financial crisis research report

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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.

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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

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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.

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The Financial Crisis at 10: Will We Ever Recover?

Regis Barnichon, Christian Matthes, and Alexander Ziegenbein

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FRBSF Economic Letter 2018-19 | August 13, 2018

A decade after the last financial crisis and recession, the U.S. economy remains significantly smaller than it should be based on its pre-crisis growth trend. One possible reason lies in the large losses in the economy’s productive capacity following the financial crisis. The size of those losses suggests that the level of output is unlikely to revert to its pre-crisis trend level. This represents a lifetime present-value income loss of about $70,000 for every American.

The size of the U.S. economy, as measured by GDP adjusted for inflation, is well below the level implied by the growth rates that prevailed before the financial crisis and Great Recession a decade ago. The United States is not alone; the United Kingdom and European economies also remain far below the levels implied by their pre-crisis trends (Barnichon, Matthes, and Ziegenbein 2018). Studies of previous episodes of financial stress around the globe point to similarly large and persistent output losses. For instance, Romer and Romer (2017) study a panel of countries in the Organisation for Economic Co-operation and Development and find that gross domestic product is typically about 9 percentage points lower five years after an extreme financial crisis.

If history is a reliable guide, academics and policymakers are rightfully worried that output might not revert to the level implied by its pre-crisis trend (black dashed line in Figure 1). The magnitude of the shortfall is evident in the figure. It displays the series of downward revisions that the Congressional Budget Office (CBO) made to its estimate of potential output—the long-run level of output that is expected to prevail once the transitory effects of cyclical factors have dissipated. The revisions over the past 10 years imply that actual U.S. GDP (solid blue line) in 2017 converged on a new potential level (dashed green line) that was about 12 percentage points below the level implied by its pre-crisis trend (based on GDP data released prior to the Bureau of Economic Analysis’ comprehensive update in July 2018). Revisions to potential GDP by other forecasters, including the San Francisco Fed, yield similar shortfalls in potential output.

Figure 1 U.S. real GDP before and after 2007–08 financial crisis

Note: Dashed lines show potential GDP estimated by the CBO in different years, measured in natural log terms, with the 2007 estimate of potential normalized to zero in 1998, such that subsequent changes are measured in fractional terms. Gray bars reflect NBER recession dates.

The CBO attributes a large fraction of the shortfall to its reassessment of trends that were under way before the recession (CBO 2014). By contrast, this Letter describes our findings in a recent paper (Barnichon, Matthes, and Ziegenbein 2018) that explores to what extent the financial crisis caused some of the shortfall in potential output. We find that a large fraction of the gap between current GDP and its pre-crisis trend level is associated with the 2007–08 financial crisis, and conclude that GDP is unlikely to revert to the level implied by its trend before the crisis.

Financial conditions and the economy: Pain but no gain?

Many studies have investigated the impact of financial market disruptions on economic activity, but the evidence is mixed. On the one hand, studies of earlier financial crises find that financial market disruptions are generally followed by a large and persistent decline in output (for example, Romer and Romer 2017). On the other hand, studies that use surprise movements in financial conditions to explore whether the cause can be traced back to financial disruptions report mild and transitory effects on economic activity (for example, Gilchrist and Zakrajsek 2012).

One way to reconcile these conflicting views of the effects of financial markets on the economy is to acknowledge the possibility that the relationship is asymmetric. When the economy is doing well, an adverse financial shock—a disturbance that limits the ability of the financial sector to handle risk—is likely to restrain economic activity by preventing some firms from financing profitable investment opportunities. But the converse is not necessarily true: When the economy is doing poorly or in a recession, favorable financial conditions may not necessarily stimulate economic activity if there are no investment opportunities. As such, financial conditions may cool a hot economy but might not heat up a cool one.

To accommodate both views of the link between financial markets and the economy, we construct a statistical model that is flexible enough to capture these asymmetries. Although such asymmetries are often discussed in theoretical work (for example, Brunnermeier and Sannikov 2014), previous empirical studies have not explicitly accounted for them. By contrast, our empirical model allows for the possibility that financial market shocks have asymmetric effects. Consistent with theory, we find that an easing of financial conditions has little effect on economic activity. However, an adverse financial shock has large effects on economic activity. Because such losses are very persistent, they can have dramatic effects on societal welfare and important implications for policy.

U.S. GDP since the financial crisis

Our model combines information on economic conditions, notably GDP, with information on financial market conditions. This is measured with the excess bond premium (EBP), which Gilchrist and Zakrajsek (2012) proposed as a quantitative measure of the risk-bearing capacity of the financial sector. The EBP measures how much more corporations have to pay to borrow in the bond market relative to the government, net of compensation for the risk that the corporation will default on its obligations. This variable is therefore a good measure of private credit availability.

Using history as a guide, our model captures how financial conditions and GDP typically interact over the business cycle (see Barnichon et al. 2018 for complete details). Since the U.S. economy has experienced many episodes of mild financial market disruptions, the model can use these episodes to calculate how future changes in financing conditions are likely to affect the economy. Based on this idea, we then use our model to assess how much of the gap between current GDP and its pre-crisis trend level is explained by the financial crisis. To do this, we develop a scenario to calculate how GDP would have fared without the large financial market disruptions of 2007–08. Figure 2 presents our results.

Figure 2 The effects of the 2007–08 financial crisis: Actual vs. scenario estimates without crisis

Note: Potential GDP in panel B represents 2007 estimate from Congressional Budget Office. GDP is measured on a log scale so that changes in GDP can be read as percent changes in GDP. EBP estimate is from Gilchrist and Zakrajsek (2012).

Panel A of Figure 2 shows the actual path (blue line) and the path from our scenario (red line) for the EBP, our measure of credit conditions. In our scenario without major financial stresses in 2007–08, the EBP increases only mildly, driven by its normal response to a deterioration in economic conditions. Indeed, during recessions, the overall appetite for risk normally decreases as the financial sector becomes more risk-averse or simply has fewer funds available to lend.

Panel B of Figure 2 shows how U.S. real GDP behaves in the actual data (blue line) and in our scenario with no financial disruptions in 2007–08 (red line). The dark red and light red bands around the red line correspond to the 68% and 90% confidence intervals around our estimates, that is, two different ranges of their statistical reliability. Importantly, for this exercise we estimate our statistical model using data from 1973 up to 2006 only, thereby excluding any information from the most recent financial crisis that could contaminate our estimates. As a result, the predicted path of GDP is explained only by the typical path of output following financial market disruptions in the pre-crisis 1973–2006 period.

Without the large adverse financial shocks experienced in 2007 and 2008, the behavior of GDP would have been very different. It would most likely resemble the less severe 1991 recession, with GDP declining by only 1.5% and reverting to close to its pre-crisis trend level in a few years. This behavior is in stark contrast to actual GDP, which has not reverted to its pre-crisis trend level.

In our statistical experiment, the mild recession would imply that, by the end of 2017, the gap between output and potential output from the 2007 CBO estimate (dashed black line) would only be about 5 percentage points instead of the 12 percentage points observed today. This means that, according to our estimates, the 2007–08 financial crisis persistently lowered output by roughly 7 percentage points. This is a large number: In dollar terms, it represents a lifetime income loss in present-discounted value terms of about $70,000 for every American. This simple calculation takes the reading of GDP per person in 2007 (approximately $50,000) and assumes an annual discount rate of 5%.

We do not yet have a good grasp on the mechanisms through which financial market disruptions can have such persistent effects on output. One possibility is simply the highly peculiar behavior of economies with financial frictions. As shown by Brunnermeier and Sannikov (2014), with financial frictions, a large adverse shock can take the economy away from its normal growth path for a very long but finite time. Another possibility is that episodes of financial distress could force businesses to cut research expenditures or could prevent high-growth potential start-ups from emerging (see, for example, Sedlacek and Sterk 2017), which could permanently affect the economy’s future productive capacity.

In this Letter , we evaluate the effect of the 2007–08 financial crisis on U.S. output 10 years later. We find that a large fraction of the gap between current output and its pre-crisis trend is associated with the large 2007–08 financial shocks. Our estimates suggest that the economy is unlikely to regain this large output loss and GDP is unlikely to revert to its previous trend level. Financial market disruptions can have large costs in terms of societal welfare by causing persistent losses in the level of GDP. This suggests that finding ways to prevent or contain future financial crises is an important research and policy priority.

Regis Barnichon is a research advisor in the Economic Research Department of the Federal Reserve Bank of San Francisco.

Christian Matthes is a senior economist in the Research Department of the Federal Reserve Bank of Richmond.

Alexander Ziegenbein is an assistant professor of economics at the University of Vienna.

Barnichon, Regis, Christian Matthes, and Alexander Ziegenbein. 2018. “Are the Effects of Financial Market Disruptions Big or Small?” Working Paper.

Brunnermeier, Markus, and Yuliy Sannikov. 2014. “A Macroeconomic Model with a Financial Sector.” American Economic Review 104(2), pp. 379–421.

Congressional Budget Office. 2014. “Revisions to CBO’s Projection of Potential Output Since 2007.” Report, February. 

Gilchrist, Simon, and Egon Zakrajsek. 2012. “Credit Spreads and Business Cycle Fluctuations.” American Economic Review 102(4), pp. 1,692–1,720.

Romer, Christina, and David Romer. 2017. “New Evidence on the Aftermath of Financial Crises in Advanced Countries.” American Economic Review 107(10), pp. 3,072–3,118.

Sedlacek, Petr, and Vincent Sterk. 2017. “The Growth Potential of Startups over the Business Cycle.” American Economic Review 107(10), pp. 3,182–3,210.

Opinions expressed in FRBSF Economic Letter do not necessarily reflect the views of the management of the Federal Reserve Bank of San Francisco or of the Board of Governors of the Federal Reserve System. This publication is edited by Anita Todd and Karen Barnes. Permission to reprint portions of articles or whole articles must be obtained in writing. Please send editorial comments and requests for reprint permission to [email protected]

• The Financial Crisis: Lessons for the Next One

The massive and multifaceted policy responses to the financial crisis and Great Recession — ranging from traditional fiscal stimulus to tools that policymakers invented on the fly — dramatically reduced the severity and length of the meltdown that began in 2008; its effects on jobs, unemployment, and budget deficits; and its lasting impact on today’s economy.

Without the policy responses of late 2008 and early 2009, we estimate that:

• The peak-to-trough decline in real gross domestic product (GDP), which was barely over 4%, would have been close to a stunning 14%;
• The economy would have contracted for more than three years, more than twice as long as it did;
• More than 17 million jobs would have been lost, about twice the actual number.
• Unemployment would have peaked at just under 16%, rather than the actual 10%;
• The budget deficit would have grown to more than 20 percent of GDP, about double its actual peak of 10 percent, topping off at $2.8 trillion in fiscal 2011.
• Today’s economy might be far weaker than it is — with real GDP in the second quarter of 2015 about $800 billion lower than its actual level, 3.6 million fewer jobs, and unemployment at a still-dizzying 7.6%.

We estimate that, due to the fiscal and financial responses of policymakers (the latter of which includes the Federal Reserve), real GDP was 16.3% higher in 2011 than it would have been. Unemployment was almost seven percentage points lower that year than it would have been, with about 10 million more jobs.

To be sure, while some aspects of the policy responses worked splendidly, others fell far short of hopes. Many policy responses were controversial at the time and remain so in retrospect. Indeed, certain financial responses were deeply unpopular, like the bank bailouts in the Troubled Asset Relief Program (TARP). Nevertheless, these unpopular responses had a larger combined impact on growth and jobs than the fiscal interventions. All told, the policy responses — the 2009 Recovery Act, financial interventions, Federal Reserve initiatives, auto rescue, and more — were a resounding success.

Our findings have important implications for how policymakers should respond to the next financial crisis, which will inevitably occur at some point because crises are an inherent part of our financial system. As explained in greater detail in Section 5:

• It is essential that policymakers employ “macroprudential tools” (oversight of financial markets) before the next financial crisis to avoid or minimize asset bubbles and the increased leverage that are the fodder of financial catastrophes.
• When financial panics do come, regulators should be as consistent as possible in their responses to troubled financial institutions, ensuring that creditors know where their investments stand and thus don’t run to dump them when good times give way to bad.
• Policymakers should not respond to every financial event, but they should respond aggressively to potential crises — and the greater the uncertainty, the more policymakers should err on the side of a bigger response.
• Policymakers should recognize that the first step in fighting a crisis is to stabilize the financial system because without credit, the real economy will suffocate regardless of almost any other policy response.
• To minimize moral hazard, bailouts of companies should be avoided. If they are unavoidable, shareholders should take whatever losses the market doles out and creditors should be heavily penalized. Furthermore, taxpayers should ultimately be made financially whole and better communication with the public should be considered an integral part of any bailout operation.
• Because fiscal and monetary policy interactions are large, policymakers should use a “two-handed” approach (monetary and fiscal) to fight recessions — and, if possible, they should select specific monetary and fiscal tools that reinforce each other.
• Because conventional monetary policy — e.g., lowering the overnight interest rate — may be insufficient to forestall or cure a severe recession, policymakers should be open to supplementing conventional monetary policy with unconventional monetary policies, such as the Federal Reserve’s quantitative easing (QE) program of large-scale financial asset purchases, especially once short-term nominal interest rates approach zero.
• Discretionary fiscal policy, which has been a standard way to fight recessions since the Great Depression, remains an effective way to do so, and the size of the stimulus should be proportionate to the magnitude of the expected decline in economic activity.
• Policymakers should not move fiscal policy from stimulus to austerity until the financial system is clearly stable and the economy is enjoying self-sustaining growth.

The worldwide financial crisis and global recession of 2007-2009 were the worst since the 1930s. With luck, we will not see their likes again for many decades. But we will see a variety of financial crises and recessions, and we should be better prepared for them than we were in 2007. That’s why we examined the policy responses to this most recent crisis closely, and why we wrote this paper.

We provide details of the methods we used to generate the findings summarized above. But generally speaking, we use the Moody’s Analytics model of the macroeconomy to simulate how growth, jobs, unemployment, and other variables might have evolved in the absence of the policy. We then compare this simulated path to what actually happened, identifying the differences as the impacts of the policy. That’s a standard approach, one that, for example, the Congressional Budget Office used to evaluate the Recovery Act (whose findings, as we show, are similar to our own).

Table 1 shows the estimated impacts of the full panoply of policy responses, along with the impacts of two specific sub-categories: fiscal stimulus and the financial response. The columns show how much the policies boosted real GDP and jobs, and how much they reduced unemployment, in the years 2009-2012. (Details in the paper provide quarterly data through the second quarter of 2015 and include impacts on inflation as well.)

Sources: BEA, BLS, Moody’s Analytics

The economic expansion would have taken much longer without the massive and unprecedented responses of policymakers. Policymakers clearly made mistakes leading up to the financial crisis and Great Recession. They failed to prevent the housing and bond bubbles from inflating, under-regulated the financial system, and erred by treating the prospective failures of Bear Stearns and Lehman Brothers so differently. Not every one of their monetary, financial, and fiscal policies after the day Lehman Brothers filed for bankruptcy was effective, and the policymaking process was messy at times. But, as a whole, the policy response was a huge success. Without it, we might have experienced something approaching Great Depression 2.0.

Today, the economic expansion is more than six years old — longer than most expansions — and we’re approaching full employment. It’s been a long time coming, but it would have taken much longer without the timely, massive, and unprecedented responses of policymakers.

In July of 2010, the two of us published a comprehensive analysis of the panoply of policy interventions that, we argued, successfully mitigated the Great Recession and put the U.S. economy on the road to recovery. [1] The estimated impacts were significant. For example, we estimated that all the policies together reduced the peak-to-trough decline in real GDP by about 70% and held the maximum unemployment rate to 10% rather than letting it top out near 16%.

To this day, that analysis — in which we used the Moody’s Analytics U.S. Macro Model extensively [2] — remains the only attempt we know of to assess the quantitative impacts of the entire package of policies (or at least most of them) promulgated by the Federal Reserve, the Treasury Department, the White House and Congress, and others. Now, with the benefit of a newly revised macro model, five more years of data, and a variety of published studies of individual pieces of policy, this paper is the second.

But it’s more than that:

• Section 1 provides a very brief description of the origins of the cataclysm that hit us in 2007-2008. [3]
• Section 2 explains the numerous and sometimes creative policy interventions — fiscal, monetary, and financial — that policymakers deployed to limit the financial damage and mitigate the recession.
• Section 3 uses the Moody’s model to assess the impacts of these policies on major macro variables, both as a whole and in parts. (Sections 2 and 3, which are the heart of this paper, replicate and extend our 2010 paper, and we find that our original estimates hold up well.)
• Section 4 addresses some of the major criticisms of the policies and briefly reviews some criticisms of our method of assessing their effects and some other studies — not based on macro econometric models — that have evaluated the effectiveness of some of the same policies.
• Finally, Section 5 seeks to draw lessons for the future. While it seems most unlikely that history will repeat itself, Mark Twain has reminded us that it often rhymes.

Section 1: Back to the Thirties?: What Hit Us

The U.S. and quite a few other countries experienced massive asset-price bubbles during the 2000s. Two kinds, mainly. The first was the well-known house-price bubble, which began in the early 2000s in the U.S. and started to burst in 2006 or 2007 (depending on which price index you use). The second was a global bubble in the prices of fixed-income securities—a “bond bubble,” for short—or, what amounts to the same thing, the compression of risk premia to inexplicably low levels as investors either ignored or underpriced risk. As one stunning and poignant example, consider that the spread between Greek and German 10-year sovereign bond yields was razor-thin—below 35 basis points—for years up until just before the crisis hit.

When the housing and bond bubbles burst at about the same time, asset holders suffered huge capital losses. (Stock markets also swooned.) Worse yet, many investors had leveraged their positions, in some cases heavily, thereby magnifying the losses. Mountains of derivatives (MBS, CDOs, CDS, etc.), some of them complex and opaque, had been built upon the shaky foundations of dubious mortgages, inflated house prices, and compressed risk spreads—often creating huge amounts of additional leverage.

This complex, opaque, overleveraged and under-regulated house of cards began to shake, gently at first, in July 2007 when Bear Stearns told investors that there was “effectively no value left” in one of its mortgage-related funds. Market jitters got even worse in August, when BNP Paribas halted withdrawals on three funds based on U.S. subprime mortgages, telling its investors that “the complete evaporation of liquidity” in these markets “made it impossible to value [these] assets fairly.” HSBC quickly followed, closing its U.S. subprime mortgage lending business in September 2007. [4]

The financial system was under mounting pressure thereafter, with markets experiencing a frightening roller-coaster ride, moving up and down as the ebb and flow of news varied from merely bad to truly horrible. But the world’s financial system might not have collapsed as it subsequently did were it not for the inconsistent handling of a pair of stumbling investment banks: Bear Stearns and Lehman Brothers.

The stock- and bondholders of these two institutions were treated very differently by policymakers working to quell the gathering panic. Bear’s shareholders lost most—but not quite all—of their equity when JP Morgan Chase took it over, but Bear’s creditors were made whole by JP Morgan with help from the Fed. Almost six months later, shareholders and creditors of mortgage giants Fannie Mae and Freddie Mac received similar treatments. But on September 15, 2008, Lehman was sent to bankruptcy court, and everything fell apart. Lehman shareholders and bondholders were wiped out, thereby “solving” what economists call the moral hazard problem, an economic distortion that arises when a person or firm believes that part of its risk will be covered by some third party. After Lehman, creditors in other financial institutions no longer knew whether the U.S. government stood behind the financial system. Interbank lending stopped, risk spreads soared, and the worldwide financial crisis was on. Within days, the U.S. government, which had decided not to “bail out” Lehman, found itself bailing out or otherwise saving AIG, Bank of America, Citigroup, Goldman Sachs, Morgan Stanley, money market mutual funds, the commercial paper market, and much else.

What happened in the financial markets did not stay in the financial markets. The U.S. economy had been sputtering but not contracting before the Lehman bankruptcy. [5] But after Lehman, it began to fall at a frightening pace: Real GDP declined by an annualized 8.2% in the fourth quarter of 2008 and 5.4% in the first quarter of 2009. Around that time, many people who are not prone to hysteria talked openly about the prospects of “Great Depression 2.0.”

It did not happen, however; and we argue here (as we did in our 2010 paper) that one major reason was the extraordinary policy response from the Federal Reserve, the Treasury, the Federal Deposit Insurance Corp., the Federal Housing Administration, and Congress. [6] The list of policy initiatives that we present in Section 3 is long and complex. But a handful stand out. We believe, and offer supporting evidence below, that the economy would have fallen much further were it not for aggressive actions taken by the Fed and FDIC to shore up liquidity in the financial system early in the crises in late 2008: the Troubled Asset Relief Program, or TARP, passed in early October 2008; the bank stress tests, or SCAP, announced in February 2009 and completed in May 2009; the large fiscal stimulus known as the American Recovery and Reinvestment Act, passed in mid-February 2009; and the unprecedented easing of monetary policy that included near-zero short-term interest rates, which continue today, and several rounds of quantitative easing, the last of which ended in late 2014.

These policies, each one complex and controversial, led, we believe, to a surprising result: Even though the U.S. was at the epicenter of the financial crisis, we experienced one of the milder recessions in the world. For example, the peak-to-trough decline in real GDP in the U.S. was only 4.1%, compared with 6.9% in Germany (which had no housing bubble) and 6% in the U.K. (which did). Even in Canada, where there was neither a housing bubble nor a homegrown financial crisis, the GDP decline matched our own. Most other countries fared worse.

Recovery from the recession has been another matter, however. There the U.S. has less to brag about. In the six years since the official recession trough in the second quarter of 2009, U.S. GDP growth has averaged a mediocre 2.1% per annum. Only miserable productivity performance turned this sluggish GDP growth into millions of new jobs and a 4.7-percentage point drop in the unemployment rate since its peak in April 2010.

Part of the reason for the weak recovery, we will argue in Section 4, is that fiscal policy turned notably contractionary beginning in 2011. In addition, political brinkmanship that led to a government shutdown in October 2013 and a near default on the Treasury’s debt payments created enormous uncertainties in an already-uncertain time. That weighed heavily on the collective psyche and presumably on business expansion plans. Even today, the long shadow of the Great Recession still constricts the flow of residential mortgage credit, particularly to first-time homebuyers, slowing the recovery from the housing bust.

Despite the recovery’s disappointing performance, it has been much better than that of nearly all other countries that have suffered financial crises over the years. Japan is still trying to dig out from its financial implosion of a quarter century ago. History shows that making it back from a financial crisis is very difficult, [7] but the U.S. economy in recent years has done better than most.

How the U.S. economy fared on the way down and on the way back up are matters of historical record. But parsing out the portions attributable to policy actions—whether in cushioning the downturn or supporting the recovery—requires a counterfactual: How would the economy have performed in the absence of some or all of the policy interventions? To answer questions like these, one needs a model; and in Section 4 we rely mostly on the Moody’s Analytics model.

Section 2: The Policy Response: Massive and Multifaceted

The policy responses to the financial crisis and the Great Recession were massive and multifaceted (see Table 2). Not only did they include the aggressive use of standard monetary and fiscal policy tools, but new tools were invented and implemented on the fly in late 2008 and early 2009. Some aspects of the response worked splendidly, while others fell far short of hopes, and many were controversial—both in real time and even in retrospect. In total, however, we firmly believe that the policies must be judged a success.

* Includes foreign-denominated debt ** Net portfolio holdings *** Excludes AMT patch **** Assumes fair value accounting Sources: Federal Reserve, Treasury, FDIC, FHA, Moody’s Analytics

The essential first steps were a series of emergency rescue operations of the financial system—something that is never popular. The Federal Reserve flooded the system with liquidity, throwing a lifeline first to banks, then also to money-market funds, commercial paper issuers, broker-dealers, insurance companies, and investment banks. These initial steps were critical because financial institutions had all but stopped lending to one another, fearful of being dragged over the brink by another failing institution—a fear that was not unreasonable after Lehman Brothers collapsed. The FDIC acted by raising insurance limits on bank deposits to quell what appeared to be silent runs at some major banks, [8] and by guaranteeing debt issued by depository institutions, which had been all but locked out of the bond market. [9] It seems fair to say that, absent a dire emergency, neither the Fed nor the FDIC would have considered any of these extraordinary measures.

Although the Fed’s efforts were substantial and valiant, they were insufficient. Congress needed to act as well. After much hand-wringing, it did, by establishing a $700 billion bailout fund known as the Troubled Asset Relief Program. Congress initially voted TARP down, but quickly reversed itself after stockholders furiously dumped shares in reaction. The word “TARP” remains political poison to this day. No member of Congress wanted to be known for supporting a bailout of the Wall Street institutions that were at the root of the crisis. But doing so was essential.

In fact, TARP’s real purpose was not to save Wall Street, but to protect Main Street. Yes, many banks were bailed out by receiving capital they desperately needed to survive. But had the banks failed, credit to businesses and households would have dried up, pushing the already-reeling economy deeper into the abyss.

The $700 billion authorized by Congress for TARP was never fully committed, and the ultimate cost to taxpayers will come in closer to $40 billion—far below initial loss estimates. [10] And much of that loss is accounted for by the auto bailout, which was not part of TARP’s original purpose (see Table 3). Taxpayers actually made money on the part of TARP, which was the majority, that was used to bail out the financial system—although, of course, virtually all investors lost money when the financial system imploded. A few small-bank recipients of TARP money were not able to pay it back, but most, including all the large banks, repaid with both interest and capital gains on warrants.

Sources: Federal Reserve, Treasury, FDIC, FHA, Moody’s Analytics

The financial panic was not fully subdued, however, until the biggest financial institutions were forced to recapitalize. In the spring of 2009, regulators demanded that banks figure out how much capital they needed in order to withstand massive losses comparable to those suffered in the Great Depression—the so-called stress tests. Then, if short, the bankers would have to go out and raise that much new equity from private investors. If they failed, they would have to accept capital from the government (using TARP funds) on highly unfavorable terms.

Bankers objected to this exercise loudly at first, since the stress tests were new and complex, and the thought of going hat in hand to investors for more capital was unpalatable. But regulators wisely overruled the banks, and the stress tests worked—probably better than anyone imagined. America’s banks were recapitalized, and both the markets and the bankers themselves were reassured that the system was sound. A few short months after the U.S. financial system had effectively collapsed, it was up and running again. Note that stress-testing requires very little public spending, and hence provides a huge “big bang for the buck.”

Stress-testing has since become a standard part of global financial regulation. When asked what he likes most about financial regulatory reform, former Fed Chairman Ben Bernanke often points to stress-testing. [11] European authorities have also conducted extensive stress tests, and the International Monetary Fund advocates their adoption by all member countries. The largest financial institutions in the world now stress-test their balance sheets and income statements every year; it has become a critical part of risk and capital management.

After getting the financial system back on solid ground, policymakers turned their attention to the faltering economy. The Federal Reserve jettisoned its historic go-slow approach, slashing short-term interest rates virtually to zero by December 2008. The Fed also brought out new monetary tools that had previously existed only in theory. Most notably, it engaged in quantitative easing, or QE, which entailed the purchase of trillions of dollars in Treasury and agency securities (such as mortgage-backed securities issued by government-sponsored enterprises). It also offered market participants a lot more forward guidance—in various forms—than it ever had before.

QE has its downsides, but it substantially lowered long-term interest rates. [12] Within a short time, homebuyers with good jobs and high credit scores could obtain mortgages at record low rates, which helped end the housing crash. QE also significantly lifted stock prices. The Fed had misjudged events leading up to the financial crises, but it committed itself to avoiding the same mistakes afterward. [13]

Away from Wall Street and the banks, the U.S. auto industry posed an especially vexing problem for the Bush and Obama administrations and Congress. U.S. automakers had been losing market share to more efficient foreign producers (including transplants on U.S. soil) for decades. Then the Great Recession hit and rising unemployment and shrinking credit made it much harder for Americans to afford new cars. Vehicle sales collapsed. Profits suffered even more, as the automakers tried desperately to maintain sales volumes by offering aggressive discounts and easier financing terms. By early 2009, GM and Chrysler were careening toward bankruptcy.

Worse, the turmoil in financial markets meant that the crippled auto companies might not find financing to keep their factories running during the months or years of restructuring that a normal bankruptcy would require. The obvious alternative was liquidation. But if Chrysler and GM closed down, other auto-related firms, maybe even Ford, would follow. The list of potential casualties included a vast network of parts suppliers and dealerships all over America. Millions of jobs were at stake, especially in the Midwest and South.

Washington’s bailout of the auto industry was not pretty, and it certainly was not part of the standard playbook of economists who believe in “creative destruction.” But it forestalled something much uglier, and it was essential to the subsequent revival of the industry. [14] By most metrics, it was a success, [15] although it cost taxpayers about $17 billon in TARP money (see Table 3).

Among the biggest and most controversial efforts to end the recession was the Obama administration’s fiscal stimulus. The logic behind fiscal stimulus is straightforward: With businesses and consumers hunkered down, the government steps in by temporarily increasing its own spending and/or cutting taxes to induce households and businesses to spend more. The objective of such a stimulus is to mitigate or end recessions and/or to jump-start or propel a recovery, depending on the timing. Importantly, but often forgotten, a stimulus is not intended to speed up longer-term economic growth. To a first approximation, real GDP five years or so later should be the same with or without stimulus measures.

Using fiscal policy to combat a recession was hardly a novel idea in 2008-2009; it had been part of the response to every recession since World War II, and the size of the stimulus was always tied to the severity of the recession. The amount of the fiscal stimulus used to fight the recession of 2007-2009 was massive, however: equal to almost 10% of GDP, more than half of which came from the American Recovery and Reinvestment Act (see Table 4). But the Great Recession was the worst downturn since 1937.

Sources: CBO, Treasury, Recovery.gov, IRS, Department of Labor, JCT, Council of Economic Advisors, Moody’s Analytics

Several rounds of fiscal stimulus measures were fired at the recession. The first consisted of the tax rebates sent out near the end of the Bush administration. The largest—and most lastingly controversial—was the American Recovery and Reinvestment Act, which passed on a largely party-line vote just weeks after Barack Obama took office. The ARRA provided more than $830 billion in stimulus measures, much of it in the first three years after its passage in February 2009; about three-fourths of this was temporary spending increases, and the other fourth was tax cuts. [16] It worked. The job losses started to abate immediately, [17] and the Great Recession officially ended in June.

The stimulus was far less successful politically, however. Skepticism about its effectiveness was widespread, fueled in part by a serious marketing blunder made by the fledgling Obama administration. In selling the ARRA, also known as the Recovery Act, to a suspicious Congress, the administration argued that the act would prevent the unemployment rate from rising above 8%. [18] In fact, the unemployment rate was already about 8% by the time the administration took office—only nobody knew that. The economy was sinking so rapidly that the data could not keep up. Policymakers planning the stimulus were working with forecasts that severely underestimated how bad things would get, and with data that underestimated how bad things already were. It was a rookie mistake by the new president and his staff, but it handed their opponents a political sledgehammer with which they proceeded, inappropriately but effectively, to bash the stimulus—even claiming that it was somehow a “job killer.”

Policymakers also focused—though not nearly enough, in our view—on the plummeting housing market, which was in a depression , not just a recession. A range of policy steps had been taken, beginning with the Bush administration’s temporary tax break on mortgage debt forgiven in a short sale and with Hope for Homeowners, which was largely wishful thinking.

The Obama administration acted more aggressively, empowering government lenders Fannie Mae, Freddie Mac, and the FHA to fill the hole created by the collapse of private mortgage lending. The FHA’s response was especially forceful. While the credit spigot closed for nearly all borrowers during the financial crisis, it remained open for mortgage borrowers because of the FHA—which was precisely what the agency’s New Deal-era designers had in mind when they set it up. Without a steady flow of credit from the FHA, the housing market might have completely shut down, taking the already-reeling economy with it.

Government policy also succeeded in breaking the vicious deflationary psychology that had gripped the housing market. A series of tax credits for first-time homebuyers, each of which lasted only a few months, gave buyers a compelling reason to act rather than to wait for prices to fall further. Home sales gyrated as the credits were extended, withdrawn, and then extended again—an element of volatility directly attributable to the government. But at least the free fall in home sales and prices stopped.

Probably the least effective of the Obama administration’s policy responses to the housing crash involved mortgage loan modifications and refinancings. Because foreclosure is costly to both homeowners and financial institutions, government officials hoped to persuade banks to change the terms of troubled mortgage loans, lowering either the interest rate or the principal owed, so as to keep homeowners in their homes. Loosening the rules on refinancing so that troubled homeowners could reduce their monthly payments also seemed promising. But these ideas worked better in theory than in practice. The Making Home Affordable Program, introduced by President Obama in mid-February 2009, was designed to push both modifications and refinancing. But it was underfinanced, under-promoted, and not effectively managed. While the program helped some, it fell well short of both expectations and needs.

With housing no longer in free fall and the economy recovering, policymakers turned later in 2009 to the daunting task of financial regulatory reform. The financial system’s catastrophic failure demanded a reworking of the system’s legal and regulatory plumbing. The Dodd-Frank Act, the reform legislation that became law in the summer of 2010 after a tortuous trip through Congress, made a vast number of changes to the financial system. This multifaceted law is not without its flaws, but overall it likely ensures that future financial crises will not be nearly as cataclysmic as the one we just suffered through.

One key reason for this is Dodd-Frank’s clearly defined process for dealing with potential failures of financial institutions that are too big to fail (now called SIFIs, for Systemically Important Financial Institutions). Regulators had been partly confused and partly unable to handle nonbank institutions that threatened to fail in 2008—ranging from Bear Stearns to Fannie and Freddie to Lehman to AIG. A myriad of problems arose in managing those failures and near failures, which allowed the financial shock waves to propagate.

Dodd-Frank does not solve the too-big-to-fail problem; there will always be institutions whose failure would rock the system. But the law does make it more likely that such failures will be more orderly in the future. Requiring big institutions to formulate “living wills”—guiding regulators on how to unwind the firms’ operations if they fail—also seems likely to help.

Importantly, although perhaps less well known, Dodd-Frank also institutionalized the bank stress tests that had so successfully ended the financial turmoil in 2009, thereby further reducing too-big-to-fail risk. The largest and most important financial institutions now must simulate adverse economic scenarios and study the effect on their balance sheets and income statements annually.

Dodd-Frank’s most controversial provision, however, was probably the establishment of the Consumer Financial Protection Bureau. Although critics were right to worry about the added regulatory burden created by this new agency, the CFPB put consumer interests front and center in a way they had not been before. Part of the CFPB’s mission is to ensure that financial products offered to consumers are appropriate to their needs, and that consumers have enough information to adequately evaluate these products. CFPB protections were sorely needed given the sometimes-dizzying complexity of financial services and the woeful state of consumer financial literacy—many homebuyers have a hard time understanding compound interest, never mind Libor and adjustable rate mortgages.

Dodd-Frank is far from a perfect law; some of its blemishes ought to get ironed out in subsequent legislation. In all, though, it should reduce the odds of another cataclysmic financial crisis. This does not mean that we will not experience big ups and downs, even asset-price bubbles, in the future, but these should not lead to a complete shattering of the financial system as we witnessed just a few years ago.

Section 3: Quantifying the economic impacts

To quantify the economic impacts of the aforementioned panoply of policies, we simulated the Moody’s Analytics model of the U.S. economy under different counterfactual scenarios. In all scenarios, the federal government’s automatic stabilizers—the countercyclical tax and spending policies that are implemented without explicit approval from Congress and the administration—are assumed to operate. So is the traditional monetary policy response via the Federal Reserve’s management of short-term interest rates, albeit constrained by the zero lower bound. [19]

To assess the full impact of the policy response, the “No Policy Response” scenario assumes that, apart from the above, policymakers simply sit on their hands in response to the crisis. They take no extraordinary fiscal or monetary measures as the turmoil mounts. While it is hard to imagine that policymakers would stand still while such a downturn intensified, many critics of the policy responses have argued that is precisely what policymakers should have done.

To isolate the economic impacts of the fiscal stimulus, the “No Fiscal Stimulus” scenario assumes that policymakers do not implement any discretionary tax cuts and government spending increases. Policymakers in this scenario do bail out the financial system, and the Federal Reserve does take extraordinary steps to provide liquidity to the financial system and engages in quantitative easing. But there is no fiscal response. The “No Recovery Act Scenario” is similar, but it focuses only on the largest and most controversial fiscal stimulus: the ARRA.

In the “No Financial Policy” scenario, we assume that the full fiscal response happens but that the Federal Reserve does not act as the lender of last resort, refusing to implement the full range of liquidity provisions and quantitative easing that it actually did. Nor is the financial system bailed out via the FDIC’s guarantee of bank debt, the bank stress-testing process, and the provision of equity capital via the TARP.

To separately analyze the economic impact of the Fed’s controversial QE program, the “No Quantitative Easing” scenario assumes that the Fed does not engage in QE, but that all other aspects of the financial rescue happen as they actually did. Finally, to isolate the impacts of the bank bailout, the “No Bank Bailout” scenario assumes that all policy steps are taken except for the Fed’s bank stress tests and the capital infusions from TARP.

The final scenario considered is the “No Auto Bailout” scenario, which examines the economic impact of policymakers’ support to the U.S. auto industry. This support was neither a fiscal stimulus nor financial policy, and is thus considered independently.

All of the scenarios are simulated using the Moody’s Analytics macro model over the period from the start of the Great Recession in 2008 through the first half of 2015. The differences between the economy’s performance under each of the scenarios and its actual performance provide the model’s estimates of the effects of the wide range of policies implemented to stem the financial crisis and end the Great Recession.

The macro model

Quantifying the economic impact of government policies is not an accounting exercise; it is an econometric one. Outcomes for employment and other measures of economic activity must be estimated by using a statistical representation of the economy based on historical relationships, such as the Moody’s Analytics macro model.

The Moody’s model is regularly used for similar purposes: forecasting, scenario analysis, bank stress-testing, and quantifying the economy-wide impacts of a range of policies. The Federal Reserve uses a similar model for its forecasting and policy analysis, as do the Congressional Budget Office and the Office of Management and Budget. Some important details about the model’s specifications are mentioned in discussing the simulation results below. [20] There are both advantages and disadvantages to using such large macroeconometric models, but no other type of model is able to consider the totality of the policy responses to the Great Recession.

Modeling fiscal stimulus

The modeling techniques for simulating the various fiscal policy responses to the economic downturn are straightforward, and have been used by countless modelers over the years. While the scale of the fiscal stimulus was massive, most of the tax and government spending instruments have been used in past recessions. So little modeling innovation was required on our part.

This does not deny that there has been a heated debate over the efficacy of fiscal stimulus measures. Much of that debate has centered on the magnitude of the multipliers generated by various fiscal policy instruments. These multipliers measure the added economic activity generated by a change in taxes or government spending.

In its analysis of the expected impacts of the ARRA, in early 2009, the Obama administration estimated government spending multipliers that were persistently near 1.5—meaning that a $1 increase in government spending results in a $1.50 increase in GDP (see Figure 1). [21] In contrast, Professor John Taylor, a critic of fiscal stimulus, estimated that the multipliers were more than 1 initially but quickly faded away. [22]

In the Moody’s Analytics macro model, the multipliers vary considerably depending on the precise fiscal policy instrument and on how far the economy is from full employment. Direct income support to low-income and unemployed individuals has some of the largest bang for the buck, with the temporary increase in SNAP benefits topping the list, as Table 5 shows.

When the economy has a large output gap, that is, when actual GDP is far below potential GDP, as it was in early 2009, the multipliers are large and persistent. For example, the early-2009 multiplier for infrastructure spending in the Moody’s model is very close to what the Obama administration assumed. However, as the output gap disappears, the multipliers diminish quickly (see Figure 1). Indeed, when the output gap is zero—that is, when the economy is at full employment—the increase in government spending crowds out private sector output almost completely. The multipliers become quite small as the higher interest rates resulting from the increased government spending and larger budget deficits reduce consumer spending and business investment nearly dollar for dollar.

Source: Moody’s Analytics

Modeling quantitative easing

Modeling the myriad of policies used to address the collapse of the financial system was more difficult, given that most were unprecedented and unconventional. This task not only demanded some creativity, it also required us to make a number of simplifying assumptions and judgment calls.

To illustrate, consider our approach to modeling the Federal Reserve’s quantitative easing programs. The federal funds rate is determined in the model by a modified Taylor rule: an equation that links the Fed’s interest rate policy to economic and financial market conditions. Specifically, the Taylor rule in the model includes a measure of the equilibrium funds rate, the difference between the unemployment rate and the natural rate, the difference between inflation (as measured by the core consumer expenditure deflator) and the Fed’s inflation target, and the VIX index—the implied volatility in Standard & Poor’s 500 index options, which is a proxy for investor confidence in the stability of the financial system (see Appendix Table A1). [23] The nominal equilibrium funds rate is determined within the model, and equals the sum of the Fed’s inflation target and the economy’s estimated growth rate of real potential GDP. [24]

Of course, the Fed reduced the funds rate rapidly when the Great Recession struck. The rate hit the 0- to 25-basis point lower bound in December 2008. A few weeks prior to that, the Fed had announced its first large-scale bond-buying program, designed to push down long-term interest rates. In the model, QE kicks in once the fitted funds rate—the funds rate determined by the modified Taylor rule—falls below zero (see Figure 2). It is captured by an expansion of the assets held on the Fed’s balance sheet. The size of the balance sheet directly impacts 10-year Treasury yields and fixed mortgage rates in the model, and those two interest rates, in turn, have wide-ranging impacts.

The magnitude of the bond-buying and balance sheet expansion is calibrated to the actual QE-related bond-buying undertaken by the Fed. Most pre-existing estimates of the impact of QE on interest rates come from event studies using “windows” of various lengths around an announcement date. Those studies typically find that QE1, which helped bring moribund markets back to life, had more bang for the buck than subsequent rounds of QE. That cannot be true given the structure of the Moody’s model. So, relative to the event-studies literature, we expect our simulations to show smaller early effects of QE1 and perhaps larger effects of subsequent rounds of QE.

Modeling the bank bailout

Modeling the channels through which the bank bailout impacted the economy is also challenging. The severity of the Great Recession was due in significant part to the collapse of the financial system, and the subsequent revival of the economy was due in no small part to the policy steps that brought the system back from the brink.

The macro model captures the interplay between the financial system and the economy through equations for commercial banks’ Tier 1 capital, net charge-offs, assets outstanding, and return on assets.

The ratio of Tier 1 capital to risk-weighted assets is a key measure used by regulators to gauge the capital adequacy of financial institutions. The bank stress-testing process, which was first implemented in early 2009, requires banks to maintain a minimum level of Tier 1 capital under a “severe adverse” scenario that is similar in severity and duration to the Great Recession. [25] The current standard is that banks must have at least a 5.5% Tier 1 capital ratio after allowing for losses from the stress scenario.

The Tier 1 capital ratio is determined in the model by banks’ returns on assets, as banks can use their profits to enhance their capital positions; by their net charge-off rates, as greater loan losses cut into capital; and by a measure of the capital that banks are required to raise to meet their regulatory minimums (see Appendix Table A2). The equity capital that the nation’s largest banks were required to take from the TARP bailout fund during the financial crisis is also accounted for.

In the model, the Tier 1 capital ratio is an important driver of bank lending standards, as measured by the Federal Reserve’s Senior Loan Officer Opinion Survey. Lending standards for commercial and industrial loans and for mortgage loans are particularly significant drivers of business investment and housing activity. As banks raise capital to meet their regulatory requirements, lending standards tighten, restricting credit availability and thus investment and housing demand. Once banks are adequately capitalized, credit conditions ease, supporting stronger investment and housing activity.

An illiquid and undercapitalized financial system also results in higher interest rates on loans, as financial institutions demand higher risk premia to compensate them for the prospect of not getting repaid in a timely manner. In the macro model, this angst in the financial system is captured by the VIX index. The VIX is a key driver of one-month Libor which, in turn, affects all interest rates in the model, including various interest rate spreads such as the spread between three-month Libor and three-month Treasury bills; the spread between fixed mortgage rates and 10-year Treasury bonds; and the spread of below-investment-grade corporate bond (“junk bond”) rates over Treasuries. Interest rate spreads rose alarmingly during the crisis, but came tumbling down once policymakers responded. The impacts of the Fed’s extraordinary liquidity provisions and the FDIC’s move to guarantee bank debt during the height of the financial crisis are also captured in the one-month Libor equation (see Appendix Table A3).

One plus one is ... three?

When quantifying the economic impact of the policy response to the financial crisis and recession, one plus one is greater than two. Because the policies reinforce each other, the combined effects of different policies exceed the sum of the effects of each of the policies taken in isolation—often by large amounts.

To illustrate this dynamic, consider the impact of providing housing tax credits, which were part of the fiscal stimulus. The tax credits boost housing demand, which pushes house prices higher. Foreclosures then decrease, so the financial system suffers smaller mortgage loan losses. These smaller losses, in turn, enhance the capital of the banking system, allowing banks to ease underwriting conditions and reduce lending rates, which supports even greater economic activity. Hence housing tax credits increase the efficacy of monetary policy.

The Federal Reserve’s effort to provide liquidity to the asset-backed securities market through the Term Asset-Backed Securities Loan Facility is another example of positive interactions. TALF was instrumental in supporting auto lending and auto sales, and thus enhancing the impact of the auto industry bailout.

There are also several important nonlinearities in the macro model that significantly amplify the economic impacts of policy changes. Particularly important in this regard is the model’s relationship between consumer spending and consumer confidence. Confidence impacts spending through the wealth effect—the change in households’ spending due to a change in their wealth. These positive wealth effects are modest when consumer confidence is low, but become larger when consumers are more confident. Therefore, a more muscular policy response to a financial crisis can have outsize economic benefits, if it lifts confidence sufficiently.

The relationship between capacity utilization and business investment is also highly nonlinear. Rising utilization rates do little to prompt more investment spending when they are low, but they have larger impacts on investment when factories, mines and utilities are operating closer to capacity. A policy response that supports a struggling economy will therefore have an extra-large economic benefit.

But the most important nonlinearity in the macro model is in the relationship between the VIX index and two key financial prices: interest rates and the value of the U.S. dollar. In the model, the VIX increases with lower capacity utilization and consumer confidence, higher price-earnings multiples for S&P 500 companies, lower bank capitalization (as measured by the Tier 1 capital ratio), and more systemic risk in the financial system as measured by the strength of the relationship between the expected default frequencies of publicly traded financial institutions (see Appendix Table A4). [26]

Movements in the VIX have outsize impacts on rates and the dollar, which in turn have large impacts on the economy. For example, big increases in the VIX signal that global investors are nervous, prompting a flight to quality into U.S. assets and an appreciation of the dollar—which is precisely what happened during the year after Bear Stearns collapsed in spring 2008. Policies that work quickly to head off such financial panic stem this flight to quality, and the economy benefits as the lower value of the dollar improves the nation’s trade balance.

What actually happened?

Before turning to the model simulations, it is worth briefly considering how the financial system and economy have performed since the extraordinary measures taken by policymakers during the crisis.

The bailout of the financial system appears to have been both highly effective and efficient. As noted earlier, the system was near collapse in the turmoil of late 2008, but was already operating well by the late spring of 2009. Liquidity in the system had been restored and the nation’s large banks had been sufficiently recapitalized to weather the mounting losses on their residential mortgages and other loans. Lenders remained cautious for a while, but credit flows began to normalize by 2011.

Many critics hold that the bankers and their creditors got unfairly bailed out by taxpayers. There is also still some unfinished business left over from the crisis response. The mortgage giants, Fannie Mae and Freddie Mac, which were put into conservatorship early in the crisis, remain stuck there, the private residential mortgage securities market remains largely dormant, and monetary policy has yet to normalize.

These are all valid criticisms, several of which will be dealt with in Section 5 below. But it is important to acknowledge that without a well-functioning financial system the broader economy might never have gotten back on its feet. This view is bolstered by recent experiences in Europe and Japan, where the banking systems, and thus the economies, have struggled. Moreover, taxpayers ultimately made money on the bailout, as noted earlier. The Dodd-Frank Act also imposed substantial changes on the financial services industry, increasing the system’s capitalization, increasing regulatory oversight, and mitigating the risk that financial institutions are too big to fail. The government continues to play an outsize role in the residential mortgage market, but that role is steadily diminishing. [27] The Fed has ended QE and, as this is written, appears poised to begin normalizing interest rates.

The economy’s performance since the crisis and recession has fallen short of most expectations. While the Great Recession ended soon after the policy response to the crisis was in full swing, the pace of recovery has been slow. Real GDP growth has averaged only 2.1% per annum over the past six years, well below the 3% average growth experienced since World War II. Job growth has been more encouraging, mainly because productivity growth has nearly stalled, but the economy has begun getting closer to full employment only recently, nearly a decade since it was last there.

However, as we will soon show, it seems perverse to blame the economy’s disappointing recovery on the policy responses. More likely, it was due to the inevitable headwinds created by the economy’s deleveraging in the wake of the financial crisis, adjustments induced by the major reforms to the healthcare and financial system during this period, the premature turn from fiscal stimulus to fiscal austerity--and even the uncertainty created by political brinkmanship over the budget, which led to a government shutdown and a downgrade of U.S. Treasury debt.

The “No Policy Response” scenario

The substantial economic benefits from the wide-ranging policy responses to the crisis and recession are clearest when considering how poorly the economy might have performed if there had been no policy response at all. It probably would have been devastating. The peak-to-trough decline in real GDP, which was barely over 4% in reality, would have been close to 14%, a stunning number, according to the model. Furthermore, the economy would have contracted for more than three years, more than twice as long as the actual contraction (see Table 6 and Appendix Table B1).

* Billions of 2009 dollars ** Millions *** 1982-1984 = 100 Sources:  BEA, BLS, Moody’s Analytics

By the time employment hits bottom in the “No Policy Response” scenario, more than 17 million jobs have been lost, which is about twice the actual number, and unemployment peaks at just under 16% (instead of 10%). Though not determined in the model, it would not be surprising if the under employment rate, which includes marginally attached workers and part-timers who want full-time jobs, would have exceeded one-fourth of the labor force. This dour scenario is also characterized by deflation, as wages and prices decline through 2011.

Furthermore, the federal budget deficit (not shown in table) surges, peaking at $2.8 trillion, more than 20% of GDP, in fiscal 2011. This, too, is about double the size of the actual deficit—which peaked in fiscal 2009. Thus, even though the policy response was costly to taxpayers, not responding would have been much more costly. [28]

According to the Moody’s Analytics model, had policymakers punted and not responded to the crisis, the economy would have unraveled into a 1930s-like depression. Indeed, to this day the economy would still be far weaker than it actually is. As of the second quarter of 2015, real GDP in the “No Policy Response” scenario is still about $800 billion lower than actual, there are 3.6 million fewer jobs, and the unemployment rate is a still-dizzying 7.6%.

The “No Fiscal Stimulus” scenario

The use of fiscal stimulus measures to combat the recession may have been the most politically contentious of the policy steps taken to combat the recession. But it was critical in stanching the hemorrhaging of the economy and jump-starting the recovery. The Recovery Act (February 2009) included myriad tax and spending provisions. Combined, they added well over 2% to GDP in 2009 and an additional almost 1% by the end of 2010 (see Figure 3). The temporary tax cuts were particularly important in supporting consumer spending in the teeth of the downturn, but the spending, including increased outlays on infrastructure, boosted growth for longer. By 2011, the provisions of the Recovery Act were winding down, which weighed on growth, shaving over a percentage point from real GDP growth. The effects of this large fiscal stimulus package had largely faded away by 2013.

But a string of other, smaller fiscal stimulus packages was to come, and taken together with the Recovery Act, they provided an important economic boost. This can be seen in the scenario in which it is assumed there is no fiscal stimulus, but that policymakers follow through on all the other policy efforts (see Table 7 and Appendix Table B2). The peak-to-trough decline in real GDP in this scenario is almost 6%, and employment declines by almost 11 million jobs. [29] The economy hits bottom in late 2009, and by the time it finally gains traction in spring 2011, the unemployment rate peaks at almost 11%.

Without the fiscal stimulus, the federal budget deficit peaks at $1.6 trillion in fiscal 2010, and does not fall below $1 trillion until fiscal 2013. The cumulative difference between the deficits in this scenario and the government’s actual deficits covers about three-fourths of the more than $1.4 trillion taxpayers shelled out to finance the stimulus packages. But the cost seems worth it. Without the stimulus, GDP, jobs and unemployment would have only recently caught up to the economy’s actual performance.

The “No Recovery Act” scenario

The American Recovery and Reinvestment Act was far and away the largest and most controversial of the fiscal stimulus efforts. It was vital to ending the free fall in the economy and jump-starting the economic recovery. The Recovery Act was passed in February 2009, the recession ended in June 2009, and job growth resumed in February 2010.

According to the Moody’s model, the maximum GDP impact from the Recovery Act occurred in 2010, when real GDP was 3.3% higher than if the stimulus had never been implemented (see Table 8 and Appendix Table B3). In terms of jobs, the stimulus added almost 3 million jobs at its apex, and the unemployment rate was reduced by more than 1.5 percentage points.

These results are consistent with those of the Congressional Budget Office in its analysis of the economic impact of the Recovery Act. [30]

Source: Moody’s Analytics, CBO

The “No Financial Policy Response” scenario

Re-establishing a stable financial system and healthy credit flows were a necessary condition for economic recovery. The long list of extraordinary policy responses that saved the nation’s financial system—including the Fed’s extraordinary efforts, the FDIC’s guarantee of bank debt, the bank stress tests, and the recapitalization through TARP—was especially important.

In a counterfactual scenario that assumes that policymakers did not take any of the steps they did to shore up the financial system but did follow through on the fiscal policies just analyzed, the economy would have struggled through spring 2011 (see Table 9 and Appendix Table B4). According to the model, GDP would have declined 6.5% from peak to trough, employment would have fallen by more than 12.5 million jobs, and the unemployment rate would have risen to nearly 12.5%. [31] There is also a period of modest deflation in 2010 and very large budget deficits in this scenario.

Perhaps most disconcerting is that, to this day, the economy would still not have recovered what it lost in the recession. As of the second quarter of 2015, real GDP in this scenario is still about $600 billion shy of where it is currently, employment is lower by 3.2 million jobs, and the unemployment rate is 1.9 percentage points higher.

The “No Quantitative Easing” scenario

Controversy over the Fed’s quantitative easing program has been extraordinarily heated. When the Fed first began QE1 in 2009, there was much hand-wringing over the prospects of runaway inflation due to the surfeit of bank reserves created by the Fed’s bond-buying. However, inflation has remained subdued. Critics then shifted to claiming that QE is fomenting bubbles in various asset markets. Stock and property values may be a bit rich today, in part because of QE. But it is hard to argue that these markets have turned speculative in the sense that investors are flipping stocks and properties and using leverage to finance their buying and selling.

There are also worries that the Fed’s policies are exacerbating the skewing of the distributions of income and wealth as older retirees who hold most of their savings in cash-like instruments have been hit hard by super-low interest rates. Some critics even worry that QE, by holding interest rates down, has let fiscal policymakers off the hook, as they did not need to make the hard budget-shrinking policy choices necessary for solid long-term growth.

Perhaps. All these objections are taken up in Section 5. But the evidence is strong that QE has done what it was intended to do, namely to lower long-term interest rates. This is captured in the macro model as follows: QE purchases push down the yield on 10-year Treasury bonds via the increase in the Fed’s balance sheet (see Appendix Table A5). Every 1-percentage point increase in the ratio of Fed assets to GDP ultimately reduces the 10-year Treasury yield by close to 5 basis points in the model. Doing the arithmetic, this implies the Fed’s QE program has reduced long-term Treasury yields by more than a percentage point. [32] , [33]

The lower long-term interest rates resulting from QE support stronger economic growth in the macro model via their impact on stock prices and housing values and the wealth effects on consumer spending. Lower long-term rates also lift business investment through a lower cost of capital, and support a better trade balance as the lower rates push down the value of the dollar.

In total, QE has increased the level of real GDP by approximately 1.5% as of the first quarter of 2015, according to the model (see Figure 4). Although the script on QE’s success or failure is still being written, and it is unclear how graceful the normalization of the Fed’s balance sheet will be, so far at least, it appears to be a significant success.

The “No Bank Bailout” scenario

As for most of the policy responses to the financial crisis there is significant disagreement about the efficacy of the bank bailout. But without the bank stress tests and the TARP bailout funds, the nation’s banking system likely would have remained undercapitalized, if not comatose, for much longer, impeding lending and economic growth. To what extent? To estimate that, the macro model was simulated under the scenario that the banks were not stress-tested and did not get capital injections from TARP.

With inadequate capital, banks respond by tightening their underwriting standards and raising their loan rates in an effort to shed risky assets. Commercial and industrial lending to businesses is hit especially hard, with outstandings cut nearly in half at their nadir in 2011 (see Figure 5). Commercial real estate and consumer lending is also much weaker. Residential mortgage lending is impacted less, owing to the effective nationalization of mortgage lending when Fannie Mae and Freddie Mac were placed into conservatorship.

The fallout on the real economy is substantial (see Figure 5, Table 10, and Appendix Table B5). Credit is the mother’s milk of economic activity. As illustrated by Europe, where the banking system was only recently adequately stress-tested and recapitalized, an economy will struggle to grow without well-functioning banks to extend credit. In the model, real GDP is lower by close to 4% at the bottom in 2011.

The “No Auto Bailout” scenario

Policymakers agonized over their decision to provide financial aid to the reeling auto industry in late 2008. No one wanted to use taxpayer dollars to shore up the industry. But the fear was that, without any government help, the Big Three would quickly end up in a Chapter 7 liquidation rather than a Chapter 11 restructuring. Given the collapse in the financial system and resulting credit crunch, debtor in possession financing would be extremely difficult to get from private sources. So their factories and other operations might shut down, resulting in hundreds of thousands of layoffs at just the wrong time.

Neither the Bush nor Obama administration wanted to take that chance in a sliding economy. The Big Three employed fewer than 250,000 people in the U.S., but given their broad links into the rest of the economy, hundreds of thousands of other jobs would have been at risk immediately. Indeed, according to the Moody’s model, not providing help to the industry would have cost the economy 800,000 jobs at the peak of its impact in mid-2010 (see Figure 6). [34]

Section 4: Some criticisms of the policy interventions

We have just argued that the dramatic policy interventions pursued by the Federal Reserve, the Treasury, and Congress in 2008-2009 had large, and largely salutary, effects on the U.S. economy: ending the financial panic, mitigating the recession, and hastening the recovery. But, to put it mildly, not everyone agrees with that assessment, not to mention with our specific numerical estimates. And in fairness, we have focused on the impacts of the anti-recession policies on macro variables such as GDP and employment, thereby estimating the benefits of the extraordinary policies but not fully considering their potential costs .

What are some of these costs? Critics have focused on a list of issues that we take up in turn, albeit briefly.

Many of the emergency rescue operations created moral hazard problems that will plague us in the future.

There can be no doubt that several of the emergency actions taken by the Fed and the Treasury created or exacerbated moral hazard. Critics worry that this may prove problematic in the future when the precedents set in 2008-2009 either lead to excessive risk-taking, followed perhaps by more financial instability, or are violated, possibly recreating the sort of market chaos that occurred when the Bear Stearns precedent was not followed in the Lehman case. These are valid concerns. But we view it as a potentially catastrophic mistake to accept the argument “it creates moral hazard” as a show stopper. Rather, we think policymakers should conceptualize bailout decisions as trade-offs : trading the costs of potential moral hazard in the future against a potential catastrophe in the present.

Moral hazard costs are conjectural, difficult to quantify, and often distant in time, whereas the macroeconomic benefits from a stronger economy are clear, quantifiable (we have argued), and immediate. Critics point out that this contrast may skew decision-making in real time toward too many bailouts. So it seems important, after the acute stage of the crisis has passed , to install new policies that limit the potential for subsequent opportunistic behavior. That was one of the guiding principles of the Dodd-Frank Act, especially in its “orderly liquidation authority” and “no taxpayer-funded bailout” provisions.

Will it work? Only time will tell. But one way to make an educated guess about whether moral hazard is better or worse today than, say, before the series of financial institution rescues in 2008 is to study the behavior of credit default swap spreads for large too-big-to-fail financial institutions. Narrower spreads imply a lower market assessment of risk, some of which may stem from investors’ beliefs that the government will bail out giant financial institutions if necessary—thus implying greater moral hazard (see Figure 7). Prior to the crisis, between 2004 and 2007, CDS spreads for these institutions averaged close to 20 basis points. This compares to a spread of over 60 basis points more recently. While many factors can impact CDS spreads, including the liquidity of trading in these derivatives, this increase in spreads is large and suggestive that investors believe that the government is no longer backing these institutions as strongly as it did pre-crisis.

The spending parts of the 2009 fiscal stimulus unduly expanded the size of the federal government, were wasteful, and probably killed more jobs than they created.

Fiscal stimulus measures did fuel a surge in federal government spending during the recession and the early part of the economic recovery. But this was temporary—by design. The central idea behind fiscal stimulus is to lift government spending temporarily in bad economic times, and then, once the economy is back on its feet, to end the additional spending. That is precisely what happened during and after the Great Recession. Whether you measure federal spending in real or nominal terms or as a share of GDP, it peaked in the first quarter of 2010. Government spending remains low as a share of GDP and is about where it was during the Reagan presidency (see Figure 8).

Regarding waste, it is hard to imagine a package of more than $800 billion worth of federal spending, tax cuts, and grants to states and localities that does not include at least some waste, fraud and abuse. But the spending components of the Recovery Act appear to have had amazingly little of that, perhaps in part because of monitoring by the Recovery Act Transparency and Accountability Board.

It may be legitimate to argue that any particular government spending program is wasteful and inefficient, reflects the wrong priorities, or even usurps functions best left to the private sector. But it is difficult to imagine how more government spending could actually “kill” jobs. [35] After all, when it purchases goods and services, the federal government is either hiring people to work for it directly or buying products from private companies, who then probably hire more workers. How can either kill jobs? In the Moody’s model, of course, as in other Keynesian macro models, that does not happen.

Some critics have argued that the conclusion that the stimulus created lots of jobs is built into the structure of these models. For example, the estimates in our 2010 paper could have been made before the stimulus was enacted; they do not depend on what actually happened in 2009-2012. [36] That is true, and one way to address this criticism is to look ex post at a variety of studies of particular pieces of the stimulus that ask whether they really stimulated spending or employment. Since our 2010 paper was published, a number of papers have done precisely that.

One of the first was by James Feyrer and Bruce Sacerdote (2011), who assessed the effectiveness of the 2009 stimulus spending by comparing what actually happened on the ground in states that received different amounts of ARRA money. In making such geography-based assessments, it is important to deal with reverse causation. For example, states hit harder by the recession received more stimulus money than states that fared comparatively well. Failing to account for that econometrically would bias the estimated effects of the stimulus downward . Feyrer and Sacerdote (2011) use instrumental variables to do that, and find that the job impact of fiscal stimulus measures depends on the type of stimulus. Specifically, they estimate that federal education grants to states created hardly any jobs. But excluding those, the rest of the stimulus created jobs at approximately the rate that macro models suggest.

A paper by Daniel Wilson (2012), who focused on Medicaid grants (which were deliberately made fungible by the federal government) and highway funds across states, found broadly similar results, as did Gabriel Chodorow-Reich et al. (2011).

A paper by Timothy Conley and Bill Dupor (2013) is the main exception to the finding that cross-sectional studies based on actual data give roughly the same assessment of the stimulus’ effects as simulations of macro models. They find strong positive effects of ARRA spending on public-sector employment but small or even negative effects on private-sector employment. Han Tran (2015), who obtains starkly different results, speculates that one reason may be that, unlike most other studies of stimulus spending, Conley and Dupor (2013) scale ARRA spending by state government spending (which was directly affected by the ARRA) instead of by state population or state GDP. Christina Romer (2011) suggests that Conley and Dupor (2013) may have a weak instruments problem.

The large fiscal stimulus increased the federal budget deficit, which left the country with a higher debt-to-GDP ratio, spelling future problems.

It is certainly true that the Recovery Act (and many of the other policy interventions) contributed to larger federal budget deficits, which increased from $459 billion in fiscal 2008 to a stunning $1.413 trillion in fiscal 2009. These bigger deficits did add to the nation’s public debt, and the debt-to-GDP ratio nearly doubled.

But the imploding economy raised the nation’s deficits and debt load even more, [37] and the effect of the weak economy on the fiscal situation would have been far larger without the policy interventions. Thus, while the policy interventions cost taxpayers a bundle, it would have cost them even more if policymakers did nothing and allowed the economy to descend into depression.

Furthermore, we agree with the majority of economists who think the cost-benefit calculus of running larger versus smaller deficits shifts dramatically in favor of deficits when the economy is depressed. So we consider the larger deficits of, say, 2009-2013 as a plus rather than a minus.

The government’s response to the crisis was unfair. It bailed out the big banks and the automakers, but it did not help homeowners much, and millions lost their homes in foreclosure.

Many have criticized the policy response for being unfair. It was argued that the U.S. government engaged in crony capitalism, favoring some groups over others for political reasons. The Bush administration was chastised for helping Goldman Sachs, where Treasury Secretary Henry Paulson had been the CEO. The Obama administration was hammered over the GM and Chrysler bailouts, which were said to favor labor unions over bondholders in those companies.

We sympathize with some of these critiques, especially the complaints that (a) more could and should have been done to limit foreclosures and (b) taxpayers could have been given more of the upside from the financial bailouts. But there are always winners and losers when policies change, and in this case the winners far outnumbered the losers. Would other Americans have been better off if the government had refused to save the (greedy and irresponsible) banks and the (incompetent) auto companies? We are pretty sure the answer is no. The policy responses were designed to get the biggest—and quickest—economic bang for the buck, not to promote distributional equity.

The Federal Reserve stretched its powers beyond the legal breaking point, in some cases poaching into the realm of fiscal policy.

While some of its actions were unprecedented, there can be little doubt that the Fed acted within its statutory authority. After all, before the Federal Reserve Act was amended by Dodd-Frank, the pliable Section 13(3) permitted the Board of Governors to extend credit to “any individual, partnership, or corporation” under “unusual and exigent circumstances” as long as borrowers posted good collateral for their loans. The circumstances of 2008-2009 were certainly “unusual and exigent,” and every recipient of Federal Reserve credit was an “individual, partnership, or corporation.” The collateral also appears to have been decent and, in any case, the law designated the Fed itself as the sole judge of that. [38] So legality is not a serious issue.

However, the Fed did put taxpayer money at risk each time it invested in (or loaned against, especially when the loans were without recourse) risky assets. And those can legitimately be considered quasi-fiscal operations. (In principle, they had scorable actuarial costs.) We agree that, in normal circumstances, the Fed should refrain from “spending” taxpayer money, even actuarially. But the circumstances of 2008-2009 were far from normal.

Congress, apparently, did not agree. When it wrote Dodd-Frank, it decided to constrain the Fed’s emergency lending powers in the future. We think that was a mistake, by the way, which leaves the fire brigade less well-equipped to fight the next conflagration. (More on this in Section 6.)

The Federal Reserve sacrificed its independence by bending to the will of the administration and Congress.

We have heard this criticism but, frankly, do not understand the basis for it. Allan Meltzer (2009, p. 13), for example, has claimed that “Chairman Ben Bernanke ... worked closely with the Treasury and yielded to pressures from the chairs of the House and Senate Banking Committee and others in Congress.” Bernanke certainly did work closely with Treasury Secretaries Henry Paulson and Timothy Geithner to extinguish the raging financial fires in 2008 and 2009; we hate to imagine what might have happened if he had not. But we do not see that as sacrificing the central bank’s independence, and we do not see what congressional “pressures” Bernanke bowed to. Perhaps most fundamentally, we do not see the Fed as less independent today than it was in, say, 2007. Were that true, you might expect to see, for example, that long-term inflationary expectations became unhinged. They did not (see Figure 9).

The Fed’s hyper-expansionary monetary policies—in particular the creation of trillions of dollars of excess bank reserves—will eventually prove inflationary.

The future will have to speak for itself. But we know this much already: When the Fed announced the beginnings of what came to be called QE1 in November 2008, the 12-month trailing core CPI inflation rate was 2%. As of this writing, more than 6½ years later, it is 1.8%; and it has been flat as a board since August 2012, never rising above 2% nor falling below 1.6%. The inflation Cassandras, while consistently wrong for years, have never stopped issuing false alarms. They do not seem to recognize either (a) that excess reserves sitting idly in banks’ accounts at the Fed do not create monetary or credit expansions, or (b) that bank reserves are basically like T-bills now that the Fed pays interest on reserves—and no one ever claimed that bank holdings of T-bills are inflationary. Finally, as just noted, market expectations do not agree with the inflation Cassandras.

Maintaining the near-zero interest rate policy, or ZIRP, for so long and engaging in massive quantitative easing risks creating bubbles and undermining financial stability.

Could be. The “bubble” criticism is hard to deal with because most bubbles are identifiable only after they burst—and there has been no such bursting to date. But bubbles are generally characterized by speculation, wherein investors purchase an asset simply because they think they can sell it quickly to another investor for a higher price. Such behavior is not much in evidence in asset markets today. We may someday look back at 2015’s record stock market—which is almost certainly higher because of the Federal Reserve’s actions—and declare that it was bubbly. We do not know that today, however, and the S&P 500 has been more or less flat since the beginning of 2015. Nor have any of the other scare stories of financial instability stemming from ZIRP or QE come true. Time will tell.

ZIRP and QE have created a massive “exit” problem for the Fed, which is likely to go badly.

Two things almost certainly are true: The Fed will eventually shrink its balance sheet (which is now about $4.5 trillion) quite a lot, and the Fed will eventually push the funds rate much higher than it is today (0 to 25 basis points). Those adjustments, which are expected to start within months, are the essence of what is commonly called the Fed’s “exit strategy,” and the Fed has been talking about and planning for exit for years (actually, since 2009!).

Nonetheless, a number of observers fear that the job will overwhelm the Fed in practice. Specifically, it is often claimed that the Fed’s reluctance to move fast enough will leave us with higher inflation in the end. We think exit, while a big job and unlikely to be executed perfectly, is not as difficult as is frequently portrayed—especially since the Fed can speed it up, slow it down, or otherwise modify the exit process as often as it wishes. No one can see the future; we will all have to wait. But we do know that inflationary expectations over the next decade remain low (see again Figure 9).

ZIRP and QE constitute financial repression that forces savers to struggle with extraordinarily low interest rates. It is the wealthy classes—the owners of stocks, bonds and real estate—who have benefited the most.

Ordinary savers, with their assets in CDs and other safe instruments, have indeed suffered from the low interest rate environment. But the number of people living off interest is very small. Most savers have other assets—such as stocks, bonds and real estate—that have benefited substantially from the Fed’s efforts that have supported asset prices by keeping interest rates low. Furthermore, QE probably reduced income inequality by giving the recovery a boost. In total, any inegalitarian redistribution from QE seems to have been modest. [39]

The Fed’s aggressive actions have taken fiscal policymakers off the hook, enabling them to avoid (or at least postpone) the hard fiscal decisions that would put the nation on a sound long-term fiscal path.

Perhaps. But the Fed had to work harder to support the economy once fiscal policymakers decided to push in the opposite direction. Moreover, while political counterfactuals can always be questioned, it seems a stretch to argue that Congress and the administration would have found it easier to work together if the Fed had not supported the flagging economy. Rather, fiscal policymakers might have bickered even more as the weaker economy fostered more political dissension. In our view, the economy would be in a far worse place today if the Fed had left more things up to the politicians.

In short, while there is some basis for some of these criticisms, we do not find any of them compelling. And we certainly do not believe that any of them—nor even the entire list—makes a plausible case that policy passivity would have been wiser in 2008-2009 than the policy activism pursued by U.S. policymakers.

Section 5: The past as prologue: Lessons for “next time”

Only a few years have passed since the financial crisis and Great Recession, and more perspective may be necessary before we can claim to understand fully the lessons from that cataclysmic period. But some already seem clear.

In the spirit of addressing potential moral hazards before, as opposed to during, the crisis, policymakers should employ macroprudential tools to avoid or minimize asset bubbles and the increased leverage that are the fodder for financial catastrophes. Doing so includes requiring more capital and liquidity in the financial system, stress-testing financial institutions, and strengthening regulatory vigilance, particularly over large institutions and rapidly growing parts of the system. Yes, it is notoriously difficult to identify bubbles before they burst, but the old banking adage that “if it is growing like a weed, it is probably a weed” will help policymakers know where to look.

Nonetheless, despite policymakers’ best efforts, there will be financial crises in the future. That is not all bad. Crises are an inherent part of our financial system; without them it is likely that the risk-taking necessary for strong long-term economic growth would be stymied. But when the good times roll, investors find it difficult to avoid getting caught up in the euphoria, to take on too much risk, and to saddle themselves with too much debt.

When financial panics do come, regulators should take care to be as consistent as possible. They should, for example, avoid the starkly different treatments of Bear Stearns and Lehman Brothers in 2008. The consistent resolution of troubled financial institutions is vital to ensure that creditors in the financial system know where their investments stand and thus do not run to dump them when the good times give way to the bad.

The line is subtle here: Policymakers should not respond to every financial event; after all, asset prices go up and down all the time. But they should respond aggressively to potential crises, wherein liquidity dries up throughout the financial system, threatening to take down many institutions and ultimately the entire financial system. Of course, making such a distinction in the fog of real time is difficult. But the greater the uncertainty, the more policymakers should err on the side of a bigger and more open response. That TARP was so big—at the time an unfathomable $700 billion—was a key to its success. Creditors had no doubt that the government was backstopping the financial system.

Furthermore, it seems to us that the first step in fighting a crisis is to stabilize the financial system. Without credit, the real economy will suffocate regardless of almost any other policy response. The Federal Reserve must ensure that there is substantial liquidity (as Walter Bagehot understood in the 19th century) and, if necessary, steps should be taken either to ensure or restore the solvency of systemically important institutions or to resolve them in an orderly way. [40] In this regard, we believe it is a mistake to limit the Fed’s ability to provide emergency loans under Section 13(3) of the Federal Reserve Act, as Dodd-Frank has done.

Conventional monetary policy—that is, lowering the overnight interest rate—may be insufficient to forestall or cure a severe recession. This realization can lead policymakers in one of two directions—or both, if the recession is severe enough or happens suddenly. One direction is to supplement conventional monetary policy with unconventional monetary policies, such as QE, especially once short-term nominal interest rates approach zero. [41] While QE has potential downsides, critics need to learn that massive infusions of bank reserves are not inflationary if they just pile up willingly as excess reserves on banks’ balance sheets.

The other direction is to deploy fiscal policy instruments such as tax cuts and government spending. Here critics need to remember that the effects of a temporary fiscal stimulus on budget deficits are temporary. [42]

Discretionary fiscal policy is an effective way to support an economy suffering a lengthy and severe downturn. Fiscal stimulus measures have been part of the standard policy playbook for combating recessions since the Great Depression. The size of the stimulus should be proportionate to the magnitude of the expected decline in economic activity. The specific tax and spending policies included as part of the stimulus should be based in large part on their efficacy or bang for the buck. But the policy steps taken may have to be more varied, or even experimental, when the downturn is anticipated to be deep. Tax breaks and transfers to persons, such as more food stamps and unemployment insurance, will generally help the economy quickly, but their benefits will fade quickly, too. Infrastructure and other spending will take longer to implement, but that could be a plus in a longer recession.

Fiscal policy should not swing from stimulus to austerity until it is clear that the financial system is stable and the economy is enjoying self-sustaining growth. A good rule of thumb is that the estimated unemployment gap—the difference between actual unemployment and the full-employment unemployment rate as a percent of the labor force—be clearly less than 1 percentage point and declining before the stimulus is withdrawn. Until the labor market is clearly approaching full employment, confidence and thus the economic recovery will remain fragile and vulnerable to almost anything that goes wrong. Policymakers may need to put other policies—for example, deficit reduction or entitlement reform—on hold until a self-sustaining expansion is under way.

Fiscal and monetary policy interactions are large, that is, fiscal stimulus measures enhance the power of monetary/financial stimulus measures substantially—and vice versa. [43] So there is a strong argument for using a “two-handed” (monetary and fiscal) policy approach to fighting recessions. Indeed, it may even be possible to select specific monetary and fiscal tools with an eye to those that reinforce each other. The new homebuyers’ tax credit, for example, enhanced the effectiveness of the Fed’s purchases of mortgage securities in reducing mortgage rates, and vice versa.

Bailouts of companies—whether financial or not—should be avoided if at all possible. If they are unavoidable, shareholders should take whatever losses the market doles out and creditors should be heavily penalized to minimize moral hazard. To the maximum extent possible, such rules should be specified in advance. Furthermore, taxpayers should ultimately be made financially whole. Better communication with the public should be considered an integral part of any bailout operation. Bailouts will never be popular, but policymakers should expend every effort to make them less politically poisonous.

Increasing moral hazard should always be considered a cost of any rescue program, but it should not be a show stopper. There have been in the past, and we suspect there will be in the future, instances in which some sort of “bailout” or rescue operation passes a cost-benefit test even though it exacerbates moral hazard. Decisions must be made case by case.

Policymakers clearly made mistakes in the lead-up to the financial crisis and Great Recession. They failed to use macroprudential policy to weigh against the housing and bond bubbles, and they botched the resolution process of failing financial institutions. But they got the policy response to the crisis mostly right. Not every monetary, financial and fiscal policy step was effective, and the policymaking process was at times messy and counterproductive. But taken in its totality, the policy response was a huge success. Without it, we might have experienced Great Depression 2.0.

The economic expansion is more than six years old, longer than most expansions, and we are getting closer to full employment. It has been a long time coming, but it would have taken much longer without the massive and unprecedented response of policymakers.

Sources: Moody’s Analytics

* Billions of 2009 dollars (seasonally adjusted annualized rate) ** Millions (seasonally adjusted) *** 1982-1984 = 100 (seasonally adjusted) Source: BEA, BLS, Moody’s Analytics

Alan S. Blinder, After the Music Stopped: The Financial Crisis, the Response, and the Work Ahead (Penguin, 2013).

Alan S. Blinder and Mark Zandi, “ How the Great Recession Was Brought to an End ,” Moody’s Analytics White Paper, July 2010.

Ben S. Bernanke, Remarks at the Conference to Honor Milton Friedman, University of Chicago, Chicago, Illinois, November 8, 2002.

Ben S. Bernanke, “Monitoring the Financial System,” speech at the 49th Annual Conference on Bank Structure and Competition, Federal Reserve Bank of Chicago, May 10, 2013.

Gabriel Chodorow-Reich, Laura Feiveston, Zachary Liscow, and William Woolston, “Does State Fiscal Relief During Recessions Increase Employment? Evidence From the American Recovery and Reinvestment Act.” American Economic Journal: Economic Policy 4, no. 3 (2012), 118-145.

John F. Cogan and John B. Taylor, “What the Government Purchases Multiplier Actually Multiplied in the 2009 Stimulus Package,” NBER Working Paper 16505, 2011.

Timothy Conley and Bill Dupor, “The American Recovery and Reinvestment Act: Solely a Government Jobs Program?” Journal of Monetary Economics, 2013, 535-549.

Congressional Budget Office, “ The Troubled Asset Relief Program: Report on Transactions Through December 31, 2008 ,” CBO Report, January 2009.

Congressional Budget Office, Estimated Impact of the American Recovery and Reinvestment Act on Employment and Economic Output from January 2010 Through March 2010 , May 2010.

Congressional Budget Office, Estimated Impact of the American Recovery and Reinvestment Act on Employment and Economic Output in 2014 , February 2015.

James Feyrer and Bruce Sacerdote, “ Did the Stimulus Stimulate? Real Time Estimates of the Effects of the American Recovery and Reinvestment Act ,” National Bureau of Economic Research Working Paper 16759, 2012.

Austan Goolsbee and Alan Krueger, “A Retrospective Look at Rescuing and Restructuring General Motors and Chrysler,” Journal of Economic Perspectives, Vol. 29, No. 2 (Spring 2015), 3-24.

Tony Hughes and Samuel Malone, “ Systemic Risk Monitor 1.0: A Network Approach ,” Moody’s Analytics White Paper, June 2005.

Allan Meltzer, “Policy Principles: Lessons from the Fed’s Past,” in J.D. Ciorciari and J.B. Taylor (eds.) The Road Ahead for the Fed (Hoover: 2009).

Steven Rattner, Overhaul: An Insider’s Account of the Obama Administration’s Emergency Rescue of the Auto Industry (Houghton Mifflin Harcourt: 2010).

Carmen Reinhart and Kenneth Rogoff, This Time is Different: Eight Centuries of Financial Folly (Princeton: 2009).

Christina Romer, “What Do We Know About the Effects of Fiscal Policy? Separating Evidence From Ideology,” Lecture delivered at Hamilton College, November 7, 2011.

Christina Romer and Jared Bernstein, “ The Job Impact of the American Recovery and Reinvestment Act ,” January 2009.

Han Tran, “Is That a Stimulus Package in Your Pocket?: The Impact of the American Recovery and Reinvestment Act on Aggregate Demand,” Princeton University senior thesis, April 2015.

John C. Williams, “ Monetary Policy at the Zero Lower Bound: Putting Theory into Practice ,” Brookings (Hutchins Center) Working Paper, January 2014.

Daniel Wilson, “Fiscal Spending Jobs Multipliers: Evidence from the 2009 American Recovery and Reinvestment Act,” American Economic Journal: Economic Policy 4, no. 3 (August 2012), 251-282.

Mark Zandi and Scott Hoyt, “ Moody’s Analytics U.S. Macro Model Methodology ,” Moody’s Analytics White Paper, April 2015.

Mark Zandi, “The State of the Domestic Auto Industry: Part II,” Testimony before the Senate Banking Committee, December 4, 2008.

Mark Zandi, Financial Shock: Global Panic and Government Bailouts—How We Got Here and What Must Be Done to Fix It (FT Press: 2009).

Mark Zandi, Paying the Price: Ending the Great Recession and Beginning a New American Century (FT Press: 2012).

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[1]    See Blinder and Zandi (July 2010).

[2]    See Zandi and Hoyt (April 2015).

[3]    For far more detail, see Zandi (2009, 2012) or Blinder (2013).

[4]    The three quotations in this paragraph come from company statements and can be found in Blinder (2013, p. 90).

[5]    Real GDP grew by nearly 2% in 2007 and was essentially flat during the first half of 2008. The NBER dates the recession as starting in December 2007.

[6]    This discussion focuses on the U.S. Similarly extraordinary responses took place in other countries.

[7]    Reinhart and Rogoff (2009).

[8]    The insurance limit was abolished altogether for business transaction accounts.

[9]    By then, “depository institutions” had been defined to include the remaining giant investment banks, Goldman Sachs and Morgan Stanley.

[10] The Congressional Budget Office (2009, p. 1) initially estimated a 26% actuarial loss rate of TARP’s disbursements to banks.

[11] See, for example, Bernanke (2013).

[12] For a good summary of the literature, see Williams (2014).

[13] While he was a Fed governor, Bernanke (2002) had famously pledged to Milton Friedman: “I would like to say to Milton and Anna [Schwartz]: Regarding the Great Depression. You’re right, we did it. We’re very sorry. But thanks to you, we won’t do it again.”

[14] Cash for clunkers, formally the Car Allowance Rebate System, in July-August 2009 also helped.

[15] See Rattner (2010) and Goolsbee and Krueger (2015).

[16] See CBO (February 2015).

[17] But actual job growth did not resume until a year later, in March 2010.

[18] See Romer and Bernstein (2009).

[19] Global economic growth and interest rates, the broad trade-weighted dollar, and oil and other commodity prices are determined in a model that is recursive to the Moody’s Analytics U.S. macro model. The simulation results from the U.S. macro model are used to drive the global and commodity market models, the results of which are then used in a second-round simulation of the U.S. macro model.

[20] See Zandi and Hoyt (April 2015).

[21] See Romer and Bernstein (2009).

[22] See Cogan and Taylor (2011).

[23] The VIX is used as a measure of financial stability by the Federal Reserve in its CCAR stress test scenarios. The macro model does not use the VIX index constructed by the Chicago Board Options Exchange, but rather a similar measure that Moody’s Analytics constructs.

[24] Potential is determined endogenously using a standard Solow growth model framework, with total factor productivity determined exogenously.

[25] There is also an “adverse” scenario which, while not as severe, moves some different economic variables. Banks must pass both.

[26] A financial institution’s expected default frequency is a measure of the probability that the firm will default within one year. Default is defined as failure to make scheduled principal or interest payments. A firm defaults when the market value of its assets (the value of the ongoing business) falls below its liabilities payable (the default point). See Hughes and Malone (2015) for more details on EDFs and how they are used to measure the degree of systemic risk in the financial system.

[27] The share of mortgage originations for government mortgage lenders the FHA and Department of Veterans Affairs has significantly declined from the peak immediately after the recession. Fannie Mae and Freddie Mac are also ramping up their credit risk sharing with private sources of capital.

[28] The estimates presented in Table 9 are different from, but quite close to, the ones we presented in Blinder and Zandi (2010). The differences stem mainly from changes to the model between 2010 and 2015.

[29] These effects are a bit larger than those presented in Blinder and Zandi in large part because of the additional fiscal stimulus provided by Congress after that paper was published. Changes to the macro model also contributed to the changed estimates.

[30] See CBO (2015)

[31] In our 2010 paper, the estimated effects on output and employment were a bit smaller, but the effect on the unemployment rate was slightly larger.

[32] QE likely also impacts the 10-year yield via global investors’ expectations regarding the future conduct of monetary policy and the path of the federal funds rate. This signaling effect was especially large for the first round of QE, but much less important by the time QE3 was rolled out. QE by other global central banks has likely also impacted 10-year Treasury yields as the Treasury bond market is a global market. The European Central Bank’s decision to begin QE in late 2014 has been especially important most recently. These effects are not explicitly captured in the macro model.

[33] Williams (2014, Table 1) presents a wide range of estimates for the effects of $600 billion worth of QE on long-term interest rates from 12 studies, mostly event studies. His range is 10 to 100 basis points. If we throw out the highest and the lowest, this huge range shrinks to a still-large 15 to 45 basis points. If we then blow up these estimates to the actual $1.425 trillion in QE in our Table, that range would translate to 36 to 107 basis points.

[34] See Zandi (2008) for a more thorough analysis of the auto bailout.

[35] The phrase “job-killing government spending” became a kind of mantra for House Speaker John Boehner (R-OH).

[36] See, for example, Cogan and Taylor (2011).

[37] For a breakdown, see Table 8.1, page 235, in Blinder (2013).

[38] As is well known, the Fed’s stated reason for not bailing out Lehman Brothers was that Lehman lacked sufficient collateral.

[39] See the results reported at a June 2015 Brookings Institution conference on this question at www.brookings.edu/events/2015/06/01-inequality-and-monetary-policy.

[40] Dodd-Frank provides for orderly liquidation.

[41] Economists used to speak of the “zero lower bound,” but we have now seen that nominal interest rates can actually go negative.

[42] Except for the subsequently greater interest burden.

[43] For example, it is well known that fiscal policies have larger multipliers if monetary policy accommodates them by preventing interest rates from rising.

More from the Authors

Alan S. Blinder, former Vice Chairman of the Federal Reserve Board, is Professor of Economics and Public Affairs at Princeton University, Vice Chairman of the Promontory Interfinancial Network, and a regular columnist for The Wall Street Journal.

Recent Work:

Mark Zandi is Chief Economist of Moody’s Analytics, and he serves on the boards of Mortgage Guaranty Insurance Company and TRF, one of the nation’s largest community development financial institutions.

FinancialResearch.gov

Reports > 2022 annual report to congress, executive summary.

The 2022 OFR Annual Report reviews financial market developments, describes potential emerging threats to U.S. financial stability, and assesses global economies, financial markets and liquidity, financial institutions, digital assets, cybersecurity risks, climate change risks, and the performance of the Office. Overall risks to U.S. financial stability are elevated and have increased since last year’s report. This report discusses the Office’s assessment of risks associated with the U.S. financial system and identifies areas causing stress, such as the following:

• Weaker economic growth and monetary tightening.
• Elevated volatility in the Treasury and short-term funding markets.
• Surges in commodity pricing and hedge fund leveraging and interconnectedness.
• Crypto asset volatility and the depegging of the third-largest stablecoin.
• Increased state-sponsored cyberattacks and resulting changes in the cyber insurance market.
• Climate-related financial risks.

February 2022 marked the beginning of major events that would stress the financial system. Contributing factors to the financial and economic stress included Russia’s war against Ukraine, the Federal Reserve’s tightening monetary policy to reduce inflation, lingering supply disruptions as economies worked past the COVID-19 pandemic, and economic uncertainty based on the slowing of global growth. Strong consumer demand, labor supply shortages, and supply disruptions in commodities markets were among the major triggers of global inflation. With rising interest rates, certain sectors are more susceptible to credit risks. The total reported market capitalization of all crypto assets has fallen by more than 70% from its peak of $3 trillion in November 2021. The increased frequency of cyberattacks and the growing costs to guard against them continue to pose risks. Finally, climate change introduced vulnerabilities to the financial system, yet assessing the risk is complicated by the threat’s medium- to long-term nature.

Macroeconomy

The U.S. labor markets remain tight, although real wages have fallen, and the participation rate remains below its pre-pandemic level due to shifting economic dynamics post-pandemic. The job market’s strength supports households but raises concerns about continued inflationary pressures. Overall, macroeconomic risks to U.S. financial stability have increased since 2021. High inflation and a slowdown in growth posed risks to household balance sheets, residential and commercial real estate, and other parts of the financial system. In addition, the rising interest rate environment affected sovereign debt risk and segments of the corporate debt market. Consumer price inflation began rising in the spring of 2021. It continued to rise through the start of 2022, climbing to high levels not seen in several decades and remaining well above the Federal Reserve’s target of 2% per annum. Several factors drove higher prices, including strong aggregate demand, a post-pandemic reopening of the economy, and a material shift from services to goods. Supply chain distortions have been larger and more persistent than markets anticipated, putting upward pressure on prices. New waves of COVID-19 infections continue to disrupt overseas supply chains (particularly in China) and the domestic services sector. As a result, domestic and global energy prices increased significantly throughout the year, affecting domestic producers and importers. The high price of energy was a key contributor to the recent record inflation, with energy as one of the fastest-rising components of several price measures. In addition, Russia’s war against Ukraine significantly disrupted European energy markets, driving up costs in the global market. At the same time, the post-pandemic recovery in the U.S. labor market has been remarkable, and indicators show that the labor market remains tight. The unemployment rate is currently near a 50-year low. On the other hand, Russia’s war against Ukraine impacted global growth and trade. The war decreased expectations of global macroeconomic growth. The World Bank reduced its global growth forecast for 2022 to 2.9% (from 4.1%) and forecasted a contraction of 4.1% in Europe and Central Asia. High inflation led to considerably tighter conditions in financial markets globally. Interest rates broadly increased. The Federal Reserve began hiking the federal funds’ target rate in March 2022 after maintaining a target rate of 0% - 0.25% since March 2020. As of September 2022, the target range of federal funds stood between 3.0% - 3.25% and is expected to increase. The Federal Reserve also began reversing its quantitative easing policy and is now engaging in quantitative tightening. Central banks around the world implemented similar measures. In June, the European Central Bank (ECB) announced that it raised its key policy rate for the first time in over 11 years. The ECB raised interest rates from -0.50% in July to 1.5% in October, with further increases planned. Despite inflation rising to reach the Bank of Japan’s target of 2% for the first time in years, the bank intends to maintain rates at just below zero with no expected rate increases.

The global economy is experiencing high inflation driven by strong demand following the COVID-19 pandemic and disruptions in the supply of energy and other commodities:

• U.S. economic growth has slowed as financial conditions have tightened, partly due to interest rate hikes and quantitative tightening. The U.S. labor market remains strong, but the labor force participation rate and the employment-to-population ratio are below pre-pandemic levels.
• Higher inflation in the post-pandemic global economy and a dramatic rise in commodity prices following Russia’s war against Ukraine have hampered global growth prospects. European economies are particularly vulnerable to rising energy costs that affect labor productivity and consumption. As a result, many European economies entered into a recession in 2022.
• Central banks are raising interest rates to fight inflation but must balance this against the risk of overtightening. European central banks are facing the prospect of stagflation as the U.S. dollar continues to strengthen and the war in Ukraine drags on. Moreover, increasing yields in peripheral eurozone countries have given rise to fragmentation concerns and a potential return of the European debt crisis of the 2010s.
• In emerging markets, food and energy prices remain high, hampering economic growth and raising social tensions. In addition, increasingly tight financial conditions may push some debt burdens to unsustainable levels.

Credit Risk from Tighter Financial Conditions

Corporate leverage remains elevated, but it has declined from the peak. Credit risk premiums, the difference in yield between a corporate bond and a Treasury bond of the same maturity, increased sharply in 2022 and are above historical medians. As the U.S. economy transitions from an era of unprecedented quantitative easing and zero interest rates to one with quantitative tightening and higher rates, the outlook for the corporate credit cycle is more uncertain. As a result, corporate sector vulnerabilities could amplify stress in the economy and financial markets. The 2007-09 financial crisis illuminated financial-stability channels related to the household sector and how systemic shocks to the financial system can originate from household balance sheet issues. The net worth of U.S. households declined to $143.8 trillion in Q2 2022 from its peak of $149.8 trillion in 2021, based on the Federal Reserve’s Financial Accounts data. Adjusting for inflation and expressed in real terms, household net worth remains slightly higher today compared to pre-pandemic levels, or $123.8 trillion compared to $116.4 trillion in Q4 2019. Household debt increased over the past year to levels not seen since 2007. The year-over-year aggregate growth in household debt is 7.0% in September 2022, or $15.6 trillion. A depressed commercial real estate (CRE) market can cause and has caused past financial stability issues, such as during the 1990-91 recession, when depository failures were primarily due to CRE lending-related losses. However, we have seen limited CRE market stress in recent years as the CRE market has performed well with strong occupancy rates, rising rents, and property values. However, offices in dense central business districts such as New York and San Francisco had physical office occupancy rates well below their pre-pandemic usage, due to the work-from-home (WFH) phenomenon.

Tighter financial conditions expose credit risk vulnerabilities:

• Nonfinancial firms with floating-rate debt or near-term maturities face larger financing burdens. This headwind is amplified by weaker fundamental trends.
• The CRE market’s performance is softening after exceptional performance in recent years. Unlike previous market downturns, credit losses on CRE loans are not expected to pose a significant risk to financial stability. The longer-run performance of the office sector is unclear, especially in dense central business districts where WFH appears to be a permanent development.
• Household leverage remains at historically low levels because low interest rates and COVID-19 pandemic-related support programs aided households in decreasing debt obligations. Household financial conditions have deteriorated for some, due to inflationary pressures. Delinquency rates have increased more rapidly for renters compared to homeowners among the most vulnerable households.
• Rapidly rising mortgage rates dampened home price appreciation, though the risks to the economy are lower than they were in the period leading up to the 2007-09 financial crisis.

Financial Markets and Liquidity

Short-term funding markets support core functions of the financial system, providing liquidity to borrowers and allowing corporations, financial firms, and other investors to meet immediate and near-term cash needs. Funding markets are relatively stable, but market liquidity remains fragile. In addition, market volatility and the impact of Federal Reserve interest rate increases are magnified in short-term markets. In Treasury markets, the persistent specialness in certain securities may have resulted from the repositioning around Federal Reserve tightening combined with one-sided positioning and limited supply. As tightening continues, there is a possibility that liquidity challenges may persist if high levels of uncertainty remain about the future path of policy. In the market for short-term Treasury securities, substantial increases in investors’ cash balances have led to demand outpacing the supply of new Treasury bills. While market risk, or volatility in asset prices, is not the same as financial-stability risk, market risk may interact with and reinforce other vulnerabilities where the combination amplifies financial-stability risk. For example, negative nominal and real yields distorted asset prices and encouraged borrowers to maintain high leverage levels. The normalization of yields reduces these effects and provides a more robust set of investment opportunities for fixed-income investors, reducing incentives to reach for yield. The overall health of the municipal market was strong after municipalities received support during the onset of the COVID-19 pandemic. In addition, states entered the monetary-tightening cycle in a strong position due to the 2021 economic expansion, which increased tax receipts and saw a decline in fuel and energy costs. Infrastructure spending continued to be a significant issue because municipal issuers invested in repairing or replacing failing bridges, dams, utilities, and other projects. Since the 1960s, the proportion of U.S. infrastructure spending to GDP has declined by 47%. This lack of expenditures has placed municipalities and states at risk of catastrophic infrastructure failures. The economic impact of infrastructure failures is significant and can impact communities for decades through higher taxes, reduced productivity, and higher costs.

Fixed income and equity investors experienced large losses from a sharp increase in risk-free rates and may face more declines if market sentiment deteriorates:

• Treasury market volatility is elevated, and liquidity remains tight amid monetary policy uncertainty. More generally, bond market stress measures are showing levels comparable to March 2020 and the early days of the 2007-09 financial crisis.
• Short-term funding market conditions have tightened as investors become more risk averse amid economic and monetary policy uncertainty. Structural vulnerabilities remain in some segments of the short-term funding market, such as money market funds and other cash management vehicles.
• Asset prices have fallen sharply, but many valuation metrics are either elevated or near historical averages. Further price declines are possible if economic conditions weaken materially or if another shock emerges.
• State and local governments emerged from the COVID-19 pandemic with strong balance sheets but face increasing cost pressures from energy and wage inflation, which siphon resources from needed infrastructure spending.

Financial Institutions

After enjoying a relatively benign economic and financial climate in 2021, buoyed by strong profitability and limited credit losses, U.S. banks entered a period of heightened uncertainty. Higher inflation and interest rates, a greater risk of recession, and enhanced global risks due to Russia’s war against Ukraine lowered the sector’s outlook. Nevertheless, despite headwinds, in aggregate, the U.S. banking sector remained well capitalized and maintained risk-based capital ratios well above regulatory minimums. While the insurance industry was not immune to the stresses of 2022, it is unlikely to meaningfully affect the U.S. financial system’s near-term stability. Yet, there remain important issues impacting the insurance industry, including the following:

• Changes in insurers’ investment policies as interest rates rise and fall.
• Rising claim costs due to inflation.
• Increased life sector involvement by private equity–affiliated insurers.
• The increasing stress on the ability of the private insurance industry to cover large and growing risks.

Since the market downturn in March 2020, hedge fund leverage and asset class exposures have grown significantly, although these increases have moderated in the past year. Hedge funds engaged in various trading strategies to maximize risk-adjusted returns. While many hedge funds sought to mitigate the sensitivity of their performance to adverse market movements, certain fund classes were not able to mitigate with the rise of inflation. In February and March 2022, the surge in commodity prices following Russia’s war against Ukraine forced several commodity-focused central counterparty (CCP) clearinghouses to raise initial margins on various commodity contracts. The increases were most significant in Europe, where margins nearly doubled compared to the prior year’s average. In the U.S., the initial margin increase at commodity CCPs was 20%-30%. The sudden increase in volatility would have led to even larger increases were it not for the residual effects of market volatility in early 2020, which led CCPs to maintain high resource levels in the U.S. due to the lengthy lookback period of their risk models. Although increased margin demands have put a temporary strain on the liquidity of some members, the resulting elevated levels of posted collateral can aid in easing concerns about potential CCP defaults going forward. Financial institutions face uncertainty and unique challenges due to higher interest rates and inflation, slower economic growth, and geopolitical risks:

• In aggregate, the U.S. banking sector remains well capitalized and has maintained risk-based capital ratios well above regulatory minimums.
• Insurers have increased the risk profile in their investment portfolios in response to low interest rates in recent years, thereby making them more exposed to investment losses during an economic downturn. Inflation continues to negatively affect property and casualty insurers as claim costs rise, especially for homeowners and automobile insurance.
• Bond fund flows are sensitive to interest rate increases. Significant outflows may strain fixed-income markets. During historical periods of rising interest rates, the size of bond funds was much smaller, and dealer capacity to intermediate was much greater.
• The hedge fund industry has experienced negative returns but has been able to outpace broad market indices during this high inflationary period in 2022. The industry’s asset exposures and leverage moderated in 2022 after rebounding from the 2020 downturn. Despite declines in aggregate industry leverage, some funds are highly leveraged and may pose a threat to financial stability.
• The surge in commodity prices in March and September 2022 triggered large increases in initial margins at some CCPs. Several commodity-centric CCPs faced significant stress, although no CCP member defaulted. The size and concentration of member positions in commodity markets have raised questions about the transparency of exposures across CCPs, making it difficult to set effective margins.

Digital Assets

Risks in the digital-assets markets were highlighted when several crypto asset lenders suspended customer withdrawals following the decline in crypto asset prices in June 2022. Central banks can issue central bank digital currencies (CBDCs), which are digital liabilities of the central bank. As discussed in the 2021 OFR Annual Report, CBDCs should be immune to the run risk of stablecoins but may increase flight-to-safety concerns. U.S. regulators are currently exploring CBDCs. The Federal Reserve issued a CBDC consultation paper in January 2022 and is continuing its independent research into and experimentation with CBDCs. Globally, around 90% of central banks now report studying or working on developing a CBDC. Four central banks issued CBDCs (the Bahamas, the Eastern Caribbean Currency Union, Jamaica, and Nigeria), and over 30 CBDCs are in development or pilot phases.

Digital assets experienced a volatile 2022, with the total market capitalization falling from over $2.2 trillion in January 2022 to under $1 trillion in August 2022. Losses to date appear largely contained within the digital-asset sector, although the risk of contagion looms.

• Many prominent crypto asset trading and lending platforms suspended customer withdrawals. Some also filed for bankruptcy.
• The third largest stablecoin at the time depegged in May 2022. During that month, the $18.5 billion loss in value highlighted risks associated with stablecoins and spillover risks in the digital-assets space.

Cybersecurity Risk

Russia’s war against Ukraine heightened the prospect of state-sponsored cyberattacks and the importance of vigilance and planning in technology infrastructure. Prior events—such as the 2012 coordinated denial-of-service cyberattack, where several major U.S. financial institutions suffered simultaneous outages—were believed to be in response to the U.S.-imposed economic sanctions on Iran. Furthermore, beyond attacks directly targeting U.S. financial services institutions, there were concerns of unintended spillovers from cyberattacks stemming from state-sponsored actions, as demonstrated by the NotPetya malware incident in 2017. This alleged Russian attack infected software used by Ukrainian organizations and then spread to companies worldwide, leading to billions of dollars in U.S. corporate losses. Organizations are continually working to mitigate the consequences of attacks in response to these various actors’ threats to the financial system. Otherwise, there is the potential that a successful attack will cause significant harm not only to the organization but to the financial systems in which they operate. Three mechanisms can be used to prepare for potential cyber incidents:

• Mechanism 1 - technology security, resiliency, and recovery. This consists of preventing attacks by minimizing vulnerabilities that adversaries could exploit, such as active cyber defense, cybersecurity hygiene, and insider threat management.
• Mechanism 2 - coordination and information sharing. Cybersecurity discussions tend to focus on reducing risk for the individual through means such as multifactor authentication and zero-trust architecture, coordination, and communication across firms and government agencies, such as the Cybersecurity and Infrastructure Security Agency (CISA), the Office of Cybersecurity and Critical Infrastructure Protection (OCCIP), and the Financial Services Information Sharing and Analysis Center (FS-ISAC).
• Mechanism 3 - cyber insurance. This can offer vital financial support and recovery assistance to an entity suffering from a cyberattack. Increased numbers of written policies and premiums per policy have driven rapid growth in this sector. As a result, annual policy premiums grew at a double-digit rate or (in some cases) a triple-digit rate, depending upon the risk-and-loss profile of the insured.

The increasing frequency of cyberattacks and the growing cost to guard against them pose risks to the financial system:

• Russia’s war against Ukraine has substantially increased the perceived risk of state-sponsored cyberattacks in the U.S. financial services sector, although the majority of attacks have been focused on theft. The cyber posture of the sector has responded through increased information sharing and focused readiness exercises.
• Firms can implement cyber-defense mechanisms that reduce financial stability risk. These include undertaking internal/individual security measures, such as the application of the zero-trust framework; information sharing and coordination among firms and the government; and cyber insurance.
• As the cyber insurance market matures and adapts to new threats, substantial changes are emerging.
• The number of policies written continues to grow as the need for cyber risk insurance becomes increasingly evident and cyber risk coverages are excluded from general insurance policies.
• Obtaining cyber insurance has become more challenging because insurers have tightened their underwriting standards and insurance premiums for cyber policies have risen substantially.

Climate-related Financial Risk

Climate-related financial risk is the risk of financial losses due to rising global temperatures and accompanying environmental shifts, such as rising sea levels and more severe weather events. Climate-related financial risk poses physical and transition risks to the financial system. Physical risks describe the potential destruction or damage of physical assets, the impact on economic activity, and other losses from extreme weather events. Transition risk, created by technological advances, policy changes, and preferences shifts, can be more challenging to quantify economically. Governments face financial risks related to climate change. An increase in climate-related events is likely to cause firms and households to increasingly rely on the insurance and banking sectors. At the same time, local municipalities and state governments are likely to rely on the federal government for financial support. Some households and businesses might be left without insurance as private insurers may become increasingly unwilling or unable to insure against climate-related physical risks. Climate-related damages in the U.S. have grown to about $133 billion per year, with the federal government often stepping in with emergency relief and acting as an insurer of last resort. Climate change impacts numerous aspects of the financial markets, often in unanticipated ways. In addition to transition risks, a myriad of physical risks can affect the financial markets. Climate risks are being priced into financial assets, but the extent varies depending upon the market, and not all risks are priced for the market. For example, the potential risk of mispricing lies in the mortgage industry. Lenders may be indirectly encouraged to underwrite mortgages without accounting for flood risks and then pass these loans to government sponsored mortgage companies (GSMC) to securitize into mortgage pools. This may indirectly encourage households to locate or, after disaster strikes, rebuild in areas prone to risks such as flood, hurricane, and wildfire. Recent evidence suggests this hasn’t been the case, but it could be a source of future risk.

Climate-related financial risk has introduced vulnerabilities into the financial system, although assessing the risk to financial stability is complicated by the medium- to long-term nature of the threat.

• Assessing and forecasting these risks to financial stability can be challenging.
• Emerging areas of research highlight how interactions and networks in financial markets might amplify these risks.
• Firms and households affected by climate disasters are increasingly relying on the insurance and banking sectors to finance repairs and fund mitigation efforts.
• State and local governments are likely to rely on federal support for recovery efforts, disaster relief, and insurance programs.
• Climate-related risks could affect financial institutions and GSMCs through securitization, especially in flood-prone areas.
• To facilitate the dissemination of data, the OFR, in collaboration with the Federal Reserve, piloted an OFR-hosted Climate Data and Analytics Hub that provided staff from the Federal Reserve Board and Federal Reserve Bank of New York access to public climate and financial data, high-performance computing tools, and analytical and visualization software.

The OFR’s Performance

FY 2022 was a significant year for the OFR, highlighted by the launch of two major pilot programs: the Non-centrally Cleared Bilateral Repo Pilot Project and the Climate Data and Analytics Hub pilot. While the OFR’s centrally cleared repo collection has been an asset in allowing regulators greater visibility into this market, non-centrally cleared bilateral repo has remained largely opaque and regarded as a potentially significant liability for regulators. This led to the creation of a pilot data collection project in which nine firms volunteered to participate. The project shed light on several market practices, including the composition of collateral, the identity of counterparties, and the terms of repo agreements. Notably, it was determined that most non-centrally cleared bilateral repos are collateralized by U.S. Treasuries, despite the eligibility of much of the collateral for bilateral central clearing. The OFR has initiated the rulemaking process to establish a permanent data collection, and the pilot data collection and subsequent analysis are expected to lead to a proposed rule governing these repo transactions. The OFR’s Climate Data and Analytics Hub pilot was intended to allow regulators to assess climate risks to financial stability. The project met the Federal Reserve’s request for reliable climate data and tools, and it allows the OFR to potentially provide additional capabilities or enhanced services to the Council and its member agencies. Pilot participants included researchers, analysts, and support staff of the OFR; the Federal Reserve; and the Federal Reserve Bank of New York. After the conclusion of the pilot, a review will be conducted to document lessons learned, assess scalability, and document future requirements.

Regulatory Oversight Committee (ROC)

The OFR assumed the role of ROC Secretariat, a key role in the organization, and is providing administrative services to the global body of authorities for multiple International Organization for Standardization (ISO) standards and data. The ROC is composed of more than 50 countries and is responsible for overseeing the governance of multiple globally used financial data standards, including the Legal Entity Identifier (LEI), the Unique Product Identifier (UPI), the Unique Transaction Identifier (UTI), and Critical Data Elements (CDE) for over-the-counter derivatives transaction reporting.

Data Center

The enhancement of the Financial Instrument Reference Database (FIRD) was a notable achievement. It included the addition of new data elements of the Financial Information eXchange (FIX) Protocol, and it brought in ideas for future functionality from the X9 Industry Forum for Financial Terms Harmonization, which analyzes and maps the terms and definitions across multiple industry standards. The Office also made significant gains toward fulfilling its mission to promote financial stability by delivering high-quality financial data standards, including improving the quality and utility of financial data in a way that facilitates data aggregation, integration, sharing, access, interoperability, and exchange.

Research and Analysis Center

Throughout the year, the OFR published numerous working papers on timely topics of high importance to financial regulators, including hedge funds, central bank digital currencies, and Treasury market stress. Other noteworthy content included financial stability monitors, research and evaluation of financial stability policies, and briefings for the FSOC and other stakeholders. In addition, the Office assisted the Defense Advanced Research Projects Agency (DARPA) EcoSystemic program to address disruptions to distributed financial ledgers.

Integrated Planning

Significant progress was achieved this year on the OFR’s Workforce Plan 2020–2024 by addressing gaps related to staff retention, workforce development, training, and recruitment. Of particular note were the development of an OFR-wide competency model and the completion of a competency assessment for all staff and leaders. In addition, the OFR expanded its team by 14%, enabling the closure of key gaps in subject matter expertise. The OFR filled multiple critical leadership positions, including Associate Director of Financial Institutions and a supervisory information technology specialist. In addition, the Office added considerable expertise and bench strength to its research, analysis, information technology, operations, and public affairs teams.

The Office implemented new layers of security focused on infrastructure and data. This included the creation of a new security operations facility that enabled significant advances toward a zero-trust architecture, in line with the federal mandate that all agencies should be compliant with zero trust by 2024. The OFR also completed the four-year migration from Treasury-hosted services, hardware, and equipment to a 100% cloud-based environment. Finally, the Office initiated hybrid workplace flexibilities, including telework and remote work, following temporary workplace provisions that began during the COVID-19 pandemic.

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Financial Markets and Financial Crises

Warnings of the threat of an impending financial crisis are not new, but do we really know what constitutes an actual episode of crisis and how, once begun, it can be prevented from escalating into a full-blown economic collapse? Contributors to this volume use an innovative framework to analyze financial crises and the conditions that lead to them. The authors examine episodes of breakdown in financial trade, where "trade" refers to the way in which financial contracts, institutions, and markets allocate risk, channel funds from ultimate savers to ultimate investors in the economy, and provide information about and incentives for borrowers' performance. Using both historical and contemporary episodes, these studies offer insights from theory and empirical data, from the experience of closed and open economies worldwide, and from detailed case studies. The research reports on four main themes: (i) the ways in which problems in contracting in financial markets can magnify economic disturbances; (ii) how historical episodes of financial panic can be used to discriminate among certain hypotheses of the economic role of financial institutions; (iii) what constraints on public policy are posed by the actual or perceived fragility of financial markets or institutions; and (iv) case studies of problems in one contemporary crisis, the sharp contraction of the U.S. savings and loan industry during the 1980s. Government economists and policymakers, scholars of industry and banking, and many in the business community will find these papers an invaluable reference.

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 .

• Feldstein Lecture
• Presenter: Cecilia E. Rouse

• Methods Lectures
• Presenter: Susan Athey

• Panel Discussion
• Presenters: Karen Dynan , Karen Glenn, Stephen Goss, Fatih Guvenen & James Pearce

• Lifestyles & Social Issues
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• Politics, Law & Government
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• Environment
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• Introduction

Causes of the crisis

• Key events of the crisis
• Effects and aftermath of the crisis

financial crisis of 2007–08

financial crisis of 2007–08 , severe contraction of liquidity in global financial markets that originated in the United States as a result of the collapse of the U.S. housing market . It threatened to destroy the international financial system; caused the failure (or near-failure) of several major investment and commercial banks , mortgage lenders, insurance companies, and savings and loan associations ; and precipitated the Great Recession (2007–09), the worst economic downturn since the Great Depression (1929– c. 1939).

Although the exact causes of the financial crisis are a matter of dispute among economists, there is general agreement regarding the factors that played a role (experts disagree about their relative importance).

First, the Federal Reserve (Fed), the central bank of the United States, having anticipated a mild recession that began in 2001, reduced the federal funds rate (the interest rate that banks charge each other for overnight loans of federal funds—i.e., balances held at a Federal Reserve bank) 11 times between May 2000 and December 2001, from 6.5 percent to 1.75 percent. That significant decrease enabled banks to extend consumer credit at a lower prime rate (the interest rate that banks charge to their “prime,” or low-risk, customers, generally three percentage points above the federal funds rate) and encouraged them to lend even to “subprime,” or high-risk, customers, though at higher interest rates ( see subprime lending ). Consumers took advantage of the cheap credit to purchase durable goods such as appliances, automobiles, and especially houses. The result was the creation in the late 1990s of a “housing bubble” (a rapid increase in home prices to levels well beyond their fundamental, or intrinsic, value, driven by excessive speculation).

Second, owing to changes in banking laws beginning in the 1980s, banks were able to offer to subprime customers mortgage loans that were structured with balloon payments (unusually large payments that are due at or near the end of a loan period) or adjustable interest rates (rates that remain fixed at relatively low levels for an initial period and float, generally with the federal funds rate, thereafter). As long as home prices continued to increase, subprime borrowers could protect themselves against high mortgage payments by refinancing, borrowing against the increased value of their homes, or selling their homes at a profit and paying off their mortgages. In the case of default, banks could repossess the property and sell it for more than the amount of the original loan. Subprime lending thus represented a lucrative investment for many banks. Accordingly, many banks aggressively marketed subprime loans to customers with poor credit or few assets, knowing that those borrowers could not afford to repay the loans and often misleading them about the risks involved. As a result, the share of subprime mortgages among all home loans increased from about 2.5 percent to nearly 15 percent per year from the late 1990s to 2004–07.

Third, contributing to the growth of subprime lending was the widespread practice of securitization , whereby banks bundled together hundreds or even thousands of subprime mortgages and other, less-risky forms of consumer debt and sold them (or pieces of them) in capital markets as securities (bonds) to other banks and investors, including hedge funds and pension funds. Bonds consisting primarily of mortgages became known as mortgage-backed securities , or MBSs, which entitled their purchasers to a share of the interest and principal payments on the underlying loans. Selling subprime mortgages as MBSs was considered a good way for banks to increase their liquidity and reduce their exposure to risky loans, while purchasing MBSs was viewed as a good way for banks and investors to diversify their portfolios and earn money. As home prices continued their meteoric rise through the early 2000s, MBSs became widely popular, and their prices in capital markets increased accordingly.

Fourth, in 1999 the Depression-era Glass-Steagall Act (1933) was partially repealed, allowing banks, securities firms, and insurance companies to enter each other’s markets and to merge, resulting in the formation of banks that were “too big to fail” (i.e., so big that their failure would threaten to undermine the entire financial system). In addition, in 2004 the Securities and Exchange Commission (SEC) weakened the net-capital requirement (the ratio of capital, or assets, to debt, or liabilities, that banks are required to maintain as a safeguard against insolvency), which encouraged banks to invest even more money into MBSs. Although the SEC’s decision resulted in enormous profits for banks, it also exposed their portfolios to significant risk, because the asset value of MBSs was implicitly premised on the continuation of the housing bubble.

Fifth, and finally, the long period of global economic stability and growth that immediately preceded the crisis, beginning in the mid- to late 1980s and since known as the “Great Moderation,” had convinced many U.S. banking executives, government officials, and economists that extreme economic volatility was a thing of the past. That confident attitude—together with an ideological climate emphasizing deregulation and the ability of financial firms to police themselves—led almost all of them to ignore or discount clear signs of an impending crisis and, in the case of bankers, to continue reckless lending, borrowing, and securitization practices.

2008 Financial Crisis: Causes and Costs

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Stanford Rock Center

Stanford law school, financial crisis inquiry commission.

This timeline allows you to view the critical events that led up to the financial crisis, as well as what happened during the crisis itself. To see the events on the timeline, click on the dots below. For more context, use the pull-down box at the left to view major economic indicators over time. Many terms used in this timeline are defined in the site’s Glossary section.

MEDIA ADVISORIES

• NARA Releases Additional FCIC Materials
• Leading Articles
• NARA Opens Financial Crisis Inquiry Commission Records 03/11/2016 | Press Release
• FCIC Releases Additional Material and Concludes Work 02/10/2011 | Press Release
• FCIC Releases Report on the Causes of the Financial Crisis 01/27/2011 | Press Release Video | Transcript

Conclusions

The Commission concluded that this crisis was avoidable—the result of human actions, inactions, and misjudgments. Warnings were ignored. “The greatest tragedy would be to accept the refrain that no one could have seen this coming and thus nothing could have been done. If we accept this notion, it will happen again.”

View Conclusions

View Dissents

Resource Library

Documents and emails, audio recordings and transcripts of interviews, reports and fact sheets developed by the staff, and graphic illustrations created by the Commission throughout its investigation.

Go to Resource Library

Exploring Financial Crises: A New Book from ESCP Experts

Posted on 26/09/2024

Of Banks And Crises by Cristina Peicuti and Jacques Beyssade

Cristina Peicuti , professor at ESCP Business School, and Jacques Beyssade , a leading expert in the banking sector and General Secretary of BPCE, have recently published a new book: Of Banks And Crisis. It offers an in-depth analysis of major economic crises and the role of banks in society, providing thoughtful insights on how they can better contribute to the common good.

Bankers and economists under media scrutiny.

As the global landscape becomes increasingly volatile, understanding how different regions manage risks and crises is crucial. The 2024 CERALE-UdeSA Colloquium on “Risk and Crisis Management in a Changing World” brought together researchers, policymakers, and business leaders from Europe and Latin America to discuss how the public and private sectors can respond to these challenges. Organized by the Centre for Studies and Research on Latin America and Europe (CERALE) at ESCP Business School and Universidad de San Andrés, this event highlighted key insights into managing uncertainty through innovation and investment.

A Journey Through Economic Crises

Of Banks And Crises stands out for its comprehensive approach to both historical and current economic crises. From the Great Depression to the Great Recession and from the impact of COVID-19 to the era of Brexit and Donald Trump's presidency, the book delves into how financial crises have shaped the global economy. The authors also highlight the pivotal role of cooperative banks in transforming the banking sector, driven by and for customers.

An Inspiring Quote from Charles Gide

The book opens with a powerful quote from Charles Gide, one of the founders of the Banques populaires and the first professor of economics in France, emphasising the importance of cooperative efforts to provide credit to the underprivileged. This sets the stage for the authors' reflection on the role of banks in society.

Why Read Of Banks And Crises?

This book is a must-read for anyone interested in the evolution of the banking sector and its impact on global crises. The authors offer fresh perspectives and practical solutions for how banks and economists can play a more proactive and positive role in society in the future.

Now available on Barnes & Noble , Of Banks And Crises is an essential read to understand the economic challenges of both the past and present.

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New Data Finds Sharper Economic Rebound From Pandemic

Updated figures show that gross domestic product, adjusted for inflation, grew faster in 2021, 2022 and early 2023 than previously reported.

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By Ben Casselman

The U.S. economy emerged from the pandemic even more quickly than previously reported, revised data from the federal government shows.

The Commerce Department on Thursday released updated estimates of gross domestic product over the past five years, part of a longstanding annual process to incorporate data that isn’t available in time for the agency’s quarterly releases.

The new estimates show that G.D.P., adjusted for inflation, grew faster in 2021, 2022 and early 2023 than initially believed. The revisions are relatively small in most quarters, but they suggest that the rebound from the pandemic — already among the fastest recoveries on record — was stronger and more consistent than earlier data showed.

Perhaps most notably, the government now says G.D.P. grew slightly in the second quarter of 2022, rather than contracting as previously believed. As a result, government statistics no longer show the U.S. economy as experiencing two consecutive quarters of declining G.D.P. in early 2022 — a common definition of a recession, though not the one used in the United States. (The revised data still shows that G.D.P. declined in the first quarter of 2022, but more modestly than previously reported.)

The official arbiter of recession in the United States is the National Bureau of Economic Research, a nonprofit research organization made up of academic economists. The group defines a recession as “a significant decline in economic activity that is spread across the economy and lasts more than a few months,” and it bases its decisions on a variety of indicators including employment, income and spending.

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Briefing: Financial Wellbeing Research 2024

This REBA insights briefing to the Financial Wellbeing Research 2024, in partnership with WEALTH at work, reveals the key societal, economic and employee value proposition (EVP) trends shaping financial wellbeing strategies.

Download the REBA Insights Briefing

This four-page briefing provides key insights from the REBA Financial Wellbeing Research 2024 , published in partnership with WEALTH at work.

If you don’t have time to read the full report, this free download will enable you to read the key findings and actions from the third edition of REBA’s Financial Wellbeing Research 2024 , which explores how employers can build a forward-looking and inclusive financial wellbeing strategy. 

Based on responses from 236 employers including: GSK, Procter &Gamble, Shell Energy Retail, and Standard Chartered Bank, this year’s research explores how factors such as environmental, social and governance, ageing and medical costs are changing behaviours and employers’ approaches to financial wellbeing. 

The report also examines the impact of life events, such as caregiving and divorce, the imminent need for pre-retirement planning and mental health as intertwined drivers of change.

The full report will give you benchmarking data, DEI agenda changes, tax implications, evolving EVPs and a blueprint of the ‘why’ and the ‘how’ for future employee wellbeing success.

About the research

This research was conducted as an online quantitative survey between April and May 2024 among REBA’s membership community and wider database of HR professionals. It achieved participation from 236 predominately medium to large organisations, representing an estimated 1.3 million employees. This approach ensured a broad and diverse set of data, reflecting a cross-section of employer sizes and industry sectors in the UK.

Contributors

Naomi Alexander

Head of reward and recognition, Utility Warehouse

Naomi has been head of reward and recognition for the multi-service provider Utility Warehouse since August 2023. Naomi’s responsibilities include creating a proactive reward and wellbeing strategy for the growing company that supports a broad demographic. Prior to this, Naomi was head of reward at Cazoo and has held other senior reward roles at Boston Scientific, BTG and Arqiva.

Alan Becken

Global employee benefits director, Salesforce

Alan is responsible for Salesforce’s global retirement and financial wellbeing strategy, supporting 80,000 employees across 35 countries. With over 20 years’ experience in both consulting and in-house roles across a variety of industries, Alan is passionate about empowering employees to make sound financial decisions and to feel confident about their financial situation.

Ant Donaldson

Reward manager , Wolseley UK Group

Ant has worked for specialist trade merchants Wolseley UK Group since 2021 in the role of reward manager. His responsibilities include leading on all aspects of employee benefits, pensions and company car schemes across the UK and Ireland. Prior to this, he managed E.ON UK’s reward and benefits activity for several years, including developing the E.ON Group’s first global employee benefits strategy.

Tim Middleton

Director of policy and public affairs, Pensions Management Institute (PMI)

Tim has worked in the pensions industry since 1987. His roleshave covered consultancy with Bacon & Woodrow (now Aon),Mercer and Barnett Waddingham. He works extensively onPMI’s Policy and Public Affairs Committee and provides inputinto the institute’s education and events programmes. He alsowrites for the pensions press. He is a Fellow of the PMI andholds the CII’s Diploma in Financial Planning

Oliver Morley

CEO , Money and Pensions Service (MaPS)

Oliver brings a blend of senior private-sector experience at Reuters, combined with a unique record of change leadership as a CEO in the public sector. 

Oliver is committed to seeing MaPS reach its full potential to help people, particularly those most in need, to make the most of their money and pensions.

Debi O'Donovan

Co-founder & Director, Reward & Employee Benefits Association

I’m Debi and I co-founded REBA in 2015, where I am a director. I enjoy sharing insights, data and information about employee benefits and pay via articles, research, guides and videos because I believe it helps so many employees receive better reward packages than they would if REBA didn’t distribute this knowledge. REBA has a great community and it makes my work fun to talk to the wide variety of people working in reward and benefits through our events, both large and small.

Oluyomi Okunowo

Senior vice-president, total reward and people operations, Wella Company

Oluyomi has worked at beauty leader Wella Company since 2020, and in the role of global head of total reward and people operations since 2022. His responsibilities include total reward, performance management, organisation design and HR systems. Prior to this, he held senior reward and compensation roles at Coty and AstraZeneca among other companies.

Michaela O’Reilly

Head of reward and HR analytics, Ipsos UK

Michaela has been head of HR and reward analytics at Ipsos Mori since 2019, having joined the polling company as reward manager in 2016. Her responsibilities include leading total reward strategies, benchmarking and compensation structures. Prior to this, she was UK pensions manager for American Express and has held pensions roles at Friends First Assurance and Davy.

Head of reward and pensions, Belron UK

Nina has worked at vehicle glass repair and replacement group Belron UK since 2018, holding the role of head of reward and pensions since 2019. She is responsible for the development and delivery of all reward aspects of the people strategy. Prior to this, she held reward roles at Britvic, Sainsbury’s Argos and Philips, among other companies.

Johnny Timpson OBE

Chair , Financial Inclusion Commission

Johnny is a financial inclusion commissioner and has roleswith the Building Resilient Households Group, VocationalRehabilitation Association and the Supporting Healthy Ageingat Work project at the University of Edinburgh Business School.He is currently lobbying for a government-led National FinancialInclusion Commission and an independent Household FinancialSecurity Commission.

Louise Woodruff

Senior policy adviser, Joseph Rowntree Foundation

Louise’s areas of expertise include living standards, pay, employment, forced labour, labour markets, skills, working with employers, services and local government, immigration, and slavery. She studied biological sciences at St. John’s College, Oxford. Her background is in education, having previously worked on developing widening participation activity at the University of Oxford after starting her career as a science teacher.

Jonathan Watts-Lay

Director, WEALTH at work

Jonathan is one of the original founders of WEALTH at work. He has worked with companies across the UK to help their employees improve their financial future through the provision of financial education, guidance and investment advice. He is a recognised commentator on a range of financial matters, from helping employees make the most of their pay and benefits, to planning for retirement.

Related topics

In partnership with WEALTH at work

WEALTH at work is a leading financial wellbeing and retirement specialist - helping those in the workplace to improve their financial future.

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Posthaste: Capital gains tax breaks in the crosshairs in housing affordability report

Ottawa's much-criticized change to inclusion rate is needed to shift the tide

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Posthaste: capital gains tax breaks in the crosshairs in housing affordability report back to video.

The corporate quest for profit via real estate holdings is exacerbating Canada’s rental affordability crisis, according to a report from Canadians for Tax Fairness .

The report, released earlier this week, blamed capital gains and residential real estate investment trust tax policies for “financializing” housing — “increasing ownership by financial actors” —  with the organization suggesting that Ottawa’s much-criticized change to the capital gains inclusion rate is needed to shift the tide.

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“The increasing financialization of housing has contributed to the affordability crisis, and is exacerbated by preferential tax treatment for capital gains and real estate investment trusts (REITs),” Silas Xuereb, a research and policy analyst and author of the study, said in the report.

“The changes to the capital gains inclusion rate proposed by the federal government are critical to counteract the trend by bringing tax rates on capital gains closer to tax rates on other streams of income. Without it, billions in capital gains flow into corporate and investor bank accounts tax free.”

Canada is contending with many housing issues, not the least of which is a rental affordability crisis . During 2023, Xuereb said rents rose eight per cent while wages rose five per cent. More recently, rent increased 8.9 per cent year over year in August even though headline inflation slowed to two per cent, according to the latest consumer price index report from Statistics Canada.

Canadians for Tax Fairness estimates the finance, insurance and real estate (FIRE) sectors have supercharged their real corporate capital gains by 700 per cent via the sale of financial and real estate assets since 2002.

Breaking business news, incisive views, must-reads and market signals. Weekdays by 9 a.m.

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“The rise of capital gains in the FIRE sector reflects the growing role of financial firms in owning and managing other companies and real estate,” Xuereb said.

In particular, the real estate sector collected corporate capital gains worth $22 billion on average in 2021 and 2022, compared with $8 billion annually during the 2010s.

Xuereb said some of that was due to an increase in property values, but he thinks “it also reflects a longer-term trend of rising financial ownership of companies and real estate, which has been incentivized by the partial inclusion of capital gains.”

REITs are the other piece of the rental affordability puzzle for Xuereb.

Financial companies own one-fifth to one-third of housing specifically built to rent, he estimates, with residential REITs holding properties “for the purpose of producing rental income, capital appreciation or both,” a statement he took from one REIT’s financial report.

Income from rents forms part of real estate property values, which are subject to capital gains taxation, Xuereb said. He said this has encouraged residential REITs, which collectively own 200,000 rental units across Canada and are now also purchasing single-family homes, to raise rents above inflation to benefit from capital gains tax rules that subjected only 50 per cent of profits to taxation. Also, increased revenues from higher rents allowed REITs to sell properties at greater values, he said.

Another tax benefit from REITs, Xuereb said, is that income is distributed to investors “without being taxed” and is then taxed at that individual level.

Combining this with the capital gains inclusion rate means “investors pay very little tax even when the majority of REITs’ income comes from rents paid by tenants,” he said. “Given the rise of capital gains in the real estate sector over time, it appears that these forms of tax avoidance are becoming more common as the financialization of housing progresses.”

Ottawa’s latest budget proposed to increase the capital gains inclusion rate for corporations and trusts to two-thirds from one-half (it applies the same rate for individuals on yearly gains exceeding $250,000). The changes were put into effect as of June 25, but the legislation has not been passed yet.

Xuereb’s report makes several suggestions to address the financialization of rental housing, including:

• Building one million non-market homes over the next decade.
• Ending preferential tax treatment for REITs.
• Full inclusion of inflation-adjusted capital gains in taxable income, especially for the finance, insurance and real estate sectors.
• Extending the underused housing tax to apply to properties owned by Canadians, which imposes a one per cent tax on properties that are left vacant.

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The population growth rate continues to grow at a decent pace despite showing signs of a slowdown in the latest quarter, according to Statistics Canada data released Wednesday.

Canada is estimated to have added 250,229 people between April and July this year, which represents a quarterly growth rate of 0.6 per cent, the agency said. This is slower than the growth rate during the same quarters in 2023 and 2022, when the population grew by 334,606 and 253,510 people, respectively. — Naimul Karim, Financial Post

Read the full story here.

• Today’s data: U.S. Bureau of Economic Analysis releases its third revision to second-quarter GDP. Statistics Canada releases data on the Survey Employment Payrolls Hours. The Canadian Federation of Independent Business releases it business barometer for September.
• Earnings: Costco Wholesale Corp.; Canada Jetlines Operations Ltd., Taiga Motors Corp., BlackBerry Ltd.
• Canada’s population continues its strong growth despite signs of slowdown
• Scary family medical histories have this 40ish couple aggressively planning to retire at 50
• Hard earned truth: Passive investing has changed the game

If you’re a business owner whose tax situation is somewhat complex, chances are you hire an accountant to prepare your personal and corporate tax returns. But beware that you are still ultimately responsible for making sure your taxes are done correctly and all your income is fully reported, and you won’t be able to put the blame on your accountant should the Canada Revenue Agency come knocking. Read Jamie Golombek here.

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Biodiversity still a low consideration in international finance: Report

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Biodiversity-related projects have seen an increase in international funding in recent years, but remain a low priority compared to other development initiatives, according to a new report from the Organisation for Economic Co-operation and Development (OECD).

The report found total official development finance (ODF) for such projects grew from $7.3 billion in 2015 to $15.4 billion in 2022. That’s still less than what the nearly 200 governments that signed the Kunming-Montreal Global Biodiversity Framework (GBF) in December 2022 agreed would be needed to halt biodiversity loss: at least $20 billion annually by 2025, and $30 billion annually by 2030.

Government funding made up the bulk of the ODF for biodiversity-related projects in the OECD report, which is welcome news, Campaign for Nature (CfN), a U.S.-based advocacy group, said in a statement .

“We welcome the increase in international biodiversity finance reported in 2022 but that good news is tempered by a range of concerns,” Mark Opel, finance lead at CfN, told Mongabay.

One concern, CfN notes, is that funding specifically for biodiversity as a principal objective declined from $4.6 billion in 2015 to $3.8 billion in 2022. CfN reviewed hundreds of projects from 2022, which formed the source for the OECD’s report, and found that many either had vague descriptions or focused on other policies like agriculture but were counted toward protecting or restoring nature.

“We need to see more emphasis on funding with a primary focus on biodiversity,” Opel said. “So-called ‘principal’ funding that has biodiversity as its primary goal continues to be down since its 2015 peak. Increases in this type of funding are essential to meet the goals of the GBF … These goals cannot be met through funding with biodiversity as only a ‘significant’ goal that mainstreams biodiversity into projects with other primary goals like humanitarian aid or agriculture.”

The report also found that funding for biodiversity-related activities represent just 2-7% of the total ODF portfolio.

“It is concerning that biodiversity considerations still represent a relatively low share of the total official development assistance,” Markus Knigge, executive director of Germany-based nonprofit foundation Blue Action Fund, told Mongabay. He added it was also problematic that most funding came via loans, which have to be repaid, rather than grants, which are often more appropriate for conservation finance.

CfN says grants are preferable to loans because they don’t add to the debt burden of low-income recipient countries.

At the same time, development funding from major donors such as Germany, France, EU institutions, the U.S. and Japan have been cut in recent years.

“We have seen minimal  announcements  of new international biodiversity finance since [the GBF signing],” Opel said. “We estimate that only the equivalent of $162 million annually has been pledged since [then], which doesn’t come close to filling the $4.6 billion gap between the $15.4 billion in 2022 and the $20 billion commitment in 2025.”

Banner image: Javan lutung by Rhett A. Butler/Mongabay.

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