research paper on economic crises

• Search Menu
• Sign in through your institution
• Browse content in C - Mathematical and Quantitative Methods
• Browse content in C1 - Econometric and Statistical Methods and Methodology: General
• C13 - Estimation: General
• Browse content in C2 - Single Equation Models; Single Variables
• C21 - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
• C26 - Instrumental Variables (IV) Estimation
• Browse content in D - Microeconomics
• Browse content in D2 - Production and Organizations
• D22 - Firm Behavior: Empirical Analysis
• Browse content in D4 - Market Structure, Pricing, and Design
• D43 - Oligopoly and Other Forms of Market Imperfection
• D44 - Auctions
• Browse content in D7 - Analysis of Collective Decision-Making
• D73 - Bureaucracy; Administrative Processes in Public Organizations; Corruption
• Browse content in D8 - Information, Knowledge, and Uncertainty
• D82 - Asymmetric and Private Information; Mechanism Design
• D86 - Economics of Contract: Theory
• Browse content in E - Macroeconomics and Monetary Economics
• E2 - Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy
• Browse content in E4 - Money and Interest Rates
• E43 - Interest Rates: Determination, Term Structure, and Effects
• Browse content in E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit
• E58 - Central Banks and Their Policies
• Browse content in F - International Economics
• Browse content in F1 - Trade
• F13 - Trade Policy; International Trade Organizations
• Browse content in F3 - International Finance
• F30 - General
• Browse content in G - Financial Economics
• Browse content in G0 - General
• G01 - Financial Crises
• Browse content in G1 - General Financial Markets
• G11 - Portfolio Choice; Investment Decisions
• G12 - Asset Pricing; Trading volume; Bond Interest Rates
• G13 - Contingent Pricing; Futures Pricing
• G14 - Information and Market Efficiency; Event Studies; Insider Trading
• G15 - International Financial Markets
• Browse content in G2 - Financial Institutions and Services
• G20 - General
• G21 - Banks; Depository Institutions; Micro Finance Institutions; Mortgages
• G22 - Insurance; Insurance Companies; Actuarial Studies
• G23 - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
• G24 - Investment Banking; Venture Capital; Brokerage; Ratings and Ratings Agencies
• G28 - Government Policy and Regulation
• Browse content in G3 - Corporate Finance and Governance
• G30 - General
• G31 - Capital Budgeting; Fixed Investment and Inventory Studies; Capacity
• G32 - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
• G33 - Bankruptcy; Liquidation
• G34 - Mergers; Acquisitions; Restructuring; Corporate Governance
• G35 - Payout Policy
• G38 - Government Policy and Regulation
• G39 - Other
• Browse content in H - Public Economics
• Browse content in H2 - Taxation, Subsidies, and Revenue
• H26 - Tax Evasion and Avoidance
• Browse content in H4 - Publicly Provided Goods
• H42 - Publicly Provided Private Goods
• Browse content in H7 - State and Local Government; Intergovernmental Relations
• H74 - State and Local Borrowing
• Browse content in J - Labor and Demographic Economics
• Browse content in J1 - Demographic Economics
• J15 - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination
• Browse content in J3 - Wages, Compensation, and Labor Costs
• J33 - Compensation Packages; Payment Methods
• Browse content in K - Law and Economics
• Browse content in K1 - Basic Areas of Law
• K11 - Property Law
• Browse content in K2 - Regulation and Business Law
• K22 - Business and Securities Law
• Browse content in L - Industrial Organization
• Browse content in L1 - Market Structure, Firm Strategy, and Market Performance
• L14 - Transactional Relationships; Contracts and Reputation; Networks
• Browse content in L2 - Firm Objectives, Organization, and Behavior
• L21 - Business Objectives of the Firm
• L22 - Firm Organization and Market Structure
• L26 - Entrepreneurship
• Browse content in L3 - Nonprofit Organizations and Public Enterprise
• L33 - Comparison of Public and Private Enterprises and Nonprofit Institutions; Privatization; Contracting Out
• Browse content in L8 - Industry Studies: Services
• L83 - Sports; Gambling; Recreation; Tourism
• Browse content in M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
• Browse content in M4 - Accounting and Auditing
• M40 - General
• M41 - Accounting
• M48 - Government Policy and Regulation
• Browse content in O - Economic Development, Innovation, Technological Change, and Growth
• Browse content in O1 - Economic Development
• O16 - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance
• Browse content in O3 - Innovation; Research and Development; Technological Change; Intellectual Property Rights
• O31 - Innovation and Invention: Processes and Incentives
• O32 - Management of Technological Innovation and R&D
• Browse content in R - Urban, Rural, Regional, Real Estate, and Transportation Economics
• Browse content in R3 - Real Estate Markets, Spatial Production Analysis, and Firm Location
• R30 - General
• Advance articles
• Editor's Choice
• Blog Series
• Author Guidelines
• Submission Site
• Open Access
• About Review of Corporate Finance Studies
• Editorial Board
• Advertising and Corporate Services
• Journals Career Network
• Self-Archiving Policy
• Dispatch Dates
• Journals on Oxford Academic
• Books on Oxford Academic

Article Contents

Introduction, 1. what happened and when, 2. cause and effect: the causes of the crisis and its real effects, 3. was this a liquidity crisis or an insolvency/counterparty risk crisis, 4. the real effects of the crisis, 5. the policy responses to the crisis, 6. conclusion, the financial crisis of 2007–2009: why did it happen and what did we learn.

• Article contents
• Figures & tables
• Supplementary Data

Anjan V. Thakor, The Financial Crisis of 2007–2009: Why Did It Happen and What Did We Learn?, The Review of Corporate Finance Studies , Volume 4, Issue 2, September 2015, Pages 155–205, https://doi.org/10.1093/rcfs/cfv001

• Permissions Icon Permissions

This review of the literature on the 2007–2009 crisis discusses the precrisis conditions, the crisis triggers, the crisis events, the real effects, and the policy responses to the crisis. The precrisis conditions contributed to the housing price bubble and the subsequent price decline that led to a counterparty-risk crisis in which liquidity shrank due to insolvency concerns. The policy responses were influenced both by the initial belief that it was a market-wide liquidity crunch and the subsequent learning that insolvency risk was a major driver. I suggest directions for future research and possible regulatory changes.

In its analysis of the crisis, my testimony before the Financial Crisis Inquiry Commission drew the distinction between triggers and vulnerabilities. The triggers of the crisis were the particular events or factors that touched off the events of 2007–2009—the proximate causes, if you will. Developments in the market for subprime mortgages were a prominent example of a trigger of the crisis. In contrast, the vulnerabilities were the structural, and more fundamental, weaknesses in the financial system and in regulation and supervision that served to propagate and amplify the initial shocks.       Chairman Ben Bernanke, April 13, 2012 1 1 Bernanke, B. S. “Some Reflections on the Crisis and the Policy Response.” Speech at the Russell Sage Foundation and the Century Foundation Conference on “Rethinking Finance,” New York, April 13, 2012.

Financial crises are a centuries-old phenomena (see Reinhart and Rogoff 2008 , 2009 , 2014 ), and there is a substantial literature on the subject (e.g., Allen and Gale 1998 , 2000 ; Diamond and Dybvig 1983 ; Gennaioli, Shleifer, and Vishny 2015 ; Gorton 2010 ; Thakor forthcoming ). Despite this familiarity, the financial crisis of 2007–2009 came as a major shock that is widely regarded as the worst financial crisis since the Great Depression of the 1930s, and rightly so. The crisis threatened the global financial system with total collapse, led to the bailouts of many large uninsured financial institutions by their national governments, caused sharp declines in stock prices, followed by smaller and more expensive loans for corporate borrowers as banks pulled back on their long-term and short-term credit facilities, and caused a decline in consumer lending and lower investments in the real sector. 2 For a detailed account of these events, see the excellent review by Brunnermeier (2009) .

Atkinson, Luttrell, and Rosenblum (2013) estimate that the financial crisis cost the United States an estimated 40% to 90% of one year’s output, an estimated $6 to $14 trillion, the equivalent of $50,000 to $120,000 for every U.S. household. Even these staggering estimates may be conservative. The loss of total U.S. wealth from the crisis—including human capital and the present value of future wage income—is estimated in this paper to be as high as $15 to $30 trillion, or 100%–190% of 2007 U.S. output. The wide ranges in these estimates reflect uncertainty about how long it will take the output of the economy to return to noninflationary capacity levels of production.

As Lo (2012) points out, we do not have consensus on the causes of the crisis. This survey discusses the various contributing factors. I believe that a combination of global macroeconomic factors and U.S. monetary policy helped to create an environment in which financial institutions enjoyed a long period of sustained profitability and growth, which elevated perceptions of their skills in risk management (see Thakor 2015a ), possibly increased bullishness in a non-Bayesian manner (e.g., Gennaioli, Shleifor, and Vishny 2015 ), and encouraged financial innovation. The financial innovation was driven by advances in information technology that helped make all sorts of securities marketable, spurred the growth of the subprime mortgage market, and made banking more intertwined with markets (see Boot 2014 ; Boot and Thakor 2014 ).

These innovative securities led to higher risks in the industry, 3 and eventually these risks led to higher-than-expected defaults, causing the securities to fall out of favor with investors, precipitating a crisis (e.g., Gennaioli, Shleifer, and Vishny 2012 ). The early signs of the crisis came in the form of withdrawals by investors/depositors and sharp increases in risk premia and collateral requirements against secured borrowing. These developments were interpreted by U.S. regulators and the government as indications of a market-wide liquidity crisis, so most of the initial regulatory and government initiatives to stanch the crisis took the form of expanded liquidity facilities for a variety of institutions and ex post extension of insurance for (a prior uninsured) investors. As the crisis continued despite these measures, there was growing recognition that the root cause of the liquidity stresses seemed to be counterparty risk and institution-specific insolvency concerns linked to the downward revisions in the assessments of the credit qualities of subprime mortgages and many asset-backed securities. This then led to additional regulatory initiatives targeted at coping with counterparty risk. It is argued that some of the government initiatives—despite their temporary nature and their effectiveness—have created the expectation of future ad hoc expansions of the safety net to uninsured sectors of the economy, possibly creating various sorts of moral hazard going forward. This crisis is thus a story of prior regulatory beliefs about underlying causes of the crisis being heavily influenced by historical experience (especially the Great Depression that many believe was prolonged by fiscal tightening by the government and inadequate liquidity provision by the central bank), 4 followed by learning that altered these beliefs, and the resulting innovations in regulatory responses whose wisdom is likely to be the subject of ongoing debate and research.

All of these policy interventions were ex post measures to deal with a series of unexpected events. But what about the ex ante regulatory initiatives that could have made this crisis less likely? The discussion of the causal events in Section 2 sheds light on what could have occurred before 2006, but a more extensive discussion of how regulation can enhance banking stability appears in Thakor (2014) . In a nutshell, it appears that what we witnessed was a massive failure of societal risk management, and it occurred because a sustained period of profitable growth in banking created a false sense of security among all; the fact that banks survived the bursting of the dotcom bubble further reinforced this belief in the ability of banks to withstand shocks and survive profitably. This led politicians to enact legislation to further the dream of universal home ownership that may have encouraged risky bank lending to excessively leveraged consumers. 5 Moreover, it caused banks to operate with less capital than was prudent and to extend loans to excessively leveraged consumers, caused rating agencies to underestimate the true risks, and led investors to demand unrealistically low risk premia. Two simple regulatory initiatives may have created a less crisis-prone financial system—significantly raising capital requirements in the commercial and shadow banking systems during the halcyon precrisis years and putting in place regulatory mechanisms—either outright proscriptions or price-based inducements—to ensure that banks focused on originating and securitizing only those mortgages that involved creditworthy borrowers with sufficient equity. This is perhaps twenty-twenty hindsight, but some might even dispute that these are the right conclusions to draw from this crisis. If so, what did we really learn?

There is a sense that this crisis simply reinforced old lessons learned from previous crises and a sense that it revealed new warts in the financial system. Reinhart and Rogoff’s (2009) historical study of financial crises reveals a recurring pattern—most financial crises are preceded by high leverage on the balance sheets of financial intermediaries and asset price booms. Claessens and Kodres (2014) identify two additional “common causes” that seem to play a role in crises: financial innovation that creates new instruments whose returns rely on continued favorable economic conditions (e.g., Fostel and Geanakoplos 2012 ), and financial liberalization and deregulation. Given that these causes go back centuries, one must wonder whether, as a society, we simply do not learn or whether the perceived benefits of the precrisis economic boom are deemed to be large enough to make the occasional occurrence of crises one worth bearing.

Numerous valuable new lessons have emerged as well—insolvency and counterparty risk concerns were primary drivers of this crisis, the shadow banking sector was highly interconnected with the banking system and thus a major influence on the systemic risk of the financial system, high leverage contributes to an endogenous increase in systemic risk (especially when it occurs simultaneously on the balance sheets of consumers as well as financial institutions), and piecemeal regulation of depository institutions in a highly fragmented regulatory structure that leaves the shadow banking system less regulated makes it easy for financial institutions to circumvent microprudential regulation and engage in financial innovation, some of which increases systemic risk. Moreover, state and federal regulators implement similar regulations in different ways (see Agarwal et al. 2014 ), adding to complexity in the implementation of regulation and elevating uncertainty about the responses of regulated institutions to these regulations. And, finally, compensation practices and other aspects of corporate culture in financial institutions may have encouraged fraud (see Piskorski, Seru, and Witkin forthcoming ), adding another wrinkle to the conditions that existed prior to the crisis.

However, it is also clear that our learning is far from complete. The pursuit of easy-money monetary policies in many countries seems to reflect the view that liquidity is still a major impediment and that these policies are needed to facilitate continued growth-stimulus objectives, but it is unlikely that such policies will help allay concerns about insolvency and counterparty risks, at least as a first-order effect. The persistence of low-interest rate policies encourage banks to chase higher yields by taking higher risks, thereby increasing the vulnerability of the financial system to future crises. And the complexity of regulations like Dodd-Frank makes the reactions of banks—that seek novel ways to lighten their regulatory burden—to these regulations more uncertain. All this means that some of the actions of regulators and central banks may inadvertently make the financial system more fragile rather than less.

This retrospective look at the 2007–2009 crisis also offers some ideas for looking ahead. Three specific ideas are discussed in Section 5 and previewed here: First, the research seems to indicate that higher levels of capital in banking would significantly enhance financial stability, with little, if any, adverse impact on bank value. However, much of our research on this issue is qualitative and does not lend itself readily to calibration exercises that can inform regulators how high to set capital requirements. The section discusses some recent research that has begun to calculate the level of optimal capital requirements. We need more of this kind of research. Second, there needs to be more normative research on the optimal design of the regulatory infrastructure. Most research attention has been focused on the optimal design of regulations, but we need more research on the kinds of regulatory institutions needed to implement simple and effective regulations consistently, without the tensions created by multiple regulators with overlapping jurisdictions. Third, beyond executive compensation practices, 6 we have virtually no research on culture in banking. 7 Yet, managerial misconduct—whether it is excessive risk taking or information misrepresentation to clients—is a reflection of not only compensation incentives but also the corporate culture in banking. This area is sorely in need of research.

The financial crisis of 2007–2009 was the culmination of a credit crunch that began in the summer of 2006 and continued into 2007. 8 Most agree that the crisis had its roots in the U.S. housing market, although I will later also discuss some of the factors that contributed to the housing price bubble that burst during the crisis. The first prominent signs of problems arrived in early 2007, when Freddie Mac announced that it would no longer purchase high-risk mortgages, and New Century Financial Corporation, a leading mortgage lender to risky borrowers, filed for bankruptcy. 9 Another sign was that during this time the ABX indexes—which track the prices of credit default insurance on securities backed by residential mortgages—began to reflect higher expectations of default risk. 10

While the initial warning signs came earlier, most people agree that the crisis began in August 2007, with large-scale withdrawals of short-term funds from various markets previously considered safe, as reflected in sharp increases in the “haircuts” on repos and difficulties experienced by asset-backed commercial paper (ABCP) issuers who had trouble rolling over their outstanding paper. 11

Causing this stress in the short-term funding markets in the shadow banking system during 2007 was a pervasive decline in U.S. house prices, leading to concerns about subprime mortgages. 12 As indicated earlier, the ABX index reflects these concerns at the beginning of 2007 (see Benmelech and Dlugosz 2009 ; Brunnermeier 2009 ; Gorton and Metrick 2012 ). The credit rating agencies (CRAs) downgraded asset-backed financial instruments in mid-2007. 13 The magnitude of the rating actions—in terms of the number of securities affected and the average downgrade—in mid-2007 appeared to surprise investors. 14 Benmelech and Dlugosz (2009) show that a large number of structured finance securities were downgraded in 2007–2008, and the average downgrade was 5–6 notches. This is substantially higher than the historical average. For example, during the 2000–2001 recession, when one-third of corporate bonds were downgraded, the average downgrade was 2–3 notches.

Consequently, credit markets continued to tighten. The Federal Reserve opened up short-term lending facilities and deployed other interventions (described later in the paper) to increase the availability of liquidity to financial institutions. But this failed to prevent the hemorrhaging, as asset prices continued to decline.

In early 2008, institutional failures reflected the deep stresses that were being experienced in the financial market. Mortgage lender Countrywide Financial was bought by Bank of America in January 2008. And then in March 2008, Bear Stearns, the sixth largest U.S. investment bank, was unable to roll over its short-term funding due to losses caused by price declines in mortgage-backed securities (MBS). Its stock price had a precrisis fifty-two-week high of $133.20 per share, but plunged precipitously as revelations of losses in its hedge funds and other businesses emerged. JP Morgan Chase made an initial offer of $2 per share for all the outstanding shares of Bear Stearns, and the deal was consummated at $10 per share when the Federal Reserve stepped in with a financial assistance package.

The problems continued as IndyMac, the largest mortgage lender in the United States, collapsed and was taken over by the federal government. Things worsened as Fannie Mae and Freddie Mac (with ownership of $5.1 trillion of U.S. mortgages) became sufficiently financially distressed and were taken over by the government in September 2008. The next shock was when Lehman Brothers filed for Chapter 11 bankruptcy on September 15, 2008, failing to raise the capital it needed to underwrite its downgraded securities. On the same day, AIG, a leading insurer of credit defaults, received $85 billion in government assistance, as it faced a severe liquidity crisis. The next day, the Reserve Primary Fund, a money market fund, “broke the buck,” causing a run on these funds. Interbank lending rates spiked.

On September 25, 2008, savings and loan giant, Washington Mutual, was taken over by the FDIC, and most of its assets were transferred to JP Morgan Chase. 15 By October, the cumulative weight of these events had caused the crisis to spread to Europe. In October, global cooperation among central banks led them to announce coordinated interest rate cuts and a commitment to provide unlimited liquidity to institutions. However, there were also signs that this was being recognized as an insolvency crisis. So the liquidity provision initiatives were augmented by equity infusions into banks. By mid-October, the U.S. Treasury had invested $250 billion in nine major banks.

The crisis continued into 2009. By October, the unemployment rate in the United States rose to 10%.

Although there is some agreement on the causes of the crisis, there are disagreements among experts on many of the links in the causal chain of events. We begin by providing in Figure 1 a pictorial depiction of the chain of events that led to the crisis and then discuss each link in the chain.

The chain of events leading up to the crisis

2.1 External factors and market incentives that created the house price bubble and the preconditions for the crisis

In the many books and articles written on the financial crisis, various authors have put forth a variety of precrisis factors that created a powder keg just waiting to be lit. Lo (2012) provides an excellent summary and critique of twenty-one books on the crisis. He observes that there is no consensus on which of these factors were the most significant, but we will discuss each in turn.

2.1.1 Political factors

Rajan (2010) reasons that economic inequities had widened in the United States due to structural deficiencies in the educational system that created unequal access for various segments of society. Politicians from both parties viewed the broadening of home ownership as a way to deal with this growing wealth inequality—a political proclivity that goes back at least to the 19th century Homestead Act—and therefore undertook legislative initiatives and other inducements to make banks extend mortgage loans to a broader borrower base by relaxing underwriting standards, and this led to riskier mortgage lending. 16 The elevated demand for houses pushed up house prices and led to the housing price bubble. In this view, politically motivated regulation was a contributing factor in the crisis.

This point has been made even more forcefully by Kane (2009 , forthcoming ) who argues that, for political reasons, most countries (including the United States) establish a regulatory culture that involves three elements: (1) politically directed subsidies to selected bank borrowers, (2) subsidized provision of implicit and explicit repayment guarantees to the creditors of banks, and (3) defective government monitoring and control of the problems created by the first two elements. These elements, Kane (2009) argues, undermine the quality of bank supervision and produce financial crises.

Perhaps these political factors can explain the very complicated regulatory structure for U.S. banking. Agarwal et al. (2014) present evidence that regulators tend to implement identical rules inconsistently because they have different institutional designs and potentially conflicting incentives. For U.S. bank regulators, they show that federal regulators are systematically tougher and tend to downgrade supervisory ratings almost twice as frequently as state supervisors for the same bank. These differences in regulatory “toughness” increase the effective complexity of regulations and impede the implementation of simple regulatory rules, making the response of regulated institutions to regulations less predictable than in theoretical models and generating another potential source of financial fragility.

A strikingly different view of political influence lays the blame on deregulation motivated by political ideology. Deregulation during the 1980s created large and powerful financial institutions with significant political clout to block future regulation, goes the argument presented by Johnson and Kwak (2010) . This “regulatory capture” created a crisis-prone financial system with inadequate regulatory oversight and a cozy relationship between government and big banks.

2.1.2 Growth of securitization and the OTD model

It has been suggested that the desire of the U.S. government to broaden ownership was also accompanied by monetary policy that facilitated softer lending standards by banks. In particular, an empirical study of Euro-area and U.S. Bank lending standards by Maddaloni and Paydro (2011) finds that low short-term interest rates (generated by an “easy money” monetary policy) lead to softer standards for household and business loans. Moreover, this softening is amplified by the originate-to-distribute (OTD) model of securitization, 17 weak supervision over bank capital, and a lax monetary policy. 18 These conditions thus made it attractive for commercial banks to expand mortgage lending in the period leading to the crisis and for investment banks to engage in warehouse lending using nonbank mortgage lenders. Empirical evidence also has been provided that the OTD model encouraged banks to originate risky loans in ever increasing volumes. Purnanandam (2011) documents that a one-standard-deviation increase in a bank’s propensity to sell off its loans increases the default rate by about 0.45 percentage points, representing an overall increase of 32%.

The effect of these developments in terms of the credit that flowed into the housing market to enable consumers to buy homes was staggering. 19 Total loan originations (new and refinanced loans) rose from $500 billion in 1990 to $2.4 trillion in 2007, before declining to $900 billion in the first half of 2008. Total amount of mortgage loans outstanding increased from $2.6 to $11.3 trillion over the same period. Barth et al. (2009) show that the subprime share of home mortgages grew from 8.7% in 1995 to a peak of 13.5% in 2005.

2.1.3 Financial innovation

Prior to the financial crisis, we witnessed an explosion of financial innovation for over two decades. One contributing factor was information technology, which made it easier for banks to develop tradable securities and made commercial banks more intertwined with the shadow banking system and with financial markets. But, of course, apart from information technology, there had to be economic incentives for banks to engage in innovation. Thakor (2012) develops an innovation-based theory of financial crises, which starts with the observation that financial markets are very competitive, so with standard financial products—those whose payoff distributions everybody agrees on—it is hard for financial institutions to have high profit margins. This encourages the search for new financial products, especially those whose creditworthiness not everybody agrees on. The lack of unanimity of the investment worth of the new financial products limits how competitive the market for those products will be and allows the offering institutions to earn high initial profits. 20

But such new products are also riskier by virtue of lacking a history. The reason is that it is not only competitors who may disagree that these are products worthy of investment but also the financiers of the institutions offering these products, and there is a paucity of historical data that can be relied upon to eliminate the disagreement. When this happens, short-term funding to the innovating institutions will not be rolled over, and a funding crisis ensues. The explosion of new asset-backed securities created by securitization prior to the crisis created an ideal environment for this to occur.

This view of how financial innovation can trigger financial crises is also related to Gennaioli, Shleifer, and Vishny’s (2012) model in which new securities—with tail risks that investors ignore—are oversupplied to meet high initial demand and then dumped by investors when a recognition of the risks induces a flight to safety. Financial institutions are then left holding these risky securities.

These theories explain the 2007–2009 crisis, as well as many previous crises. For example, perhaps the first truly global financial crisis occurred in 1857 and was preceded by significant financial innovation to enable investments by British and other European banks in U.S. railroads and other assets.

2.1.4 U.S. monetary policy

Taylor (2009) argues that the easy-money monetary policy followed by the U.S. Federal Reserve, especially in the six or seven years prior to the crisis, was a major contributing factor to the price boom and subsequent bust that led to the crisis. Taylor (2009) presents evidence that monetary policy was too “loose fitting” during 2007–2009 in the sense that actual interest rate decisions fell well below what historical experience would suggest policy should be based on the Taylor rule. 21

Taylor (2009) shows that these unusually low interest rates, a part of a deliberate monetary policy choice by the Federal Reserve, accelerated the housing boom and thereby ultimately led to the housing bust. The paper presents a regression to estimate the empirical relationship between the interest rate and housing starts, showing that there was a high positive correlation between the intertemporal decline in interest rates during 2001–2007 and the boom in the housing market. Moreover, a simulation to see what would have happened in the counterfactual event that the Taylor rule interest rate policy had been followed indicates that we would not have witnessed the same housing boom that occurred in reality. And without a housing boom, there would be no bubble to burst and no crisis.

The impact of low interest rates on housing prices was amplified by the incentives the low interest rate environment provided for lenders to make riskier (mortgage) loans. When the central bank keeps interest loans low for so long, it pushes down banks’ net interest margins, and one way for banks to respond is to elevate these margins by taking on more risk. This induced banks to increase the borrower pool by lending to previously excluded high-risk borrowers, further fueling the housing price boom.

It was not only the U.S. central bank that followed an easy-money policy and experienced a housing boom. In Europe, deviations from the Taylor rule varied in size across countries due to differences in inflation and GDP growth. The country with the largest deviation from the rule was Spain, and it had the biggest boom in housing, as measured by the change in housing investment as a share of GDP. Austria had the smallest deviation from the rule and also experienced the smallest change in housing investment as a share of GDP.

Taylor (2009) notes that there was apparently coordination among central banks to follow this easy-money policy. A significant fraction of the European Central Bank (ECB) interest rate decisions can be explained by the influence of the Federal Reserve’s interest rate decisions.

2.1.5 Global economic developments

Jagannathan, Kapoor, and Schaumburg (2013) have pointed to developments in the global economy as a contributing factor. In the past two decades, the global labor market has been transformed, with emerging-market countries—most notably China—accounting for an increasing percentage of global GDP. The opening up of emerging-market economies, combined with centrally controlled exchange rates to promote exports, has led to the accumulation of large amounts of savings in these countries. And the lack of extensive social safety nets means that these savings have not been depleted by elevated domestic consumption. Rather, the savers have sought to invest in safe assets, resulting in huge inflows of investments in the United States in assets like Treasury bonds and AAA-rated mortgages. When coupled with the easy-money monetary policy pursued in the United States over roughly the same time period, the result was a very large infusion of liquidity into the United States and Western Europe, which contributed to exceptionally low mortgage interest rates.

This would normally lead to an increase in inflation as more money is available to purchase goods and services. However, the rise of emerging-market economies meant that companies like Wal-Mart, IBM, and Nike could move procurement, manufacturing, and a variety of back-office support services to these countries with lower labor costs. Consequently, core inflation stayed low in the west and put little pressure on central banks to reverse their easy-money monetary policies.

It is argued that the flood of this “hot money” found its way into real estate, increasing demand for housing, and pushing house prices to unprecedented levels.

2.1.6 Misaligned incentives

There are many who have suggested misaligned incentives also played a role. The argument goes as follows. Financial institutions, especially those that viewed themselves as too big to fail (TBTF), took excessive risks because de jure safety-net protection via deposit insurance and de facto safety-net protection due to regulatory forbearance stemming from the reluctance to allow such institutions to fail. 22 Such risk taking was permitted due to lax oversight by regulators whose incentives were not aligned with those of taxpayers. 23 Moreover, “misguided” politicians facilitated this with their overzealous embrace of unregulated markets. 24 This is also the essence of the report of the U.S. government’s Financial Crisis Inquiry Commission (FCIC). 25

The risk taking was a part of the aggressive growth strategies of banks. These strategies were pursued to elevate net interest margins that were depressed by the prevailing low-interest-rate monetary policy environment, as discussed earlier. Banks grew by substantially increasing their mortgage lending, which provided increased “throughput” for investment banks to securitize these mortgages and create and sell securities that enhanced these banks’ profits, with credit rating agencies being viewed as complicit due to their willingness to assign high ratings to structured finance products. 26 This increase in financing was another facilitating factor in pushing up home prices. The presence of government safety nets also created incentives for banks to pursue high leverage, as the credit ratings and market yields of bank debt remained less sensitive to leverage increases than for nonfinancial firms. 27 Combined with riskier asset portfolio strategies, this increased the fragility of banks. Moreover, reputational concerns may have also played a role. Thakor (2005) develops a theory in which banks that have extended loan commitments overlend during economic booms and high stock price periods, sowing the seeds of a subsequent crisis. The prediction of the theory that there is overlending by banks during the boom that precedes the crisis seems to be supported by the data. There is also evidence of managerial fraud and other misconduct that may have exacerbated the misalignment of incentives at the bank level. Piskorski, Seru, and Witkin (2014) provide evidence that buyers of mortgages received false information about the true quality of assets in contractual disclosures made by selling intermediaries in the nonagency market. They show that misrepresentation incentives became stronger as the housing market boomed, peaking in 2006. What is somewhat surprising is that even reputable intermediaries were involved in misrepresentation, suggesting that managerial career concerns were not strong enough to deter this sort of behavior. 28 Consequently, the element of surprise on the part of investors when true asset qualities began to be revealed was likely greater than it would have been absent the fraud and may have added to the precipitous decline in liquidity during the crisis.

2.1.7 Success-driven skill inferences

One weakness in the misaligned-incentives theory is that it fails to explain the timing of the crisis of 2007–2009. After all, these incentives have been in place for a long time, so why did they become such a big problem in 2007 and not before? Thakor (forthcoming) points out that there are numerous perplexing facts about this crisis that cannot be readily explained by the misaligned incentives story of the crisis, and thus, as important as misaligned incentives were, they cannot be the whole story of the crisis. For example, the financial system was flush with liquidity prior to the crisis, but then liquidity declined sharply during the crisis. Why? Moreover, the recent crisis followed a long period of high profitability and growth for the financial sector, and during those good times, there was little warning of the onset and severity of the crisis from any of the so-called “watchdogs” of the financial system-rating agencies, regulators, and creditors of the financial system. 29

If misaligned incentives were the major cause of the crisis, then one would expect a somewhat different assessment of potential risks from the one expressed above. Thakor (2015a) develops a theory of risk management over the business cycle to explain how even rational inferences can weaken risk management and sow the seeds of a crisis. 30 The idea is as follows. Suppose that there is a high probability that economic outcomes—most notably the probabilities of loan defaults—are affected by the skills of bankers in managing credit risk and a relatively small probability that these outcomes are purely exogenous, that is, driven solely by luck or factors beyond the control of bankers. Moreover, there is uncertainty and intertemporal learning about the probability that outcomes are purely exogenous. Banks initially make relatively safe loans because riskier (potentially more profitable) loans are viewed as being too risky and hence not creditworthy. Suppose that these safe loans successfully pay off over time. As this happens, everybody rationally revises upward their beliefs about the abilities of banks to manage (credit) risk. Moreover, because aggregate defaults are low, the probability that outcomes are purely exogenous is also revised downward. Consequently, it becomes possible for banks to finance riskier loans. And if these successfully pay off, then even riskier loans are financed. This way, increased risk taking in banking continues unabated, and no one talks about an impending crisis.

Eventually, even though the probability of the event is low, it is possible that a large number of defaults will occur across banks in the economy. At this stage, investors revise their beliefs about the skills of bankers, as well as beliefs about the probability that outcomes are purely exogenous. Because beliefs about bankers’ skills were quite high prior to the occurrence of large aggregate defaults, investors infer with a relatively high probability that outcomes are indeed driven by luck. This causes beliefs about the riskiness of loans to move sharply in the direction of prior beliefs. And since only relatively safe loans could be financed with these prior beliefs, the sudden drop in beliefs about the risk-management abilities of banks causes investors to withdraw funding for the loans that are suddenly viewed as being “excessively risky.” This theory predicts that when there is a sufficiently long period of high profitability and low loan defaults, then bank risk-taking increases and that a financial crisis occurs only when its ex ante probability is being viewed as being sufficiently low.

2.1.8 The diversification fallacy

Prior to the crisis, many believed that diversification was a cure-all for all sorts of risks. In particular, by pooling (even subprime) mortgages from various geographies and then issuing securities against these pools that were sold into the market, it was believed that the benefits of two kinds of diversification were achieved: geographic diversification of the mortgage pool and then the holding of claims against these pools by diversified investors in the capital market. However, many of these securities were being held by interconnected and systemically important institutions that operated in the financial market, so what the process actually did was to concentrate risk on the balance sheets of institutions in a way that created greater systemic risk. Clearly, advances in information technology and financial innovation were facilitating factors in these developments.

2.2 Housing prices respond to external factors and market incentives

As a consequence of the factors just discussed, house prices in the United States experienced significant appreciation prior to the crisis, especially during the period 1998–2005. The Case-Shiller U.S. national house price index more than doubled between 1987 and 2005, with a significant portion of the appreciation occurring after 1998. Further supporting empirical evidence that there was a housing price bubble is the observation that the ratio of house prices to renting costs appreciated significantly around 1999. 31 See Figure 2 .

Ratio of home prices to rents

Source: Federal Reserve Board: Flow of Funds, Bureau of Economic Analysis: National Income and Product Accounts, and Cecchetti (2008) .

2.3 Leverage and consumption rise to exacerbate the problem

The housing price bubble permitted individuals to engage in substantially higher consumption, fueled by a decline in the savings rate as well as additional borrowing using houses as collateral (see Mian and Sufi 2014 ). U.S. households, feeling rich in an environment of low taxes, low interest rates, easy credit, expanded government services, cheap consumption goods, and rising home prices, went on a consumption binge, letting their personal savings rate drop below 2%, for the first time since the Great Depression. 32 Jagannathan, Kapoor, and Schaumburg (2013) note that the increase in U.S. household consumption during this period was striking; per capita consumption grew steadily at the rate of $1,994 per year during 1980–1999, but then experienced a big jump to approximately $2,849 per year from 2001 to 2007. “Excess consumption,” defined as consumption in excess of wages and salary accruals and proprietors’ income, increased by almost 230% from 2000 to 2007. See Figure 3 .

U.S. household consumption, wages, and excess consumption

All numbers are in 1980 dollar per household. Source: Jagannathan, Kapoor, and Schaumburg (2013) .

Some of this higher consumption was financed with higher borrowing, which was supported by rising home prices. Indeed, the simplest way to convert housing wealth into consumption is to borrow. As the value of residential real estate rose, mortgage borrowing increased even faster. Figure 4 shows this phenomenon—home equity fell from 58% of home value in 1995 to 52% of home value by 2007. 33

Evolution of equity and borrowing in residential real estate

Source: Federal Reserve Flow of Funds and Cecchetti (2008) .

This increase in consumer leverage, made possible by the housing price bubble, had a significant role in the crisis that was to come. Mian and Sufi (2009) show that the sharp increase in mortgage defaults during the crisis was significantly amplified in subprime ZIP codes, or ZIP codes with a disproportionately large share of subprime borrowers as of 1996. They show that, during 2002–2005, the subprime ZIP codes experienced an unprecedented relative growth in mortgage credit, despite significantly declining relative income growth—and in some cases declining absolute income growth—in these neighborhoods. Mian and Sufi (2009) also note that this was highly unusual in that 2002–2005 is the only period in the past eighteen years during which personal income and mortgage credit growth were negatively correlated. 34

The notion that the housing price bubble and its subsequent collapse were due to a decoupling of credit flow from income growth has recently been challenged by Adelino, Schoar, and Severino (2015) . Using data on individual mortgage transactions rather than whole zip codes, they show that the previous findings were driven by a change in borrower composition, i.e., higher-income borrowers buying houses in areas where house prices go up. They conclude that middle-income and high-income borrowers contributed most significantly to the house price bubble and then the subsequent defaults after 2007.

What made the situation worse is that this increase in consumer leverage—and that too by those who were perhaps least equipped to handle it—was also accompanied by an increase in the leverage of financial institutions, especially investment banks and others in the shadow banking system, which turned out to be the epicenter of the crisis. 35 This made these institutions fragile and less capable of handling defaults on consumer mortgages and sharp declines in the prices of mortgage-backed securities (MBS) than they would have been had they been not as thinly capitalized.

The observation that high leverage in financial institutions contributed to the 2007–2009 crisis is sometimes challenged on the grounds that commercial banks were well above the capital ratios required by regulation prior to the start of the crisis. For example, based on a study of bank holding companies (BHCs) during 1992–2006, Berger et al. (2008) document that banks set their target capital levels substantially above well-capitalized regulatory minima and operated with more capital than required by regulation. However, such arguments overlook two important points. First, U.S. investment banks, which were at the epicenter of the subprime crisis, had much lower capital levels than BHCs. Second, it is now becoming increasingly clear that regulatory capital requirements have both been too low to deal with systemic risk issues and also been too easy to game within the risk-weighting framework of Basel I and Basel II. Moreover, the flexibility afforded by Basel II to permit institutions to use internal models to calculate required capital may explain the high leverage of investment banks.

Another argument to support the idea that higher capital in banking would not have helped much is that the losses suffered during the crisis by many institutions far exceeded any reasonable capital buffer they could have had above regulatory capital requirements. The weakness in this argument is that it fails to recognize that the prescription to have more capital in banking is not just based on the role of capital in absorbing actual losses before they threaten the deposit insurance fund but also on the incentive effects of capital on the risk management choices of banks. Indeed, it is the second role that is typically emphasized more in the research on this subject, and it has to do with influencing the probabilities of hitting financial insolvency states, rather than how much capital can help once the bank is in one of those states.

Whether it is the incentive effect or the direct risk-absorption effect of capital or a combination, the key question for policy makers is “does higher capital increase the ability of banks to survive a financial crisis?” Berger and Bouwman (2013) document that commercial banks with higher capital have a greater probability of surviving a financial crisis and that small banks with higher capital are more likely to survive during normal times as well. This is also consistent with Gauthier, Lehar, and Souissi (2012) , who provide evidence that capital requirements based on banks’ contributions to the overall risk of the banking system can reduce the probability of failure of an individual bank and that of a systemic crisis by 25%. Even apart from survival, higher capital appears to facilitate bank performance. Beltratti and Stulz (2012) show that large banks with higher precrisis tier-one capital (i.e., at the end of 2006) had significantly higher stock returns during the crisis. 36

There is also evidence of learning that speaks—albeit indirectly—to this issue. Calomiris and Nissim (2014) find that how the stock market views leverage has also changed as a result of the crisis. They document that while the market rewarded higher leverage with high market values prior to the crisis, leverage has become associated with lower values during and after the crisis.

2.4 Risky lending and diluted screening add fuel to the fire

In Ramakrishnan and Thakor’s (1984) theory of financial intermediation, a raison d’etre for banks is specialization in screening borrowers with a priori unknown default risk (see also Allen 1990 ; Bhattacharya and Thakor 1993 ; Coval and Thakor 2005 ; Millon and Thakor 1985 ). This paves the way for banks to provide a host of relationship banking services (see Boot and Thakor 2000 ). Thus, if these screening incentives are affected by the business model banks use to make loans, it has important implications. Keys et al. (2010) provide empirical evidence indicating that securitization may have weakened the incentives of banks to screen the borrowers whose loans had a high likelihood of being securitized. There is also additional evidence that during the dramatic growth of the subprime (securitized) mortgage market, the quality of the market declined significantly. Demyanyk and Van Hemert (2011) document that the quality of loans deteriorated for six consecutive years prior to the crisis. 37 The fact that lenders seemed aware of the growing default risk of these loans is suggested by the higher rates lenders charged borrowers as the decade prior to the crisis progressed. For a similar decrease in the quality of the loan (e.g., a higher loan-to-value ratio), a loan made early in the decade was associated with a smaller interest rate increase than a loan made late in the decade. Thus, even though lenders may have underestimated the credit risks in their loans, Demyanyk and Van Hemert (2011) note that they do seem to have been aware that they were making discernibly riskier loans. 38

There is also evidence that these lenders took steps to shed some of these elevated risks from their balance sheets. Purnanandam (2011) shows that from the end of 2006 until the beginning of 2008, originators of loans tended to sell their loans, collect the proceeds, and then use them to originate new loans and repeat the process. The paper also shows that banks with high involvement in the OTD market during the precrisis period originated excessively poor-quality mortgages, and this result cannot be explained by differences in observable borrower quality, geographical location of the property, or the cost of capital for high-OTD and low-OTD banks. This evidence suggests that the OTD model induced originating banks to have weaker incentives to screen borrowers before extending loans in those cases in which banks anticipated that the loans would be securitized. However, this effect is stronger for banks with lower capital, suggesting that capital strengthens the screening incentives of banks. 39

2.5 The bubble bursts to set the stage for the crisis

Most accounts of the financial crisis attribute the start of the crisis to the bursting of the housing price bubble and the fact that the failure of Lehman Brothers in September 2008 signaled a dramatic deepening of the crisis. But exactly what caused the housing price bubble to burst? Most papers tend to gloss over this issue.

Some papers cite evidence that run-ups in house prices are a commonplace occurrence prior to the start of a crisis. 40 But they do not explain what caused the bubble to burst. However, we can get some insights into what happened by scrutinizing the dynamics of loan defaults in relation to initial home price declines and how this fueled larger subsequent price declines, causing the bubble to burst. Home prices reached their peak in the second quarter of 2006. Holt (2009) points out that initial decline in home prices from that peak was a rather modest 2% from the second quarter of 2006 to the fourth quarter of 2006.

With prime mortgages held by creditworthy borrowers, such a small decline is unlikely to lead to a large number of defaults, and especially not defaults that are highly correlated across geographic regions of the United States. The reason is that these borrowers have 20% of equity in the home when they buy the home, so a small price drop does not put the mortgage “under water” and threaten to trigger default.

Not so with subprime mortgages. Even the small decline in home prices pushed these highly risky borrowers over the edge. Foreclosure rates increased by 43% over the last two quarters of 2006 and increased by a staggering 75% in 2007 compared with 2006, as documented by Liebowitz (2008) . Homeowners with adjustable rate mortgages that had low teaser rates to attract them to buy homes were hit the hardest. The drop in home prices meant that they had negative equity in their homes (since many of them put no money down in the first place), and when their rates adjusted upward, they found themselves hard pressed to make the higher monthly mortgage payments. 41 As these borrowers defaulted, credit rating agencies began to downgrade mortgage-backed securities. This tightened credit markets, pushed up interest rates, and accelerated the downward price spiral, eventually jeopardizing the repayment ability of even prime borrowers. From the second quarter of 2006 to the end of 2007, foreclosure rates for fixed-rate mortgages increased by about 55% for prime borrowers and by about 80% for subprime borrowers. Things were worse for those with adjustable-rate mortgages—their foreclosure rates increased by much higher percentages for prime and subprime borrowers, as noted by Liebowitz (2008) .

2.6 Liquidity shrinks as the crisis begins to set in

Before the crisis, the shadow banking sector of the U.S. economy had experienced dramatic growth. This was significant because the shadow banking system is intricately linked with the “official” insured banking system and supported by the government by backup guarantees. For example, insured banks write all sorts of put options sold to shadow banks and also are financed in part by the shadow banking system. If an insured bank defaults on an insured liability in the shadow banking system, it tempts the government to step in and “cover” shadow banks to “protect” the insured bank. One notable aspect of the shadow banking system is its heavy reliance on short-term debt, mostly repurchase agreements (repos) and commercial paper. As Bernanke (2010) notes, repo liabilities of U.S. broker dealers increased dramatically in the four years before the crisis. The IMF (2010) estimates that total outstanding repo in U.S. markets at between 20% and 30% of U.S. GDP in each year from 2002 to 2007, with even higher estimates for the European Union—a range of 30% to 50% of EU GDP per year from 2002 to 2007.

A repo transaction is essentially a “collateralized” deposit. 42 The collateral used in repo transactions consisted of Treasury bonds, mortgage-backed securities (MBS), commercial paper, and similar highly liquid securities. As news about defaults on mortgages began to spread, concerns about the credit qualities of MBS began to rise. The bankruptcy filings of subprime mortgage underwriters and the massive downgrades of MBS by the rating agencies in mid-2007 created significant downward revisions in perceptions of the credit qualities of many types of collateral being used in repo transactions (as well as possibly the credit-screening investments and abilities of originators of the underlying mortgages) and caused repo haircuts to spike significantly. This substantially diminished short-term borrowing capacity in the shadow banking sector.

The ABCP market fell by $350 billion in the second half of 2007. Many of these programs required backup support from their sponsors to cover this shortfall. As the major holders of ABCPs, MMFs were adversely affected, and when the Reserve Primary Fund broke the buck, ABCP yields rose for outstanding paper. Many shrinking ABCP programs sold their underlying assets, putting further downward pressure on prices. 43 All of these events led to numerous MMFs requiring assistance from their sponsors to avoid breaking the buck.

Many of these events seemed to have market-wide implications. The failure of Lehman Brothers was followed by larger withdrawals from money-market mutual funds (MMFs) after the Reserve Primary Funds, a large MMF, “broke the buck.” The ABCP market also experienced considerable stress. By July 2007, there was $1.2 trillion of ABCP outstanding, with the majority of the paper held by MMFs. 44 Issuers of commercial paper were unable in many cases to renew funding when a portion of the commercial paper matured, and some have referred to this as a “run.” 45 As Figure 5 shows, things deteriorated quite dramatically in this market beginning August 2007.

Runs on asset-based commercial paper programs

Source: Covitz, Liang, and Suarez (2013) .

The stresses felt by MMFs were a prominent feature of the crisis. The run experienced by the Reserve Primary Fund spread quickly to other funds and led to investors redeeming over $300 billion within just a few days after the failure of Lehman Brothers. This was a surprise at the time it occurred because MMFs have been traditionally regarded as relatively safe. The presumption was that, given this perception of safety, these large-scale withdrawals represented some sort of market-wide liquidity crisis, and this is perhaps why the U.S. government decided to intervene by providing unlimited insurance to all MMF depositors; this was an ad hoc ex post move since there was no formal insurance scheme in place for MMF investors. While the move stopped the hemorrhaging for MMFs, it also meant an ad hoc expansion of the government safety net to a $3 trillion MMF industry.

Determining the nature of this crisis is important for how we interpret the evidence and what we learn from it. The two dominant views of what caused this crisis are (1) illiquidity and (2) insolvency. It is often claimed that the financial crisis that caused the Great Depression was a liquidity crisis, and the Federal Reserve’s refusal to act as a Lender of Last Resort in March 1933 caused the sequence of calamitous events that followed. 46 Thus, determining what caused this crisis and improving our diagnostic ability to assess the underlying nature of future crises based on this learning would be very valuable.

The loss of short-term borrowing capacity and the large-scale withdrawals from money-market funds discussed in the previous section have been viewed by some as a systemic liquidity crisis, but there is some disagreement about whether this was a market-wide liquidity crunch or an institution-specific increase in concerns about solvency risk that caused liquidity to shrink for some banks, but not for others. That is, one viewpoint is that when people realized that MBS were a lot riskier than they thought, liquidity dried up across the board because it was hard for an investor to determine which MBS was of high quality and which was not. The reason for this difficulty is ascribed to the high level of asymmetric information and opaqueness in MBS arising from the opacity of the underlying collateral and the multiple steps in the creation of MBS—from the originations of multiple mortgages to their pooling and then to the specifics of the tranching of this pool. So when bad news arrived about mortgage defaults, there was a (nondiscriminating) market-wide effect. See Gorton (2010) for this interpretation of the data.

A theoretical argument supporting the idea that this was a liquidity crisis is provided by Diamond and Rajan (2011) . In their model, banks face the prospect of a random exogenous liquidity shock at a future date before loans mature, at which time they may have to sell their assets in a market with a limited number of “experts” who can value the assets correctly. The assets may thus have to be sold at fire-sale prices, and the bank may face insolvency as a result. This may cause depositors to run the bank, causing more assets to be dumped and a further price decline. They argue that those with access to cash can therefore purchase assets at very low prices and enjoy high returns, causing holders of cash to demand high returns today and inducing banks to hold on to illiquid assets; this exacerbates the future price decline and illiquidity. Moreover, illiquidity means lower lending initially.

While the liquidity view focuses on the liability side of the bank’s balance sheet—the inability of banks to roll over short-term funding when hit with a liquidity shock—the insolvency view focuses on shocks to the asset side. It says that when the quality of a bank’s assets was perceived to be low, lenders began to reduce the credit they were willing to extend to the bank. According to this view, the crisis was a collection of bank-specific events, and not a market-wide liquidity crunch. Banks with the biggest declines in asset quality perceptions were the ones experiencing the biggest funding shortages.

While one can argue that the underlying causes discussed in the previous section can be consistent with either viewpoint of the crisis and the end result is the same regardless of which viewpoint is correct—banks face dramatically reduced access to liquidity—the triggering events, the testable predictions, and the appropriate policy interventions are all different. In this section I will discuss the differences with respect to the triggering events and testable predictions. I will discuss what the existing empirical evidence has to say and also suggest new empirical tests that can focus more sharply on distinguishing between these viewpoints. Note that empirically distinguishing between these two viewpoints is quite challenging because of the endogeneity created by the relationship between solvency and liquidity risks. A market-wide liquidity crunch can lead to fire sales (e.g., Shleifer and Vishny 2011 ) that can depress asset prices, diminish financing capacity, and lead to insolvency. And liquidity crunches are rarely sunspot phenomena—they are typically triggered by solvency concerns. 47

3.1 The triggering events

If a liquidity shortage caused this crisis, then what could be identified as triggering events? The Diamond and Rajan (2011) model suggests that a sharp increase in the demand for liquidity by either the bank’s depositors or borrowers could provide the liquidity shock that could trigger a crisis. In the data one should observe this in the form of a substantial increase in deposit withdrawals at banks as well as a significant increase in loan commitment takedowns by borrowers prior to the crisis.

If this was an insolvency crisis, then the trigger for the crisis should be unexpectedly large defaults on loans or asset-backed securities that cause the risk perceptions of investors to change substantially. This is implied by the theories developed in the papers of Gennaioli, Shleifer, and Vishny (2012) and Thakor ( 2012 , 2015a , forthcoming ). I will use these different triggering events when I discuss how empirical tests might be designed in future research.

3.2 The testable predictions

If this was a liquidity crisis, then all institutions that relied on short-term debt should have experienced funding declines and engaged in fire sales during the crisis. 48 If this was an insolvency crisis, then only those banks whose poor operating performance (e.g., higher-than-expected default-related losses) should have experienced declines in funding and lending.

If this was a liquidity crisis, then it would have been preceded by large deposit withdrawals and/or large loan commitment takedowns (both representing liquidity shocks) at banks. 49 If this was an insolvency crisis, it would have been preceded by deteriorating loan/asset quality at banks.

If this was a liquidity crisis, it would have affected banks with all capital structures (within the range of high-leverage capital structures observed in practice). 50 If this was an insolvency crisis, its adverse effect would be significantly greater for banks with lower capital ratios.

If this was a liquidity crisis (with a substantial increase in the expected return on holding cash), then borrowing costs would have increased regardless of the collateral offered. If this was an insolvency crisis, then borrowing costs would depend on the collateral offered, and the spread between the costs of unsecured and secured borrowing would increase significantly prior to and during the crisis.

If the crisis was indeed triggered by a liquidity shock that raised the expected return on holding cash, investors would demand a high return to lend money, regardless of how much collateral was offered. Depending on the circumstances, the “haircut” may vary, so more or less collateral may be offered, but the fact will remain that the price of obtaining liquidity will be high. By contrast, if it was an insolvency crisis, then offering collateral will diminish insolvency concerns, so one should observe a significant increase in the difference between the rates on unsecured and secured borrowing. 51

3.3 The existing empirical evidence and possible new tests

On prediction 1, the evidence seems to point to this being an insolvency crisis. Boyson, Helwege, and Jindra (2014) examine funding sources and asset sales at commercial banks, investment banks, and hedge funds. The paper hypothesizes that if liquidity dries up in the financial market, institutions that rely on short-term debt will be forced to sell assets at fire-sale prices. The empirical findings are, however, that the majority of commercial and investment banks did not experience funding declines during the crisis and did not engage in the fire sales predicted to accompany liquidity shortages. The paper does find evidence of pockets of weakness that are linked to insolvency concerns. Problems at financial institutions that experienced liquidity shortages during the crisis originated on the asset side of their balance sheets in the form of shocks to asset value. Commercial banks’ equity and asset values are documented to have been strongly affected by the levels of net charge-offs, whereas investment banks’ asset changes seemed to reflect changes in market valuation. 52

Another piece of evidence comes from MMFs. The notion that MMFs were almost as safe as money was debunked by Kacperczyk and Schnabl (2013) , who examined the risk-taking behavior of MMFs during 2007–2010. They document four noteworthy results. First, MMFs faced an increase in their opportunity to take risk starting in August 2007. By regulation, MMFs are required to invest in highly rated, short-term debt securities. Before August 2007, the debt securities MMFs could invest in were relatively low in risk, yielding no more than 25 basis points above U.S. Treasuries. However, the repricing of risk following the run on ABCP conduits in August 2007 caused this yield spread to increase to 125 basis points. The MMFs now had a significant risk choice: either invest in a safe instrument like U.S. Treasuries or in a much riskier instrument like a bank obligation.

Second, the paper documents that fund flows respond positively to higher realized yields, and this relationship is stronger after August 2007. This created strong incentives for MMFs to take higher risk to increase their yields.

Third, the MMFs did take risks, the paper finds. The funds sponsored by financial intermediaries that had more money-fund business took more risk.

Of course, this by itself does not settle the issue of whether these events were due to a liquidity shock that prompted investors to withdraw money from MMFs, turn inducing higher risk taking by fund managers, or whether the withdrawals were due to elevated risk perceptions. However, Kacperczyk and Schnabl (2010) point out that the increase in yield spreads in August 2007 had to do with the fact that outstanding ABCP fell sharply in August 2007 following news of the failure of Bear Stearns’ hedge funds that had invested in subprime mortgages and BNP Paribas’ suspension of withdrawals from its investment funds due to the inability to assess the values of mortgages held by the funds. Moreover, the massive withdrawals from MMFs from September 16–19, 2008, were triggered by the Reserve Primary Fund announcing that it had suffered significant losses on its holdings of Lehman Brothers Commercial paper. Thus, it appears that the runs suffered by MMFs were mainly due to asset risk and solvency concerns, rather than a liquidity crisis per se, even though what may have been most salient during the early stages of the crisis had the appearance of a liquidity crunch.

As for the second prediction, I am not aware of any evidence that large deposit withdrawals or commitment takedowns preceded this crisis, particularly before asset quality concerns became paramount. There is evidence, however, that loan quality was deteriorating prior to the crisis. The Demyanyk and Van Hemert (2011) evidence, as well as the evidence provided by Purnanandam (2011) , points to this. It also indicates that lenders seemed to be aware of this, which may explain the elevated counterparty risk concerns when the crisis broke.

Now consider the third prediction. There seems to be substantial evidence that banks with higher capital ratios were less adversely affected by the crisis. Banks with higher precrisis capital (1) were more likely to survive the crisis and gained market share during the crisis ( Berger and Bouwman 2013 ), (2) took less risk prior to the crisis ( Beltratti and Stulz 2012 ), and (3) exhibited smaller contractions in lending during the crisis ( Carlson, Shan, and Warusawithana 2013 ).

Turning to the fourth prediction, the empirical evidence provided by Taylor and Williams (2009) is illuminating. Taylor and Williams (2009) examine the LIBOR-OIS Spread . This spread is equal to the three-month LIBOR minus the three-month Overnight Index Swap (OIS). The OIS is a measure of what the market expects the federal funds rate to be over the three-month period comparable to the three-month LIBOR. Subtracting OIS from LIBOR controls for interest rate expectations, thereby isolating risk and liquidity effects. Figure 6 shows the behavior of this spread just before and during the crisis.

The LIBOR-OIS spread during the first year of the crisis

Source: Taylor (2009) .

The figure indicates that the spread spiked in early August 2007 and stayed high. This was a problem because the spread not only is a measure of financial stress but it affects how monetary policy is transmitted due to the fact that rates on loans and securities are indexed to LIBOR. An increase in the spread, holding fixed the OIS, increases the cost of loans for borrowers and contracts the economy. Policy makers thus have an interest in bringing down the spread. But just like a doctor who cannot effectively treat a patient if he misdiagnoses the disease, so can a central bank not bring down the spread if it does not correctly diagnose the reason for its rise in the first place.

To see whether the spread had spiked due to elevated risk concerns or liquidity problems, Taylor and Williams (2009) measured the difference between interest rates on unsecured and secured interbank loans of the same maturity and referred to this as the “unsecured-secured” spread. 53 This spread is essentially a measure of risk. They then regressed the LIBOR-OIS spread against the secured-unsecured spread and found a very high positive correlation. They concluded that the LIBOR-OIS spread was driven mainly by risk concerns and that there was little role for liquidity.

Thus, the evidence that exists at present seems to suggest that this was an insolvency/counterparty risk crisis. However, one may argue that, given the close relationship between liquidity and insolvency risks, the evidence does not necessarily provide a conclusively sharp delineation. This suggests the need for some new tests, which I now discuss.

One possible new test would be to examine international data. In countries with stronger government safety nets (especially LOLR facilities), one would expect liquidity shocks to cause less of a problem in terms of institutions being unable to replace the lost funding. So if this was a liquidity crisis, then it should have been worse in countries with weaker safety nets. On the other hand, stronger safety nets induce greater risk taking, so if this was an insolvency crisis, it should have been worse in countries with stronger safety nets.

Another test would be to look for exogenous variation to get a better handle on causality by examining whether it was the drying up of liquidity that induced price declines for mortgage-backed securities or whether it was the price declines (due to elevated risk concerns) that induced the liquidity evaporation.

A third test would be to conduct a difference-in-differences analysis to examine the changes in funding costs during the crisis for banks with different amounts of collateral. If this was a liquidity crisis, the amount of collateral should not matter much—borrowing costs should rise for all borrowers due to the higher expected returns demanded by those with liquidity available for lending. If this was an insolvency crisis, the increase in borrowing costs should be significantly negatively related to collateral since collateral has both incentive and sorting effects in addition to being a direct source of safety for the lender. This test is in the spirit of the Taylor and Williams (2009) test discussed earlier, but that test speaks to spreads at the aggregate level, whereas I am suggesting a more borrower-specific test.

While these new tests can potentially provide valuable insights, they also will be helpful in better understanding the extent to which regulatory actions and monetary policy contributed to what appears to have been an insolvency crisis. The political desire for universal home ownership led to the adoption of regulations that permitted (and possibly encouraged) riskier mortgage lending, and the easy-money monetary policies in the United States and Europe facilitated access to abundant liquidity to finance these mortgages (see Section 2). Thus, the availability of excess liquidity—rather than its paucity—may have sown the seeds for lax underwriting standards and excessively risky lending that subsequently engendered insolvency concerns. This suggests that in a sense this may be called a “liquidity crisis” after all, but one caused by too much liquidity, rather than too little. Future research could flesh out this idea theoretically, and empirical tests could focus on whether excess precrisis liquidity is causally linked to crises; see Berger and Bouwman (2014) for evidence that excess liquidity creation predicts future crises.

This financial crisis had significant real effects. These included lower household credit demand and lower credit supply (resulting in reduced consumer spending), as well as reduced corporate investment and higher unemployment. I now discuss each of the real effects in this section.

4.1 Credit demand effects

The argument for why the crisis adversely affected household demand for credit has been presented by Mian, Rao, and Sufi (2013) , and it goes as follows: First, due to a variety of reasons discussed earlier (including easy credit with relaxed underwriting standards, booming house prices, and low interest rates), household debt went up significantly. Then the bursting of the house price bubble shocked household balance sheets, depleting household net worth. In response, the highly levered households reduced consumption. However, the relatively unlevered households did not increase consumption to offset this decline because of various frictions in the economy related to nominal price rigidities and a lower bound of zero on nominal interest rates.

Mian, Rao, and Sufi (2013) show that this interaction between precrisis household leverage and decline in consumption made a major contribution to the events witnessed during the crisis. In particular, their evidence indicates that the large accumulation of household debt 54 prior to the recession, in combination with the decline in house prices, explains the onset, severity, and length of the subsequent consumption collapse. The decline in consumption was much stronger in high-leverage counties with larger house price declines and in areas with greater reliance on housing as a source of wealth. Thus, as house prices plunged, so did consumption and the demand for credit.

4.2 Credit supply effects

There is persuasive empirical evidence that the crisis caused a significant decline in the supply of credit by banks. One piece of evidence is that syndicated loans declined during the crisis, which is important since syndicated lending is a major source for credit for the corporate sector (see Ivashina and Scharfstein 2010 ). The syndicated loan market includes not only banks but also investment banks, institutional investors, hedge funds, mutual funds, insurance companies, and pension funds. The evidence is that syndicated lending began to fall in mid-2007, and, starting in September 2008, this decline accelerated. Syndicated lending volume in the last quarter of 2008 was 47% lower than in the prior quarter and 79% lower than in the second quarter of 2007, which was the height of the credit boom. Lending declined across all types of corporate loans.

Accompanying the fall in lending volume was an increase in the price of credit. Santos (2011) documents that firms paid higher loan spreads during the crisis, and the increase was higher for firms that borrowed from banks that incurred larger losses. This result holds even when firm-specific, bank-specific, and loan-specific factors are controlled for, and the endogeneity of bank losses is taken into account.

As usual, separating supply and demand effects is difficult. Puri, Rocholl, and Steffen (2011) examine whether there are discernible reductions in credit supply, even when overall demand for credit is declining. They examine German savings banks, which operate in specific geographies and are required by law to serve only local customers. In each geography there is a Landesbank , owned by the savings bank in that area. These Landesbanken (the regional banks) had varying degrees of exposure to U.S. subprime mortgages. Losses on these exposures therefore varied across these Landesbanken, requiring different amounts of equity injections from their respective savings banks. In other words, different savings banks were impacted differently, depending on the losses suffered by their Landesbanken. What the paper uncovers is that the savings banks that were hit harder cut back on credit more. The average rate at which loan applicants were rejected was significantly higher than the rate at which rejections occurred at unaffected banks.

Campello, Graham, and Harvey (2010) survey 1,050 chief financial officers (CFOs) in thirty-nine countries in North America, Europe, and Asia and provide evidence of reduced credit supply during the crisis. About 20% of the surveyed firms in the United States (about 14% in Europe and 8.5% in Asia) indicated that they were very affected in the sense that they faced reduced availability of credit. Consequently, they cut back on capital expenditures, dividends, and employment.

4.3 Reduction in corporate investment and increase in unemployment

With both household consumption going down and credit availability becoming more scarce and expensive, it is not surprising that corporate investment fell and unemployment spiked. The United States entered a deep recession, with almost nine million jobs lost during 2008 and 2009, which represented about 6% of the workforce. It also discouraged many from trying to re-enter the workforce after the crisis abated, leading the labor participation rate to plunge. This meant that subsequent measurements of the unemployment rate tended to understate the true unemployment rate. Even measured unemployment rose every month from 6.2% in September 2008 to 7.6% in January 2009. U.S. housing prices declined about 30% on average, and the U.S. stock market fell approximately 50% by mid-2009. The U.S. automobile industry was also hit hard. Car sales fell 31.9% in October 2008 compared with September 2008. 55

A causal link between the reduction in credit supply during the crisis and an increase in unemployment is provided by Haltenhof, Lee, and Stebunovs (2014) . They provide evidence that household access to bank loans seemed to matter more than firm access to bank loans in determining the drop in employment in the manufacturing sector, but reduced access to commercial and industrial loans and to consumer installment loans played a significant role.

Beginning in August 2007, the governments of all developed countries undertook a variety of policy interventions to mitigate the financial crisis. The IMF (2009) identifies as many as 153 separate policy actions taken by thirteen countries, including forty-nine in the United States alone. That represents too large a set of policy interventions to discuss here. So I will briefly describe the major categories of interventions here 56 and then provide a brief assessment.

5.1 The policy responses

The policy responses fell in four major groups: provision of short-term liquidity to financial institutions, provision of liquidity directly to borrowers and investors, expansion of open market operations, and initiatives designed to address counterparty risk. See Figure 7 .

The major categories of intervention by the federal reserve board

5.1.1 Expansion of traditional role of central bank as lender of last resort in providing short-term liquidity

This set of interventions included the discount window, Term Auction Faculty (TAF), Primary Dealer Credit Facility (PDCF), and Term Securities Lending Facility (TSLF). The Federal Reserve also approved bilateral currency swap agreements with fourteen foreign central banks to assist these central banks in the provision of dollar liquidity to banks in their jurisdictions.

The discount window has long been a primary liquidity-provision tool used by the Fed. In December 2007, the TAF was introduced to supplement the discount window. The TAF provided credit to depository institutions through an auction mechanism. Like discount window loans, TAF loans had to be fully collateralized. The final TAF auction was held on March 8, 2010.

The PDCF was established in March 2008 in response to strains in the triparty repo market and the resulting liquidity pressures faced by primary securities dealers. Primary dealers are broker-dealers that serve as the trading counterparties for the Federal Reserve’s open-market operations and thus play a pivotal role in providing liquidity in the market for U.S. treasuries. The PDCF served as an overnight loan facility for primary dealers, similar to the discount window for depository institutions. Credit extension required full collateralization. This facility was closed on February 1, 2010.

The TSLF was a weekly loan facility designed to promote liquidity in Treasury and other collateral markets. The program offered Treasury securities for loan for one month against other program-eligible collateral. The borrowers were primary dealers who participated in single-price auctions to obtain these loans. The TSLF was closed on February 1, 2010.

5.1.2 Provision of liquidity directly to borrowers and investors in key credit markets

These interventions included the Commercial Paper Funding Facility (CPFF), ABCP MMF Liquidity Facility (AMLF), Money Market Investors Funding Facility (MMIFF), and the Term Asset-Backed Securities Loan Facility (TALF).

The CPFF was established in October 2008 to provide liquidity to U.S. issuers of commercial paper. Under the program, the Federal Reserve Bank of New York provided three-month loans to a specially created limited liability company that then used the money to purchase commercial paper directly from issuers. The CPFF was dissolved on August 30, 2010.

The AMLF was a lending facility that provided funds to U.S. depository institutions and bank holding companies to finance their purchases of high-quality ABCF from MMFs under prespecified conditions. The goal of the program was to bolster liquidity in the ABCP market. The AMLF opened on September 22, 2008 and was closed on February 1, 2010.

The MMIFF was designed to provide liquidity to U.S. money market investors. Under this facility, the Federal Reserve Bank of New York could provide senior secured loans to a series of special purpose vehicles to finance the purchase of eligible assets. This essentially “insured” money market investors who might have otherwise suffered losses due to the decline in the values of their holdings. The MMIFF was announced on October 21, 2008 and dissolved on October 30, 2009.

TALF was created to help market participants meet the credit needs of households and small businesses by supporting the issuance of asset-backed securities collateralized by consumer and small-business loans. The goal was to revive the consumer-credit securitization market. The facility was launched in March 2009 and dissolved by June 2010.

5.1.3 Expansion of Open Market operations

The goal of these initiatives was to support the functioning of credit markets and put downward pressure on long-term interest rates. These initiatives involved the purchase of longer-term securities for the Federal Reserve’s portfolio. For example, starting in September 2012, the Federal Open Market Committee (FOMC) decided to purchase agency-guaranteed MBS at the rate of $40 billion per month. In addition, starting January 2013, the Fed began purchasing longer-term Treasury securities at the rate of $45 billion per month as part of its “Quantitative Easing” programs.

5.1.4 Initiatives designed to address counterparty risk

These initiatives included various programs. One was the Troubled Asset Repurchase Program (TARP), which was initially authorized in October 2008 and ended on October 3, 2010. The original idea was for the government to buy troubled, illiquid assets from financial institutions in order to diminish concerns about their solvency and to stabilize markets. 57 In practice, it took the form of the government buying equity (the Capital Purchase Program) and taking ownership in various financial and nonfinancial firms and providing help to consumers to avoid home foreclosures.

The willingness of the U.S. government to take equity positions in banks was also accompanied by regulatory demands that banks recapitalize themselves through other means as well. The implied threat that the alternative to recapitalization via shareholder-provided equity was the infusion of equity (and thus the assumption of some ownership) by the government was an effective one. No bank wanted to be nationalized. The result was that U.S. banks were recapitalized fairly quickly. In retrospect, this may have been one of the most effective policy responses to the crisis, as the contrast with the struggling banking systems in the Euro zone—where regulators did not force banks to recapitalize—reveals.

Another program involved the Federal Reserve purchasing direct obligations of housing-related Government-Sponsored Enterprises (GSEs). The goal of these purchases, combined with the purchases of mortgage-backed securities by Fannie Mae, Freddie Mac, and Ginnie Mae, was to make it cheaper and easier for people to buy homes. The idea was that this goal would be served if the spread between GSE debt and U.S. Treasury debt narrowed, and it was believed that these purchases would do that.

In addition to these programs, the Federal Reserve also introduced stress tests of large banks, in order to determine their ability to withstand systemic shocks of various magnitudes. These simulations were designed to shed light on how much capital and access to liquidity banks would need if confronted with the kinds of shocks that pummeled banks during the crisis of 2007–2009 and hence to provide early-warning signals to both banks and regulators.

5.2 Assessment of policy initiatives

Many believe that the liquidity support provided by central banks was effective in calming markets in the initial phases of the crisis. However, there is no consensus on whether these were the right measures for the long run or whether the problem was even correctly diagnosed. At the very least, markets exhibited considerable volatility after the collapse of Lehman Brothers, indicating that central banks were learning as they went along—building the bridge as they walked on it, so to speak—and not all the initiatives had the intended effects.

A key issue for central banks was to determine whether the unfolding events were due to liquidity or counterparty risk arising from asymmetric information about the quality of assets on bank balance sheets and the opaqueness of those balance sheets. The Federal Reserve and the European Central Bank (ECB) clearly believed it was a liquidity problem, at least until the failure of Lehman Brothers, and this is reflected in many of the measures discussed earlier. But if the issue was counterparty risk, then the proper approach would have been to require banks to make their balance sheets more transparent, deal directly with the rising mortgage defaults, and undertake measures to infuse more capital into financial institutions, possibly with government assistance to supplement private-sector infusions.

Some of the programs that were developed in the later stages of the crisis were directed at dealing with the counterparty risk issue. These include TARP’s Capital Purchase Program, the purchases of GSE debt, and large-bank stress tests, all of which were discussed in the previous section.

Perhaps it should come as no surprise that the initial assessment of central banks was that this was a market-wide liquidity crunch, since beliefs about the underlying causes of the crisis were conditioned on historical experience, especially that associated with the Great Depression. 58 There are many who believe that what began as a recession turned into a big depression back then because the “gold standard” pegged currencies to gold stocks, so when the drop in global demand caused balance-of-payments crises in various countries due to gold outflows, governments and central banks responded by tightening monetary policy and exercising greater fiscal restraint. This led to the view that interest rate reductions and monetary-stimulus initiatives like quantitative easing were the appropriate policy responses to crises. Of course, every crisis is different, and the circumstances that existed around the time the subprime crisis hit the economy were quite different from those that preceded the Great Depression. Nonetheless, the rapid escalation of unanticipated problems made quick policy responses an imperative, and the time for deep explorations of the root causes of observable events was simply not there.

As discussed earlier, the existing evidence suggests that this was an insolvency crisis. The Taylor and Williams (2009) paper discussed earlier also examines the effect of some of the policy interventions to shed further light on this issue. Taylor and Williams (2009) show that the TAF had little effect on the LIBOR-OIS spread. Moreover, the sharp reduction in the federal funds rate during the crisis—the Fed funds target rate went from 5.25% in August 2007 to 2% in April 2008—also did not succeed in reducing the LIBOR-OIS spread (see Figure 6 ). However, it caused a depreciation of the dollar and caused oil prices to jump, causing a sharp decline in world economic growth.

Taylor and Williams (2009) go on to show that in October 2008, the crisis worsened as the LIBOR-OIS spread spiked even further. That is, more than a year after it started, the crisis worsened. Some point to the failure of Lehman Brothers in September 2008 as a proximate cause. Taylor and Williams (2009) suggest, however, that that may have been more a symptom than a cause and that the real culprit may have been the elevated perception of risk in the fundamentals, fueled by sinking house prices and rising oil prices.

The main point brought out by the Taylor and Williams (2009) analysis is that counterparty risk concerns generated by rising insolvency risk perceptions were an important driver of short-term funding strains for banks during August 2007–2008. This suggests that interventions designed to address counterparty risk (like capital infusions and stress tests) should have been implemented earlier than they were. Their analysis does not necessarily imply that liquidity facilities for banks were not helpful in the early stages of the crisis or that liquidity was not a concern of any magnitude during the crisis. One problem with making a determination of whether liquidity interventions by the Federal Reserve served any useful purpose is that we do not observe the counterfactual, that is, we do not know how market participants would have reacted in the absence of the liquidity intervention. While it is true that borrowing at the discount window was somewhat limited until 2008, it is difficult to know what would have happened had the discount window assurance provided by the role of the Federal Reserve as a Lender of Last Resort (LOLR) been absent. 59 Would the absence of the initial liquidity interventions have exacerbated the later counterparty risk concerns?

Even apart from the issue of whether the real problem was liquidity or counterparty risk, the massive ex post expansion of the government safety net to mutual fund investors and nondepository institutions to deal with the crisis raises the possibility that the expectations of market participants about the nature of implicit government guarantees have been significantly altered insofar as future crisis events are concerned. This has potentially significant moral hazard implications that may distort not only the behavior of investors and institutions but also possibly regulators who may feel compelled to adopt more intensive regulation to cope with the greater moral hazard.

5.3 What should have been done ex ante?

While one can play “Monday morning quarterback” with the government initiatives to cope with the crisis and learn a lot about which responses will serve us well in the future, it is even more important to reflect on what should have been done ex ante to reduce the probability of occurrence of the crisis. For such an exercise, the root-cause analysis in Section 2 is helpful. This analysis reveals that a rich set of factors interacted to generate this crisis, but if one were to try and extract the most essential drivers, one would conclude that the long period of sustained banking profitability was at the heart of the problem, since it is this period of relatively tranquil prosperity that corrupted risk management at many levels by creating the belief that banks were highly skilled at managing a variety of complex risks (see Thakor 2015a ). It tempted politicians to push the home-ownership agenda by creating regulatory and other inducements for banks to originate and securitize risky mortgages because banks were viewed as being capable of handling the risks. It tempted consumers to become excessively highly leveraged, thereby increasing the likelihood of default on mortgages (see, for example, Mian, Rao, and Sufi, 2013 ). It deterred regulators from imposing substantially higher capital requirements on banks because the diversification and risk-management skills of bankers were considered to be good enough to contain whatever risks were associated with the massive financial innovation that was occurring. It encouraged banks to engage in financial innovation and operate with relatively low levels of capital. It led credit rating agencies to underestimate risks and assign ratings that turned out ex post to be inflated.

Given this, what should we think of doing prospectively? Three issues are discussed below.

5.3.1 Higher capital requirements and more research on quantitative estimates of optimal capital requirements

In an environment in which a long sequence of good outcomes induces a “false sense of security,” as discussed above, it would be useful to consider higher capital requirements in both the depository financial institutions sector and in shadow banking. 60 Purnanandam’s (2011) empirical evidence indicates that banks with higher capital control credit risk more effectively when it comes to mortgages. Moreover, as Thakor (2014) discusses, increasing capital requirements will reduce correlated risk taking by banks, and hence lead to lower systemic risk. 61 In addition, if only mortgages with sufficient borrower equity can be securitized, then consumer leverage can also be limited. While these initiatives are unlikely to suffice by themselves to reduce the probability of future crises to socially acceptable levels, they may go a long way in enhancing financial stability. Moreover, by achieving some reduction in the probability of future crises, they will also reduce the probability of ad hoc ex post expansions of the government safety net that carry with them the baggage of increased moral hazard.

Increasing capital in banking also has other advantages. Sufficiently well capitalized institutions have little need to engage in fire sales of assets and therefore are unlikely to run into funding constraints ( Shleifer and Vishny (2011) discuss the macroeconomic effects of fire sales). This leads to high liquidity in the market (see Brunnermeier and Pedersen 2009 ), indicating that liquidity risk can be diminished without having institutions keep lots of low-return liquid assets (like cash) on their balance sheets. Thakor (2014) discusses how higher bank capital reduces insolvency risk by attenuating asset-substitution moral hazard and strengthening the bank's monitoring and screening incentives. So, higher levels of bank capital can reduce both liquidity risk and insolvency risk.

There have been two major impediments to the adoption of higher capital requirements in banking. One is that regulators have used backward-looking models of risk assessments (e.g., Rajan, Seru, and Vig 2015 ), which makes it difficult to overcome the temptation to keep capital requirements low during economic booms and periods of low defaults. The use of stress tests, and calculations of capital surcharges based on those tests, can help to partially overcome this problem. The second impediment is that our models of bank capital structure are largely qualitative, 62 so, while they can identify the factors that will tend to tilt the bank’s optimal capital structure in one direction or the other, they are not amenable to calibration exercises that provide the magnitudes of (socially optimal) bank capital requirements. This makes it difficult to answer questions like “what should regulators set minimum capital requirements at?” And if we cannot answer such questions, the guidance we can provide to regulators is limited. With differences of opinion, even among researchers, about the desirability of asking banks to keep more capital, this limitation creates the risk that debates on this may devolve into mere assertions based largely on assumptions made in qualitative models that cannot be tested.

Fortunately, recent research has begun to address this issue by calculating how increases in bank capital requirements may affect the cost of capital and profitability of banks. For example, Hanson, Kashyap, and Stein (2011) argue that a ten percentage-point increase in capital requirements will increase the weighted average cost of capital for banks by a mere 25 basis points, which the authors describe as “… a small effect.” Kisin and Manela (2014) use a clever empirical approach to estimate the shadow cost of bank capital requirements. They document that a ten percentage point increase in capital requirements would impose an average cost per bank of only 4% of annual profits, leading to an increase in lending rates of only 3 basis points. Roger and Vitek (2012) develop a macroeconometric model to determine how global GDP would respond to an increase in bank capital requirements, and conclude that monetary policy responses would largely offset any adverse impact of capital requirements.

So, the costs of significantly higher capital requirements appear to be small. What about the benefits? Mehran and Thakor (2011) provide empirical evidence that the bank value is increasing in bank capital in the cross-section. This militates against the notion that increasing capital in banking will necessarily jeopardize shareholder value in banking—a claim often made by bankers in resisting calls for higher capital levels—thereby questioning a basic premise of the presumed trade-off between financial stability and bank value creation. 63 However, it does not tell us how high capital requirements should be set. Some recent papers have started taking a stab at this. For example, Nguyen (2014) develops a general equilibrium model in which a dynamic banking sector endogenously determines aggregate growth. It takes into account the risk-shifting behavior of inadequately capitalized banks that causes financial fragility and calculates the optimal level of minimum tier-one capital requirements at 8%. This exceeds what is prescribed by both the Basel II and III accords, but it is below what many believe is needed for financial stability (e.g., Acharya, Engle, and Richardson 2012 ; Admati and Hellwig 2013 ). Nguyen (2014) also shows that increasing bank capital requirements can produce welfare gains greater than 1% of lifetime consumption. While one might quibble with the parameter values that produce such precise estimates, the benefit of engaging in serious modeling that is aimed at extracting such estimates cannot be overstated. The good news is that policymakers are already beginning to pay heed to the calls for higher capital. The bad news is that despite the capital surcharges based on stress-test results, the largest U.S. and European banks are still undercapitalized as of end 2014. The largest European banks (each with assets exceeding $100 billion) that account for 78% of all EU banking assets have only 4% capital as a percentage of total assets (leverage ratio). The situation is better in the United States where regulators have decided on a minimum 5% leverage ratio (above the 3% Basel III minimum), but as of December 2014, the largest U.S. Bank Holding Companies need to raise about $68 billion in capital to comply.

5.3.2 Designing a more integrated regulatory structure

Apart from the weakness of pre-crisis regulation in being insufficiently attentive to consumer and bank leverage, there was also little attention paid to the growth of the repo market and its escalating importance in the short-term funding of shadow banks. Concerns about the credit risks associated with the collateral used in repo transactions and the solvency of shadow banks that are heavily reliant on repos for short-term funding had a lot to do with what triggered the subprime crisis. Part of the reason for this inattention was due to the enormously complex yet fragmented regulatory structure for financial institutions that was discussed earlier. This produced inconsistent and often conflicting regulation, and made “regulatory arbitrage” easy, allowing risks that were regulated and monitored in one sector to migrate in an amplified form to another less regulated or unregulated sector. 64 A more integrated approach to the regulation of depository institutions and shadow banks—that have become increasingly connected through time—would have helped to alert regulators to the early warning signs. The creation of the Financial Stability Oversight Council (FSOC) under the Dodd-Frank Act is intended to eliminate some of these informational gaps. However, other than that, this Act seems to have done little to deal with possible future episodes of insolvency-driven stresses in the repo market or the associated drying up of short-term liquidity (see, for example, Acharya and Öncü 2011 ). Since the repo market is likely to experience bouts of illiquidity when the rest of the financial market is in a state of duress, this risk is potentially systemic, so not dealing with it in regulatory reform is a significant oversight. We need more normative research on the optimal design of regulatory agencies.

5.3.3 Bank misconduct, corporate governance, and corporate culture

Finally, the quality of corporate governance in banking has also been questioned. One could argue that if equity governance were strengthened, the case for higher capital requirements could be made stronger. Nonfinancial companies are not allowed to take ownership positions in banks in the United States. An investor with more than a 10% ownership stake in a bank is deemed to be “controlling shareholder” and thus must become a bank holding company (BHC). A BHC cannot invest in non-bank activities, so effectively ownership of banks is denied to many types of firms that create value through more effective governance, for example, private equity firms. This constraint on equity ownership in banks means that equity governance in banking is likely to be weaker than in nonfinancial corporations, which, in turn, makes equity less attractive for banks than for nonfinancials. What makes the situation worse is that controlling bank shareholders are deemed to be a “source of strength” for their institutions, which means they may be required by bank regulators to provide substantial incremental investments when the bank is considered to be financially impaired. This further reduces the attractiveness of bank equity investments for nonbank investors.

Whether stronger equity governance will suffice to significantly alter bank behavior is questionable. The culture of an organization has an important effect on its performance (see, for example, Bouwman 2013 ; Cameron et al. 2014 ). We need a lot more research on corporate culture in banking and how regulators should assess and monitor it.

This paper has reviewed a very large body of research on the causes and effects of the most devastating financial crisis since the Great Depression, and the policy responses undertaken by central banks to deal with the crisis. It appears that the crisis resulted from the interaction of many factors: politics, monetary policy, global economic developments, misaligned incentives, fraud, growth of securitization, a fragmented regulatory structure, and a complacency born of success-driven skill inferences. The existing evidence suggests that these factors produced an insolvency/counterparty risk crisis, in contrast to the more popular view that this was primarily a liquidity crisis. 65

It is well recognized that dealing with insolvency risk to diminish the likelihood of future crises will call for banks to operate with higher capital levels. One encouraging piece of evidence is that the value of bank capital seems to have been enhanced in the “eyes” of the market in the postcrisis period compared to the precrisis period, as documented by Calomiris and Nissim (2014) . For regulators, an important question is how should we assess the trade-offs between bank capital and stability? Thakor’s (2014) review of the extensive research on this topic concludes that the impact of bank capital on systemic risk has to be at the heart of any such assessment. It appears that higher levels of capital in banking will reduce both insolvency and liquidity risks. Gauthier, Lehar, and Souissi (2012) show that a properly designed capital requirement can reduce the probability of a systemic crisis by 25%. Of course, we need to know how to measure systemic risk for purposes of calibration of regulatory capital requirements. Acharya, Engle, and Richardson (2012) discuss the measurement of systemic risk and implementable schemes to regulate it. 66 We need more of this kind of research, including models that are amenable to quantitative estimations of socially optimal capital requirements. Moreover, it is also clear that we need to better understand the interaction between bank capital, borrower capital, monetary policy and asset prices. The recent theory proposed by di Lasio (2013) provides a microfounded justification for macroprudential regulation that involves countercyclical capital buffers and higher capital requirements during periods of lower fundamental risk. This theory can be a useful starting point for the examination of more complex interactions involving monetary policy.

Two other issues deserve research attention. One is the effect that regulatory complexity has on the efficacy of regulation. An example is the enormous complexity of the Dodd-Frank Act. While an important goal of the regulation is to eliminate the too-big-to-fail problem, it is doubtful it will achieve that goal. 67 The other issue is how regulators should deal with corporate culture in banking. 68 Culture is an important driver of risk management, but we know little about it.

I thank Arnoud Boot, Jennifer Dlugosz, Emre Ergungor, Stuart Greenbaum, Roni Kisin, Asaf Manela, Giorgia Piacentino, an anonymous referee, and, especially, Paolo Fulghieri (editor) and the other editors of the journal for helpful comments. I alone am responsible for any errors (either omission or commission) or misstatements.

2 See Campello, Graham, and Harvey (2010) , Gorton and Metrick (2012) , and Santos (2011) .

3 The higher risk associated with financial innovation was systematic, partly because the new securities were traded, market-based securities that not only caused banks to become more connected with the market but were also more connected with each other since banks were holding similar securities for investment purposes.

4 Massive deposit withdrawals experienced by New York banks in February 1933 led to these banks turning to the U.S. Federal Reserve as a Lender of Last Resort (LOLR). However, on March 4, 1933, the Fed shut off the liquidity spigot and declared a week-long bank “holiday.” Many believe this denial of liquidity to the banking system is what led to the darkest days of the Great Depression. This view of the Great Depression is not shared by all, however. Some believe the problem then was also insolvency, not illiquidity, just as in the subprime crisis.

5 See Agarwal et al. (2012) . Fannie Mae and Freddie Mac received a mandate to support low-income housing in 2003. This was actually helpful to these agencies in expanding their activities beyond their initial charter and in growing by purchasing subprime residential mortgage-backed securities.

6 It is argued that ROE is used extensively as a performance benchmark for executive compensation in banking. This may provide one explanation for why bankers resist higher capital requirements.

7 For an initial stab at this, see Thakor (2015b) .

8 The credit crunch was the symptom, rather than the cause, of the crisis.

9 See Marshall (2009) .

10 See Benmelech and Dlugosz (2009) .

11 See Gorton and Metrick (2012) . A “repo” is a repurchase transaction, a vehicle for short-term borrowing secured by a marketable security. A “haircut” on a repo is the discount relative to the market value of the security offered as collateral in a repurchase transaction that the borrower must accept in terms of how much it can borrow against that collateral.

12 The shadow banking system consists of a variety of nondepository financial institutions—like investment banks, brokerage houses, finance companies, insurance companies, securitization structures for a variety of asset-backed securities, and money-market mutual funds—that borrow (mostly short-term) in the financial market, using funding arrangements like commercial paper and repos that are backed by, among other things, the securities generated by securitization.

13 See Marshall (2009) .

14 “The odds are only about 1 in 10,000 that a bond will go from highest grade, AAA, to the low-quality CCC level during a calendar year,” as reported in “Anatomy of a Ratings Downgrade,” BusinessWeek , October 1, 2007. This notion that investors were “surprised” by the realization of a previously unforeseen risk is similar to Gennaioli, Shleifer, and Vishny’s (2012) assumptions that investors ignore tail risks, as well as the idea of Fostel and Geanakoplos (2012) that financial innovation created new securities whose returns significantly depended on the continuation of favorable economic conditions.

15 He and Manela (2012) note that Washington Mutual actually suffered two separate bank runs. One was a gradual withdrawal of deposits totaling $9 billion during the first 20 days in July 2008 after Indy Mac failed, and the other resulted in $15 billion in deposit withdrawals during 15 days in September 2008, then culminating in the FDIC takeover.

16 One of these initiatives involves the strengthening of the Community Reinvestment Act (CRA) in the mid-1990s. Agarwal et al. (2012) provide evidence that they interpret as suggesting that the CRA led to riskier lending by banks. They find that in the six quarters surrounding the CRA exams, lending increases on average by 5% every quarter, and loans in those quarters default about 15% more often. Another important development was the regulatory change represented by the Bankruptcy Abuse Prevention and Consumer Protection Act of 2005 (BAPCA). BAPCA expanded the definition of repurchase agreements to include mortgage loans, mortgage-related securities, and interest from these loans and securities. This meant that repo contracts on MBS, collateralized debt obligations (CDOs), and the like as collateral became exempt from automatic stay in bankruptcy (see Acharya and Öncü 2011 ). This made MBS and other mortgage-related securities more liquid, increasing demand for these securities and creating stronger mortgage origination incentives for banks. Song and Thakor (2012) provide a theory of how politics shapes bank regulation.

17 Many investment banks retained the asset-backed securities they could not sell and financed them with increased leverage. This made these banks riskier.

18 It can be shown theoretically that the OTD model of securitization makes it less costly for banks to relax credit standards, invest less in screening, and make riskier loans, resulting in higher systematic risk. See Cortes and Thakor (2015) .

19 As of early 2009, the U.S. housing market was valued at about $19.3 trillion. See Barth et al. (2009) .

20 As long as investors agree on these financial products being worthy of investment. The risk that investors may later change their minds is a form of “model risk.”

21 The “Taylor rule” is a monetary policy rule that stipulates how much the central bank should change the nominal interest rate in response to changes in inflation, output, or other economic conditions. Specifically, the rule, attributed to John B. Taylor, stipulates each 1% increase in inflation should be met with a more than 1% increase in the nominal interest rate by the central bank.

22 See Bebchuk and Fried (2010) and Litan and Bailey (2009) , for example. This risk taking also involved correlated asset choices and correlated high leverage choices by financial institutions. See Acharya, Mehran, and Thakor (2013) and Goel, Song, and Thakor (2014) for theories of correlated leverage and asset choices.

23 See, for example, Boot and Thakor (1993) , Kane (1990) , and Barth, Caprio, and Levine (2012) .

24 See Johnson and Kwak (2010) and Stiglitz (2010) .

25 The report claims that industry players and government regulators saw warning signs of the impending crisis but chose to ignore them. It blames the Federal Reserve for being too supportive of industry growth objectives, including a desire to encourage growth in the subprime lending market. Nonetheless, it appears that there were some in the Federal Reserve System and other regulatory agencies who had concerns. Andrews (2007) writes “Edward M. Gramlich, a Federal Reserve governor who died in September, warned nearly seven years ago that a fast-growing new breed of lenders as luring many people into risky mortgages they could not afford. But when Mr. Gramlich privately urged Fed examiners to investigate mortgage lenders affiliated with national banks, he was rebuffed by Alan Greenspan, the Fed chairman. In 2001, a senior Treasury official, Sheila C. Bair, tried to persuade subprime lenders to adopt a code of ‘best practices’ and to let outside monitors verify their compliance. None of the lenders would agree to the monitors, and many rejected the code itself. Even those who did adopt those practices, Ms. Bair recalled recently, soon let them slip.”

26 The incentives for rating agencies to issue “inflated” ratings have been attributed to the “issuer pays” model, which involves the issuer of the debt securities paying the rating agency to obtain a rating. Competition for business among rating agencies is then typically viewed as incenting rating agencies to cater to the issuer’s wishes by assigning “inflated” ratings. See Becker and Milbourn (2011) for empirical evidence.

27 See Pfleiderer (2012). The incentive to increase leverage in the presence of safety nets is not a new phenomenon. After the Bank of England was established as a lender of last resort, many British banks became highly levered, and this was a contributing factor to the 1857 crisis.

28 Cortes and Thakor (2015) develop a model that explains how managerial career concerns get diluted in the securitization of large loan pools.

29 During 2004–2007, the period directly leading to the crisis, the IMF reported that individual financial institutions were sound. The Independent Evaluation Office (IEO) of the IMF (2011) recently criticized the IMF for failing to warn about risks and vulnerabilities in the financial system.

30 A related theory is developed by Thakor (forthcoming) , where the “availability heuristic”—a behavioral bias that leads agents to use mental shortcuts that rely on readily available data to draw inferences—leads to an overestimation of the skill of bankers. This permits very risky investments to be financed by thinly-capitalized banks, increasing the probability of a future crisis. This theory explains why the economy falls to pieces after a crisis and predicts that the development of a loan resale market will improve loan liquidity but increase the probability of a financial crisis.

31 See Cecchetti (2008) .

32 See Jagannathan, Kapoor, and Schaumburg (2013) .

33 See Cecchetti (2008) .

34 The study attributes this disassociation from 2002–2005 to the increase in the securitization of subprime mortgages.

35 See Goel, Song, and Thakor (2014) .

36 This does not necessarily rule out “model risk,” that is, lenders relying on an incorrect model of borrower risk determination.

37 The quality of loans is measured as the performance of loans, adjusted for differences in borrower characteristics, such as the credit score, level of indebtedness, loan amount, and ability to provide documentation, differences in loan characteristics, such as product type, amortization term, loan amount, and mortgage interest rate, and macroeconomic conditions, such as house price appreciation, level of neighborhood income, and change in unemployment

38 This does not necessarily rule out “model risk,” that is, lenders relying on an incorrect model of borrower risk determination.

39 This may provide one explanation for Berger and Bouwman’s (2013) finding that higher-capital banks have a higher probability of surviving a financial crisis.

40 See Reinhart and Rogoff (2008) for evidence on this.

41 Adding to the woes of these borrowers were “negative amortization” loans in which part of the interest was added to the principal (to lower initial payments), so that the principal increased, rather than falling, over time.

42 See Gorton and Metrick (2012) .

43 See Gorton and Metrick (2012) .

44 See Gorton and Metrick (2012) .

45 This was a run on shadow banks. See Covitz, Liang, and Suarez (2013) .

46 See, for example, Lawrence (2014) .

47 So if there are no solvency concerns and banks are sufficiently highly capitalized, liquidity problems are likely to be nonexistent over even intermediate time horizons, primarily because market participants with relatively deep pockets will take advantage of opportunities created by short-term liquidity shortages. Such self-correcting market mechanisms will largely obviate the need for any government intervention.

48 An essential difference between a liquidity and a solvency crisis is that the former is a market-wide phenomenon that engulfs all banks, whereas the latter is a bank-specific phenomenon that affects only banks whose solvency is in question due to perceptions of deteriorating asset quality. For example, in discussing the liquidity crisis in their model, Diamond and Rajan (2011) note “Moreover, the institutional overhang will affect lending not only by distressed banks, but also by healthy potential lenders, a feature that distinguishes this explanation from those where the reluctance to lend is based on the poor health of either the bank or its borrowers.”

49 This is consistent with the interpretation of the liquidity shock in Diamond and Rajan (2011) .

50 The implications of a liquidity crisis for banks with different capital structures are hard to derive since models in which a liquidity crisis arises typically involve no capital structure choice for the bank—the bank is funded entirely with deposits or short-term debt, for example, Diamond and Dybvig (1983) and Diamond and Rajan (2011) .

51 This difference is always positive for any risky lending, regardless of whether it is a liquidity or an insolvency crisis, but the point is that a liquidity crisis should not cause the difference to spike up significantly, whereas an insolvency crisis should.

52 Fahlenbrach, Prilmeier, and Stulz (2012) support the idea that problems faced by institutions in this crisis were specific to these institutions and not to market-wide phenomena. The paper shows that a bank’s stock return performance during the 1998 crisis predicts its stock return performance and failure likelihood during the 2007–2009 crisis, highlighting the importance of bank-specific attributes like business models and credit culture.

53 Unsecured-secured spread = LIBOR minus Repo rate on government-backed collateral.

54 Facilitated, according to Taylor (2009) , by the Federal Reserve’s easy-money monetary policies.

55 See Marshall (2009) .

56 This discussion is based on the Board of Governors of the Federal Reserve; available at www.federalreserve.gov/monetarypolicy/bst_crisisresponse.html .

57 Tirole (2012) develops a theoretical model in which such intervention by the central bank can unfreeze the credit market.

58 See, for example, Bernanke (2000) . The subprime crisis of 2007–2009 has been frequently compared with the Great Depression. The Economist (November 8, 2013) notes, “Since the start of what some now call the “Great Recession” in 2007, economists have been unable to avoid comparing it with the Depression of the early 1930s. For some, the comparisons are explicit. Economists like Paul Krugman and Barry Eichengreen have drawn parallels between the two slumps. Oliver Blanchard, chief economist of the International Monetary Fund (IMF), warned several times over the last few years that the world risked falling into a new ‘Great Depression,’ Economic historians themselves have had an unprecedented role in policy making during the recent crisis. Ben Bernanke at the Federal Reserve and Obama-administration advisors like Christina Romer all have academic backgrounds in the discipline.”

59 Market disruptions that occurred outside the Taylor and Williams (2009) sample period (e.g., during and after Fall 2008) may have reflected liquidity concerns. In September 2008, even high-quality nonfinancial companies seemed to experience higher borrowing costs and constraints on borrowing in the commercial paper market. Of course, this may simply have reflected the perception of dimming prospects for the real economy, rather than a market-wide liquidity crunch per se.

60 For example, regulatory-mandated “haircuts” in repo transactions and “skin-in-the-game” requirements for securitized mortgages (requiring originating banks to hold some of the equity tranche in securitizations) are ways to implement capital requirements in shadow banking. By ensuring that shadow banks are subject to the necessary capital requirements, regulators can minimize the ability of depository institutions to evade higher capital requirements by shifting activities to the less-regulated shadow banking sector. This would counter one of the typical arguments made against raising capital requirements for banks.

61 Admati et al. (2012) also advocate higher capital requirements, partly on the basis of the observation that debt overhang problems obstruct the voluntary infusion of more capital by banks themselves. Pfleiderer (2012) points out that one reason why banks are attracted to high leverage is that implicit and explicit safety nets provide banks higher credit ratings and hence lower yields on their debt than other firms.

62 A related impediment is the disagreement, even among qualitatively oriented capital structure models, related to whether banks should be highly levered or have high levels of capital. See Thakor (2014) for a discussion of these competing theoretical viewpoints.

63 The basic premise is that higher bank capital levels lead to lower bank values because they decrease shareholder value in banking or they lead to less discipline on banks, causing banks, in turn, to engage in a lower level of value-creating activities. See Thakor (2014) for a detailed discussion.

64 A good example is credit default swaps (CDSs), an insurance policy that was not regulated by either the Federal Reserve or insurance regulations because regulation tends to be based on product labels rather than on economic function, and there is little coordination among regulators.

65 As discussed earlier, the interaction of political factors, regulatory initiatives, and monetary policy may have created the incentives for financial institutions to take excessive risk, then leading to elevated insolvency concerns and the crisis. That is, excess liquidity may have led to an insolvency crisis.

66 They have developed a new measure of systemic risk, SRISK, which calculates the amount of capital banks would need to withstand a systemic crisis, defined as a 40% drop in equity market value.

67 For papers dealing with the pros and cons of large banks, see Bertay, Demirguc-Kunt, and Huizinga (2013) and Hughes and Mester (2013) .

68 See Thakor (2015b) for a discussion. Guiso, Sapienza, and Zingales (2014) examine the impact of governance structure on corporate culture.

Google Scholar

Google Preview

Email alerts

Citing articles via.

• Recommend to your Library

Affiliations

• Online ISSN 2046-9136
• Print ISSN 2046-9128
• Copyright © 2024 Society for Financial Studies
• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Institutional account management
• Rights and permissions
• Get help with access
• Accessibility
• Advertising
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

The real effects of the financial crisis

• Download the final draft
• Download the presentation
• Data and programs

Subscribe to the Hutchins Roundup and Newsletter

Ben s. bernanke ben s. bernanke distinguished senior fellow - the brookings institution, economic studies.

September 13, 2018

This paper is part of the Fall 2018 edition of the Brookings Papers on Economic Activity, the leading conference series and journal in economics for timely, cutting-edge research about real-world policy issues. Research findings are presented in a clear and accessible style to maximize their impact on economic understanding and policymaking. The editors are Brookings Nonresident Senior Fellow and Northwestern University Economics Professor  Janice Eberly  and  James  Stock , Brookings Nonresident Senior Fellow and Harvard University economics professor.   Read summaries of all  five papers from the journal here .

Economists both failed to predict the global financial crisis and underestimated its consequences for the broader economy. Focusing on the second of these failures, this paper make two contributions. First, I review research since the crisis on the role of credit factors in the decisions of households, firms, and financial intermediaries and in macroeconomic modeling. This research provides broad support for the view that credit-market developments deserve greater attention from macroeconomists, not only for analyzing the economic effects of financial crises but in the study of ordinary business cycles as well. Second, I provide new evidence on the channels by which the recent financial crisis depressed economic activity in the United States. Although the deterioration of household balance sheets and the associated deleveraging likely contributed to the initial economic downturn and the slowness of the recovery, I find that the unusual severity of the Great Recession was due primarily to the panic in funding and securitization markets, which disrupted the supply of credit. This finding helps to justify the government’s extraordinary efforts to stem the panic in order to avoid greater damage to the real economy.

Bernanke, Ben. 2018. “The Real Effects of the Financial Crisis.” Brookings Papers on Economic Activity , Fall, 251-342.

Conflict of Interest Disclosure

Dr. Ben S. Bernanke is a Distinguished Fellow in residence with the Economic Studies Program at the Brookings Institution, as well as a Senior Advisor to PIMCO and Citadel. The author did not receive financial support from any firm or person for this paper or from any firm or person with a financial or political interest in this paper. With the exception of the aforementioned, he is currently not an officer, director, or board member of any organization with an interest in this paper. No outside party had the right to review this paper before circulation.

Related Content

Ben S. Bernanke

Federal Reserve

Economic Studies

The Hutchins Center on Fiscal and Monetary Policy

David Wessel

August 21, 2024

Aaron Klein

July 29, 2024

Louise Sheiner

January 12, 2024

The Great Recession of 2008-2009: Causes, Consequences and Policy Responses

IZA Discussion Paper No. 4934

62 Pages Posted: 29 Jun 2010

Sher Verick

International Labour Organization (ILO); IZA Institute of Labor Economics

Iyanatul Islam

Griffith University - Griffith Asia Institute

Starting in mid-2007, the global financial crisis quickly metamorphosed from the bursting of the housing bubble in the US to the worst recession the world has witnessed for over six decades. Through an in-depth review of the crisis in terms of the causes, consequences and policy responses, this paper identifies four key messages. Firstly, contrary to widely-held perceptions during the boom years before the crisis, the paper underscores that the global economy was by no means as stable as suggested, while at the same time the majority of the world's poor had benefited insufficiently from stronger economic growth. Secondly, there were complex and interlinked factors behind the emergence of the crisis in 2007, namely loose monetary policy, global imbalances, misperception of risk and lax financial regulation. Thirdly, beyond the aggregate picture of economic collapse and rising unemployment, this paper stresses that the impact of the crisis is rather diverse, reflecting differences in initial conditions, transmission channels and vulnerabilities of economies, along with the role of government policy in mitigating the downturn. Fourthly, while the recovery phase has commenced, a number of risks remain that could derail improvements in economies and hinder efforts to ensure that the recovery is accompanied by job creation. These risks pertain in particular to the challenges of dealing with public debt and continuing global imbalances.

Keywords: global financial crisis, unemployment, macroeconomic policy, labour market policy

JEL Classification: E24, E60, G01, J08, J60

Suggested Citation: Suggested Citation

Sher Verick (Contact Author)

International labour organization (ilo) ( email ).

Route des Morillons 4 Geneva, 1211 Switzerland

IZA Institute of Labor Economics ( email )

P.O. Box 7240 Bonn, D-53072 Germany

Griffith University - Griffith Asia Institute ( email )

Queensland, 4111 Australia

Do you have a job opening that you would like to promote on SSRN?

Paper statistics, related ejournals, iza institute of labor economics discussion paper series.

Subscribe to this free journal for more curated articles on this topic

Macroeconomics: Monetary & Fiscal Policies eJournal

Subscribe to this fee journal for more curated articles on this topic

Macroeconomics: Prices, Business Fluctuations, & Cycles eJournal

Labor: public policy & regulation ejournal.

2008 Financial Crisis: Causes and Costs

• BCP Business & Management 41:303-308
• This person is not on ResearchGate, or hasn't claimed this research yet.

Discover the world's research

• 25+ million members
• 160+ million publication pages
• 2.3+ billion citations
• Christophy J Dodd
• Barney Frank
• Shen Posner
• John C Dugan
• Dong Yuping
• Bian Weihong
• Zhu Yuanqian
• Recruit researchers
• Join for free
• Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up

• Previous Article

Contributor Notes

This paper reviews the literature on financial crises focusing on three specific aspects. First, what are the main factors explaining financial crises? Since many theories on the sources of financial crises highlight the importance of sharp fluctuations in asset and credit markets, the paper briefly reviews theoretical and empirical studies on developments in these markets around financial crises. Second, what are the major types of financial crises? The paper focuses on the main theoretical and empirical explanations of four types of financial crises—currency crises, sudden stops, debt crises, and banking crises—and presents a survey of the literature that attempts to identify these episodes. Third, what are the real and financial sector implications of crises? The paper briefly reviews the short- and medium-run implications of crises for the real economy and financial sector. It concludes with a summary of the main lessons from the literature and future research directions.

• I. Introduction

The 2007-09 global financial crisis has been a painful reminder of the multifaceted nature of crises. They hit small and large countries as well as poor and rich ones. As fittingly described by Reinhart and Rogoff (2009a) , “financial crises are an equal opportunity menace.” They can have domestic or external origins, and stem from private or public sectors. They come in different shapes and sizes, evolve over time into different forms, and can rapidly spread across borders. They often require immediate and comprehensive policy responses, call for major changes in financial sector and fiscal policies, and can necessitate global coordination of policies.

The widespread impact of the latest global financial crisis underlines the importance of having a solid understanding of crises. As the latest episode has vividly showed, the implications of financial turmoil can be substantial and greatly affect the conduct of economic and financial policies. A thorough analysis of the consequences of and best responses to crises has become an integral part of current policy debates as the lingering effects of the latest crisis are still being felt around the world.

This paper provides a selected survey of the literature on financial crises. 2 Crises are, at a certain level, extreme manifestations of the interactions between the financial sector and the real economy. As such, understanding financial crises requires an understanding of macro-financial linkages, a truly complex challenge in itself. The objective of this paper is more modest: it presents a focused survey considering three specific questions. First, what are the main factors explaining financial crises? Second, what are the major types of financial crises? Third, what are the real and financial sector implications of crises? The paper also briefly reviews the literature on the prediction of crises and the evolution of early warning models.

Section II reviews the main factors explaining financial crises. A financial crisis is often an amalgam of events, including substantial changes in credit volume and asset prices, severe disruptions in financial intermediation, notably the supply of external financing, large scale balance sheet problems, and the need for large scale government support. While these events can be driven by a variety of factors, financial crises often are preceded by asset and credit booms that then turn into busts. As such, many theories focusing on the sources of financial crises have recognized the importance of sharp movements in asset and credit markets. In light of this, this section briefly reviews theoretical and empirical studies analyzing the developments in credit and asset markets around financial crises.

Section III classifies the types of financial crises identified in many studies. It is useful to classify crises in four groups: currency crises; sudden stop (or capital account or balance of payments) crises; debt crises; and banking crises. The section summarizes the findings of the literature on analytical causes and empirical determinants of each type of crisis.

The identification of crises is discussed in Section IV . Theories, that are designed to explain crises, are used to guide the literature on the identification of crises. However, it has been difficult to transform the predictions of the theories into practice. While it is easy to design quantitative methods to identify currency (and inflation) crises and sudden stops, the identification of debt and banking crises is typically based on qualitative and judgmental analyses. Irrespective of the classification one uses, different types of crises are likely to overlap. Many banking crises, for example, are also associated with sudden stop episodes and currency crises. The coincidence of multiple types of crises leads to further challenges of identification. The literature therefore employs a wide range of methods to identify and classify crises. The section considers various identification approaches and reviews the frequency of crises over time and across different groups of countries.

Section V analyzes the implications of financial crises. The macroeconomic and financial implications of crises are typically severe and share many commonalities across various types. Large output losses are common to many crises, and other macroeconomic variables typically register significant declines. Financial variables, such as asset prices and credit, usually follow qualitatively similar patterns across crises, albeit with variations in terms of duration and severity of declines. The section examines the short- and medium-run effects of crises and presents a set of stylized facts with respect to their macroeconomic and financial implications.

Section VI summarizes the main methods used for predicting crises. It has been a challenge to predict the timing of crises. Financial markets with high leverage can easily be subject to crises of confidence, making fickleness the main reason why the exact timing of crises is very difficult to predict. Moreover, the nature of crises changes over time as economic and financial structures evolve. Not surprisingly, early warning tools can quickly become obsolete or inadequate. This section presents a summary of the evolution of different types of prediction models and considers the current state of early warning models.

The last section concludes with a summary and suggestions for future research. It first summarizes the major lessons from this literature review. It then considers the most relevant issues for research in light of these lessons. One is that future research should be geared to eliminate the “this-time-is-different” syndrome. However, this is a very broad task requiring to address two major questions: How to prevent financial crises? And, how to mitigate their costs when they take place? In addition, there have to be more intensive efforts to collect necessary data and to develop new methodologies in order to guide both empirical and theoretical studies.

II. Explaining Financial Crises

While financial crises have common elements, they do come in many forms. A financial crisis is often associated with one or more of the following phenomena: substantial changes in credit volume and asset prices; severe disruptions in financial intermediation and the supply of external financing to various actors in the economy; large scale balance sheet problems (of firms, households, financial intermediaries and sovereigns); and large scale government support (in the form of liquidity support and recapitalization). As such, financial crises are typically multidimensional events and can be hard to characterize using a single indicator.

The literature has clarified some of the factors driving crises, but it remains a challenge to definitively identify their deeper causes. Many theories have been developed over the years regarding the underlying causes of crises. While fundamental factors—macroeconomic imbalances, internal or external shocks—are often observed, many questions remain on the exact causes of crises. Financial crises sometimes appear to be driven by “irrational” factors. These include sudden runs on banks, contagion and spillovers among financial markets, limits to arbitrage during times of stress, emergence of asset busts, credit crunches, and fire-sales, and other aspects related to financial turmoil. Indeed, the idea of “animal spirits” (as a source of financial market movements) has long occupied a significant space in the literature attempting to explain crises ( Keynes, 1930 ; Minsky, 1975 ; Kindleberger, 1978 ). 3

Financial crises are often preceded by asset and credit booms that eventually turn into busts. Many theories focusing on the sources of crises have recognized the importance of booms in asset and credit markets. However, explaining why asset price bubbles or credit booms are allowed to continue and eventually become unsustainable and turn into busts or crunches has been challenging. This naturally requires answering why neither financial market participants nor policy makers foresee the risks and attempt to slow down the expansion of credit and increase in asset prices.

The dynamics of macroeconomic and financial variables around crises have been extensively studied. Empirical studies have documented the various phases of financial crises, from initial, small-scale financial disruptions to large-scale national, regional, or even global crises. They have also described how, in the aftermath of financial crises, asset prices and credit growth can remain depressed for a long time and how crises can have long-lasting consequences for the real economy. Given their central roles, we next briefly discuss developments in asset and credit markets around financial crises.

• A. Asset Price Booms and Busts

Sharp increases in asset prices, sometimes called bubbles, and often followed by crashes have been around for centuries. Asset prices sometimes seem to deviate from what fundamentals would suggest and exhibit patterns different than predictions of standard models with perfect financial markets. A bubble, an extreme form of such deviation, can be defined as “ the part of a grossly upward asset price movement that is unexplainable based on fundamentals” ( Garber, 2000 ). Patterns of exuberant increases in asset prices, often followed by crashes, figure prominently in many accounts of financial instability, both for advanced and emerging market countries alike, going back millenniums (see Evanoff, Kaufman, Malliaris (2012) and Scherbina (2013) for detailed reviews of asset price bubbles).

Some asset price bubbles and crashes are well known. Such historical cases include the Dutch Tulip Mania from 1634 to 1637, the French Mississippi Bubble in 1719-20, and the South Sea Bubble in the United Kingdom in 1720 ( Garber, 2000 ; Kindleberger, 1986 ). During some of these periods, certain asset prices increased very rapidly in a short period of time, followed by sharp corrections. These cases are extreme, but not unique. In the recent financial crisis, for example, house prices in a number of countries have followed this inverse U-shape pattern ( Figure 1 ).

Evolution of House Prices During Financial Crises

Citation: IMF Working Papers 2013, 028; 10.5089/9781475561005.001.A001

• Download Figure
• Download figure as PowerPoint slide

What explains asset price bubbles?

Formal models attempting to explain asset price bubbles have been developed for some time. Some of these models consider how individual rational behavior can lead to collective mispricing, which in turn can result in bubbles. Others rely on microeconomic distortions that can lead to mispricing. Some others assume “irrationality” on the part of investors. Although there are parallels, explaining asset price busts (such as fire-sales) often requires accounting for different factors than explaining bubbles.

Some models employing rational investors can explain bubbles without distortions. These consider asset price bubbles as agents’ “justified” expectations about future returns. For example, in Blanchard and Watson (1982) , under rational expectations, the asset price does not need to equal its fundamental value, leading to “rational” bubbles. Thus, observed prices, while exhibiting extremely large fluctuations, are not necessarily excessive or irrational. These models have been applied relatively successfully to explain the internet “bubble” of the late 1990s. Pastor and Veronesi (2006) show how a standard model can reproduce the valuation and volatility of internet stocks in the late 1990s, thus arguing that there is no reason to refer to a “dotcom bubble.” Branch and Evans (2008) , employing a theory of learning where investors use most recent (instead of past) data, find that shocks to fundamentals may increase return expectations. This may cause stock prices to rise above levels consistent with fundamentals. As prices increase, investors’ perceived riskiness declines until the bubble bursts. 4 More generally, theories suggest that bubbles can appear without distortions, uncertainty, speculation, or bounded rationality (see Garber (2000) and Scherbina (2013) for reviews of models of bubbles).

But both micro distortions and macro factors can lead to bubbles as well. Bubbles may relate to agency issues ( Allen and Gale, 2007 ). For example, due to risk shifting – as when agents borrow to invest (e.g., margin lending for stocks, mortgages for housing), but can default if rates of return are not sufficiently high – prices can escalate rapidly. Fund managers who are rewarded on the upside more than on the downside (somewhat analogous to limited liability of financial institutions), bias their portfolios towards risky assets, which may trigger a bubble ( Rajan, 2005 ). 5 Other microeconomic factors (e.g., interest rate deductibility for household mortgages and corporate debt) can add to this, possibly leading to bubbles (see BIS, 2002 for a general review, and IMF (2009) for a review of debt and other biases in tax policy with respect to the recent financial crisis).

Investors’ behavior can also drive asset prices away from fundamentals, at least temporarily. Frictions in financial markets (notably those associated with information asymmetries) and institutional factors can affect asset prices. Theory suggests, for example, that differences of information and opinions among investors (related to disagreements about valuation of assets), short sales constraints, and other limits to arbitrage are possible reasons for asset prices to deviate from fundamentals. 6 Mechanisms, such as herding among financial market players, informational cascades, and market sentiment, can affect asset prices. Virtuous feedback loops – rising asset prices, increasing net worth positions, allowing financial intermediaries to leverage up, and buy more of the same assets – play a significant role in driving the evolution of bubbles. The phenomenon of contagion – spillovers beyond what “fundamentals” suggest – may have similar roots. Brunnermeier (2001) reviews these models and show how they can help understand bubbles, crashes, and other market inefficiencies and frictions. Empirical work confirms some of these channels, but formal econometric tests are most often not powerful enough to separate bubbles from rational increases in prices, let alone to detect the causes of bubbles ( Gürkaynak, 2008 ). 7

Bubbles may also be the results of the same factors that are argued to lead to asset price anomalies. Many “deviations” of asset prices from the predictions of efficient markets models, on a small scale with no systemic implications, have been documented ( Schwert, 2003 and Lo and MacKinlay, 2001 , and earlier Fama 1998 review). 8 While some of these deviations have diminished over time, possibly as investors have implemented strategies to exploit them, others, even though documented extensively, persist to today. Furthermore, deviations have been found in similar ways across various markets, time periods, and institutional contexts. As such, anomalies cannot easily be attributed to specific, institution-related distortions. Rather, they appear to reflect factors intrinsic to financial markets. Studies under the rubric of “behavioral finance” have tried to explain these patterns, with some success ( Shleifer 2000 , and Barberis and Thaler 2003 review). 9 Of course, “evidence of irrationally” may reflect a mis-specified model, i.e., irrational behavior is not easily falsifiable.

Busts following bubbles can be triggered by small shocks. Asset prices may experience small declines, whether due to changes in fundamental values or sentiment. Changes in international financial and economic conditions, for example, may drive prices down. The channels by which such small declines in asset prices can trigger a crisis are well understood by now. Given information asymmetries, for example, a small shock can lead to market freezes. Adverse feedback loops may then arise, where asset prices exhibit rapid declines and downward spirals. Notably, a drop in prices can trigger a fire sale, as financial institutions experiencing a decline in asset values struggle to attract short-term financing. Such “sudden stops” can lead to a cascade of forced sales and liquidations of assets, and further declines in prices, with consequences for the real economy.

Flight to quality can further intensify financial turmoil. Relationships among financial intermediaries are multiple and complex. Information asymmetries are prevalent among intermediaries and in financial markets. These problems can easily lead to financial turmoil. They can be aggravated by preferences of investors to hold debt claims ( Gorton, 2008 ). Specifically, debt claims are “low information-intensive” in normal states of the world – as the risk of default is remote, they require little analysis of the underlying asset value. They become “high information-intensive,” however, in times of financial turmoil as risks increase, requiring investors to assess default risks, a complex task involving a multitude of information problems. This puts a premium on safety and can create perverse spirals. As investors flight to quality assets, e.g., government bonds, they avoid some, lower quality types of debt claims, leading to sharper drops in their prices ( Gorton and Ordonez, 2012 ).

• B. Credit Booms and Busts

A rapid increase in credit is another common thread running through the narratives of events prior to financial crises. Leverage buildups and greater risk-taking through rapid credit expansion, in concert with increases in asset prices, often precede crises (albeit typically only recognized with the benefits of hindsight). Both distant past and more recent crises episodes typically witnessed a period of significant growth in credit (and external financing), followed by busts in credit markets along with sharp corrections in asset prices. In many respects, the descriptions of the Australian boom and bust of the 1880-90s, for example, fit the more recent episodes of financial instability. Likewise, the patterns before the East Asian financial crisis in the late-1990s resembled those of the earlier ones in Nordic countries as banking systems collapsed following periods of rapid credit growth related to investment in real estate. The experience of the United States in the late 1920s and early 1930s exhibits some features similar to the run-up to the recent global financial crisis with, beside rapid growth in asset prices and land speculation, a sharp increase in (household) leverage. The literature has also documented common patterns in various other macroeconomic and financial variables around these episodes.

What explains credit booms?

Credit booms can be triggered by a wide range of factors, including shocks and structural changes in markets. 10 Shocks that can lead to credit booms include changes in productivity, economic policies, and capital flows. Some credit booms tend to be associated with positive productivity shocks. These generally start during or after periods of buoyant economic growth. Dell’Ariccia and others (2013) find that lagged GDP growth is positively associated with the probability of a credit boom: in the three-year period preceding a boom, the average real GDP growth rate reaches 5.1 percent, compared to 3.4 percent during a tranquil three-year period.

Sharp increases in international financial flows can amplify credit booms. Most national financial markets are affected by global conditions, even more so today, making asset bubbles easily spill across borders. Fluctuations in capital flows can amplify movements in local financial markets when inflows lead to a significant increase in the funds available to banks, relaxing credit constraints for corporations and households ( Claessens et al. 2010 ). Rapid expansion of credit and sharp growth in house and other asset prices were indeed associated with large capital inflows in many countries before the recent financial crisis.

Accommodative monetary policies, especially when in place for extended periods, have been linked to credit booms and excessive risk taking. The channel is as follows. Interest rates affect asset prices and borrower’s net worth, in turn affecting lending conditions. Analytical models, including on the relationship between agency problems and interest rates (e.g., Stiglitz and Weiss, 1981 ), suggest more risk-taking when interest rates decline and a flight to quality when interest rates rise, with consequent effects on the availability of external financing. Empirical evidence (e.g., for Spain, Maddaloni and Peydró, 2010 ; Ongena et al. 2009 ), supports such a channel as credit standards tend to loosen when policy rates decline. The relatively low interest rates in the U.S. during 2001-04 are often mentioned as a main factor behind the rapid increases in house prices and household leverage ( Lansing, 2008 ; Hirata et. al, 2012 ). 11

Structural factors include financial liberalization and innovation. Financial liberalization, especially when poorly designed or sequenced, and financial innovation can trigger credit booms and lead to excessive increases in leverage of borrowers and lenders by facilitating more risk taking. Indeed, financial liberalization has been found to often precede crises in empirical studies ( Kaminsky and Reinhart, 1999 ; Detragiache and Demirguc-Kunt, 2006). Dell’Ariccia and others (2013) report that roughly a third of booms they identify follow or coincide with financial liberalization episodes.

The mechanisms involved include institutional weaknesses as well as the perverse effects of competition. One channel seems to be that regulation, supervision, and market discipline is slow to catch up with greater competition and innovation (possibly set in motion by shocks or liberalization). Vulnerabilities in credit markets can naturally arise. Another mechanism commonly linking booms to crises is a decline in lending standards. Greater competition in financial services, while generally enhancing efficiency and stability in the long run, can contribute to financial fragility over shorter periods. For the latest crisis in the United States, this was evident in higher delinquency rates in those metropolitan areas with higher growth in loan origination prior to the onset of the crisis, with the deterioration in lending standards appearing in part related to increases in competition ( Dell’Ariccia, Igan and Laeven, 2012 ).

• C. Impact of Asset Price and Credit Busts

Sharp movements in asset and credit markets during financial crises are quite different from those normally observed. Asset prices and credit booms and busts differ from the movements observed over the course of a normal business cycle. Booms in credit and asset markets are shorter, stronger, and faster than other upturns. For example, these episodes often take place over relatively shorter time periods than other episodes and are associated with much faster increases in the financial variables ( Figure 2A ). The slope of a typical boom is two to three times larger than that of regular episodes. And crunches and busts are longer, deeper and more violent than other downturns. Credit crunches and asset price busts have much larger declines than other declines ( Figure 2B ). Specifically, credit crunches and house price busts lead to respectively roughly 10 and 15 times larger drops than other downturns, while equity busts more than 2.5 times as large. These episodes also last longer, some two times, than other downturns, with house price busts the longest of all, about 18 quarters, whereas a credit crunch and equity busts last about 10-12 quarters. Moreover, disruptions are more violent, as evidenced by higher slope coefficients, with busts in equity prices three times more violent than those in credit and house prices ( Claessens, Kose and Terrones, 2010a ).

Credit and Asset Price Booms

Credit Crunches and Asset Price Busts

There are typically adverse real effects of asset price busts and credit crunches on the real economy. 12 Asset price busts can affect bank lending and other financial institutions’ investment decisions and in turn the real economy through two channels. First, when borrowing/lending is collateralized and the market price of collateral falls, the ability of firms to rely on assets as collateral for new loans and financial institutions’ ability to extend new credit become impaired, which in turn adversely affect investment. Second, the prospect of large price dislocations arising from fire sales and related financial turmoil distorts decisions of financial institutions to lend or invest, prompting them inter alia to hoard cash. Through these channels, fire sales can trigger a credit crunch and cause a severe contraction in real activity.

Those asset price booms supported through leveraged financing and involving financial intermediaries appear to entail larger risks for the economy. Evidence from past episodes suggests that whether excessive movements in asset prices lead to severe misallocations of resources depends in large part on the nature of boom and how it is financed. Booms largely involving equity market activities appear to have lower risks of adverse consequences. The burst of the internet bubble of the late 1990s, which largely involved only equity markets, has not been very costly for the real economy. When banks are involved in financing asset price booms, however, as in real estate mortgage and corporate sector financing, risks of adverse consequences of a following asset bust are typically much higher. The main reason is that these booms involve leverage and banks, implying that the flow of credit to the economy gets interrupted when a bust occurs.

The burst of the latest bubble, as it was financed by banks (and the shadow banking system) and involving housing, has been very costly. For the most recent episode, Dell’Ariccia et al (2011) report that, in a 40-country sample, almost all the countries with “twin booms” in real estate and credit markets (21 out of 23) ended up suffering from either a crisis or a severe drop in GDP growth rate relative to the country’s performance in the 2003–07 period ( Figure 3 ). Eleven of these countries actually suffered both financial sector damage and a sharp drop in economic activity. In contrast, of the seven countries that experienced a real estate boom, but not a credit boom, only two went through a systemic crisis and, on average, had relatively mild recessions. We present a broader discussion of the real and financial implications of financial crises and disruptions in Section V .

Coincidence of Financial Booms and Crises

(fraction of total, in percent)

III. Types of Financial Crises

While financial crises can take various shapes and forms, in terms of classification, broadly two types can be distinguished. Reinhart and Rogoff (2009a) distinguish two types of crises: those classified using strictly quantitative definitions; and those dependent largely on qualitative and judgmental analysis. The first group mainly includes currency and sudden stop crises and the second group contains debt and banking crises. Regardless, definitions are strongly influenced by the theories trying to explain crises.

While financial crises can take various shapes and forms, the literature has been able to arrive at concrete definitions of many types of crises. For example, a currency crisis involves a speculative attack on the currency resulting in a devaluation (or sharp depreciation), or forcing the authorities to defend the currency by expending large amount of international reserves, or sharply raising interest rates, or imposing capital controls. A sudden stop (or a capital account or balance of payments crisis) can be defined as a large (and often unexpected) fall in international capital inflows or a sharp reversal in aggregate capital flows to a country, likely taking place in conjunction with a sharp rise in its credit spreads. Since these are measurable variables, they lend themselves to the use of quantitative methodologies.

Other crises are associated with adverse debt dynamics or banking system turmoil. A foreign debt crisis takes place when a country cannot (or does not want to) service its foreign debt. It can take the form of a sovereign or private (or both) debt crisis. A domestic public debt crisis takes place when a country does not honor its domestic fiscal obligations in real terms, either by defaulting explicitly, or by inflating or otherwise debasing its currency, or by employing some (other) forms of financial repression. In a systemic banking crisis, actual or potential bank runs and failures can induce banks to suspend the convertibility of their liabilities or compel the government to intervene to prevent this by extending liquidity and capital assistance on a large scale. Since these are not so easily measurable variables, they lend themselves more to the use of qualitative methodologies.

Other classifications are possible, but regardless the types of crises likely overlap. A number of banking crises, for example, are associated with sudden stop episodes and currency crises. We examine analytical causes and empirical determinants of each type of crisis in this section and consider the identification, dating and frequency of crises in the next section.

• A. Currency Crises

Theories on currency crises, often more precisely articulated than for other types of crises, have evolved over time in part as the nature of such crises has changed. In particular, the literature has evolved from a focus on the fundamental causes of currency crises, to emphasizing the scope for multiple equilibria, and to stressing the role of financial variables, especially changes in balance sheets, in triggering currency crises (and other types of financial turmoil). Three generations of models are typically used to explain currency crises that took place during the past four decades.

The first generation of models, largely motivated by the collapse in the price of gold, an important nominal anchor before the floating of exchange rates in the 1970s, was often applied to currency devaluations in Latin America and other developing countries ( Claessens, 1991 ). 13 These models are from seminal papers by Krugman (1979) and Flood and Garber (1984) , and hence called “KFG” models. They show that a sudden speculative attack on a fixed or pegged currency can result from rational behavior by investors who correctly foresee that a government has been running excessive deficits financed with central bank credit. Investors continue to hold the currency as long as they expect the exchange rate regime remain intact, but they start dumping it when they anticipate that the peg is about to end. This run leads the central bank to quickly lose its liquid assets or hard foreign currency supporting the exchange rate. The currency then collapses.

The second generation of models stresses the importance of multiple equilibria. These models show that doubts about whether a government is willing to maintain its exchange rate peg could lead to multiple equilibria and currency crises ( Obstfeld and Rogoff, 1986 ). In these models, self-fulfilling prophecies are possible, in which the reason investors attack the currency is simply that they expect other investors to attack the currency. As discussed in Flood and Marion (1997) , policies prior to the attack in the first generation models can translate into a crisis, whereas changes in policies in response to a possible attack (even if these policies are compatible with macroeconomic fundamentals) can lead to an attack and be the trigger of a crisis. The second generation models are in part motivated by episodes like the European Exchange Rate Mechanism crisis, where countries like the UK came under pressure in 1992 and ended up devaluing, even though other outcomes (that were consistent with macroeconomic fundamentals) were possible too (see Eichengreen, Rose and Wyplosz (1996) , Frankel and Rose (1996) ).

The third generation of crisis models explores how rapid deteriorations of balance sheets associated with fluctuations in asset prices, including exchange rates, can lead to currency crises. These models are largely motivated by the Asian crises of the late 1990s. In the case of Asian countries, macroeconomic imbalances were small before the crisis – fiscal positions were often in surplus and current account deficits appeared to be manageable, but vulnerabilities associated with financial and corporate sectors were large. Models show how balance sheets mismatches in these sectors can give rise to currency crises. For example, Chang and Velasco (2000) show how, if local banks have large debts outstanding denominated in foreign currency, this may lead to a banking cum currency crisis. 14

This generation of models also considers the roles played by banks and the self-fulfilling nature of crises. McKinnon and Pill (1996) , Krugman (1998), and Corsetti, Pesenti, and Roubini (1998) suggest that over-borrowing by banks can arise due to government subsidies (to the extent that governments would bail out failing banks). In turn, vulnerabilities stemming from over-borrowing can trigger currency crises. Burnside, Eichenbaum, and Rebelo ( 2001 and 2004 ) argue that crises can be self-fulfilling because of fiscal concerns and volatile real exchange rate movements (when the banking system has such a government guarantee, a good and/or a bad equilibrium can result). Radelet and Sachs (1998) argue more generally that self-fulfilling panics hitting financial intermediaries can force liquidation of assets, which then confirms the panic and leads to a currency crisis.

Empirical research has not been able to differentiate which generation of these models provides the best characterization of currency crises. Early work had good success with the KFG model. Blanco and Garber (1986) , for example, applied the KFG model to the Mexican devaluations in 1976 and 1981-82 and showed crisis probabilities to build up to peaks just before the devaluations ( Cumby and van Wijnbergen (1989) and Klein and Marion (1994) ). However, while the KFG model worked well in cases where macroeconomic fundamentals grow explosively, it was not successful when fundamentals are merely highly volatile and money-demand unstable.

Later empirical work moved away from explicit tests of structural models. Some studies used censored dependent variable models, e.g., Logit models, to estimate crisis probabilities based on a wide range of lagged variables ( Eichengreen, Rose and Wyploz (1996) , Frankel and Rose (1996) , Kumar et al (2003)). Others, such as Kaminsky, Lizondo, and Reinhart (1998) and Kaminsky and Reinhart (1999) , employed signaling models to evaluate the usefulness of several variables in signaling an impending crisis. While this literature has found that certain indicators tend to be associated with crises, the outcomes have been nevertheless disappointing, with the timing of crises very hard to predict (see Kaminsky, Lizondo and Reinhart (1998) for an early review, Kaminsky (2003) for an update, and Frankel and Saravelos (2012) for an extensive recent survey up to the 2000s). We will revisit the issue of crisis prediction later.

• B. Sudden Stops

Models with sudden stops make a closer association with disruptions in the supply of external financing. These models resemble the latest generation of currency crises models in that they also focus on balance sheet mismatches – notably currency, but also maturity – in financial and corporate sectors ( Calvo et al., 2006 ). They tend to give greater weight, however, to the role of international factors (as captured, for example, by changes in international interest rates or spreads on risky assets) in causing “sudden stops” in capital flows. These models can account for the current account reversals and the real exchange rate depreciation typically observed during crises in emerging markets. The models explain less well the typical sharp drops in output and total factor productivity (TFP).

In order to match data better, more recent sudden stop models introduce various frictions. While counterintuitive, in most models, a sudden stop cum currency crisis generates an increase in output, rather than a drop. This happens through an abrupt increase in net exports resulting from the currency depreciation. This has led to various arguments explaining why sudden stops in capital flows are associated with large output losses, as is often the case. Models typically include Fisherian channels and financial accelerator mechanisms, or frictions in labor markets, to generate an output drop during a sudden stop, without losing the ability to account for the movements of other variables.

Following closely the domestic literature, models with financial frictions help to account better for the dynamics of output and productivity in sudden stops. With frictions, e.g., when firms must borrow in advance to pay for inputs (e.g., wages, foreign inputs), a fall in credit – the sudden stop combined with rising external financing premium – reduces aggregate demand and causes a fall in output ( Calvo and Reinhart, 2000 ). Or because of collateral constraints in lending, a sudden stop can lead to a debt-deflation spiral of declines in credit, prices and quantity of collateral assets, resulting in a fall in output. Like the domestic financial accelerator mechanism, financial distress and bankruptcies cause negative externalities, as banks become more cautious and reduce new lending, in turn inducing a further fall in credit, and thereby contributing to a recession ( Calvo, 2000 ).

These types of amplification mechanisms can make small shocks cause sudden stops. Relatively small shocks – to imported input prices, the world interest rate, or productivity – can trigger collateral constraints on debt and working capital, especially when borrowing levels are high relative to asset values. Fisher’s style debt-deflation mechanisms can then cause sudden stops through a spiraling decline in asset prices and holdings of collateral assets ( Fisher, 1933 ). This chain of events immediately affects output and demand. Mendoza (2009) shows how a business cycle model with collateral constraints can be consistent with the key features of sudden stops. Korinek (2010) provides a model analyzing the adverse implications of large movements in capital flows on real activity.

Sudden stops often take place in countries with relatively small tradable sectors and large foreign exchange liabilities. Sudden stops have affected countries with widely disparate per capita GDPs, levels of financial development, and exchange rate regimes, as well as countries with different levels of reserve coverage. There are though two elements most episodes share, as Calvo, Izquierdo and Mejía (2008) document: a small supply of tradable goods relative to domestic absorption – a proxy for potential changes in the real exchange rate – and a domestic banking system with large foreign–exchange denominated liabilities, raising the probability of a “perverse” cycle.

Empirical studies find that many sudden stops have been associated with global shocks. For a number of emerging markets, e.g., those in Latin America and Asia in the 1990s and in Central and Eastern Europe in the 2000s, following a period of large capital inflows, a sharp retrenchment or reversal of capital flows occurred, triggered by global shocks (such as increases in interest rates or changes in commodity prices). Sudden stops are more likely with large cross-border financial linkages. Milesi-Ferretti and Tille (2011) document that rapid changes in capital flows were important triggers of local crises during the recent crisis. Other papers, e.g., Rose and Spiegel (2011) , however, find little role for international factors, including capital flows, in the spread of the recent crisis.

• C. Foreign and Domestic Debt Crises

Theories on foreign debt crises and default are closely linked to those explaining sovereign lending. Absent “gun-boat” diplomacy, lenders cannot seize collateral from another country, or at least from a sovereign, when it refuses to honor its debt obligations. Without an enforcement mechanism, i.e., the analogue to domestic bankruptcy, economic reasons, instead of legal arguments, are needed to explain why international (sovereign) lending exists at all.

Models developed rely, as a gross simplification, on either intertemporal or intratemporal sanctions. Intertemporal sanctions arise because of a threat of cutoff from future lending if a country defaults ( Eaton and Gersovitz, 1981 ). With no access (forever or for some time), the country can no longer smooth idiosyncratic income shocks using international financial markets. This cost can induce the country to continue its debt payments today, even though there are no immediate, direct costs to default. Intratemporal sanctions can arise from the inability to earn foreign exchange today because trading partners impose sanctions or otherwise shut the country out of international markets, again forever or for some time (Bulow and Rogoff, 1989a). Both types of costs can support a certain volume of sovereign lending (see Eaton and Fernandez, (1995) and Panizza, Sturzenegger and Zettelmeyer (2009) for reviews).

These models imply that inability or unwillingness to pay, i.e., default, can result from different factors. The incentives governments face in repaying debt differ from those for corporations and households in a domestic context. They also vary across models. In the intertemporal model, a country defaults when the opportunity cost of not being able to borrow ever again is low, one such case presumably being when the terms of trade is good and is expected to remain so ( Kletzer and Wright, 2000 ). In the intratemporal sanction model, in contrast, the costs of a cutoff from trade may be the least when the terms of trade is bad. Indeed, Aguiar and Gopinath (2006) demonstrate how in a model with persistent shocks, countries default in bad times to smooth consumption. The models thus also have different implications with respect to a country’s borrowing capacity.

Such models are unable, however, to fully account why sovereigns default and why creditors lend as much as they do. Many models actually predict that default does not happen in equilibrium as creditors and debtors avoid the dead-weight costs of default and renegotiate debt payments. While some models have been calibrated to match actual experiences of default, models often still underpredict the likelihood of actual defaults. Notably, countries do not always default when times are bad, as most models predict: Tomz and Wright (2007) report that in only 62 percent of defaults cases output was below trend. Models also underestimate the willingness of investors to lend to countries in spite of large default risk. Moreover, changes in the institutional environment, such as those implemented after the debt crises of the 1980s, do not appear to have modified the relation between economic and political variables and the probability of a debt default. Together, this suggests that models still fail to capture all aspects necessary to explain defaults ( Panizza, Sturzenegger and Zettelmeyer, 2009 ).

Although domestic debt crises have been prevalent throughout history, these episodes had received only limited attention in the literature until recently. Economic theory assigns a trivial role to domestic debt crises since models often assume that governments always honor their domestic debt obligations—the typical assumption is of the “risk-free” government assets. Models also often assume Ricardian equivalence, making government debt less relevant. However, recent reviews of history ( Reinhart and Rogoff, 2009a ) shows that few countries were able to escape default on domestic debt, with often adverse economic consequences.

This often happens through bouts of high inflation because of the abuse of governments’ monopoly on currency issuance. One such episode was when the U.S. experienced a rate of inflation close to 200 percent in the late 1770s. The periods of hyperinflation in some European countries following the World War II were also in this category. Debt defaults in the form of inflation are often followed by currency crashes. In the past, countries would often “debase” their currency by reducing the metal content of coins or switching to another metal. This reduced the real value of government debt and thus provided fiscal relief. There have also been other forms of debt “default,” including through financial repression ( Reinhart, Kirkegaard, and Sbrancia, 2011 ). After inflation or debasing crises, it takes a long time to convince the public to start using the currency with confidence again. This in turn significantly increases the fiscal costs of inflation stabilization, leading to large negative real effects of high inflation and associated currency crashes.

Debt intolerance tends to be associated with the “extreme duress” many emerging economies experience at levels of external debt that would often be easily managed by advanced countries. Empirical studies on debt intolerance and serial default suggests that, while safe debt thresholds hinge on country specific factors, such as a country’s record of default and inflation, when the external debt level of an emerging economy is above 30-35 percent of GNP, the likelihood of an external debt crisis rises substantially ( Reinhart and Rogoff, 2009b ). More importantly, when an emerging market country becomes a serial defaulter of its external debt, this increases its debt intolerance and, in turn, makes it very difficult to graduate to the club of countries that have continuous access to global capital markets.

Many challenges remain regarding modeling the countries’ ability to sustain various types of domestic and external debt. An important challenge is that the form of financing countries use is endogenous. Jeanne (2003) argues that short-term (foreign exchange) debt can be a useful commitment device for countries to employ good macroeconomic policies. Diamond and Rajan (2001) posit that banks in developing countries have little choice but to borrow short-term to finance illiquid projects given the low-quality institutional environment they operate in. Eichengreen and Hausmann (1999) propose the “original sin” argument explaining how countries with unfavorable conditions have no choice but to rely mostly on short-term, foreign currency denominated debt as their main source of capital. More generally, although short-term debt can increase vulnerabilities, especially when the domestic financial system is underdeveloped, poorly supervised, and subject to governance problems, it also may be the only source of (external) financing for a capital-poor country with limited access to equity or FDI inflows. This makes the countries’ choice of accumulating short-term debt and becoming more vulnerable to crises simultaneous outcomes.

More generally, the deeper causes driving debt crises are hard to separate from the proximate causes. Many of the vulnerabilities raising the risk of a debt crisis can result from factors related to financial integration, political economy and institutional environments. Opening up to capital flows can make countries with profligate governments and weakly supervised financial sectors more vulnerable to shocks. McKinnon and Pill ( 1996 , 1998 ) describe how moral hazard and inadequate supervision combined with unrestricted capital flows can lead to crises as banks incur currency risks. Debt crises are also likely to involve sudden stops, currency or banking crises (or various combinations), making it hard to identify the initial cause. Empirical studies on the identification of causes are thus subject to the usual problems of omitted variables, endogeneity and simultaneity. Although using short-term (foreign currency) debt as a crisis predictor may work, for example, it does not constitute a proof of the root cause of the crisis. The difficulty to identify the deeper causes is more generally reflected in the fact that debt crises have also been around throughout history.

• D. Banking Crises

Banking crises are quite common, but perhaps the least understood type of crises. Banks are inherently fragile, making them subject to runs by depositors. Moreover, problems of individual banks can quickly spread to the whole banking system. While public safety nets – including deposit insurance – can limit this risk, public support comes with distortions that can actually increase the likelihood of a crisis. Institutional weaknesses can also elevate the risk of a crisis. For example, banks heavily depend on the information, legal and judicial environments to make prudent investment decisions and collect on their loans. With institutional weaknesses, risks can be higher. While banking crises have occurred over centuries and exhibited some common patterns, their timing remains empirically hard to pin down.

Bank Runs and Banking Crises

Financial institutions are inherently fragile entities, giving rise to many possible coordination problems. Because of their roles in maturity transformation and liquidity creation, financial institutions operate with highly leveraged balance sheets. Hence, banking, and other similar forms of financial intermediation, can be precarious undertakings. Fragility makes coordination, or lack thereof, a major challenge in financial markets. Coordination problems arise when investors and/or institutions take actions – like withdrawing liquidity or capital – merely out of fear that others also take similar actions. Given this fragility, a crisis can easily take place, where large amounts of liquidity or capital are withdrawn because of a self-fulfilling belief – it happens because investors fear it will happen. Small shocks, whether real or financial, can translate into turmoil in markets and even a financial crisis.

A simple example of a coordination problem is a bank run. It is a truism that banks borrow short and lend long. This maturity transformation reflects preferences of consumers and borrowers. However, it makes banks vulnerable to sudden demands for liquidity, i.e., “runs” (the seminal reference here is Diamond and Dybvig, 1983 ). A run occurs when a large number of customers withdraw their deposits because they believe the bank is, or might become, insolvent. As a bank run proceeds, it generates its own momentum, leading to a self-fulfilling prophecy (or perverse feedback loop): as more people withdraw their deposits, the likelihood of default increases, and this encourages further withdrawals. This can destabilize the bank to the point where it faces bankruptcy as it cannot liquidate assets fast enough to cover its short-term liabilities.

These fragilities have long been recognized, and markets, institutions, and policy makers have developed many “coping” mechanisms (see further Dewatripoint and Tirole, 1994 ). Market discipline encourages institutions to limit vulnerabilities. At the firm level, intermediaries have adopted risk management strategies to reduce their fragility.

Furthermore, micro-prudential regulation, with supervision to enforce rules, is designed to reduce risky behavior of individual financial institutions and can help engineer stability. Deposit insurance can eliminate concerns of small depositors and can help reduce coordination problems. Lender of last resort facilities (i.e., central banks) can provide short-run liquidity to banks during periods of elevated financial stress. Policy interventions by public sector, such as public guarantees, capital support and purchases of non-performing assets, can mitigate systemic risk when financial turmoil hits.

Although regulation and safety net measures can help, when poorly designed or implemented they can increase the likelihood of a banking crisis. Regulations aim to reduce fragilities (for example, limits on balance sheet mismatches stemming from interest rate, exchange rate, maturity mismatches, or certain activities of financial institutions). Regulation (and supervision), however, often finds itself playing catch up with innovation. And it can be poorly designed or implemented. Support from the public sector can also have distortionary effects (see further Barth, Caprio and Levine, 2006 ). Moral hazard due to a state guarantee (e.g., explicit or implicit deposit insurance) may, for example, lead banks to assume too much leverage. Institutions that know they are too big to fail or unwind, can take excessive risks, thereby creating systemic vulnerabilities. 15 More generally, fragilities in the banking system can arise because of policies at both micro and macro levels ( Laeven, 2011 ).

History of banks runs

Runs have occurred in many countries throughout history. In the U.S., bank runs were common during the banking panics of the 1800s and in the early 1900s (during the Great Depression). Only with the introduction of deposit insurance in 1933, did most runs stop in the U.S. (Calomiris and Gorton, 1998). Wide-spread runs also happened frequently in emerging markets and developing countries in recent decades, such as in Indonesia during the 1997 Asian financial crisis. Runs occurred more rarely in other advanced countries, and even less so in recent decades, in part due to the wide spread availability of deposit insurance. 16 Yet, Northern Rock, a bank specializing in housing finance in the U.K., constitutes a very recent example of a bank run in an advanced country (Shin, 2011). Rapid withdrawals of wholesale market funding also took place during the recent financial crisis, when several investment and some commercial banks faced large liquidity demands from investors.

Widespread runs can also take place in non-bank financial markets. For example, in the U.S. during the fall of 2008, some mutual funds “broke the buck”, i.e., their net asset value fell below par. This triggered sharp outflows from individual investors and many other mutual funds ( Wermers, 2012 ). This “run”, in turn, led the government to provide a guarantee against further declines. These guarantees constitute a continued source of fiscal risk as the government might be forced to step in to prevent a run again. Other investment vehicles specializing in specific asset classes (such as emerging markets) also experienced sharp outflows as there was a general “flight to safety” (i.e., more demand for advanced countries’ government bonds and T-bills). More generally, the 2007-08 crisis has been interpreted by many as a widespread liquidity run ( Gorton, 2009 ).

Deeper causes of banking crises

Although funding and liquidity problems can be triggers or proximate causes, a broader perspective shows that banking crises often relate to problems in asset markets. Banking crises may appear to originate from the liability side, but they typically reflect solvency issues. Banks often run into problems when many of their loans go sour or when securities quickly lose their value. This happened in crises as diverse as the Nordic banking crises in the late 1980s, the crisis in Japan in the late 1990s, and the recent crises in Europe. In all of these episodes, there were actually no large-scale deposit runs on banks, but large-scale problems arising from real estate loans made many banks undercapitalized and required support of governments. Problems in asset markets, such as those related to the subprime and other mortgage loans, also played a major role part during the recent crisis. These types of problems in asset markets can go undetected for some time, and a banking crisis often comes into the open through the emergence of funding difficulties among a large fraction of banks.

Although the exact causal sources are often hard to identify, and risks can be difficult to foresee beforehand, looking back banking crises and other financial panics are rarely random events. Banking panics more likely occur near the peak of the business cycle, with recessions on the horizon, because of concerns that loans do not get repaid ( Gorton 1988 ; Gorton and Wilton, 2000). Depositors, noticing the risks, demand cash from the banks. As banks cannot (immediately) satisfy all requests, a panic may occur. The large scale bank distress in the 1930s was traced back this way to shocks in the real sector. In many emerging markets, banking crises were triggered by external developments, such as sharp movements in capital flows, global interest rates and commodity prices, which in turn led to an increase in non-performing loans.

Panics can too be policy induced. Panics can take place when some banks experience difficulties and governments intervene in an ad-hoc manner, without providing clear signals as to the status of other institutions. The banking panic in Indonesia in 1997, has been attributed to poorly-managed early interventions (see Honohan and Laeven, 2007 , for this and other case studies). Runs can also be directly triggered by government actions: the runs on banks in Argentina in 2001 occurred when the government imposed a limit on withdrawals, making depositors question the soundness of the entire banking system. The recent financial crisis in advanced countries has in part been attributed to the lack of consistency across government interventions and other policy measures (e.g., Calomiris, 2009 ).

Structural problems can also lead to banking crises. Studies (e.g., Lindgren, Garcia and Saal, 1996 ; Barth, Caprio and Levine, 2006 , and many others) have identified some common, structural characteristics related to banking crises. These include notably: poor market discipline due to moral hazard and excessive deposit insurance; limited disclosure; weak corporate governance framework; and poor supervision, in part due to conflict of interests. 17 Other structural aspects found to increase the risk of a crisis include: large state-ownership and limited competition in the financial system, including restricted entry from abroad; and an undiversified financial system, e.g., a dominance of banks (World Bank, 2001).

Because the financial sector receives many forms of public support, policy distortions that can lead to crises easily arise. In the context of the recent financial crisis in the US, large government support for housing finance (through the government sponsored enterprises Fannie Mae and Freddie Mac) has been argued to lead to excessive risk taking. The tendency to pursue accommodative monetary and fiscal policies following crises, at least in some advanced countries, can also be interpreted as a form of an ex-post systemic bailout, which in turn distorts ex-ante incentives and can lead to excessive risk taking (Farhi and Tirole, 2010). Another often cited problem has been “connected lending” which leads to perverse incentives – as corporations and politicians borrow too much from banks – and can cause a buildup of systemic risk. Some well-studied cases of this phenomenon include Mexico ( La Porta et al. 2000 ; Haber 2005 ), Russia ( Laeven, 2001 ), and Indonesia (Fisman, 2000).

Systemic banking panics still require further study as many puzzles remain, especially regarding how contagion arises. The individual importance of the factors listed above in contributing to crises is not known, in part since many of them tend to be observed at the same time. Fragilities remain inherent to the process of financial intermediation, with the causes for panics often difficult to understand. For reasons often unknown, small shocks can result significant problems for the entire financial system. Similarly, shocks may spillover from one market to another and/or from one country to others leading to financial crises.

The latest financial crisis had many elements in its genesis common to other crises. Much has been written about the causes of the recent crisis (see Calomiris (2009) , Gorton (2009) , Claessens et al. (2012) , and many others). While observers differ on the exact weights given to various factors, the list of factors common to previous crises is generally similar. Four features often mentioned in common are: (1) asset price increases that turned out to be unsustainable; (2) credit booms that led to excessive debt burdens; (3) build-up of marginal loans and systemic risk; and (4) the failure of regulation and supervision to keep up with financial innovation and get ahead of the crisis when it erupted. 18

The global financial crisis was, however, also rooted in some new factors. Four key new aspects often mentioned are: (1) the widespread use of complex and opaque financial instruments; (2) the increased interconnectedness among financial markets, nationally and internationally, with the U.S. at the core; (3) the high degree of leverage of financial institutions; and (4) the central role of the household sector. These factors, in combination with the ones common to other crises, and fuelled at times by poor government interventions during different stages, led to the worst financial crisis since the Great Depression. It required massive government outlays and guarantees to restore confidence in financial systems. The consequences of the crisis are still being felt in many advanced countries and the crisis is still ongoing in some European countries.

IV. Identification, Dating and Frequency of Crises

A large body of work has been devoted to the identification and dating of crises, but ambiguities remain. Methodologies based on the main theories explaining various types of crises can be used to identify (and accordingly classify) crises. 19 In practice, however, this is not straightforward. While currency (and inflation) crises and sudden stops lend themselves to quantitative approaches, the dating of debt and banking crises is typically based on qualitative and judgmental analyses. Irrespective of type, variations in methodologies can lead to differences in the start and end dates of crises. And, as noted, various types of crises can overlap in a single episode, creating possible ambiguities as to how to classify the episode.

This in part because the frequency and types of financial crises have evolved over time. In practice, a wide range of quantitative and qualitative methods involving judgment are used to identify and classify crises. The data also shows that crises have evolved over time. For example, currency crises were dominant during the 1980s whereas banking crises and sudden stops became more prevalent in the 1990s and 2000s. This section begins with a summary of common identification and dating methods (see also IMF WEO 1998; Reinhart and Rogoff, 2009a ; and Laeven and Valencia, 2008 , 2012). It then provides a summary of the frequency of crises over time, across groups of countries, and the overlap among types of crises.

• A. Identification and Dating

Currency crises , as they involve large changes in exchange rates, and (related) inflation crises, are relatively easy to identify. Reinhart and Rogoff (2009a) distinguish these episodes by assigning threshold values for the relevant variables. In the case of currency crises, they consider exchange rate depreciations in excess of 15 percent per year as a crisis, while, for inflation, they adopt a threshold of 20 percent per year. 20 A currency crisis is defined in Frankel and Rose (1996) as a depreciation of at least 25 percent cumulative over a 12-month period, and at least 10 percentage points greater than in the preceding 12 months. The dates identified are obviously sensitive to such thresholds used. These thresholds can also be universal, specific to the sample of countries under study, or country-specific (as when the threshold is adjusted for the country’s “normal” exchange rate variations).

A measurement issue naturally arises when there was no significant adjustment in currency, even if there were pressures or attacks. Movements in international reserves or adjustment in interest rates can absorb exchange rate pressures and prevent or moderate the fluctuations in the rate. However, episodes involving such pressures and/or attacks are also important to document and study. To address this, starting with Eichengreen, Rose and Wyplosz (1996) , different methodologies have been employed. A composite index of speculative pressure is often constructed based on actual exchange rate changes, and movements in international reserves and interest rates, with weights chosen to equalize the variance of the components, thereby avoiding one component dominating the index. Thresholds are then set to date the currency events, including both large exchange rate movements and periods of pressure (see Frankel and Saravelos (2012) and Glick and Hutchison (2012) for reviews; Cardarelli, Elekdag and Kose (2010) for applications).

Sudden stops and balance-of-payments crises can also be objectively classified. Calvo, Izquierdo and Talvi (2004) define systemic sudden stop events as episodes with output collapses that coincide with large reversals in capital flows. Calvo, Izquierdo and Mejía (2008) expand on these criteria in two ways: one, the period contains one or more year-on-year fall in capital flows that are at least two standard deviations below its sample mean (this addresses the “unexpected” requirement of a Sudden Stop); two, it starts (ends) when the annual change in capital flows falls (exceeds) one standard deviation below (above) its mean (Mauro and Becker, 2006).

Since methodologies vary, various samples of events follow. Calvo et al. (2004) identified 33 Sudden Stop events with large and mild output collapses in a sample of 31 emerging market countries. While studies use different cutoff criteria ( Calvo and Reinhart (1999) , Calvo, Izquierdo and Loo-Kung (2006) , and Milesi-Ferretti and Razin (2000) , for example differ), the datings of events are very similar. Some studies also require a fall in output, but later studies excluded this requirement (since a fall may be endogenous) and replaced it with the requirement of large spikes in the Emerging Markets Bond Index (EMBI) spread, indicating a shift in the supply of foreign capital (see further Izquierdo, 2012). Cardarelli, Kose and Elekdag (2010) consider a large capital inflow episode to end “abruptly” if the ratio of net private capital inflows to GDP in the year after the episode terminates is more than 5 percentage point lower than at the end of the episode – closely following the definition of “sudden stops” in the literature. An episode is also considered to finish abruptly if its end coincides with a currency crisis.

Balance-of-payments crises and other parallel episodes can similarly be identified using capital flows data. Although there are some differences in approaches (e.g., how reserves losses are treated) and statistical variations across studies (e.g., whether the same current account deficit threshold is used for all countries or whether country-specific variables thresholds are used), but many of them point to similar samples of actual events. Forbes and Warnock (2012) analyze for a large set of countries gross flows, instead of the more typical net capital flows (or current account). They identify episodes of extreme capital flow movements using quarterly data, differentiating activity by foreigners and domestics. They classify episodes as “surge”, “stop”, “flight,” or “retrenchment, with surges and stops related respectively to periods of large gross capital in- or outflows by foreigners, and flights and retrenchments respectively related to periods of large capital out- or inflows by domestic residents.

External sovereign debt crises are generally easy to identify as well, although there remain differences in classifications across studies. Sovereign defaults are relatively easy to identify since they involve a unique event, the default on payments. Typical dating of such episodes relies on the classification of rating agencies or on information from international financial institutions (see McFadden, Eckaus, Feder, and Hajivassiliou (1984); and papers summarized in Sturzenegger and Zettelmeier (2007) ). Still, there are choices in terms of methodology. For example differences arise from considering the magnitude of defaults (whether default has to be widespread or on just one class of claims), default by type of claims (such as bank claims or bond claims, private or public claims), and the length of default (missing a single or several payments). Others look instead at the increases in spreads in sovereign bonds as an indicator of (the probability of) default ( Edwards, 1984 ).

The end of a default is harder to date though. A major issue with dating, including of default and sovereign debt crises, can be identifying their end, i.e., when default is over. Some studies date this as when countries regained access in some form to private financial markets. Others use as a criteria when countries regain a certain credit rating (IMF, 2005 and 2011). Differences consequently arise as to how long it takes for a country to emerge after a sovereign default.

Domestic debt crises are more difficult to identify. First, consistent historical data on domestic public debt across countries was missing, at least until recently. Furthermore, following a crisis, unrecorded debt obligations can come to light. However, Abbas et al (2011) and Reinhart and Rogoff (2009a) have since made significant progress in putting together historical series on (domestic) debt. Second, countries can default in many ways: outright direct defaults; periods of hyper- or high inflation; punitive taxation of interest payments; forced interest rate or principal adjustments or conversions; gold clause abrogation; debasing of currency; and forms of financial repression. Reinhart and Rogoff (2009a) describe these and make clear that there remains considerable ambiguity in classifications of defaults, especially of “inflation-related default” episodes.

Banking crises can be particularly challenging to date as to when they start and especially when they end. Such crises have usually been dated by researchers using a qualitative approach on the basis of a combination of events – such as forced closures, mergers, or government takeover of many financial institutions, runs on several banks, or the extension of government assistance to one or more financial institutions. In addition, in-depth assessments of financial conditions have been used as a criterion. Another metric used has been the fiscal costs associated with resolving these episodes. The end of a banking crisis is also difficult to identify, in part since its effects can linger on for some time.

There are large overlaps in the dating of banking crises across different studies. Reinhart and Rogoff (2009a) date the beginning of banking crises by two types of events: bank runs that lead to closure of, merging or takeover by the public sector of one or more financial institutions. If there are no runs, they check the closure, merging, takeover, or large-scale public assistance of an important financial institution. As they acknowledge, this approach has some obvious drawbacks: it could date crises too late (or too early) and gives no information about the end date of these episodes. Still, the classification of Reinhart and Rogoff (2009a) largely overlaps with that of Laeven and Valencia (2012).

Still, there remain differences in the dating of crises which can affect analyses. One example of difference is the start of Japan’s banking crisis which is dated by Reinhart and Rogoff (2009a) as of 1992 and as of 1997 by Laeven and Valencia. Another example, with significant implications for analyses, is from Lopez-Salido and Nelson (2010) . Analyzing events surrounding financial market difficulties in the U.S. over the past 60 years, Lopez-Salido and Nelson report three distinct crises: 1973–75; 1982–84; and 1988–91. This differs from Reinhart and Rogoff, who identify only one crisis (1984–91), and Laeven and Valencia (2012) who also have only one crisis, 1988 (and since then 2007), over that period. Importantly, using their new chronology, Lopez-Salido and Nelson argue that crises need not impact the strength of recoveries, in contrast to most claims that recoveries are systematically slower after financial crises. 21 These differences clearly show the importance of dating.

Lastly, asset price and credit booms, busts and crunches, common to many crises, are relatively easy to classify, but again specific approaches vary across studies. Asset prices (notably equity and to a lesser degree house prices) and credit volumes are available from standard data sources. Large changes (in nominal or real terms) in these variables can thus easily be identified. Still, since approaches and focus vary, so do the classifications of booms, busts, and crunches. Claessens, Kose and Terrones (2012) use the classical business cycles approach, looking at the level of real asset prices or credit to identify peaks and troughs in these variables. They then focus on the top and bottom quartile of these changes to determine the booms, busts, or crunches. Other methods exist: large deviations from trend in real credit growth ( Mendoza and Terrones, 2008 ) and from the credit-to-GDP ratio can be used to classify credit booms. And Gourinchas, Valdes, and Landerretche (2001) classify 80 booms based on absolute and relative (to the credit-to-GDP ratio) deviation from trend, but rather than setting the thresholds first, they limit the number of episodes they want to classify.

Regardless, it is important to recognize that different types of crises can overlap and do not necessarily take place as independent events. One type of crisis can lead to another type of crisis. Or two crises can take place simultaneously due to common factors. To classify a crisis as only one type can then be misleading when one event is really a derivative of another. Crises in emerging markets, for example, often have been combinations of currency and banking crises, associated with sudden stops in capital flows, and often subsequently turning into sovereign debt crises. Overall, considerable ambiguity remains on the identification and dating of financial crises, which should serve as an important caveat when one reviews the frequency and distribution of crises over time as we do in the next section.

• B. Frequency and Distribution

Crises have afflicted both emerging markets and advanced countries throughout centuries. In the three decades before 2007, most crises occurred in emerging markets. Emerging market crises during those decades include the Latin American crises in the late 1970s-early 1980s, the Mexican crisis in 1995, and the East Asian crises in the mid- to late 1990s. “Emerging” markets being more prone to crises is not new ( Reinhart and Rogoff, 2013 ). History shows that many countries which are developed today experienced financial crises when they were going through their own process of emergence, including Australia, Spain, the U.K. and the U.S. in the 1800s. For example, France defaulted on its external debt eight times over the period 1550-1800. Some advanced countries experienced crises in recent decades as well, from the Nordic countries in the late 1980s, to the Japan in the 1990s. The most recent crises starting with the U.S. subprime crisis in late 2007 and then spreading to other advanced countries show (once again) that crises can affect all types of countries.

Some claim that crises have become more frequent over time. The three decades after the World War II were relatively crises-free, whereas the most recent three decades have seen many episodes ( Figure 4 ). Some relate this increase to more liberalized financial markets, including floating exchange rates, and greater financial integration. Indeed, using macroeconomic and financial series for 14 advanced countries for the 1870-2008 period, Jordà, Schularick and Taylor (2012) report no financial crises during the Bretton Woods period of highly regulated financial markets and capital controls. Also, Bordo et al. (2001) argue that the sudden stop problem has become more severe since the abandonment of the Gold Standard in the early 1970s.

Coincidence of Financial Crises

More recent crises seem to have lasted shorter though, but banking crises still last the longest. The median duration of debt default episodes in the post-World War II has been much shorter than for the period 1800-1945, possibly because of improvement in policies in the later period, improved international financial markets, or the active involvement of multilateral lending agencies (see further Das and others (2012) ). Currency and sudden stop crises are relatively short (almost by definition). With the major caveat that their end is hard to date, banking crises tend to last the longest, consistent with their large real and fiscal impacts.

Financial crises clearly often come in bunches. Sovereign defaults tend to come in waves and in specific regions. Jordà, Schularick and Taylor (2012) report that there were five major periods when a substantial number of now-advanced countries experienced a crisis: 1893, the early 1890s, 1907, 1930-31, and 2007-08. Earlier crises bunched around events such as the Napoleonic Wars. Examples of bunches over the last three decades include in the 1980s, the Latin America debt crises; in 1992, the European ERM currency crises; in the late 1990s, the East Asian, Russia and Brazil financial crisis; the multiple episodes observed in 2007-2008, and the ongoing crises in Europe. Periods of widespread sovereign defaults often coincide with a sharp rise in the number of countries going through a banking crisis. These coincidences point towards common factors driving these episodes as well as spillovers of financial crises across borders.

Some types of crises are more frequent than others. Comparisons can be made for the post Bretton Woods period (while some types of crises have been documented for longer periods, not all have; and currency crises were non-existent during the fixed exchange rate period; together this necessitates the common, but shorter period). Of the total number of crises Laeven and Valencia (2013) report, there are 147 banking crises, 217 currency crises, and 67 sovereign debt crises over the period 1970 to 2011 (note that several countries experienced multiple crises of the same type).

However, as noted before, there is some overlap between the various types of crises. Currency crises frequently tend to overlap with banking crises – so called twin crises ( Kaminsky and Reinhart, 1999 ). In addition, sudden stop crises, not surprisingly, can overlap with currency and balance-of-payments crises, and sometimes sovereign crises ( Figure 5 ). Of the 431 banking (147), currency (217) and sovereign (67) crises Laeven and Valencia (2013) report, they consider 68 as twin crises, and 8 can be classified as triple crises. The overlaps are thus far from complete. There are also relative differences in coincidences of these episodes. A systemic banking crisis, for example, often involves a currency crisis and a sovereign crisis sometimes overlaps with other crises, 20 out of 67 sovereign crises are also a banking and 42 also a currency crisis.

Average Number of Financial Crises over Decades

V. Real and Financial Implications of Crises

Macroeconomic and financial consequences of crises are typically severe and share many commonalities across various types. While there are obviously differences between crises, there are many similarities in terms of the patterns macroeconomic variables follow during these episodes. Large output losses are common to many crises and other macroeconomic variables (consumption, investment and industrial production) typically register significant declines. And financial variables like asset prices and credit usually follow qualitatively similar patterns across crises, albeit with variations in terms of duration and severity. This section provides a summary of the literature on the macroeconomic and financial implications of crises.

• A. Real Effects of Crises

Financial crises have large economic costs. Crises have large effects on economic activity and can trigger recessions ( Claessens, Kose, and Terrones, 2009 and 2012 ). There are indeed many recessions associated with financial crises ( Figure 6 ). And financial crises often tend to make these recessions worse than a “normal” business cycle recession ( Figure 7 ). The average duration of a recession associated with a financial crisis is some six quarters, two more than a normal recession. There is also typically a larger output decline in recessions associated with crises than in other recessions. And the cumulative loss of a recession associated with a crisis (computed using the lost output relative to the pre-crisis peak) is also much larger than that of a recession without a crisis.

Coincidence of Recessions and Crises

(number of events)

Real Implications of Financial Crises, Crunches, and Busts

The real impact of a crisis on output can be computed using various approaches. For a large cross-section of countries and long time period, Claessens, Kose and Terrones (2012) use the traditional business cycles methodology to identify recessions. They show that recessions associated with credit crunches and housing busts tend to be more costly than those associated with equity price busts. Overall losses can also be estimated by adding up the differences between trend growth and actual growth for a number of years following the crisis or until the time when annual output growth returned to its trend. On this basis, Laeven and Valencia (2012) estimate that the cumulative cost of banking crises is on average about 23 percent of GDP during the first four years. 22 Regardless of the methodology, losses do vary across countries. While overall losses tend to be larger in emerging markets, the large losses in recent crises in advanced countries (e.g., both Iceland and Ireland’s output losses exceed 100 percent) paint a different picture. The median output loss for advanced countries is now about 33 percent which exceeds that of emerging markets, 26 percent.

Crises are generally associated with significant declines in a wide range of macroeconomic aggregates. Recessions following crises exhibit much larger declines in consumption, investment, industrial production, employment, exports and imports, compared to those recessions without crises. For example, the decline in consumption during recessions associated with financial crises is typically seven to ten times larger than those without such crises in emerging markets. In recessions without crises, the growth rate of consumption slows down but does not fall below zero. In contrast, consumption tends to contracts during recessions associated with financial crises, another indication of the significant toll that crises have on overall welfare.

There are also large declines in global output during financial crises episodes. The significant cost for the world economy associated with the Great Depression has been documented in many studies. The global financial crisis was associated with the worst recession since WWII, as it saw a 2 percent decline in world per capita GDP in 2009. In addition to 2009, there were two other years after WWII the world economy experienced a global recession and witnessed crises in multiple countries ( Kose, Loungani and Terrones, 2013 ). In 1982, a global recession was associated with a host of problems in advanced countries, as well as the Latin American debt crisis. 23 The global recession in 1991 also coincided with financial crises in many parts of the world, including difficulties in US credit markets, banking and currency crises in Europe, and the burst of the asset price bubble in Japan. While the world per capita GDP grows by about 2 percent in a typical year, it declined by about 0.8 percent in 1982 and 0.2 percent in 1991.

Recent studies also document that recoveries following crises tend to be weak and slow, with long-lasting effects. Kannan, Scott, and Terrones (2013) employ cross-country data and conclude that recoveries following financial crises have been typically slower, associated with weak domestic demand and tight credit conditions. These findings are consistent with those reported in several other studies ( Reinhart and Rogoff, 2009a ; Claessens, Kose, and Terrones, 2012 ; Papell and Prudan, 2011 ; and Jordà, Schularick and Taylor, 2012 ). Abiad and others (2013) analyze the medium term impact of financial crises and conclude that output tends to be depressed substantially following banking crises. Specifically, seven years after a crisis, the level of output is typically about 10 percent lower relative to precrisis trend (even though growth tends to eventually return to its precrisis rate). They report that the depressed path of output is associated with long-lasting reductions of roughly equal proportions in the employment rate, the capital-to-labor ratio, and total factor productivity.

From a fiscal perspective, especially banking crises can be very costly. Both gross fiscal outlays and net fiscal costs of resolving financial distress and restructuring the financial sector can be very large. For banking crises, Laeven and Valencia (2013) , estimate that fiscal costs, net of recoveries, associated with crisis are on average about 6.8 percent of GDP. They can, however, be as high as 57 percent of GDP and in several cases are over 40 percent of GDP (for example Chile and Argentina in the early 1980s, Indonesia in the later 1990s, and Iceland and Ireland in 2008). Net resolution costs for banking crises tend to be higher for emerging markets, 10 percent vs. 3.8 percent for advanced countries. Although gross fiscal outlays can be very large in advanced countries as well—as in many of the recent and ongoing cases, the final direct fiscal costs have generally been lower in advanced countries, reflecting the better recoveries of fiscal outlays.

Debt crises can be costly for the real economy. Borensztein and Panizza (2009) , Levy-Yeyati and Panizza (2011) , and Furceri and Zdzienicka (2012) all document that debt crises are associated with substantial GDP losses. Furceri and Zdzienicka (2012) report that debt crises are more costly than banking and currency crises and are typically associated with output declines of 3-5 percent after one year and 6-12 percent after 8 years. Gupta, Mishra, and Sahay (2007) find that currency crises are often contractionary.

The combination of financial system restructuring costs and a slow economy can lead public debt to rise sharply during financial crises. Reinhart and Rogoff (2009a) document that crises episodes are often associated with substantial declines in tax revenues and significant increases in government spending. For example, government debt on average rises by 86 percent during the three years following a banking crisis. Using a larger sample, Laeven and Valencia (2013) report the median increase in public debt to be about 12 percent for their sample of 147 systemic banking crises. Including indirect fiscal costs, such as those resulting from expansionary fiscal policy and reduced fiscal revenues as a consequence of a recession, makes the overall fiscal costs of the recent crises in advanced countries actually greater than those in emerging markets, 21.4 percent vs. 9.1 percent of GDP. 24

Although empirical work has not been able to pinpoint the exact reasons, sudden stops are especially costly. Using a panel data set over 1975–1997 and covering 24 emerging markets, Hutchison (2008) finds that while a currency crisis typically reduces output by 2–3%, a sudden stop reduces output by an additional 6–8 percent in the year of the crisis. The cumulative output loss of a sudden stop is even larger, about 13–15 percent over a 3-year period. 25 Edwards (2004) finds sudden stops and current account reversals to be closely related, with reversals in turn having a negative effect on real growth and more so for emerging markets. Cardarelli, Kose and Elekdag (2010) , examining 109 episodes of large net private capital inflows to 52 countries over 1987–2007, report that the typical post-inflow decline in GDP growth for episodes that end abruptly is about 3 percentage points lower than during the episode, and about 1 percentage point lower than during the two years before the episode. These fluctuations are also accompanied by a significant deterioration of the current account during the inflow period and a sharp reversal at the end.

• B. Financial Effects of Crises

Crises are associated with large downward corrections in financial variables. A large research program has analyzed the evolution of financial variables around crises. Some of the studies in this literature focus on crises episodes using the dates identified in other work, others consider the behavior of the financial variables during periods of disruptions, including credit crunches, house and equity price busts. Although results differ across the types of crises, both credit and asset prices tend to decline or grow at much lower rates during crises and disruptions than they do during tranquil periods, confirming the boom-bust cycles in these variables discussed in previous sections. In a large sample of advanced countries ( Figure 8 ), credit declines by about 7 percent, house prices fall by about 12 percent and equity prices drop by more than 15 percent during credit crunches, house and equity price busts, respectively (Claessens, Kose and Terrones, 2011). Asset prices (exchange rates, equity and house prices) and credit around crises exhibit qualitatively similar properties in terms of their temporal evolution in advanced and emerging market countries, but the duration and amplitude of declines tend to be larger for the latter than for the former.

Financial Implications of Crises, Crunches, and Busts

The most notable drag on the real economy from a financial crisis is the lack of credit from banks and other financial institutions. Dell’Ariccia, Detragiache, Rajan (2005) and Klingebiel, Laeven and Kroszner (2007) show how after banking crises, sectors grow slower that naturally need more external financing, likely because banks are impaired in their lending capacity. Recoveries in aggregate output and its components following recessions associated with credit crunches tend to take place before the revival of credit growth and turnaround in house prices ( Figure 9 ). These temporal patterns are similar to those in the case of house price busts, i.e., economic recoveries start before house prices bottom out during recessions coinciding with sharp drops in house prices.

Creditless Recoveries

(Percent change from a year earlier; zero denotes peak; x-axis quarter)

Both advanced and emerging market countries have experienced the phenomenon of “creditless recoveries”. Creditless recoveries are quite common to financial crises associated with sudden-stops in many emerging market economies ( Calvo, Izquierdo and Talvi, 2006 ). Abiad, Dell’Ariccia, and Li (2013) using a large sample of countries, show that about one out of five recoveries is creditless. Creditless recoveries are, as expected, more common after banking crises and credit booms. The average GDP growth during these episodes is about a third lower than during “normal” recoveries. 26 Furthermore, sectors more dependent on external finance grow relatively less and more financially dependent activities (such as investment) are curtailed more (see also Kannan (2009) ). Micro evidence for individual countries also shows that financial crises are associated with reductions in investment, R&D and employment, and firms passing up on growth opportunities ( Campello, Graham, and Harvey, 2010 review evidence for the U.S.). Collectively, this suggests that the supply of credit following a financial crisis can constrain economic growth.

• VI. Predicting Financial Crises

It has long been a challenge to predict the timing of crises. There is obviously a great benefit in knowing whether and if so when a crisis may occur: it can help put in place measures aimed at preventing a crisis from occurring in the first place or limiting the damage if it does happen. As such, there is much to be gained from better detecting the likelihood of a crisis. Yet, in spite of much effort, no single set of indicators has proven to explain the various types of crises or consistently so over time. Periods of turmoil often arise in endogenous ways, with possibilities of multiple equilibria and many non-linearities. 27 And while it is easier to document vulnerabilities, such as increasing asset prices and high leverage, it remains difficult to predict with some accuracy the timing of crises. This section presents a short review of the evolution of the empirical literature on prediction of crises. 28

Early warning models have evolved over time, with the first generation of models focusing on macroeconomic imbalances. In early crisis prediction models, mostly aimed at banking and currency crises, the focus was largely on macroeconomic and financial imbalances, and often in the context of emerging markets. Kaminsky and Reinhart (1999) show that growth rates in money, credit, and several other variables exceeding certain thresholds made a banking crisis more likely. In a comprehensive review, Goldstein, Kaminsky and Reinhart (2000) report that a wide range of monthly indicators help predict currency crises, including the appreciation of the real exchange rate (relative to trend), a banking crisis, a decline in equity prices, a fall in exports, a high ratio of broad money (M2) to international reserves, and a recession. Among annual indicators, the two best were both current-account indicators, namely, a large current-account deficit relative to both GDP and investment. For banking crises, the best (in descending order) monthly indicators were: appreciation of the real exchange rate (relative to trend), a decline in equity prices, a rise in the money (M2) multiplier, a decline in real output, a fall in exports, and a rise in the real interest rate. Among eight annual indicators tested, the best were a high ratio of short-term capital flows to GDP and a large current-account deficit relative to investment. 29

In the next generation of models, still largely geared towards external crises, balance sheet variables became more pronounced. Relevant indicators found include substantial short-term debt coming due (Berg et al. 2004). The ratio of broad money to international reserves in the year before the crisis was found to be higher (and GDP growth slower) for crises in emerging markets. In these models, fiscal deficit, public debt, inflation, and real broad money growth, however, were often found not to be consistently different between crisis and non-crisis countries before major crises. Neither did interest rate spreads or sovereign credit ratings generally rank high in the list of early warning indicators of currency and systemic banking crises. Rather, crises were more likely preceded by rapid real exchange rate appreciation, current account deficits, domestic credit expansion, and increases in stock prices.

Later models showed that a combination of variables can help identify situations of financial stress and vulnerabilities. Frankel and Saravelos (2012) perform a meta-analysis based on reviews of crises prediction models and seven papers published since 2002. The growth rate of credit, foreign exchange reserves, the real exchange rate, GDP growth, and the current account to GDP are the most frequent significant indicators in the 83 papers reviewed (see also Threhan, 2009; Lane and Milesi-Ferretti, 2011 ). Crises are typically preceded by somewhat larger current account deficits relative to historical averages, although credit trends more than external imbalances appear to be the best predictor (Schularick and Taylor, 2011; Taylor, 2013 ; Alessi and Detken, 2011 ).

Global factors can play important roles in driving sovereign, currency, balance-of-payments, and sudden stops crises. A variety of global factors is often reported to trigger crises, including deterioration in the terms of trade, and shocks to world interest rates and commodity prices. For example, the sharp rise in US interest rates at the time has been identified as a trigger for the Latin American sovereign debt crises of the 1980s. More generally, crises are often preceded by interest rate hikes in advanced economies and by sudden changes in commodity, especially oil, prices. But low interest rates can matter as well. For example, Jordà, Schularick and Taylor (2011) report that global financial crises often take place in an environment of low interest rates. Other studies argue that the global imbalances of the 2000s and the recent crisis are intimately connected ( Obstfeld and Rogoff, 2009 ; Obstfeld, 2012 ). International trade and other real linkages can be channels of transmission, and contagion in financial markets is associated with crises ( Forbes, 2012 ). Studies highlight for example the role of a common lender in particular in spreading the East Asian financial crisis ( Kaminsky and Reinhart, 2001 ). These global factors can themselves be outcomes, as in the most recent crisis, when interest rates and commodity prices experienced sharp adjustments following the onset of the crisis.

Overall though, rapid growth in credit and asset prices is found to be the most reliably related to increases in financial stress and vulnerabilities. Borio and Lowe (2002) document that out of asset prices, credit and investment data, a measure based on credit and asset prices is the most useful: almost 80 percent of crises can be predicted on the basis of a credit boom at a one-year horizon, while false positive signals are issued only about 18 percent of the time. Building on this, Cardarelli, Elekdag, and Lall (2009) find that banking crises are typically preceded by sharp increases in credit and house prices. Many others have found the coexistence of unusually rapid increases in credit and asset prices, large booms in residential investment, as well as deteriorating current account balances, to contribute to the likelihood of credit crunch and asset price busts.

Recent studies confirm that credit growth is the most important, but still imperfect predictor. Many of the indicators, such as sharp asset price increases, a sustained worsening of the trade balance, and a marked increase in bank leverage, lose predictive significance once one condition for the presence of a credit boom. Still, there are both Type I and Type II errors. As Dell’Ariccia et al (2012) show, not all booms are associated with crises: only about a third of boom cases end up in financial crises. Others do not lead to busts but are followed by extended periods of below-trend economic growth. And many booms result in permanent financial deepening and benefit long-term economic growth. While not all booms end up in a crisis, the probability of a crisis increases with a boom. Furthermore, the larger the size of a boom episode, the more likely it results in a crisis. Dell’Ariccia and others (2013) find that close to half or more of the booms that either lasted longer than six years (4 out of 9), exceeded 25 percent of average annual growth (8 out of 18), or started at an initial credit-to-GDP ratio higher than 60 percent (15 out of 26) ended up in crises.

In practical terms, recent early warning models typically use a wide array of quantitative leading indicators of vulnerabilities, with a heavy focus on international aspects. Indicators used capture vulnerabilities that stem from or are centered in the external, public, financial, nonfinancial corporate, or household sectors – and combine these with qualitative inputs (IMF-FSB, 2010). Since international financial markets can play multiple roles in transmitting and causing, or at least triggering, various types of crises, as happened recently, several international linkages measures are typically used. Notably banking system measures, such as exposures to international funding risks and the ratio of non-core to core liabilities, have been found to help signal vulnerabilities ( Shin, 2013 ). 30 Since international markets can also help with risk-sharing and can reduce volatility, and the empirical evidence is mixed, the overall relationship of international financial integration and crises is, however, much debated ( Kose and others, 2010 ; Lane, 2012 ).

VII. Conclusions

This paper presents a survey on financial crises to answer three specific questions. First, what are the main factors explaining financial crises? Although the literature has clarified some of the main factors driving crises, it remains a challenge to definitively identify their causes. Many theories have been developed over the years regarding the underlying causes of crises. These have recognized the importance of booms in asset and credit markets that turned into busts as the main driving forces of most crises episodes. Given their central roles, the paper briefly summarizes the theoretical and empirical literature analyzing developments in credit and asset markets around financial crises.

Second, what are the major types of crises? While financial crises can take various shapes and forms, the literature has focused on four major types of crises: currency crises; sudden stop (or capital account or balance of payments) crises; debt crises; and banking crises. It is possible to classify crises in other ways, but regardless they can often overlap in types. A number of banking crises, for example, are also sudden stop episodes and currency crises. The paper examines the literature on the analytical causes and empirical determinants of each type of crisis. In addition, it presents a review of studies on various approaches for the identification of crises, their frequency over time and across different groups of countries.

Third, what are the real and financial sector implications of crises? Large output losses are common to many crises and other macroeconomic variables (consumption, investment and industrial production) typically register significant declines. Financial variables like asset prices and credit usually follow qualitatively similar patterns across crises, albeit with variations in terms of duration and severity of declines. The paper provides a summary of the literature on the macroeconomic and financial implications of crises.

The paper also briefly reviews the literature on the prediction of crises. While there are many benefits in knowing whether and if so when a crisis may occur, it has been a challenge to predict crises. It is easy to document vulnerabilities, such as increasing asset prices and high leverage, but it remains difficult to predict with some accuracy the timing of crises. No single set of indicators has proven to predict the various types of crises. The paper reviews how the empirical literature on prediction of crises has evolved and analyzes its current state.

• Is this time really different?

One of the main conclusions of the literature on financial crises is that it has been hard to beat the “this-time-is-different” syndrome. This, as aptly described by Reinhart and Rogoff (2009a) , is the belief that “ financial crises are things that happen to other people in other countries at other times; crises do not happen to us, here and now. We are doing things better, we are smarter, we have learned from past mistakes.” Although often preceded by similar patterns, policy makers tend to ignore the warnings and argue that: “ the current boom, unlike the many booms that preceded catastrophic collapses in the past (even in our country) is built on sound fundamentals…” Leading up to every crisis, it is often claimed that developments appear to be different from those before the earlier episodes. Before the latest episode, for example, the extensive diversification of risks and advanced institutional frameworks were touted as such features argued to justify the belief that “this time is different”.

As the literature reviewed here makes abundantly clear, there are many similarities in the run-ups to crises. In the latest one, increases in credit and asset prices were common to those observed in the earlier ones. Given these commonalities, it should be possible to prevent crises. Yet, that seems to have been an impossible task. This suggests that future research should be geared to beat the “this-time-is-different” syndrome. This is a very broad task requiring addressing of two major questions: How to prevent financial crises? How to mitigate their costs when they take place? In addition, there have to be more intensive efforts to collect necessary data to guide both empirical and theoretical studies. The rest of this conclusion takes each of these issues in turn and points to future research directions.

• How to prevent financial crises?

In light of the lessons from the latest crisis, many agree that asset price bubbles and credit booms can entail substantial costs, if they deflate rapidly. Specifically, many now agree on a number of issues with respect to asset price bubbles and credit booms. First, rapid increases in asset prices and credit can lead to financial turmoil and crises with significant adverse macroeconomic effects. Second, it is important to monitor vulnerabilities stemming from such sharp increases, and determine if they could be followed by large and rapid declines (crashes, busts or crunches, capital outflows). Third, the subsequent busts and crunches are likely to be more harmful if bubbles arise due to “distortions.” Fourth, even if not due to distortions, evidence of irrationality can be interpreted as a sign of inefficiency and a potential source of welfare loss. As such, bubbles and credit booms can call for interventions.

The challenge for policy makers and researchers is twofold: when to intervene and how to intervene. First, they need to determine when (and to what extent) increases in asset prices and credit represent substantial deviations from those that can be explained by fundamentals. Second, if the behavior of credit and asset markets suggests signs of risk, they need to determine what would be the optimal policy responses to minimize risks and mitigate the adverse effects when risks materialize.

There has been an active debate on if, and how, monetary policy should respond to movements in asset prices and credit. The consensus before the crisis was that the formulation of monetary policy only needed to consider asset prices to the extent that they were relevant for forecasting economic outlook and inflation, but not otherwise (see Mishkin 2008 , and Kohn 2008, for reviews; and Campbell 2008 for a collection of papers). However, the crisis has made clear (again) that both financial stability and economic activity might be affected by asset price movements and a view has emerged that monetary policy should take into account to some degree developments in asset prices (Blanchard, Dell’Ariccia and Mauro, 2009; Bernanke, 2009 and 2011; Trichet, 2009). How to operationalize this, remains under discussion though (Eichengreen et. al 2011; Mishkin, 2011 ). While the case for policy intervention is considered stronger when the banking system is directly involved in financing the bubble, whereas other asset prices bubbles can more justifiably be left to themselves (Crowe et. al, 2011), the exact adjustment of monetary policy remains unclear ( Bean, Paustian, Penalver, and Taylor, 2010 ; King, 2012).

There remain important lessons to be learned about the design of micro-prudential regulations and institutional structures for the prevention of crises. The latest crisis has once again exposed flaws in the micro-prudential regulatory and institutional frameworks. The global nature of the crisis has also shown that financially integrated markets have benefits, but also present risks, with the international financial architecture still far from institutionally matching the policy demands of the closely-integrated financial systems. Although elements of existing frameworks provide foundations, the crisis has forced a rethink of regulatory policies, with many open questions. While rules calling for well capitalized and liquid banks that are transparent and adhere to sound accounting standards are being put in place (e.g., Basel III), clarity on how to deal with large, complex financial institutions that operate across many borders is still needed. In addition, it remains unclear what types of changes to the institutional environments – e.g., changes in the accounting standards for mark-to-market valuation, adaptations of employee compensation rules, moves of some derivatives trading to formal exchanges, greater use of central counter parties – help best to reduce financial markets’ procyclicality and the buildup of systemic risks. The crisis has also showed that fiscal policies, both micro – such as deductibility of interest payments – and macro – as in the amount of resources available to deal with financial crises – can play a role in creating vulnerabilities, but which adaptations are needed is not always clear.

While there is also a call for the use of macro-prudential policies, the design of such policies and their interactions with other policies, especially monetary policy, remain unclear. By constraining ex-ante financial markets participants’ behavior, macroprudential policies can reduce the impact of externalities and market failures that lead to systemic vulnerabilities. It that way, they can reduce the risks of financial crises and help improve macroeconomic stability (De Nicolò and others (2012)). But the exact design of such policies is yet to be formulated. Although it is clear that multiple tools are needed, complications are abound. Different financial distortions, for example, can lead to different types of risks, which in turn imply the use of multiple intermediate targets. Moreover, the relevant distortions can change over time and vary by country circumstances. Excessive leverage among corporations may give way, for example, to excessive leverage in the household sector. Factors, such as development of financial sector and exchange rate regime, can greatly affect the types of risks economies face. Much is still unknown on these factors and implications for the formulation of macroprudential policies. As new macroprudential frameworks are being established, policymakers have also been increasingly turning their attention to the complex dynamics between macroprudential and monetary policies. These hinge importantly on the “side effects” that one policy has on the other, but conceptual models and empirical evidence on these issues are still at early stages (see IMF (2013) for a review).

The review here clearly shows that further analytical research and empirical work on these issues are needed. Macroeconomic models need to better reflect the roles of financial intermediaries. Current models are often limited in the way that they capture financial frictions. In terms of financial stress, they often assume that available instruments can fully offset financial shocks and abstract from effects, such as those of monetary policy on financial stability. More realistic modeling of the channels that give rise to financial instability and the actual transmission of policies and instruments is needed. In particular, the supply side of finance is not well understood and models with realistic calibrations reflecting periods of financial turmoil are still missing (Brunnermeier and Sanikov, 2012). The roles of liquidity and leverage in such periods have yet to be examined using models better suited to address the relevant policy questions. More insights, including from empirical studies, are necessary to help calibrate these models and allow the formulation of policy prescriptions that can be adapted to different country circumstances. Only with progress in modeling financial crises, can one hope to not only avoid some of these episodes and be prepared with better policies when they occur, but also to minimize their impacts.

From an applied perspective, there remains a need for better early warning models. An issue extensively discussed in policy forums and receiving substantial attention from international organizations is the need to improve the prediction of the onset of crises ( IMF, 2010 ) . As the review here shows, the predictive power of available models remains limited. Historical record indicates that asset price busts have been especially difficult to predict. Even the best indicator failed to raise an alarm one to three years ahead of roughly one-half of all busts since 1985. This was the case again for the recent crisis. Although a number of recent papers that analyze the ability of various models in predicting the latest crisis come to negative conclusions as well, others have found some predictive patterns. Regardless, there is scope to improve these models.

While known risks are being addressed, new risks can emerge. The limited ability of crises prediction models arises in part because countries do take steps to reduce vulnerabilities. In response to increased financial globalization and sudden stop risks, many emerging markets increased their international reserves since the late 1990s, which may have helped some countries avoid the impact of the recent crisis ( De Gregorio, 2013 ; Kose and Prasad, 2010 ). Similarly, improvements in institutional environments which many countries have put in place over the last decades likely helped reduce some vulnerabilities. At the same time, however, new risks have emerged. In the latest crisis, the explosion of complex financial instruments and greater balance-sheet opaqueness and reliance on wholesale funding in highly integrated global financial markets led to greater risks of a crisis.

• How to mitigate the costs of financial crises?

It has been a challenge to explain the substantial (real) costs associated with crises. As documented, there are various theories regarding the channels by which different types of crises affect the real economy. There also exist many descriptions of the empirical patterns around crises episodes. Yet, why crises cause large costs remains an enigma. Many of the channels that lead to macro-financial linkages during normal times also “cause” the adverse effects of crises, but it is also clear that there are other dynamics at work. Normal lending seems undermined for an extended period as evidenced by creditless recoveries following crises. Fiscal policy and public debt dynamics can be affected for decades, in part since governments often end up directly supporting financial systems (by injecting liquidity or recapitalization) or suffer from the expansionary policies to mitigate the costs of crises.

In great part, the major challenge is to explain the sharp, non-linear behavior of financial markets in response to “small” shocks. While the procyclicality of leverage among financial institutions, as highlighted by its increase during the run up to the 2007-09 crisis followed by the sharp deleveraging in its aftermath, has extensively been documented (Adrian and Shin, 2012), the exact causes of this behavior have yet to be identified. Why crises involve the degree of liquidity hoarding leading to aggregate liquidity shortages and disrupt transmission of monetary policy remains a puzzle. Although credit crunches are in part attributable to capital shortages at financial institutions, these do not seem to fully explain the phenomena with lenders becoming overly risk-averse following a crisis. This lack of knowledge of the forces shaping the dynamics before and during periods of financial stress greatly complicates the design of proper policy responses.

It is also important to explore why financial spillovers across entities (institutions, markets, countries, etc.) are much more potent than most fundamentals suggest (in other words, why is there so much contagion?). Financial crises often generate effects across markets and have global repercussions. The latest episode is a case in point as its global reach and depth are without precedent in the post–World War II period. This emphasizes the value of having a better grasp of transmission mechanisms through which such episodes spill over to other countries. In addition to trade and cross-border banking linkages, research needs to consider the roles played by new financial channels, such as commercial paper conduits and shadow banking, and new trade channels, such as vertical trade networks, in the transmission of crises across borders. Given their adverse impact, the exact nature of these spillovers matters for the appropriate design of both crisis mitigation and crisis management responses. In light of their cross-border implications, pooling (regional or global) resources to provide ample liquidity proactively becomes, for example, more important as it can avoid liquidity runs escalating into self-fulfilling solvency crises and help break chains of contagion.

Although many stylized facts are already available, work on the implications of interactions among different crises and sovereign debt defaults is still limited. The review documents that various types of crises can overlap in a single episode, but research on the implications of such overlapping crises episodes has been lagging. Although default on domestic debt tends to be less frequent than that on external debt, it still takes place quite often, suggesting the usual assumption of risk-free government debt needs to be revisited. Furthermore, there appear to be interplays between domestic and foreign debt defaults. While domestic debt tends to account for a large share of the total debt stock in both advanced countries and emerging markets, many emerging countries default on their external debt at seemingly low thresholds of debt levels. This suggests that for a given level of unsustainable debt, the cost of defaulting on external debt appears less than that on domestic debt. More generally, there are likely tradeoffs that depend on country circumstances, maybe because the risk of high inflation varies. With the rising public debt stocks in many advanced countries, more work on this would be very useful.

There are still many questions about the best policy responses to financial crises. The global crisis and associated recessions have shown the limits of policy measures in dealing with financial meltdowns. It has led to an extensive discussion about the ability of macroeconomic and financial sector policies to mitigate the costs stemming from such episodes. Some research shows that countercyclical policies might mitigate the cost and reduce the duration of recessions ( Kannan, Terrones, and Scott, 2013 ). Others argue that such policies can worsen recession outcomes ( Taylor, 2009 and 2011 ). And some others find limited effects associated with expansionary policies ( Claessens, Kose, and Terrones, 2009 ; Baldacci, Gupta, Mulas-Granados, 2013 ). The discussion on the potency of policies clearly indicates a fertile ground for future research as well.

While there are valuable lessons on crisis resolution, countries are still far from adopting the “best” practices to respond to financial turmoil. It is clear now that open-bank assistance without proper restructuring and recapitalization is not an efficient way of dealing with an ailing banking system ( Laeven and Valencia, 2013 ; Landier and Ueda, 2013 ). Excessive liquidity support and guarantees of bank liabilities cannot substitute for proper restructuring and recapitalization either as most banking crises involve solvency problems and not only liquidity shortfalls. In the case of banking crises, the sooner restructuring is implemented, the better outcomes are. Such a strategy removes residual uncertainty that triggers precautionary contractions in consumption and investment, which in turn further exacerbate recessions. Still in spite of this understanding, many countries do not adopt these policy responses, including in some current crises ( Claessens et al. 2013 ), suggesting that there are deeper factors that research has not be able to uncover or address. Moreover, issues related to restructuring of both household debt and sovereign debt require more sophisticated theoretical and empirical approaches ( Laeven and Laryea, 2013 ; Das, 2013 ; Igan and others, 2013 ).

• What are the major needs for additional data and methods?

As the review here documents, it is necessary to put together new data series and to design new methodologies to get a better understanding of crises episodes. The review lists several recent studies that put together new data series on financial crises. In spite of these, there is clearly a case for more research to collect additional cross-country data on aspects relevant to financial crises. Better data on domestic debt and house prices are urgently needed to get a richer understanding of domestic debt dynamics and fluctuations in housing markets. There is also a need for better (international) data for both surveillance and early warning exercises (see Heath, 2013 and Cerutti, Claessens and McGuire, 2013 , for data needs). For a deeper understanding of crises and the policy issues surrounding these episodes, another need is to design new methods to classify crises in a more robust manner. Moreover, it would be important to examine periods of financial disruptions, which are not necessarily crises. Although good luck or adequate policy measures may have prevented a financial crisis following such disruption episodes, there are lessons to be learned since those are the types of periods that can provide case studies of counterfactuals to analyze the macroeconomic outcomes and implications of policy responses.

Abbas , S. A. , M. Belhocine , A. El Ganainy , and M. Horton , 2011 , “ Historical Patterns and Dynamics of Public Debt- Evidence from a New Database, ” IMF Economic Review , Vol . 59 , No. 4 , pp. 717 – 42 .

• Search Google Scholar
• Export Citation

Abiad , A. , R. Balakrishnan , P. K. Brooks , D. Leigh , and I. Tytell , 2013 , “ What’s the Damage: Medium-term Output Dynamics after Financial Crises, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming .

Abiad , A. , G. Dell’Ariccia , B. Li , 2013 , “ What Have We Learned about Creditless Recoveries?, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming .

Abreu , D. , and M. K. Brunnermeier , 2003 , “ Bubbles and Crashes, ” Econometrica , Vol . 71 , No. 1 , pp. 173 – 204 .

Allen , R. E. , 2010 , Financial Crises and Recession in the Global Economy , Edward Elgar Publishing , 3rd Edition .

Allen , F. , A. Babus , and E. Carletti , 2009 , “ Financial Crises: Theory and Evidence, ” Annual Review of Financial Economics , Vol . 1 , pp. 97 – 116 .

Allen , F. , and D. Gale 2007 , Understanding Financial Crises (Clarendon Lect. Finance) , Oxford : Oxford University Press .

Alessi , L. , and C. Detken , 2011 , “ Quasi Real Time Early Warning Indicators for Costly Asset Price Boom/bust Cycles: A Role for Global Liquidity, ” European Journal of Political Economy , Vol . 27 , No. 3 , pp. 520 – 33 .

Auguiar , M. , and G. Gopinath , 2006 , “ Defaultable Debt, Interest Rates and the Current Account, ” Journal of International Economics , Vol . 69 , pp. 64 – 83 .

Baldacci , E. , S. Gupta , and C. Mulas-Granados , 2013 , “ How Effective is Fiscal Policy Response in Financial Crises?, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming .

Barberis , N. , and R. Thaler , 2003 , “ A Survey of Behavioral Finance, ” in Handbook of the Economics of Finance , G.M. Constantinides , M. Harris and R. Stulz , eds . Chap.18 , pp. 1051 – 121 .

Barth , J. , G. Caprio , and R. Levine , 2006 , Rethinking Bank Regulation: Till Angels Govern , Cambridge University Press , New York, NY .

Barth , J. , G. Caprio , and R. Levine , 2012 , Guardians of Finance: Making Regulators Work for Us , The MIT Press , First Edition .

Bean , C , M Paustian , A. Penalver , and T. Taylor , 2010 , “ Monetary Policy After the Fall, ” proceedings of the Federal Reserve Bank of Kansas City Annual Conference , Jackson Hole, Wyoming .

Blanchard O. , G. Dell’Ariccia , P. Mauro , 2010 , “ Rethinking Macroeconomic Policy, ” Journal of Money, Credit and Banking , Vol . 42 , No. 1 , pp. 199 – 215 .

Blanchard , O. J. , and M. W. Watson , 1982 , “ Bubbles, Rational Expectations and Speculative Markets, ” in Crisis in Economic and Financial Structure: Bubbles, Bursts, and Shocks , P. Wachtel , ed. Lexington Books : Lexington .

Blanco , H. , and P. M. Garber , 1986 , “ Recurrent Devaluation and Speculative Attacks on the Mexican Peso, ” Journal of Political Economy , Vol . 94 , No 1 , pp. 148 – 66 .

Bordo , M. D. , B. Eichengreen , D. Klingebiel , and M.S. Martinez-Peria , 2001 , “ Is the Crisis Problem Growing More Severe? ” Economic Policy , Vol .16 , pp. 51 – 82 .

Bordo , M. , and J. Haubrich , 2012 , “ Deep Recessions, Fast Recoveries, and Financial Crises: Evidence from the American Record, ” NBER Working Paper 18194 .

Borensztein , E. , and U. Panizza , 2009 , “ The Costs of Sovereign Default, ” IMF Staff Papers , Vol . 56 , No. 4 , pp. 683 – 741 .

Borio , C. , and P. Lowe , 2002 , “ Asset Prices, Financial and Monetary Stability: Exploring the Nexus, ” BIS Working Paper, No. 114 .

Branch , W. , and G. W. Evans , 2008 , “ Learning about Risk and Return: A Simple Model of Bubbles and Crashes, ” University of Oregon Economics Department Working Papers 2008-1 .

Brunnermeier , M. , 2001 , Asset Pricing Under Asymmetric Information: Bubbles, Crashes, Technical Analysis and Herding , Oxford University Press .

Bulow , J. , and K. Rogoff , 1989 , “ Sovereign Debt: Is to Forgive to Forget? ” American Economic Review , Vol . 79 , No. 1 , pp. 43 – 50 .

Burnside , C. , M. Eichenbaum , and S. Rebelo , 2001 , “ Prospective Deficits and the Asian Currency Crisis, ” Journal of Political Economy , Vol . 109 , No. 6 , pp. 1155 – 197 .

Burnside , C. , M. Eichenbaum , and S. Rebelo , 2004 , “ Government Guarantees and Self-fulfilling Speculative Attacks, ” Journal of Economic Theory , Vol .119 , pp. 31 – 63 .

Calomiris , C. W. , 2009 , “ The Subprime Turmoil: What’s Old, What’s New, and What’s Next, ” Journal of Structured Finance , Spring 2009 , Vol . 15 , No. 1 , pp. 6 – 52 .

Calomiris , C , and G. Gorton , 1991 , “ The Origins of Banking Panics, Models, Facts, and Bank Regulation, ” in Financial Markets and Financial Crises , R.G. Hubbard , ed. , pp. 107 – 73 .

Calvo , G. A. , 2000 . “ Betting Against the State Socially Costly Financial Engineering, ” Journal of International Economics , Vol . 51 , No. 1 , pp. 5 – 19 .

Calvo , G. A. , A. Izquierdo , and R. Loo-Kung , 2006 , “ Relative Price Volatility under Sudden Stops: The Relevance of Balance Sheet Effects, ” Journal of International Economics , Vol . 69 , 1 , pp. 231 – 54 .

Calvo , G. A. , A. Izquierdo , and L. Mejía , 2008 , “ Systemic Sudden Stops: The Relevance of Balance-Sheet Effects and Financial Integration, ” NBER Working Papers 14026 , National Bureau of Economic Research, Inc .

Calvo , G. A. , A. Izquierdo , and L. Mejía , 2004 , “ On the Empirics of Sudden Stops: The Relevance of Balance-Sheet Effects, ” Proceedings , Federal Reserve Bank of San Francisco .

Calvo , G. A. , A. Izquierdo , and E. Talvi , 2006 , “ Phoenix Miracles in Emerging Markets: Recovering without Credit from Systemic Financial Crises, ” NBER Working Papers 12101 , National Bureau of Economic Research .

Calvo , G. , and C. Reinhart , 1999 , “ Capital Flow Reversals, the Exchange Rate Debate, and Dollarization, ” Finance and Development , International Monetary Fund , September .

Calvo , G. , and C. Reinhart , 2000 , “ When Capital Inflows Come to a Sudden Stop: Consequences and Policy Options, ” in P. B. Kenen and A. K. Swoboda , eds. , Reforming the International Monetary and Financial System , Washington, DC , International Monetary Fund .

Campbell , J. ( ed. ), 2008 , Asset Prices and Monetary Policy , NBER Conference Report . University of Chicago Press

Campello , M. , J. Graham , and C. R. Harvey , 2010 . “ The real effects of financial constraints: Evidence from a financial crisis, ” Journal of Financial Economics , Vol . 97 , No. 3 , pp. 470 – 87 .

Cardarelli , R. , M. A. Kose , and S. Elekdag , 2010 , “ Capital Inflows: Macroeconomic Implications and Policy Responses, ” Economic Systems , Vol . 34 , No. 4 .

Cardarelli , R. , S. Elekdag , and Subir Lall , 2009 , Financial Stress, Downturns, and Recoveries, IMF Working Paper No. 09/100 , forthcoming Journal of Financial Stability .

Cerutti , E. , S. Claessens , and P. McGuire , 2013 , “ Systemic Risks in Global Banking: What Available Data Can Tell Us and What More Data Are Needed? ” in Systemic Risk and Macro Modeling , M. K. Brunnermeier and A. Krishnamurthy , eds. , forthcoming , NBER/University of Chicago Press .

Chang , R. , and A. Velasco , 2000 , “ Liquidity Crises in Emerging Markets: Theory and Policy, ” Chapter in : NBER Macroeconomics Annual 1999 , Vol . 14 , p. 11 – 78 .

Chen , J. , H. Hong , and J. C. Stein , 2002 , “ Breadth of Ownership and Stock Returns, ” Journal of Financial Economics , Vol . 66 , No. 2-3 , pp. 171 – 205 .

Čihák , M. , A. Demirgüç-Kunt , M. Soledad Martínez Pería , and A. Mohseni-Cheraghlou , 2012 , “ Bank Regulation and Supervision around the World: A Crisis Update, ” World Bank Policy and Research Working Paper, No.6286 .

Claessens , S. , “ Balance of Payments Crises in an Optimal Portfolio Model, ” European Economic Review , 1991 , 35 , pp. 81 – 101 .

Claessens , S. , 2009 , “ Competition in the Financial Sector: Overview of Competition Policies, ” World Bank Research Observer , Vol . 24 , pp. 83 – 118 .

Claessens , S. , C. Pazarbasioglu , M. Dobler , F. Valencia , O. Nedelescu , and K. Seal , 2013 , “ Crisis Management and Resolution: Early Lessons from the Financial Crisis, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming .

Claessens , S. , G. Dell’Ariccia , D. Igan , and L. Laeven , 2010 , “ Cross-Country Experience and Policy Implications from the Global Financial Crisis, ” Economic Policy . A European Forum , April 2010 , Vol . 62 . PP. 269 – 93 .

Claessens , S. , G. Dell’Ariccia , D. Igan , and L. Laeven , 2012 , “ A Cross-Country Perspective on the Causes of the Global Financial Crisis, ” in Handbooks in Financial Globalization: The Evidence and Impact of Financial Globalization , pp. 737 – 52 . Elsevier UK : Academic Press .

Claessens , S. , M. A. Kose , and M. Terrones , 2009 , “ What Happens During Recessions, Crunches and Busts? ” Economic Policy , Vol . 60 , pp. 653 – 700 .

Claessens , S. , M. A. Kose , and M. Terrones , 2010a , “ Financial Cycles: What? How? When? ” in NBER International Seminar in Macroeconomics 2010 , Richard Clarida and Francesco Giavazzi , eds. Chicago : University of Chicago Press .

Claessens , S. , M. A. Kose , and M. Terrones , 2010b , “ The Global Financial Crisis: How Similar? How Different? How Costly? ” Journal of Asian Economics , Vol . 21 , No. 3 , pp. 247 – 64 .

Claessens , S. , M. A. Kose , and M. Terrones , 2012 , “ How do Business and Financial Cycles Interact? ” Journal of International Economics , Vol . 87 , pp. 178 – 90 .

Corsetti , G. , P. Pesenti , and N. Roubini , 1998 , “ Paper Tigers? A Model of the Asian Crises, ” European Economic Review , Vol . 43 , No. 7 , pp. 1211 – 236 .

Crespo-Cuaresma , J. , and T. Slacik , 2009 , “ On the Determinants of Currency Crisis: The Role of Model Uncertainty, ” Journal of Macroeconomics , Vol . 31 , pp. 621 – 32 .

Crowe , C. , G. Dell’Ariccia , D. Igan , and P. Rabanal , 2013 , “ Policies for Macrofinancial Stability: Managing Real Estate Booms and Busts, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming .

Cruces , J. J. , and C. Trebesch , 2011 , “ Sovereign Defaults: The Price of Haircuts, ” ( unpublished ; Berlin, Germany : Free University of Berlin ).

Cumby , R. E. , and S. van Wijnbergen , 1989 , “ Financial Policy and Speculative Runs with a Crawling Peg: Argentina 1979-1981, ” Journal of International Economics , Vol .27 , pp. 111 – 27 .

Das , U. S. , 2013 , “ Restructuring Sovereign Debt: Lessons from Recent History, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming .

Das , U. S. , M. G. Papaioannou , and C. Trebesch , 2012 , “ Sovereign Debt Restructurings 1950–2010: Literature Survey, Data, and Stylized Facts, ” IMF Working Paper No. 12/203 ( Washington : International Monetary Fund ).

De Gregorio , J. , 2013 , “ Resilience in Latin America: Lessons from Macroeconomic Management and Financial Policies, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming .

De la Torre , A. , and A. Ize , 2011 , “ Containing Systemic Risk: Paradigm-based Perspectives on Regulatory Reform, ” Policy Research Working Paper Series 5523 , The World Bank .

Dell’Ariccia , G. , E. Detragiache , Enrica , and R. Rajan , 2008 , “ The Real Effect of Banking Crises, ” Journal of Financial Intermediation , Vol . 17 , pp. 89 – 112 .

Dell’Ariccia , G. , D. Igan , and L. Laeven , 2012 , “ Credit Booms and Lending Standards: Evidence from the U.S. Subprime Mortgage Market, ” Journal of Money, Credit and Banking , Vol . 44 , pages 367 – 84 .

Dell’Ariccia , G. , D. Igan , L. Laeven , and H. Tong , 2013 , “ Policies for Macrofinancial Stability: Dealing with Credit Booms and Busts, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming .

Dell’Ariccia , G. , L. Laeven , and R. Marquez , 2010 , “ Monetary Policy, Leverage, and Bank Risk-taking, ” IMF Working Papers 10/276 , International Monetary Fund .

De Nicolò , G. , G. Dell’Ariccia , L. Laeven , and F. Valencia , 2010 , “ Monetary Policy and Bank Risk-Taking, ” IMF Staff Position Note, SDN/10/09 .

Demirgüç-Kunt , A. , E. J. Kane , and L. Laeven , 2008 , “ Determinants of Deposit-insurance Adoption and Design, ” Journal of Financial Intermediation , Vol . 17 , No. 3 , pp. 407 – 38 .

Dewatripont , M. , and J. Tirole , 1994 , The Prudential Regulation of Banks , MIT Press .

Diamond , D. , and R. Rajan , 2001 , “ Banks, Short-term Debt, and Financial Crises: Theory, Policy Implications and Applications, ” Carnegie-Rochester Conference Series , Vol . 54 , pp. 37 – 71 .

Diamond , D. , and P. Dybvig , 1983 , “ Bank Runs, Deposit Insurance, and Liquidity, ” Journal of Political Economics , Vol . 91 , pp. 401 – 19 .

Diether , K. , C. J. Malloy , and A. Scherbina , 2002 , “ Differences of Opinion and the Cross-Section of Stock Returns, ” Journal of Finance , Vol . 57 , No. 5 .

Eaton , J. , and R. Fernandez , 1995 , “ Sovereign Debt, ” in the Handbook of International Economics , G.M. Grossman and K. Rogoff , eds. , Vol . 3 , Chapter 3 , pp. 2031 – 077 .

Eaton , J. , and M. Gersovitz , 1981 , “ Debt with Potential Repudiation: Theoretical and Empirical Analysis, ” The Review of Economic Studies , Vol . 48 , No. 2 , pp. 289 – 309 .

Edwards , S. , 1984 , “ The Demand for International Reserves and Monetary Equilibrium: Some Evidence from Developing Countries, ” The Review of Economics and Statistics , MIT Press , Vol . 66 , No. 3 , pp. 495 – 500 .

Eichengreen , B. , 2002 , Financial Crises: And What To Do About Them , Oxford University Press .

Eichengreen , B. , A. K. Rose , and C. Wyplosz , 1996 , “ Speculative Attacks on Pegged Exchange Rates: An Empirical Exploration with Special Reference to the European Monetary System, ” in M.B. Canzoneri , P.R. Masson , and V.U. Grilli , eds. , Transatlantic economic issues ( Cambridge University Press , Cambridge, UK ).

Eichengreen , B. , and R. Hausmann , 1999 , “ Exchange Rates and Financial Fragility, ” Proceedings , Federal Reserve Bank of Kansas City , pages 329 – 68 .

Evanoff , D. D. , G. G. Kaufman , A. G. Malliaris , 2012 , New Perspectives on Asset Price Bubbles , Oxford University Press .

Fama , E. F. , 1998 , “ Market Efficiency, Long-term Returns, and Behavioral Finance, ” Journal of Financial Economics , Vol . 49 , pp. 283 – 306 .

Farhi , E. , and J. Tirole , 2012 , “ Collective Moral Hazard, Maturity Mismatch, and Systemic Bailouts, ” American Economic Review , Vol . 102 , No. 1 , pp. 60 – 93 .

Feldstein , M. 2009 , “ Rethinking the Role of Fiscal Policy, ” American Economic Review , Vol . 99 , No. 2 , pp. 556 – 59 .

Fisher , I. , 1933 , “ The Debt Deflation Theory of Great Depressions ” Econometrica , Vol 1 , pp. 337 – 57 .

Flood , R. , and N. P. Marion , 1997 , “ Policy Implications of “Second-Generation” Crisis Models, ” IMF Staff Papers , Vol .44 , No. 3 , pp. 383 – 90 .

Flood , R. , and P. Garber , 1984 , “ Collapsing Exchange-Rate Regimes: Some Linear Examples, ” Journal of International Economics , Vol .17 , pp. 1 – 13

Forbes , K. J. 2012 , “ The Big “C”: Identifying and Mitigating Contagion, ” Proceedings 2012 Jackson Hole Symposium , hosted by the Federal Reserve Bank of Kansas City .

Forbes , K. J. , and F. Warnock , 2012 , “ Capital Flow Waves: Surges, Stops, Flight, and Retrenchment, ” Journal of International Economics , Vol . 88 , No. 2 , pp. 235 – 51 .

Frankel , J. A. , and A. K. Rose , 1996 , “ Currency crashes in emerging markets: An empirical treatment, ” Journal of International Economics , Vol . 41 , Nos. 3-4 , pp. 351 – 66 .

Frankel , J. , and G. Saravelos , 2012 , “ Can Leading Indicators Assess Country Vulnerability? Evidence from the 2008–09 Global Financial Crisis, ” Journal of International Economics , Vol . 87 , pp. 216 – 31 .

Furceri , D. , and A. Zdzienicka , A. , 2012 , “ How Costly Are Debt Crises? ” Journal of International Money and Finance , Vol . 31 . No. 4 , pp. 726 – 42 .

Garber , P. M. , 2000 , Famous First Bubbles: The Fundamentals of Early Manias , Cambridge, MA : MIT Press .

Glick R. , and M. Hutchison , 2012 , Currency Crises , in Elsevier Encyclopedia on Financial Globalization .

Goldstein , M. , C. Reinhart , and G. Kaminsky , 2000 , Assessing financial vulnerability, an Early Warning System for Emerging Markets , Peterson Institute for International Economics Press , No. 100 .

Gorton , G. , 1988 , “ Banking Panics and Business Cycles, ” Oxford Economics Papers , Vol . 40 , pp. 751 – 81 .

Gorton , G. , 2008 , “ The Panic of 2007, ” in Maintaining Stability in a Changing Financial System, Proceedings of the 2008 Jackson Hole Conference , Federal Reserve Bank of Kansas City .

Gorton , G. , 2009 , “ Slapped in the Face by the Invisible Hand: Banking and the Panic of 2007, ” Paper prepared for the Federal Reserve Bank of Atlanta’s 2009 Financial Markets Conference: Financial Innovation and Crisis , May 11-13 .

Gorton , G. , 2012 , Misunderstanding Financial Crises: Why We Don’t See Them Coming , Oxford University Press .

Gorton G. and G. Ordonez , 2012 , “ Collateral Crises, ” NBER Working Papers, No. 17771 , National Bureau of Economic Research, Inc.

Gourinchas , P.-O. , R. Valdés , and O. Landerretche , 2001 , “ Lending Booms: Latin America and the World, ” Economia , Vol . 1 , pp. 47 – 99 .

Gupta , P. , D. Mishra , and R. Sahay , 2007 , “ Behavior of Output During Currency Crises, ” Journal of International Economics , Vol . 72 , No. 2 , pp. 428 – 50 .

Gurkaynak , R. S. , 2008 , “ Econometric Tests of Asset Price Bubbles: Taking Stock, ” Journal of Economic Surveys , Vol . 22 , No. 1 , pp. 166 – 86 .

Haber , S. , 2005 , “ Banking and Economic Growth in Mexico, ” Working Paper , Hoover Institution .

Harrison , J. M. , and D. M. Kreps , 1978 , “ Speculative Investor Behavior in a Stock Market with Heterogeneous Expectations, ” The Quarterly Journal of Economics , Vol . 92 . No. 2 , pp. 323 – 36 .

Heath , Robert , 2013 , “ Why are the G-20 Data Gaps Initiative and the SDDS Plus Relevant for Financial Stability Analysis? ” IMF Working Paper, No. 13/6 , Washington, D.C.

Hirata , H. , M. A. Kose , C. Otrok , and M. E. Terrones , 2012 , “ Global House Price Fluctuations: Synchronization and Determinants, ” in Francesco Giavazzi and Kenneth West , eds. NBER International Seminar on Macroeconomics 2012 , National Bureau of Economic Research .

Hong , H. , J. Scheinkman , and W. Xiong , 2008 , “ Advisors and Asset Prices: A Model of the Origins of Bubbles, ” Journal of Financial Economics , Vol . 89 , No. 2 , pp. 268 – 87 .

Honohan , P. and L. Laeven ( eds. ), 2007 , Systemic Financial Crises , Cambridge Books, Cambridge University Press ,

Howard , G. , R. Martin , B. A. Wilson , 2011 , “ Are Recoveries from Banking and Financial Crises Really So Different? ” Board of Governors of the Federal Reserve System, International Finance Discussion Papers, Working Paper Number 1037 .

Igan , D. , D. Leigh , J. Simon , and P. Topalova , 2013 , “ Dealing with Household Debt, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming .

IMF , 2010 , “ The IMF-FSB Early Warning Exercise: Design and Methodological Toolkit, ” IMF , available at www.imf.org/external/np/pp/eng/2010/090110.pdf .

IMF , 2013 , “ The Interaction of Monetary and Macroprudential Policies, ” Board Paper , forthcoming .

Jeanne , O. , 2003 , “ Why do Emerging Economies Borrow in Foreign Currency? ” IMF Working Papers, No. 03/177 , International Monetary Fund .

Jorda , O. , M. Schularick , and A. M. Taylor , 2012 , “ When Credit Bites Back: Leverage, Business Cycles, and Crises, ” San Francisco Fed , Working Paper No. 2011-27 .

Kaminsky , G. 2003 , “ Varieties of Currency Crises, ” NBER Working Papers, No. 10193 , National Bureau of Economic Research, Inc.

Kaminsky , G. , S. Lizondo , and C. Reinhart , 1998 , “ Leading Indicators of Currency Crisis, ” IMF Staff Papers , Vol . 45 , No. 1 .

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. , and C. Reinhart , 2001 , “ Bank Lending and Contagion: Evidence from the Asian Crisis, ” NBER Chapters , in: Regional and Global Capital Flows: Macroeconomics Causes and Consequences , Vol . 10 , pp. 73 – 116 .

Kannan , P. , 2009 , “ On the Welfare Benefits of an International Currency, ” European Economic Review , Vol . 53 , No. 5 , pp. 588 – 606 .

Kannan , P. , A. Scott , and M. E. Terrones , 2013 , “ From Recession to Recovery: How Soon and How Strong, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming .

Keynes , J. M. , 1930 , The Great Slump of 1930 . London : The Nation & Athenæum , ( First Edition ).

Kindleberger , C. , 1978 , Manias, Panics, and Crashes: A History of Financial Crises , New York : Basic Books

Kindleberger , C. , 1986 , The World in Depression: 1929-1939 , Berkeley : University of California Press .

Klein , M. W. , and N. P. Marion , 1994 , “ Explaining the Duration of Exchange-Rate Pegs, ” NBER Working Papers 4651 , National Bureau of Economic Research, Inc.

Kletzer , K. M. , and B. D. Wright , 2000 , “ Sovereign Debt as Intertemporal Barter, ” American Economic Review , Vol . 90 , No. 3 , pp. 621 – 39 .

Klingebiel , D. , R. Kroszner , and L. Laeven , 2007 . “ Banking Crises, Financial Dependence, and Growth, ” Journal of Financial Economics , Vol . 84 , No. 1 , pp. 187 – 228 .

Kose , M. A. , P. Loungani , M. Terrones , 2013 , “ Global Recessions and Recoveries, ” IMF Working Paper , forthcoming .

Kose , M. A. , and E. Prasad , 2010 , Emerging Markets: Resilience and Growth Amid Global Turmoil , Brookings Institute .

Kose , M. A. , E. Prasad , K. Rogoff , and S.-J. Wei , 2010 , “ Financial Globalization and Economic Policies, ” in D. Rodrik and M. Rosenzweig , eds. , Handbook of Development Economics Vol . 5 , pp. 4283 – 362 .

Krugman , P. , 1979 , “ A Model of Balance-of-Payments Crises, ” Journal of Money, Credit and Banking , Vol . 11 , No. 3 , pp. 311 – 25 .

Krugman , P. , 1999 , “ Balance Sheets, the Transfer Problem, and Financial Crises, ” International Tax and Public Finance , Vol . 6 , No. 4 , pp. 459 – 72 .

La Porta , R. , F. Lopez-de-Silanes , A. Shleifer , and R. Vishny , 2000 , “ Investor Protection and Corporate Governance, ” Journal of Financial Economics , Vol . 58 , Nos. 1-2 , pp. 3 – 27 .

Laeven , L. , 2001 , “ Insider Lending and Bank Ownership: The Case of Russia, ” Journal of Comparative Economics , Vol . 29 , No. 2 , pp. 207 – 29 .

Laeven , L. , 2011 , “ Banking Crises: A Review, ” Annual Review of Financial Economics, Annual Reviews , Vol . 3 , No. 1 , pp. 17 – 40 .

Laeven , L. , and T. Laryea , 2013 , “ Principles of Household Debt Restructuring, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming .

Laeven , L. , and F. Valencia , 2008 , “ Systemic Banking Crises: A New Database, ” IMF Working Papers 08/224 , International Monetary Fund .

Laeven , L. , and F. Valencia , 2013a , “ Systemic Banking Crises ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming . ( also issued as “ Systemic Banking Crises Database: An Update, ” IMF Working Paper, No.12/163 .)

Laeven , L. , and F. Valencia , 2013b , “ Resolution of Banking Crises: The Good, the Bad, and the Ugly, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming . ( also issued as “ Resolution of Banking Crises: The Good, the Bad, and the Ugly, ” IMF Working Paper, No. 10/146 .)

Lamont , O. , and A. R. H. Thaler , 2003 , “ Can the Market Add and Subtract? Mispricing in Tech Stock Carve-outs, ” Journal of Political Economy , Vol . 111 , No. 2 , pp. 227 – 68 .

Landier , A. , and K. Ueda , 2013 , “ The Economics of Bank Restructuring: Understanding the Options, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming .

Lane , P. R. , 2012 , “ The European Sovereign Debt Crisis, ” Journal of Economic Perspectives , Vol . 26 , No. 3 , pp. 49 – 68 .

Lane , P. R. , and G-M. Milesi-Ferretti , 2011 , “ The Cross-Country Incidence of the Global Crisis, ” IMF Economic Review , Vol . 59 , No. 1 , pp. 77 – 110 .

Lansing , K. J. , 2008 , “ Speculative Growth and Overreaction to Technology Shocks, ” Working Paper Series 2008-08 , Federal Reserve Bank of San Francisco .

Levy-Yeyati , E. L. and U, Panizza , 2011 , “ The Elusive Costs of Sovereign Defaults, ” Journal of Development Economics , Vol . 94 ( 1 ), pp. 95 – 105 .

Lindgren C.-J. , G. Garcia , and M. Saal ( eds. ), 1996 , Bank Soundness and Macroeconomic Policy , International Monetary Fund , Washington .

Lo , A. W. , and A. C. MacKinlay , 2001 , A Non-Random Walk Down Wall Street , Princeton University Press .

Lopez-Salido , D. , and E. Nelson , 2010 , “ Postwar Financial Crises and Economic Recoveries in the United States, ” Working Paper , Federal Reserve Board .

Maddaloni , A. , and J-L. Peydró , 2010 , “ Bank Risk-taking, Securitization, Supervision and Low Interest Rates: Evidence from the Euro Area and the U.S. Lending Standards, ” Working Paper Series 1248 , European Central Bank .

Magud , N. E. , C. M. Reinhart , and E. R. Vesperoni , 2012 , “ Capital Inflows, Exchange Rate Flexibility, and Credit Booms, ” IMF Working Paper, No. 12/41 .

McKinnon , R , and H. Pill , 1996 , “ Credible Liberalizations and International Capital Flows: The Overborrowing Syndrome, ” in T. Ito , and A. Krueger , eds. , Financial Deregulation and Integration in East Asia , pp. 7 – 42 ( University of Chicago Press ).

McKinnon , R , and H. Pill , 1998 , “ International Overborrowing: A Decomposition of Credit and Currency Risks, ” World Development , Vol . 26 , No. 7 , pp. 1267 – 282 .

Mendoza , E. G. , 2010 , “ Sudden Stops, Financial Crises, and Leverage, ” American Economic Review , Vol . 100 , No. 5 , pp. 1941 – 966 .

Mendoza , E. G. , and M. E. Terrones , 2008 , “ An Anatomy of Credit Booms: Evidence From Macro Aggregates and Micro Data, ” NBER Working Papers 14049 .

Mendoza , E. G. , and M. E. Terrones , 2012 , “ An Anatomy of Credit Booms and Their Demise, ” Journal of Economia Chilena , Central Bank of Chile , Vol . 15 , pp. 4 – 32 .

Milesi-Ferretti , G-M. , and C. Tille , 2011 , “ The Great Retrenchment: International Capital Flows During the Global Financial Crisis, ” Economic Policy , Vol . 26 , No. 66 , pp. 285 – 342 .

Milesi-Ferretti , G-M. , and A. Razin , 2000 , “ Current Account Reversals and Currency Crises, Empirical Regularities, ” NBER Chapters , in Currency Crises , pp. 285 – 326 , National Bureau of Economic Research .

Miller , E.M. , 1977 , “ Risk, Uncertainty and Divergence of Opinion, ” Journal of Finance , Vol . 32 , pp. 1151 – 61 .

Minsky , H. P. , 1975 , John Maynard Keynes , Columbia University Press .

Minsky , H. P. , 1977 , “ A Theory of Systemic Fragility, ” in E.J. Altman and A. W. Sametz , eds. , Financial Crises: Institutions and Markets in a Fragile Environment , Wiley , pp. 138 – 52 .

Mishkin , F. S. , 2008 , “ Does Stabilizing Inflation Contribute To Stabilizing Economic Activity? ” NBER Working Papers 13970 , National Bureau of Economic Research, Inc.

Mishkin , F. S. , 2011 , “ Monetary Policy Strategies: Lessons from the Crisis, ” NBER Working Papers 16755 , National Bureau of Economic Research .

Obstfeld , M. , 2012 , “ Financial Flows, Financial Crises, and Global Imbalances, ” Journal of International Money and Finance , Vol . 31 , No. 3 , pp. 469 – 80 .

Obstfeld , M. , and K. Rogoff , 1986 , “ Ruling Out Divergent Speculative Bubbles, ” Journal of Monetary Economics , Vol . 17 , No. 3 , pp. 349 – 62 .

Obstfeld , M. , and K. Rogoff , 2009 , “ Global Imbalances and the Financial Crisis: Products of Common Causes, ” CEPR Discussion Papers, No. 7606 .

Ofek , E. , and M. Richardson , 2003 , “ DotCom Mania: The Rise and Fall of Internet Stock Prices, ” Journal of Finance , Vol . 58 , pp. 1113 – 137 .

Ongena , S. , I. Vasso , and J. L. Peydró , 2009 , Monetary policy, risk-taking and pricing: Evidence from a quasi-natural experiment. Discussion Paper 2009-31 , Tilburg University, Center for Economic Research .

Panizza , U. , F. Sturzenegger , and J. Zettelmeyer , 2009 , “ The Economics and Law of Sovereign Debt and Default, ” Journal of Economic Literature , Vol . 47 , No. 3 , pp. 651 – 98 .

Papell , D. H. , and R. Prudan , 2011 , “ The Statistical Behavior of GDP after Financial Crises and Severe Recessions, ” Paper prepared for the Federal Reserve Bank of Boston conference on “Long-Term Effects of the Great Recession,” October 18-19 .

Pastor , L. , and P. Veronesi , 2006 , “ Was There a Nasdaq Bubble in the Late 1990s? ” Journal of Financial Economics , Vol . 81 , No. 1 , pp. 61 – 100 .

Radelet , S. , and J. Sachs . 1998 , “ The East Asian Financial Crisis: Diagnosis, Remedies, Prospects, ” Brookings Papers on Economic Activity , Vol . 1 , pp. 1 – 74 .

Rajan , R. G. , 2005 , “ Has Financial Development Made the World Riskier? ” Proceedings , Federal Reserve Bank of Kansas City , August , pp. 313 – 69 .

Rancière , R. , and A. Tornell , 2011 , “ Financial Black-Holes: The Interaction of Financial Regulation and Bailout Guarantees, ” CEPR Discussion Papers 8248, C.E.P.R. Discussion Papers .

Reinhart , C. M. , and K. S. Rogoff , 2008 , “ Is the 2007 U.S. Subprime Crisis So Different? An International Historical Comparison, ” American Economic Review , Vol . 98 , No. 2 , pp. 339 – 44 .

Reinhart , C. M. , and K. S. Rogoff , 2009a , This Time is Different: Eight Centuries of Financial Folly , Princeton Press .

Reinhart , C. M. , and K. S. Rogoff , 2009b , “ The Aftermath of Financial Crises, ” American Economic Review , Vol . 99 , pp. 466 – 72 .

Reinhart , C. M. , and K. S. Rogoff , 2011 , “ From Financial Crash to Debt Crisis, ” American Economic Review . Vol . 101 , No. 5 , pp. 1676 – 706 .

Reinhart , C. M. , and K. S. Rogoff , 2013 , “ Financial and Sovereign Debt Crises: Some Lessons and Those Forgotten, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming .

Reinhart , C. , J. Kirkegaard , and B. Sbrancia , 2011 , “ Financial Repression Redux, ” IMF Finance and Development , Vol . 48 , No. 1 .

Rose , A. K. , and M. M. Spiegel ., 2011 , “ Cross-Country Causes and Consequences of the 2008 Crisis: Early Warning. ” European Economic Review , Vol . 55 , No. 3 , pp. 309 – 24 .

Salant , S. , 1983 , “ The Vulnerability of Price Stabilization Schemes to Speculative Attack, ” Journal of Political Economy , Vol . 91 , pp. 1 – 38 .

Salant , S. , and D. Henderson , 1978 , “ Market Anticipations of Government Policies and the Price of Gold, ” Journal of Political Economy , Vol . 86 , pp. 627 – 48 .

Scheinkman , J. A. , and W. Xiong , 2003 , “ Overconfidence and Speculative Bubbles, ” Journal of Political Economy , Vol . 111 , No. 6 , pp. 1183 – 219 .

Schularick , M. , and A. M. Taylor , 2012 , “ Credit Booms Gone Bust: Monetary Policy, Leverage Cycles, and Financial Crises, 1870-2008, ” American Economic Review , Vol . 102 , No. 2 , pp. 1029 – 061 .

Schwert , G. W. , 2003 , “ Anomalies and Market Efficiency, ” in Handbook of the Economics of Finance , G.M. Constantinides , M. Harris , and R. M. Stulz ( ed. ), Vol . 1 , chapter 15 , pp. 939 – 74 .

Shin , H. S. , 2009 , “ Reflections on Northern Rock: The Bank Run that Heralded the Global Financial Crisis, ” Journal of Economic Perspectives , Vol . 23 , No. 1 , pp. 101 – 19 .

Shin , H. S. , 2013 , “ Procyclicality and the Search for Early Warning Indicators, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming .

Shleifer , A. , 2000 , Inefficient Markets: An Introduction to Behavioral Finance , Oxford University Press .

Shleifer , A. , and R.W. Vishny , 1997 , “ The Limits of Arbitrage, ” Journal of Finance , Vol . 52 , No. 1 , pp. 35 – 55 .

Stiglitz , J. , and A. Weiss , 1981 . “ Credit Rationing in Markets with Imperfect Information, ” American Economic Review , Vol . 71 , No. 3 , pp. 393 – 410 .

Sturzenegger , F. , and J. Zettelmeyer , 2007 , “ Debt Defaults and Lessons from a Decade of Crises, ” Cambridge and London : MIT Press .

Taylor , A. M. , 2013 , “ External Imbalances and Financial Crises, ” in S. Claessens , M. A. Kose , L. Laeven , and F. Valencia , eds. , Financial Crises, Consequences, and Policy Responses , forthcoming .

Taylor , J. B. , 2009 , “ The Financial Crisis and the Policy Responses: An Empirical Analysis of What Went Wrong, ” NBER Working Paper, No. 14631 .

Taylor , J. B. , 2011 , “ An Empirical Analysis of the Revival of Fiscal Activism in the 2000s, ” Journal of Economic Literature , Vol . 49 , No. 3 , pp. 686 – 702 .

Tirole , J. , 2002 , Financial Crises, Liquidity, and the International Monetary System , Princeton University Press .

Tomz , M. , and M. L. J. Wright , 2007 , “ Do Countries Default in “Bad Times”? ” Journal of the European Economic Association , Vol . 5 , No. 2-3 , pp. 352 – 60 .

Wang , P. , and Y. Wen , 2010 , “ Speculative Bubbles and Financial Crises, ” American Economic Journal: Macroeconomics , Vol . 4 , No. 3 , pp. 184 – 221 .

Wermers , R. , 2012 , “ Runs on Money Market Mutual Funds, ” Working Paper , University of Maryland .

This paper is written for a forthcoming book, Financial Crises: Causes, Consequences, and Policy Responses , edited by Stijn Claessens, M. Ayhan Kose, Luc Laeven, and Fabián Valencia, to be published by the International Monetary Fund. We thank Ezgi Ozturk for outstanding research assistance.

For further reading on financial crises, the starting point is the authoritative study by Reinhart and Rogoff (2009). Classical references are Minsky (1975) and Kindleberger (1976). See IMF (1998), Eichengreen (2002) , Tirole (2002) , Allen and Gale (2007) , Allen, Babus, Carletti (2009) , Allen (2009), and Gorton (2012) for reviews on causes and consequences of financial crises.

Related are such concepts as “reflexivity” (Soros, 1987), “irrational exuberance” (Greenspan, 1996), and “collective cognition” ( De La Torre and Ize, 2011 ).

Wen and Wang (2012) argue that systemic risk, commonly perceived changes in the bubble’s probability of bursting, can produce asset price movements many times more volatile than the economy’s fundamentals and generate boom-bust cycles in the context of a DSGE model.

In Rajan’s (2005) “alpha-seeking” argument, firms, asset managers, and traders take more risk to improve returns, with private rewards in the short-run. See Gorton and He (2000) and Dell’Ariccia and Marquez (2000) for theories linking credit booms to the quality of lending standards and competition.

Models include Miller (1977) , Harrison and Kreps (1978) , Chen, Hong and Stein (2002) , Scheinkman and Xiong (2003) , and Hong, Scheinkman and Xiong (2007).

Empirical studies include Abreu and Brunnermeier (2003) , Diether, Malloy and Scherbina (2002) , Lamont and Thaler (2003) , Ofek and Richardson (2003) , and Shleifer and Vishny (1997) .

For example, stocks of small firms get higher rates of return than other stocks do, even after adjusting for risk, liquidity and other factors. Spreads on lower-rated corporate bonds appear to have a relatively larger compensation for default risk than higher-rated bonds do. Mutual funds whose assets cannot be liquidated when investors sell the funds (so called closed-end funds) can trade at prices different those implied by the intrinsic value of their assets.

For example, firms tend to issue new stocks when prices (and firm profitability) are high and markets’ reaction to initial public offerings can be “hot” or “cold.” Both contradict the assumption that firms seek external financing only when they need to (due to lack of internal funds while having good growth opportunities). Many individual investors also appear to diversify their assets insufficiently (or naively) and rebalance their portfolio too infrequently. At the same time, some investors respond too much to price movements, and sell winners too early and hold on to losers too long. These patterns have been “explained” by various behavioral factors.

For reviews of factors associated with the onset of credit booms, see further Mendoza and Terrones ( 2008 and 2012 ), Magud, Reinhart, and Vesperoni (2012) , and Dell’Ariccia and others (2013) .

However, whether and how monetary policy affects risk taking, and thereby asset prices and leverage, remains a subject of further research (see De Nicolo and others (2010) for recent analysis and review). The extent of bank capitalization appears to be an important factor as it affects incentives: when facing a lower interest rate, a well-capitalized bank decreases its monitoring and takes more risk, while a highly levered, low capitalized bank does the opposite (see further Dell’Ariccia, Laeven and Marquez (2010) ).

Some used to be sanguine on the costs of busts in credit and asset markets. Until the most recent crisis, for example, some appeared to be sanguine on the economic cost of bubbles. For example, Roger W. Ferguson, then Vice Chairman of the Federal Reserve Board, argued in January 2005 that “recessions that follow swings in asset prices are not necessarily longer, deeper, and associated with a greater fall in output and investment than other recessions…” There are also theories in which even fully irrational asset bubbles are not necessarily harmful or could even be beneficial (Kocherlakota, 2009). Bubbles can allow for a store of value (“collateral”) and thereby enhance overall financial intermediation through facilitating exchanges, and thereby improve overall economic performance. As such, the presence of bubbles per se , whether rational or irrational, need not necessarily be a cause for concern.

Earlier versions of the canonical crisis model were Salant and Henderson (1978) and Salant (1983) .

Hallwood and MacDonald (2000) provide a detailed summary of the first and second generation models and consider their extensions to different contexts. Krugman (1999) , in an attempt to explain the Asian financial crisis, also provides a similar mechanism operating through firms’ balance sheets, and investment is a function of net worth.

Ranciere and Tornell (2011) model how financial innovations can allow institutions to maximize a systemic bailout guarantee, and report evidence supporting this mechanism in the context of the 2007 US financial crisis.

Deposit insurance, first introduced in the U.S. in 1933, was adopted following the World War II by many advanced countries, and has since employed by developing countries ( Demirguc-Kunt, Kane and Laeven, 2008 ). While deposit insurance can reduce the risk of bank runs, it can have severe negative side effects, including increased moral hazard, leading to more risk taking.

Failures in regulation and supervision remain the most mentioned cause for crises, despite significant upgrading of regulations, supervisory capacity and expertise over decades. For analysis how weaknesses in regulation and supervision contributed to the recent crisis, see Čihák, DemirgüçKunt, Martínez Pería and Mohseni-Cheraghlou (2012) . Analysis suggests though that the design of regulation matters for the risk of financial distress. Barth, Caprio and Levine ( 2006 ; 2012 ), for example, suggest not relying solely on regulation and supervision. Rather, they advocate, inter alia, for an active but carefully balanced mix of market discipline and official regulation and supervision. This should all be supported by institutional infrastructure that protects property rights, allows for competition, including engagement with global finance, and ensures adequate information. The wider threats to financial stability, including those arising from political economy and corruption, should be kept at bay.

Specifically, there was an increase in real estate prices in many markets around the world, paralleled by a run-up in other asset prices, especially in equity. Reinhart and Rogoff (2008) demonstrate that the appreciation of equity and house prices in the U.S. before the crisis was even more dramatic than appreciations experienced before the “Big Five” post-war debt crises. As the global crisis unfolded, those countries that had experienced the greatest increases in equity and house prices during the boom found themselves most vulnerable (see Feldstein, 2009 , and Teslik, 2009). Unfortunately, the similarity in crises patterns was, as is often the case, only recognized ex-post.

Dating does not of course establish causes, including whether the event was a rational outcome to some other “cause” (e.g., a crash in an asset price may be rational in response to a real shock or not).

Their comprehensive analysis also includes the 1258-1799 period during which the principal means of exchange was metallic coins. During this earlier era, instead of modern inflation and currency crises, there were a number of episodes of currency debasements which were associated with a reduction in the metallic content of coins in circulation in excess of 5 percent. They also consider the introduction of a brand new currency replacing a much-depreciated earlier currency in circulation as another form of currency debasement, which has still been practiced in the modern era.

Bordo and Haubrich (2012) and Howard, Martin and Wilson (2011) also argue that recoveries following financial crises do not appear to be different than typical recoveries.

These loss numbers rely on an estimated trend growth, typically proxied by the trend in GDP growth up to the year preceding the crisis. They can overstate output losses, however, as the economy could have experienced a growth boom before the crisis or been on an unsustainable growth path.

Mexico’s default in August 1982 marked the beginning of the crisis and the region’s decade long stagnation (i.e., the lost decade). A number of Latin American countries, including Argentina, Mexico and Venezuela in 1982, and Brazil and Chile in 1983, experienced debt crises during the period.

Reinhart and Rogoff (2011) provide further statistical analysis of the linkages between debt and banking crises.

Of course, this and other analyses can suffer from reverse causality. That is, private agents see events that lead them to predict future drops in a country’s output, and as a result, these agents pull their capital from the country. In this view, anticipated output drops drive sudden stops, rather than the reverse. While possible and reasonable, is hard to document or refute quantitatively this view.

The fact that the economy recovers without credit growth and increases in asset prices reflects a combination of factors. First, consumption is typically the key driver of recoveries. In particular, private consumption is often the most important contributor to output growth during recoveries. Investment (especially non-residential) recovers only with a lag, with the contribution of fixed investment growth to recovery often relatively small. Second, firms and households may be able to get external financing from sources other than commercial banks that are adversely affected by the crisis. These sources are not captured in the aggregate credit series most studies focus on. Thirdly, there can be a switch from more to less credit-intensive sectors in such a way that overall credit does not expand, yet, because of productivity gains, output increases. The aggregate data employed in many studies hide such reallocations of credit across sectors, including between corporations and households that vary in their “credit-intensity.”

The slow movement of the financial system from stability to crisis is something for which Hyman Minsky is best known, and the phrase “Minsky moment” – the sudden occurrence of an open financial crisis – refers to this aspect of his work, see Minsky (1992).

Babecky and others (2012) present a detailed review of the empirical studies of early warning models.

Crespo-Cuaresma and Slacik (2009) report that most of the early warning variables for currency crises in the literature are quite fragile whereas the extent of real exchange rate misalignment and financial market indicators appear to be relatively robust determinants of crisis in certain contexts.

Shin (2013) compares the predictive power from price-based measures (CDS and other spreads, implied volatility, Value-at-Risk, etc.), the gap of credit-to-GDP ratio from a trend, and monetary aggregates and other bank liability aggregates, and shows that the last group has the most predictive power.

Same Series

• Booms, Crises, and Recoveries: A New Paradigm of the Business Cycle and its Policy Implications
• A Model to Assess the Probabilities of Growth, Fiscal, and Financial Crises
• External Imbalances and Financial Crises
• Regulatory Cycles: Revisiting the Political Economy of Financial Crises
• Commodity Price Movements and Banking Crises
• The Corporate Sector Dynamics of Systemic Financial Crises
• IMF Lending and Banking Crises
• Trade and Financial Contagion in Currency Crises
• Fiscal Crises
• Systemic Banking Crises Database: An Update

Other IMF Content

• Chapter 1. Financial Crises Explanations, Types, and Implications
• Analytics of Systemic Crises and the Role of Global Financial Safety Nets
• Q&A: Seven Questions on Financial Crises: Perspectives from the Frontier of Research
• Financial Cycles – Early Warning Indicators of Banking Crises?
• Part I: Introduction and Description of Financial Crises
• Part III: Short-Term Effects: Crises, Recessions, and Recoveries
• Sovereign Debt Repatriation During Crises
• Part V: Policy Measures to Prevent Booms, Mitigate Busts, and Avoid Financial Crises
• Policies for Macrofinancial Stability: How to Deal with Credit Booms
• IntroductionPart I. Anatomy of the North Atlantic Financial CrisisPart II. Misdiagnosing the North Atlantic EconomyPart III. Completing the CureFinal Thoughts

Other Publishers

Asian development bank.

• Financial Integration and Macrofinancial Linkages in Asia: Crises, Responses, and Policy Considerations
• Policies to Optimize the Performance of Credit Guarantee Schemes During Financial Crises
• Three Decades of International Financial Crises: What Have We Learned and What Still Needs to be Done?
• Financial Digitalization and Its Implications for ASEAN+3 Regional Financial Stability
• Local Currency Collateral for Cross-Border Financial Transactions: Policy Recommendations from the Cross-Border Settlement Infrastructure Forum

Inter-American Development Bank

• Banking Crises and Financial Integration
• Coping with Financial Crises: Latin American Answers to European Questions
• Financial Crises and Macro-Prudential Policies
• Financial Crises in Japan and Latin America
• Foreign Bank Behavior during Financial Crises
• Equilibrium Unemployment During Financial Crises
• Multilateral Safety Nets for Financial Crises
• Maturity Mismatch and Financial Crises: Evidence from Emerging Market Corporations
• The Roots of Banking Crises: The Macroeconomic Context
• Credit Frictions and "Sudden Stop" in Small Open Economies: An Equilibrium Business Cycle Framework for Emerging Markets Crises

International Labour Organization

• Financial crises, deflation and trade union responses: What are the lessons?: International Journal of Labour Research, IJLR, Vol 2, No 1/2010

The World Bank

• Debt and Financial Crises
• Learning from Financial Crises
• Global Corporate Debt during Crises: Implications of Switching Borrowing Across Markets
• Do Phoenix Miracles Exist?: Firm-Level Evidence from Financial Crises
• Resolving systemic financial crises: policies and institutions
• Financial Crises, Financial Dependence, and Industry Growth
• International aid and financial crises in donor countries
• Crises, capital controls, and financial integration
• Financial policies and the prevention of financial crises in emerging market economies
• Share on facebook Share on linkedin Share on twitter

Table of Contents

• View raw image
• Download Powerpoint Slide

International Monetary Fund Copyright © 2010-2021. All Rights Reserved.

• [185.66.14.236]
• 185.66.14.236

Character limit 500 /500

Financial Crises and Economic Activity

We study the output costs of 40 systemic banking crises since 1980. Most, but not all, crises in our sample coincide with a sharp contraction in output from which it took several years to recover. Our main findings are as follows. First, the current financial crisis is unlike any others in terms of a wide range of economic factors. Second, the output losses of past banking crises were higher when they were accompanied by a currency crisis or when growth was low at the onset of the crisis. When accompanied by a sovereign debt default, a systemic banking crisis was less costly. And, third, there is a tendency for systemic banking crises to have lasting negative output effects.

This paper was prepared for "Financial Stability and Macroeconomic Policy," a symposium sponsored by the Federal Reserve Bank of Kansas City, at Jackson Hole, Wyoming, on August 20-22,2009. We would like to thank participants at the Symposium, our discussant Mark Gertler, and Roberto Blanco.for useful comments. Jimmy Shek and Clara Garcia provided excellent research assistance, and Luc Laeven and Fabian Valencia kindly shared their database of crises. The views expressed in this paper are those of the authors and not necessarily those of the BIS. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research.

MARC RIS BibTeΧ

Download Citation Data

Published Versions

More from nber.

In addition to working papers , the NBER disseminates affiliates’ latest findings through a range of free periodicals — the NBER Reporter , the NBER Digest , the Bulletin on Retirement and Disability , the Bulletin on Health , and the Bulletin on Entrepreneurship  — as well as online conference reports , video lectures , and interviews .