## _wp11241

## Source details

**Canonical URL:** [_wp11241](https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2011/_wp11241.pdf)

## Other formats

- [Markdown version](/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2011/_wp11241.pdf.md)
- [Structured JSON version](/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2011/_wp11241.pdf.json)

---

### Overview
- Motivated by rapid credit growth across many emerging economies, particularly in Asia.
- Event study identifies 99 credit booms, of which 39 and 60 originated in advanced and emerging economies, respectively.
- Episodes of excessive credit growth—credit booms—tend to generate financial imbalances and often end abruptly, frequently as financial crises.
- Historically, credit booms in emerging Asia were associated with a higher incidence of crises relative to other emerging economies.

### Main findings
- As credit booms build, they are jointly associated with deteriorating bank and corporate balance sheet soundness and overheating symptoms including:
  - large capital inflows (including less stable bank flows),
  - widening current account deficits,
  - buoyant asset prices,
  - strong domestic demand.
- While credit booms are associated with episodes of large capital inflows, international interest rates (a proxy for global liquidity) are virtually flat during these periods, implying an important role for domestic factors in driving credit growth across emerging economies.
- Loose macroeconomic policy stances appear to have contributed to the build-up of credit booms:
  - Domestic policy rates were below trend during the pre-peak phase of credit booms in emerging economies.
  - Monetary policy appears especially important as a driver of real credit growth across emerging economies, including those in Asia.

### Identification methodology (key technical points)
- Sample: annual macroeconomic, financial, corporate-, and banking-level data from 1960–2010.
- Credit booms definition:
  - A boom occurs when the cyclical component of real credit exceeds 1.55 times its standard deviation (an event in the top 6th percentile of the distribution).
  - Baseline threshold: 1.55; sensitivity check uses 1.96; Mendoza and Terrones (2008) used 1.75.
- Trend extraction: Hodrick-Prescott (HP) filter with penalty parameter set to 100 for annual data; thresholds are country-specific.
- Credit aggregate: primarily bank credit to the private sector (IFS line 22d); where available, broader credit (IFS line 42d) is used to capture nonbank intermediation.
- Pattern-recognition approach used to date start, peak, and end of booms; one standard deviation used to pin down start and end dates.

### What credit booms look like (empirical regularities)
- Sample breakdown:
  - Of 99 booms, 60 occurred in emerging economies; among these 60, 16 occurred in Asian emerging markets and 44 in other emerging markets.
- Duration:
  - A typical boom lasts about three years, with build-up, peak, and ending phases each lasting about one year on average.
  - Booms in Asia are more asymmetric and tend to end more abruptly.
- Temporal clustering:
  - Notable clusters around 1997 and 2007.
- Capital inflows:
  - Almost 60 percent of all emerging economy credit booms were preceded by an episode of large capital inflows.
- Rapid credit growth versus booms:
  - Episodes of rapid credit growth (threshold = one standard deviation) have about a fifty-fifty chance of mutating into a boom.
- Monitoring thresholds:
  - Real credit growth exceeding 15 percent and nominal credit growth exceeding 20 percent could warrant closer financial sector surveillance (reported medians suggest these levels could be concern thresholds).

### Dynamics and warning signs — External factors
- Pre-peak external patterns:
  - Net private capital inflows (as percent of GDP) during pre-peak for typical booms: about 2 percent (booms ending smoothly), 4 percent (booms ending abruptly), and 6 percent (the 13 worst boom-bust episodes).
  - Sharp reversals occur after the peak; for the 13 worst boom-bust episodes, reversals exceeded 10 percentage points.
  - Composition matters: booms that ended in credit busts were characterized by large portfolio and other (bank) flows; bank flows are especially precarious.
  - Example reversals associated with the worst boom-busts: current account reversal of about 10 percentage points, real exchange rate depreciation of about 25 percent.
- International interest rates:
  - Federal funds rate (proxy for global liquidity) is virtually flat throughout the seven-year windows centered on boom peaks.

### Dynamics and warning signs — Domestic factors
- Real sector:
  - Real GDP tends to run above trend by about 2 to 4 percent in the pre-peak phase for booms ending abruptly.
  - After peak, sharp contractions follow: for the 13 worst cases, real GDP was 4 percent below trend post-peak and on a downtrend three years after the peak.
  - Real domestic demand can fall below trend by up to 8 percent following busts.
  - Booms ending abruptly are often associated with “creditless recoveries.”
- Prices:
  - Credit booms do not appear to have a major effect on inflation during build-up; inflation deviates modestly from trend during the ending phase (pass-through of depreciations).
- Policy stance:
  - Policy and lending rates are below trend in the pre-peak phase; lower pre-peak policy rates are most prominent for the 13 worst boom-bust episodes.
  - Pre-peak nominal policy rate reductions bring down lending rates and cost of borrowing, fueling asset valuations and risk-taking.
  - During peaks/ending phases of worst episodes: spikes in policy rates, sharp decline in reserves, and dramatic nominal (effective) exchange rate depreciation (reported over 60 percent peak-to-trough in the worst cases).
  - Fiscal policy tended to be procyclical in pre-peak phases (overall balance and real government consumption deviate), likely amplifying downturns.

### Financial sector and corporate balance sheets
- Bank balance sheets:
  - Build-up phase characterized by deterioration in bank balance sheet soundness: bank credit-to-total assets and credit-to-M2 ratios rise; nondeposit (non-core) liabilities increase as share of total liabilities.
  - Increased non-core liabilities and foreign-currency-denominated liabilities point to funding via capital inflows and shorter-maturity bank flows.
  - Deterioration in credit quality often materializes post-bust as substantially higher nonperforming loans.
  - Bank profitability appears healthy pre-peak but collapses in busts.
- Corporate sector:
  - Lower policy rates reduce firm-level average interest rates, incentivizing leverage.
  - Corporate leverage rises sharply during build-up for booms that end in busts.
  - Return on equity and P/E ratios are inflated pre-peak; Rajan-Zingales (RZ) index (external finance dependence) is higher for booms that ended abruptly.
  - CAPEX and investment patterns mirror credit expansion; when credit retracts, “creditless” recoveries constrain firms to internal financing.

### Cross-country and sample-wide observations (99 booms)
- Broader sample differences:
  - Real credit and inflation deviations from trend are large for emerging economies; however, GDP and major demand components can be more volatile in advanced economies during booms.
  - Emerging economy current account deficits are more often financed by non-FDI flows—particularly other (bank) flows—whereas advanced economy deficits are more often financed by portfolio flows.
- Monetary policy role:
  - Loose pre-peak monetary policy appears associated with the build-up of credit booms in both advanced and emerging economies.
  - Firm-level data show especially striking links between low pre-peak interest rates and higher leverage, CAPEX, and external financing dependence in emerging economies.
- Robustness:
  - Main conclusions are robust to alternative thresholds (1.96) and alternative specifications; lowering threshold to 1.55 enabled identification of additional booms (total 99 versus 49 in Mendoza and Terrones (2008)).

### Policy implications and recommendations
- Widen perimeter of financial supervision:
  - Rapid rise in nonbank intermediation can hide credit booms; monitoring must extend beyond traditional bank credit aggregates to capture vulnerabilities arising from nonbank institutions and off-balance-sheet channels.
- Monitor bank liability composition:
  - Tracking non-core liabilities and foreign-currency-denominated liabilities of banks can provide early signals of the financial cycle and looming vulnerabilities.
- Monetary policy considerations:
  - Low domestic policy rates during pre-peak phases appear associated with the build-up of credit booms; monetary authorities should account for financial-stability externalities when setting policy stances.
  - Price stability alone (inflation targeting) may not ensure financial stability; macroprudential considerations and tools are important complements.
- Capital flow and macroprudential measures:
  - Given the role of volatile bank and portfolio flows in financing current account deficits during booms, policies managing the composition and volatility of capital inflows can reduce the risk of abrupt reversals.
- Fiscal policy:
  - Avoid procyclical fiscal stances that amplify business cycles in boom-bust episodes; countercyclical fiscal buffers can mitigate post-bust contractions.
- Early-warning indicators:
  - Persistent real and nominal credit growth above 15 percent and 20 percent, respectively, and rapid increases in bank nondeposit liabilities and corporate leverage warrant closer surveillance and possibly pre-emptive policy responses.

### Caveats and research directions
- Event-study nature:
  - Results are stylized facts and should not be interpreted as causal; structural models are needed to establish causality and quantify mechanisms.
- Data limitations:
  - BankScope and Worldscope coverage limitations, and limited availability of nonbank credit series for many countries, constrain some analyses.
- Future research:
  - Develop structural models to probe causal links, quantify policy trade-offs, and run counterfactual scenarios to inform policymaking.

### Conclusion (policy-relevant summary)
- Since 2009, elevated credit growth in many emerging economies raises concern because credit booms are typically associated with growing financial imbalances and tend to end abruptly—especially in emerging Asia.
- Two principal policy-relevant findings:
  - Loose macroeconomic policy stances—particularly low domestic policy rates during pre-peak phases—appear to have contributed to the build-up of credit booms, which coincide with bank and corporate balance sheet vulnerabilities, buoyant asset prices, strong domestic demand, widening current account deficits, and large capital inflows.
  - Although credit booms are associated with large capital inflows, international interest rates are virtually flat during these periods; domestic factors—especially monetary policy—are important drivers of real credit growth in emerging economies.
- The paper provides stylized facts to inform policymakers and motivate structural research to analyze causality and policy counterfactuals.

*Source: IMF working paper — Executive Summary (authors’ calculations and figures as presented in the content unit).*

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

### Executive Summary

### Structure of the document
- I. Introduction
- II. How are Credit Booms Identified?
  - A. Identifying Credit Booms: An Example
  - B. Focusing Only on Bank Credit Could Yield Misleading Policy Implications
- III. What Do Credit Booms Look Like?
- IV. The Dynamics of Credit Booms
  - A. External Factors
  - B. Domestic Factors
- V. 99 Credit Balloons
  - A. Credit Booms Across Advanced and Emerging Economies
- VI. Conclusion
- References

### Figures (listed in the source)
- 1.   Nominal Credit to Private Sector
- 2.   Crises Associated with Emerging Market Credit Booms
- 3.   Indonesia: Identifying Credit Booms
- 4.   Korea: Identifying Credit Booms
- 5.   Credit Dynamics during Booms
- 6.   Credit Booms: Duration
- 7.   Peaks of Credit Booms Over Time
- 8.   Credit Booms in Emerging Economies Associated with Episodes of Capital Inflows
- 9.   Credit Booms: External Sector
- 10. Credit Booms: Real Sector
- 11. Credit Booms: The Role of Policies
- 12. Credit Booms and Financial Instability
- 13. Credit Booms: Corporate Sector
- 14. Advanced versus Emerging Economics: Real Sector
- 15. Advanced versus Emerging Economics: Real GDP
- 16. Advanced versus Emerging Economics: External Sector
- 17. Advanced versus Emerging Economics: The Role of Policies
- 18. Advanced versus Emerging Economics:Credit Booms and Financial Instability
- 19. Advanced versus Emerging Economics: Corporate Sector

### Tables (listed in the source)
- 1.   Credit Booms, Capital Inflows, and Crises
- 2.   Rapid Credit Growth and Booms
- 3.   Credit Booms Associated with Crises
- 4.   Pre-Peak Credit Growth

*Source: _wp11241 - Executive Summary*

### Executive Summary

### _wp11241 - Executive Summary

### Overview
- Motivated by rapid credit growth across many emerging economies, particularly in Asia.
- Event study identifies 99 credit booms, of which 39 and 60 originated in advanced and emerging economies, respectively.
- Episodes of excessive credit growth—credit booms—tend to generate financial imbalances and often end abruptly, frequently as financial crises. Historically, credit booms in emerging Asia were associated with a higher incidence of crises relative to other emerging economies.

### Main findings
- As credit booms build, they are jointly associated with deteriorating bank and corporate balance sheet soundness and overheating symptoms including:
  - large capital inflows (including less stable bank flows),
  - widening current account deficits,
  - buoyant asset prices,
  - strong domestic demand.
- While credit booms are associated with episodes of large capital inflows, international interest rates (a proxy for global liquidity) are virtually flat during these periods, implying an important role for domestic factors in driving credit growth across emerging economies.
- Loose macroeconomic policy stances appear to have contributed to the build-up of credit booms:
  - Domestic policy rates were below trend during the pre-peak phase of credit booms in emerging economies.
  - Monetary policy appears especially important as a driver of real credit growth across emerging economies, including those in Asia.

### Identification methodology (key technical points)
- Sample: annual macroeconomic, financial, corporate-, and banking-level data from 1960–2010.
- Credit booms definition:
  - A boom occurs when the cyclical component of real credit exceeds 1.55 times its standard deviation (an event in the top 6th percentile of the distribution).
  - Baseline threshold: 1.55; sensitivity check uses 1.96; Mendoza and Terrones (2008) used 1.75.
- Trend extraction: Hodrick-Prescott (HP) filter with penalty parameter set to 100 for annual data; thresholds are country-specific.
- Credit aggregate: primarily bank credit to the private sector (IFS line 22d); where available, broader credit (IFS line 42d) is used to capture nonbank intermediation.
- Pattern-recognition approach used to date start, peak, and end of booms; one standard deviation used to pin down start and end dates.

### What credit booms look like (empirical regularities)
- Sample breakdown: of 99 booms, 60 occurred in emerging economies; among these 60, 16 occurred in Asian emerging markets and 44 in other emerging markets.
- Duration: a typical boom lasts about three years, with build-up, peak, and ending phases each lasting about one year on average. Booms in Asia are more asymmetric and tend to end more abruptly.
- Temporal clustering: notable clusters around 1997 and 2007 in the sample.
- Capital inflows:
  - Credit booms are tightly interconnected with episodes of large (net) capital inflows.
  - Almost 60 percent of all emerging economy credit booms were preceded by an episode of large capital inflows.
- Rapid credit growth versus booms:
  - Episodes of rapid credit growth (threshold = one standard deviation) have about a fifty-fifty chance of mutating into a boom.
- Monitoring thresholds:
  - Real credit growth exceeding 15 percent and nominal credit growth exceeding 20 percent could warrant closer financial sector surveillance (reported medians suggest these levels could be concern thresholds).

### Dynamics and warning signs

External factors
- Pre-peak external patterns:
  - Net private capital inflows (as percent of GDP) during pre-peak for typical booms: about 2 percent (booms ending smoothly), 4 percent (booms ending abruptly), and 6 percent (the 13 worst boom-bust episodes).
  - Sharp reversals of these flows occur after the peak; for the 13 worst boom-bust episodes, reversals exceeded 10 percentage points.
  - Composition matters: booms that ended in credit busts were characterized by large portfolio and other (bank) flows; bank flows are especially precarious.
  - Example external reversals associated with the worst boom-busts: current account reversal of about 10 percentage points, real exchange rate depreciation of about 25 percent.
- International interest rates:
  - Federal funds rate (proxy for global liquidity) is virtually flat throughout the seven-year windows centered on boom peaks, suggesting global interest rate shocks are not the proximate trigger of booms.

Domestic factors
- Real sector:
  - Real GDP tends to run above trend by about 2 to 4 percent in the pre-peak phase for booms ending abruptly; after peak, sharp contractions follow (for the 13 worst cases, real GDP was 4 percent below trend post-peak and on a downtrend three years after the peak).
  - Real domestic demand can fall below trend by up to 8 percent following busts.
  - Booms ending abruptly are often associated with “creditless recoveries.”
- Prices:
  - Credit booms do not appear to have a major effect on inflation during build-up; inflation deviates modestly from trend during the ending phase (pass-through of depreciations).
- Policy stance:
  - Policy and lending rates are below trend in the pre-peak phase; lower pre-peak policy rates are most prominent for the 13 worst boom-bust episodes.
  - Pre-peak nominal policy rate reductions bring down lending rates and cost of borrowing, fueling asset valuations and risk-taking.
  - During peaks/ending phases of worst episodes: spikes in policy rates, sharp decline in reserves, and dramatic nominal (effective) exchange rate depreciation (reported over 60 percent peak-to-trough in the worst cases).
  - Fiscal policy tended to be procyclical in pre-peak phases (overall balance and real government consumption deviate), likely amplifying downturns.

Financial sector and corporate balance sheets
- Bank balance sheets:
  - Build-up phase characterized by deterioration in bank balance sheet soundness: bank credit-to-total assets and credit-to-M2 ratios rise; nondeposit (non-core) liabilities increase as share of total liabilities.
  - Increased non-core liabilities and foreign-currency-denominated liabilities point to funding via capital inflows and shorter-maturity bank flows.
  - Deterioration in credit quality often materializes post-bust as substantially higher nonperforming loans.
  - Bank profitability appears healthy pre-peak but collapses in busts.
- Corporate sector:
  - Lower policy rates reduce firm-level average interest rates, incentivizing leverage.
  - Corporate leverage rises sharply during build-up for booms that end in busts.
  - Return on equity and P/E ratios are inflated pre-peak; Rajan-Zingales (RZ) index (external finance dependence) is higher for booms that ended abruptly.
  - CAPEX and investment patterns mirror credit expansion; when credit retracts, “creditless” recoveries constrain firms to internal financing.

### Cross-country and sample-wide observations (99 booms)
- Broader sample differences:
  - Real credit and inflation deviations from trend are large for emerging economies; however, GDP and major demand components can be more volatile in advanced economies during booms (puzzling result discussed in text).
  - Emerging economy current account deficits are more often financed by non-FDI flows—particularly other (bank) flows—whereas advanced economy deficits are more often financed by portfolio flows.
- Monetary policy role:
  - Loose pre-peak monetary policy appears associated with the build-up of credit booms in both advanced and emerging economies.
  - Firm-level data show especially striking links between low pre-peak interest rates and higher leverage, CAPEX, and external financing dependence in emerging economies.
- Robustness:
  - Main conclusions are robust to alternative thresholds (1.96) and alternative specifications; lowering threshold to 1.55 enabled identification of additional booms (total 99 versus 49 in Mendoza and Terrones (2008)).

### Policy implications and recommendations
- Widen perimeter of financial supervision:
  - Rapid rise in nonbank intermediation can hide credit booms; monitoring must extend beyond traditional bank credit aggregates to capture vulnerabilities arising from nonbank institutions and off-balance-sheet channels.
- Monitor bank liability composition:
  - Tracking non-core liabilities and foreign-currency-denominated liabilities of banks can provide early signals of the financial cycle and looming vulnerabilities.
- Monetary policy considerations:
  - Low domestic policy rates during pre-peak phases appear associated with the build-up of credit booms; monetary authorities should account for financial-stability externalities when setting policy stances.
  - Price stability alone (inflation targeting) may not ensure financial stability; macroprudential considerations and tools are important complements.
- Capital flow and macroprudential measures:
  - Given the role of volatile bank and portfolio flows in financing current account deficits during booms, policies managing the composition and volatility of capital inflows can reduce the risk of abrupt reversals.
- Fiscal policy:
  - Avoid procyclical fiscal stances that amplify business cycles in boom-bust episodes; countercyclical fiscal buffers can mitigate post-bust contractions.
- Early-warning indicators:
  - Persistent real and nominal credit growth above 15 percent and 20 percent, respectively, and rapid increases in bank nondeposit liabilities and corporate leverage warrant closer surveillance and possibly pre-emptive policy responses.

### Caveats and research directions
- Event-study nature:
  - Results are stylized facts and should not be interpreted as causal; structural models are needed to establish causality and quantify mechanisms.
- Data limitations:
  - BankScope and Worldscope coverage limitations, and limited availability of nonbank credit series for many countries, constrain some analyses.
- Future research:
  - Develop structural models to probe causal links, quantify policy trade-offs, and run counterfactual scenarios to inform policymaking.

### Conclusion (policy-relevant summary)
- Since 2009, elevated credit growth in many emerging economies raises concern because credit booms are typically associated with growing financial imbalances and tend to end abruptly—especially in emerging Asia.
- Two principal policy-relevant findings:
  - Loose macroeconomic policy stances—particularly low domestic policy rates during pre-peak phases—appear to have contributed to the build-up of credit booms, which coincide with bank and corporate balance sheet vulnerabilities, buoyant asset prices, strong domestic demand, widening current account deficits, and large capital inflows.
  - Although credit booms are associated with large capital inflows, international interest rates are virtually flat during these periods; domestic factors—especially monetary policy—are important drivers of real credit growth in emerging economies.
- The paper provides stylized facts to inform policymakers and motivate structural research to analyze causality and policy counterfactuals.

*Source: IMF working paper — Executive Summary (authors’ calculations and figures as presented in the content unit).*

### References

### References

### Credit booms, lending cycles, and financial crises
- Abiad, A., G. Dell'Ariccia, and B. Li, 2011, “Creditless Recoveries,” IMF Working Paper 11/58 (Washington: International Monetary Fund).
- Bakker, B.B., and, A.M. Gulde, 2010, “The Credit Boom in the EU New Member States: Bad Luck or Bad Policies?” IMF Working Paper 10/130 (Washington: International Monetary Fund).
- Barajas, A., R. Chami, R.A. Espinoza, and H. Hesse, 2010, “Recent Credit Stagnation in the MENA Region: What to Expect? What Can Be Done?” IMF Working Paper 10/219 (Washington: International Monetary Fund).
- Barajas, A., G. Dell’Ariccia, and A. Levchenko, forthcoming, “Credit Booms: The Good, the Bad, and the Ugly,” IMF Working Paper (Washington: International Monetary Fund).
- Dell’Ariccia, G., and R. Marquez, 2006, “Lending Booms and Lending Standards,” Journal of Finance, Vol. 61, pp. 2511–545.
- Gourinchas, P.-O., R. Valdes, and O. Landerretche, 2001, “Lending Booms: Latin America and the World,” Economia, Vol. 1 (spring), pp. 47–99.
- Jorda, O., M. Schularick, and A.M. Taylor, 2010, “Financial Crises, Credit Booms, and External Imbalances: 140 Years of Lessons,” NBER Working Paper No. 16567 (Cambridge, Massachusetts: National Bureau of Economic Research).
- Kannan, P., 2010, “Credit Conditions and Recoveries from Recessions Associated with Financial Crises,” IMF Working Paper 10/83 (Washington: International Monetary Fund).
- Mendoza, E. and M. 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).
- Schularick, M. and A.M. Taylor, 2009, “Credit Booms Gone Bust: Monetary Policy, Leverage Cycles and Financial Crises, 1870–2008,” NBER Working Paper No. 15512 (Cambridge, Massachusetts: National Bureau of Economic Research).
- Terrones, M. and E. Mendoza, 2004, “Are Credit Booms in Emerging Markets a Concern?” World Economic Outlook, pp. 148-166 (Washington: International Monetary Fund).
- Claessens, S., M.A. Kose, and M. Terrones, 2011, “Financial Cycles: What? How? When?” IMF Working Paper 11/76 (Washington: International Monetary Fund).
- Borio, C. and P. Lowe, 2004, “Securing Sustainable Price Stability: Should Credit Comeback from the Wilderness?” BIS Working Paper No. 157 (Basel: Bank for International Settlements).
- Mendoza, E. and M. 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).
- Shin, H.S. and K. Shin, 2011, “Procyclicality and Monetary Aggregates”, NBER Working Paper No. 16836 (Cambridge, Massachusetts: National Bureau of Economic Research).

### Capital flows, sudden stops, and macro-financial linkages
- Calvo, G., L. Leiderman, and C. Reinhart. (1996). “Inflows of Capital to Developing Countries in the 1990s.” Journal of Economic Perspectives, Vol. 10, No. 2, pp. 123‒39.
- Calvo, G., A. Izquierdo, and E. Talvi, 2006, “Sudden Stops and Phoenix Miracles in Emerging Markets,” American Economic Review Papers and Proceedings, Vol. 96, No.2, pp.405-10.
- Calvo, G.A., A. Izquierdo, and L.F. Mejia, 2004, “On the empirics of Sudden Stops: The Relevance of Balance Sheet Effects,” NBER Working Paper No. 10520 (Cambridge, Massachusetts: National Bureau of Economic Research).
- Cardarelli, R., S. Elekdag, and M.A. Kose, 2007, “Managing Large Capital Inflows,” in World Economic Outlook, October 2007: Globalization and Inequality, World Economic and Financial Surveys (Washington: International Monetary Fund).
- Cardarelli, R., S. Elekdag, and M.A. Kose, 2010, “Capital Inflows: Macroeconomic Implications and Policy Responses,” Economic Systems, Vol. 34, No. 4, pp. 333–56.
- Reinhart, C. and V. Reinhart, 2009, “Capital Flow Bonanzas: An Encompassing View of the Past and Present,” in NBER International Seminar on Macroeconomics (Chicago: University of Chicago Press).
- Kaminsky, G., and C. Reinhart, 1999, “The Twin Crises: The Causes of Banking and Balance-of-Payments Problems,” American Economic Review, Vol. 89, pp. 473-500.
- Kaminsky, G.L., C.M. Reinhart, C.A. Végh, 2005, “When It Rains, It Pours: Procyclical Capital Flows and Macroeconomic Policies,” in NBER Macroeconomics Annual 2004, Vol. 19, ed. by M. Gertler and K. Rogoff, pp. 11–82 (Cambridge, Massachusetts: National Bureau of Economic Research).
- Cardarelli, R., S. Elekdag, and M.A. Kose, 2010, “Capital Inflows: Macroeconomic Implications and Policy Responses,” Economic Systems, Vol. 34, No. 4, pp. 333–56.
- Barajas, A., R. Chami, R.A. Espinoza, and H. Hesse, 2010, “Recent Credit Stagnation in the MENA Region: What to Expect? What Can Be Done?” IMF Working Paper 10/219 (Washington: International Monetary Fund).

### Methodology, business cycle analysis, and monetary policy
- Bean, C., M. Paustian, A. Penalver, and T. Taylor, 2010, “Monetary Policy after the Fall,” presented at the Federal Reserve Bank of Kansas City Annual Conference, Jackson Hole, Wyoming, September 16, 2010.
- Bernanke, B., M. Gertler, and S. Gilchrist, 1999, “The Financial Accelerator in a Quantitative Business Cycle Framework,” in Handbook of Macroeconomics, ed. by J. B. Taylor and M. Woodford, Vol. 1, pp. 1341–393 (The Netherlands: Elsevier Science).
- Bry, G. and C. Boschan, 1971, Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, (New York: National Bureau of Economic Research).).
- Burns, A.F., and W.C. Mitchell, 1946, Measuring Business Cycles (New York: National Bureau of Economic Research).).
- Harding, D., and A. Pagan, 2002, “Dissecting the Cycle: A Methodological Investigation,” Journal of Monetary Economics Vol. 49, pp. 365–81.
- Hodrick, R., and E.C. Prescott, 1997, “Postwar U.S. Business Cycles: An Empirical Investigation,” Journal of Money, Credit, and Banking, Vol. 29, No. 1, pp. 1–16.
- Ravn, M.O., and H. Uhlig, 2002, “On Adjusting the Hodrick-Prescott Filter for the Frequency of Observations,” Review of Economics and Statistics, Vol. 84, No. 2, pp. 371-76.
- Gertler, M. and N. Kiyotaki, forthcoming, “Financial Intermediation and Credit Policy in Business Cycle Analysis,” Handbook of Monetary Economics.
- Taylor, J.B., 2010, “Macroeconomic Lessons from the Great Deviation,” remarks at the 25th NBER Macro Annual Meeting, May 2010: http://www.johnbtaylor.com/

### Growth, finance, and development
- Levine, R. 2005, “Finance and Growth: Theory and Evidence,” in Handbook of Economic Growth, ed. by P. Aghion and S. Durlauf (The Netherlands: Elsevier Science).
- Rajan, R.G., and L. Zingales, 1998, “Financial Dependence and Growth,” American Economic Review, Vol. 88, No. 3, 559–86.
- Tornell, A., and F. Westermann, 2002, “Boom-Bust Cycles in Middle Income Countries: Facts and Explanation,” IMF Staff Papers, Vol. 49, Special Issue, pp. 111–53.
- Eichengreen, B., A. Rose, and C. Wyplosz, 1996, “Contagious Currency Crises: First Tests,” The Scandinavian Journal of Economics, Vol. 98, No. 4, pp. 463–84.

*Source: _wp11241 - References*

---


_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2011/_wp11241.pdf_