modeling financial crises and sovereign risks
TRANSCRIPT
Modeling Financial Crisesand Sovereign Risks
Dale F. Gray
Monetary and Capital Markets Department, International Monetary Fund,
Washington, D.C. 20431; email: [email protected]
Annu. Rev. Financ. Econ. 2009. 1:117–44
First published online as a Review in Advance on
September 15, 2009
The Annual Review of Financial Economics is
online at financial.annualreviews.org
This article’s doi:
10.1146/annurev.financial.050808.114316
Copyright © 2009 by Annual Reviews.
All rights reserved
1941-1367/09/1205-0117$20.00
Abstract
The complex interactions, spillovers, and feedbacks of the global
crisis that began in 2007 remind us of how important it is to
improve our analysis and modeling of financial crises and sover-
eign risk. This review provides a broad framework to examine how
vulnerabilities can build up and suddenly erupt in a financial crisis,
with potentially disastrous feedback effects for sovereign debt and
economic growth. Traditional macroeconomic analyses overlook
the importance of risk, which makes them ill-suited to examine
interconnectedness, risk transmission mechanisms, and contagion.
After presenting an overview of the key features of the global
2007-2009 crisis, this review discusses new directions for research
on modeling financial crises and sovereign risk, including the need
for integrating risk into macroeconomic policy models and enhanc-
ing early warning system and financial contagion models through a
more comprehensive view of economy-wide risks. Also, new tools
to mitigate and control macro risk need to be developed, along
with new approaches to regulate financial sector risk-taking and
monitor and manage the interactions between private sector and
sovereign risk.
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INTRODUCTION
The global crisis that started in the United States with the subprime credit crisis spread to
major financial institutions, before affecting financial systems and sovereigns across the
globe. The complex interactions, spillovers, and feedbacks remind us of how important it
is to improve our analysis and modeling of financial crises and sovereign risk. Although
the late twentieth century saw a spate of crises in emerging markets (Japan and Europe),
the fact that this latest crisis originated in the United States has shaken confidence world-
wide in U.S. leadership and caused concern about the ability of the largest economy in the
world to save itself, preserve a viable financial system, and avoid serious economic reces-
sion or worse.
This review begins with a brief overview of the history of modeling financial crises
and sovereign risk. The next section is an overview of the crisis of 2007-2009, which
describes key features and market events, the actions of the authorities, and feedbacks
from the markets to the real economy. This is followed by a section on what has been
missing in the measurement and analysis of financial crises and sovereign risk, including
a discussion of the need for better measurement and analysis of risk exposures, balance
sheet risk, interconnectedness, and contagion. I present conceptual frameworks that can
better analyze risk exposures and risk-adjusted balance sheets, along with a critique of
traditional macroeconomic analysis, which overlooks risk analysis in general and credit
risk in particular. I then discuss macro financial risk analysis of interlinked risk-adjusted
balance sheets.
The last section presents new directions for research on modeling financial crises and
sovereign risk. Six areas of future research include unified macroeconomic and risk mod-
els, integrating risk into monetary policy models, new models of early warning and
contagion, new tools to mitigate and control macro risk, new approaches to regulation of
financial sector risk taking, and monitoring and managing sovereign risk.
BRIEF OVERVIEW OF THE HISTORY OF MODELING FINANCIALCRISES AND SOVEREIGN RISK
A good place to start to gain an understanding of financial crisis and sovereign risk is
Charles Kindleberger’s (1978) book, Manias, Panics, and Crashes: A History of Finan-
cial Crisis. Its sober analysis of the history of financial crises and international spillovers
for the past 300 years is as relevant today as it was when it was first published. He
starts with the anatomy of a typical crisis based on the model developed by Hyman
Minsky. (Minsky’s model is in the tradition of classical economists including John
Stuart Mill, Alfred Marshall, and Irving Fisher.) In this type of model, borrowers in-
crease their indebtedness during economic upturns, fueled by cheap credit, to invest in
real estate, stocks, or other investments, which leads to a generalized mania and bubble.
A displacement occurs and if it is sufficiently large that it alters the behavior of the
investors who race out of real or financial assets into money, which turns into a
stampede and triggers a financial crisis. International spillovers can occur via various
channels. Kindleberger (1973) discusses the importance of the lender of last resort
in recovering from the crisis as well as the need for an international lender of last
resort. Kindleberger also investigates various explanations of the causes of the Great
Depression.
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Following the string of crises in the 1970s, economists began a more careful analysis
of the anatomy of crises. Laeven & Valencia (2008) analyze 124 systemic banking
crises, 208 currency crises, and 63 sovereign debt crises. Of these, 42 are considered to
be twin crises (banking and currency crises together), and 10 are classified as triple
crises (banking, currency, and debt crises combined). Currency crises and sovereign debt
crises were most frequent in the 1980s, and banking crises were most common in the
1990s. Causes of the crises include (a) macroeconomic imbalances, (b) bubble or price
collapse, (c) financial panic, (d) moral hazard (from government guarantees), (e) disorderly
debt workout, and (f) contagion or sudden stop (lenders stop rolling over current debt and
restrict new lending).
Models of crises can be placed into one of three generations. The third generation,
which focuses on balance sheet effects, is the product of dissecting the causes of the Asian
financial crisis, whereas the first two were formulated to explain previous generations of
crises. The first-generation models, exemplified by Krugman (1979) and Flood & Garber
(1984), emphasize the role of fundamental economic factors and unsustainable policy in
leading to the abandonment of an exchange rate peg. The central idea is straightforward:
A government cannot continue to run a fiscal deficit financed by money creation while
simultaneously maintaining a credible exchange rate peg. At some point, the country will
run out of foreign exchange reserves and will be forced to abandon the peg. A crucial
nonlinearity in these models is the occurrence of a speculative attack when the reserves
deteriorate to a critical level. This speculative attack corresponds to the crisis event.
A second generation of models came out after the exchange rate mechanism (ERM)
crisis of 1992 and the Mexican crisis of 1994. The primary examples of second-generation
models include Obstfeld (1994), Drazen & Masson (1994), and Cole & Kehoe (1996). In
the second-generation models, as in the first-generation models, fundamental weaknesses,
such as exchange rate overvaluation, play a key role in setting the stage for crisis. In
addition, second-generation models emphasize the importance of policy tradeoffs in re-
ducing the credibility of a peg (in the ERM crisis) and the possibility of self-fulfilling
panics on the part of lenders being the “straw that breaks the camel’s back” (as in the
Mexican crisis). A key feature of second-generation crisis models is the existence of
multiple equilibria, as the onset of a crisis can shift the mood of international lenders in
different directions, allowing for different outcomes.
Third-generation crisis models were formulated in the aftermath of the largely unfore-
seen Asian crisis of 1997-1998. The innovation of third-generation models is the recogni-
tion that problems on the balance sheets of the banking sector, corporate sector, and
government sector, separately or in combination, can play a fundamental role in leaving a
country vulnerable to crisis. In his discussion of third-generation models, Dornbusch
(2001) makes a distinction between old-style or slow-motion crises, based on the financing
of the current account in a financially repressed economy, and new-style crises, which are
spurred by concerns about the balance sheet of a significant part of the economy, public or
private, and its impact on the exchange rate. Doubt about the solvency of one sector can
lead to capital flight. The resulting drawdown on reserves can put pressure on the ex-
change rate and force the abandonment of fixed exchange rates. Dornbusch (2001) goes
on to point out,
There are three primary sources of vulnerability: a substantially misaligned
exchange rate, balance sheet problems in the form of nonperforming loans,
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and balance sheet problems in the form of mismatched exposures. The last of
these sources includes maturity mismatches leading to liquidity issues as well
as currency mismatches. In a situation where the willingness to hold assets on
current terms is impaired – either because there is a question about the
exchange rate or about the willingness and ability of debtors to meet their
liabilities – these misalignments or mismatches become explosive.
Radelet & Sachs (1998) and Rodrik & Velasco (1999) focus on the liquidity-run
aspects of the Asian crisis, in terms of the refusal of foreign banks to roll-over loans to
banks. While relevant, there was clearly more going on than a bank run driven by
balance sheet weakness of banks and skittish investors. In particular, another strand of
the third-generation literature focuses on the role of explicit and implicit government
bail-out guarantees to banks and their role in encouraging over-lending by domestic
banks in foreign currency to domestic firms in the nontraded sector that did not have a
natural hedge in terms of export receipts for currency risk. Two papers that focus in
particular on the role of government bail-out guarantees are Corsetti et al. (1999) and
Schneider & Tornell (2004). In both papers, bail-out guarantees support excess borrow-
ing and lending.
In addition to the preceding groups of papers, which emphasize maturity mismatch
problems and contingent liabilities, respectively, there is a strand of the third-generation
literature that emphasizes the problem of currency mismatch. This group of papers
includes Krugman (1999), Cespedes et al. (2000), Gertler et al. (2001), Aghion et al.
(2001), and Perri et al. (2004). The common theme in these papers is the idea that
currency depreciation can increase the real burden of servicing foreign currency debt and
decrease net worth.
Banking sector liquidity problems occur when normal interbank lending dries up,
leading to a systemic funding liquidity crisis. Fire sale of assets or counterparty risk,
potential or real, can fuel contagion among financial institutions. Similarly, at the interna-
tional level, sudden stops occur when credit to countries dries up, which can have
serious consequences for firms, banks, and sovereigns. There is a set of contributions in
the third-generation literature, exemplified by Calvo (1998), Calvo & Mendoza (2000),
and Mendoza (2002, 2006), that emphasizes the phenomenon of the sudden stop, or
reversal, of capital inflows.
In the 1980s, Japan’s financial liberalization and easy credit led to a situation where
four-fifths of lending was related to property. The Japanese financial crisis followed the
collapse of the bubble in real estate prices in the early 1990s, and undercapitalized
banks responded by restraining lending, which led to a protracted period of deflation and
slow economic growth that lasted for more than a decade. The rise and fall of Japan’s
economy and the financial crisis is described in Katz (1998), Bayoumi & Collyns (2000),
and Hoshi & Kashyap (2000, 2008).
Early warning system (EWS) models were developed in the 1990s in an attempt to find
early warning signals for currency crises and banking crises. Kaminsky et al. (1998) and
Kaminsky & Reinhart (1999) use signal extraction models to try to determine which
variables are precursors to currency and banking crises. Demirguc-Kunt & Detragiache
(1998) found that credit growth, gross domestic product (GDP), bank accounting indica-
tors, and ratio of money supply to foreign currency reserves were good explanatory
variables for the likelihood of a crisis. Berg & Pattillo (1999) compare several EWS
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models and conclude most do not forecast crises, and some, while informative, are not
reliable. An EWS model for banking system risks by Weistroffer & Valles (2008) shows
positive results for in-sample crisis warning but poor performance for out-of-sample
crises. Problems with EWS models include the use of accounting or flow variables that
are backward looking, and the difficulty of defining a banking crisis event.
Traditional sovereign risk models used by rating agencies and macroeconomists rely on
macroeconomic and accounting balance sheet variables. In his book, The Volatility Ma-
chine, Michael Pettis (2001) shows how emerging market sovereigns have inverted capital
structures, in which a shock lowers assets and simultaneously increases liabilities, potentially
causing the debt burden to spiral out of control. Clarke & Zenaidi (2004) estimate a
hypothetical insurance policy that would be needed to cover the cost of a sovereign default,
and Frenkel et al. (2004) provide an overview of sovereign risk and financial crises models.
Gray et al. (2002; 2007a,b; 2008) and Gapen et al. (2005) develop a sovereign contin-
gent claims option theoretic model. They apply modern finance and risk-adjusted balance
sheets, using contingent claims analysis (CCA), to all the key sectors of the economy.
These finance and balance sheet models are integrated with macroeconomic monetary
policy models, dynamic stochastic general equilibrium models, and other macro models
(Gray & Malone 2008).
In modeling financial and sovereign crises, one must not forget we are modeling
systems of human interactions where human behavior can accentuate booms and react to
crises in a way that accentuates the declines. Models of financial behavior are thus
different than models of the physical world. Soros (1998) suggests that markets do not
tend toward equilibrium, but rather, booms and busts are evidence of disequilibrium
influenced by human behavior (what he calls reflexivity).
The understanding of financial crises must take into account global imbalances and
shifting of bubbles from one part of the world to the other. Martin Wolf (2008b) reviews
global financial crises from the 1980s from the perspective of the microeconomics of
finance and the macroeconomics of payment imbalances among countries. Indeed, the
sequence of major crises from the 1980s can be seen as a series of the connected bubbles
shifting from one part of the world to the other. The aftermath of the bursting of the
Japanese property bubble led to Japanese savings “sloshing first into Nordic countries and
then into Asia” (Economist 2009). The financial contagion in the Asian crisis was directly
related to Japan being the largest common creditor to the Asia crisis countries and its
pullback from those countries in 1997. Following the Asian and Russian crises, funds
sloshed next to the U.S. stock market tech boom in the run-up to Y2K. The subsequent
bursting of the tech bubble, and other factors, led to fears of deflation and contributed to
the decision of the U.S. Federal Reserve to sharply lower interest rates. Asian nations—
especially China—have been determined to avoid vulnerabilities of the Asian crisis by
building up large cushions of foreign reserves and running large current account surpluses,
the counterpart of which were large current account deficits of the United States, as well as
the United Kingdom, Spain, and Ireland, all of which had housing bubbles that burst in
2007 (see Reinhart & Rogoff 2009 and Wolf 2008b).
OVERVIEW OF THE CRISIS 2007–2009
The subprime mortgage turmoil that started in mid-2007 has morphed into a severe global
crisis, the most serious since the Great Depression. In 2002–2003, the Federal Reserve
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reduced interest rates to low levels owing to concern about deflation. The low interest
rates fueled credit growth, setting the stage for the eventual crisis. To understand the
origin of the crisis, one must look at the huge growth in what was termed subprime
mortgage lending between 2000 and 2006. Subprime mortgages are mortgages to people
with low incomes and few assets, which allowed them to purchase houses with small
down payments and low initial interest rates. As lending grew, housing prices rose, so
creative ways were devised to offer inviting teaser rates to attract new buyers that were
low for the first two or three years but then increased sharply afterward (see Int. Monet.
Fund 2007, 2008; Zandi 2009).
Initially, the mortgage market was dominated by Freddie Mac and Fannie Mae, two
government-sponsored enterprises (GSEs) who pooled mortgages together in mortgage-
backed securities (MBS) and sold them. This was a profitable business. The mortgage
market structure changed after 2003 as Wall Street firms moved aggressively to issue
private label MBS; these grew from 24% of the market in 2003 to 57% by mid-2006.
The private label MBS expanded into subprime mortgages via securitization, which
pooled a large number of mortgages together in a new structure called asset-backed
securities (ABS). In an ABS, cash flows from the pool of mortgages are allocated to
tranches, dividing up the risk. Cash flows first to the senior tranche (the most secure),
then to the mezzanine tranche, then to the equity tranche. In a typical ABS, for example,
the first 5% of losses are borne by the equity tranche holders, losses between 5% and 25%
are borne by the mezzanine tranche holders, and losses above 25% are borne by the senior
tranche holders (Hull 2008). The senior tranche was designed to be rated AAA and could
be easily sold, and equity tranches were bought by hedge funds or other investors, but
finding buyers of the mezzanine tranche was not so easy. Therefore, financial engineers
devised a new type of ABS by pooling mezzanine tranches of ABS into ABS collateralized
debt obligations (ABS CDOs). Rating agencies continued to provide AAA ratings for many
structured products up to mid-2007.1
The surge in new credit created in this way contributed to the upward spiral of higher
house prices, and eventually to speculation and a bubble in the housing market. Poor
regulation meant discipline in mortgage lending eroded from a loosening of lending
standards (recall the term Ninja loans: no income, no job, no assets). As initial low teaser
rates expired and adjustable rate mortgage interest payments increased, many households
could not afford to pay their mortgages. Eventually, housing price growth slowed and
borrowers owing more than the house was worth, defaulted.
The regulatory rules for banks gave them an incentive to put structured assets into
off-balance sheet vehicles because they avoided having to hold as much capital.
Structured finance and regulatory rules created incentives for regulatory arbitrage,
which allowed for a reduction in the capital cushion across the financial system. Lower
yields for investors in 2003–2006 made it harder to attract investors for the senior
tranches of the ABS CDOs, and so sponsors sought funding solutions by including cheap
guarantees from insurance companies (so-called monoline insurance companies). Banks
holding the senior tranches placed them in off-balance sheet entities such as structured
1Rating agencies earned large fees for rating structured products. This created a conflict of interest and the agencies
came under severe criticism for not being more objective in rating ABS CDOs; their delay in lowering ratings
prolonged the bubble and made the crisis worse when it did come.
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investment vehicles (SIVs) and so-called conduits, as well as in asset-backed commercial
paper (ABCP) vehicles. This strategy of creating such off-balance sheet vehicles was part
of the originate and distribute model that allowed banks to hold less capital than if the
assets were held on-balance sheet. The structured assets placed in these off-balance sheet
vehicles were financed by very short-term funding. The commercial paper market
provided a large portion of this short-term funding. The funding was rolled over every
week, essentially turning loans to these off-balance sheet vehicles into the equivalent of a
short-term deposit.
In another part of the financial system, investment banks (broker-dealers) borrowed short-
term as well. Their financing came from short-term repo or repurchase funding with average
maturity of 40 to 90 days; in fact two-thirds of this funding was being rolled over each week.2
While the crisis started with a credit shock from defaults by subprime borrowers in
mid-2007, there are additional factors that amplified the subprime credit shock and
turned it into such a serious crisis. The beginning of the crisis in 2007 can be thought
of as a run on the parallel banking system. The sufficient conditions for a run are (a) a
negative credit shock from subprime borrowers, (b) illiquid structured credit without
transparent values, (c) very short-term funding of longer maturity assets (maturity transfor-
mation), and (d) lack of a lender of last resort to key institutions in what has grown into
a very sizable parallel banking system (outside the regulated banking world) (Loeys &
Cannella 2008, p. 8).3
The buildup in leverage, financed by wholesale short-term funding, was a key contrib-
uting factor to the severity of the crisis. The leverage in securitized products does not come
from the products but rather from how they are funded (CDOs merely redistribute risk).
By 2007, short-dated funding of longer maturity assets outside of the regulated banking
world were approximately $5.9 trillion.4 Overall, this maturity transformation outside of
the banking world amounted to 40% of total maturity transformation in the U.S. financial
system in 2007 according to the JPM study “How will the crisis change markets?” (Loeys
& Cannella 2008). Yet there was no official lender of last resort to this parallel banking
system. The vulnerabilities were building from 2003 to 2007 but did not erupt into a full-
blown crisis until mid-2007 when lenders stopped providing short-dated funding to SIVs,
conduits, and ABCPs. This was similar to a run.
In the beginning, it was not clear what the exposure of various banks and broker-
dealers was to subprime loans/structured credit. As the crisis progressed, falling housing
prices and mortgage resets made it clear that losses would have to occur, and the magni-
tude was sufficiently large to affect the value of senior tranches of the CDOs. As values of
the mortgage-backed CDO tranches fell, investors reassessed and downgraded their value.
Major banks, who had been keeping the subprime assets off their books in SIVs and
conduits, had to fund these vehicles to replace the short-term funding that had dried up,
2Repo funding is a form of wholesale funding (similar to secured lending) whereby the cash lender receives securities
as collateral for the life of the transaction. “Haircuts” and valuation margins further help insure the lender against
declines in the price of collateral (King 2008).
3Also, in Financial Shock, Mark Zandi (2009) describes how the banks had off-loaded a substantial amount of risk
onto the shadow banking system.
4The $5.9 trillion was composed of (a) broker-dealers funding through repos and customer deposits ($2.2 trillion);
(b) commercial paper issued by ABS issuers, finance companies ($1.4 trillion); (c) auction rate securities ($900
billion); and (d) repo funding by hedge funds ($1.3 trillion).
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and eventually brought them back onto their books, further increasing their (on-balance
sheet) leverage. This created liquidity problems for major banks. Suddenly, banks were
wary of lending to each other, as it was not clear which banks had poorly performing
assets. The result was a generalized hoarding of liquidity. The reaction of the authorities in
mid-2007 was to reduce interest rates and provide liquidity through normal central bank
lending windows and via new facilities. Figure 1 shows the linkage of key risk transfer
between balance sheets at the beginning stages of the crisis in the United States.
Banks began to write off assets and try to raise more capital late in 2007 and 2008, but
capital raising was difficult due to the lack of understanding of who was holding the toxic
assets and the high spreads in the interbank market. Credit default swaps (CDSs) are
insurance contracts against default of a borrower. CDS spreads rose, as there was increas-
ing uncertainty about the impact of the illiquid assets and the riskiness of banks’ balance
sheets.5 Bear Stearns, the second-biggest underwriter of mortgage bonds, suffered a severe
liquidity crisis in March 2008. The Federal Reserve provided financing via an arrangement
whereby JP Morgan Chase bought Bear Stearns for only $240 million, a 98% discount to
its book value. The Federal Reserve provided support to the transaction, buying as much
as $30 billion of Bear Stearns’ less-liquid assets. This was to avert a chain reaction of
counterparty failures in the credit derivatives market, in which Bear Stearns was a signif-
icant player. Treasury Secretary Paulson defended the bailout, indicating that moral haz-
ard concerns are trumped by the need to preserve financial stability. Following the Bear
Stearns rescue, markets calmed in May and June 2008, as market participants believed
that there now was a lender of last resort for broker-dealers and other too-interconnected-
to-fail institutions.
In July 2008 it became evident that the mortgage defaults were affecting Freddie Mac
and Fannie Mae. On September 11, 2008, financial markets and the rating agencies
decided that Lehman Brothers was near bankruptcy. During the next weekend, the U.S.
Treasury tried to arrange financial support but decided not to participate in a bailout or
facilitate an orderly workout for Lehman. AIG was also in discussions with the authorities
for emergency help during the same weekend. Lehman declared bankruptcy on September
14, 2008, which by a factor of six was the largest bankruptcy in the history of the world
(Rotman Sch. Manag. 2008, p. 7).
The next day, the Dow closed down more than 500 points (-4.4%), for its worst one-
day point drop since September 2001. Market concerns about AIG revolved around the
possibility of its failing to meet obligations on CDS insurance protection it had sold for
structured products. In an unprecedented action, the Federal Reserve agreed to provide an
$85 billion loan to AIG in exchange for an 80% stake in the troubled insurer.
Prime money market funds (MMFs) that held the $4 billion Lehman commercial paper
and $20 billion short-term debt had to write down these assets when Lehman went
bankrupt. This led one MMF to “break the buck,”6 which shook confidence in the
supposedly safe prime MMFs and prompted intense redemption pressures from institu-
tional investors. Falling confidence led to a precipitous pull back from MMFs, engender-
ing a downward spiral in confidence in the financial system.
5CDS spreads increased as did the skew in equity options of major banks as investors tried to hedge the uncertainty
surrounding asset values and risks of a spiral of losses from fire sales of semiliquid assets (Gray & Malone 2008).
6Breaking the buck refers to closing with a net asset value less than $1.
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The Treasury moved to get bipartisan approval from congress for a $700 billion rescue
package to buy bad debts for ailing banks, the Troubled Asset Relief Program (TARP).
However, at the end of September, members of the House of Representatives shocked the
world by rejecting the rescue plan. World stock markets plunged, wiping out $1 trillion in
market value. The crisis rapidly spilled over internationally. Several banks in the United
Kingdom, Belgium, and other countries were taken over by their governments. Depositors
started a run on an Icelandic bank, the Icelandic Krona fell by more than 60%, and the
three largest Icelandic banks had to be nationalized, triggering a sovereign debt crisis
(Iceland had a triple crisis). The speed of the global spillovers from the Lehman default
and rejection of the U.S. rescue plan was stunning. “That fateful week proved to the world
that the United States was unable to provide decisive leadership or take decisive action to
deal with the crisis” (Rotman Sch. Manag. 2008, p. 7). Representatives returned to
Washington and approved the rescue plan on October 3, but the damage had been done.
Emerging stock markets plummeted. Flight to safety and extremely low-risk appetite was
destabilizing banks and sovereigns around the world. The countries that were overlever-
aged with bank assets multiple times the size of their GDP (e.g., in Iceland where bank
assets were 10 times GDP) could not afford to bail out their banking system, and thus
credit to the sovereign was withdrawn. In such cases, exchange rates plummeted and
sovereign CDS spreads skyrocketed. Iceland and a number of emerging market countries
quickly went to the International Monetary Fund (IMF) for help and rescue programs
Risky MortgageDebt
Net WorthRealEstate
Non-Prime Households
Interlinkage of Household, RMBS, GSE, Broker Dealers, Bank CCA Balance Sheets (up to mid-2007)
Debt &QualifyingMortgageGuarantees
EquityMortgagePools
Other FinancialAssets
Govt. ImplictGuarantee toGSE Creditors
GSE
NetWorth
Risky MortgageDebt
RealEstate
Prime Households
RMBS
Senior
Mezz
EquityRMBS
IntermediaryRMBS CDO
Risky Debt and Deposits
EquityAssetsLoansContingentCredit Lines to SIVsOther AssetsDeposit Guarantee
Bank
Risky Debt
Equity
SIV &ABCP
Short-term CommercialPaper Wholesale Market Funding
Risky Debt
Repo and Secured Financing
EquityEquities
Derivatives
Other Assets
Inventory of unsold CDOtranches
Security Broker Dealers
Short-termRepo Market Funding
Repo
EquityAssets
Hedge Funds
Figure 1
Interlinkage of household, RMBS, GSE, broker dealers, bank CCA balance sheets (up to mid-2007).
www.annualreviews.org � Financial Crises and Sovereign Risks 125
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were negotiated. An emergency G-20 meeting was held in November to address the global
crisis. U.S. interest rates were cut to zero in December. Worldwide losses from securitized
assets and bad loans were projected to reach $4.1 trillion by the end of 2010 as the
recession and credit crisis exact a higher toll on financial institutions (Int. Monetary Fund
2009a).
The September and October panic and extreme risk aversion led consumers, compa-
nies, and the authorities to expect a global credit contraction and severe economic reces-
sion. By the first quarter of 2009, global economic activity was projected to contract by
1.3% in 2009, with advanced economies expected to contract by 3.8% in 2009 (Int.
Monetary Fund 2009b). As pointed out by Wolfgang Munchau of the Financial Times,
It is not too difficult to construct a plausible scenario for an economic catas-
trophe. Pick some of the following and you could end up with a depression
that beats every modern record: a rise in global protectionism; competitive
currency devaluations; a sterling crisis; social unrest in China; refusal by
eurozone leaders to coordinate; a payment default by large sovereign in the
eurozone; an acute emerging market crisis; continued lack of synchronization
of monetary policies; or a collapse of the CDS market (Munchau 2008).
Across the globe, people asked how such a crisis could have happened. A sober analysis
was provided by Martin Wolf (2008a):
We need to ask ourselves whether we could have done a better job of under-
standing the processes at work. The difficulty we had was that we all look at
one bit of the cliched elephant in the room. Monetary economists looked at
the monetary policy. Financial economists looked at risk management. Inter-
national macroeconomists looked at global imbalances. Central bankers fo-
cused on inflation. Regulators looked at Basel capital ratios and then only
inside the banking system. Politicians enjoyed the good times and did not ask
too many questions.. . . One big lesson of this experience is that economics is
too compartmentalized and so, too, are official institutions. To get a full sense
of the risks we need to combine the worst scenarios of each set of experts.
Only then would we have had some sense of how the global imbalances,
inflation targeting, the impact of China, asset price bubbles, financial innova-
tion, deregulation and risk management systems might interact.
WHAT HAS BEEN MISSING IN THE MEASUREMENTAND ANALYSISOF FINANCIAL CRISES AND SOVEREIGN RISKS?
What are needed are better frameworks to model macro financial risk transmission,
macroeconomic flows, and financial and sovereign risks in an integrated way. Martin
Wolf talks about monetary economists, financial economists, international macroecono-
mists, central bankers, regulators, and politicians. What is clearly missing from this list are
macro financial risk economists.7 Where were the macro financial risk experts that work
7The financial economists he mentioned looked at risk management, but he is referring primarily to private sector
risk managers at the level of the individual financial institution.
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(or should have been working) for the central banks, ministries of finance, regulatory
bodies, and international institutions; the ones who should be constantly measuring and
analyzing (a) risk exposures and risk-adjusted balance sheets at the aggregate sector and
sovereign level, including off-balance sheet risks in the system; (b) the integration of
financial sector risks with monetary policy models; and (c) financial contagion and inter-
connections? To mitigate and manage financial sector risk and sovereign risk, new tools
and regulatory frameworks are needed.8 Below is a closer look at what has been missing in
the areas mentioned above.
Risk Exposures and Risk-Adjusted Balance Sheets
Traditional macroeconomic and banking models do not adequately measure risk expo-
sures of financial institutions and sovereigns and cannot be used to understand the trans-
mission and amplification of risk within and among balance sheets in the economy.
Traditional macroeconomic analysis of the government and central bank is almost entirely
flow- or accounting balance sheet–based. Sovereign debt analyses focus on debt sustain-
ability (stocks and flows). A fundamental point is that you cannot get a risk exposure,
which is forward-looking, from an accounting balance sheet or from a flow of funds.9 A
risk exposure measures how much can be lost during a forward-looking horizon period
with an estimated probability.
EWS models have failed. The inputs to these models are overwhelmingly accounting or
macro variables that are backward-looking. Forward-looking market information is rarely
used for EWS models or modeling crises.
One key risk that macroeconomists have left out of their models is default risk. As
pointed out by Charles Goodhart, “the study of financial fragility has not been well served
by economic theory. Financial fragility is intimately related to probability of default.
Default is hard to handle analytically being a discontinuous, nonlinear event so most
macro models. . .transversality assumptions exclude the possibility of default” (C. Goodhart,
presentation at IMF, 2005). Default risk models and risk-adjusted balance sheets are needed to
analyze financial fragility, including that of the sovereign. Not only is there an absence
of credit risk modeling in macroeconomics, but there is also an absence of models that
integrate credit, market, and liquidity risks into financial and sovereign crisis models into one
framework.
Short-term funding of illiquid assets is a crucial aspect of vulnerability. Tony Jackson of
the Financial Times pointed out that, according to Bagehot, “the only securities which a
banker, using money that he might be asked on short notice to repay, ought to touch, are
those which are easily saleable and easily intelligible. . . .Off-balance sheet vehicles were
funded in short-term money markets; and the fact that [banks’ funds] were invested in the
most obscure kind of [unintelligible] credit derivatives would have struck him as mad”
(Jackson 2008). Short-term repo transactions and other short-term funding sources fi-
nanced the broker-dealers (major parts of the parallel banking system) to an unprece-
8This is similar to what some central bankers call a macroprudential approach to financial stability.
9Robert C. Merton (2002) pointed out that “country risk exposures give us important information about the
dynamics of future changes that cannot be inferred from the standard ‘country accounting statements,’ either the
country balance sheet or the country income flow-of-funds statements.”
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dented degree in the buildup to the crisis of 2007-2009. Risk-adjusted balance sheets need
to account for all types of risks, including funding risk and credit risk.
In many crises, the buildup and bursting of a bubble in the residential or commercial
real estate market was the underlying cause of the financial crisis. Frequently, the
bursting of the real estate bubble was transmitted to the financial system and, ultimately,
to the sovereign and the rest of the economy through off-balance sheet entities or other
third-party entities such as affiliates and/or subsidiaries. In Japan, risk was transmitted
by affiliates and subsidiaries of parent banks; in Sweden, it was transmitted by related
finance companies; and in the 2007-2008 U.S. credit crisis, it occurred largely by off-
balance sheet SIV conduits. Lack of transparency about the financial condition of these
off-balance sheet or related entities (their leverage, maturity, and currency profile, etc.)
was a major factor in allowing the risk buildup that triggered the crisis. Just as banking
regulators have missed the risk transmission from undercapitalized off-balance sheet
vehicles, macroeconomists have missed the risk transmission to the public balance sheet
from the government’s undercapitalized off-balance entities and large contingent liabil-
ities, such as GSEs.
Integration of Financial Sector and Sovereign Risk Indicators inMonetary Policy Models
Traditional monetary and macroeconomic models omit key risk indicators, especially
forward-looking, market-based measures of financial sector risk. In reality, however, cred-
it risk indicators derived from the sovereign risk-adjusted balance sheets affect interest
rates, growth, and exchange rates. Not including such risk indicators in monetary policy
models may contribute to fueling the growth of bubbles and potentially suboptimal policy
choices.
Interconnections, Contagion, and Destructive Feedback Loops
Financial institutions and policy makers have not focused in a comprehensive way on
assessing the interconnectedness within financial institutions and financial markets. Con-
tagion can occur through several channels. Market and liquidity risk can lead to credit risk
in financial institutions. A rise in system-wide counterparty risk,10 which is a combination
of credit risk and liquidity risk, induces the risk of fire sales of assets, leading to broader
implications for all financial institutions holding similar assets on their balance sheets.
Reduced risk appetite among investors and a rush to safer government securities would
further result in contagion. Regulators, governments, and central banks have not focused
enough on interconnectedness between financial sector risk exposures and sovereign risk
exposures and their potential interactions and spillovers to other sectors in the economy or
internationally. Frameworks for analyzing cross-border liquidity and contagion need im-
provement.
10The crisis has made it clear to many risk managers, regulators, and policy makers that counterparty risk coming
from the credit default swap (CDS) market needs to be addressed. The introduction of a central clearing house is
being put in place.
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There should be more emphasis on the use of system-wide stress testing approaches to
evaluate vulnerabilities and the potential impact of destructive feedback loops. Improve-
ments are needed in modeling destabilization processes and what Robert Merton calls
“destructive feedback loops” caused by situations where a guarantor provides a guaran-
tee, with obligations the guarantor may not be able to meet precisely in those states of the
world in which it is called on to pay (Merton 2008).
From a global perspective, new models integrating macroeconomic trade and growth
models with international risk sharing and financial risk transfer are needed. The spillover
of the financial crisis globally to other developed countries and emerging markets, at a
time when they were beginning to participate in the free market global system, threatens
to induce protectionist behavior.
What Conceptual Frameworks Can be Used to Better Analyze Risk Exposuresand Risk-Adjusted Balance Sheets?
The conventional models and analytical tools used by central banks and government today
are ill-suited for analyzing risk exposures. To understand what conceptual frameworks are
needed, it is useful to understand the differences in the conceptual frameworks of macro-
economics versus those of finance. Macroeconomists frequently focus on forecasts of the
mean value of macro variables (i.e., the first moment). Stocks, flows, and macroeconomic
accounting variables change over time in a way that past values of the variable can be used
to help forecast future values.
Finance models focus more on variables, particularly asset prices, which follow
random walk processes. The changes in asset prices are very different from the changes
in stock/flow and typical macroeconomic variables. New information arrives and is
incorporated into prices, so the price at time t is uncorrelated with the price at t-1. Many
problems in finance and risk analysis involve how an asset price evolves relative to a
threshold or barrier and, more specifically, the probability that the asset price hits the
threshold or barrier within a certain time horizon. An important determinant of risk is
volatility (or second moment). Typical risk measures, such as value-at-risk (VaR), ex-
press the probability that the price of an asset will be below a particular threshold at a
given time.
CCA can help central banks analyze and manage the financial risks of the econo-
my. A contingent claim is a financial asset whose future payoff depends on the value
of another asset. The prototypical contingent claim is an option—the right to buy or
sell the underlying asset at a specified exercise price by a certain expiration date. A
call is an option to buy; a put is an option to sell. The important point is that the
underlying asset follows a random walk relative to a barrier or threshold. CCA is a
generalization of the option pricing theory pioneered by Black & Scholes (1973) and
Merton (1973). When applied to the analysis and measurement of credit risk, CCA is
commonly called the Merton model (see sidebar on Pricing Contingent Claims and
Risk Exposures).11
11See Merton (1973, 1974, 1977, 1992, 1998). Initially developed for valuation of corporate firms, CCA has been
adapted to financial institutions and sovereigns.
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The basic analytical tool is the risk-adjusted balance sheet, which shows the sensitivity
of the enterprise’s assets and liabilities to external shocks. At the national level, the sectors
of an economy can be viewed as interconnected risk-adjusted balance sheets with portfo-
lios of assets, liabilities, and guarantees—some explicit and others implicit. Traditional
approaches have difficulty analyzing how risks can accumulate gradually and then suddenly
PRICING CONTINGENT CLAIMS AND RISK EXPOSURES
The core concept of contingent claims derives from option pricing techniques.
Merton Model Equations for Pricing Contingent Claims
The total market value of assets at any time, t, is equal to the market value of the claims on the assets,
equity, and risky debt maturing at time T:
Assets ¼ Equityþ Risky Debt
AðtÞ ¼ JðtÞ þDðtÞAsset value is stochastic and in the future may decline below the point where debt payments on scheduled
dates cannot be made. The equity can be modeled and calculated as an implicit call option on the assets,
with an exercise price equal to the promised payments, B, maturing in T-t periods. The risky debt is
equivalent in value to default-free debt minus a guarantee against default. This guarantee can be calculated
as the value of a put on the assets with an exercise price equal to B.
Risky Debt ¼ Default-free Debt�Debt Guarantee
DðtÞ ¼ Be�rðT�tÞ � PðtÞWe omit the time subscript at t = 0.
The value of the equity is computed using the Black-Scholes-Merton formula for the value of a call:
J ¼ ANðd1Þ � Be�rTNðd2Þ
d1 ¼ln A
B
� �þ rþ s22
� �T
sffiffiffiffiT
p and d2 ¼ d1 � sffiffiffiffiT
p;
Where r is the risk-free rate, s is the asset return volatility, and N(d) is the cumulative probability of the
standard normal density function below d.
The yield to maturity on the risky debt, y, is defined by
D ¼ Be�yT
y ¼ ln B=Dð ÞT
;
and the credit spread is s ¼ y � r ¼ �1/T(ln(1-Put Option/(Bexp(-rT))).
The risk-neutral or risk-adjusted default probability is N(�d2).
Example: Assuming that A = $100, s = 0.40 (40%), B = $75, r = 0.05 (5%), and T = 1 (one year), the value
of the equity is $32.367 and the value of risky debt is $67.633; the yield to maturity on the risky debt is
10.34% and the credit spread 5.34%. The risk adjusted probability of default is 26%.
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erupt in a full-blown crisis. The CCA approach is well-suited to capturing such non-linear-
ities and to quantifying the effects of asset-liability mismatches within and across institu-
tions. Risk-adjusted CCA balance sheets facilitate simulations and stress testing to evaluate
the potential impact of policies to manage systemic risk.
Balance sheet risk is the key to understanding default risk and crisis probabilities.
Default happens when assets cannot service debt payments. Uncertain changes in future
asset value, relative to promised payments on debt, is the driver of default risk. When
there is a chance of default, the repayment of debt is considered risky, to the extent that it
is not guaranteed in the event of default (risky debt = risk-free debt minus guarantee
against default). The guarantee can be held by the debt holder, in which case it can be
thought of as the loss in the case of default (as in the case of uninsured subordinated debt
holders) or by a third-party guarantor, such as the government (for example, bank deposits
are often partially guaranteed by a state deposit insurance, such as the Federal Deposit
Insurance Corporation in the United States). The value of such government guarantees can
be measured with implicit put options (Merton 1977).
The values of the contingent claims on the CCA balance sheets contain embedded
implicit options that can be used to obtain measures of risk exposures. These include
risk exposures in risky debt, probabilities of default, distance-to-distress, the expected loss
(i.e., the value of the implicit put option), spreads on debt, and the sensitivity of the
implicit options to the change in the underlying asset and other measures (such as the
delta or gamma of the implicit put option). The implicit put option increases in a nonline-
ar way as the market value of the sector’s assets decline (see Draghi et al. 2003).
The market value of assets of corporations, financial institutions, or sovereigns cannot
be observed directly, but it can be implied using CCA. From the observed prices and
volatilities of market-traded securities, one can estimate the implied values and volatilities
of the underlying assets.12 Domestic equity markets provide pricing and volatility infor-
mation for the calculation of implied assets and implied asset volatility in corporate, bank,
and nonbank financial institutions. Also, in some cases, asset and asset volatility can be
estimated directly and can be used to calibrate risk-adjusted balance sheet models.
Figure 2 illustrates the key relationships between changes in balance sheet assets, asset
volatility, and changes in the distress/default barrier due to changes in short- and long-
term debt and funding liquidity. The uncertainty in asset value is represented by a proba-
bility distribution at time horizon T. At the end of the period, the value of assets may be
above the promised payments, indicating that debt service can be made, or below the
promised payments, leading to default. In periods of high market liquidity, short-term
debt can be easily rolled over and thus the effective default barrier is lower. This is shown
in Figure 2a.
However, in periods of stress, asset values are lower, and if assets are illiquid there is a
risk they might need to be sold at a sharp discount (in the case of marketable assets) or
contain a higher default risk (in the case of loans). This case is shown in Figure 2b. The
probability distribution of the assets shows a risk of a sharp decline (fat tail). Simulta-
neously, the ability to rollover debt has most likely evaporated, due to lenders’ uncertainty
about the viability of the particular borrower and/or general market tightness, because
there is a system-wide reluctance to rollover existing debt or make new credit available,
12An implied value refers to an estimate derived from other observed data. Techniques for using implied values are
widely practiced in options pricing and financial engineering applications (see Bodie et al. 2009).
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which results in more short-term debt and a higher default barrier.13 The combination of
changes in the probability distribution of assets and the higher default barrier means that
the probability of default and credit spreads are much higher than in the calm situation.
This way of looking at risk-adjusted balance sheets applies to financial institutions and to
sovereigns (as well as corporations and households). An important analysis by Khandani,
Lo, & Merton (2009) shows how the refinancing ratchet effect in U.S. household balance
Asset Value
Distributions of Asset value at T, when there ishigher asset uncertainty and risk assets could besharply lower
Distress Barrier including higher interestpayments and without being able to roll-overold debt or obtain new debt
A0
T Time
High Probability of Default, much HigherCredit Spreads
Asset Value
Distributions of Asset value at T, inCalm Periods with Easy Funding Liquidity
Lower “Effective” DistressBarrier with ample FundingLiquidity” i.e. rolloveroption can be “exercised”
A0
TTime
Low Probability of Default, Very Low Spread
Figure 2
Assets and distress barrier in (a) calm and (b) crisis periods using the contingent claims risk-adjusted balance sheet concepts.
13The default barrier, which is the amount of liabilities that assets can cover in the case of default, is typically
estimated as short-term debt and a fraction of long-term debt.
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sheets increases mortgage default correlation and leads to higher systemic risk and very
large losses.
Figure 3 is an illustrative four-sector model of an economy with interlinked risk-adjusted
balance sheets for the financial sector, sovereign, as well as corporate sector and household
real estate sector. The risky debt of each sector is the default-free value debt minus the
implicit debt guarantee (implicit put options). The (explicit or implicit) financial guarantee
of the government to the financial sector is modeled as an implicit put option as well.
ASSETS LIABILITIES
CORPORATE SECTOR
HOUSEHOLD REAL ESTATE SECTOR
FINANCIAL SECTOR
SOVEREIGN (Government and Monetary Authorities)
Foreign Currency Reserves
Net Fiscal Asset(PV of taxes minus expenditures)
Other Public Assets
Household Real Estate Assets
Corporate Assets(Present Value of Profits plus
Other Assets)
Default-free Value of Debt minus
Default-free Mortgage Debt minusImplicit GuaranteeNet Equity in Home
Deposits and Debt(minus Implicit Debt Guarantees
not Covered by GovernmentFinancial Guarantees)
Implicit Guarantee
Equity
Equity
Loans and other Assets(including loans to corporates,
households and sovereign)
Government Financial Guarantees
Government FinancialGuarantees
Default-free Value of Foreign-currency Debt minus Implicit
Guarantee
Default-free Value of Local-currency Debt minus Implicit
Guarantee
Base Money
Figure 3
Four-sector interlinked balance sheets model of an economy.
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Risk transmission and feedbacks can occur through a number of channels. The corporate
sector’s financial distress—possibly caused by stock market decline, recession, and commodity
price drops—can be transmitted to the financial sector. If the value of the assets of the
corporate sector declines, so does the value of the risky debt (and equity), which leads to a
decline in bank assets and an increase in banking sector credit risk. A decline in house prices
and default on mortgage payment, including via MBS and structured products, transmit risk
to the financial sector in a similar manner. The banking assets are affected by the changes in
the embedded put options in risky loans to the borrower.
A vicious destructive feedback loop could arise in the situation in which the financial
system is large compared with the government, and distress in the financial system triggers
government financial guarantees. Potential costs to the government, due to the guarantees,
lead to a rise in sovereign spreads. Banks’ spreads depend on (a) retained risk, which is
lower given the application of government guarantees, plus (b) the government spread
because investors view the bank’s and sovereign risk as intertwined. Concern that the
government balance sheet will not be strong enough for it to make good on guarantees
could lead to deposit withdrawals or a cutoff of credit to the financial sector, triggering a
destructive feedback where both bank and sovereign spreads increase. In some situations,
this vicious cycle can spiral out of control, resulting in the inability of the government to
provide sufficient guarantees to banks and leading to a systemic financial crisis and a
sovereign debt crisis.
Fiscal, banking, and other problems can cause distress for the government, which can
transmit risk to holders of government debt. Holders of foreign-currency debt have a claim
on the value of the debt minus the potential credit loss, which is dependent on the level of
assets of the sovereign (in foreign currency terms) compared with the foreign-currency
default barrier. A sudden stop in accessing foreign funding (inability to rollover short-term
debt and to borrow) can dramatically increase credit spreads for the sovereign and for
banks. A vicious spiral of devaluation, high bailout costs for banks, and inability to borrow
can lead to default of both banks and the sovereign.
Econometric models can be combined with the CCA models. For example, factor
models can be used where domestic and foreign factors (GDP, interest rates, commodity
prices, etc.) are the dependent variables used to explain components of the CCA model
(such as changes in assets) and the effect on risk indicators (Crouhy et al. 2000, Gray &
Walsh 2008).
It is important to note that the traditional macroeconomic flow-of-funds can be recov-
ered from the CCA equations when uncertainty in the balance sheets is ignored. When the
volatility of assets in the CCA balance sheet equations is set to zero, the values of the
implicit put options go to zero.14 The result is the accounting balance sheet of the sectors.
The flow-of-funds can thus be seen as a special deterministic case of the CCA balance
sheet equations when volatility is set to zero and annual changes are calculated. Note that
it is the implicit put options in risky debt and contingent liabilities that allow for risk to be
transmitted among sectors in the CCA model. Without volatility the risk transmission
between sectors is lost.
14If the volatility of assets goes to zero, the implicit put option values in the sectors go to zero. If volatility goes to
zero, the value for the junior claim of the representative sector then reduces to the accounting balance sheet (see
Gray & Malone 2008 for details).
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NEW DIRECTIONS FOR FUTURE RESEARCH ON MODELINGFINANCIAL CRISES AND SOVEREIGN RISK
The ultimate goals of these new directions for future research are to improve the measure-
ment, analysis, and management of financial sector and sovereign risk, and to reduce the
severity and frequency of sovereign and financial crises. Six new directions for further
research are outlined below.
1. Unified Frameworks that Integrate Risk and Risk-Adjusted Balance Sheetswith Macroeconomic, Monetary Policy, and Interest Rate Models
An integrated CCA-macroeconomic model for vulnerability and policy analysis can be
used to examine the interactions among financial sector risks, monetary policy, fiscal
policy, and debt management. Figure 4 shows an example of a unified macrofinance
framework. Interlinked risk-adjusted balance sheets of key sectors use forward-looking
information from several markets (equity, fixed income, interest rate, and foreign currency
markets) to calibrate risk-adjusted balance sheets. The risk-adjusted balance sheets are
interlinked via risk exposures modeled with contingent claims, and thus provide a risk
accounting framework for the economy. Corporate and household risk-adjusted balance
sheets are linked to the financial sector. Financial system risk indicators, derived from the
aggregated financial sector CCA-type model, and the sovereign risk indicators, derived
Unified Macrofinance Framework (Targets: Inflation, GDP, Financial System Credit Risk,
Sovereign Credit Risk)
Sovereign CCA Balance
Sheet Model
Monetary Policy Model
Interest Rate Term Structure
Financial System Credit Risk IndicatorFinancial
Sector CCA
Model
• Fiscal Policy
• Debt Management
• Reserve Management
• Policy Rate
• Liquidity Facilities
• Quantitative Actions
• Capital Adequacy
• Financial Regulations
• Economic Capital
Fiscal and Debt Policies:
Guarantees
Financial Stability Policies:
Sovereign Credit Risk Indicator
Monetary Policies:
Household CCA
Balance Sheet(s)
Corporate Sector CCA
Balance Sheet(s)
Sovereign Equity Claims (from Capital Injections)
Global Market Claims
on Sovereign
Figure 4
Unified macrofinance framework.
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from the CCA sovereign model, are included in the monetary policy (or similar macroeco-
nomic) model. Guarantees to the financial sector, and any government equity claims, are
key risk transmission channels.
This type of framework is integrated to analyze the financial stability, monetary, fiscal,
debt, and reserve policies together to understand the impact on inflation, growth, financial
sector risk, and sovereign risk. The monetary, financial sector, and sovereign sector com-
ponents are discussed in more detail below.
2. Integrating Financial Sector and Sovereign Risk into Monetary Policy Models
An important area of research going forward is to integrate financial risk indicators into
monetary policy models used by the central bank to set interest rates and other monetary
policy measures. Market-based financial sector stability indicators summarize the effects
of both the credit/lending channel and credit risk transmission from distressed borrowers
in the economy. These indicators can provide information on the banking sector’s financial
condition, which is related to the quantity of credit extended and the possible or expected
effects of this channel on the real economy and GDP (credit expansion and the financial
accelerator). These risk indicators also capture the distress in the financial sector when
borrowers default in periods of economic distress. This is a reflection of the economic
condition of borrowers and of the real economy.
Because the economy and interest rates affect financial sector credit risk, and the
financial sector affects economic growth, it is important to include market-based financial
stability indicators in monetary policy models.15 Similarly, risk indicators for the sovereign
(e.g., credit spreads on sovereign debt) have an impact on interest rates and on exchange
rates, so it is important to include these indicators in the monetary policy model as well.
Including an aggregate credit risk indicator in the GDP gap equation and testing whether
the coefficient is significant is an important first step to achieving a better understanding
of how the financial sector credit risk affects GDP. An important question is whether the
central bank should include explicitly financial stability indicators in the interest rate
reaction function.16 The alternative would be to react only indirectly to financial risk by
reacting to inflation and GDP gaps because they already include the effect financial factors
have in the economy. Not including the risk indicators results in misspecification error and
suboptimal policy choices.
3. Toward New Models of Early Warning, Financial Contagion,and Interconnectedness
Better EWS models and frameworks for analyzing financial contagion are needed. One
purpose of EWS exercises is to identify vulnerabilities in time to take remedial action to
prevent crises or make them less severe should they occur.
15A typical monetary model consists of an equation for the output gap (IS), an equation for inflation (Phillips curve
or aggregate supply), an equation for the exchange rate (interest parity condition), a yield curve relating short- and
long-run interest rates, and the Central Bank interest rate reaction function (Taylor rule). Indeed, the primary tool
for macroeconomic management is the interest rates set by the central bank as a reaction to the deviations of
inflation from the target and the output gap (Taylor 1993). An example of this approach is described in Gray et al.
(2008).
16A related literature examines to which extent asset bubbles should be included in monetary policy models.
136 Gray
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Multiple tools and frameworks should be investigated and developed. The CCA ap-
proach could be extended in several directions:
� Risk-adjusted balance sheets, which capture forward-looking information (from equity,
credit, interest rate, FX, and other markets) provide key ingredients for EWS models.
Multivariate probit and signal extraction models can be improved by inclusion of these
variables. Similarly, regime switching models used in financial econometrics are power-
ful tools that can enhance and improve EWS-type tools.� Equity option-based, risk-adjusted balance sheets are a promising area of research on
financial contagion. Information from equity options can be used to measure tail risk
(risk of sharp drop in equity prices) and tail-risk correlation and dependence structure
among different financial institutions which measures systemic risk (Gray & Jobst
2009b,c). Equity options are liquid, contain forward-looking information, seem to lead
CDS spreads, and are not affected by financial guarantees (debt and CDS spreads are
reduced after the imposition of government guarantees, diminishing their usefulness as
measures of financial contagion).� Stress-testing, risk-adjusted balance sheets are another important component of any
EWS framework. This framework uses calibrated risk-adjusted balance sheets along
with stochastic process models for key prices (interest rates, exchange rates, etc.) and
macro variables that are stressed and shocked to try to understand how risk amplifica-
tions, feedbacks, and destabilization mechanisms could produce financial crises and/or
sovereign crises. This approach recognizes that the accurate prediction of the crisis is
difficult, if not impossible, and adopts stress testing approaches to evaluate areas of
weakness and the potential magnitude of risk exposures—i.e. the potential size of the
house of cards.� New models are needed to analyze interconnectedness and financial contagion among
banks, financial institutions, and countries. This includes improved models, frameworks
to analyze cross-border banking, and financial sector risk and sovereign risk. Network/
contagion models and ideas borrowed and adapted from other fields, including epide-
miology, network models, econophysics, power grid, and complex stochastic process
models, are promising new areas of investigation. Networks and interconnections can be
within an economy, between different economies, between banks and sovereigns, between
sovereigns, or many other possible combinations.
4. New Tools and Techniques to Mitigate, Control, and Transfer Risk
Important new directions in the analysis and management of financial crises and sovereign
risk depend on developing new tools and techniques to mitigate, control, and transfer risk
in the economy. Once identified, risk can be managed in several ways, including by
changing the financial structure of a firm (capital/equity, liabilities, or assets), transferring
it to other entities (diversification, hedging, and insurance), or mitigating it through
guarantees or longer run changes in institutional structure (see Figure 5). Gray & Malone
(2008) discuss ways to mitigate, control, and transfer risk among the government, central
bank, and financial institutions in terms of the management of default risk and the
managing guarantees to the financial sector.
Alternative risk transfer (ART) products combine insurance products with derivatives
to facilitate risk management in innovate ways. Such contracts have been pioneered by
www.annualreviews.org � Financial Crises and Sovereign Risks 137
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insurance and reinsurance firms for use by large banks and firms, and have the potential to
play an important role in financial sector and sovereign risk management. The CCA
approach can be used to determine if hedging contracts or insurance agreements will help
improve the risk profile and how these should be priced.
A guarantor can manage the risks of guarantees in the following ways: (a) monitoring,
(b) asset restrictions, and (c) risk-based premiums (see Merton & Bodie 1992). Gray &
Malone (2008) discuss ways to mitigate, control, and transfer risk among the government,
central bank, and financial institutions in terms of the management of default risk and the
managing guarantees to the financial sector.
5. New Approachs to Regulation of Financial Sector Risk Taking
In the wake of the crisis, the failure to fully understand linkages among financial institu-
tions, new product structures, and new markets makes it clear that a new generation of
regulatory tools is needed. This includes rethinking banking capital adequacy, cross-bor-
der banking regulation, and developing new tools and incentives to mitigate, control, and
transfer risk. A clear lesson from the crisis that started in 2007 is the need to better
understand the risk implications of the regulatory framework. Unintended consequences
of inappropriate regulations, as we have seen, can be very costly (i.e., if regulation is too
tight, it may be arbitraged with less-regulated areas, whereas if it is too lax, it may lead to
risk under pricing). Insights on the design of financial systems, both function and struc-
ture, are described in Merton & Bodie (2005).
The recent crisis has lead to a system with fewer very large banks. As many capital
markets have become illiquid or frozen, half of all nonfinancial debt in the United States at
the end of 2008 was held by the top 15 financial institutions. The influence of these financial
conglomerates will be enormous. These are really too big to fail and may be too big to
rescue. Prices may be more volatile with only a handful of large players. Regulators need to
examine the consequences of these trends for financial stability, as well as for competition
and economic efficiency. The CCA framework provides a unique platform for considering
these issues by allowing us to quantify the potential size and consequence of risk transfers
and their economic consequences for the government (i.e., in the case of bailout).
Risk
Retained TransferredHedging
Insurance
Diversification
Funded Unfunded
Paid-In Contingent
Figure 5
The ways that the guarantor has to manage the risks of guarantees are (a) monitoring, (b) asset
restrictions, and (c) risk-based premiums (see Merton & Bodie 1992). Gray & Malone (2008) discussways to mitigate, control, and transfer risk between the government, central bank, and financial institu-
tions in terms of the management of default risk and the managing guarantees to the financial sector.
138 Gray
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Several capital measures are likely to be needed to assess and maintain capital adequacy
(leverage, tangible equity, risk-weighted assets). Capital adequacy regulation should be
based on comprehensive risk management: It should be counter-cyclical in nature (i.e.,
avoid procylical macroprudential regulations) and allow for a variety of concepts, includ-
ing leverage, risk exposures, and systemic importance (i.e., it should be objective-based
rather than rule-based). Regulators should measure the contribution of financial institu-
tions to systemic risk and impose systemic capital charge/fee or require the purchase
of insurance (proposals for the regulation of systemic risk are discussed in Archarya
et al. 2009 and “systemic CCA” for measuring and setting systemic risk fees in Gray &
Jobst 2009). Hybrid capital instruments can be useful in reducing systemic risk.
The CCA framework can also be a useful guide for setting economic capital levels. The
amount of equity or economic capital a financial institution needs to keep default risk
below a target threshold can be calculated with CCA (see Belmont 2004). At the system
level, CCA is ideally suited to calculate the contribution of individual institutions to
systemic risk and calculate systemic risk fees or insurance premiums.
Comprehensive risk exposure data must be collected. A major lesson of this crisis has
been the lack of understanding of counterparty risk and off-balance sheet risk. Data that
allows monitoring risk exposures of all relevant financial institutions and markets must be
available to regulators and other policymakers so as to ensure that they can assess vulner-
abilities and anticipate risks.
As pointed out earlier, government deposit insurance and financial guarantees risk are
called precisely in the states of the world where governments find it difficult to pay them,
creating destructive feedbacks between financial sector and sovereign risk. One partial solu-
tion could be a system of reinsurance at the international level where international bodies
facilitate reinsurance for domestic deposit insurance and financial guarantee programs.17
6. Monitoring and Managing Sovereign Risk
In the aftermath of the financial crisis that started in 2007, we are in a new world of
government intervention. In the past five years, the increase in government-managed assets
has been astonishing, both in industrial countries as a consequence of the crisis and also in
the increase in assets in sovereign wealth funds (SWFs). Risk-adjusted balance sheets
provide an important tool to examine a number of pressing issues in this area.
First, risk-adjusted balance sheets can be used to better understand the impact of
financial guarantees (whether on a pool of assets or liabilities) on particular institutions
or markets (see Gray & Jobst 2009a). This is particularly helpful as standard risk metrics,
such as CDS spreads, may no longer provide all the relevant information to investors,
as these metrics combine information due to government intervention and market
perceptions.
Second, the CCA methodology, through its stress testing capacity, can be a powerful tool
to help understand the impact of various government measures. For example, it can be used
to examine how the impact of financial guarantees may differ from, say, an outright pur-
chase of bad assets (i.e., through a bad bank approach) or capital injections. Theoretically, a
financial guarantee could be designed to yield equivalent outcomes to an asset purchase. In
practice, however, this may not necessarily be the case, depending on how credible the
17The author thanks Paul Mills for suggesting this point.
www.annualreviews.org � Financial Crises and Sovereign Risks 139
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guarantees are and how they affect market perceptions. However, guarantees have other
important advantages, including a lower up-front price tag. Sovereign CCA analysis is well
suited to help evaluate the impact of financial sector rescue/support programs, stimulus
programs, and tax policy on the sovereign debt levels and sovereign credit spreads.
Third, risk-adjusted balance sheets can help us understand the role of capital injections
in weak financial institutions. For example, to what extent does it matter whether the
injection is done at arms’ length (i.e., via preferred shares) versus through nationalization
(i.e., via common shares)? How does the capital structure affect default risk and other key
risk indicators, such as CDS spreads?
Fourth, the sovereign CCA risk-adjusted balance sheet framework can help to deter-
mine the best asset allocation for commodity exporters’ SWF desiring a certain risk profile
for their fiscal accounts.
The interaction between financial government intervention and sovereign risk is a very
important area for further investigation. In particular, policymakers need to assess how
easily they could unwind such intervention and avoid the negative consequences of state
involvement. Key issues going forward are how to get to a stable system with reduced state
involvement, how and when to unwind guarantees, how to reduce public ownership
stakes, and how to transition to a system with greater private sector ownership operating
under an improved regulatory system. Risk analytic tools described above can help with
the measurement, analysis, reform, and management tasks ahead.
There may be scope for financial guarantees or insurance for sovereign borrowers
provided by international financial institutions. This would be the parallel of government
guarantees to newly issued debt of financial institutions but at the international level.
Contingent sovereign debt arrangements could be considered as well. These could be com-
ponents in a comprehensive risk mitigation program for the sovereign and financial system.
Monitoring and managing sovereign risk in a currency union with unclear contingency
lines is especially complex to understand, but the CCA provides a way to consider them
explicitly. For example, in the Euro currency union, the cost of bank rescue packages will
increase budget deficits in several countries. If a medium-sized country were to default on its
sovereign debt, this could threaten the Euro currency union. New architecture for managing
fiscal risk and sovereign risk within the currency union are needed. Such a new framework
could benefit from the analysis of interlinked risk-adjusted balance sheets to aid in the design
of fiscal rules, risk mitigation strategies, and lender of last resort guidelines.
Ways to mitigate and transfer risk among countries, including SWFs, should be inves-
tigated. This would help shed light on cross-border risk exposures. China, the United
States, the Euro currency union, the United Kingdom, Japan, commodity producers, and
other emerging markets have very different risk exposures. Risk-transfer arrangements
(such as intergovernmental swaps, etc.) could be used to cut off the tail risk between
different countries. Comprehensive sovereign risk accounting and VaR for sovereign risk
are important tools for risk mitigation policy design. The sovereign CCA risk-adjusted
balance sheet framework can also help determine the best asset allocation for SWFs
desiring a certain risk profile for their fiscal accounts.
DISCLOSURE STATEMENT
Dale Gray is the Sr. Risk Expert for the IMF Monetary and Capital Markets Department
and President of MF Risk, Inc. The author is not aware of any affiliations, memberships,
140 Gray
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funding, or financial holdings that might be perceived as affecting the objectivity of this
review. The views are those of the author and do not reflect the views of the management
or board of the International Monetary Fund.
ACKNOWLEDGMENTS
The author would like to thank Andrea Maechler, Matthew Jones, Robert C. Merton,
Paul Mills, Sam Malone, and Colin Gray for very useful comments and suggestions, as
well as Ryan Scuzzarella for editing assistance.
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Annual Review of
Financial Economics
Contents
Preface to the Annual Review of Financial Economics
Andrew W. Lo and Robert C. Merton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
An Enjoyable Life Puzzling Over Modern Finance Theory
Paul A. Samuelson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Credit Risk Models
Robert A. Jarrow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
The Term Structure of Interest Rates
Robert A. Jarrow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
Financial Crises: Theory and Evidence
Franklin Allen, Ana Babus, and Elena Carletti . . . . . . . . . . . . . . . . . . . . . . 97
Modeling Financial Crises and Sovereign Risks
Dale F. Gray. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
Never Waste a Good Crisis: An Historical Perspective on
Comparative Corporate Governance
Randall Morck and Bernard Yeung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
Capital Market-Driven Corporate Finance
Malcolm Baker. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
Financial Contracting: A Survey of Empirical Research and
Future Directions
Michael R. Roberts and Amir Sufi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
Consumer Finance
Peter Tufano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
Life-Cycle Finance and the Design of Pension Plans
Zvi Bodie, Jerome Detemple, and Marcel Rindisbacher . . . . . . . . . . . . . . 249
Finance and Inequality: Theory and Evidence
Asli Demirguc-Kunt and Ross Levine . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287
Volume 1, 2009
v
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Volatility Derivatives
Peter Carr and Roger Lee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319
Estimating and Testing Continuous-Time Models in Finance:
The Role of Transition Densities
Yacine Aıt-Sahalia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341
Learning in Financial Markets
Lubos Pastor and Pietro Veronesi. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 361
What Decision Neuroscience Teaches Us About Financial
Decision Making
Peter Bossaerts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383
Errata
An online log of corrections to Annual Review of Financial Economics articles
may be found at http://financial.annualreviews.org
vi Contents
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