## _wp09100 - Executive Summary

## Source details

**Canonical URL:** [_wp09100 - Executive Summary](https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2009/_wp09100.pdf)

## Other formats

- [Markdown version](/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2009/_wp09100.pdf.md)
- [Structured JSON version](/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2009/_wp09100.pdf.json)

---

### Overview and purpose
- Study period and sample: 17 advanced economies over the past 30 years.
- Objective: analyze past episodes of financial stress in banking, securities, and foreign exchange markets, identify 113 episodes of financial stress, and assess their implications for subsequent economic activity using a Financial Stress Index (FSI).
- Main focus: how financial stress—especially banking distress—affects the real economy, and which initial conditions and financial-system features determine whether stress leads to slowdowns or recessions.

### Methodology — Financial Stress Index (FSI)
- FSI construction: variance-weighted average of three subindices associated with banking, securities, and foreign exchange markets; episodes identified where a country’s FSI is more than one standard deviation above its HP-filtered trend.
- Banking-related subindex components:
  - Slope of the yield curve (short- minus long-term government yields; inverted term spread).
  - TED spread (interbank rates minus Treasury bill yield).
  - Beta of banking sector returns (recorded as non-zero only during periods when returns are negative).
- Securities-related subindex components:
  - Corporate bond spreads (corporate yields minus long-term government yields).
  - Stock market returns (monthly return multiplied by -1).
  - Time-varying stock return volatility (GARCH(1,1)).
- Foreign-exchange-related subindex component:
  - Time-varying volatility of monthly changes in the nominal effective exchange rate (GARCH(1,1)).
- Advantages emphasized:
  - High-frequency, market-based indicators comparable across 17 countries.
  - Precise dating of onset and peaks of stress episodes.
  - Ability to distinguish banking, securities, and FX stress and their interactions.

### Episodes identified and classification
- Total financial stress episodes identified: 113.
  - Banking-driven episodes: 43.
  - Securities-market episodes: 50.
  - Foreign-exchange episodes: 20.
- Banking-related episodes (where banks were dominant or second largest factor with contribution ≥ one-third): 60.
  - In 17 episodes that mainly reflected securities or FX stress, the banking variables nonetheless accounted for at least one third of the spike.
- Cross-country propagation: 87 of the 113 episodes simultaneously affected two or more countries.
- Typical episode duration: average financial stress duration reported as 2.42 quarters.

### Key empirical findings on macroeconomic impact
- Frequency of downturns:
  - About half of the financial stress episodes were associated with an economic slowdown or recession.
  - Of 113 episodes, 29 were followed by a slowdown and 29 by a recession; 55 were not followed by an economic downturn.
- Timing:
  - Average lag between onset of financial stress and the slowdown/recession: about seven months.
  - ~50 percent of slowdown/recessions occurred within one quarter, ~25 percent took more than a year.
- Magnitude of output losses (medians):
  - Slowdowns preceded by financial stress: median cumulative output loss of 2.8 percent of GDP.
  - Recessions preceded by financial stress: median cumulative output loss of 4.4 percent of GDP.
  - For comparison, slowdowns not preceded by financial stress: about 1.6 percent of GDP; recessions not preceded by financial stress: about 2.3 percent of GDP.
- Duration and recovery:
  - Recessions associated with banking-related financial stress tend to last at least twice as long as recessions not preceded by financial stress.
  - Banking-related recessions take about five quarters to recover (typical “U-shaped” pattern), whereas recessions not preceded by financial stress revert back to pre-contraction output in about two quarters (“V-shaped”).
- Banking vs. nonbank stress:
  - Banking-system stress is more likely to be associated with severe and protracted downturns than episodes mainly in securities or FX markets.
  - Around 60 percent of the episodes of financial stress followed by slowdowns or recessions are banking-related.
  - Banking-related episodes are followed by more severe slowdowns and recessions; differences statistically significant (in many cases at the 10 percent level or better).
- Banking sector behavior around stress:
  - Bank asset growth slows significantly in banking-related stress episodes that are followed by downturns.
  - Cost of capital rises appreciably after such episodes; changes in bank assets and cost of capital in these cases are statistically significant (5 percent level or better in contrasts reported).

### Role of initial conditions, balance sheets, and credit/asset buildups
- Pre-stress build-ups increase likelihood and severity of downturns:
  - Faster rises in house prices and in the credit-to-GDP ratio during the upswing are associated with a higher probability that financial stress will be followed by a slowdown or recession.
  - Statistical tests confirm the association; variables measuring initial conditions are statistically different for episodes followed by recession versus “Other” at the five percent level or better.
- Sectoral exposure:
  - Firms with greater reliance on external financing (higher net borrowing ratios) in the run-up to stress are associated with sharper downturns.
  - Household exposure (higher household net borrowing ratio) is crucial in distinguishing episodes that turn into recessions (household exposure significant for recessions but not for slowdowns).
- Multivariate (cross-section) regressions:
  - Firms’ net borrowing ratio at the onset of stress enters significantly in almost all specifications explaining cumulative output loss.
  - Household net borrowing ratio is significant alone, and when interacted with duration, household position matters especially when the financial shock is sustained.
  - Duration of financial stress features in regressions as a proxy for shock severity.

### Financial innovation, financial-system structure, and leverage
- Arm’s-Length Index:
  - The Arm’s-Length Index (Lall, Cardarelli, and Tytell, 2006) ranges from zero to one; higher values indicate greater arm’s-length content (more market-based intermediation).
  - Despite financial innovation, banks remain central—symbiotic relationship between banks and markets persists, particularly in arm’s-length systems.
- Procyclicality of leverage:
  - Investment banks: leverage is strongly procyclical (leverage expands with asset growth).
  - Commercial banks: evidence is mixed, but commercial banks in more arm’s-length systems tend to be more procyclical.
  - Countries with more arm’s-length systems exhibit greater procyclicality of bank leverage (median regressions show positive association between Arm’s-Length Index and degree of procyclical leverage).
- Consequences for downturns:
  - Slowdowns and recessions tend to be deeper in economies with more arm’s-length financial systems, though duration is broadly similar across types.
  - Leverage ratios (asset-to-equity) in more arm’s-length systems tend to fall more sharply following stress, starting from a lower base; differences statistically significant at the 10 percent level for periods shown.
  - Important qualification: arm’s-length systems are not necessarily more prone to stress overall, and they provide advantages in resource reallocation.

### Historical context and case observations
- Six well-known banking-related stress episodes discussed: Finland (early 1990s), Sweden (early 1990s), Norway (early 1990s), Japan (1990s), United Kingdom (early 1990s), United States (early 1990s).
- Common pattern in severe cases:
  - Large pre-crisis buildups in credit, house prices, and bank asset growth correlated with deeper and longer recessions and with stronger deleveraging by households and firms.
  - Nordic countries (Finland, Sweden, Norway) exhibited the largest credit and asset booms and experienced the most dramatic collapses and deepest, longest recessions.
- Recovery patterns:
  - Recessions not preceded by financial stress: typical quick recovery (two quarters to revert to pre-contraction output).
  - Banking-related recessions: take at least twice as long to recover (typically four to five quarters).

### Policy implications and recommendations
- Early detection and monitoring:
  - Policymakers should monitor credit growth, house prices, and sectoral net borrowing (households and firms) during financial-cycle upswings as indicators of vulnerabilities.
- Prudential and macroprudential stance:
  - Prudential measures and monetary policy should pay due regard to vulnerabilities building up in balance sheets and asset prices to limit the probability that financial stress leads to large output losses.
- Crisis response and financial stability framework:
  - In episodes where balance sheets are overextended and the core of the banking system is affected, rapid policy action to recognize losses and restore capital is important to mitigate output consequences.
  - Restoring capital bases of core financial intermediaries, including broker-dealers and investment banks, is particularly important given their role in transmission of shocks to the real economy.
- Moral hazard considerations:
  - While supporting financial intermediation is important, policymakers must guard against creating inappropriate long-term incentives and limit fiscal costs of support.

### Conclusions (summary)
- Financial stress only sometimes precedes economic slowdowns or recessions, but when it does—especially if banking-related—it typically produces substantially larger and longer output losses.
- Key determinants of whether stress leads to a downturn include prior house-price and credit buildups and the degree to which firms and households rely on external financing.
- Procyclical leverage—especially in more arm’s-length financial systems—helps explain why banking stress can amplify downturns.
- Prompt actions to restore financial-intermediary capital and to contain balance-sheet vulnerabilities can reduce real economic costs, balanced against moral hazard and fiscal-cost considerations.

*Source: _wp09100 - EXECUTIVE SUMMARY (IMF Working Paper content provided).*

### Executive Summary ......................................................................................................

### _wp09100 - Executive Summary ......................................................................................................

### I. Introduction
- Section title: "Introduction"
- Purpose: frames the study and sets out the questions and scope addressed in the paper.

### II. Identifying Episodes of Financial Stress
- Section title: "Identifying Episodes of Financial Stress"
- Subsections explicitly listed:
  - "A. The Financial Stress Index"
  - "B. Episodes of Financial Stress"
- Focus: identification and measurement of financial stress episodes using a Financial Stress Index and classification of episodes.

### III. Financial Stress, Economic Slowdowns, and Recessions
- Section title: "Financial Stress, Economic Slowdowns, and Recessions"
- Subsections explicitly listed:
  - "A. Why Are Some Financial Stress Episodes Associated with Economic Slowdowns?"
  - "B. Is Banking Related Financial Stress Different?"
  - "C. Financial Imbalances and Firm and Household Financial Exposure"
- Focus: links between financial stress and macroeconomic contractions, distinctions for banking-related stress, and the role of financial imbalances and exposures.

### IV. Financial Innovation, Financial Stress, and Economic Cycles
- Section title: "Financial Innovation, Financial Stress, and Economic Cycles"
- Subsections explicitly listed:
  - "A. The Arm’s-Length Index"
  - "B. Financial Systems and Leverage"
- Focus: interactions between financial innovation, arm’s-length finance structures, leverage dynamics in financial systems, and cyclical outcomes.

### V. Financial Crisis in Historical Context
- Section title: "Financial Crisis in Historical Context"
- Focus: situating financial crises and stress episodes within historical periods and comparisons.

### VI. Conclusions
- Section title: "Conclusions"
- Focus: synthesis of findings and implications drawn by the paper.

### Supplementary Content (Appendices and Supporting Material)
- Appendices listed:
  - "1. Major Financial Stress Episodes Identified in the Literature"
  - "2. Data and Methodology"
- Appendix tables listed:
  - "II.1. Average Yearly Share of Total Bank Assets of Banks in Sample"
  - "II.2. Data  Sources"
- Tabular and graphical materials enumerated in the source for empirical support (figures and tables titles are present in the source listing).

*Source: _wp09100 - Executive Summary (table of contents and section headings as provided in the source PDF).*

### EXECUTIVE SUMMARY

### EXECUTIVE SUMMARY

### Overview and purpose
- Study period and sample: 17 advanced economies over the past 30 years.
- Objective: analyze past episodes of financial stress in banking, securities, and foreign exchange markets, identify 113 episodes of financial stress, and assess their implications for subsequent economic activity using a Financial Stress Index (FSI).
- Main focus: how financial stress—especially banking distress—affects the real economy, and which initial conditions and financial-system features determine whether stress leads to slowdowns or recessions.

### Methodology — Financial Stress Index (FSI)
- FSI construction: variance-weighted average of three subindices associated with banking, securities, and foreign exchange markets; episodes identified where a country’s FSI is more than one standard deviation above its HP-filtered trend.
- Banking-related subindex components:
  - Slope of the yield curve (short- minus long-term government yields; inverted term spread).
  - TED spread (interbank rates minus Treasury bill yield).
  - Beta of banking sector returns (recorded as non-zero only during periods when returns are negative).
- Securities-related subindex components:
  - Corporate bond spreads (corporate yields minus long-term government yields).
  - Stock market returns (monthly return multiplied by -1).
  - Time-varying stock return volatility (GARCH(1,1)).
- Foreign-exchange-related subindex component:
  - Time-varying volatility of monthly changes in the nominal effective exchange rate (GARCH(1,1)).
- Advantages emphasized:
  - High-frequency, market-based indicators comparable across 17 countries.
  - Precise dating of onset and peaks of stress episodes.
  - Ability to distinguish banking, securities, and FX stress and their interactions.

### Episodes identified and classification
- Total financial stress episodes identified: 113.
  - Banking-driven episodes: 43.
  - Securities-market episodes: 50.
  - Foreign-exchange episodes: 20.
- Banking-related episodes (where banks were dominant or second largest factor with contribution ≥ one-third): 60.
  - In 17 episodes that mainly reflected securities or FX stress, the banking variables nonetheless accounted for at least one third of the spike.
- Cross-country propagation: 87 of the 113 episodes simultaneously affected two or more countries.
- Typical episode duration (Table 1): average financial stress duration reported as 2.42 quarters.

### Key empirical findings on macroeconomic impact
- Frequency of downturns:
  - About half of the financial stress episodes were associated with an economic slowdown or recession.
  - Of 113 episodes, 29 were followed by a slowdown and 29 by a recession; 55 were not followed by an economic downturn.
- Timing:
  - Average lag between onset of financial stress and the slowdown/recession: about seven months; ~50 percent of slowdown/recessions occurred within one quarter, ~25 percent took more than a year.
- Magnitude of output losses (medians):
  - Slowdowns preceded by financial stress: median cumulative output loss of 2.8 percent of GDP.
  - Recessions preceded by financial stress: median cumulative output loss of 4.4 percent of GDP.
  - For comparison, slowdowns not preceded by financial stress: about 1.6 percent of GDP; recessions not preceded by financial stress: about 2.3 percent of GDP.
- Duration and recovery:
  - Recessions associated with banking-related financial stress tend to last at least twice as long as recessions not preceded by financial stress.
  - Recessions associated with banking-related financial stress take about five quarters to recover (typical “U-shaped” pattern), whereas recessions not preceded by financial stress revert back to pre-contraction output in about two quarters (“V-shaped”).
- Banking vs. nonbank stress:
  - Banking-system stress is more likely to be associated with severe and protracted downturns than episodes mainly in securities or FX markets.
  - Around 60 percent of the episodes of financial stress followed by slowdowns or recessions are banking-related.
  - Banking-related episodes are followed by more severe slowdowns and recessions; differences statistically significant (in many cases at the 10 percent level or better).
- Banking sector behavior around stress:
  - Bank asset growth slows significantly in banking-related stress episodes that are followed by downturns.
  - Cost of capital rises appreciably after such episodes; changes in bank assets and cost of capital in these cases are statistically significant (5 percent level or better in contrasts reported).

### Role of initial conditions, balance sheets, and credit/asset buildups
- Pre-stress build-ups increase likelihood and severity of downturns:
  - Faster rises in house prices and in the credit-to-GDP ratio during the upswing are associated with a higher probability that financial stress will be followed by a slowdown or recession.
  - Statistical tests confirm the association; variables measuring initial conditions are statistically different for episodes followed by recession versus “Other” at the five percent level or better.
- Sectoral exposure:
  - Firms with greater reliance on external financing (higher net borrowing ratios) in the run-up to stress are associated with sharper downturns.
  - Household exposure (higher household net borrowing ratio) is crucial in distinguishing episodes that turn into recessions (household exposure significant for recessions but not for slowdowns).
- Multivariate (cross-section) regressions:
  - Firms’ net borrowing ratio at the onset of stress enters significantly in almost all specifications explaining cumulative output loss.
  - Household net borrowing ratio is significant alone, and when interacted with duration, household position matters especially when the financial shock is sustained.
  - Duration of financial stress features in regressions as a proxy for shock severity.

### Financial innovation, financial-system structure, and leverage
- Arm’s-length vs. relationship-based systems:
  - The Arm’s-Length Index (Lall, Cardarelli, and Tytell, 2006) ranges from zero to one; higher values indicate greater arm’s-length content (more market-based intermediation).
  - Despite financial innovation, banks remain central—symbiotic relationship between banks and markets persists, particularly in arm’s-length systems.
- Procyclicality of leverage:
  - Investment banks: leverage is strongly procyclical (leverage expands with asset growth).
  - Commercial banks: evidence is mixed, but commercial banks in more arm’s-length systems tend to be more procyclical.
  - Countries with more arm’s-length systems exhibit greater procyclicality of bank leverage (median regressions show positive association between Arm’s-Length Index and degree of procyclical leverage).
- Consequences for downturns:
  - Slowdowns and recessions tend to be deeper in economies with more arm’s-length financial systems, though duration is broadly similar across types.
  - Leverage ratios (asset-to-equity) in more arm’s-length systems tend to fall more sharply following stress, starting from a lower base; differences statistically significant at the 10 percent level for periods shown.
  - Important qualification: arm’s-length systems are not necessarily more prone to stress overall, and they provide advantages in resource reallocation.

### Historical context and six case studies
- Six well-known banking-related stress episodes discussed: Finland (early 1990s), Sweden (early 1990s), Norway (early 1990s), Japan (1990s), United Kingdom (early 1990s), United States (early 1990s).
- Common pattern in severe cases:
  - Large pre-crisis buildups in credit, house prices, and bank asset growth correlated with deeper and longer recessions and with stronger deleveraging by households and firms.
  - Nordic countries (Finland, Sweden, Norway) exhibited the largest credit and asset booms and experienced the most dramatic collapses and deepest, longest recessions.
- Recovery patterns:
  - Recessions not preceded by financial stress: typical quick recovery (two quarters to revert to pre-contraction output).
  - Banking-related recessions: take at least twice as long to recover (typically four to five quarters).

### Policy implications and recommendations
- Early detection and monitoring:
  - Policymakers should monitor credit growth, house prices, and sectoral net borrowing (households and firms) during financial-cycle upswings as indicators of vulnerabilities.
- Prudential and macroprudential stance:
  - Prudential measures and monetary policy should pay due regard to vulnerabilities building up in balance sheets and asset prices to limit the probability that financial stress leads to large output losses.
- Crisis response and financial stability framework:
  - In episodes where balance sheets are overextended and the core of the banking system is affected, rapid policy action to recognize losses and restore capital is important to mitigate output consequences.
  - Restoring capital bases of core financial intermediaries, including broker-dealers and investment banks, is particularly important given their role in transmission of shocks to the real economy.
- Moral hazard considerations:
  - While supporting financial intermediation is important, policymakers must guard against creating inappropriate long-term incentives and limit fiscal costs of support.

### Conclusions (summary)
- Financial stress only sometimes precedes economic slowdowns or recessions, but when it does—especially if banking-related—it typically produces substantially larger and longer output losses.
- Key determinants of whether stress leads to a downturn include prior house-price and credit buildups and the degree to which firms and households rely on external financing.
- Procyclical leverage—especially in more arm’s-length financial systems—helps explain why banking stress can amplify downturns.
- Prompt actions to restore financial-intermediary capital and to contain balance-sheet vulnerabilities can reduce real economic costs, balanced against moral hazard and fiscal-cost considerations.

*Source: _wp09100 - EXECUTIVE SUMMARY (IMF Working Paper content provided).*

### APPENDIX I. MAJOR FINANCIAL STRESS EPISODES IDENTIFIED IN THE LITERATURE

### APPENDIX I. MAJOR FINANCIAL STRESS EPISODES IDENTIFIED IN THE LITERATURE

### Chronological listing of major financial stress episodes
- 1982
  - Savings and Loans Crisis begins. Several small midwest banks in the United States collapse, leading to bank runs on some larger U.S. banks including Continental Illinois.
  - Latin American Debt Crisis. In August, Mexico declared that it would no longer be able to service its debt. Subsequently, credit lines were cut and many countries in the region could not roll over their short-term debt obligations, thus generating a systemic crisis.
- 1984
  - S&L Crisis grows. During the first quarter of the year, the Federal Reserves and the Federal Deposit Insurance Corporation (FDIC) rescue Continental Illinois (US$ 10 billion).
- 1985
  - S&L Crisis intensifies. In March, emergency bank holiday in Ohio to stave off run on deposits (Home State Savings Bank of Cincinnati collapsed). First significant S&L failures in Maryland, but still not yet widespread.
  - Plaza Accord (September). U.S.-initiated devaluation, coordinated with Japan and Germany.
  - Second Latin American Debt Crisis. Argentina, Mexico, and Nigeria can not meet debt obligations, Baker initiates debt rescheduling.
- 1986
  - S&L Crisis spreads. U.S. Federal S&L Insurance Corporation (FSLIC) declares bankruptcy.
- 1987
  - Louvre Accord. Before the Accord, the U.S. dollar hits record low (50 percent off 1985 peak). U.S.-initiated coordinated intervention to support the dollar (lasts about 18 months).
  - October 1987—Stock Market Crash. On October 19, 1987, Dow Jones fell by 23 percent (Mishkin and White, 2002; furthermore, depending on the exact index used, this represent a 25 standard deviation shock). Brokerage firms and specialists were severely in need of additional funds to finance their activities. Despite the financial strength of these firms, the heightened uncertainty implied that banks were reluctant to lend to the securities industry at a time when it was most needed.
  - Brazil declares debt service moratorium.
- 1990
  - Junk bond market collapse in the United States.
  - Nikkei Crash. Tokyo stock market falls by 50 percent.
  - Drexel Burnham Lambert (DBL) bankruptcy (February). DBL, at its height, was the fifth-largest investment bank in the United States, which first rose to prominence and then was driven into bankruptcy in February 1990 by its involvement in illegal activities in the junk bond market.
- 1991
  - Scandinavian banking crises. Finland most severely affected relative to Norway and Sweden.
- 1992
  - ERM crisis. The European Exchange Rate Mechanism (ERM) is effectively abandoned. The British government was forced to withdraw the pound from the ERM on Wednesday September 16, 1992 after they were unable to keep the Sterling above the agreed lower limit.
- 1994
  - Global bond rout (first quarter).
  - Turkish currency crisis—Lira depreciated against the dollar by about 50 percent.
  - Mexican “Tequila” Crisis (started in December 1994).
- 1997
  - Asian Crisis. Begins in July 2, 1997 with the float of the Thai baht. Indonesia (August), Korea (November), and Malaysia (December) get affected by the crisis sequentially.
- 1998
  - Russian Crisis (August).
  - LTCM Collapse (September).
  - S&P 500 fell by 13 percent in two months.
- 1999
  - Brazilian Devaluation (January).
- 2000
  - Stock market crash. NASDAQ declines by 40 percent during March and April. Furthermore, the decline in S&P began in August 2000, falling 23 percent by December 2001. However, stock collapse not evenly felt across the market, but higher tech and higher risk stocks severely affected.
- 2001
  - September (9/11) attacks on the United States.
  - Enron scandal. The scandal involved Enron Corporation and its accounting firm Arthur Andersen revealed in late 2001. After a series of revelations involving irregular accounting procedures conducted throughout the 1990s, Enron was on the verge of bankruptcy by November of 2001. Eventually, Enron filed for bankruptcy on December 2, 2001—at the time, the largest bankruptcy in history.
  - Turkish financial crisis (worst in post-war history) occurs in February.
- 2002
  - The demise of Arthur Andersen, which was convicted of obstruction of justice in conjunction with the Enron scandal on June 15, 2002.
  - WorldCom files for bankruptcy on July 21, 2002, the largest in U.S. history at the time.
  - Argentine crisis. The 10-year currency board (Convertibility) is abandoned during January 2002, and default in the last week of 2001.
- 2003
  - Mutual fund scandals. On September 3, 2003, the New York State Attorney General announced he had “obtained evidence of widespread illegal trading schemes, ‘late trading’ and ‘market timing,’ that potentially cost mutual fund shareholders billions of dollars annually." On April 28, 2003, every major U.S. investment bank, including Merrill Lynch, Goldman Sachs, Morgan Stanley, Citigroup, Credit Suisse First Boston, Lehman Brothers Holdings, J.P. Morgan Chase, UBS Warburg, and U.S. Bancorp Piper Jaffray, were found to have aided and abetted efforts to defraud investors. The firms were fined a total of $1.4 billion by the Securities and Exchange Commission (SEC), triggering the creation of a Global Research Analyst Settlement Fund.
- 2006
  - May/June. Tightening global liquidity conditions triggered increased risk aversion and a substantial retrenchment by investors from a wide range of risky assets. Many emerging market countries adversely affected by sell-off (including Brazil, Hungary, Indonesia, Poland, South Africa, and Turkey).

### Notable quantitative and contextual details cited in the text
- Continental Illinois rescue: US$ 10 billion (1984).
- October 19, 1987 Dow Jones decline: 23 percent; described also as a 25 standard deviation shock (depending on index).
- S&L bailout required a bailout of $150 billion (footnote context in the source).
- Dow and S&P major decline beginning in August (footnote context): Dow fell by 16 percent and S&P fell by 15 percent.
- Nikkei Crash: Tokyo stock market falls by 50 percent (1990).
- NASDAQ decline in 2000: 40 percent during March and April.
- S&P decline starting August 2000: falling 23 percent by December 2001.
- SEC fines related to mutual fund/investment bank settlement: $1.4 billion total.
- Goldman Sachs penalty context: agreed to pay over $9.3 million in penalties—for a total of 120 million (footnote context).

*Source: APPENDIX I. MAJOR FINANCIAL STRESS EPISODES IDENTIFIED IN THE LITERATURE (excerpt).*

### REFERENCES

### _wp09100 - REFERENCES

### Monographs and books
- Conover, W.J., 1980, Practical Nonparametric Statistics (New York: John Wiley and Sons, 2nd ed.).
- Kindleberger, Charles, Robert Aliber, and Roberto Solow, 2005, Manias, Panics, and Crashes: A History of Financial Crises (Wiley Investment Classics).
- Minsky, Hyman, 1992, “The Financial Instability Hypothesis,” The Jerome Levy Economics Institute Working Paper, No. 74 (May).
- Kindelberger, Charles, Robert Aliber, and Roberto Solow, 2005, Manias, Panics, and Crashes: A History of Financial Crises (Wiley Investment Classics).

### Journal articles and working papers
- Adrian, Tobias and Hyun Song Shin, 2007, “Liquidity and Leverage,” Federal Reserve Bank of New York Staff Reports, No. 328.
- Adrian, Tobias and Hyun Song Shin, 2008, “Financial Intermediary Leverage and Value at Risk,” Working Paper (Federal Reserve Bank of New York and Princeton University).
- Altunbas, Yener, Leonardo Gambacorta, and David Marqués, 2007, “Securitization and the Bank Lending Channel,” Working Paper Series, No. 838 (Frankfurt: European Central Bank).
- Bernanke, Ben, and Cara Lown, 1991, “The Credit Crunch,” Brookings Papers on Economic Activity, Vol. 22 (1991–2), pp. 205–48.
- Bernanke, Ben, and Mark Gertler, 1995, “Inside the Black Box: The Credit Channel of Monetary Policy Transmission,” Journal of Economic Perspectives, Vol. 9 (Autumn), pp. 27–48.
- Bernanke, Ben, Mark Gertler, and Simon Gilchrist, 1999, “The Financial Accelerator in a Quantitative Business Cycle Framework,” Handbook of Macroeconomics, Vol. 1C, pp. 1341–93 (Elsevier: Amsterdam).
- Bollerslev, Tim, Ray Yeutien Chou, and Kenneth F. Kroner, 1992, “ARCH Modeling in Finance: A Review of the Theory and Empirical Evidence,” Journal of Econometrics, Vol. 52, No. 1-2, pp. 5-59.
- Bordo, Michael D. and Olivier Jeanne, 2002, “Boom-Busts in Asset Prices, Economic Instability, and Monetary Policy,” NBER Working Papers 8966 (Cambridge, Massachusetts: National Bureau of Economic Research).
- Borio, Claudio, 2007, “Change and Constancy in the Financial System: Implications for Financial Distress and Policy,” BIS Working Papers, No. 237 (October).
- Caprio, Gerard, and Daniela Klingebiel, 2006, “Episodes of Systematic and Borderline Financial Crises,” (Washington: World Bank).
- Cardarelli, Roberto, Subir Lall, and Irina Tytell, 2006, World Economic Outlook, September 2006: How Do Financial Systems Affect Economic Cycles? World Economic and Financial Surveys (Washington: International Monetary Fund).
- Cardarelli, Roberto, Deniz Igan, and Alessandro Rebucci, 2008, World Economic Outlook, April 2008: The Changing Housing Cycle and the Implications for Monetary Policy, World Economic and Financial Surveys (Washington: International Monetary Fund).
- Cardarelli, Roberto, Selim Elekdag, and Subir Lall, 2008, World Economic Outlook, October 2008: Financial Stress and Economic Downturns, World Economic and Financial Surveys (Washington: International Monetary Fund).
- Cihak, Martin, and Petya Koeva Brooks, “From Subprime Loans to Subprime Growth? Evidence for the Euro Area,” forthcoming, IMF Working Paper (Washington: International Monetary Fund).
- Claessens, Stijn., M. Ayhan. Kose, and Marco. E. Terrones, 2008, “What Happens During Recessions, Crunches and Busts?” IMF Working Paper 08/274 (Washington: International Monetary Fund).
- Demirguc-Kunt, Asli, Enrica Detragiache, and Poonam Gupta, 2006, “Inside the Crisis: An Empirical Analysis of Banking Systems in Distress,” Journal of International Money and Finance, Vol. 25, pp. 702–18.
- Edison, Hali, 2003, “Do Indicators of Financial Crises Work? An Evaluation of an Early Warning System,” International Journal of Finance and Economics, Vol. 8, pp. 11–53.
- Edwards, Sebastian, 2007, “On Current Account Surpluses and the Correction of Global Imbalances,” NBER Working Paper No. 12904 (Cambridge, Massachusetts: National Bureau of Economic Research).
- Eichengreen, Barry and Michael D. Bordo, 2002, “Crises Now and Then: What Lessons from the Last Era of Financial Globalization,” NBER Working Paper No. 8716 (Cambridge, Massachusetts: National Bureau of Economic Research).
- Fama, Eugene F., Lawrence Fisher, Michael C. Jensen, and Richard Roll, 1969, “The Adjustment of Stock Prices to New Information,” International Economic Review, Vol. 10, No. 1 (February), pp. 1–21.
- Frankel, Jeffrey, and Andrew Rose, 1996, “Currency Crashes in Emerging Markets: An Empirical Treatment,” Journal of International Economics, Vol. 41, No. 3/4, pp. 351–66.
- Freund, Caroline, 2005, “Current Account Adjustment in Industrial Countries,” Journal of International Money and Finance, Vol. 24, Issue 8 (December), pp. 1278–98.
- Gibbons, Michael, R., 1987, “The Interrelations of Finance and Economics: Empirical Perspectives,” American Economic Review Papers and Proceedings, Vol. 77, No. 2, pp. 35–41.
- Goodhart, Charles, 1996, “An Incentive Structure for Financial Regulation,” LSE Financial Markets Group Special Paper Series, No. 88, pp. 1–22 (July) (United Kingdom: London School of Economics and Political Science).
- Harding, Don, and Adrian Pagan, 2002, “Dissecting the Cycle: A Methodological Investigation,” Journal of Monetary Economics, Vol. 49, No. 2 (March), pp. 365–81.
- Iacoviello, Matteo, 2005, “House Prices, Borrowing Constraints, and Monetary Policy in the Business Cycle,” American Economic Review, Vol. 95 (June), pp. 739–64.
- Illing, Mark and Ying Liu, 2006, “Measuring Financial Stress in a Developed Country: An Application to Canada,” Journal of Financial Stability, Vol. 2, No. 3 (October), pp. 243–65.
- Mendoza, Enrique and Marco Terrones, 2008, “An Anatomy of Credit Booms: Evidence from Macro Aggregates and Micro Data,” NBER Working Paper No. 14049 (Cambridge, Massachusetts, National Bureau of Economic Research).
- Morsink, James, Thomas Helbling, and Stephen Tokarick, 2002, World Economic Outlook, April 2002: Recessions and Recoveries, World Economic and Financial Surveys (Washington: International Monetary Fund).
- JP Morgan Research, 2008, “Credit and Growth: The Case of the Euro Area,” (June 19).
- Kaminsky, Graciela, and Carmen Reinhart, 1999, “The Twin Crises: The Causes of Banking and Balance-of-Payments Problems,” American Economic Review, Vol. 89, No. 3 (June), pp. 473–500.
- Kashyap, Anil, and Jeremy Stein, 1995, “The Impact of Monetary Policy on Bank Balance Sheets,” Carnegie-Rochester Conference Series on Public Policy, Vol. 42 (June), pp. 151–95.
- Kashyap, Anil, Raghuram Rajan, and Jeremy Stein, 2008, “Rethinking Capital Regulation,” paper prepared for the Federal Reserve Bank of Kansas City Symposium at Jackson Hole.
- Kiyotaki, Nobuhiro, and John Moore, 1997, “Credit Cycles,” Journal of Political Economy, Vol. 105 (April), pp. 211–48.
- Mann, H.B., and D.R. Whitney, 1947, “On a Test of Whether One of Two Random Variables is Stochastically Larger Than the Other,” Annals of Mathematical Statistics, Vol. 18, pp. 50–60.
- Melander, Ola, and Tamim Bayoumi, 2008, “Credit Matters: Empirical Evidence on U.S. Macro-Financial Linkages,” IMF Working Paper 08/169 (Washington: International Monetary Fund).
- Milesi-Ferretti, Gian Maria, and Assaf Razin, 1998, “Sharp Reductions in Current Account Deficits: An Empirical Analysis,” European Economic Review, Vol. 42 (April), pp. 897–908.
- Rajan, Raghuram, and Luigi Zingales, 2003, “Banks and Markets: the Changing Character of European Finance,” CEPR Discussion Papers, No. 3865.
- Reinhart, Carmen and Kenneth Rogoff, 2008a, “Is the 2007 U.S. Sub-Prime Financial Crisis so Different? An International Historical Comparison,” NBER Working Papers 13761 (National Bureau of Economic Research, Inc.).
- Reinhart, Carmen and Kenneth Rogoff, 2008b, “This Time is Different: A Panoramic View of Eight Centuries of Financial Crises,” NBER Working Papers 13882 (National Bureau of Economic Research, Inc.).
- Reinhart, Carmen and Kenneth Rogoff, 2004, “The Modern History of Exchange Rate Arrangements: A Reinterpretation,” Quarterly Journal of Economics, Vol. CXIX, No. 1 (February), pp. 1–48.
- Shiller, Robert J., 1999, “Measuring Bubble Expectations and Investor Confidence,” NBER Working Papers 7008 (National Bureau of Economic Research, Inc.).
- Shin, Hyun Song, 2008, “Reflections on Modern Bank Runs: A Case Study of Northern Rock,” Working Paper (Princeton University).
- Wilcoxon, Frank, 1945, “Individual Comparisons By Ranking Methods,” Biometrics Bulletin, Vol. 1, pp. 80–83.

### Methodological and statistical sources
- Mann, H.B., and D.R. Whitney, 1947, “On a Test of Whether One of Two Random Variables is Stochastically Larger Than the Other,” Annals of Mathematical Statistics, Vol. 18, pp. 50–60.
- Wilcoxon, Frank, 1945, “Individual Comparisons By Ranking Methods,” Biometrics Bulletin, Vol. 1, pp. 80–83.
- Bollerslev, Tim, Ray Yeutien Chou, and Kenneth F. Kroner, 1992, “ARCH Modeling in Finance: A Review of the Theory and Empirical Evidence,” Journal of Econometrics, Vol. 52, No. 1-2, pp. 5-59.
- Conover, W.J., 1980, Practical Nonparametric Statistics (New York: John Wiley and Sons, 2nd ed.).

*Content compiled from the REFERENCES section of the source PDF.*

---


_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2009/_wp09100.pdf_