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PART I
Introduction and
Description of Financial
Crises
3
CHAPTER 1
Financial Crises: Explanations,
Types, and Implications
STIJN CLAESSENS AND M. AYHAN KOSE
The 2007–09 global financial crisis and its aftermath have been painful reminders
of the multifaceted nature of crises. They hit small and large countries as well as
poor and rich ones. As fittingly described by Reinhart and Rogoff (2008b), crises
“are an equal opportunity menace.”1 They can have domestic or external origins,
and stem from private or public sectors. They come in different shapes and sizes,
evolve into different forms, and can rapidly spread across borders. They often
require immediate and comprehensive policy responses, call for major changes in
financial sector and fiscal policies, and can compel global coordination of policies.
The widespread impact of the 2007–09 global financial crisis underlines the
importance of having a solid understanding of crises. As the latest episode has
vividly shown, the implications of financial turmoil can be substantial and greatly
affect the conduct of economic and financial policies. A thorough analysis of the
consequences of and best responses to crises has become an integral part of cur-
rent policy debates as the lingering effects of the latest crisis are still being felt
around the world.
This chapter provides a selected survey of the literature on financial crises.2
Crises are, at a certain level, extreme manifestations of the interactions between
the financial sector and the real economy. As such, understanding financial crises
requires an understanding of macro-financial linkages, a truly complex challenge
in itself. The objective of this chapter is more modest: it presents a focused survey
considering three specific questions. First, what are the main factors explaining
financial crises? Second, what are the major types of financial crises? Third, what
are the real sector and financial sector implications of crises? The chapter also
briefly reviews the literature on the prediction of crises and the evolution of early-
warning models.
The first section reviews the main factors explaining financial crises. A finan-
cial crisis is often an amalgam of events, including substantial changes in credit
1 Reinhart and Rogo (forthcoming) use this phrase in the context of banking crises, but it also applies
to a wider range of crises.
2 For further reading on nancial crises, the starting point is the authoritative study by Reinhart and
Rogo (2009b). Classical references are Minsky (1975) and Kindleberger (1976). See IMF (1998);
Eichengreen (2002); Tirole (2002); Allen and Gale (2007); Allen, Babus, and Carletti (2009); Allen
(2010) and Gorton (2012) for reviews of the causes and consequences of nancial crises.
4 Financial Crises: Explanations, Types, and Implications
volume and asset prices; severe disruptions in financial intermediation, notably
the supply of external financing; large-scale balance sheet problems; and the need
for large-scale government support. Although these events can be driven by a
variety of factors, financial crises often are preceded by asset and credit booms
that then turn into busts. Thus, many theories focusing on the sources of finan-
cial crises have recognized the importance of sharp movements in asset and credit
markets. In light of this, this section briefly reviews theoretical and empirical
studies analyzing developments in credit and asset markets around financial
crises.
The second section classifies the types of financial crises identified in many
studies into four main groups: currency crises, sudden stop (or capital account or
balance of payments) crises, debt crises, and banking crises. This section sum-
marizes the findings of the literature on the analytical causes and empirical deter-
minants of each type of crisis.
The identification of crises is discussed in the third section. Theories designed
to explain crises are used to guide the literature on the identification of crises.
However, transforming the predictions of the theories into practice has been dif-
ficult. Although it is easy to design quantitative methods for identifying currency
(and inflation) crises and sudden stops, the identification of debt and banking
crises is typically based on qualitative and judgmental analyses. Irrespective of the
classification used, different types of crises are likely to overlap. Many banking
crises, for example, are also associated with sudden stop episodes and currency
crises. The coincidence of multiple types of crises leads to further challenges of
identification. The literature, therefore, employs a wide range of methods to
identify and classify crises. The section considers various identification approaches
and reviews the frequency of crises over time and across different groups of coun-
tries.
The fourth section analyzes the implications of financial crises. The macroeco-
nomic and financial implications of crises are typically severe and share many
common features across various types. Large output losses are common to many
crises, and other macroeconomic variables typically register significant declines.
Financial variables, such as asset prices and credit, usually follow qualitatively
similar patterns across crises, albeit with variations in duration and severity of
declines. The section examines the short- and medium-term effects of crises and
presents a set of stylized facts with respect to their macroeconomic and financial
implications.
The fifth section summarizes the main methods used for predicting crises.
Predicting the timing of crises has been a challenge. Financial markets with
high leverage can easily be subject to crises of confidence, making fickleness
the main reason that the exact timing of crises is so difficult to predict.
Moreover, the nature of crises changes over time as economic and financial
structures evolve. Not surprisingly, early-warning tools can quickly become
obsolete or inadequate. This section presents a summary of the evolution of
different types of prediction models and considers the current state of early-
warning models.
Claessens and Kose 5
The last section first summarizes the major lessons from this literature review,
then considers the most relevant issues for research in light of these lessons,
including that future research should be geared toward eliminating the “this-time-
is-different” syndrome. However, this is a very broad task requiring that two
major issues be addressed: How can financial crises be prevented? And, can their
costs be mitigated when they take place? In addition, more intensive efforts are
required to collect the necessary data and to develop new methods to guide both
empirical and theoretical studies.
EXPLAINING FINANCIAL CRISES
Financial crises have common elements, but they come in many forms. A finan-
cial crisis is often associated with one or more of the following phenomena: sub-
stantial changes in credit volume and asset prices; severe disruptions in financial
intermediation and the supply of external financing to various actors in the
economy; large-scale balance sheet problems (of firms, households, financial
intermediaries, and sovereigns); and large-scale government support (in the form
of liquidity support and recapitalization). Financial crises are typically multidi-
mensional events and can be hard to characterize using a single indicator.
The literature has clarified some of the factors driving crises, but definitively
identifying their deeper causes remains a challenge. Many theories have been
developed regarding the underlying causes of crises. Although fundamental fac-
tors—macroeconomic imbalances, internal or external shocks—are often
observed, many questions remain about the exact causes of crises. Financial crises
sometimes appear to be driven by “irrational” factors, including sudden runs on
banks; contagion and spillovers among financial markets; limits to arbitrage dur-
ing times of stress; the emergence of asset busts, credit crunches, and fire sales;
and other aspects of financial turmoil. Indeed, the idea of “animal spirits” (as a
source of financial market movements) has long occupied a significant space in
the literature attempting to explain crises (Keynes, 1930; Minsky, 1975;
Kindleberger, 1976).3
Financial crises are often preceded by asset and credit booms that eventually
turn into busts. Many theories focusing on the sources of crises have recognized
the importance of booms in asset and credit markets. However, explaining why
asset price bubbles or credit booms are allowed to continue and eventually
become unsustainable and turn into busts or crunches has been challenging. This
naturally requires answering why neither financial market participants nor poli-
cymakers foresee the risks and attempt to slow down the expansion of credit or
the increase in asset prices.
The dynamics of macroeconomic and financial variables around crises have
been extensively studied. Empirical studies have documented the various phases
3 Related are such concepts as “re exivity” (Soros, 1987), “irrational exuberance” (Greenspan, 1996)
and “collective cognition” (de la Torre and Ize, 2011).
6 Financial Crises: Explanations, Types, and Implications
of financial crises, from initial, small-scale financial disruptions to large-scale
national, regional, or even global crises. They have also described how, in the
aftermath of financial crises, asset prices and credit growth can remain depressed
for a long time and how crises can have long-lasting consequences for the real
economy. Given their central roles, the chapter next briefly discusses develop-
ments in asset and credit markets around financial crises.
Asset Price Booms and Busts
Sharp increases in asset prices, sometimes called bubbles, and often followed by
crashes, have been experienced for centuries. Asset prices sometimes seem to devi-
ate from what fundamentals would suggest and exhibit patterns different from
predictions of standard models with perfect financial markets. A bubble, an
extreme form of such deviation, can be defined as “the part of asset price move-
ment that is unexplainable based on what we call fundamentals” (Garber, 2000,
p. 4). Patterns of exuberant increases in asset prices, often followed by crashes,
figure prominently in many accounts of financial instability, for both advanced
countries and emerging market economies, going back millennia.4
Some asset-price bubbles and crashes are well known. Such historical cases
include the Dutch Tulip Mania from 1634 to 1637, the French Mississippi Bubble
in 1719–20, and the South Sea Bubble in the United Kingdom in 1720
(Kindleberger, 1986; Garber, 2000). During some of these periods, certain asset
prices increased very rapidly in a short time, followed by sharp corrections. These
cases are extreme, but not unique. In the 2007–09 financial crisis, for example, house
prices in a number of countries followed this inverse U-shaped pattern (Figure 1.1).
What Explains Asset Price Bubbles?
Formal models attempting to explain asset-price bubbles have been available for
some time. Some of these models consider how individual episodes of rational
behavior can lead to collective mispricing, which in turn can result in bubbles.
Others rely on microeconomic distortions that can lead to mispricing. Some oth-
ers assume “irrationality” on the part of investors. Despite parallels, explaining
asset-price busts (such as fire sales) often requires accounting for different factors
than does explaining bubbles.
Some models using rational investors can explain bubbles without distortions.
These models consider asset-price bubbles as agents’ justified expectations about
future returns. For example, in Blanchard and Watson (1982), under rational
expectations, the asset price does not need to equal its fundamental value, leading
to “rational” bubbles. Thus, observed prices, although exhibiting extremely large
fluctuations, are not necessarily excessive or irrational. These models have been
applied relatively successfully to explain the Internet bubble of the late 1990s.
Pastor and Veronesi (2006) show how a standard model can reproduce the valu-
4 For detailed reviews of models of asset-price bubbles, see Garber (2000); Evano , Kaufman, and
Malliaris (2012); and Scherbina (2013).
Claessens and Kose 7
ation and volatility of Internet stocks in the late 1990s, thus arguing that there is
no reason to refer to a “dot-com bubble.” Branch and Evans (2008), employing a
theory of learning in which investors use the most recent (instead of past) data,
find that shocks to fundamentals may increase return expectations. This may
cause stock prices to rise above levels consistent with fundamentals. As prices
increase, investors’ perceptions of riskiness decline until the bubble bursts.5 More
generally, theories suggest that bubbles can appear without distortions, uncer-
tainty, speculation, or bounded rationality.
But both micro distortions and macro factors can also lead to bubbles. Bubbles
may relate to agency issues (Allen and Gale, 2007). For example, as a result of risk
shifting—when agents borrow to invest (e.g., margin lending for stocks, mort-
gages for housing), but can default if rates of return are not sufficiently high—
prices can escalate rapidly. Fund managers who are rewarded on the upside more
than on the downside (somewhat analogous to the limited liability of financial
institutions) bias their portfolios toward risky assets, which may trigger a bubble
5 Wang and Wen (2012) argue that systemic risk, commonly perceived as changes in the bubble’s prob-
ability of bursting, can produce asset-price movements many times more volatile than the economy’s
fundamentals and generate boom-bust cycles in the context of a dynamic stochastic general equilib-
rium model.
Figure 1.1 Evolution of House Prices during Financial Crises
Sources: Bank for International Settlements; Haver Analytics; and the Organization for Economic Cooperation and
Development.
Note: The real house price index is equal to 100 five years before each banking crisis. For the 2007–09 crisis, the beginning
date is assumed to be 2007:Q3. “Big 5” refers to the average of the house price indices for five major banking crises: Spain
in 1977, Norway in 1987, Finland in 1991, Sweden in 1991, and Japan in 1992.
180
160
140
120
100
80
–20 –16 –12 –8 –4 0 4 8
Real house price index
United States
United Kingdom
New Zealand
Big 5
Spain
Sweden
France
Ireland
Quarters
8 Financial Crises: Explanations, Types, and Implications
(Rajan, 2005).6 Other microeconomic factors (e.g., interest rate deductibility for
household mortgages and corporate debt) can exacerbate this risk-taking, possibly
leading to bubbles.7
Investors’ behavior can also drive asset prices away from fundamentals, at least
temporarily. Frictions in financial markets (notably those associated with infor-
mation asymmetries) and institutional factors can affect asset prices. Theory sug-
gests, for example, that differences of information and opinions among investors
(related to disagreements about valuation of assets), short sales constraints, and
other limits to arbitrage are possible reasons for asset prices to deviate from fun-
damentals.8 Mechanisms such as herding among financial market players, infor-
mational cascades, and market sentiment can affect asset prices. Virtuous
feedback loops—rising asset prices and increasing net worth positions that allow
financial intermediaries to leverage up and buy more of the same assets—play a
significant role in driving the evolution of bubbles. The phenomenon of conta-
gion, that is, spillovers beyond what fundamentals would suggest, may have
similar roots. Brunnermeier (2001) reviews these models and shows how they can
help explain bubbles, crashes, and other market inefficiencies and frictions.
Empirical work confirms some of these channels, but formal econometric tests are
most often not powerful enough to separate bubbles from rational increases in
prices, let alone to detect the causes of bubbles (Gürkaynak, 2008).9
Bubbles may also be the result of the same factors that are argued to lead to
asset-price anomalies. Many deviations of asset prices from the predictions of
efficient-market models, on a small scale with no systemic implications, have been
documented (Fama, 1998; Lo and MacKinlay, 2001; Schwert, 2003).10 Although
some of these deviations have diminished over time, possibly as investors have
implemented strategies to exploit them, others, even though documented exten-
sively, persist today. Furthermore, deviations have similarly been found across
various markets, time periods, and institutional contexts. Thus, anomalies cannot
easily be attributed to specific, institution-related distortions. Rather, they appear
to reflect factors intrinsic to financial markets. Studies under the rubric of behav-
ioral finance have tried to explain these patterns, with some success (Shleifer, 2000;
6 In Rajan’s (2005) “alpha-seeking” argument, rms, asset managers, and traders take more risk to
improve returns, with private rewards in the short term. See Gorton and He (2000) and Dell’Ariccia
and Marquez (2000) for theories linking credit booms to the quality of lending standards and com-
petition.
7 See BIS (2002) for a general review and IMF (2009) for a review of debt and other biases in tax policy
with respect to the 2007–09 nancial crisis.
8 Models include Miller (1977); Harrison and Kreps (1978); Chen, Hong, and Stein (2002); Scheink-
man and Xiong (2003); and Hong, Scheinkman, and Xiong (2008).
9 Empirical studies include Abreu and Brunnermeier (2003); Diether, Malloy, and Scherbina (2002);
Lamont and aler (2003); Ofek and Richardson (2003); and Shleifer and Vishny (1997).
10 For example, stocks of small rms get higher rates of return than other stocks do, even after adjusting
for risk, liquidity, and other factors. Spreads on lower-rated corporate bonds appear to have a relatively
larger compensation for default risk than higher-rated bonds do. Mutual funds whose assets cannot be
liquidated when investors sell the funds (so-called closed-end funds) can trade at prices di erent from
those implied by the intrinsic value of their assets.
Claessens and Kose 9
Barberis and Thaler, 2003).11 Of course, “evidence of irrationality” may reflect a
misspecified model, that is, irrational behavior is not easily falsifiable.
What Triggers Asset-Price Busts?
Busts following bubbles can be triggered by small shocks. Asset prices may experi-
ence small declines due to changes in either fundamental values or sentiment.
Changes in international financial and economic conditions, for example, may
drive prices down. The channels by which small declines in asset prices can trigger
a crisis are well understood now. Given information asymmetries, for example, a
small shock can lead to market freezes. Adverse feedback loops may then arise, in
which asset prices exhibit rapid declines and downward spirals. Notably, a drop
in prices can trigger a fire sale as financial institutions experiencing a decline in
asset values struggle to attract short-term financing. Such sudden stops can lead
to a cascade of forced sales and liquidations of assets, and further declines in
prices, with consequences for the real economy.
Flight to quality can further intensify financial turmoil. Relationships among
financial intermediaries are multiple and complex. Information asymmetries are
prevalent among intermediaries and in financial markets. These problems can
easily lead to financial turmoil. They can be aggravated by preferences of investors
to hold debt claims (Gorton, 2008). Specifically, debt claims are “low informa-
tion intensive” in normal states of the world; because the risk of default is remote,
little analysis of the underlying asset value is required. They become “high infor-
mation intensive,” however, in times of financial turmoil as risks increase, requir-
ing investors to assess default risks, a complex task involving a multitude of
information problems. This situation puts a premium on safety and can create
perverse spirals. As investors turn to quality assets, for example, government
bonds, they avoid some lower-quality types of debt claims, leading to sharper
drops in the prices of those debt claims (Gorton and Ordonez, 2012).
Credit Booms and Busts
A rapid increase in credit is another common thread running through the narra-
tives of events that precede financial crises. Leverage buildups and greater risk
taking through rapid credit expansion, in concert with increases in asset prices,
often precede crises (albeit typically only recognized with the benefit of hind-
sight). Both distant and more recent crisis episodes typically witnessed a period
of significant growth in credit (and external financing), followed by busts in credit
11 For example, rms tend to issue new stock when prices (and rm pro tability) are high. Another
example is that the market’s reaction to initial public o erings can be “hot” or “cold.” Both examples
contradict the assumption that rms seek external nancing only when they need to (because of a
lack of internal funds while growth opportunities are good). Many individual investors also appear to
diversify their assets insu ciently (or naively) and rebalance their portfolios too infrequently. At the
same time, some investors respond too quickly to price movements, and sell winners too early and hold
on to losers too long. ese patterns have been “explained” by various behavioral factors.
10 Financial Crises: Explanations, Types, and Implications
markets along with sharp corrections in asset prices. In many respects, the
descriptions of the Australian boom and bust of the 1880–90s, for example, fit
the more recent episodes of financial instability. Likewise, the patterns before the
East Asian financial crisis in the late 1990s resembled those of the earlier ones in
Nordic countries as banking systems collapsed following periods of rapid credit
growth related to investment in real estate. The experience of the United States in
the late 1920s and early 1930s exhibits some features similar to the run-up to the
2007–09 global financial crisis with, in addition to rapid growth in asset prices
and land speculation, a sharp increase in (household) leverage. The literature has
also documented common patterns in various other macroeconomic and finan-
cial variables around these episodes.
What Macroeconomic Factors Explain Credit Booms?
Credit booms can be triggered by a wide range of factors, including shocks and
structural changes in markets.12 Shocks that can lead to credit booms include
changes in productivity, economic policies, and capital flows. Some credit booms
tend to be associated with positive productivity shocks. These booms generally
start during or after periods of buoyant economic growth. Dell’Ariccia and others
(Chapter 11, this volume) find that lagged GDP growth is positively associated
with the probability of a credit boom: in the three-year period preceding a boom,
the average real GDP growth rate reaches 5.1 percent, compared with 3.4 percent
during a tranquil three-year period.
Sharp increases in international financial flows can amplify credit booms.
Most national financial markets are affected by global conditions, even more so
today, so asset bubbles can easily spill across borders. Fluctuations in capital flows
can amplify movements in local financial markets when inflows lead to a signifi-
cant increase in the funds available to banks, relaxing credit constraints for cor-
porations and households (Claessens and others, 2010). Rapid expansion of
credit and sharp growth in house and other asset prices were indeed associated
with large capital inflows in many countries before the 2007–09 financial crisis.
Accommodative monetary policies, especially when in place for extended peri-
ods, have been linked to credit booms and excessive risk taking. The channel
works as follows: Interest rates affect asset prices and borrowers’ net worth, in turn
affecting lending conditions. Analytical models, including of the relationship
between agency problems and interest rates (e.g., Stiglitz and Weiss, 1983), sug-
gest more risk taking when interest rates decline and a flight to quality when
interest rates rise, with consequent effects on the availability of external financing.
Empirical evidence (e.g., for Spain, Ioannidou, Ongena, and Peydró, 2009;
Maddaloni and Peydró, 2010) supports such a channel because credit standards
tend to loosen when policy rates decline.
12 For reviews of factors associated with the onset of credit booms, see Mendoza and Terrones (2008,
2012); Magud, Reinhart, and Vesperoni (2012); and Dell’Ariccia and others (Chapter 11, this vol-
ume).
Claessens and Kose 11
The relatively low interest rates in the United States during 2001–04 are often
mentioned as a main factor behind the rapid increases in house prices and house-
hold leverage (Lansing, 2008; Hirata and others, 2012).13
What Structural Factors Explain Credit Booms?
Structural factors include financial liberalization and innovation. Financial liber-
alization, especially when poorly designed or sequenced, and financial innovation
can trigger credit booms and lead to excessive increases in leverage by facilitating
more risk taking. Financial liberalization has been found to often precede crises
in empirical studies (Kaminsky and Reinhart, 1999; Demirgüç-Kunt and
Detragiache, 2005). Dell’Ariccia and others (Chapter 11, this volume) report that
roughly a third of booms they identified follow or coincide with financial liberal-
ization episodes.
The mechanisms involved include institutional weaknesses as well as the per-
verse effects of competition. Regulation, supervision, and market discipline seem
to be slow to catch up with greater competition and innovation (possibly set in
motion by shocks or liberalization). Vulnerabilities in credit markets can naturally
arise. Another mechanism commonly linking booms to crises is a decline in lend-
ing standards. Greater competition in financial services, although generally
enhancing efficiency and stability in the long term, can contribute to financial
fragility over shorter periods. This was evident in the higher delinquency rates in
those metropolitan areas in the United States with higher growth in loan origina-
tion before the onset of the crisis, with the deterioration in lending standards
appearing to be related, in part, to increases in competition (Dell’Ariccia, Igan,
and Laeven, 2008).
Impact of Asset-Price and Credit Busts
Movements in asset and credit markets during financial crises are much sharper
than those observed over the course of a normal business cycle. Booms in credit
and asset markets, defined as those upturns in the uppermost quartile of all
upturns, are shorter, stronger, and faster than other upturns. For example,
booms often take place over relatively shorter periods than do other upturns and
are associated with much faster increases in the financial variables (Figure 1.2A).
The slope of a typical boom, that is, the average increase in the financial variable
in each quarter, is two to three times larger than that of regular upturns. And
crunches and busts are longer, deeper, and more violent than other downturns.
13 However, whether and how monetary policy a ects risk taking, and thereby asset prices and leverage,
remains a subject for further research (see De Nicolo and others, 2010, for recent analysis and review).
e extent of bank capitalization appears to be an important factor given that it a ects incentives:
when facing a lower interest rate, a well-capitalized bank decreases its monitoring and takes more
risk, whereas a highly levered, poorly capitalized bank does the opposite (see Dell’Ariccia, Laeven, and
Marquez, 2011).
12 Financial Crises: Explanations, Types, and Implications
Figure 1.2.A. Credit and Asset Price Booms
Source: IMF staff calculations.
Note: The sample includes data for 23 advanced countries and covers 1960–2011. Amplitude and slope correspond to
sample median, and duration corresponds to sample mean. Duration is the time it takes to attain the level of the previous
peak after the trough. Amplitude is calculated as the one-year change in each respective variable after the trough. Slope
is the amplitude from peak to trough divided by the duration. Booms are the top 25 percent of upturns calculated by the
amplitude.
*** indicates that the difference between corresponding financial boom and other upturns is statistically significant at
1 percent level.
a. Duration
∗∗∗
∗∗∗
Booms Other upturns
Credit House price
b. Amplitude
c. Slope
Equity price
30
25
15
5
20
10
0
Quarters
∗∗∗
∗∗∗
Booms Other upturns
Credit House price Equity price
60
50
30
10
40
20
0
PercentPercent
∗∗∗
∗∗∗
∗∗∗
∗∗∗
Booms Other upturns
Credit House price Equity price
14
12
8
6
4
2
10
0
Credit crunches and asset-price busts have much larger declines than do other
downturns (Figure 1.2B). Specifically, credit crunches and house-price busts,
respectively, lead to roughly 10 and 15 times larger drops than do other down-
turns, whereas equity busts are more than 2.5 times as large. These episodes also
last longer, some two times longer, than other downturns, with house-price busts
Claessens and Kose 13
Figure 1.2.B Credit Crunches and Asset Price Busts
Source: IMF staff calculations.
Note: The sample includes data for 23 advanced countries and covers 1960–2011. Amplitude and slope correspond to
sample median, and duration corresponds to sample mean. Duration is the number of quarters between peak and
trough. Amplitude is calculated as the decline in each respective variable during the downturn. Slope is the amplitude
from peak to trough divided by the duration. Crunches and busts are the worst 25 percent of downturns calculated by
the amplitude.
***, ** indicate that the difference between the corresponding disruptions and other downturns is statistically significant
at the 1 and 5 percent levels respectively.
a. Duration
∗∗∗
∗∗∗
∗∗∗
Disruptions
Other downturns
Disruptions
Other downturns
Credit House price
b. Amplitude
c. Slope
Equity price
18
16
14
12
8
4
2
10
6
0
Quarters
∗∗∗
∗∗∗
∗∗∗
Credit House price Equity price
0
–10
–30
–50
–20
–40
–60
Percent
Disruptions
Other downturns
∗∗∗
∗∗
∗∗∗
Credit House price Equity price
0
–1
–3
–5
–2
–4
–6
–7
Percent
the longest of all, about 18 quarters, whereas credit crunches and equity busts
last about 10–12 quarters. Moreover, disruptions are more violent, as evidenced
by higher slope coefficients, with busts in equity prices being three times more
violent than those in credit and house prices (Claessens, Kose, and Terrones,
2010a).
14 Financial Crises: Explanations, Types, and Implications
Asset price busts and credit crunches typically have adverse effects on the real
economy.14 Asset price busts can affect bank lending and other financial institu-
tions’ investment decisions and, in turn, the real economy through two channels.
First, when borrowing and lending is collateralized and the market price of col-
lateral falls, the ability of firms to rely on assets as collateral for new loans and
financial institutions’ ability to extend new credit become impaired, which in
turn adversely affect investment. Second, the prospect of large price dislocations
arising from fire sales and related financial turmoil distorts financial institutions’
decisions to lend or invest, prompting them (among other actions) to hoard cash.
Through these channels, fire sales can trigger a credit crunch and cause a severe
contraction in real activity.
Those asset-price booms supported by leveraged financing and involving
financial intermediaries appear to entail larger risks for the economy. Evidence
from past episodes suggests that whether excessive movements in asset prices lead
to severe misallocations of resources depends in large part on the nature of the
boom and how it is financed. Booms largely involving equity market activities
appear to have lower risks of adverse consequences. The burst of the Internet
bubble of the late 1990s, which mainly involved only equity markets, was not
very costly for the real economy. When banks are involved in financing asset-price
booms, however, as in real estate mortgage and corporate sector financing, risks
of adverse consequences from a subsequent asset bust are typically much higher.
These booms involve leverage and banks, meaning that the flow of credit to the
economy is interrupted when a bust occurs.
The burst of the latest bubble—financed by banks (and the shadow banking
system) and involving housing—has been very costly. For the 2007–09 episode,
Crow and others (Chapter 12, this volume) report that, in a 40-country sample,
almost all the countries with “twin booms” in real estate and credit markets (21
out of 23) ended up suffering from either a crisis or a severe drop in the GDP
growth rate relative to the country’s performance in the 2003–07 period (Figure
1.3). Eleven of these countries actually suffered both financial sector damage and
a sharp drop in economic activity. In contrast, of the seven countries that experi-
enced a real estate boom but not a credit boom, only two went through a systemic
crisis and, on average, had relatively mild recessions. A broader discussion of the
real and financial implications of financial crises and disruptions is presented in
the section below titled “Real and Financial Implications of Crises.”
14 Some economists used to be sanguine about the costs of busts in credit and asset markets. Until
the 2007–09 crisis, for example, the economic cost of bubbles was dismissed by some analysts. For
example, Roger W. Ferguson, then Vice Chairman of the U.S. Federal Reserve Board, argued in Janu-
ary 2005 that “recessions that follow swings in asset prices are not necessarily longer, deeper, and
associated with a greater decline in output and investment than other recessions” (Ferguson, 2005,
p. 16). ere are also theories in which even fully irrational asset bubbles are not necessarily harmful
or could even be bene cial (Kocherlakota, 2009). Bubbles can allow for a store of value (collateral)
and thereby enhance overall nancial intermediation through facilitating exchanges, thus improving
overall economic performance. As such, the presence of bubbles per se, whether rational or irrational,
need not necessarily be a cause for concern.
Claessens and Kose 15
TYPES OF FINANCIAL CRISES
Financial crises can take various shapes and forms, but two broad types can be
distinguished. Reinhart and Rogoff (2009b) describe two types of crises: those
classified using strictly quantitative definitions, and those dependent largely on
qualitative and judgmental analysis. The first group mainly includes currency and
sudden stop crises, and the second group contains debt and banking crises.
Regardless, definitions are strongly influenced by the theories trying to explain
crises.
The literature has been able to arrive at concrete definitions of many types of
crises. For example, a currency crisis involves a speculative attack on the currency
resulting in a devaluation (or sharp depreciation); or forces the authorities to
defend the currency by expending large amounts of international reserves, or
sharply raising interest rates, or imposing capital controls. A sudden stop (or capi-
tal account or balance of payments crisis) can be defined as a large (and often
unexpected) decline in international capital inflows or a sharp reversal in aggre-
gate capital flows to a country, likely taking place in conjunction with a sharp rise
in its credit spreads. Because these are measurable variables, they lend themselves
to the use of quantitative methodologies.
Other crises are associated with adverse debt dynamics or banking system
turmoil. A foreign debt crisis takes place when a country cannot (or does not want
to) service its foreign debt, sovereign, private, or both. A domestic public debt
crisis takes place when a country does not honor its domestic fiscal obligations in
real terms, either by defaulting explicitly, or by inflating or otherwise debasing its
currency, or by employing other forms of financial repression. In a systemic bank-
ing crisis, actual or potential bank runs and failures can induce banks to suspend
Figure 1.3 Coincidence of Financial Booms and Crises: 1960–2011
Source: Dell’ Ariccia, Laeven, and Marquez, 2011.
Note: The sample consists of 40 countries. The numbers, except “Neither,” show the percentage of the cases in which a
crisis or poor macroeconomic performance happened after a boom was observed (out of the total number of cases in
which a boom occurred).
100
80
60
40
20
0
Percent
Credit House prices Both Neither
Followed by financial crisis
Followed by poor performance
Followed by financial crisis or poor performance
16 Financial Crises: Explanations, Types, and Implications
the convertibility of their liabilities, or compel the government to intervene to
prevent them from doing so by extending liquidity and capital assistance on a
large scale. Because these variables are not so easily measured, these crises lend
themselves more to the use of qualitative methodologies.
Other classifications are possible, but the types of crises are still likely to over-
lap. A number of banking crises, for example, are associated with sudden stop
episodes and currency crises. This section examines analytical causes and empiri-
cal determinants of each type of crisis. The identification, dating, and frequency
of crises are considered in the next section.
Currency Crises
Theories of currency crises, often more precisely articulated than theories for
other types of crisis, have evolved as the nature of such crises has changed. In
particular, the literature has changed from a focus on the fundamental causes of
currency crises, to emphasizing the scope for multiple equilibria, and to stressing
the role of financial variables, especially changes in balance sheets, in triggering
currency crises (and other types of financial turmoil). Three generations of mod-
els are typically used to explain currency crises that took place during the past four
decades.
The first generation of models, largely motivated by the collapse in the price
of gold, an important nominal anchor before the floating of exchange rates in the
1970s, was often applied to currency devaluations in Latin America and other
developing countries (Claessens, 1991).15 These models are from seminal papers
by Krugman (1979) and Flood and Garber (1984), and hence called “KFG”
models. They show that a sudden speculative attack on a fixed or pegged currency
can result from rational behavior by investors who correctly foresee that a govern-
ment has been running excessive deficits financed with central bank credit.
Investors continue to hold the currency as long as they expect the exchange rate
regime to remain intact, but they start dumping it when they anticipate that the
peg is about to end. This run leads the central bank to quickly lose its liquid assets
or hard foreign currency supporting the exchange rate. The currency then col-
lapses.
The second-generation models stress the importance of multiple equilibria.
These models show that doubts about whether a government is willing to main-
tain its exchange rate peg could lead to multiple equilibria and currency crises
(Obstfeld and Rogoff, 1986). In these models, self-fulfilling prophecies are pos-
sible, in which the reason investors attack the currency is simply that they expect
other investors to attack the currency. As discussed in Flood and Marion (1997),
policies before the attack in the first-generation models can translate into a crisis,
whereas changes in policies in response to a possible attack (even if these policies
are compatible with macroeconomic fundamentals) can lead to an attack and be
the trigger of a crisis. The second-generation models are, in part, motivated by
15 Earlier versions of the canonical crisis model were Salant and Henderson (1978) and Salant (1983).
Claessens and Kose 17
episodes like the European Exchange Rate Mechanism crisis, in which countries
like the United Kingdom came under pressure in 1992 and ended up devaluing,
even though other outcomes (that were consistent with macroeconomic funda-
mentals) were possible too (Eichengreen, Rose, and Wyplosz, 1995; Frankel and
Rose, 1996).
The third-generation crisis models explore how rapid deteriorations of balance
sheets associated with fluctuations in asset prices, including exchange rates, can
lead to currency crises. These models were largely motivated by the Asian crises
of the late 1990s. In the Asian countries, macroeconomic imbalances were small
before the crisis—fiscal positions were often in surplus and current account defi-
cits appeared to be manageable, but vulnerabilities associated with financial and
corporate sectors were large. The models show how balance sheet mismatches in
these sectors can give rise to currency crises. For example, Chang and Velasco
(2000) show how local banks with large debts outstanding that are denominated
in foreign currency may lead to a banking and currency crisis.16
This generation of models also considers the roles played by banks and the
self-fulfilling nature of crises. McKinnon and Pill (1996), Krugman (1999), and
Corsetti, Pesenti, and Roubini (1998) suggest that overborrowing by banks can
arise as the result of government subsidies (to the extent that governments would
bail out failing banks). In turn, vulnerabilities stemming from overborrowing
can trigger currency crises. Burnside, Eichenbaum, and Rebelo (2001, 2004)
argue that crises can be self fulfilling because of fiscal concerns and volatile real
exchange rate movements (when the banking system has such a government
guarantee, a good or a bad equilibrium can result). Radelet and Sachs (1998)
argue more generally that self-fulfilling panics hitting financial intermediaries
can force liquidation of assets, which then confirms the panic and leads to a cur-
rency crisis.
Empirical research has not been able to determine which generation of these
models provides the best characterization of currency crises. Early work had good
success with the KFG model. Blanco and Garber (1986), for example, applied the
KFG model to the Mexican devaluations in 1976 and 1981–82 and showed that
crisis probabilities had built to peaks just before the devaluations (Cumby and van
Wijnbergen, 1989; Klein and Marion, 1994). However, although the KFG model
worked well in cases in which macroeconomic fundamentals grew explosively, it
was not successful if fundamentals were merely highly volatile and money
demand was unstable.
Later empirical work moved away from explicit tests of structural models.
Some studies used censored dependent variable models, for example, logit mod-
els, to estimate crisis probabilities based on a wide range of lagged variables
(Eichengreen, Rose, and Wyploz, 1995; Frankel and Rose, 1996; Kumar and
16 Hallwood and MacDonald (2000) provide a detailed summary of the rst- and second-generation
models and consider their extensions to di erent contexts. Krugman (1999), in an attempt to explain
the Asian nancial crisis, also provides a similar mechanism operating through rms’ balance sheets,
and investment is a function of net worth.
18 Financial Crises: Explanations, Types, and Implications
others, 2003). Others, such as Kaminsky, Lizondo, and Reinhart (1998) and
Kaminsky and Reinhart (1999), employed signaling models to evaluate the use-
fulness of several variables in signaling an impending crisis. This literature found
that certain indicators tend to be associated with crises, but the outcomes have
nevertheless been disappointing, with the timing of crises very hard to predict.17
The issue of crisis prediction will be revisited later.
Sudden Stops
Models with sudden stops are more closely associated with disruptions in the
supply of external financing. These models resemble the third generation of cur-
rency crisis models in that they also focus on balance sheet mismatches—notably
currency, but also maturity—in financial and corporate sectors (Calvo, Izquierdo,
and Mejia, 2004). They tend to give greater weight, however, to the role of inter-
national factors (as captured, for example, by changes in international interest
rates or spreads on risky assets) in causing sudden stops in capital flows. These
models can account for the current account reversals and the real exchange rate
depreciation typically observed during crises in emerging markets. The models
explain less well the typical sharp drops in output and total factor productivity.
To match data better, more-recent sudden stop models introduce various
frictions. Although counterintuitive, in most models, a sudden stop or cur-
rency crisis generates an increase in output rather than a drop. This increase in
output happens through an abrupt increase in net exports resulting from the
currency depreciation. This theory has led to various arguments explaining
why sudden stops in capital flows are associated with large output losses, as is
often the case. Models typically include Fisherian channels and financial accel-
erator mechanisms, or frictions in labor markets, to generate an output drop
during a sudden stop, without losing the ability to account for the movements
of other variables.
Closely following the literature on domestic financial intermediation , mod-
els with financial frictions help to account better for the dynamics of output
and productivity in sudden stops. With frictions, for example, when firms must
borrow in advance to pay for inputs (e.g., wages, foreign inputs), a decline in
credit—the sudden stop combined with rising external financing premiums—
reduces aggregate demand and causes a decline in output (Calvo and Reinhart,
2000). Or as a result of collateral constraints in lending, a sudden stop can lead
to a debt-deflation spiral of declines in credit, prices, and quantity of collateral
assets, resulting in a decline in output. Like the domestic financial accelerator
mechanism, financial distress and bankruptcies cause negative externalities,
because banks become more cautious and reduce new lending, in turn, induc-
ing a further decline in credit, and thereby contributing to a recession (Calvo,
2000).
17 See Kaminsky, Lizondo, and Reinhart (1998) for an early review; Kaminsky (2003) for an update;
and Frankel and Saravelos (2012) for an extensive recent survey up to the 2000s.
[[AQ: Pls
add to
refs.]]
Claessens and Kose 19
These types of amplification mechanisms can make small shocks cause sudden
stops. Relatively small shocks—to imported input prices, the world interest rate,
or productivity—can trigger collateral constraints on debt and working capital,
especially when borrowing levels are high relative to asset values. Fisher’s debt-
deflation mechanisms can then cause sudden stops through a spiraling decline in
asset prices and holdings of collateral assets (Fisher, 1933). This chain of events
immediately affects output and demand. Mendoza (2010) shows how a business
cycle model with collateral constraints can be consistent with the key features of
sudden stops. Korinek (2011) provides a model analyzing the adverse implica-
tions of large movements in capital flows on real activity.
Sudden stops often take place in countries with relatively small tradable sectors
and large foreign exchange liabilities. Sudden stops have affected countries with
widely disparate levels of per capita GDP, levels of financial development, and
exchange rate regimes, as well as countries with different levels of reserve coverage.
However, most episodes share two elements, as Calvo, Izquierdo, and Mejía
(2008) document: a small supply of tradable goods relative to domestic absorp-
tion—a proxy for potential changes in the real exchange rate—and a domestic
banking system with large foreign exchange–denominated liabilities, raising the
probability of a “perverse” cycle.
Empirical studies find that many sudden stops have been associated with
global shocks. For a number of emerging markets, for example, those in Latin
America and Asia in the 1990s and in Central and Eastern Europe in the 2000s,
after a period of large capital inflows, a sharp retrenchment or reversal of capital
flows occurred, triggered by global shocks (such as increases in interest rates or
changes in commodity prices). Sudden stops are more likely with large cross-
border financial linkages. Milesi-Ferretti and Tille (2011) document that rapid
changes in capital flows were important triggers of local crises during the
2007–09 crisis. Others, such as Rose and Spiegel (2011), however, find little role
for international factors, including capital flows, in the spread of the 2007–09
crisis.
Foreign and Domestic Debt Crises
Theories on foreign debt crises and default are closely linked to those explaining
sovereign lending. Absent military action, lenders cannot seize collateral from
another country, or at least from a sovereign, when it refuses to honor its debt
obligations. Without an enforcement mechanism—the analogue to domestic
bankruptcy—economic reasons, instead of legal arguments, are needed to explain
why international (sovereign) lending exists at all.
As a gross simplification, models so far rely on either intertemporal or intra-
temporal sanctions. Intertemporal sanctions arise because of the threat that future
lending will be cut off if a country defaults (Eaton and Gersovitz, 1981). With
no access to credit (forever or for some time), the country would no longer be able
to smooth idiosyncratic income shocks using international financial markets.
This cost can induce the country to continue making its debt payments today,
[[AQ: Pls
add to refs
or change
date to
2009.]]
20 Financial Crises: Explanations, Types, and Implications
even without any immediate, direct costs to default. Intratemporal sanctions can
arise from the inability to earn foreign exchange today because trading partners
impose sanctions or otherwise shut the country out of international markets,
again forever or for some time (Bulow and Rogoff, 1989). Both types of cost can
support a certain volume of sovereign lending (Eaton and Fernandez, 1995;
Panizza, Sturzenegger, and Zettelmeyer, 2009).
These models imply that inability or unwillingness to pay, that is, default,
can result from different factors. The incentives governments face in repaying
debt differ from those for domestic corporations and households. They also
vary across models. In the intertemporal model, a country defaults when the
opportunity cost of not being able to borrow ever again is low, one such case
presumably being when the terms of trade are good and are expected to remain
so (Kletzer and Wright, 2000). In the intratemporal sanctions model, in con-
trast, the costs of a cutoff from trade may be the least when the terms of trade
are bad. Aguiar and Gopinath (2006) demonstrate how in a model with persis-
tent shocks, countries default in bad times to smooth consumption. The mod-
els thus also have different implications with respect to a country’s borrowing
capacity.
However, these models are unable to fully account for why sovereigns default
and why creditors lend as much as they do. Many models actually assume that
default does not happen in equilibrium because creditors and debtors want to
avoid the dead-weight costs of default and renegotiation of debt payments.
Although some models have been calibrated to match actual experiences of
default, models often still underpredict the likelihood of actual defaults. Notably,
countries do not always default when times are bad, as most models predict: Tomz
and Wright (2007) report that output was below trend in only 62 percent of
default cases. Models also underestimate the willingness of investors to lend to
countries in spite of large default risk. Moreover, changes in the institutional
environment, such as those implemented after the debt crises of the 1980s, do not
appear to have modified the relationship between economic and political vari-
ables and the probability of a debt default. Together, these factors suggest that
models still fail to capture all aspects necessary to explain defaults (Panizza,
Sturzenegger, and Zettelmeyer, 2009).
Although domestic debt crises have occurred throughout history, these epi-
sodes received only limited attention in the literature until recently. Economic
theory assigns a trivial role to domestic debt crises because models often assume
that governments always honor their domestic debt obligations—the typical
assumption is of “risk-free” government assets. Models also often assume
Ricardian equivalence, making government debt less relevant. However, recent
reviews of history (Reinhart and Rogoff, 2009b) show that few countries were
able to escape default on domestic debt, with often adverse economic conse-
quences.
Government default on domestic debt often happens through bouts of high
inflation caused by abuse of the government monopoly on currency issuance.
One such episode was when the United States experienced an inflation rate of
Claessens and Kose 21
close to 200 percent in the late 1770s. The periods of hyperinflation in some
European countries following World War II were also in this category. Debt
defaults in the form of inflation are often followed by currency crashes. In the
past, countries would often “debase” their currency by reducing the metal content
of coins or switching to another metal. This tactic reduced the real value of gov-
ernment debt and thus provided fiscal relief. There have also been other forms of
debt “default,” including through financial repression (Reinhart, Kirkegaard, and
Sbrancia, 2011). After inflation or debasing crises, it takes a long time to convince
the public to start using the currency again. This, in turn, significantly increases
the fiscal costs of inflation stabilization, leading to large negative real effects of
high inflation and associated currency crashes.
Debt intolerance tends to be associated with the extreme duress many emerg-
ing market economies experience at levels of external debt that would often be
easily managed by advanced economies. Empirical studies on debt intolerance
and serial default suggest that, although safe debt thresholds hinge on country-
specific factors, such as a country’s record of default and inflation, when the
external debt level of an emerging economy is greater than 30–35 percent of
GNP, the likelihood of an external debt crisis rises substantially (Reinhart and
Rogoff, 2009a). More important, when an emerging market economy becomes a
serial defaulter on its external debt, its debt intolerance increases, making it very
difficult to graduate to the club of countries that have continuous access to global
capital markets.
Many challenges remain with regard to modeling the ability of countries to
sustain various types of domestic and external debt. An important challenge is
that the form of financing countries use is endogenous. Jeanne (2003) argues that
short-term (foreign exchange) debt can be a useful commitment device for coun-
tries to employ good macroeconomic policies. Diamond and Rajan (2001) posit
that banks in developing countries have little choice but to borrow short term to
finance illiquid projects given the low-quality institutional environments in
which they operate. Eichengreen and Hausmann (1999) propose the “original
sin” argument, explaining how countries with unfavorable conditions have no
choice but to rely mostly on short-term, foreign currency–denominated debt as
their main source of capital. More generally, although short-term debt can
increase vulnerabilities, especially when the domestic financial system is underde-
veloped, poorly supervised, and subject to governance problems, it also may be
the only source of (external) financing for a capital-poor country with limited
access to equity or foreign direct investment inflows. Thus, the country’s accumu-
lation of short-term debt and increasing vulnerability to crises are simultaneous
outcomes.
More generally, the deeper causes behind debt crises are hard to separate
from the proximate causes. Many of the vulnerabilities raising the risk of a debt
crisis can result from factors related to financial integration, political economy,
and institutional environments. Opening up to capital flows can make coun-
tries with profligate governments and weakly supervised financial sectors more
vulnerable to shocks. McKinnon and Pill (1996, 1998) describe how moral
22 Financial Crises: Explanations, Types, and Implications
hazard and inadequate supervision combined with unrestricted capital flows
can lead to crises as banks incur currency risks. Debt crises are also likely to
involve sudden stops or currency or banking crises (or various combinations),
making it hard to identify the initial cause. Empirical studies of the identifica-
tion of causes are thus subject to the usual problems of omitted variables,
endogeneity, and simultaneity. For example, although using short-term (foreign
currency) debt as a crisis predictor may work, it does not constitute a proof of
the root cause of the crisis. The difficulty of identifying the deeper causes is
more generally reflected in the fact that debt crises have occurred throughout
history.
Banking Crises
Banking crises are quite common, but perhaps the least understood type of crisis.
Banks are inherently fragile, making them subject to runs by depositors.
Moreover, the problems of individual banks can quickly spread to the whole
banking system. Although public safety nets, including deposit insurance, can
limit this risk, public support comes with distortions that can actually increase the
likelihood of a crisis. Institutional weaknesses can also elevate the risk of a crisis.
For example, banks depend heavily on the informational, legal, and judicial envi-
ronments to make prudent investment decisions and collect on their loans. With
institutional weaknesses, risks can be higher. Although banking crises have
occurred over the centuries and exhibited some common patterns, their timing
remains hard to predict empirically.
Bank Runs and Banking Crises
Financial institutions are inherently fragile entities, giving rise to many possible
coordination problems. Because of their roles in maturity transformation and
liquidity creation, financial institutions operate with highly leveraged balance
sheets. Hence, banking and other similar forms of financial intermediation can be
precarious undertakings. Fragility makes coordination, or lack thereof, a major
challenge in financial markets. Coordination problems arise when investors or
institutions take actions—like withdrawing liquidity or capital—merely out of
fear that others will also take such actions. Given this fragility, a crisis can easily
occur in which large amounts of liquidity or capital are withdrawn because of a
self-fulfilling belief: it happens because investors fear it will happen. Small shocks,
whether real or financial, can translate into turmoil in markets and even a finan-
cial crisis.
A simple example of a coordination problem is a bank run. It is a truism that
banks borrow short and lend long. This maturity transformation reflects the
preferences of consumers and borrowers. However, it makes banks vulnerable
to sudden demands for liquidity, that is, runs (the seminal reference here is
Diamond and Dybvig, 1983). A run occurs when a large number of customers
withdraw their deposits because they believe the bank is, or might become,
insolvent. As a bank run proceeds, it generates its own momentum, leading to
Claessens and Kose 23
a self-fulfilling prophecy (or perverse feedback loop): as more people withdraw
their deposits, the likelihood of default increases, encouraging further with-
drawals. This sequence can destabilize the bank to the point that it faces bank-
ruptcy because it cannot liquidate assets fast enough to cover its short-term
liabilities.
These fragilities have long been recognized, and markets, institutions, and
policymakers have developed many coping mechanisms (Dewatripont and
Tirole, 1994). Market discipline encourages institutions to limit vulnerabilities.
At the firm level, intermediaries have adopted risk-management strategies to
reduce their fragility. Furthermore, microprudential regulation, with supervi-
sion to enforce rules, is designed to reduce the risky behavior of individual
financial institutions and can help engineer stability. Deposit insurance can
eliminate the concerns of small depositors and can help reduce coordination
problems. Lender-of-last-resort facilities (i.e., central banks) can provide short-
term liquidity to banks during periods of elevated financial stress. Policy inter-
vention by the public sector, such as public guarantees, capital support, and
purchases of nonperforming assets, can mitigate systemic risk when financial
turmoil hits.
Although regulation and safety net measures can help, when poorly designed
or implemented these measures can increase the likelihood of a banking crisis.
Regulations aim to reduce fragility (for example, limits on balance sheet mis-
matches stemming from interest rate, exchange rate, or maturity mismatches, or
certain activities of financial institutions). Regulation and supervision, however,
often find themselves playing catch-up with innovation. And they may be poorly
designed or implemented. Support from the public sector can also have distor-
tionary effects (Barth, Caprio, and Levine, 2006). Moral hazard caused by a state
guarantee (e.g., explicit or implicit deposit insurance) may, for example, lead
banks to assume too much leverage. Institutions that know they are too big to fail
or unwind can take excessive risks, thereby creating systemic vulnerabilities.18
More generally, fragilities in the banking system can arise because of policies at
both the micro and macro levels (Laeven, 2011).
History of Bank Runs
Runs have occurred in many countries throughout history. In the United States,
bank runs were common during the banking panics of the 1800s and in the early
1900s (during the Great Depression). Only with the introduction of deposit
insurance in 1933 did most runs stop in the United States (Calomiris and
Gorton, 1991). Widespread runs also happened frequently in emerging markets
and developing countries in the later decades of the twentieth century, such as in
Indonesia during the 1997 Asian financial crisis. Runs occurred more rarely in
18 Ranciere and Tornell (2011) model how nancial innovations can allow institutions to maximize a
systemic bailout guarantee, and report evidence supporting this mechanism in the context of the 2007
U.S. nancial crisis.
24 Financial Crises: Explanations, Types, and Implications
other advanced countries, and have occurred even less so in the first decade of the
2000s, in part as a result of the widespread availability of deposit insurance.19 Yet,
Northern Rock, a bank specializing in housing finance in the United Kingdom,
provides a very recent example of a bank run in an advanced country (Shin,
2009). Rapid withdrawals of wholesale market funding also took place during the
2007–09 financial crisis, when several investment banks and some commercial
banks faced large liquidity demands from investors.
Widespread runs can also take place in nonbank financial markets. For exam-
ple, in the United States during the fall of 2008, some mutual funds “broke the
buck,” that is, their net asset value fell below par. This triggered sharp outflows
from individual investors and many other mutual funds (Wermers, 2012). This
“run,” in turn, led the government to provide a guarantee against further declines.
These guarantees are a continued source of fiscal risk because the government
might be forced to step in to prevent a run again. Other investment vehicles
specializing in specific asset classes (such as emerging markets) also experienced
sharp outflows because there was a general flight to safety (i.e., more demand for
advanced countries’ government bonds and treasury bills). More generally, the
2007–09 crisis has been interpreted by many as a widespread liquidity run
(Gorton, 2009).
Deeper Causes of Banking Crises
Although funding and liquidity problems can be triggers or proximate causes, a
broader perspective shows that banking crises often relate to problems in asset
markets. Banking crises may appear to originate from the liability side, but they
typically reflect solvency issues. Banks often run into problems when many of
their loans go sour or when securities quickly lose their value. This happened in
crises as diverse as the Nordic banking crises in the late 1980s, the crisis in Japan
in the late 1990s, and the crises in Europe in the 2010s. In all of these episodes,
no large-scale deposit runs on banks occurred, but large-scale problems arising
from real estate loans resulted in undercapitalization in many banks and required
government support. Problems in asset markets, such as those related to the sub-
prime and other mortgage loans, also played a major role during the 2007–09
crisis. These types of problems in asset markets can go undetected for some time,
and a banking crisis often comes into the open through the emergence of funding
difficulties among a large fraction of banks.
Although the exact causes are often hard to identify, and risks can be difficult
to foresee, in hindsight, banking crises and other financial panics are rarely ran-
dom events. Banking panics more likely to occur near the peak of the business
cycle, with recessions on the horizon, because of concerns that loans will not be
19 Deposit insurance, rst introduced in the United States in 1933, was adopted following World War
II by many advanced countries, and has since been employed by developing countries (Demirgüç-
Kunt, Kane, and Laeven, 2008). Although deposit insurance can reduce the risk of bank runs, it
can have severe negative side e ects, including increased moral hazard, leading to more risk taking.
Claessens and Kose 25
repaid (Gorton, 1988; Gorton and Winton, 2003). Depositors, noticing the
risks, demand cash from the banks. Because banks cannot immediately satisfy all
requests, a panic may occur. The large-scale bank distress in the 1930s in the
United States was traced back to shocks in the real sector. In many emerging
markets, banking crises were triggered by external developments, such as sharp
movements in capital flows, global interest rates, and commodity prices, which,
in turn, led to an increase in nonperforming loans.
Panics can also be policy induced. Panics can take place when some banks
experience difficulties and governments intervene in an ad hoc manner, without
providing clear signals about the status of other institutions. The banking panic
in Indonesia in 1997 has been attributed to poorly managed early interventions.20
Runs can also be directly triggered by government actions: the runs on banks in
Argentina in 2001 occurred when the government imposed a limit on withdraw-
als, making depositors question the soundness of the entire banking system. The
2007–09 financial crisis in advanced countries has, in part, been attributed to the
lack of consistency across government interventions and other policy measures
(Calomiris, 2009).
Structural problems can also lead to banking crises. Studies have identified
some common, structural characteristics related to banking crises (e.g., Lindgren,
Garcia; and Saal, 1996; Barth, Caprio, and Levine, 2006; and many others).
These include notably poor market discipline caused by moral hazard and exces-
sive deposit insurance; limited disclosure; weak corporate governance frame-
works; and poor supervision, in part due to conflicts of interest.21 Other structural
aspects found to increase the risk of a crisis include large state ownership and
limited competition in the financial system, including restricted entry from
abroad; and an undiversified financial system, for example, a dominance of banks
(World Bank, 2001).
Because the financial sector receives many forms of public support, policy
distortions that can lead to crises easily arise. In the context of the 2007–09 finan-
cial crisis in the United States, large government support for housing finance
(through the government-sponsored enterprises Fannie Mae and Freddie Mac)
has been argued to lead to excessive risk taking. The tendency to pursue accom-
modative monetary and fiscal policies following crises, at least in some advanced
countries, can also be interpreted as a form of ex post systemic bailout, which, in
20 See Honohan and Laeven (2007) for this and other case studies.
21 Failures in regulation and supervision remain the most mentioned cause for crises, despite signi cant
upgrading of regulations, supervisory capacity, and expertise. For analysis of how weaknesses in regula-
tion and supervision contributed to the 2007–09 crisis, see Čihák and others (2012). Analysis sug-
gests, though, that the design of regulation matters for the risk of nancial distress. Barth, Caprio, and
Levine (2006, 2012), for example, suggest not relying solely on regulation and supervision. Rather,
they advocate, among other actions, an active but carefully balanced mix of market discipline and o -
cial regulation and supervision. is should all be supported by institutional infrastructure that pro-
tects property rights; allows for competition, including engagement with global nance; and ensures
adequate information. e wider threats to nancial stability, including those arising from political
economy and corruption, should be kept at bay.
26 Financial Crises: Explanations, Types, and Implications
turn, distorts ex ante incentives and can lead to excessive risk taking (Farhi and
Tirole, 2012). Another often-cited problem has been “connected lending,” which
leads to perverse incentives, because politically connected firms and individuals
borrow too much from banks, which can cause a buildup of systemic risk. Some
well-studied cases of this phenomenon include Mexico (La Porta and others,
2000; Haber, 2005), the Russian Federation (Laeven, 2001), and Indonesia
(Fisman, 2001).
Systemic banking panics still require further study because many puzzles
remain, especially about how contagion arises. The individual importance of
the factors listed above in contributing to crises is not known, in part because
many of them tend to be observed at the same time. Fragilities remain inherent
to the process of financial intermediation, with the causes for panics often dif-
ficult to understand. For reasons usually unknown, small shocks can result in
significant problems for the entire financial system. Similarly, shocks may spill
over from one market to another or from one country to others, leading to
financial crises.
The 2007–09 financial crisis had many elements common to other crises.
Much has been written about the causes of the 2007–09 crisis (Calomiris, 2009;
Gorton, 2009; Claessens and others, 2012a; and many others). Although observ-
ers differ on the exact weights, the list of factors common to previous crises is
generally similar. Four features often mentioned in common are asset-price
increases that turned out to be unsustainable, credit booms that led to excessive
debt burdens, buildups of marginal loans and systemic risk, and the failure of
regulation and supervision to keep up with financial innovation and get ahead of
the crisis when it erupted.22
The global financial crisis was, however, also rooted in some new factors. Four
key new aspects often mentioned are the widespread use of complex and opaque
financial instruments; the increased interconnectedness among financial markets,
nationally and internationally, with the United States at the core; the high degree
of leverage of financial institutions; and the central role of the household sector.
These factors, in combination with those common to other crises, and fueled at
times by poor government interventions during different stages, led to the worst
financial crisis since the Great Depression. It required massive government out-
lays and guarantees to restore confidence in financial systems. The consequences
of the crisis are still being felt in many advanced countries and as of early 2013
the crisis is still ongoing in some European countries.
22 Speci cally, there was an increase in real estate prices in many markets around the world, paral-
leled by a run-up in other asset prices, especially in equity. Reinhart and Rogo (2008) demonstrate
that the appreciation of equity and house prices in the United States before the crisis was even more
dramatic than appreciations experienced before the “Big Five” post–World War II debt crises. As
the global crisis unfolded, those countries that had experienced the greatest increases in equity and
house prices during the boom found themselves most vulnerable (Feldstein, 2009). Unfortunately,
the similarity in crises patterns was, as is often the case, only recognized after the fact.
Claessens and Kose 27
IDENTIFICATION, DATING, AND
FREQUENCY OF CRISES
A large body of work has been devoted to the identification and dating of
crises, but ambiguities remain. Methodologies based on the main theories
explaining various types of crises can be used to identify and classify crises.23
In practice, however, this classification is not so straightforward. Although
currency and inflation crises and sudden stops lend themselves to quantitative
approaches, the dating of debt and banking crises is typically based on qualita-
tive and judgmental analyses. Irrespective of type, variations in methodologies
can lead to differences in the start and end dates of crises. And, as noted,
various types of crises can overlap in a single episode, creating possible ambi-
guities about how to classify the episode. In practice, a wide range of quantita-
tive and qualitative methods involving judgment are used to identify and
classify crises.
The difficulties arise, in part, because the frequency and types of financial
crises have evolved. For example, currency crises were dominant during the
1980s, whereas banking crises and sudden stops became more prevalent in the
1990s and the first decade of the 2000s. This section begins with a summary of
common identification and dating methods (IMF, 1998; Reinhart and Rogoff,
2009b; and Laeven and Valencia, 2008, and Chapter 2, this volume).It then
provides a summary of the frequency of crises over time and across groups of
countries, and of the overlap among types of crises.
Identification and Dating
Because currency crises involve large changes in exchange rates, and related infla-
tion crises, they are relatively easy to identify. Reinhart and Rogoff (2009b) dis-
tinguish these episodes by assigning threshold values for the relevant variables. For
currency crises, they consider exchange an rate depreciation in excess of 15 per-
cent per year to be a crisis, whereas for inflation, they adopt a threshold of 20
percent per year.24 A currency crisis is defined in Frankel and Rose (1996) as a
cumulative depreciation of at least 25percent over a 12-month period, and at
least 10percentage points greater than in the preceding 12months. The dates
identified are obviously sensitive to the thresholds used. These thresholds can be
universal, specific to the sample of countries under study, or country specific (as
23 Dating does not, of course, establish causes, including whether the event was a rational outcome of
some other “cause” (e.g., a crash in an asset price may be rational in response to a real shock).
24 eir comprehensive analysis includes the period 1258–1799, during which the principal means of
exchange was metallic coins. During this earlier era, instead of modern in ation and currency crises,
there were a number of episodes of currency debasements, which were associated with a reduction in
the metallic content of coins in circulation in excess of 5 percent. ey also consider the introduction
of a brand new currency replacing a much-depreciated earlier currency in circulation as another form
of currency debasement, which is still practiced in the modern era.
28 Financial Crises: Explanations, Types, and Implications
when the threshold is adjusted for the country’s “normal” exchange rate varia-
tions).
A measurement issue naturally arises if no significant adjustment in the cur-
rency occurred despite pressures or attacks. Movements in international reserves
or adjustments in interest rates can absorb exchange rate pressures and prevent or
moderate the fluctuations in the rate. However, episodes involving such pressures
or attacks are also important to document and study. To address this issue, start-
ing with Eichengreen, Rose, and Wyplosz (1995), different methodologies have
been employed. A composite index of speculative pressure is often constructed
based on actual exchange rate changes and movements in international reserves
and interest rates, with weights chosen to equalize the variance of the compo-
nents, thereby preventing one component from dominating the index. Thresholds
are then set to date the currency events, including both large exchange rate move-
ments and periods of pressure.25
Sudden stops and balance of payments crises can also be objectively classified.
Calvo, Izquierdo, and Mejia (2004) define systemic sudden stop events as epi-
sodes with output collapses that coincide with large reversals in capital flows.
Calvo, Izquierdo, and Mejía (2008) expand on these criteria in two ways: first,
the period contains one or more year-on-year declines in capital flows that are at
least two standard deviations below its sample mean (thus addressing the “unex-
pected” requirement of a sudden stop); second, it starts (ends) when the annual
change in capital flows falls (exceeds) one standard deviation below (above) its
mean (Mauro and Becker, 2006).
Because methodologies vary, various samples of events follow. Calvo,
Izquierdo, and Mejia, (2004). identified 33 sudden stop events with large and
mild output collapses in a sample of 31 emerging market countries. Although
studies use different cutoff criteria (Calvo and Reinhart, 2000; Milesi-Ferretti and
Razin, 2000; Calvo, Izquierdo, and Loo-Kung, 2006), the datings of events are
very similar. Some studies also require a decline in output, but later studies
excluded this requirement (since a decline may be endogenous) and replaced it
with the requirement of large spikes in the Emerging Markets Bond Index spread,
indicating a shift in the supply of foreign capital (Calvo, Izquierdo, and Mejia,
2008). Cardarelli, Elekdag, and Kose (2010) consider a large capital inflow epi-
sode to end “abruptly” if the ratio of net private capital inflows to GDP in the
year after the episode terminates is more than 5percentage point lower than at
the end of the episode—closely following the definition of sudden stops in the
literature. An episode is also considered to finish abruptly if its end coincides with
a currency crisis.
Balance of payments crises can similarly be identified using capital flow data.
Despite some differences in approach (e.g., how reserve losses are treated) and
statistical variations across studies (e.g., whether the same current account deficit
threshold is used for all countries or whether country-specific thresholds are
25 See Frankel and Saravelos (2012) and Glick and Hutchison (2012) for reviews; and Cardarelli, Ele-
kdag, and Kose (2010) for applications.
Claessens and Kose 29
used), many of them point to similar samples of actual events. Forbes and
Warnock (2011) analyze a large set of countries’ gross flows instead of the more
typical net capital flows (or current account). They identify episodes of extreme
capital flow movements using quarterly data, differentiating activity by foreigners
and domestics. They classify episodes as “surge,” “stop,” “flight,” or “retrench-
ment,” with surges and stops related, respectively, to periods of large gross capital
in- or outflows by foreigners, and flights and retrenchments, respectively, related
to periods of large capital out- or inflows by domestic residents.
External sovereign debt crises are generally easy to identify as well, although dif-
ferences in classifications across studies remain. Sovereign defaults are relatively
easy to identify because they involve a unique event, the default on payments.
Typical dating of such episodes relies on the classification by rating agencies or on
information from international financial institutions (see McFadden and others,
1985; and papers summarized in Sturzenegger and Zettelmeyer, 2007). Still,
there are choices of methodology. For example, differences arise from considering
the magnitude of defaults (whether default has to be widespread or on just one
class of claims), default by type of claim (such as bank claims or bond claims,
private or public claims), and the length of default (missing a single or several
payments). Others look instead at the increases in spreads in sovereign bonds as
an indicator of the probability of default (Edwards, 1984).
The end of a default is harder to date. A major issue with dating an episode,
including of default and sovereign debt crises, can be identifying its end, that is,
when default or crisis is over. Some studies date this as when countries regained
access in some form to private financial markets. Others date it as when countries
regain a certain credit rating (IMF, 2005, 2011). As a consequence, differences
arise as to how long it takes for a country to emerge from a sovereign default.
Domestic debt crises are more difficult to identify. First, consistent historical
data on domestic public debt across countries were missing, at least until
recently. Furthermore, following a crisis, unrecorded debt obligations can come
to light. However, Abbas and others (2011) and Reinhart and Rogoff (2009b)
have since made significant progress in putting together historical series on
domestic debt. Second, countries can default in many ways: outright direct
default, periods of hyper or high inflation, punitive taxation of interest pay-
ments, forced interest rate or principal adjustments or conversions, gold clause
abrogation, debasing of currency, and forms of financial repression. Reinhart
and Rogoff (2009b) describe each of these and make clear that considerable
ambiguity remains in classifications of defaults, especially of “inflation-related
default” episodes.
Determining start and end dates for banking crises can be particularly challeng-
ing. Such crises are usually dated by researchers using a qualitative approach on
the basis of a combination of events, such as forced closures, mergers, or govern-
ment takeover of many financial institutions; runs on several banks; or the exten-
sion of government assistance to one or more financial institutions. In addition,
in-depth assessments of financial conditions are used as a criterion. Another
metric is the fiscal cost associated with resolving these episodes. The end of a
30 Financial Crises: Explanations, Types, and Implications
banking crisis is also difficult to identify, in part, because its effects can linger for
some time.
There are large overlaps in the dating of banking crises across different studies.
Reinhart and Rogoff (2009b) date the beginning of banking crises by two types
of events: First are bank runs that lead to the closure of, merging, or takeover by
the public sector of one or more financial institutions. Second, if there are no
runs, they check the closure of, merging of, takeover of, or large-scale public
assistance to an important financial institution. As they acknowledge, this
approach has some obvious drawbacks: it could date crises too late (or too early)
and gives no information about the end date of these episodes. Still, the classifica-
tion of Reinhart and Rogoff (2009b) largely overlaps with that of Laeven and
Valencia (Chapter 2, this volume).
Differences remain in the dating of crises, which can affect analyses. One
example of a difference is the start of Japan’s banking crisis, which is dated by
Reinhart and Rogoff (2009b) as 1992 and as 1997 by Laeven and Valencia
(Chapter 2, this volume). Another example, with significant implications for
analysis, is from Lopez-Salido and Nelson (2010). Analyzing events surrounding
financial market difficulties in the United States over the past 60 years, Lopez-
Salido and Nelson report three distinct crises: 1973–75; 1982–84; and 1988–91.
These differ from Reinhart and Rogoff (2009b), who identify only one crisis
(1984–91), and Laeven and Valencia (Chapter 2, this volume) who also identify
only one crisis, 1988 in that period (and another in 2007, since that period). In
contrast to most claims that recoveries are systematically slower after financial
crises, Lopez-Salido and Nelson (2010) argue on the basis of their analysis that
crises need not impact the strength of recoveries.26 These differences clearly show
the importance of dating.
Last, asset-price and credit booms, busts, and crunches, common to many
crises, are relatively easy to classify, but again approaches vary across studies. Asset
prices (notably equity and to a lesser degree house prices) and credit volumes are
available from standard data sources. Large changes (in nominal or real terms) in
these variables can thus easily be identified. Still, because approaches and focus
vary, so do the classifications of booms, busts, and crunches. Claessens, Kose, and
Terrones (2012) use the classical business cycle approach, looking at the level of
real asset prices or credit to identify peaks and troughs in these variables. They
then focus on the top and bottom quartiles of these changes to determine the
booms, busts, or crunches. Large deviations from trend in real credit growth
(Mendoza and Terrones, 2008) and from the credit-to-GDP ratio can also be used
to classify credit booms. And Gourinchas, Valdes, and Landerretche (2001) clas-
sify 80 booms based on absolute and relative (to the credit-to-GDP ratio) devia-
tion from trend, but rather than setting the thresholds first, they limit the number
of episodes to classify.
26 Bordo and Haubrich (2012) and Howard, Martin, and Wilson (2011) also argue that recoveries
following nancial crises do not appear to be di erent from typical recoveries.
Claessens and Kose 31
Different types of crises can overlap and do not necessarily take place as inde-
pendent events. One type of crisis can lead to another type. Or two crises can take
place simultaneously because of common factors. To classify a crisis as only one
type can be misleading when one event is really a derivative of another. Crises in
emerging markets, for example, have often been combinations of currency and
banking crises associated with sudden stops in capital flows, and subsequently
turning into sovereign debt crises. Overall, considerable ambiguity remains on the
identification and dating of financial crises, which should serve as an important
caveat in reviewing the frequency and distribution of crises over time, as is done
in the next section.
Frequency and Distribution
Crises have afflicted both emerging market economies and advanced countries
throughout centuries. In the three decades before 2007, most crises occurred in
emerging markets and included the Latin American crises in the late 1970s and
early 1980s, the Mexican crisis in 1995, and the East Asian crises in the mid- to
late 1990s. The susceptibility of emerging markets to crises is not new (Reinhart
and Rogoff, Chapter 3, this volume). History shows that many countries that are
advanced today, including Australia, Spain, the United Kingdom, and the United
States, experienced financial crises when they were going through their own emer-
gence processes in the 1800s. For example, France defaulted on its external debt
eight times during the period 1550–1800. Some advanced countries experienced
crises in recent decades as well, from the Nordic countries in the late 1980s, to
Japan in the 1990s. The most recent crises, starting with the U.S. subprime crisis
in late 2007 and then spreading to other advanced countries, show (once again)
that crises can affect all types of countries.
Some claim that crises have become more frequent. The three decades after
World War II were relatively crisis free, whereas the most recent three decades
have seen many episodes (Figure 1.4). Some relate this increase to more liberal-
ized financial markets, including floating exchange rates and greater financial
integration. Using macroeconomic and financial series for 14 advanced countries
for 1870–2008, Jordà, Schularick, and Taylor (2011) report no financial crises
during the Bretton Woods period of highly regulated financial markets and capi-
tal controls. Also, Bordo and others (2001) argue that the sudden stop problem
has become more severe since the abandonment of the gold standard in the early
1970s.
More recent crises seem to have been shorter, but banking crises still last the
longest. The median duration of debt-default episodes in the post–World War II
period has been much shorter than for the period 1800–1945, possibly because
of improvement in policies in the later period, improved international financial
markets, or the active involvement of multilateral lending agencies (see further
Das, Papaioannou, and Trebesch, 2012). Currency and sudden stop crises are
relatively short (almost by definition). With the major caveat that their ends are
hard to date, banking crises tend to last the longest, consistent with their large
real and fiscal impacts.
32 Financial Crises: Explanations, Types, and Implications
Financial crises clearly often come in bunches. Sovereign defaults tend to come
in waves and in specific regions. Jordà, Schularick, and Taylor (2011) report that
there were five major periods when a substantial number of now-advanced coun-
tries experienced crises: 1890, 1907, 1921, 1930–31, and 2007–08. Earlier crises
bunched around events such as the Napoleonic Wars. Examples of bunches since
the 1980s include the Latin America debt crises in the 1980s; in 1992, the
European Exchange Rate Mechanism currency crises; in the late 1990s, the East
Asian, Russian, and Brazilian financial crisis; the multiple episodes observed in
2007–08; and the crises in Europe still ongoing in 2013. Periods of widespread
sovereign defaults often coincide with a sharp rise in the number of countries
going through banking crises. These coincidences point toward common factors
driving these episodes as well as spillovers of financial crises across borders.
Some types of crises are more frequent than others. Comparisons can be made
for the post–Bretton Woods period (although some types of crises have been
documented for longer periods, not all have; and currency crises were nonexistent
Figure 1.4 Coincidence of Financial Crises: 1970–2011
Sources: The dates of banking, currency, and debt crises are from Laeven and Valencia (2008, 2011) and the dates of sud-
den stops are from Forbes and Warnock (2011).
Note: A financial crisis starting at time T coincides with another financial crisis if the latter starts at any time between T–3
and T+3. A financial crisis starting at time T coincides with two other financial crises if the latter two start at any time
between T–3 and T+3. The sample consists of 181 countries.
Banking
crises
(147)
Banking
crises
(147)
Banking
crises
(147)
Currency
crises
(217)
Currency
crises
(217)
Currency
crises
(217)
Debt crises (67)
Debt
crises
(67)
Debt
crises
(67)
Sudden stops (219)
Sudden stops (219)Sudden stops (219)
74 53 122
18
224
23
47 54 133
17
29 13
160
151
85 16 44
170
4
42 3
36 24
6
24 1
188
AQ: T= month,
quarter or year?
Claessens and Kose 33
during the fixed exchange rate period; together this necessitates the common, but
shorter period). Of the total number of crises Laeven and Valencia (Chapter 2,
this volume) report, 147 are banking crises, 217 are currency crises, and 67 are
sovereign debt crises during the period 1970–2011 (note that several countries
experienced multiple crises of the same type).
However, as noted before, the various types of crises overlap to some extent.
Currency crises frequently tend to overlap with banking crises, the so-called twin
crises (Kaminsky and Reinhart, 1999). In addition, sudden stop crises, not sur-
prisingly, can overlap with currency and balance of payments crises, and some-
times sovereign crises (Figure 1.5). Of the 431 banking (147), currency (217),
and sovereign (67) crises Laeven and Valencia report in Chapter 2, this volume,
they consider 68 to be twin crises, and 8 can be classified as triple crises. There
are relative differences in coincidences of these episodes. A systemic banking cri-
sis, for example, often involves a currency crisis, and a sovereign debt crisis some-
times overlaps with other crises—20 out of 67 sovereign debt crises are also
banking crises, and 42 are also currency crises.
REAL AND FINANCIAL IMPLICATIONS OF CRISES
Macroeconomic and financial consequences of crises are typically severe and are
similar across the various types of crisis. Despite the obvious differences between
crises, the macroeconomic variables follow similar patterns. Large output losses
are common and other macroeconomic variables (consumption, investment, and
industrial production) typically register significant declines. Financial variables
Figure 1.5 Average Number of Financial Crises per Decade
Sources: The dates of banking, currency, and debt crises are from Laeven and Valencia (2008, 2011), and the dates of sud-
den stops are from Forbes and Warnock (2011).
Note: This figure shows the average number of financial crises in each of the decades.
10
8
6
4
2
0
Currency crises
Number of crises
1970–79 1980 –89 1990–99 2000– 11
Banking crises Debt crises Sudden stops
34 Financial Crises: Explanations, Types, and Implications
like asset prices and credit usually follow qualitatively similar patterns across
crises, albeit with variations in duration and severity. This section provides a
summary of the literature on the macroeconomic and financial implications of
crises.
Real Effects of Crises
Financial crises have large economic costs with large effects on economic activity.
Many recessions follow from financial crises (Figure 1.6) (Claessens, Kose, and
Terrones, 2009, 2012). And financial crises often tend to make these recessions
worse than a “normal” business cycle recession (Figure 1.7). The average duration
of a recession associated with a financial crisis is some six quarters, two more than
a normal recession. There is also typically a larger output decline in recessions
associated with crises than in other recessions. And the cumulative loss of a reces-
sion associated with a crisis (computed using lost output relative to the precrisis
peak) is also much larger than that of a recession without a crisis.
The real impact of a crisis on output can be computed using various
approaches. For a large cross-section of countries and a long period, Claessens,
Kose, and Terrones (2012) use the traditional business cycle methodology to
identify recessions. They show that recessions associated with credit crunches and
housing busts tend to be more costly than those associated with equity price
busts. Overall losses can also be estimated by adding up the differences between
trend growth and actual growth for a number of years following the crisis or until
the time when annual output growth returns to its trend. On this basis, Laeven
Figure 1.6 Coincidence of Recessions and Crises, 1960–2011
Source: IMF staff calculations.
Notes: The sample includes data for 23 advanced countries and 38 emerging market countries. A recession is associated
with a financial crisis if the financial crisis starts at the same time as the recession or one year before or two years after the
peak of the recession.
350
300
250
200
150
100
50
0
Number of recessions
World Advanced economies Emerging market
economies
All recessions
Recessions with crises
Claessens and Kose 35
Figure 1.7 Real Implications of Financial Crises, Crunches, and Busts, 1960–2011
Source: IMF staff calculations.
Notes: The sample includes data for 23 advanced countries and covers 1960–2011. For “Duration” means are shown, for
“Cumulative Loss” and “Amplitude” medians are shown. Amplitude is calculated based on the decline in output from
peak to trough of a recession, duration is the number of quarters between peak and trough, and cumulative loss com-
bines information about the duration and amplitude to measure overall cost of a recession and is expressed in percent.
Disruptions (severe disruptions) are the worst 25 percent (12.5 percent) of downturns calculated by amplitude. A reces-
sion is associated with a (severe) credit crunch or a house price bust if the (severe) credit crunch or the house price bust
starts at the same time or one quarter before the peak of the recession. A recession is associated with a financial crisis
if the financial crisis starts at the same time as the recession or one year before or two years after the peak of the reces-
sion. The severe financial crises are the worst 50 percent of financial crises as measured by output decline during the
recession.
a. Duration
b. Amplitude
c. Cumulative loss
Recessions without
Recessions with
Recessions with severe
Recessions without
Recessions with
Recessions with severe
Recessions without
Recessions with
Recessions with severe
6
4
2
0
0
0
–1
–2
–2
–4
–6
–8
–10
–3
–4
–5
QuartersOutput (%)Output (%)
Financial crises Credit crunches House price busts
Financial crises Credit crunches House price busts
Financial crises Credit crunches House price busts
36 Financial Crises: Explanations, Types, and Implications
and Valencia (Chapter 2, this volume) estimate that the cumulative cost of bank-
ing crises is, on average, about 23 percent of GDP during the first four years.27
Regardless of the methodology, losses do vary across countries. Overall losses tend
to be larger in emerging markets, but the large losses in recent crises in advanced
countries (e.g., both Iceland and Ireland’s output losses exceeded 100 percent)
paint a different picture. The median output loss for advanced countries is now
about 33 percent, which exceeds that of emerging markets at 26 percent.
Crises are generally associated with significant declines in a wide range of
macroeconomic aggregates. Recessions following crises exhibit much larger
declines in consumption, investment, industrial production, employment, and
exports and imports compared with those recessions without crises. For example,
the decline in consumption during recessions associated with financial crises is
typically seven to ten times larger than those without such crises in emerging
markets. In recessions without crises, the growth rate of consumption slows down
but does not fall below zero. In contrast, consumption tends to contract during
recessions associated with financial crises, another indication of the significant toll
that crises have on overall welfare.
Large declines in global output also occur during financial crisis episodes. The
significant cost for the world economy associated with the Great Depression has
been documented in many studies. The 2007–09 global financial crisis was asso-
ciated with the worst recession since World War II, causing a 2 percent decline in
world per capita GDP in 2009. In addition to 2009, the world economy experi-
enced a global recession and witnessed crises in multiple countries in two other
postwar years (Kose, Loungani, and Terrones, forthcoming). In 1982, a global
recession was associated with a host of problems in advanced countries, as well as
with the Latin American debt crisis.28 The global recession in 1991 also coincided
with financial crises in many parts of the world, including difficulties in U.S.
credit markets, banking and currency crises in Europe, and the burst of the asset-
price bubble in Japan. Although world per capita GDP grows by about 2 percent
in a typical year, it declined by about 0.8 percent in 1982 and 0.2 percent in
1991.
Recent studies also document that recoveries following crises tend to be weak
and slow, with long-lasting effects. Kannan, Scott, and Terrones (Chapter 8, this
volume) use cross-country data and conclude that recoveries following financial
crises have typically been slower, and are associated with weak domestic demand
and tight credit conditions. These findings are consistent with those reported in
several other studies (Reinhart and Rogoff, 2009b; Claessens, Kose, and Terrones,
27 ese loss numbers rely on an estimated trend growth, typically proxied by the trend in GDP growth
up to the year preceding the crisis. ese numbers can overstate output losses, however, because the
economy could have experienced a growth boom before the crisis or been on an unsustainable growth
path.
28 Mexico’s default in August 1982 marked the beginning of the crisis and the region’s decade-long
stagnation (the lost decade). A number of Latin American countries, including Argentina, Mexico, and
Venezuela in 1982, and Brazil and Chile in 1983, experienced debt crises during the period.
Claessens and Kose 37
2012; Papell and Prudan, 2011; Jordà, Schularick, and Taylor, 2011). Abiad and
others (Chapter 9, this volume) analyze the medium-term impact of financial
crises and conclude that output tends to be depressed substantially following
banking crises. Specifically, seven years after a crisis, the level of output is typically
about 10 percent lower relative to the precrisis trend (even though growth tends
to return to its precrisis rate eventually). They report that the depressed path of
output is associated with long-lasting reductions of roughly equal proportions in
the employment rate, the capital-to-labor ratio, and total factor productivity.
From a fiscal perspective, banking crises can be especially costly. Both gross
fiscal outlays and net fiscal costs of resolving financial distress and restructuring
the financial sector can be very large. For banking crises, Laeven and Valencia
(Chapter 2, this volume) estimate that fiscal costs, net of recoveries, associated
with crises are on average about 6.8 percent of GDP. These costs can, however, be
as high as 57 percent of GDP and in several cases are greater than 40 percent of
GDP (for example, Chile and Argentina in the early 1980s, Indonesia in the later
1990s, and Iceland and Ireland in 2008). Net resolution costs for banking crises
tend to be higher for emerging markets, at 10 percent of GDP, in contrast to 3.8
percent of GDP for advanced countries. Although gross fiscal outlays can be very
large in advanced countries too—as in many of the recent and ongoing cases—
the final direct fiscal costs have generally been lower in advanced countries,
reflecting better recovery of fiscal outlays.
Debt crises can be costly for the real economy. Borensztein and Panizza
(2009), Levy-Yeyati and Panizza (2011), and Furceri and Zdzienicka (2012)
document that debt crises are associated with substantial GDP losses. Furceri and
Zdzienicka (2012) report that debt crises are more costly than banking and cur-
rency crises and are typically associated with output declines of 3–5 percent after
one year and 6–12 percent after eight years. Gupta, Mishra, and Sahay (2007)
find that currency crises are often contractionary.
The combination of financial system restructuring costs and a slow economy
can lead public debt to rise sharply during financial crises. Reinhart and Rogoff
(2009a) document that crisis episodes are often associated with substantial
declines in tax revenues and significant increases in government spending. For
example, government debt rises by 86 percent, on average, during the three years
following a banking crisis. Using a larger sample, Laeven and Valencia (Chapter
2, this volume) report the median increase in public debt to be about 12 percent
for their sample of 147 systemic banking crises. Including indirect fiscal costs,
such as those resulting from expansionary fiscal policy and reduced fiscal revenues
as a consequence of a recession, makes the overall fiscal costs of the recent crises
in advanced countries actually greater than those in emerging markets, 21.4 per-
cent as compared with 9.1 percent of GDP.29
Although empirical work has not been able to pinpoint the exact reasons, sud-
den stops are especially costly. Using a panel data set for 1975–97 and covering
29 Reinhart and Rogo (2011) provide further statistical analysis of the links between debt and bank-
ing crises.
38 Financial Crises: Explanations, Types, and Implications
24 emerging markets, Hutchison and Noy (2006) finds that while a currency
crisis typically reduces output by 2–3 percent, a sudden stop reduces output by
an additional 6–8 percent in the year of the crisis. The cumulative output loss of
a sudden stop is even larger, about 13–15 percent over a three-year period.30
Edwards (2004) finds sudden stops and current account reversals to be closely
related, with reversals, in turn, having a negative effect on real growth, an effect
that is more pronounced for emerging markets. Cardarelli, Elekdag, and Kose
(2010) examine 109 episodes of large net private capital inflows to 52 countries
during 1987–2007 and report that the typical post-inflow decline in GDP
growth for episodes that end abruptly is about 3 percentage points lower than
during the episode, and about 1 percentage point lower than during the two years
before the episode. These fluctuations are also accompanied by a significant dete-
rioration of the current account during the inflow period and a sharp reversal at
the end.
Financial Effects of Crises
Crises are associated with large downward corrections in financial variables. A
sizable research effort has analyzed the evolution of financial variables around
crises. Some of the studies in this literature focus on crisis episodes using the dates
identified in other work; others consider the behavior of the financial variables
during periods of disruptions, including credit crunches and house and equity
price busts. Although results differ across the types of crises, both credit and asset
prices tend to decline or grow at much lower rates during crises and disruptions
than they do during tranquil periods, confirming the boom-bust cycles in these
variables discussed in previous sections. In a large sample of advanced countries
(Figure 1.8), credit declines by about 7 percent, house prices fall by about 12
percent, and equity prices drop by more than 15 percent during credit crunches
and house and equity price busts, respectively (Claessens, Kose, and Terrones,
2012). Asset prices (exchange rates, equity and house prices) and credit around
crises exhibit qualitatively similar properties in their temporal evolution in
advanced and emerging market countries, but the duration and amplitude of
declines tend to be larger for the latter than for the former.
The most notable drag on the real economy from a financial crisis is the lack
of credit from banks and other financial institutions. Dell’Ariccia, Detragiache,
and Rajan (2008) and Klingebiel, Kroszner, and Laeven (2007) show how after
banking crises, sectors that naturally need more external financing grow more
slowly, likely because banks are impaired in their lending capacity. Recoveries in
aggregate output and its components following recessions associated with credit
crunches tend to take place before the revival of credit growth and turnaround in
30 Of course, this and other analyses can su er from reverse causality. at is, private agents see events
that lead them to predict future drops in a country’s output and, as a result, these agents pull their
capital from the country. In this view, anticipated output drops drive sudden stops, rather than the
reverse. Although possible and reasonable, it is hard to prove or refute this view quantitatively.
Claessens and Kose 39
house prices (Figure 1.9). These temporal patterns are similar to those for house
price busts, that is, economic recoveries start before house prices bottom out dur-
ing recessions coinciding with sharp drops in house prices.
Both advanced and emerging market countries have experienced the phenom-
enon of “creditless recoveries.” Creditless recoveries are quite common in financial
a. House prices
b. Equity prices
Recessions without
Recessions with
Recessions with severe
Recessions without
Recessions with
Recessions with severe
0
–3
–6
–9
–12
–15
–15
–30
–45
15
0
Financial crises Credit crunches House price busts
Financial crises Credit crunches House price busts
Figure 1.8 Financial Implications of Crises, Crunches, and Busts, 1960–2011
Source: IMF staff calculations.
Notes: The sample includes data for 23 advanced countries. Each panel shows the median change in respective variable
during recessions associated with indicated financial events. Disruptions (severe disruptions) are the worst 25 percent
(12.5 percent) of downturns calculated by amplitude. A recession is associated with a (severe) credit crunch or a house
price bust if the (severe) credit crunch or house price bust starts at the same time or one quarter before the peak of the
recession. A recession is associated with a financial crisis if the crisis starts at the same time as the recession or one year
before or two years after the output peak preceding the recession. Severe financial crises are the worst 50 percent of
financial crises as measured by output decline during the recession.
40 Financial Crises: Explanations, Types, and Implications
crises associated with sudden stops in many emerging market economies (Calvo,
Izquierdo, and Talvi, 2006). Abiad, Dell’Ariccia, and Li (Chapter 10, this vol-
ume), using a large sample of countries, show that about one out of five recover-
ies is creditless. Creditless recoveries are, as expected, more common after banking
crises and credit booms. The average GDP growth during these episodes is about
Figure 1.9 Creditless Recoveries, 1960–2011
Source: IMF staff calculations.
Notes: The sample includes data for 23 advanced countries. Each panel shows the median year-over-year growth rate of
the respective variable during recessions associated with credit crunches. Zero is the quarter at which a recession with a
credit crunch begins.
8
6
4
2
–2
–4
–12 –8 –4 0
Quarters
4812
–12 –8 –4 0
Quarters
4812
–12 –8 –4 0
Quarters
4812
0
Output
Credit
House prices
Annual percent changeAnnual percent change
15
10
5
0
–5
–10
Annual percent change
15
10
5
0
–5
–10
–15
Claessens and Kose 41
a third lower than during “normal” recoveries.31 Furthermore, sectors more
dependent on external finance grow relatively less, and more-financially depen-
dent activities (such as investment) are curtailed more (see also Kannan, 2009).
Micro evidence for individual countries also shows that financial crises are associ-
ated with reductions in investment, research and development, and employment,
and firms pass up on growth opportunities.32 Collectively, these issues suggest
that the supply of credit following a financial crisis can constrain economic
growth.
PREDICTING FINANCIAL CRISES
It has long been a challenge to predict the timing of crises. Knowing whether and
when a crisis may occur would obviously have great benefits: measures can be put
in place to prevent a crisis from occurring in the first place or to limit the damage
if it does happen. Therefore, much can be gained from better detecting the likeli-
hood of a crisis. Yet, despite significant effort, no single set of indicators can
explain the various types of crises, or can do so consistently over time. Periods of
turmoil often arise endogenously, with possibilities of multiple equilibria and
many nonlinearities.33 And although it is now easier to document vulnerabilities,
such as increasing asset prices and high leverage, predicting the timing of crises
with some accuracy remains difficult. This section presents a short review of the
evolution of the empirical literature on prediction of crises.34
Early-warning models have evolved from the first generation of models that
concentrated on macroeconomic imbalances. Early crisis prediction models,
mostly aimed at banking and currency crises, focused largely on macroeconomic
and financial imbalances, and often in the context of emerging markets.
Kaminsky and Reinhart (1999) show that growth rates in money, credit, and
several other variables exceeding certain thresholds made a banking crisis more
likely. In a comprehensive review, Goldstein, Kaminsky, and Reinhart (2000)
report that a wide range of monthly indicators help predict currency crises,
31 e fact that the economy recovers without credit growth and increases in asset prices re ects a
combination of factors. First, consumption is typically the key driver of recovery. In particular, private
consumption is often the most important contributor to output growth during recoveries. Investment
(especially investment other than residential housing) recovers only with a lag, with the contribution of
xed investment growth to recovery often relatively small. Second, rms and households may be able
to get external nancing from sources other than commercial banks that have been adversely a ected
by the crisis. ese sources are not captured in the aggregate credit series most studies focus on. ird,
there can be a switch from more to less credit-intensive sectors in such a way that overall credit does not
expand, yet, because of productivity gains, output increases. e aggregate data used in many studies
hide such reallocations of credit across sectors, including between corporations and households that
vary in their credit intensity.
32 Campello, Graham, and Harvey (2009) review evidence for the United States.
33 e slow movement of the nancial system from stability to crisis is something for which Hyman
Minsky is best known, and the phrase “Minsky moment”—the sudden occurrence of an open nancial
crisis—refers to this aspect of his work (Minsky, 1992).
34 Babecky and others (2012) present a detailed review of the empirical studies of early-warning models.
42 Financial Crises: Explanations, Types, and Implications
including the appreciation of the real exchange rate (relative to trend), a banking
crisis, a decline in equity prices, a decline in exports, a high ratio of broad money
(M2) to international reserves, and a recession. Among annual indicators, the two
best were both current account indicators, namely, a large current account deficit
relative to both GDP and investment. For banking crises, the best monthly indi-
cators (in descending order) were appreciation of the real exchange rate (relative
to trend), a decline in equity prices, a rise in the money (M2) multiplier, a decline
in real output, a decline in exports, and a rise in the real interest rate. Among
eight annual indicators tested, the best were a high ratio of short-term capital
flows to GDP and a large current account deficit relative to investment.35
In the next generation of models, still largely geared toward external crises,
balance sheet variables became more pronounced. Relevant indicators include
substantial short-term debt coming due and the level of reserves (Berg and others,
2004). The ratio of broad money to international reserves in the year before the
crisis was found to be higher (and GDP growth slower) for crises in emerging
markets. In these models, fiscal deficit, public debt, inflation, and real broad
money growth, however, were often found not to be consistently different
between crisis and noncrisis countries before major crises. Neither did interest
rate spreads or sovereign credit ratings generally rank high in the list of early-
warning indicators of currency and systemic banking crises. Rather, crises were
more likely to be preceded by rapid real exchange rate appreciation, current
account deficits, domestic credit expansion, and increases in equity prices.
Later models show that a combination of variables can help identify situations
of financial stress and vulnerabilities. Frankel and Saravelos (2012) perform a
meta analysis based on reviews of crisis prediction models and seven papers pub-
lished since 2002. The growth rates of credit, foreign exchange reserves, the real
exchange rate, GDP, and the current account to GDP ratio are the most frequent
significant indicators in the 83 papers reviewed; Lane and Milesi-Ferretti, 2011).
Crises are typically preceded by somewhat larger current account deficits relative
to historical averages, although credit trends more than external imbalances
appear to be the best predictor (Alessi and Detken, 2011; Schularick and Taylor,
2012; Taylor, Chapter 6, this volume).
Global factors can play important roles in driving sovereign, currency, balance
of payments, and sudden stop crises. A variety of global factors are often reported
to trigger crises, including deterioration in the terms of trade and shocks to world
interest rates and commodity prices. For example, the sharp rise in U.S. interest
rates has been identified as a trigger for the Latin American sovereign debt crises
of the 1980s. More generally, crises are often preceded by interest rate hikes in
advanced economies and by sudden changes in commodity prices, especially oil.
But low interest rates can matter as well. For example, Jordà, Schularick, and
Taylor (2011) report that global financial crises often take place in an environ-
35 Crespo-Cuaresma and Slacik (2009) report that most of the early-warning variables for currency
crises in the literature are quite fragile, whereas the extent of real exchange rate misalignment and
nancial market indicators appear to be relatively robust determinants of crisis in certain contexts.
[[AQ: Pls
add to
refs.]]
Claessens and Kose 43
ment of low interest rates. Other studies argue that the global imbalances of the
2000s and the 2007–09 crisis are intimately connected (Obstfeld and Rogoff,
2009; Obstfeld, 2012). International trade and other real linkages can be chan-
nels of transmission, and contagion in financial markets is associated with crises
(Forbes, 2012). Studies highlight, for example, the role of a common lender in
particular in spreading the East Asian financial crisis (Kaminsky and Reinhart,
2001). These global factors can themselves be outcomes, as in the 2007–09 crisis,
when interest rates and commodity prices experienced sharp adjustments follow-
ing the onset of the crisis.
Overall though, rapid growth in credit and asset prices is found to be the fac-
tor most reliably related to increases in financial stress and vulnerabilities. Borio
and Lowe (2002) document that out of asset-price, credit, and investment data,
a measure based on credit and asset prices is the most useful: almost 80 percent
of crises can be predicted on the basis of a credit boom at a one-year horizon,
whereas false positive signals are issued only about 18 percent of the time.
Building on this, Elekdag, Cardarelli, and Lall (2009) find that banking crises are
typically preceded by sharp increases in credit and house prices. Many others have
found the coexistence of unusually rapid increases in credit and asset prices, large
booms in residential investment, and deteriorating current account balances, to
contribute to the likelihood of credit crunches and asset-price busts.
Recent studies confirm that credit growth is the most important, but still
imperfect, predictor. Many of the indicators, such as sharp asset-price increases, a
sustained worsening of the trade balance, and a marked increase in bank leverage,
lose predictive significance once one conditions for the presence of a credit boom.
Still, there are both Type I and Type II errors. As Bakker and others (Chapter 11,
this volume) show, not all booms are associated with crises: only about a third of
boom cases end up in financial crises. Others do not lead to busts but are followed
by extended periods of below-trend economic growth. And many booms result in
permanent financial deepening and benefit long-term economic growth. Although
not all booms end up in a crisis, the probability of a crisis increases with a boom.
Furthermore, the larger the increase in credit during the boom, the more likely
the episode is to result in a crisis. Bakker and others (Chapter 11, this volume)
find that half or more of the booms that either lasted longer than six years (4 out
of 9), exceeded 25 percent of average annual growth (8 out of 18), or started at
an initial credit-to-GDP ratio higher than 60 percent (15 out of 26) ended up in
crises.
In practical terms, recent early-warning models typically use a wide array of
quantitative leading indicators of vulnerabilities, with a heavy focus on interna-
tional factors. These indicators capture vulnerabilities that stem from or are cen-
tered in the external, public, financial, nonfinancial corporate, or household
sectors, and combine these with qualitative inputs (IMF, 2010). Because interna-
tional financial markets can play multiple roles in transmitting and causing, or at
least triggering, various types of crises, as with the 2007–09 crisis, several interna-
tional linkage measures are typically used. Notably banking system measures,
such as exposures to international funding risks and the ratio of noncore to core
44 Financial Crises: Explanations, Types, and Implications
liabilities, have been found to help signal vulnerabilities (Shin, Chapter 4, this
volume).36 International markets can also help with risk sharing and can reduce
volatility, and the empirical evidence is mixed, so the overall relationship of inter-
national financial integration and crises is much debated (Kose and others, 2010;
Lane, 2012).
CONCLUSION
This chapter presents a survey of the literature on financial crises to answer three
specific questions. First, what main factors explain financial crises? Although the
literature has clarified some of these factors, it remains a challenge to definitively
identify the causes of crises. Many theories have been developed about the under-
lying causes of crises. These theories have recognized the importance of booms in
asset and credit markets that turned into busts as the driving forces behind most
crisis episodes. Given their central roles, the chapter briefly summarizes the theo-
retical and empirical literature analyzing developments in credit and asset markets
around financial crises.
Second, what are the major types of crises? Although financial crises can take
various shapes and forms, the literature has focused on four major types: currency
crises, sudden stop (or capital account or balance of payments) crises, debt crises,
and banking crises. Crises can be classified in other ways, too, but the types still
often overlap. A number of banking crises, for example, are also sudden stop
episodes and currency crises. The chapter examines the literature on the analytical
causes and empirical determinants of each type of crisis. In addition, it reviews
studies of various approaches to the identification of crises and their frequency
over time and across different groups of countries.
Third, what are the real sector and financial sector implications of crises? Large
output losses are common to many crises, and other macroeconomic variables
(consumption, investment, and industrial production) typically register signifi-
cant declines. Financial variables like asset prices and credit usually follow quali-
tatively similar patterns across crises, albeit with variations in duration and
severity. The chapter summarizes the literature on the macroeconomic and finan-
cial implications of crises.
The chapter also briefly reviews the literature on the prediction of crises.
Although there are many benefits to knowing whether and when a crisis may
occur, predicting crises remains a challenge. Vulnerabilities, such as increasing
asset prices and high leverage, are easily documented, but it remains difficult to
predict with any accuracy the timing of crises. No single set of indicators has
proved to predict the various types of crises. The chapter reviews how the empir-
ical literature on the prediction of crises has evolved and analyzes its current state.
36 In Chapter 4, Shin compares the predictive power from price-based measures (credit default swaps
and other spreads, implied volatility, value at risk, and others), the gap of the credit-to-GDP ratio from
a trend, and monetary aggregates and other bank liability aggregates, and shows that the last group has
the most predictive power.
Claessens and Kose 45
Is This Time Really Different?
One of the main conclusions of the literature on financial crises is that it has been
hard to beat the “this-time-is-different” syndrome. This syndrome, as aptly
described by Reinhart and Rogoff (2009b), is the belief that “financial crises are
things that happen to other people in other countries at other times; crises do not
happen to us, here and now. We are doing things better, we are smarter, we have
learned from past mistakes” (p. 15). Although often preceded by similar patterns,
policymakers tend to ignore the warnings and argue that “the current boom,
unlike the many booms that preceded catastrophic collapses in the past (even in
our country) is built on sound fundamentals” (p. 15). Leading up to every crisis,
claims are made that developments appear to be different from those before ear-
lier episodes. Before the 2007–09 crisis, for example, the extensive diversification
of risks and advanced institutional frameworks were used to justify the belief that
“this time is different.”
As the literature reviewed here makes abundantly clear, there are many simi-
larities in the run-ups to crises. In the 2007–09 crisis, increases in credit and asset
prices were similar to those observed in earlier crises. Given these commonalities,
it should be possible to prevent crises. Yet, that seems to have been an impossible
task. This suggests that future research should be geared to beating the “this-time-
is-different” syndrome. This is a very broad task requiring that two major ques-
tions be addressed: How can financial crises be prevented? How can their costs be
mitigated when they take place? In addition, more intensive efforts are needed to
collect the necessary data to guide both empirical and theoretical studies. The rest
of this section takes each of these issues in turn and points to future research
directions.
How Can Financial Crises Be Prevented?
In light of the lessons from the 2007–09 crisis, asset-price bubbles and credit
booms can entail substantial costs if they deflate rapidly. Many now agree on a
number of issues with respect to asset-price bubbles and credit booms. First, rapid
increases in asset prices and credit can lead to financial turmoil and crises with
significant adverse macroeconomic effects. Second, it is important to monitor
vulnerabilities stemming from such sharp increases, and to determine whether
they could be followed by large and rapid declines (crashes, busts or crunches,
capital outflows). Third, the subsequent busts and crunches are likely to be more
harmful if bubbles arise from “distortions.” Fourth, even if not caused by distor-
tions, evidence of irrationality can be interpreted as a sign of inefficiency and a
potential source of welfare loss. Thus, bubbles and credit booms can warrant
intervention.
The challenge for policymakers and researchers is twofold: when to inter-
vene and how to intervene. First, they need to determine when (and to what
extent) increases in asset prices and credit represent substantial deviations from
those that can be explained by fundamentals. Second, if the behavior of credit
and asset markets suggests signs of risk, they need to determine the optimal
46 Financial Crises: Explanations, Types, and Implications
policy responses to minimize risks and mitigate the adverse effects when risks
materialize.
The debate on whether, and how, monetary policy should respond to move-
ments in asset prices and credit remains active. The consensus before the 2007–09
crisis was that the formulation of monetary policy only needed to consider asset
prices to the extent that they were relevant for forecasting the economic outlook
and inflation, but not otherwise.37 However, the crisis has made clear (again) that
both financial stability and economic activity might be affected by asset-price
movements and a view has emerged that monetary policy should take into
account, to some degree, developments in asset prices (Blanchard, Dell’Ariccia,
and Mauro, 2010, 2013); Bernanke, 2009, 2010; Trichet, 2009). A way to make
this objective operational remains under discussion (Eichengreen, 2011; Mishkin,
2011). The case for policy intervention is considered to be stronger when the
banking system is directly involved in financing the bubble (whereas other asset-
price bubbles can more justifiably be left to themselves (Crowe and others,
Chapter 12, this volume), but the exact adjustment of monetary policy remains
unclear (Bean and others, 2010; King, 2012.
Important lessons are still to be learned about the design of microprudential
regulations and institutional structures for the prevention of crises (see also
Claessens and others, 2012b). The 2007–09 crisis once again exposed flaws in
microprudential regulatory and institutional frameworks. The global nature of
the crisis has also shown that financially integrated markets have benefits, but also
present risks, because the international financial architecture still is far from insti-
tutionally equal to the policy demands of closely integrated financial systems.
Elements of existing frameworks provide foundations, but the crisis has forced
regulatory policies to be rethought, with many open questions. Although rules
calling for well-capitalized and liquid banks that are transparent and adhere to
sound accounting standards are being put in place (e.g., Basel III), clarity on how
to deal with large, complex financial institutions that operate across many borders
is still needed. In addition, what types of changes to the institutional environ-
ments—for example, changes in the accounting standards for mark-to-market
valuation, adaptations of employee compensation rules, transfers of some deriva-
tives trading to formal exchanges, greater use of central counterparties—would
best help to reduce financial markets’ procyclicality and the buildup of systemic
risks remain elusive. The crisis has also shown that fiscal policies, both micro,
such as deductibility of interest payments, and macro, as in the amount of
resources available to deal with financial crises, can play a role in creating vulner-
abilities, but which adaptations are needed is not always apparent.
Although there is also a call for the use of macroprudential policies, the design
of such policies and their interactions with other policies, especially monetary
policy, remain unclear. By constraining financial market participants’ behavior in
advance, macroprudential policies can reduce the impact of externalities and
37 See Mishkin (2008) and Kohn (2008) for reviews, and Campbell (2008) for a collection of papers.
Claessens and Kose 47
market failures that lead to systemic vulnerabilities. In that way, they can reduce
the risks of financial crises and help improve macroeconomic stability (De
Nicolò, Favara, and Ratnovski, 2012). But the exact design of such policies is yet
to be formulated. Although it is evident that multiple tools are needed, complica-
tions abound. Different financial distortions, for example, can lead to different
types of risks, which, in turn, imply the use of multiple intermediate targets.
Moreover, the relevant distortions can change over time and vary by country
circumstances. Excessive leverage among corporations may give way, for example,
to excessive leverage in the household sector. Factors such as the development of
the financial sector and the exchange rate regime can greatly affect the types of
risks economies face. Much is still unknown about these factors and their implica-
tions for the formulation of macroprudential policies. As new macroprudential
frameworks are established, policymakers have also been increasingly turning
their attention to the complex dynamics between macroprudential and monetary
policies. These dynamics hinge on the side effects that one policy has on the
other, but conceptual models and empirical evidence on these issues are still in
the early stages (see IMF, 2013, for an overview).
The review here clearly shows that further analytical research and empirical
work on these issues are needed. Macroeconomic models need to reflect the roles
of financial intermediaries better. Current models are often limited in the way
that they capture financial frictions. With regard to financial stress, they often
assume that available instruments can fully offset financial shocks and abstract
from effects, such as those of monetary policy on financial stability. More realistic
modeling of the channels that give rise to financial instability and the actual
transmission of policies and instruments is needed. In particular, the supply side
of finance is not well understood and models with realistic calibrations reflecting
periods of financial turmoil are still missing (Brunnermeier and Sanikov, 2012).
The roles of liquidity and leverage in such periods have yet to be examined using
models better suited to addressing the relevant policy questions. More insights,
including from empirical studies, are necessary to help calibrate these models and
allow the formulation of policy prescriptions that can be adapted to different
country circumstances. Only with progress in modeling financial crises can one
hope to not only avoid some of these episodes and be prepared with better poli-
cies when they occur, but also to minimize their impacts.
From an applied perspective, better early-warning models are needed. An issue
extensively discussed in policy forums and receiving substantial attention from
international organizations is the need to improve the prediction of the onset of
crises (IMF, 2010). As the review in this chapter shows, the predictive power of
available models remains limited. The historical record indicates that asset-price
busts have been especially difficult to predict. Even the best indicator failed to
raise an alarm one to three years ahead of roughly one-half of all busts since 1985.
This was the case again for the 2007–09 crisis. Although a number of recent
papers that analyze the ability of various models to predict the latest crisis come
to negative conclusions as well, others have found some predictive patterns.
Regardless, there is scope to improve these models.
48 Financial Crises: Explanations, Types, and Implications
While known risks are being addressed, new risks can emerge. The limited
strength of crisis prediction models arises in part because countries do take steps
to reduce vulnerabilities. In response to increased financial globalization and sud-
den stop risks, many emerging markets increased their international reserves
beginning in the late 1990s, which may have helped some countries avoid the
impact of the 2007–09 crisis (Kose and Prasad, 2010; De Gregorio, Chapter 5,
this volume). Similarly, improvements in institutional environments that many
countries have put in place during the last decades likely helped reduce some
vulnerabilities. At the same time, however, new risks have emerged: the explosion
of complex financial instruments, greater balance sheet opaqueness, and reliance
on wholesale funding in highly integrated global financial markets increased the
risks leading to the 2007–09 crisis.
How Can the Costs of Financial Crises Be Mitigated?
Explaining the substantial real costs associated with crises has been a challenge.
Various theories attempt to explain the channels by which different types of crises
affect the real economy. Many descriptions of the empirical patterns around crisis
episodes can also be found. Yet, why crises cause large costs remains an enigma.
Many of the channels that lead to macro-financial linkages during normal times
also “cause” the adverse effects of crises, but other dynamics are also clearly at
work. Normal lending seems undermined for an extended period as evidenced by
creditless recoveries following crises. Fiscal policy and public debt dynamics can
be affected for decades, in part because governments often end up directly sup-
porting financial systems (by injecting liquidity or providing recapitalization) or
suffer from expansionary policies undertaken to mitigate the costs of crises.
The major challenge is to explain the sharp, nonlinear behavior of financial
markets in response to “small” shocks. Although the procyclicality of leverage
among financial institutions, as highlighted by its increase during the run up to
the 2007–09 crisis followed by the sharp deleveraging in its aftermath, has been
extensively documented (Adrian and Shin, 2011), the exact causes of this behav-
ior have yet to be identified. Why crises involve liquidity hoarding to such a
degree that aggregate liquidity shortages occur and transmission of monetary
policy is disrupted remains a puzzle. Although credit crunches are, in part, attrib-
utable to capital shortages at financial institutions, shortages do not seem to fully
explain the phenomena of lenders becoming overly risk averse following a crisis.
This lack of knowledge of the forces shaping the dynamics before and during
periods of financial stress greatly complicates the design of proper policy
responses.
It is also important to explore why financial spillovers across entities (institu-
tions, markets, countries, and so on) are much more potent than most fundamen-
tals suggest (in other words, why is there so much contagion?). Financial crises
often generate effects across markets and have global repercussions. The 2007–09
episode is a case in point; its global reach and depth are without precedent in the
post–World War II period. This underscores the value of having a better grasp of
Claessens and Kose 49
the mechanisms through which such episodes spill over to other countries. In
addition to trade and cross-border banking linkages, research needs to consider
the roles played by new financial channels, such as commercial paper conduits
and shadow banking, and new trade channels, such as vertical trade networks, in
the transmission of crises across borders. Given their adverse impact, the exact
nature of these spillovers matters for the appropriate design of both crisis-mitiga-
tion and crisis-management responses. For example, in light of their cross-border
implications, pooling resources (regionally or globally) to provide ample liquidity
proactively becomes more important because it can prevent liquidity runs from
escalating into self-fulfilling solvency crises and help break chains of contagion.
Although many stylized facts are already available, work on the implications of
interactions among different crises and sovereign debt defaults is still limited.
This review documents that various types of crises can overlap in a single episode,
but research on the implications of such overlapping has been lagging. Although
default on domestic debt tends to be less frequent than that on external debt, it
still takes place quite often, suggesting that the usual assumption of risk-free
government debt needs to be revisited. Furthermore, domestic and foreign debt
defaults seem to touch on each other. Although domestic debt tends to account
for a large share of the total debt stock in both advanced countries and emerging
markets, many emerging market economies default on their external debt at
seemingly low debt levels. This suggests that, for a given level of unsustainable
debt, the cost of defaulting on external debt appears less than the cost of default-
ing on domestic debt. More generally, trade-offs that depend on country circum-
stances likely come into play, maybe because the risk of high inflation varies. With
the rising public debt stocks in many advanced countries, more work on this
would be very useful.
Many questions are left about the best policy responses to financial crises. The
2007–09 global crisis and associated recessions have shown the limits of policy
measures in dealing with financial meltdowns. It has led to an extensive discus-
sion about the ability of macroeconomic and financial sector policies to mitigate
the costs stemming from such episodes. Some research shows that countercyclical
policies might mitigate the cost and reduce the duration of recessions (Kannan,
Scott, and Terrones, Chapter 8, this volume). Others argue that such policies can
worsen recession outcomes (Taylor, 2009, 2011). And some others find limited
effects associated with expansionary policies (Claessens, Kose, and Terrones,
2009; Baldacci, Gupta, and Mulas-Granados, Chapter 14, this volume). The
discussion on the potency of policies clearly indicates fertile ground for future
research as well.
Although valuable lessons have been learned about crisis resolution, countries
are still far from adopting the “best” practices to respond to financial turmoil. It
is clear now that open bank assistance without proper restructuring and recapital-
ization is not an efficient way of dealing with an ailing banking system (Laeven
and Valencia, Chapter 13, this volume; Landier and Ueda, Chapter 15, this vol-
ume). Excessive liquidity support and guarantees of bank liabilities cannot substi-
tute for proper restructuring and recapitalization either, because most banking
50 Financial Crises: Explanations, Types, and Implications
crises involve solvency problems, not just liquidity shortfalls. For banking crises,
the sooner restructuring is implemented, the better the outcomes will be. Such a
strategy removes residual uncertainty that can trigger precautionary contractions
in consumption and investment, which, in turn, can further exacerbate reces-
sions. Still, in spite of this understanding, many countries do not adopt these
policy responses, including in the crises since 2007 (Claessens and others,
Chapter 15, this volume), suggesting that there are deeper factors that research
has not been able to uncover or address. Moreover, issues related to restructuring
of both household debt and sovereign debt require more sophisticated theoretical
and empirical approaches (Laeven and Laryea, Chapter 17, this volume; Das,
Papaioannou, and Trebesch, Chapter 19, this volume; Igan and others, Chapter
18, this volume).
What Additional Data and Methods Are Needed?
As the review in this chapter illustrates, new data series need to be put together
and new methodologies need to be designed to gain a better understanding of
crisis episodes. The review lists several recent studies that constructed new data
series on financial crises. However, more research is clearly needed to collect addi-
tional cross-country data on aspects relevant to financial crises. Better data on
domestic debt and house prices are urgently needed to provide a richer under-
standing of domestic debt dynamics and fluctuations in housing markets. Better
international data are also needed for both surveillance and early-warning exer-
cises (see Heath, 2013; and Cerutti, Claessens, and McGuire, forthcoming, for
data needs). For a deeper understanding of crises and the policy issues surround-
ing these episodes, another requirement is for new methods to be designed to
classify crises more robustly. Moreover, it would be important to examine periods
of financial disruptions that are not necessarily crises. Although good luck or
adequate policy measures may have prevented financial crises following such
disruption episodes, there are lessons to be learned because these are the types of
periods that can provide case studies of counterfactuals to analyze the macroeco-
nomic outcomes and implications of policy responses.
REFERENCES
Abbas, S.A., M. Belhocine, A. El Ganainy, and M. Horton, 2011, “Historical Patterns and
Dynamics of Public Debt: Evidence from a New Database,” IMF Economic Review, Vol. 59,
No. 4, pp. 717–42.
Abreu, D., and M.K. Brunnermeier, 2003, “Bubbles and Crashes,” Econometrica, Vol. 71, No.1,
pp. 173–204.
Adrian, T., and H.S. Shin, 2011, “Financial Intermediaries and Monetary Economics,” in
Handbook of Monetary Economics, Vol. 3, No. 3, ed. by B. Friedman and M. Woodford (San
Diego and Amsterdam: North-Holland) pp. 601–50.
Aguiar, M., and G. Gopinath, 2006, “Defaultable Debt, Interest Rates and the Current
Account,” Journal of International Economics, Vol. 69, No. 1, pp. 64–83.
Alessi, L., and C. Detken, 2011, “Quasi Real Time Early Warning Indicators for Costly Asset
Price Boom/Bust Cycles: A Role for Global Liquidity,” European Journal of Political Economy,
Vol. 27, No. 3, pp. 520–33.
Claessens and Kose 51
Allen, F., A. Babus, and E. Carletti, 2009, “Financial Crises: Theory and Evidence,” Annual
Review of Financial Economics, Vol. 1, No. 1, pp. 97–116.
Allen, F., and D. Gale, 2007, Understanding Financial Crises, Clarendon Lectures in Finance
(Oxford, UK: Oxford University Press).
Allen, R.E., 2010, Financial Crises and Recession in the Global Economy, 3rd ed. (Cheltenham:
UK: Edward Elgar Publishing).
Babecký, J., T. Havránek, J. Matějů, M. Rusnák, K. Šmídková, and B. Vašíček, 2012, “Banking,
Debt and Currency Crises: Early Warning Indicators for Developed Countries,” Working
Paper No. 1485 (Frankfurt: European Central Bank).
Bakker, B., G. Dell’Ariccia, L. Laeven, J. Vandenbussche, D. Igan, and H. Tong, 2012, “Policies
for Macrofinancial Stability: How to Deal with Credit Booms,” IMF Staff Discussion Note
No. 12/6 (Washington: International Monetary Fund).
Bank for International Settlements (BIS), 2002, “Turbulence in Asset Markets: The Role of
Micro Policies,” Report by Contact Group on Asset Prices (Basel).
Barberis, N., and R. Thaler, 2003, “A Survey of Behavioral Finance,” in Handbook of the
Economics of Finance, ed. by G.M. Constantinides, M. Harris, and R. Stulz (Amsterdam:
Elsevier B.V.) pp.1051–121.
Barth, J., G. Caprio, and R. Levine, 2006, Rethinking Bank Regulation: Till Angels Govern (New
York, New York: Cambridge University Press).
———, 2012, Guardians of Finance: Making Regulators Work for Us (Cambridge, Massachusetts:
MIT Press).
Bean, C., M. Paustian, A. Penalver, and T. Taylor, 2010, “Monetary Policy after the Fall,” Paper
presented at the Federal Reserve Bank of Kansas City Annual Conference, Jackson Hole,
Wyoming, August 31–September 1.
Bernanke, B., 2009, “Reflections on a Year of Crisis,” Speech at the Federal Reserve Bank
of Kansas City’s Annual Economic Symposium, Jackson Hole, Wyoming, August
31–September 1.
———, 2010, “Monetary Policy and Housing Bubble,” Speech at the Annual Meeting of the
American Economic Association, Atlanta, Georgia, January 3.
Blanchard O., G. Dell’Ariccia, and P. Mauro, 2010, “Rethinking Macroeconomic Policy,”
Journal of Money, Credit and Banking, Vol. 42, No. s1, pp. 199–215.
———, 2013, “Rethinking Macroeconomic Policy: Getting Granular,” IMF Staff Discussion
Note No. 13/3 (Washington: International Monetary Fund).
Blanchard, O.J., and M.W. Watson, 1982, “Bubbles, Rational Expectations and Financial
Markets,” in Crisis in the Economic and Financial Structure: Bubbles, Bursts, and Shocks, ed. by
P. Wachtel (Lexington, Massachusetts: Lexington Press).
Blanco, H., and P.M. Garber, 1986, “Recurrent Devaluation and Speculative Attacks on the
Mexican Peso,”Journal of Political Economy, Vol. 94, No. 1, pp. 148–66.
Bordo, M., and J. Haubrich, 2012, “Deep Recessions, Fast Recoveries, and Financial Crises:
Evidence from the American Record,” NBER Working Paper No. 18194 (Cambridge,
Massachusetts: National Bureau of Economic Research).
Bordo, M.D., B. Eichengreen, D. Klingebiel, and M.S. Martinez-Peria, 2001, “Is the Crisis
Problem Growing More Severe?” Economic Policy, Vol. 16, pp. 51–82.
Borensztein, E., and U. Panizza, 2009, “The Costs of Sovereign Default,” IMF Staff Papers, Vol.
56, No. 4, pp. 683–741.
Borio, C., and P. Lowe, 2002, “Asset Prices, Financial and Monetary Stability: Exploring the
Nexus,” BIS Working Paper No. 114 (Basel: Bank for International Settlements).
Branch, W., and G.W. Evans, 2008, “Learning about Risk and Return: A Simple Model of
Bubbles and Crashes,” Working Paper 2008-1 (Eugene, Oregon: University of Oregon
Economics Department).
Brunnermeier, M., 2001, Asset Pricing under Asymmetric Information: Bubbles, Crashes, Technical
Analysis and Herding (Oxford, UK: Oxford University Press).
———, and Y. Sannikov, 2012, “A Macroeconomic Model with a Financial Sector,” 2012
Meeting Papers No. 507 (St. Louis, Missouri: Society for Economic Dynamics).
52 Financial Crises: Explanations, Types, and Implications
Bulow, J., and K. Rogoff, 1989, “Sovereign Debt: Is to Forgive to Forget?” American Economic
Review, Vol. 79, No.1, pp. 43–50.
Burnside, C., M. Eichenbaum, and S. Rebelo, 2001, “On the Fiscal Implications of Twin
Crises,” Working Paper No. 01-02 (Chicago, Illinois: Federal Reserve Bank of
Chicago).
———, 2004, “Government Guarantees and Self-Fulfilling Speculative Attacks,” Journal of
Economic Theory, Vol. 119, pp. 31–63.
Calomiris, C.W., 2009, “The Subprime Turmoil: What’s Old, What’s New, and What’s Next,”
Journal of Structured Finance, Vol. 15, No. 1, pp. 6–52.
———, and G. Gorton, 1991, “The Origins of Banking Panics: Models, Facts, and Bank
Regulation,” in Financial Markets and Financial Crises, ed. by R.G. Hubbard (Cambridge,
Massachusetts: NBER Books) pp.107–73.
Calvo, G.A., 2000. “Betting against the State: Socially Costly Financial Engineering,” Journal of
International Economics, Vol. 51, No. 1, pp. 5–19.
———, A. Izquierdo, and R. Loo-Kung, 2006, “Relative Price Volatility under Sudden Stops:
The Relevance of Balance Sheet Effects,” Journal of International Economics, Vol. 69, No. 1,
pp. 231–54.
Calvo, G., A. Izquierdo, and L.-F. Mejia, 2004, “On the Empirics of Sudden Stops: The
Relevance of Balance-Sheet Effects,” NBER Working Paper No. 10520 (Cambridge,
Massachusetts: National Bureau of Economic Research).
———, 2008, “Systemic Sudden Stops: The Relevance of Balance-Sheet Effects and Financial
Integration,” NBER Working Paper No. 14026 (Cambridge, Massachusetts: National Bureau
of Economic Research).
Calvo, G.A., A. Izquierdo, and E. Talvi, 2006, “Phoenix Miracles in Emerging Markets:
Recovering without Credit from Systemic Financial Crises,” NBER Working Paper No.
12101 (Cambridge, Massachusetts: National Bureau of Economic Research).
Calvo, G., and C. Reinhart, 1999, “Capital Flow Reversals, the Exchange Rate Debate, and
Dollarization,” MPRA Paper 8951 (Munich: University of Munich).
———, 2000, “When Capital Inflows Come to a Sudden Stop: Consequences and Policy
Options,” MPRA Paper 6982 (Munich, Germany: University of Munich).
Campbell, J., ed., 2008, Asset Prices and Monetary Policy, NBER Conference Report (Chicago,
Illinois: University of Chicago Press).
Campello, M., J. Graham, and C.R. Harvey, 2009, “The Real Effects of Financial Constraints:
Evidence from a Financial Crisis,” NBER Working Paper No. 15552 (Cambridge,
Massachusetts: National Bureau of Economic Research).
Cardarelli, R., S. Elekdag, and M.A. Kose, 2010, “Capital Inflows: Macroeconomic Implications
and Policy Responses,” Economic Systems, Vol. 34, No. 4, pp. 333–56.
Cerutti, E., S. Claessens, and P. McGuire, Forthcoming, “Systemic Risks in Global Banking:
What Available Data Can Tell Us and What More Data Are Needed?” in Risk Topography:
Systemic Risk and Macro Modeling, ed. by M.K. Brunnermeier and A. Krishnamurthy
(Chicago, Illinois: NBER/University of Chicago Press).
Chang, R., and A. Velasco, 2000, “Liquidity Crises in Emerging Markets: Theory and Policy,”
in NBER Macroeconomics Annual 1999, ed. by B.S. Bernanke and J.J. Rotemberg (Cambridge,
Massachusetts: MIT Press) pp. 11–78.
Chen, J., H. Hong, and J.C. Stein, 2002, “Breadth of Ownership and Stock Returns,” Journal
of Financial Economics, Vol. 66, No. 2-3, pp. 171–205.
Čihák, M., A. Demirgüç-Kunt, M. Soledad Martínez Pería, and A. Mohseni-Cheraghlou,
2012,“Bank Regulation and Supervision around the World: A Crisis Update,” World Bank
Policy and Research Working Paper No. 6286 (Washington: World Bank).
Claessens, S., 1991, “Balance of Payments Crises in an Optimal Portfolio Model,” European
Economic Review, Vol. 35, pp. 81–101.
Claessens, S., G. Dell’Ariccia, D. Igan, and L. Laeven, 2010, “Cross-Country Experience and
Policy Implications from the Global Financial Crisis,” Economic Policy, Vol. 25 (April), pp.
267–93.
Claessens and Kose 53
———, 2012a, “A Cross-Country Perspective on the Causes of the Global Financial Crisis,” in
The Evidence and Impact of Financial Globalization, ed. by Gerard Caprio (Amsterdam:
Elsevier B.V.) 753–61.
———, 2012b, “Lessons and Policy Implications from the Global Financial Crisis,” in The
Evidence and Impact of Financial Globalization, ed. by Gerard Caprio (Amsterdam: Elsevier
B.V.) 753–61.
Claessens, S., M.A. Kose, and M.E. Terrones, 2009, “What Happens during Recessions,
Crunches and Busts?” Economic Policy, Vol. 60, pp. 653–700.
———, 2010a, “Financial Cycles: What? How? When?” in NBER International Seminar in
Macroeconomics 2010, ed. by Richard Clarida and Francesco Giavazzi (Chicago, Illinois:
University of Chicago Press).
———, 2010b, “The Global Financial Crisis: How Similar? How Different? How Costly?”
Journal of Asian Economics, Vol. 21, No. 3, pp. 247–64.
———, 2012, “How Do Business and Financial Cycles Interact?” Journal of International
Economics, Vol. 87, pp.178–90.
Corsetti, G., P. Pesenti, and N. Roubini, 1998, “Paper Tigers? A Model of the Asian Crises,”
NBER Working Paper No. 6783 (Cambridge, Massachusetts: National Bureau of Economic
Research) .
Crespo-Cuaresma, J., and T. Slacik, 2009, “On the Determinants of Currency Crisis: The Role
of Model Uncertainty,” Journal of Macroeconomics, Vol. 31, pp. 621–32.
Cumby, R.E., and S. van Wijnbergen, 1989, “Financial Policy and Speculative Runs with a
Crawling Peg: Argentina 1979–1981,” Journal of International Economics, Vol. 27, No. 1-2,
pp.111–27.
Das, U.S., M.G. Papaioannou, and C. Trebesch, 2012, “Sovereign Debt Restructurings 1950–
2010: Literature Survey, Data, and Stylized Facts,” IMF Working Paper 12/203 (Washington:
International Monetary Fund).
de la Torre, A., and A. Ize, 2011, “Containing Systemic Risk: Paradigm-Based Perspectives on
Regulatory Reform,” Policy Research Working Paper No. 5523 (Washington: World Bank).
Dell’Ariccia, G., E. Detragiache, and R. Rajan, 2008, “The Real Effect of Banking Crises,”
Journal of Financial Intermediation, Vol. 17, No. 1, pp. 89–112.
Dell’Ariccia, Giovanni, Deniz Igan, and Luc Laeven, 2012, “Credit Booms and Lending
Standards: Evidence from the Subprime Mortgage Market,” Journal of Money, Credit and
Banking, Vol. 44, No. 3, pp. 367–84.
Dell’Ariccia, G., D. Igan, and L. Laeven, 2008, “Credit Booms and Lending Standards:
Evidence from the U.S. Subprime Mortgage Market,” IMF Working Paper 08/106
(Washington: International Monetary Fund).
Dell’Ariccia, G., L. Laeven, and R. Marquez, 2011, “Monetary Policy, Leverage, and Bank
Risk-Taking,” CEPR Discussion Paper No. 8199 (London: Centre for Economic Policy
Research).
Demirgüç-Kunt, A., E.J. Kane, and L. Laeven, 2008, “Determinants of Deposit-Insurance
Adoption and Design,” Journal of Financial Intermediation, Vol. 17, No. 3, pp. 407–38.
Demirgüç-Kunt, A., and E. Detragiache, 2005, “Cross-Country Empirical Studies of Systemic
Bank Distress: A Survey,” National Institute Economic Review, Vol. 192, pp. 68–83.
De Nicolò, G., G. Dell’Ariccia, L. Laeven, and F. Valencia, 2010, “Monetary Policy and Bank
Risk-Taking,” IMF Staff Position Note 10/09 (Washington: International Monetary Fund).
De Nicolo, G., G. Favara, and L. Ratnovski, 2012, “Externalities and Macroprudential Policy,”
IMF Staff Discussion Note 12/05 (Washington: International Monetary Fund).
Dewatripont, M., and J. Tirole, 1994, The Prudential Regulation of Banks (Cambridge,
Massachusetts: MIT Press).
Diamond, Douglas, and P. Dybvig, 1983, “Bank Runs, Deposit Insurance, and Liquidity,”
Journal of Political Economics, Vol. 91, pp. 401–19.
Diamond, Douglas, and R. Rajan, 2001, “Banks, Short-Term Debt and Financial Crises:
Theory, Policy Implications and Applications,” Carnegie-Rochester Conference Series, Vol. 54,
pp. 37–71.
[[AQ: Now I
don’t see this
particular work
directly cited,
so it should be
deleted. Okay?
Or is this the
source for fig-
ure 1.3?]]
54 Financial Crises: Explanations, Types, and Implications
Diether, K., C.J. Malloy, and A. Scherbina, 2002, “Differences of Opinion and the Cross-
Section of Stock Returns,” Journal of Finance, Vol. 57, No. 5, pp. 2113–41.
Eaton, J., and R. Fernandez, 1995, “Sovereign Debt,” in Handbook of International Economics,
Vol. 3, ed. by G.M. Grossman and K. Rogoff (Amsterdam: Elsevier B.V.) pp. 2031–77.
Eaton, J., and M. Gersovitz, 1981, “Debt with Potential Repudiation: Theoretical and
Empirical Analysis,” Review of Economic Studies, Vol. 48, No. 2, pp. 289–309.
Edwards, S., 1984, “The Demand for International Reserves and Monetary Equilibrium: Some
Evidence from Developing Countries,” Review of Economics and Statistics, Vol. 66, No. 3, pp.
495–500.
———, 2004, “Financial Openness, Sudden Stops, and Current-Account Reversals,” American
Economic Review, Vol. 94, No. 2, pp. 59–64.
Eichengreen, B., 2002, Financial Crises: And What to Do about Them (Oxford, UK: Oxford
University Press).
———, 2011, “The Great Recession and the Great Depression: Reflections and Lessons,”
Economía Chilena, Vol. 13, No. 2, pp. 5–10.
———, and R. Hausmann, 1999, “Exchange Rates and Financial Fragility,” NBER Working
Paper No. 7418 (Cambridge, Massachusetts: National Bureau of Economic Research).
Eichengreen, B., A.K. Rose, and C. Wyplosz, 1995, “Speculative Attacks on Pegged Exchange
Rates: An Empirical Exploration with Special Reference to the European Monetary System,”
Working Papers in Applied Economic Theory, No. 95-04, Federal Reserve Bank of San
Francisco.
Elekdag, S., R. Cardarelli, and Subir Lall, 2009, “Financial Stress, Downturns, and Recoveries,”
IMF Working Paper 09/100 (Washington: International Monetary Fund).
Evanoff, D.D., G.G. Kaufman, and A.G. Malliaris, 2012, New Perspectives on Asset Price Bubbles
(Oxford, UK: Oxford University Press).
Fama, E.F., 1998, “Market Efficiency, Long-Term Returns, and Behavioral Finance,” Journal of
Financial Economics, Vol. 49, No. 3, pp. 283–306.
Farhi, E., and Jean Tirole, 2012, “Collective Moral Hazard, Maturity Mismatch, and Systemic
Bailouts,”American Economic Review, Vol. 102, No. 1, pp. 60–93.
Feldstein, M., 2009, “Rethinking the Role of Fiscal Policy,” American Economic Review, Vol. 99,
No. 2, pp. 556–59.
Ferguson, Roger W., 2005, “Recessions and Recoveries Associated with Asset-Price Movements:
What Do We Know?” Address to the Stanford Institute for Economic Policy Research,
Stanford, California, January 12.
Fisher, I., 1933, “The Debt Deflation Theory of Great Depressions,” Econometrica, Vol. 1, pp.
337–57.
Fisman, R., 2001, “Estimating the Value of Political Connections,” American Economic Review,
Vol. 91, No. 4, pp. 1095–1102.
Flood, R., and P. Garber, 1984, “Collapsing Exchange-Rate Regimes: Some Linear Examples,”
Journal of International Economics, Vol.17, No. 1-2, pp. 1–13.
Flood, R., and N.P. Marion, 1997, “Policy Implications of ‘Second-Generation’ Crisis Models,”
IMF Working Paper 97/16 (Washington: International Monetary Fund).
Forbes, K.J., 2012, “The Big ‘C’: Identifying and Mitigating Contagion,” Paper prepared for
the Jackson Hole Symposium hosted by the Federal Reserve Bank of Kansas City, August
31–September 1.
———, and F. Warnock, 2011, “Capital Flow Waves: Surges, Stops, Flight, and Retrenchment,”
NBER Working Paper No. 17351 (Cambridge, Massachusetts: National Bureau of Economic
Research).
Frankel, J.A., and A.K. Rose, 1996, “Currency Crashes in Emerging Markets: Empirical
Indicators,” CEPR Discussion Paper 1349 (London: Centre for Economic Policy Research).
Frankel, J.A., and G. Saravelos, 2010, “Are Leading Indicators of Financial Crises Useful for
Assessing Country Vulnerability? Evidence from the 2008–09 Global Crisis,” NBER
Working Paper No. 16047 (Cambridge, Massachusetts: National Bureau of Economic
Research).
Claessens and Kose 55
———, 2012, “Can Leading Indicators Assess Country Vulnerability? Evidence from the 2008–
09 Global Financial Crisis,” Journal of International Economics, Vol. 87, No. 2, pp. 216–31.
Furceri, D., and A. Zdzienicka, 2012, “How Costly Are Debt Crises?” Journal of International
Money and Finance, Vol. 31, No. 4, pp. 726–42.
Garber, P.M., 2000, Famous First Bubbles: The Fundamentals of Early Manias (Cambridge,
Massachusetts: MIT Press).
Glick, R., and M. Hutchison, 2012, “Currency Crises,” in Encyclopedia on Financial
Globalization (Amsterdam: Elsevier B.V.).
Goldstein, M., G.L. Kaminsky, and C.M. Reinhart, 2000, Assessing Financial Vulnerability: An
Early Warning System for Emerging Markets (Washington: Institute for International
Economics).
Gorton, G., 1988, “Banking Panics and Business Cycles,” Oxford Economic Papers, Vol. 40, No.
4, pp. 751–81.
———, 2008, “The Panic of 2007,” in Maintaining Stability in a Changing Financial System,
Proceedings of the 2008 Jackson Hole Conference (Kansas City, Missouri: Federal Reserve Bank
of Kansas City).
———, 2009, “Slapped in the Face by the Invisible Hand: Banking and the Panic of 2007,”
Paper prepared for the Federal Reserve Bank of Atlanta’s “2009 Financial Markets Conference:
Financial Innovation and Crisis,” May 11–13.
———, 2012, Misunderstanding Financial Crises: Why We Don’t See Them Coming (Oxford, UK:
Oxford University Press).
———, and G. Ordonez, 2012, “Collateral Crises,” NBER Working Paper No. 17771
(Cambridge, Massachusetts: National Bureau of Economic Research).
Gorton, G., and A. Winton, 2003, “Financial Intermediation,” in Handbook of the Economics of
Finance, Vol 1., ed. by G.M. Constantinides, M. Harris, and R.M. Stulz (Amsterdam:
Elsevier) 431–552.
Gourinchas, Pierre-Olivier, Rodrigo Valdés, and Oscar Landerretche, 2001,“Lending Booms:
Latin America and the World,” Economia, Vol. 1, pp. 47–99.
Greenspan, A., 1996, “The Challenge of Central Banking in a Democratic Society,” Speech at
the American Enterprise Institute , December 5.
Gupta, P., D. Mishra, and R. Sahay, 2007, “Behavior of Output during Currency Crises,”
Journal of International Economics, Vol. 72, No. 2, pp. 428–50.
Gürkaynak, R.S., 2008, “Econometric Tests of Asset Price Bubbles: Taking Stock,” Journal of
Economic Surveys, Vol. 22, No. 1, pp. 166–86.
Haber, S., 2005, “Banking and Economic Growth in Mexico,” Working Paper (Stanford,
California: Hoover Institution at Stanford University).
Hallwood, C.P., and R. MacDonald, 2000, International Money and Finance, 3rd ed. (Malden
Massachusetts: Blackwell Publishing).
Harrison, J.M., and D.M. Kreps, 1978, “Speculative Investor Behavior in a Stock Market with
Heterogeneous Expectations,” Quarterly Journal of Economics, Vol. 92, No. 2, pp. 323–36.
Heath, R., 2013, “Why Are the G-20 Data Gaps Initiative and the SDDS Plus Relevant for
Financial Stability Analysis?” IMF Working Paper 13/6 (Washington: International Monetary
Fund).
Hirata, H., M.A. Kose, C. Otrok, and M.E. Terrones, 2012, “Global House Price Fluctuations:
Synchronization and Determinants,” in NBER International Seminar on Macroeconomics
2012, ed. by Francesco Giavazzi and Kenneth West (Cambridge, Massachusetts: National
Bureau of Economic Research).
Hong, H., J. Scheinkman, and W. Xiong, 2008, “Advisors and Asset Prices: A Model of the
Origins of Bubbles,” Journal of Financial Economics, Vol. 89, No. 2, pp. 268–87.
Honohan, P., and L. Laeven, eds., 2007, Systemic Financial Crises (New York, New York:
Cambridge University Press).
Howard, G.,R. Martin, and B.A. Wilson, 2011, “Are Recoveries from Banking and Financial
Crises Really So Different?” International Finance Discussion Papers, Working Paper
Number 1037 (Washington: U.S. Federal Reserve System).
56 Financial Crises: Explanations, Types, and Implications
Hutchison, M.M., and I. Noy, 2006, “Sudden Stops and the Mexican Wave: Currency Crises,
Capital Flow Reversals and Output Loss in Emerging Markets,” Journal of Development
Economics, Vol. 79, pp. 225–48.
International Monetary Fund (IMF), 1998, World Economic Outlook, May (Washington).
———, 2005, “Information Note on Modifications to the Fund’s Debt Sustainability
Assessment Framework for Market Access Countries” (Washington).
———, 2009, “Debt Bias and Other Distortions: Crisis-Related Issues in Tax Policy,”
(Washington).
———, 2010, “The IMF-FSB Early Warning Exercise: Design and Methodological Toolkit”
(Washington: International Monetary Fund). http://www.imf.org/external/np/pp/
eng/2010/090110.pdf.
———, 2011, “Modernizing the Framework for Fiscal Policy and Public Debt Sustainability
Analysis,” Policy Paper (Washington).
———, 2013, “The Interaction of Monetary and Macroprudential Policies,” Board Paper
(Washington).
Ioannidou, V., S. Ongena, and J.L. Peydró, 2009, “Monetary Policy, Risk-Taking and Pricing:
Evidence from a Quasi-Natural Experiment,” Discussion Paper 2009-31 S (Tilburg, The
Netherlands: University of Tilburg).
Jeanne, O., 2003, “Why Do Emerging Economies Borrow in Foreign Currency?” IMF Working
Paper 03/177 (Washington: International Monetary Fund).
Jordà, O., M. Schularick, and A.M. Taylor, 2011, “Financial Crises, Credit Booms, and External
Imbalances: 140 Years of Lessons,” IMF Economic Review, Vol. 59, No. 2, pp. 340–78.
Kaminsky, G., 2003, “Varieties of Currency Crises,” NBER Working Paper No. 10193
(Cambridge, Massachusetts: National Bureau of Economic Research).
———, S. Lizondo, and C. Reinhart, 1998, “Leading Indicators of Currency Crisis,” IMF Staff
Papers, Vol. 45, No. 1, pp. 1–48.
Kaminsky, G., and C. Reinhart, 1999, “The Twin Crises: The Causes of Banking and Balance-
of-Payments Problems,” American Economic Review, Vol. 89, No. 3 pp. 473–500.
———, 2001, “Bank Lending and Contagion: Evidence from the Asian Crisis,” in Regional and
Global Capital Flows: Macroeconomics Causes and Consequences, Vol. 10, ed. by Takatoshi Ito
and Anne O. Krueger (Chicago, Illinois: University of Chicago Press) pp. 73–116.
Kannan, P., 2009, “On the Welfare Benefits of an International Currency,” European Economic
Review, Vol. 53, No. 5, pp. 588–606.
Keynes, J.M., 1930, The Great Slump of 1930 (London: The Nation & Athenæum, issues of
December 20 and December 27).
Kindleberger, C., 1976, “Technical Education and the French Entrepreneur,” in Enterprise and
Entrepreneurs in 19th and 20th century France, ed. by E.C. Carter II., R. Foster, and J.N.
Moody (Baltimore, Maryland: Johns Hopkins University Press) pp. 3–39.
———, 1986, The World in Depression: 1929–1939 (Berkeley, California: University of
California Press).
King, M., 2012, “Twenty Years of Inflation Targeting,” Speech given at the Stamp Memorial
Lecture, London School of Economics, October 9. http://www.bankofengland.co.uk/publi-
cations/Pages/speeches/2012/606.aspx.
Klein, M.W., and N.P. Marion, 1994, “Explaining the Duration of Exchange-Rate Pegs,” NBER
Working Paper No. 4651 (Cambridge, Massachusetts: National Bureau of Economic Research).
Kletzer, K.M., and B.D. Wright, 2000, “Sovereign Debt as Intertemporal Barter,” American
Economic Review, Vol. 90, No. 3, pp. 621–39.
Klingebiel, D., R. Kroszner, and L. Laeven, 2007, “Banking Crises, Financial Dependence and
Growth,” Journal of Financial Economics, Vol. 84, No. 1, pp. 187–228.
Kocherlakota, N., 2009, “Bursting Bubbles: Consequences and Cures,” paper presented at
“Macroeconomic and Policy Challenges Following Financial Meltdowns” Conference hosted
by International Monetary Fund, April 3.
Kohn, D.L., 2008, “Monetary Policy and Asset Prices Revisited,” Speech at the Cato Institute’s
26th Annual Monetary Policy Conference, Washington, DC, November 19.
Claessens and Kose 57
Korinek, A., 2011, “Foreign Currency Debt, Risk Premia and Macroeconomic Volatility,”
European Economic Review, Vol. 55, No. 3. pp. 371–85.
Kose, M.A., P. Loungani, and M. Terrones, Forthcoming, “Global Recessions and Recoveries,”
IMF Working Paper (Washington: International Monetary Fund).
Kose, M.A., and E. Prasad, 2010, Emerging Markets: Resilience and Growth amid Global Turmoil
(Washington: Brookings Institution Press).
———, K. Rogoff, and S.-J. Wei, 2010, “Financial Globalization and Economic Policies,” in
Handbook of Development Economics, Vol. 5, ed. by Dani Rodrik and Mark Rosenzweig
(Amsterdam: Elsevier B.V.) pp. 4283–362.
Krugman, P., 1979. “A Model of Balance-of-Payments Crises,” Journal of Money, Credit and
Banking, Vol. 11, No. 3, pp. 311–25.
———, 1999, “Balance Sheets, the Transfer Problem, and Financial Crises,” International Tax
and Public Finance, Vol. 6, No. 4, pp. 459–72.
Laeven, L., 2001, “Insider Lending and Bank Ownership: The Case of Russia,” Journal of
Comparative Economics, Vol. 29, No. 2, pp. 207–29.
———, 2011, “Banking Crises: A Review,” Annual Review of Financial Economics, Vol. 3, No.
1, pp. 17–40.
———, and F. Valencia, 2008, “Systemic Banking Crises: A New Database,” IMF Working
Paper 08/224 (Washington: International Monetary Fund).
Lamont, O., and A.R.H. Thaler, 2003, “Can the Market Add and Subtract? Mispricing in Tech
Stock Carve-outs,” Journal of Political Economy, Vol. 111, No. 2, pp. 227–68.
Lane, P.R., 2012, “The European Sovereign Debt Crisis,” Journal of Economic Perspectives, Vol.
26, No. 3, pp. 49–68.
———, and G.-M. Milesi-Ferretti, 2011, “The Cross-Country Incidence of the Global Crisis,”
IMF Economic Review, Vol. 59, No. 1, pp.77–110.
Lansing, K.J., 2008, “Speculative Growth and Overreaction to Technology Shocks,” Working
Paper No. 2008-08 (San Francisco, California: Federal Reserve Bank of San Francisco).
La Porta, R., F. Lopez-de-Silanes, A. Shleifer, and R. Vishny, 2000, “Investor Protection and
Corporate Governance,” Journal of Financial Economics, Vol. 58, No. 1-2, pp. 3–27.
Levy-Yeyati, E.L., and U. Panizza, 2011, “The Elusive Costs of Sovereign Defaults,” Journal of
Development Economics, Vol. 94, No. 1, pp. 95–105.
Lindgren, C.-J., G. Garcia, and M. Saal, eds., 1996, Bank Soundness and Macroeconomic Policy
(Washington: International Monetary Fund).
Lo, A.W., and A.C. MacKinlay, 2001, A Non-Random Walk Down Wall Street (Princeton, New
Jersey: Princeton University Press).
Lopez-Salido, D., and E. Nelson, 2010, “Postwar Financial Crises and Economic Recoveries in
the United States,” Working Paper (Washington: Federal Reserve Board).
Maddaloni, A., and J.-L. Peydró, 2010, “Bank Risk-Taking, Securitization, Supervision and
Low Interest Rates: Evidence from the Euro Area and the U.S. Lending Standards,” Working
Paper No. 1248 (European Central Bank: Frankfurt).
Mauro, P., and T.I. Becker, 2006, “Output Drops and the Shocks That Matter,” IMF Working
Papers 06/172 (Washington: International Monetary Fund).
Magud, N.E., C.M. Reinhart, and E.R. Vesperoni, 2012, “Capital Inflows, Exchange Rate
Flexibility, and Credit Booms,” IMF Working Paper No. 12/41 (Washington: International
Monetary Fund).
McKinnon, R., and H. Pill, 1996, “Credible Liberalizations and International Capital Flows:
The Overborrowing Syndrome,” in Financial Deregulation and Integration in East Asia, ed. by
T. Ito and A. Krueger (Chicago, Illinois: University of Chicago Press) pp.7–42.
———, 1998, “International Overborrowing: A Decomposition of Credit and Currency
Risks,”World Development, Vol. 26, No. 7, pp. 1267–82.
McFadden, D., R. Eckaus, G. Feder, V. Hajivassiliou, and S. O’Connell, 1985, “Is there life
after Debt? An Econometric Analysis of the Creditworthiness of Developing Countries,” in
International Debt and the Developing Countries, ed. by Gordon Smith and John Cuddington
(Washington: World Bank) 179–209.
Laeven and
Valencia 2011
(one of the
sources for figures
1.3 and 1.4)]]
should be 2012
[[AQ: Okay, then
pls add Laeven
and Valencia
2012 to the
refs.]]
58 Financial Crises: Explanations, Types, and Implications
Mendoza, E.G., 2009, “Comment on ‘Financial Integration within EU Countries: The Role of
Institutions, Confidence, and Trust’,” in NBER International Seminar on Macroeconomics
2007 (Cambridge, Massachusetts: National Bureau of Economic Research) pp. 395–400.
———, 2010, “Sudden Stops, Financial Crises, and Leverage,” American Economic Review, Vol.
100, No. 5, pp. 1941–66.
———, and M. Terrones, 2008, “An Anatomy of Credit Booms: Evidence from Macro
Aggregates and Micro Data,” NBER Working Paper No. 14049 (Cambridge, Massachusetts:
National Bureau of Economic Research).
———, 2012, “An Anatomy of Credit Booms and Their Demise,” Journal of Economia Chilena,
Central Bank of Chile, Vol. 15, pp. 4–32.
Milesi-Ferretti, G.-M., and A. Razin, 2000, “Current Account Reversals and Currency Crises,
Empirical Regularities,” in Currency Crises, ed. by Paul Krugman (Cambridge, Massachusetts:
National Bureau of Economic Research) pp. 285–326.
Milesi-Ferretti, G.-M., and C. Tille, 2011, “The Great Retrenchment: International
Capital Flows during the Global Financial Crisis,” Economic Policy, Vol. 26, No. 66, pp.
285–342.
Miller, M.H., 1977, “Debt and Taxes,” Journal of Finance, Vol. 32, pp. 261–75.
Minsky, H.P., 1975, John Maynard Keynes (New York, New York: Columbia University Press).
———, 1992, “The Financial Instability Hypothesis,” Working Paper No. 74 (Annandale-on-
Hudson, New York: Levy Economics Institute of Bard College).
Mishkin, F.S., 2008, “Does Stabilizing Inflation Contribute to Stabilizing Economic Activity?”
NBER Working Paper No. 13970 (Cambridge, Massachusetts: National Bureau of Economic
Research).
———, 2011, “Monetary Policy Strategies: Lessons from the Crisis,” NBER Working Paper
No. 16755 (Cambridge, Massachusetts: National Bureau of Economic Research.
Obstfeld, M., 2012, “Financial Flows, Financial Crises, and Global Imbalances,” Journal of
International Money and Finance, Vol. 31, No. 3, pp. 469–80.
———, and K. Rogoff, 1986, “Ruling Out Divergent Speculative Bubbles,” Journal of
Monetary Economics, Vol. 17, No. 3, pp. 349–62.
———, 2009, “Global Imbalances and the Financial Crisis: Products of Common Causes,”
CEPR Discussion Paper No. 7606 (London: Centre for Economic Policy Research).
Ofek, E., and M. Richardson, 2003, “DotCom Mania: The Rise and Fall of Internet Stock
Prices,” Journal of Finance, Vol. 58, pp.1113–37.
Panizza, U., F. Sturzenegger, and J. Zettelmeyer, 2009, “The Economics and Law of Sovereign
Debt and Default,” Journal of Economic Literature, Vol. 47, No. 3, pp. 651–98.
Papell, D.H., and R. Prudan, 2011, “The Statistical Behavior of GDP after Financial Crises and
Severe Recessions,” Paper prepared for the Federal Reserve Bank of Boston conference on
“Long-Term Effects of the Great Recession,” October 18–19.
Pastor, L., and P. Veronesi, 2006, “Was There a Nasdaq Bubble in the Late 1990s?”Journal of
Financial Economics, Vol. 81, No. 1, pp. 61–100.
Radelet, S., and J. Sachs, 1998, “The East Asian Financial Crisis: Diagnosis, Remedies,
Prospects,” Brookings Papers on Economic Activity, Vol. 1, No. 1, pp. 1–74.
Rajan, R.G., 2005, “Has Financial Development Made the World Riskier?” Proceedings, Federal
Reserve Bank of Kansas City, August, pp. 313–69.
Rancière, R., and A. Tornell, 2011, “Financial Black-Holes: The Interaction of Financial
Regulation and Bailout Guarantees,” CEPR Discussion Paper 8248 (London: Centre for
Economic Policy Research).
Reinhart, C., J. Kirkegaard, and B. Sbrancia, 2011, “Financial Repression Redux,” Finance and
Development, Vol. 48, No. 1.
Reinhart, C.M., and K.S. Rogoff, 2008a, “Is the 2007 U.S. Subprime Crisis So Different? An
International Historical Comparison,” American Economic Review, Vol. 98, No. 2, pp. 339–44.
———, 2009a, “The Aftermath of Financial Crises,” American Economic Review, Vol. 99, pp.
466–72.
Claessens and Kose 59
———, 2009b, This Time is Different: Eight Centuries of Financial Folly (Princeton, New Jersey:
Princeton University Press).
———, 2011, “From Financial Crash to Debt Crisis,” American Economic Review, Vol. 101,
No. 5, pp. 1676–706.
———, forthcoming, “Banking Crises: An Equal Opportunity Menace,” Journal of Banking
and Finance.
Rose, A.K., and M.M. Spiegel, 2011, “Cross-Country Causes and Consequences of the 2008
Crisis: Early Warning,” European Economic Review, Vol. 55, No. 3, pp. 309–24.
Salant, S., 1983, “The Vulnerability of Price Stabilization Schemes to Speculative Attack,”
Journal of Political Economy, Vol. 91, No. 1, pp. 1–38.
———, and D. Henderson, 1978, “Market Anticipations of Government Policies and the Price
of Gold,” Journal of Political Economy, Vol. 86, No. 4, pp. 627–48.
Scheinkman, J.A., and W. Xiong, 2003, “Overconfidence and Speculative Bubbles,” Journal of
Political Economy, Vol. 111, No. 6, pp. 1183–219.
Scherbina, A., 2013, “Asset Price Bubbles: A Selective Survey,” IMF Working Paper 13/45
(Washington: International Monetary Fund).
Schularick, M., and A.M. Taylor, 2012, “Credit Booms Gone Bust: Monetary Policy, Leverage
Cycles, and Financial Crises, 1870–2008,” American Economic Review, Vol. 102, No. 2, pp.
1029–61.
Schwert, G.W., 2003, “Anomalies and Market Efficiency,” in Handbook of the Economics of
Finance, Vol. 1, ed. by G.M. Constantinides, M. Harris, and R.M. Stulz (Amsterdam:
Elsevier B.V.) pp. 939–74.
Shin, H.S., 2009, “Reflections on Northern Rock: The Bank Run that Heralded the Global
Financial Crisis,” Journal of Economic Perspectives, Vol. 23, No. 1, pp. 101–19.
Shleifer, A., 2000, Inefficient Markets: An Introduction to Behavioral Finance (Oxford, UK:
Oxford University Press).
———, and R.W. Vishny, 1997, “The Limits of Arbitrage,” Journal of Finance, Vol. 52, No. 1,
pp. 35–55.
Soros, G., 1987, The Alchemy of Finance: Reading the Mind of the Market (New York, New York:
Touchstone/Simon & Schuster).
Stiglitz, J., and A. Weiss, 1983, “Alternative Approaches to Analyzing Markets with Asymmetric
Information: Reply [The Theory of ‘Screening,’ Education, and the Distribution of Income],”
American Economic Review, Vol. 73, No. 1, pp. 246–49.
Sturzenegger, F., and J. Zettelmeyer, 2007, Debt Defaults and Lessons from a Decade of Crises
(Cambridge, Massachusetts, and London: MIT Press).
Taylor, J.B., 2009, “The Financial Crisis and the Policy Responses: An Empirical Analysis of
What Went Wrong,” NBER Working Paper No. 14631 (Cambridge, Massachusetts: National
Bureau of Economic Research).
———, 2011, “An Empirical Analysis of the Revival of Fiscal Activism in the 2000s,” Journal
of Economic Literature, Vol. 49, No. 3, pp. 686–702.
Tirole, J., 2002, Financial Crises, Liquidity, and the International Monetary System (Princeton,
New Jersey: Princeton University Press).
Tomz, M., and M.L.J. Wright, 2007, “Do Countries Default in ‘Bad Times’?”Journal of the
European Economic Association, Vol. 5, No. 2-3, pp. 352–60.
Trichet, J.-C., 2009, “Credible Alertness Revisited,” speech at the symposium on “Financial
Stability and Macroeconomic Policy,” sponsored by the Federal Reserve Bank of Kansas City,
Jackson Hole, Wyoming, August 22.
Wang, P., and Y. Wen, 2012, “Speculative Bubbles and Financial Crises,” American Economic
Journal: Macroeconomics, Vol. 4, No. 3, pp. 184–221.
Wermers, R., 2012, “Runs on Money Market Mutual Funds,” Working Paper (College Park,
Maryland: University of Maryland).
World Bank, 2001, Finance for Growth: Policy Choices in a Volatile World (Washington: World
Bank).
