identification issues (Worrell and Leon, 2001; Aizenman and Pinto, 2004).

### III. STRESS TESTS
- Role: explore low-probability, high-cost events and contingencies with uncertain probabilities; complement analysis of high-probability, low-loss vulnerabilities.
- Common focuses: capital adequacy, profitability, liquidity under shocks to interest rates, exchange rates, credit quality, equity and real estate prices, liquidity runs (especially in dollarized economies).
- Methodological features and limitations:
  - Calibration of shocks relies on judgment; historical experience may be a poor guide.
  - Results sensitive to timing and incomplete capture of dynamic system responses.
- Typical categories of stress tests:
  - Individual shocks and balance sheet adjustments: apply changes to recent balance sheets/P&L; banks may use internal VaR models for regulator-specified shocks; common tests: interest rates, exchange rates, credit quality, equity and real estate prices.
  - Aggregate and correlated shocks: aggregate individual shock effects or derive credit quality shocks from macroeconomic-linking models (examples: Arpa et al. (2001); Andreeva (2004); Kalirai and Scheicher (2002)).
  - Interbank contagion: measure contagion via interbank exposures, settlement systems, and liquidity-run channels (e.g., Diamond and Rajan (2002); Elsinger, Lehar and Summer (2002)); empirical contagion tests include autocorrelation of failures, survival time during panics, news effects on failures and on interbank risk premiums.
  - Corporate and household balance-sheet deterioration: analyze effects of income contractions or liquidity shortages on firms and households; indicators include debt-to-income, debt-to-asset, liquidity ratios and bankruptcy probabilities (examples: Kim and Stone (1999); Lindgren and others (1999); Bris and Koskinen (2002); Gapen et al. (2004); Norges Bank bankruptcy database use in Andreeva (2004) and Froyland and Larsen (2002)).

### IV. MODEL-BASED FINANCIAL FORECASTS
- Use of macroeconomic forecasts as inputs:
  - Some central banks derive financial forecasts from structural macroeconomic models (examples: Norges Bank, Bank of Finland, Bank of England experimental FSAP-linked exercises; proposed model for Central Bank of Barbados).
  - Forecast outputs used to evaluate debt capacity, credit quality, CAMELS ratios, and as inputs for stress tests.
- Early warning of exchange rate crises (EWS-ER):
  - Wealth of EWS-ER models exists and may be leveraged because exchange rate crises often accompany financial crises.
  - Examples: Flood and Marion (1999) survey; IMF models using macro variables and models including corporate/legal variables (Berg, Borenzstein, Milesi-Ferretti and Pattillo, 2000); Kaminsky-Lizondo-Reinhart model.

### V. QUANTITATIVE ASSESSMENT: AN INTEGRATED APPROACH
- Recommended integrated assessment components:
  - An Early Warning System for Financial Institutions (EWS-FI) predicting vulnerable institutions.
  - A financial sector forecast derived from macroeconomic forecasts where available.
  - Stress tests of institution balance sheets and income statements, adjusted for suspected weaknesses, possibly applied to systemically important institutions.
  - Interbank contagion tests linked to institution-level outcomes.
  - Forecasts of corporate and household performance and their impact on the financial sector.
  - Estimates of probability of exchange rate crisis from EWS-ER models to calibrate exchange rate shocks.
- EWS-FI design guidance:
  - Expand impaired-institution observations by including intensive-supervision cases and near-bank institutions; refine logit specifications with CAMELS ratios, interest rate changes, inflation, exchange rate changes, asset-price changes and real activity indices.
  - Country-specific experimentation required due to data constraints and parameter heterogeneity.
- Financial system/ institution forecasts:
  - Aggregate forecasts commonly attainable: NPLs, deposits, loans, financial prices; individual-institution forecasts possible by applying current distributions to forecast means.
  - Forecasted NPLs frequently produced econometrically; CAMELS may be derived at aggregate or, with assumptions, individual levels.
- Stress-test procedure within integrated framework:
  - Correct individual institution data for underreporting or overvaluation to generate adjusted CAMELS.
  - Input forecast balance sheet and P&L variables to create forecast CAMELS.
  - Apply shocks to credit quality, interest rates, asset prices, exchange rates to generate stress CAMELS.
  - Apply shocks to macro model (exchange rate, terms of trade, inflation, growth) and repeat above steps.
- Refinements:
  - Conduct contagion analysis for each scenario-generated failure.
  - Incorporate corporate and household balance sheet transmission channels using available databases (Scandinavian examples).
  - Use EWS-ER forecasts to inform exchange rate shock calibration and to assess probabilities for stress scenarios.

### VI. CONCLUSION
- Financial soundness assessment methodology remains immature; techniques are complementary and partial.
- Integrated framework combining EWS-FI, financial forecasts, stress tests, interbank contagion analysis, and corporate/household indicators enhances insight into system strengths and vulnerabilities.
- Ongoing needs:
  - Better understanding of time horizons and appropriate risk aversion degrees in assessments.
  - Expanded methodologies beyond banking to insurance, pension/superannuation funds, and capital markets where systemically important.

### APPENDIX — Selected Financial Stability Report Practices (high-level summaries)
- Finland and Norway: most comprehensive, combining macro-based financial forecasts with FSIs, corporate/household indicators and stress tests; example horizon: a 2 year benchmark forecast in Bank of Finland practice.
- Austria: market risk focus; banks report interest rate stress tests; stress tests for exchange rates; corporate/household indicators monitored.
- Brazil: banking system accounts for 98 percent of financial assets; stress tests include interest rate, exchange rate, credit deterioration and combinations; value-at-risk (VaR) and a hybrid nonparametric model used.
- ECB: “bank performance” and “bank risk outlook” chapters; stress testing and macro-prudential modeling performed, not fully public.
- Indonesia: FSIs, international comparisons, stress tests for loan quality, exchange rate and interest rate changes.
- Netherlands: FSIs across banks, nonbanks, corporates, households; indicators include CAR, loan concentration, housing market statistics, pension fund coverage.
- Norway (Norges Bank): structural model-derived forecasts; firm bankruptcy probabilities estimated via logit (Bernhardsen, 2001); forecast NPLs derived from exposure-weighted bankruptcy probabilities; stress scenarios include demand shock via petroleum revenue decline.
- Spain: NPL analysis by borrower and loan characteristics; corporate and household credit trends reviewed.
- United Kingdom: global focus due to London’s role; FSIs for large U.K.-owned banks; VaR used for market risk; Financial Services Authority publishes Financial Risk Outlook.

*Source: _wp04153 - References*

### References..............................................................................................................

### _wp04153 - References

### I. INTRODUCTION
- High incidence of financial instability since the late 1990s has driven development of quantitative methods to assess financial sector robustness, exposures and vulnerability to shocks.
- Quantitative methodologies reviewed: indicators of financial sector soundness, early warning systems, sensitivity analysis and extreme scenarios (“stress tests”), and financial forecasting.
- These techniques are used alongside expert judgment and institutional/legal analysis; they do not replace qualitative assessment.
- Surveys and guides cited as foundational: BIS (2001); Evans and others (2000); Blaschke, Jones, Majnoni and Peria (2001); Sundararajan and others (2002); IMF draft guide for FSIs (IMF, 2003a).

### II. USE OF FINANCIAL SOUNDNESS INDICATORS (FSIs)
- Purpose: capture macroprudential vulnerabilities via macroeconomic and prudential indicators (including CAMELS ratios, interbank exposures, external contagion measures).
- Practical use:
  - Aggregate FSI analysis is judgmental, complemented by institution-level FSI analysis where feasible.
  - Benchmarks/norms remain developing; data comparability via IMF draft manual is a first step.
  - Peer group comparisons recommended where number of banks permits; focus on systemically important banks when concentration is high.
- Signaling and aggregation methods:
  - Scoring and threshold models: Caprio (1998); Kaminsky, Lizondo and Reinhart (1998); Goldstein, Kaminsky and Reinhart (2000); Edison (2000).
  - Weighted combinations and summary indices are used by IMF, Bank of England, and private sector risk providers.
- Statistical early-warning models:
  - Probit/logit/discriminant approaches estimate probability of financial failure from FSIs and macro variables (examples include Demirgüç-Künt and Detragiache (1998); Gonzalez-Hermosillo (1999); Mulder, Perrelli and Rocha (2001); Bussiere and Fratzcher (2002); Worrell, Cherebin and Polius-Mounsey (2001); Polius and Sahely (2003)).
  - Limitations: unsatisfactory out-of-sample forecasting power; single-country models constrained by limited crisis observations; promising alternative is institution-level failure models to infer systemic risk.
- Volatility forecasting:
  - Market volatility proposed as an FSI (Morales and Schumacher, 2003); empirical results mixed due to data frequency and identification issues (Worrell and Leon, 2001; Aizenman and Pinto, 2004).

### III. STRESS TESTS
- Role: explore low-probability, high-cost events and contingencies with uncertain probabilities; complement analysis of high-probability, low-loss vulnerabilities.
- Common focuses: capital adequacy, profitability, liquidity under shocks to interest rates, exchange rates, credit quality, equity and real estate prices, liquidity runs (especially in dollarized economies).
- Methodological features and limitations:
  - Calibration of shocks relies on judgment; historical experience may be a poor guide.
  - Results sensitive to timing and incomplete capture of dynamic system responses.
- Typical categories of stress tests:
  - Individual shocks and balance sheet adjustments: apply changes to recent balance sheets/P&L; banks may use internal VaR models for regulator-specified shocks; common tests: interest rates, exchange rates, credit quality, equity and real estate prices.
  - Aggregate and correlated shocks: aggregate individual shock effects or derive credit quality shocks from macroeconomic-linking models (examples: Arpa et al. (2001); Andreeva (2004); Kalirai and Scheicher (2002)).
  - Interbank contagion: measure contagion via interbank exposures, settlement systems, and liquidity-run channels (e.g., Diamond and Rajan (2002); Elsinger, Lehar and Summer (2002)); empirical contagion tests include autocorrelation of failures, survival time during panics, news effects on failures and on interbank risk premiums.
  - Corporate and household balance-sheet deterioration: analyze effects of income contractions or liquidity shortages on firms and households; indicators include debt-to-income, debt-to-asset, liquidity ratios and bankruptcy probabilities (examples: Kim and Stone (1999); Lindgren and others (1999); Bris and Koskinen (2002); Gapen et al. (2004); Norges Bank bankruptcy database use in Andreeva (2004) and Froyland and Larsen (2002)).

### IV. MODEL-BASED FINANCIAL FORECASTS
- Use of macroeconomic forecasts as inputs:
  - Some central banks derive financial forecasts from structural macroeconomic models (examples: Norges Bank, Bank of Finland, Bank of England experimental FSAP-linked exercises; proposed model for Central Bank of Barbados).
  - Forecast outputs used to evaluate debt capacity, credit quality, CAMELS ratios, and as inputs for stress tests.
- Early warning of exchange rate crises (EWS-ER):
  - Wealth of EWS-ER models exists and may be leveraged because exchange rate crises often accompany financial crises.
  - Examples: Flood and Marion (1999) survey; IMF models using macro variables and models including corporate/legal variables (Berg, Borenzstein, Milesi-Ferretti and Pattillo, 2000); Kaminsky-Lizondo-Reinhart model.

### V. QUANTITATIVE ASSESSMENT: AN INTEGRATED APPROACH
- Recommended integrated assessment components:
  - An Early Warning System for Financial Institutions (EWS-FI) predicting vulnerable institutions.
  - A financial sector forecast derived from macroeconomic forecasts where available.
  - Stress tests of institution balance sheets and income statements, adjusted for suspected weaknesses, possibly applied to systemically important institutions.
  - Interbank contagion tests linked to institution-level outcomes.
  - Forecasts of corporate and household performance and their impact on the financial sector.
  - Estimates of probability of exchange rate crisis from EWS-ER models to calibrate exchange rate shocks.
- EWS-FI design guidance:
  - Expand impaired-institution observations by including intensive-supervision cases and near-bank institutions; refine logit specifications with CAMELS ratios, interest rate changes, inflation, exchange rate changes, asset-price changes and real activity indices.
  - Country-specific experimentation required due to data constraints and parameter heterogeneity.
- Financial system/ institution forecasts:
  - Aggregate forecasts commonly attainable: NPLs, deposits, loans, financial prices; individual-institution forecasts possible by applying current distributions to forecast means.
  - Forecasted NPLs frequently produced econometrically; CAMELS may be derived at aggregate or, with assumptions, individual levels.
- Stress-test procedure within integrated framework:
  - Correct individual institution data for underreporting or overvaluation to generate adjusted CAMELS.
  - Input forecast balance sheet and P&L variables to create forecast CAMELS.
  - Apply shocks to credit quality, interest rates, asset prices, exchange rates to generate stress CAMELS.
  - Apply shocks to macro model (exchange rate, terms of trade, inflation, growth) and repeat above steps.
- Refinements:
  - Conduct contagion analysis for each scenario-generated failure.
  - Incorporate corporate and household balance sheet transmission channels using available databases (Scandinavian examples).
  - Use EWS-ER forecasts to inform exchange rate shock calibration and to assess probabilities for stress scenarios.

### VI. CONCLUSION
- Financial soundness assessment methodology remains immature; techniques are complementary and partial.
- Integrated framework combining EWS-FI, financial forecasts, stress tests, interbank contagion analysis, and corporate/household indicators enhances insight into system strengths and vulnerabilities.
- Ongoing needs:
  - Better understanding of time horizons and appropriate risk aversion degrees in assessments.
  - Expanded methodologies beyond banking to insurance, pension/superannuation funds, and capital markets where systemically important.

### APPENDIX — Selected Financial Stability Report Practices (high-level summaries)
- Finland and Norway: most comprehensive, combining macro-based financial forecasts with FSIs, corporate/household indicators and stress tests; example horizon: a 2 year benchmark forecast in Bank of Finland practice.
- Austria: market risk focus; banks report interest rate stress tests; stress tests for exchange rates; corporate/household indicators monitored.
- Brazil: banking system accounts for 98 percent of financial assets; stress tests include interest rate, exchange rate, credit deterioration and combinations; value-at-risk (VaR) and a hybrid nonparametric model used.
- ECB: “bank performance” and “bank risk outlook” chapters; stress testing and macro-prudential modeling performed, not fully public.
- Indonesia: FSIs, international comparisons, stress tests for loan quality, exchange rate and interest rate changes.
- Netherlands: FSIs across banks, nonbanks, corporates, households; indicators include CAR, loan concentration, housing market statistics, pension fund coverage.
- Norway (Norges Bank): structural model-derived forecasts; firm bankruptcy probabilities estimated via logit (Bernhardsen, 2001); forecast NPLs derived from exposure-weighted bankruptcy probabilities; stress scenarios include demand shock via petroleum revenue decline.
- Spain: NPL analysis by borrower and loan characteristics; corporate and household credit trends reviewed.
- United Kingdom: global focus due to London’s role; FSIs for large U.K.-owned banks; VaR used for market risk; Financial Services Authority publishes Financial Risk Outlook.

*Source: _wp04153 - References*

### References

### _wp04153 - References

### Stress testing and financial stability
- Arpa, Marcus, Irene Giulini, Andreas Ittner and Franz Pauer, 2001, “The Influence of Macroeconomic Developments on Austrian Banks: Implications for Banking Supervision,” BIS Papers No. 1, March, pages 91-116.
- Austrian National Bank, 1999, “Stress Testing,” Guidelines for Market risk, Vol. 5, September.
- Austrian National Bank, 2003, Financial Stability Report 6, November.
- Banco Central do Brasil, 2003, Financial Stability Report, Volume 2, No. 2, November.
- Banco de España, 2003, Estabilidad Financiera, No. 3, November.
- Bank of England, 2003, “The Financial Stability Conjuncture and Outlook,” Financial Stability Review, No. 15, December.
- Bank of Finland, 2003, Financial Stability Bulletin.
- Bank Indonesia, 2003, Financial Stability Review, June.
- Blaschke, Winfrid, Matthew Jones, Giovanni Majnoni and Soledad Peria, 2001, “Stress Testing Of Financial Systems: A Review Of The Issues, Methodologies And FSAP Experiences,” IMF Working Paper WP/01/88, June.
- Elsinger, Helmut, Alfred Lehar and Martin Summer, 2002, “A New Approach To Assessing The Risk Of Interbank Loans,” Austrian National Bank Financial Stability Report 3.
- Froyland, Espen and Kai Larsen, 2002, “How Vulnerable Are Financial Institutions to Macroeconomic Changes? An Analysis Based On Stress Testing,” Norges Bank Economic Bulletin, third quarter.
- Hilbers, Paul, Matthew Jones and Graham Slack, forthcoming, “Stress Testing Financial Systems: What to do When the Governor Calls,” IMF Working Paper.
- Hoggarth, Glenn and John Whitley, 2003, “Assessing The Strength of UK Banks Through Macroeconomic Stress Tests,” Bank of England Financial stability Review, June.
- Kalirai, Harvir and Martin Scheicher, 2002, “Macroeconomic Stress Testing: Preliminary Evidence For Austria,” Austrian National Bank Financial Stability Report 3, 2002.
- Lowe, Philip, 2002, “Credit Risk Measurement and Procyclicality,” BIS Working Paper, September.

### Early warning systems, crisis detection, and vulnerability assessment
- Aizenman, Joshua and Brian Pinto, 2004, “Managing Volatility And Crises: Overview,” Draft Chapter For Managing Volatility and Crises: A Practitioner's Guide, World Bank, March.
- Berg, Andrew, Eduardo Borensztein, Gian Maria Milesi-Ferretti, and Catherine Pattillo, 2000, “Anticipating Balance Of Payments Crises - The Role Of Early Warning Systems,” IMF Occasional Paper No. 186, January.
- Bussiere, Matthieu and Marcel Fratzscher, 2002, “Towards a New Early Warning System of Financial Crises,” European Central Bank Working Paper No. 145, May.
- Edison, Hali J., 2000, “Do Indicators of Financial Crises Work? An Evaluation of an Early Warning System,” Federal Reserve Board IFDP Working Paper No. 675, July.
- Goldstein, Morris, Graciela Kaminsky and Carmen Reinhart, 2000, “Assessing Financial Vulnerability: an Early Warning System for Financial markets,” Institute for International Economics, June.
- Kaminsky, Graciela, Saul Lizondo and Carmen Reinhart, 1998, “Leading Indicators Of Currency Crises,” IMF Staff Papers, Vol. 45, No. 1, March, pages 1-48.
- Morales, Armando and Liliana Schumacher, 2003, “Market volatility as a financial soundness indicator: an application to Israel,” IMF Working Paper WP/03/47, March.
- Mulder, Christian, Roberto Perrelli and Manuel Rocha, 2001, “The Role Of Corporate, Legal And Macro Balance Sheet Indicators In Crisis Detection And Prevention,” IMF Policy Development Paper, March.
- Worrell, DeLisle and Hyginus Leon, 2001, “Price Volatility and Financial Instability,” IMF Working Paper WP/01/60, May.
- Edison, Hali J., 2000, “Do Indicators of Financial Crises Work? An Evaluation of an Early Warning System,” Federal Reserve Board IFDP Working Paper No. 675, July.

### Corporate sector, bankruptcy, leverage, and firm-level vulnerability
- Andreeva, Olga, 2004, “Aggregate Bankruptcy Probabilities And Their Role In Explaining Banks' Loan Losses,” Norges Bank Working Paper No. 2004/2, February.
- Bell, James and Darren Pain, 2000, “Leading Indicator Models Of Banking Crises - A Critical Review,” Bank of England Financial Stability Review, December.
- Benito, Andrew and Gertjan Vliege, 2000, “Stylised Facts On UK Corporate Financial Health: Evidence From Micro-Data,” Bank of England Financial Stability Review, June, 83-93.
- Benito, Andrew, John Whitley and Garry Young, 2001, “Analyzing Corporate And Household Sector Balance Sheets,” Bank of England Financial Stability Review, December.
- Bris, Arturo and Yrjö Koskinen, 2002, “Corporate Leverage And Currency Crises,” Journal of Financial Economics, Vol. 63, pages 275-310.
- Bunn, Philip, 2003, “Company-Accounts-Based Modeling Of Business Failures,” Bank of England Financial Stability Review, December.
- Claessens, Stijn, Simeon Djankov and Lixin Colin Xu, 2000, “Corporate Performance in the East Asian Financial Crisis,” World Bank Research Observer, Vol. 15, No. 1, February.
- Demirgüç-Kunt, Asli and Enrica Detragiache, 1998, “The Determinants Of Banking Crises In Developing And Developed Countries,” IMF Staff Papers, Vol. 45, No. 1, March, pages 81-109.
- Diamond, Douglas W. and Raghuram G. Rajan, 2002, “Liquidity Shortages and Banking Crises,” NBER Working Paper No. W8937, May.
- Gonzalez-Hermosillo, Brenda, 1999, “Determinants Of Ex-Ante Banking System Distress: A Macro-Micro Empirical Exploration,” IMF WP/99/33, March.
- Gray, Dale, 1999, “Assessment Of Corporate Sector Value And Vulnerability: Links To Exchange Rate And Financial Crises,” World Bank technical paper, September.
- Heytens, Paul and Cem Karacadag, 2001, “An Attempt To Profile the Finances of China's Enterprise Sector,” IMF WP/01/182, November.
- Kim, Se-Jik and Mark Stone, 1999, “Corporate leverage, bankruptcy, and output adjustment in post-crisis East Asia,” Working Paper, IMF Working Paper WP/99/143, October.
- Lim, Youngjae, 2003, “Sources of Corporate Financing and Economic Crisis in Korea: A Micro-Evidence,” NBER Working Paper No. W9575, March.
- Sahely, Leah and Judy Jacobs, 2000, “Documentation on the Implementation of Peer Groups in the ECCU,” ECCB Working Paper, June.
- Wilson, B., A. Saunders and G. Caprio, Jr., 2000, “Mexico's Financial Sector Crisis: Propagative Linkages To Devaluation,” The Economic Journal, Vol. 110, No. 460, January, pages 292-308.

### Interbank exposures, systemic risk, contagion, and network analysis
- Blavarg, Martin and Patrick Nimander, 2002, “Inter-Bank Exposures And Systemic Risk,” Sveriges Riksbank Economic Review, No. 2/2002, pages 19-45.
- De Bandt, Olivier and Philipp Hartmann, 2000, “Systemic Risk: A Survey,” European Central Bank Working Paper No. 35, November.
- Diamond, Douglas W. and Raghuram G. Rajan, 2002, “Liquidity Shortages and Banking Crises,” NBER Working Paper No. W8937, May.
- Pesaran, Hashem and Andreas Pick, 2003, “Econometric Issues In The Analysis Of Contagion,” University of Cambridge, November.
- Wells, Simon, 2002, “UK interbank exposures: systemic risk implications,” Bank of England Financial Stability Review, December.
- Wilson, B., A. Saunders and G. Caprio, Jr., 2000, “Mexico's Financial Sector Crisis: Propagative Linkages To Devaluation,” The Economic Journal, Vol. 110, No. 460, January, pages 292-308.

### Central bank, country case studies, and regional assessments
- Bank of England, 2003, “The Financial Stability Conjuncture and Outlook,” Financial Stability Review, No. 15, December.
- Banco Central do Brasil, 2003, Financial Stability Report, Volume 2, No. 2, November.
- Banco de España, 2003, Estabilidad Financiera, No. 3, November.
- Bank Indonesia, 2003, Financial Stability Review, June.
- De Nederlansche Bank, 2003, Quarterly Bulletin, December.
- European Central Bank, 2003, EU Banking Sector Stability, November.
- Greenidge, Kevin, Warrick Ward and Karen Chase, 2001, “Financial Sector Assessment: A Case Study of Barbados,” Central Bank of Barbados Working Paper July.
- Norges Bank, 2003 Financial Stability, No. 2, November.
- Polius, Tracy and Leah Sahely, 2003, “Predicting Bank Performance in the Eastern Caribbean Currency Union,” Paper presented to the Caribbean Centre for Monetary Studies Conference, St. Kitts, November.
- Worrell, DeLisle, Desiree Cherebin and Tracy Polius-Mounsey, 2001, “Financial System Soundness in the Caribbean: an Initial Assessment,” IMF Working Paper WP/01/123, September.

### Methodologies, indicators, and analytical frameworks
- Bank for International Settlements, 2001, Marrying the Macro- and Micro-prudential Dimensions of Financial Stability, BIS Papers No. 1.
- Blaschke, Winfrid, Matthew Jones, Giovanni Majnoni and Soledad Peria, 2001, “Stress Testing Of Financial Systems: A Review Of The Issues, Methodologies And FSAP Experiences,” IMF Working Paper WP/01/88, June.
- Eijffinger, Sylvester C.W. and Benedikt Goderis, 2002, “Financial Crises, Monetary Policy and Financial Fragility; A Second-Generation Model of Currency Crises,” Centre for Economic Policy Research (CEPR) Discussion Paper No. 3637, November.
- Eitrheim, Oyvind and Bjarne Gulbrandsen, 2001, “A model Based Approach to Analyzing Financial Stability,” BIS, Marrying the Macro- and Micro-prudential Dimensions of Financial Stability, BIS Papers No. 1.
- Evans, Owen and others, 2002, Macroprudential Indicators of Financial System Soundness, IMF Occasional Paper No. 192, April.
- Gapen, Michael, Dale Gray, Cheng Hoon Lim and Yingbin Xiao, 2004, “The contingent claims approach to corporate vulnerability analysis: estimating default risk ad economy-wide risk transfer,” IMF seminar paper, May.
- Goodhart, Charles, 2004, “Some New Directions For Financial Stability?” Per Jacobsson lecture, Zurich, June 27, 2004.
- Haldane, Andrew, Glenn Hoggarth and Victoria Saporta, 2001, “Assessing Financial System Stability, Efficiency and Structure at the Bank of England,” in BIS, Marrying the Macro- and Micro-prudential Dimensions of Financial Stability, BIS Papers No.1.
- Houben, Aerdt, Jan Kakes and Garry Schinasi, forthcoming, “Towards a framework for financial stability,” IMF Working Paper.
- IMF, 2001, “Approaches to Vulnerability Assessment,” Policy Development Paper, September.
- IMF, 2002, Global Financial Stability Report - Market Developments And Issues, December.
- IMF, 2003a, “A Compilation Guide On Financial Soundness Indicators," Draft, March. http://www.imf.org/external/np/sta/fsi/eng/guide/index.htm
- IMF, 2003b, Global Financial Stability Report - Market Developments and Issues, September.
- IMF and World Bank, 2003, “Analytical Tools Of The FSAP,” Staff Report Supplement 1, February.
- Lindgren, Carl-Johan and others, 1999, Financial Sector Crisis and Restructuring: Lessons from Asia, IMF Occasional Paper.
- Morales, Armando and Liliana Schumacher, 2003, “Market volatility as a financial soundness indicator: an application to Israel,” IMF Working Paper WP/03/47, March.
- Mulder, Christian, Roberto Perrelli and Manuel Rocha, 2001, “The Role Of Corporate, Legal And Macro Balance Sheet Indicators In Crisis Detection And Prevention,” IMF Policy Development Paper, March.
- Sahel, Benjamin and Jukka Vesala, 2001, “Financial Stability Analysis Using Aggregated Data,” in BIS, Marrying the Macro- and Micro-prudential Dimensions of Financial Stability, BIS Papers No. 1.
- Sundararajan, V. and others, 2002, Financial Soundness Indicators: Analytical Aspects and Country Practices, IMF Occasional Paper, No. 212.
- Syrdal, Stig Arild, 2002, “A Study Of Implied Risk-Neutral Density Functions In The Norwegian Option Market,” Norges Bank Working Paper WP 13/02, December.
- Virolainen, Kimmo, 2001, “Financial Stability Analysis at the Bank of Finland,” BIS, Marrying the Macro- and Micro-prudential Dimensions of Financial Stability, BIS Papers No. 1.

*References list from _wp04153 - References*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2004/_wp04153.pdf_