Sogang IIAS Research Series on International Affairs Vol.3
１
An Early Warning System for Contagious
Currency Crisis
Gongpil Choi*
Abstract
Despite widespread skepticism concerning the feasibility of building an EWS for
the currency crisis, our empirical evidence suggests that the prudent monitoring of the contagion
effect as well as key macroeconomic and financial variables is an essential measure to guard
against the fragile nature of creditor panic, which can easily trigger a crisis phenomenon. While
fundamentals matter for determining the vulnerability of an economy against various shocks,
the contagion proved to be important in precipitating crises dynamics through various links. As
such, the degree of vulnerability and the relative importance of various channels suggested for
contagion are important to understand the shock-propagation mechanism in the Asian region. In
this paper, we investigate the role of contagion in explaining currency crises in terms of the
contagion vulnerability index. Incorporating this additional piece of information would allow us
to expect improvements in the predictability of an EWS. Predicting exogenous shocks would be
an impossible task, but measuring vulnerability to contagious currency crises can be done with
reasonable accuracy.
Executive Summary
The fact that a country can suddenly experience a crisis situation even with relatively sound
fundamentals tells us that contagion and vulnerability deserve renewed attention to better understand the
dynamics leading to crises in Asia. Even with self-fulfilling expectations and contagion, economic
fundamentals do matter for crises, and an early warning system(EWS) would be infeasible otherwise. The
elements of sudden attacks and weak fundamentals, two seemingly independent causes for crisis, may be
intertwined because structurally unsound economies are likely to be more vulnerable to the instability of
financial markets.
This study examines the feasibility of designing an early warning system for a currency crisis in
Korea by looking into the dynamics of vulnerability and contagion. It is built on the idea that the seed for
crises can be detected and monitored with relative accuracy even with the nonlinear features of the
dynamics of the crises that were observed during the 1997-98 crises in Asia.
Regardless of the differences between competing theories of crises, contagion and vulnerability
emerged as essential features of the recent Asian crises. Contagion refers to the situation where problems
*
Gongpil Choi is a Senior Research Fellow at Korea Institute of Finance. Prepared for presentation at the ADBI workshop on
“Synchronized Recession and Policy Coordination in Asia” (April, Tokyo) The author is grateful to Gongju Hwang for his
research assistance and dedication. Correspondence to the author: [email protected]. I hold all errors as my responsibility.
１
Sogang IIAS Research Series on International Affairs Vol.3
２
in other parts of the region increase the probability of crisis at home. Shocks from outside can be grouped
to better explain contagion: trade link, common lender, and similarity with other countries in terms of the
capital market structure, macro conditions, etc.
Quantifying the contagion effect is not an easy task, but at least we can start building the contagion
vulnerability index ; e.g., Kaminsky and Reinhart (1999). One of the fundamental changes from the
previous version of EWS is that we take the role of vulnerability in transmitting shocks seriously. In
addition to the role of key fundamentals-related variables, the dynamics are affected by the level of
vulnerability of the country in question as well as other countries within the region. It turns out that the
contagion vulnerability index does a reasonable job in predicting a crisis in this region.
Empirical evidence shows that even though the trade link among Asian nations is not as strong as
inter-regional cases, the financial market plays a more significant role in transmitting shocks within the
region. We also detect a significant rise in volatility as well as increasing interdependence in currency
markets, contributing to the synchronized business cycle. Clearly, the conditions for Asia become more
susceptible to contagion, because of the increased interdependence through financial linkage as well as
similarity in an industrial structure (weak trade links among the countries within the region) observed
within the region.
The proposed EWS in this study is constructed to predict the target variable (crisis index) with
reasonable accuracy. We try to use a measure of economic vulnerability to better explain the crisis index.
To construct a composite index for vulnerability, we need to incorporate these channels in addition to
variables related with economic fundamentals. Relative weights depend on their signaling performance,
and the inverse of N/S can be utilized for them. As predicted, relative weights of sectoral indices show that
financial and contagion variables play a more visible role in the Korean crisis. This index can further be
used to generate probability forecasts of a crisis, e.g. logit/probit model. Given four channels for contagion,
relative weights are determined according to the activation pattern of the contagion channel with weights
set by the inverse of the noise-signal ratio of each channel.
In conclusion, interdependence among currencies and interest rates among Asian nations have
increased significantly after the crisis. Given the role of trade and financial links, financial markets are
regarded as identical and tend to be grouped together. Financial sector links, especially those of Japanese
banks, have played an important role in the 90s in transmitting shocks across the region, but it would not
be a direct shock since Japanese banks already reduced their lending significantly over the years. Given
increased interdependence, however, the shock-propagation mechanism will be much more complex. Asia
can easily succumb to contagion because of its similarity in an industrial structure, weaker capital markets,
greater dependence on banks, i.e., greater exposure to identical sets of shocks, which will be more likely
related to trade links with the financial origin. Given the increasing importance of contagion and
vulnerability, the performance of an EWS relies on region-wide surveillance and policy responses.
1. Introduction
Disputes on how to resolve the crisis seem to have originated from divided views on what caused the
crisis in the first place. For the sake of simplicity, academic circles may be split into two camps. One
camp, which focuses on Asian countries’ liquidity shortage, emphasizes the instability of the international
financial market and the sudden shifts in market expectations and confidence as the major triggering factor
２
Sogang IIAS Research Series on International Affairs Vol.3
３
in the outbreak of the crisis.12 The fact that a country can suddenly experience a crisis situation even with
relatively sound fundamentals tells us that contagion and vulnerability deserve renewed attention to better
understand the dynamics leading to crises in Asia. In opposition to this financial panic view, the other
camp stresses structural weaknesses and policy distortions of the country in question, and, in particular,
moral hazard problems in both the corporate and financial sectors. This view emphasizes the necessity of
restructuring and the sustainability of growth based upon sound macroeconomic and financial systems.3
In Korea’s case, even with seemingly sound macroeconomic fundamentals compared to other East Asian
neighbors, the lax supervision of and regulations for financial institutions, and the resulting significant
mismatch in the sources and uses of funds helped activate crisis dynamics (Choi 1999).
In retrospect, we believe that both an internal structural weakness and the instability of international
financial markets led to the Asian crisis. Also, while the identification of either of the two as the primary
cause of the crisis might help in some regards, an eclectic approach would be more beneficial in
constructing an EWS and drawing policy lessons. Furthermore, two seemingly independent causes may be
intertwined because structurally unsound economies are likely to be more vulnerable to the instability of
financial markets. At least, the contagion related crisis dynamics are also related to the fundamental
weakness even with the visible role of expectations that contributes to the realization of a crisis. In fact, if
the triggering mechanism for a currency crisis cannot be traced to structural problems or macroeconomic
imbalances, it is almost impossible to design an early warning system (EWS) for a currency crisis since
subtle changes in investor's risk appetite are hard to predict. Also, even with early signs of an impending
crisis identified, it may be too late to expect an effective policy response, which far exceeds the leading
time of any reliable EWS. This study examines the feasibility of designing an early warning system for a
currency crisis in Korea by looking into the dynamics of vulnerability and contagion. It is built on the idea
that the seed for crises can be detected and monitored with relative accuracy even with the nonlinear
features of crises dynamics that were observed during the 1997-98 crises in Asia.
Regardless of the differences between competing theories of crises, contagion and vulnerability
emerged as essential features of the recent Asian crises. Contagion refers to the situation where problems
in other parts of the region increase the probability of crisis at home. Shocks from outside can be grouped
to better explain contagion: trade link, common lender, and similarity with other countries in terms of the
capital market structure, macro conditions, etc. Notably, some of the possible explanations for recent
contagions include herding behavior or the common lender problem. There have been several incidences
of contagious currency crises, notably those of Asian crises during 1997-98. The Tequila effect confirmed
that a trade link is not necessary for contagion to affect a nation as financial markets become intricately
linked. A particularly well-known example is the extensive research done on the contagion effect that
affected many nations after the Mexican crisis in 1994.45 These studies are based on cross-country data
and allow us to investigate the general pattern of crisis that goes beyond the experience of an individual
country. However, cross-country studies cannot properly reveal the characteristics of each individual
country, and inter-country comparison is at best limited. In this paper, we are interested in investigating
the dynamics of crises that emanate mainly from Asian countries from the Korean perspective.
1
Change and Velasco (1998), Feldstein (1998), and Radelet and Sachs (1998) asserted that the
Asian crisis was primarily caused by illiquidity brought to the head by a panicky, herd behavior
of international investors and
creditors.
2
Krugman (1999) proposes the third generation of crisis models, which emphasizes balance
sheet effects on
firms. If a country has the combination of highly leveraged firms and the substantial component of unhedged foreign currency
denominated debts, the country has the possibility of a self-fulfilling collapse, in which a loss of confidence leads to the collapse
of the currency, which leads to the implosion of the balance sheet, which leads to the collapse of the output, which validates the
loss of confidence in the first place.
3
Studies emphasizing the economic fundamentals as the primary cause of the financial crisis in
Asia are Corsetti et al. (1998a, 1998b), Fischer (1998), Kaminsky (1998) and Krugman (1998a, 1998b). In the case of Korea, see
also Park and Choi (1998b).
4
See Calvo and Reinhart (1995) and Eichengreen, Rose, and Wyplosz (1996).
5
In advanced countries, see Eichengreen, Rose and Wyplosz (1995), and in the cases of
developing countries, one can refer to Frankel and Rose (1996) and Sachs, Tornell, and Velasco (1996b). See Kaminsky and
Reinhart (1996) for a more comprehensive study covering both.
３
Sogang IIAS Research Series on International Affairs Vol.3
４
Quantifying the contagion effect is not an easy task, but at least we can start building the contagion
vulnerability index ; e.g., Kaminsky and Reinhart (1999). Special attention is given to the role of the
Japanese banking system in setting off shocks that would test the vulnerabilities of other Asian nations,
specifically Korea. After the crisis, the role of the Japanese bank in supplying credit has been less
noticeable in Korea. Still, given a sizable exposure to European banks, the common lender problem may
exacerbate the situation in an abrupt manner. Also, the trade link remains one of the potential channels of
contagion because the most likely fallout from the Japanese problem would be a depreciation of Japanese
Yen. Given that Korea has high exports, like Japan, exchange market pressure is like to build up when the
Japanese banking problem begins to be realized.
One of the fundamental changes from the previous version of EWS is that we take the role of
vulnerability in transmitting shocks seriously. In addition to the role of key fundamentals-related variables,
the dynamics are affected by the level of vulnerability of the main country as well as other countries
within the region. It turns out that the contagion vulnerability index does a reasonably better job in
predicting a crisis in this region. The issue is how to model the nonlinear feature of crisis dynamics using
the vulnerability index. Above a certain level of vulnerability, the crisis index remains sensitive to any
changes in leading indicators, including various contagion variables. As such, the nonlinearity feature can
be the result of not fully utilizing the relevant information set. Also, another modeling issue is to allow
different responses to various shocks. If the number of countries within the region increase or when the
vulnerability increases above a certain threshold, then the contagion effect should be stronger.
The paper is organized as follows. In section II, a simple exposition is made to compare traditional and
self-fulfilling currency crises, and some improvements over the previous version are explained. In section III,
we construct a crisis index and introduce some of the factors explaining the movement in the crisis index. In
section IV, the signals approach was applied to ferret out explanatory variables, which are then followed by a
brief discussion on the newly constructed composite index of vulnerability with its connection to the
probability of a crisis. In section V, some of the likely scenarios in which contagion is likely to be propagated
are examined. The final section concludes the study.
2. Models for Currency Crises in Asia
2.1. Comparison
In the face of a currency crisis, changes in policy response allow multiple equilibria, and the selffulfilling nature of the currency crisis sets in. For instance, reduced foreign reserves prompt market
participants to form expectations about the future depreciation and the cost of maintaining the fixed level
of exchange rate increases, forcing the authority to give up in the final round. When expectations are selffulfilling, a crisis can erupt abruptly and it is virtually impossible to predict a crisis. However, the nature
of a crisis is such that a crisis associated with structural vulnerability is observationally equivalent to a
self-fulfilling crisis. Speculators increase their holdings of foreign currency when they realize that the
authority cannot maintain the exchange rate, forcing the immediate depreciation of the currency. It needs
to be noted, however, that the second-generation model simply emphasizes the triggering mechanism in
the presence of structural weakness, but does not show that a crisis can occur without a link to market
fundamentals. It is important to note that a crisis can only occur when the economy enters into a crisisprone zone due to structural weaknesses or contagion.
This study rests on the vulnerability to contagion to explain this process. In this context, the
difference between the first and second generation model is not great since they both equally allow for the
possibilities that a crisis can develop when market fundamentals are threatened and that a crisis can
develop in an abrupt manner. In this study, we conduct an empirical investigation into the possibility of
４
Sogang IIAS Research Series on International Affairs Vol.3
５
currency crisis from the perspective that economic vulnerability, financial fragility, and distress can be
equally explained by variables for market fundamentals and contagion variables as building blocks for the
second generation model (Kaminsky, 1998). The results can pretest the feasibility of building an EWS for
the currency crisis in Korea.
2.2. The Role of Contagion in the Propagation Mechanism
Since crisis countries have shown a remarkable turnaround, the role of the contagion effect is gaining
wide support among academics. Radelet and Sachs (1999) reaffirmed their original position that a crisis is
mainly triggered by investors' panic rather than weak fundamentals. Even Krugman, who emphasized the
moral hazard issue in the region, acknowledged the role of contagion (Krugman, 1999a), yet structural
weakness remain the primary cause for the crisis (Krugman, 1999b). In short, previous experiences show
that contagion is an important channel for crises in Asia, it can be decomposed into market fundamentals
and self-fulfilling elements as pointed out by Masson (1998).
First, there is the monsoonal effect that points out the influence on developing countries for advanced
countries’ exchange rates and interest rates. If candidate countries excessively rely on foreign financing
and have weak financial markets, a common shock can easily trigger a currency crisis for these susceptible
economies. For example, as interest rates during the 1980s rose up in the U.S., South American countries
experienced debt crises. Moreover, the weakening of the yen after 1996 and the deep recession in Japan
noticeably exacerbated the export environment in Asia.
Second, the spillover effect is related to the change incurred by other countries through trade and
financial linkage. 6 For example, when a country in the region raises exchange rates substantially,
competing nations are forced to depreciate in order to remain competitive, while financial instability in
one country triggers massive outflow from neighboring countries due to heightened risk consciousness.
The above effects are closely related to market fundamentals and cannot be classified as contagion effects.
In the case of the monsoonal effect, a common shock in the region resulted in a crisis because fundamental
weaknesses and market fundamentals remained an important factor. As for the spillover effects, market
fundamentals related to trade and financial linkage remain the cause of the crisis. Since both monsoonal
and spillover effects explain the transmission mechanism without assuming multiple equilibrium in the
economy, these should be distinguished from a self-fulfilling crisis model under multiple equilibria.
Third, the pure contagion effect refers to a situation in which a crisis is driven by self-fulfilling
expectations that are not directly related to market fundamentals. For example, when a country is hit by a
crisis, expectations about the future depreciation can develop for those neighboring countries even with no
close trade or financial linkages.
As discussed, the empirical effort to identify self-fulfilling expectations is extremely difficult. This
point is important in designing an early warning system for a currency crisis since self-fulfilling
expectations delimit the predictability of an EWS effectively. Accordingly, the proposed EWS
concentrates on fundamentals related contagion in this region. Among Asian nations, Korea, Thailand, and
Indonesia do not show impressive financial and trade linkage, although Singapore and Malaysia have a
closer link between them. In addition, Japan’s influence in this region increased after 1985, especially for
Korea. The mere fact that crisis countries have shown a fast recovery does not support the claim that selffulfilling expectations are singled out as the primary reason for crisis transmission, especially in light of
the fact that the Japanese yen remained relatively steady, promoting the regional turnaround. Thus, it is
important to capture the contagion effect that is fundamentals-based.7
6
7
Contagion models based on trade linkage are Gerlach and Smets (1995) and Eichengreen,
Rose, and Wyplosz (1996).
Masson (1998) analyzes the contagion effect during the Mexican crisis and the recent Asian crisis, but points out that the
conditions for multiple equilibria that allow the contagion effect cannot be found in Korea and Malaysia, which both had a
５
Sogang IIAS Research Series on International Affairs Vol.3
６
[Table 1] Trade Linkage among Asian Neighbors
Japan
Indonesia
Korea
Malaysia
Philippines
Singapore
Thailand
Other
Japan
-
1.59
6.42
2.90
2.15
4.36
2.85
79.73
Indonesia
23.21
-
6.95
3.18
1.32
10.57
1.65
53.12
Korea
11.91
2.04
-
2.05
1.96
3.29
1.17
77.59
Malaysia
13.02
1.74
3.30
-
1.76
18.39
3.62
58.18
Philippines
14.68
0.48
3.07
3.60
-
8.18
3.16
66.83
Singapore
7.54
-
3.56
18.16
2.46
-
4.26
64.03
Thailand
14.80
1.94
1.84
4.07
1.57
8.69
-
67.09
Note : The ratio shows trade volume with trade partners/ total trade volume of individual country.
Source: IMF(2000) data.
Korea
Thailand
Malaysia
Philippines
Taiwan
Indonesia
Korea
1
0.822196
0.214356
0.369653
0.633141
0.242733
[Table 2] Correlation Between Nominal Exchange Rates
(January 1, 1996 ~ April 30, 1997)
Thailand
Malaysia
Philippines Taiwan
Indonesia
1
0.291593
0.519760
0.660979
0.501129
1
-0.089820
0.613109
0.029315
1
0.451459
0.822800
1
0.482074
1
Source : Bloomberg, nominal exchange rates.
(May 1, 1998 ~ December 31, 2001)
Korea
Thailand
Malaysia
Philippines
Taiwan
Indonesia
Korea
1
0.464545
-0.51889
0.941242
0.871794
0.539014
Thailand
Malaysia
Philippines Taiwan
Indonesia
1
-0.18381
0.361494
0.286408
0.247787
1
-0.39859
-0.59475
-0.26099
1
0.820466
0.420869
1
1
0.501529
Source : Bloomberg, nominal exchange rates.
The following Figures and tables show that even though the trade link among Asian nations is not as
strong as the inter-regional cases, the financial market plays a more significant role in transmitting shocks
within the region. The Figures also show a significant rise in volatility in emerging markets during the
1997-98 crisis episode. Taken together, interdependence among currencies and interest rates among Asian
relatively low ratio of overseas liabilities. Also, Baig and Goldgajn (1998) emphasize the fact that correlations among stock
prices, exchange rates, and interest rates increased significantly after the Asian crisis, which supports the evidence of
contagion effect, or monsoonal effect.
６
Sogang IIAS Research Series on International Affairs Vol.3
７
nations increased in the wake of the financial crisis, contributing to the synchronized business cycle. This
paper does not address the issue of how to measure the propagation mechanism and contagion channels
per se. Rather, the susceptibility of an economy to various shocks is explicitly considered in terms of
contagion channels. This allows us to monitor the changes in vulnerability of an economy and helps us
better predict the episodes of crises.
[Table 3] Daily Interest Rates: Causality Test (lag=10)
(January 1, 1996 ~ July 1, 1997)
Indonesia
F-Statistic
(Probability)
Malaysia
F-Statistic
(Probability)
Philippines
F-Statistic
(Probability)
Korea
F-Statistic
(Probability)
Thailand
F-Statistic
(Probability)
-
Malaysia
Indonesia
0.70
(0.72)
Philippines
Korea
Thailand
1.95
(0.04) *
0.55
(0.85)
0.26
(0.98)
1.38
(0.18)
-
1.13
(0.27)
0.57
(0.83)
5.17
(5.7E-07)
0.72
(0.70)
1.08
(0.38)
-
0.76
(0.66)
2.78
(0.003) *
0.48
(0.15)
0.57
(0.83)
1.59
(0.11)
-
2.18
(0.02)*
1.14
(0.33)
1.13
(0.35)
0.58
(0.83)
0.68
(0.74)
-
(July 2, 1997 ~ November 16, 1997)
Indonesia
F-Statistic
(Probability)
Malaysia
F-Statistic
(Probability)
Philippines
F-Statistic
(Probability)
Korea
F-Statistic
(Probability)
-
Malaysia
Indonesia
0.18
(0.99)
Philippines
Korea
Thailand
0.78
(0.64)
1.18
(0.32)
0.51
(0.87)
0.47
(0.90)
-
2.52
(0.01)*
0.17
(2.5E-09)*
5.70
(4.7E-06)*
1.88
(0.06)**
1.50
(0.16)
-
0.09
(0.99)
0.49
(0.88)
0.92
(0.52)
0.47
(0.90)
1.62
(0.12)
-
0.28
(0.98)
７
Sogang IIAS Research Series on International Affairs Vol.3
８
Thailand
F-Statistic
(Probability)
7.34
(1.3E-07)*
0.49
(0.88)
1.36
(0.22)
4.64
(1.9E-06)*
Note: * ,** show 5 and 10% level of significance, respectively.
-
(November 17, 1997 ~ December 31, 2001)
Indonesia
F-Statistic
(Probability)
Malaysia
F-Statistic
(Probability)
Philippines
F-Statistic
(Probability)
Korea
F-Statistic
(Probability)
Thailand
F-Statistic
(Probability)
-
Malaysia
Indonesia
0.04
(0.59)*
Philippines
Korea
Thailand
0.16
(0.88)
0.02
(0.09)**
0.35
(0.84)
0.10
(0.91)
-
2.52
(0.01)*
6.31
(2.5E-09)*
0.44
(0.92)
0.03
(0.92)
1.50
(0.16)
-
0.59
(0.81)
1.59
(0.10) **
0.01
(0.89)
1.42
(0.17)
8.12
(1.6E-06)*
-
2.14
(0.01)
1.94
(0.05) *
2.43
(0.00)*
1.85
(0.05)*
4.64
(1.9E-06)*
-
Note: * ,** show 5 and 10% level of significance, respectively.
Source: All interest rate series are call rates or interbank rates (Philippines, Thailand) and
Bloomberg
gathered from the
[Table 4] Daily Exchange Rate Changes: Causality Test
(January 1, 1996 ~ July 1, 1997)
Indonesia
F-Statistic
(Probability)
Malaysia
F-Statistic
(Probability)
Philippines
F-Statistic
(Probability)
Korea
F-Statistic
(Probability)
-
Malaysia
Indonesia
0.72
(0.71)
Philippines
Korea
Thailand
1.42
(0.17)
1.08
(0.38)
0.37
(0.96)
1.33
(0.21)
-
1.13
(0.33)
1.82
(0.05)
3.65
(0.00) *
1.01
(0.43)
0.76
(0.66)
-
1.37
(0.19)
1.95
(0.03)*
0.91
(0.52)
1.66
(0.09)**
1.65
(0.09)
-
1.68
(0.08) **
８
Sogang IIAS Research Series on International Affairs Vol.3
９
Thailand
F-Statistic
(Probability)
3.68
(0.00)*
Note:
1.68
(0.08)**
3.89
(5.7E-05)*
3.86
(6.5E-05)*
-
* ,** show 5 and 10% level of significance, respectively.
.
(July 2, 1997 ~ November 16, 1997)
Indonesia
F-Statistic
(Probability)
Malaysia
F-Statistic
(Probability)
Philippines
F-Statistic
(Probability)
Korea
F-Statistic
(Probability)
Thailand
F-Statistic
(Probability)
Note:
-
Malaysia
Indonesia
2.63
(0.05)*
Philippines
Korea
Thailand
1.31
(0.25)
1.38
(0.22)
0.65
(0.76)
0.39
(0.94)
-
1.25
(0.29)
0.33
(0.96)
0.82
(0.61)
1.55
(0.16)
2.88
(0.00)*
-
0.51
(0.87)
0.71
(0.70)
0.37
(0.94)
0.93
(0.51)
0.46
(0.90)
-
0.75
(0.67)
1.65
(0.13)
0.75
(0.66)
0.69
(0.72)
1.27
(0.27)
-
* ,** show 5 and 10% level of significance, respectively.
(November 17, 1997 ~ December 31, 2001)
Indonesia
F-Statistic
(Probability)
Malaysia
F-Statistic
(Probability)
Philippines
F-Statistic
(Probability)
Korea
F-Statistic
(Probability)
Thailand
F-Statistic
(Probability)
-
Malaysia
Indonesia
4.15
(1.3E-05)*
Philippines
Korea
Thailand
1.89
(0.04) *
5.12
(2.9E-07)*
4.22
(1.0E-05)*
6.48
(1.2E-09)*
-
1.34
(0.20)
7.23
(5.7E-11)*
6.12
(5.2E-09)*
1.97
(0.03) *
0.28
(0.98)
-
5.27
(1.6E-07)*
3.18
(0.00)*
6.07
(6.3E-09) *
4.88
(7.3E-07)*
4.02
(2.2E-05) *
-
3.08
(0.00)*
5.76
(2.2E-08)*
5.21
(2.0E-07)*
1.57
(0.11)
5.93
(1.1E-06)*
-
Note:
* Significant at 5% level of significance,** significant at 10% level of significance.
Source: All interest rate series are call rates or interbank rates (Philippines, Thailand) and
gathered from the Bloomberg.
９
Sogang IIAS Research Series on International Affairs Vol.3
１０
[Figure 1]
Stock Market Volatility and Regime Changes
(January 1995 ~ December 2001)
0.007
3.5
0.006
3
0.005
2.5
0.004
2
0.003
1.5
0.002
1
0.001
0.5
volitility(left)
01/29/02
07/10/01
12/08/00
06/12/00
11/11/99
05/18/99
10/15/98
04/20/98
09/26/97
03/13/97
08/23/96
02/02/96
08/02/95
0
01/19/95
0
regim e changes(right)
Note: Data for stock market analyses are gathered from 10 countries (Japan, Thailand, Singapore, Korea, Taiwan, Malaysia,
China, Indonesia, Hong Kong, US), daily stock returns from January 1995 to December 2001. Data used for analyzing bond
market volatility analyses of the five countries (Korea, Singapore, Philippines, Thailand, China) are daily data of the three-month
CD series from July 1995 to December 2001. Residuals from VAR are gathered to produce the covariance matrix using a 20 daywindow, whose norm is based on maximum singular value. Regimes are classified according to standard errors such that high
volatile regime refers to the case when norm is greater than 3, while low volatile regime shows those episodes with norm less than
1.
Source: Bloomberg.
[Figure 2] Bond Market Volatility and Regime Changes
(July 1996 ~ December 2001)
200
3.5
180
3
160
2.5
140
120
2
100
1.5
80
60
1
40
0.5
20
20011119
20010709
20010302
20001017
20000616
20000131
19991001
19990602
19990127
19980914
19980506
19971211
19970804
19970321
19961119
0
19960711
0
vo litility(left)
reg im e chang es(rig ht)
source: Bloomberg
１０
Sogang IIAS Research Series on International Affairs Vol.3
１１
In a related context, we need to distinguish the vulnerability to a crisis and the timing of a speculative
attack. While the former is largely determined by key factors such as the current account deficit and
M2/reserves, the latter is determined by the authority’s policy response and the presence of contagion. In
particular, the credibility of the government's commitment to defend the exchange rate plays a crucial role
in influencing the timing of an attack. Credibility is evaluated using the information on expected economic
growth, the size of foreign reserves, and the extent of financial contagion. Contagion, on the other hand,
comes mainly through trade and financial links: 1) devaluation by trading partners that is transmitted
through economic linkage and 2) change in the appetite for risk with no changes in economic
fundamentals, which usually is transmitted through financial linkage. Kaminksy and Reinhart (1999)
propose four channels through which contagion takes place and the proposed EWS utilizes their
classification.
3. Basic Building Blocks of the EWS
In this section, we explore to analyze the relationship between the currency crisis and market
fundamentals based on a few important variables, such as the exchange rate, interest rate, and foreign
reserves, without referring to the chronology of a crisis. For this purpose, the crisis index is defined and
variables for market fundamentals are explained. In designing an early warning system, it is important to
decide on a target variable and a set of leading indicators, with explicit reference to the role of contagion
variables.
3.1. Crisis index
In order to study the cause of the currency crisis, we need to define it accordingly. Existing literature
is divided into two strands in terms of defining the crisis. First, a chronological examination and a
comprehensive set of standards are applied to define a crisis.7 Second, empirical definitions based on the
exchange rate, interest rate, and foreign reserves can be applied. In this study, we resort to the second
venue to define a crisis. During the crisis, it is a common practice to monitor abrupt changes in the
exchange rate associated with sudden changes in capital flow (Edwards, 1989; Frankel and Rose, 1996).
However, in the case of an aborted currency crisis, preventive measures such as the raise of interest rates
or exhausting foreign reserves to protect the exchange rate can often result in serious side effects on a
domestic economy, and Eichengreen, Rose, and Wyplosz (ERW; 1995) measure exchange market
pressures recognizing this chain of aborted episodes during the crisis. The so-called ERW index is widely
applied in empirical investigations, among which Sachs, Tornell, and Velasco (1996b) and Kaminsky,
Lizondo, and Reinhart (1997) are some of the notable examples.
In this section, the ERW index is slightly modified so that exchange market pressure is defined as the
weighted combination of the won depreciation (△e , yoy), percentage point changes in the interest rate
(△i , yoy ), and changes in foreign reserves (△R , yoy). Weights are the inverse of the standard
deviation of each variable so that volatile series do not affect exchange market pressures
disproportionately.8
8
9
See Kaminsky, Lizondo, and Reinhart (1997).
When weights are applied, conditional variance was used in place of unconditional variance for the sake of convenience. In
defining a currency crisis, Eichengreen, Rose, and Wyplosz (1995) and Kaminsky, Lizondo, and Reinhart (1997) used
conditional variance, while Sachs, Tornell, and Velasco (1996b) used unconditional variance. In chapter IV, sensitivity
analysis was performed using conditional variance.
１１
Sogang IIAS Research Series on International Affairs Vol.3
１２
Exchange market pressure (EMP) =
1

 e 
e
1

 i 
i
1

 R
R
 e : standard deviation of changes in the won/dollar exchange rate
( e )
 i : standard deviation of changes in the interest rate over the
corresponding period of the previous year ( i )
 R : standard deviation of changes in foreign reserves ( R )
When the EMP exceeds a certain threshold (   k , where k, which is a multiplicative constant that
defines a currency crisis in terms of exchange market pressure (EMP), a currency crisis occurs. In
empirical implementation, the presence of a seasonal unit root was tested using the method proposed by
Frances (1990), whose results show that unit roots in the interest rate, exchange rate, and foreign reserves
cannot be rejected. The null of  i , i  1,...,12 cannot be rejected either, so that the 12 filter can be
applied (Park and Choi 1998). With the percentage transformation of crisis factors in terms of year-onyear (yoy), the crisis index should be stationary. In this study, the monthly Korean data for the years 19892001 are used for empirical investigation. This allows us to look into the cause of the crisis, since the
exchange market pressure shot up for the first time in 1997.
Most studies use multi-country data on the crises, and the inherent limitations of this study in using
only a Korean time series data prevent us from drawing a more general conclusion. Despite this problem,
the reasons for using only Korean data are as follows. First, multi-country studies cannot escape from the
reality that the occurrence of a crisis in Korea was severely limited and the study is better dubbed as a
study on an Asian crisis rather than Korean studies. Comparison with these studies allows us to seek
similarities and differences with existing studies. Second, the evolution of a crisis can be a high-frequency
phenomenon, whereas previous multi-country studies typically use yearly data. Proper treatment of market
fundamentals in high frequency can be useful to overcome this difficulty in multi-country studies.
[Figure 3] Exchange Market Pressures
%
10
k=1.1
8
k=1.5
6
4
2
0
-2
1990.01
1991.01
1992.01
1993.01
1994.01
1995.01
1996.01
1997.01
1998.01
1999.01
2000.01
2001.01
2002.01
Note: Exchange market pressure is measured by a linear combination of the change in the won/dollar exchange
１２
Sogang IIAS Research Series on International Affairs Vol.3
１３
rate (yoy), changes in corporate bond yields (yoy), (negative) changes in reserves (tot), with weights determined by
the inverse of the standard deviation of each variable. And k stands for multiplicative constant that determines the
threshold level of EMP for currency crisis.
Source: BOK
[Figure3] shows the changes in pressure in the exchange market, which began to increase in 1996 and
posted a sharp upturn in early 1997. The trend is roughly in line with the contemporary public recognition
of the probability of a crisis. Excluding 1997, the end of 1990 also posted an increased level of exchange
market pressure. After a sizable current account surplus during 1986-89, Korea experienced a sharp
turnaround in the current account to a deficit, and interest rates started to climb as a result of an increase in
market pressure. Clearly, the level of exchange market pressure in 1990 is only half of that of 1997, yet it
is interesting to observe that the regime shift took place after the brief span of favorable external
conditions came to an end in 1990.
3.2. Economic Fundamentals and Contagion
The proposed EWS in this study is constructed to predict the target variable (crisis index) with
reasonable accuracy. We try to use a measure of economic vulnerability to better explain the crisis index.
To construct a composite index for vulnerability, we need to incorporate these channels in addition to
variables related with economic fundamentals. Since the financial sector is largely blamed for the causes
of crisis, financial variables were subject to closer scrutiny, in addition to real and external variables. Even
though a sizable set of candidate variables for explaining the currency crisis is reported, the variables were
finally selected for consideration in view of the availability of data and predictability. Previous studies
based on the nonparametric criterion (Park and Choi (1998)) served as a benchmark in addition to the
results of various studies. Among key variables, the real appreciation of local currency vis-a-vis the U.S.
dollar, domestic credit/GDP, M2/reserve, and Standard & Poor's credit ratings all turned out to be
statistically significant. As the theory suggests, an expansion in domestic credit and M2/reserve and a
reduction in foreign reserves result in an increase in the upward pressure on local currency. Also, if the lag
effects of overvalued currency are taken into account, the appreciation of the real exchange rate is seen to
increase the probability of a crisis. Since the sole use of Korean data cannot avoid the fundamental
problem that arises due to the lack of crisis episodes, it is important to draw inferences from other findings.
According to Sachs, Tornell, and Velasco (1996b), whose panel study results were based on seven Asian
nations and 20 crisis countries, identical results were obtained among 10 candidate variables, underscoring
the importance of the real exchange rate and domestic credit/GDP and M2/reserve.
Further, we need to investigate the link between exchange market pressure and contagion related
variables. Building on earlier works on an early warning system for Korea (2001), this study considers
possible contagion channels from Asian countries. The current task is how one incorporates the emerging
channel of contagion into EWS. Specifically, we define the contagion index based on a set of vulnerability
index with weights defined as the inverse of the noise/signal ratio. And, the contagion effect is
incorporated into the model along four separate channels: bank cluster, high-correlation cluster, third-party
cluster, and bilateral trade cluster.
If a currency crisis is due to self-fulfilling expectations, the relationship between the crisis index and
market fundamentals could change during a crisis, possibly taking on a nonlinear relationship. A nonlinear
relationship between market fundamentals and a crisis could be even clearer in cross-country data due to
the contagion effect. For example, the sensitivity of the crisis index to market fundamentals could increase
when market fundamentals are weak, while the converse is true when market fundamentals remain solid.
In this study, the contagion effect cannot be refuted properly due to data limitations, yet we can perform a
１３
Sogang IIAS Research Series on International Affairs Vol.3
１４
check on self-fulfilling expectations by dividing a sample into crisis/non-crisis zones based on the
vulnerability index. In a related context, it needs to be noted that the traditional method of checking out
the role of self-fulfilling expectations did not turn out with any significant results (Park and Choi). Even
with the methodological limitations of dummy variable testing, a similar study by Masson (1998) also
points out the lack of evidence for self-fulfilling characteristics of currency crises in this region. However,
as shown in the subsequent chapters, the proposed EWS incorporates the nonlinear feature of crisis
dynamics as the relationship between the level of vulnerability and the reliability of warning signal clearly
shows.
In addition to the role of economic fundamentals, the role of contagion becomes important in crisis
dynamics. As discussed, the first type of contagion is due to economic interdependence and mainly affects
economic fundamentals of another country. A typical example would be a competitive devaluation, often
called fundamentals-based contagion effect. While Masson(1996) distinguishes “contagion” from
“spillovers” that are based on market fundamentals in one way or another. Contagion in this sense is
related with changes in market sentiments or revaluation of market fundamentals. Self-fulfilling
expectations are activated in multiple equilibrium situations, but this is related to some changes in market
fundamentals. So, technically, even the second type of pure contagion is not entirely devoid of any
changes in market fundamentals. And contagion channels became diverse as well as unstable recently via
the foreign exchange market, stock market, and common lender. It can be transmitted via first or second
moment (Kaminsky and Schmukler 1999, Yoo and Kim 1998).
Among different channels of contagion, the trade link is still important even with the fact that trade
among Asian nations are limited. The previous EMS crisis shows that this link is real (Eichengreen et. al
1996, Glick and Rose 1998, Gerlach and Smets 1995). Due to the existence of time lags observed in a
contagion, a trade link remains a viable factor in explaining contagions that were detected in previous
episodes of crises. The third party link is even more appealing to Asian nations because most countries in
this region rely on US export for their growth, and competitive devaluation usually activates this channel.
In addition, the common creditor emerges as an important factor for contagion. A liquidity shortage
by international investors can incite massive sales of assets in another country. When an international
investor happens to be a large commercial bank, bank-dependent countries are bound to suffer the hit
(Kaminsky and Reinhart 1998). The strength of contagion depends on trade links, especially the region’s
disproportionate dependence on the US market and equally heavier dependence on Japanese banks. The
choice of exchange rate regime would also affect the degree of contagion. Preliminary studies find that a
less flexible form of exchange rate better insulates the contagion effect in the short run. Other factors
considered important for contagion were not found significant (Song 2000). A common lender problem is
especially acute since its impact is transmitted gradually over time, but remain the most persuasive factor
for the Thai crisis in 1997(Song 2000).
4. Designing the Early Warning System
The methodology that was applied to developing an EWS largely draws on the leading indicator
approach commonly found in business cycle literature. Since the previous results largely confirm the
validity of constructing an EWS for a currency crisis in Korea, a signal approach was adopted to select
variables for leading indicators with a lead-time horizon of 6 to 24 months. While previous studies only
report results on identifying leading indicators (KLR 1997), this study explicitly considers policymakers’
perspectives. It helps them evaluate the vulnerability of an economy to a currency crisis at time t and then
makes projections on the economy’s likely path in the future using a set of leading indices and probability
measurements.
Our model draws on past theoretical and empirical works on currency crashes and extends previous
studies (e.g., Rose 1998) on panel data toward creating a practical signaling device on a monthly basis.
１４
Sogang IIAS Research Series on International Affairs Vol.3
１５
Our objective is to study past crashes that occurred under circumstances not much different from today’s
world of high capital mobility and low capital controls. The target variable for the early warning system is
the probability of a currency crisis in terms of exchange market pressure. This new EWS allows us to
determine the critical point to take necessary policy measures. In fact, in addition to the fundamental
vulnerability to a currency crisis determined by slowly evolving macroeconomic variables, high frequency
monitoring is critical in evaluating foreign investors’ confidence levels. Besides trade dependency,
quantitative measures of the currency crash contagion include a loss of investor confidence and weak
fundamentals.
4.1. Composite index of vulnerability
a. Variable Selection
In constructing a monthly early warning system, external debt Figures (stock variables) tend to lag
behind the business cycle and do not qualify as a leading indicator. Also, maturity mismatches and the
evolution of the rollover ratio of short-term debt could not be included among candidate variables due to
the limited availability of data (i.e. few historical data points). Selecting candidate variables is the crucial
step in formulating the current EWS. The selection procedure involves three steps. First, we select
candidate variables among those discussed in previous literature that are timely, representative, and
economically significant. Selected variables are put into the composite index for vulnerability to check the
level of exposure to a sudden increase in exchange market pressure. All together 35 variables were
selected to construct the composite index for vulnerability. Second, we apply a signals approach to the
first set of variables in order to construct a leading index that enjoys both a low noise-signal ratio and
longer lead time. This set of variables is also utilized in generating probability measures in the standard
probit regression.
b. Component Series of the Vulnerability Index
The following component series are combined to produce the composite vulnerability index (CVI) =
X
1 n
( ) i  i , where n= number of component series, X i = individual component series and  i =
n i 1
i
standard deviation of individual indicators,  i = 1 when the threshold value is set at the upper limit and
–1 when threshold values are set at the lower limit. The CVI primarily measures the extent to which a
country is susceptible to possible speculative attack, even though the timing of such an attack cannot be
exactly pinned down. However, the vulnerability index is a useful device in monitoring changes in the
overall risk level and in tracking down risk factors in sectoral categories. It also serves as an information
set, whose fluctuations are partly prompted by autonomous changes in control or weakly exogenous
variables. [Table 7] lists selected variables to be used for constructing CVI of EWS. Using the formula of
CVI, we have monthly CVI as shown in [Figure5].
It needs to include the contagion effect based on contagion vulnerability indices. Weights depend on
Kaminsky and Reinhart (1999), depending on their signaling performance, and inverse of N/S can be
utilized. Before constructing a new index, make sure that divisional indices are properly constructed. For
example, the real sector index is comprised of several individual indicators with appropriate N/S ratio
gathered from signaling analysis. After constructing divisional or sectoral indices, real, external, financial,
and a newly added contagion (which again comprises bank cluster, high correlation cluster, third party
cluster, bilateral trade cluster with appropriate weights), a composite contagion vulnerability index can be
constructed. As predicted, relative weights of sectoral indices show that financial and contagion variables
play more visible role in the case of Korean crisis. This index can further be used to generate probability
forecasts of a crisis, e.g.probit model. Given four channels for contagion, relative weights are determined
１５
Sogang IIAS Research Series on International Affairs Vol.3
１６
according to the activation pattern of contagion channel with weights set by the inverse of the noise-signal
ratio of each channel. The overall weight given to the contagion channel differs depending on the number
of activated channel within the contagion category (Table8).
[Table 5] Warning Signals of Individual Indicators
Indicators
1
2
3
4
5
2001
6 7
8
9
10 11 12
Industrial production
Inventory/Shipment
KOSPI
Real
Dishonored bill ratio
Service/Commodity price
Average operating ratio
Unemployment ratio+inflation
Terms of trade
Foreign reserves
Interest rate differential
Capital account/GDP
External
Current account/GDP
Real effective exchange rate
Exports growth rate
Concentration of exports
Depreciation of Asian currency
１６
Sogang IIAS Research Series on International Affairs Vol.3
１７
S&P rating
Total external liabilities/Total export
ratio
Stock price (financial sector)
Commercial bank foreign liabilities
/foreign liabilities
Demand deposit
Lending in foreign currency
Commercial banks lending
/industrial production
Commercial
bank
net
liabilities
Domestic credit/GDP
Financial
foreign
M2 multiplier
M2/foreign reserves
Monetary
institutions
foreign
liabilities
/total liabilities
Financial institutions foreign liabilities
/foreign reserves
Excess money supply
Bank Cluster
Contagion
Note:
High-Correlation Cluster
Third-Party Trade Cluster
Bilateral Trade Cluster
Shaded areas show that a warning signal based on a threshold level (   k ) has been issued.
4.2. Leading Index and Probability Measures
As briefly mentioned, the leading index allows us to predict future developments of the vulnerability
index developed in the previous section. Instead of keeping track of all the variables that comprise the
vulnerability index, a subset of variables turned out to be useful in evaluating the likelihood of a currency
crisis in the future. As explained in detail by Park and Choi (1998a, 1998b), a signals approach was
applied to select candidate variables for the composite leading index or division indices that are subsets of
the composite leading index. It turned out that most variables that were selected in KLR (1997) were also
useful in predicting future crisis in Korea. Also, the composite leading index enjoys a very low
noise/signal ratio and a long lead time compared with individual variables, justifying the use of a
composite leading index for predicting a currency crisis. The selection of variables based on the signals
approach undergoes the usual scrutiny check of varying the threshold level(k) of exchange market
pressure and the time horizon for prediction.
[Figure 4] Leading Indicators for Currency Crisis
１７
Sogang IIAS Research Series on International Affairs Vol.3
１８
3.0
2.5
2.0
1.5
1.0
0.5
0.0
-0.5
-1.0
-1.5
-2.0
1990.4
1991.7
1992.10
k=1.1 24m o n th
1994.1
1995.4
k=1.5 24m o n th
1996.7
1997.10
k=1.1 12m o n th
1999.1
2000.4
k=1.5 12m o n th
In addition to typical economic fundamentals, the composite index incorporates additional
information about contagion. Given the nature of contagion, the internal level of vulnerability is adjusted
to yield the proposed EWS. Also, given the level of the vulnerability index, it should be noted that the
noise/signal ratio changes in a nonlinear manner, highlighting the difficulty of detecting the early signs of
a crisis when vulnerability remains relatively low. This describes the nature of currency crises in recent
episodes, showing that even a low level of vulnerability is not a sure bet against a currency crisis.
[Table 6] Component series of composite vulnerability index of EWS
Real Sector
External Sector
Financial Sector
Terms of trade volatility, Industrial production index, Dishonored bills ratio, KOSPI,
Inventory/shipment, Average operating ratio(Manufacturing), Service price/commodity
price , Fiscal balance
Foreign exchange reserves, Capital and financial account/GDP, interest rate
differential,
Current account/GDP, Exports growth rate, Real effective exchange rate volatility,
Trade balance/total trade volume, Export concentration, Depreciation of Asian
currencies(15 countries), S&P rating
Stock price(financial), Commercial bank foreign debt/foreign assets, Lending in
foreign currency, Total loans- Industrial production, Demand deposit, Commercial
bank net foreign liabilities/total deposit, Domestic credit/GDP, M2 multiplier,
M2/foreign reserves, Excess M1 supply, Foreign liabilities of monetary
institutions/total liabilities, Foreign liabilities of financial institutions/foreign reserves
１８
Sogang IIAS Research Series on International Affairs Vol.3
１９
Bank Cluster (borrowings in foreign currency), High-Correlation Cluster (Asian
countries stock returns that show high-correlation with Korea stock returns), ThirdParty Trade Cluster (exports), Bilateral Trade Cluster (exports)
Contagion
[Table 7] Forecasting the Performance of Sectoral Indicators
(k=1.1, 24months)
Good Signals
Percentage as percentage
of Crises of Possible
Predicted Good Signals
A/(A+C)
Real
50.0
16.1
External 68.4
41.9
Financial 100
58.1
Contagion
76.9
32.3
Bad Signals as
percentage of
Possible
Good
SignalsB/(B+D)
Noise/Signal
Upper
(Adjusted)
/Lower*
[B/(B+D)]/
Bound
[A/(A+C)]
P(Crisis P(Crisis
/Signal) /Signal)
A/(A+B) -P(Crisis)
7.7
9.2
0.0
0.48
0.22
0.0
10.4
19.8
18.8
50.0
68.4
100
17.7
36.1
67.7
4.6
0.14
13.5
71.9
44.6
[Figue 5] Composite Vulnerability
450
400
350
300
250
200
150
100
50
0
1996.1
1996.1
1
1997.9
real
1998.7
external
1999.5
financial
2000.3
2001.1
contagion
2001.1
1
[Table 8] Weights of the Contagion Channels by Types
I=1
Bank Cluster(B)
7.14
High-Correlation Cluster(HC)
16.67
Third-Party Trade Cluster(TPT)
16.67
Bilateral Trade Cluster(BT)
1.32
I=2
B-HC
23.81
１９
Sogang IIAS Research Series on International Affairs Vol.3
２０
B-TPT
23.81
B-BT
8.46
HC-TPT
33.34
HC-BT
17.99
TPT-BT
17.99
I=3
B-HC-TPT
40.48
B-HC-BT
25.13
B-TPT-BT
25.13
HC-TPT-BT
34.66
I=4
B-HC-TP-BT
41.8
[Figure 6] Nonlinear Relation Between the N/S ratio and the Level of CVI
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
40
80
120
160
200
240
280
320
360
400
２０
Sogang IIAS Research Series on International Affairs Vol.3
２１
[Figure 7] Crisis Probability by Forecasting Horizon
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
1996.1
1996.11
1997.9
C R IP
1998.7
1999.5
C R I6
2000.3
2001.1
C R I12
5. The Impact of Foreign Shock on the Korean economy
Even with seemingly stable economic trends, the potential shocks from Japan can hardly be ignored.
It is important to assess the extent of the damage in view of the vulnerability and the potential sources of
disturbance. For instance, asset deflation can further affect Japanese banks’ asset quality and would
contribute to the worsening situation in the region. Depending on Korea’s similarity to Japan’s industrial
structure, Korea can face great exposure to Japanese problems when the banking problem continues to
depress the Japanese economy. In contrast to the previous episode when Japanese banks retrenched from
Korea just before the crisis, a situation can evolve along trade links through which Korea faces a reduced
demand from abroad. An inflationary policy cannot persist and would result in debt-deflation at a later
stage when the bubble finally collapses. So the Japanese problem may not lead to Korean banking
problems per se, but can contribute to a significant time lag. Even though banks would not be the
immediate trigger of a financial contagion, their actions would contribute to spillovers, making the
situation more severe than otherwise. Is there any evidence of a greater dependence on external shocks?
The possibility of contagion by increased interdependence other than the previously mentioned
contagion channels can be further examined by examining the causal patterns among Asian nations in
interests, exchange rates, and stock returns. The Wake-up call argument applies when investor recognition
changes abruptly and stronger scrutiny applies in this region as reflected in the market information. As
shown in chapter II, Korea is subject to shocks in other countries with increasing signs of interdependence
via exchange rate and interest rate changes within the region.
Korea’s exposure to the interest rate risk is increasing at a rapid speed with increasing bank credit in
the household sector. Increased household debt is intimately linked with asset price movements and the
chance of asset price adjustment in connection with various external and internal factors is increasing.
Problems can be serious since the household is less likely to have risk management capabilities when
dealing with volatile asset price movements. Banks relegate the burden of enhancing risk management to
the households who assume the role without proper protection.
While the need for better risk management increases, the exposure to various shocks that can
destabilize the asset market increases drastically. Notably, the increased role of contagion in bringing
about a risky situation became more pronounced as recent episodes clearly demonstrate. Simply, the
increased debt burden of the household sector needs to be scrutinized in light of its risk management
２１
Sogang IIAS Research Series on International Affairs Vol.3
２２
capability, which seems rather fragile, given the nature of shocks and the increased exposure to such risks.
As the financial vulnerability index indicates, an increased debt burden retards the household as well as
the banking sector capability of coping with various shocks. Unless domestic factors remain under prudent
regulations, even smaller shocks can significantly destabilize the situation.
As shown in the following table, Korea is more likely to experience fallouts in the trade linkage as
the exposure to Japanese banks reduced significantly in the wake of the financial crisis in 1997-98.
However, this does not mean that Korea’s economy is less exposed to Japanese woes since the mostly
likely adjustment channel would be exchange rate changes and asset market channels.
[Figure 8 ] Japanese NPL Situation 1)
(u n it: a b illio n y e n )
40
33.9
35
29.8
30
30.37
29.6
32.5
31.8
35.8 36.8
33.7
25
20
15
10
5
0
1997
1998
1999
R is k m a n a g e m e n t lo a n s
Note :
Source :
2000
2001.9
Lo a n s u n d e r fin a n c ia l re c o n s tru c tio n la w
1) Based on the fiscal year from April to March of the following year.
Financial Supervisory Agency (FSA).
[Figure 9] Foreign Position of Japanese Bank and Lending to Korean Banks
(a m illion dollar)
(% )
450000
60
400000
50
350000
40
300000
30
250000
20
200000
10
150000
0
100000
-10
50000
-20
0
-30
`90
`91
`92
`93
`94
L e n d i n g to K o r e a n b a n k s
`95
`96
`97
`98
`99
`00
F o r e i g n p o s i ti o n o f J a p a n e s e b a n k s
２２
Sogang IIAS Research Series on International Affairs Vol.3
２３
Source: BIS.
[Table
9]
Japanese Corporate Failures
(Unit : Billion Yen)
1998
1999
2000
2001
Numberof Bankruptcies
18,988
15,352
18,769
19,164
Liabilities
13,748.3
13,621.4
23,885.0
16,519.5
Note: Firms with liabilities over 10 million yen.
Source: TRS.
Empirical studies show the impact of housing prices and interest rate shocks on the real
economy. It turns out that the Japanese factor significantly affects the pattern of consumption and
household debt, especially that of asset price shock (Choi et.al.2002). Credit market frictions can also
worsen significantly since balance sheet conditions that underscore the current exposure to external shocks
have increased significantly. Asset price shock can paralyze bank lending in an abrupt manner. Empirically,
interest rate shock is hard to capture since Japanese interest rate is already suffering from a liquidity trap.
Instead of using changes in bank credit, stock price changes are used as a proxy to simulate external shock
that impinges on the Korean economy. The KOSPI’s sensitivity declined noticeably during recent episodes
against the Japanese stock market crash. KOSPI’s resiliency is due to the abundant supply of credit
through the banking sector that helps ease the credit frictions and accelerates the recovery by supporting
consumption. However, the Japanese shock can still trigger a massive downturn in consumption via a
decline in asset price and a shortage of foreign demand through various contagion channels.
[Table 10]
KOSPI Responses to Major NIKKEI Declines
Periods of major Nikkei decline ‘92. 4
‘93. 11
‘97. 1
‘00. 5
‘01. 9
Average
One-month cumulative change
-1.7
of KOSPI
7.2
-0.2
2.2
8.0
3.1
Two-month cumulative change
-4.0
of KOSPI
14.8
-2.9
-9.7
16.1
2.9
Three-month
change of KOSPI
17.6
-3.5
-10.1
29.3
5.6
cumulative
-5.3
Note : Episodes of major Nikkei decline over 10% (changes from previous month).
Source: Bloomberg
Under the current setting, increased interest rate risk is smaller than an asset price shock triggered by
an increase in the interest rate. The Japanese financial crisis can be transmitted to the entire region through
increased corporate failures and asset deflation as an increase in the interest rate is likely. Similarities in
exports between the Japanese and Korean economies expose Korea to Japanese shocks since an exchange
rate shock is the mostly likely venue for absorbing stresses associated with the increased NPL. Further, a
common lender problem would trigger the further adjustment of banks in other regions, resulting in a
２３
Sogang IIAS Research Series on International Affairs Vol.3
２４
serious portfolio adjustment burden. A common lender is likely to exercise a significant effect on
contagion with some time lags, even though the immediate impact is rather hard to assess. If the common
lender phenomenon continues to exercise its lingering effect on contagion, it will sustain its impact over
time.
[Figure 10] Bank Lending to Korea by Region
(a million dollar)
45000
4000
0
3500
0
3000
0
2500
0
2000
0
1500
0
1000
0500
0 0
1986
Q2
1987
Q4
1990
Q4
1989
Q2
Europe
1992
Q2
1993
Q4
1995
Q2
1996
Q4
UNITED
1998
Q2
1999
Q4
2001
Q2
JAPAN
STATES
Note : Consolidated Foreign Claims of Reporting Banks on Individual countries
Source: BIS.
[Figure 11]
Common Lender Effect to Japan and Korea
0. 75
0. 7
0. 65
0. 6
0. 55
0. 5
0. 45
0. 4
0. 35
0. 3
98
99
00
01
As borrowing patterns from advanced countries become more identical, the common lender problem
becomes more serious. Typically, domestic firms’ exposure to external shocks is greater in the short run in
comparison with financial institutions. The lingering effect associated with the common lender problem
２４
Sogang IIAS Research Series on International Affairs Vol.3
２５
would surface with a time lag. For instance, when several countries borrow from a common lender,
contagion is more likely among bank-dependent countries.
[Figure 12] Trade Link (Direct and Indirect) between Japan and Korea 1)
0.39
0.37
0.35
0.33
0.31
0.29
0.27
0.25
98
99
00
01
Note : Based on Glick and Rose (1998).
[Figure 13] Yen/Dollar and Exports
%
0.5
0.4
0.3
0.2
0.1
0
-0.1
-0.2
-0.3
95
96
97
E xp o rts
98
g ro w th ra te
99
00
01
Y e n /D o lla r c h a n g e ra te
Source: Bloomberg
The prevailing conditions and constraints underscore the possibility of a significant shockwave from
the Japanese banking sector, even though its contagion channel to other Asian nations would be different
２５
Sogang IIAS Research Series on International Affairs Vol.3
２６
than the previous one. Amid situations in which exchange rates and interest rates among Asian economies
have increased significantly in the wake of the financial crisis, and no discernible changes in trade and
financial linkage, a more synchronized business cycle pattern is likely to emerge through complex
interplays of contagion and vulnerability. Even though Korea reduced its exposure to the Japanese Yen,
the deterioration of the current account remains a threat to the viability of the Korean economy through its
dampening effect on intra-trade.
6. Summary and Conclusion
This paper has evolved from the previous version of EWS (1999) in considering the contagion
vulnerability explicitly to better monitor a crisis prone situation. When domestic vulnerability and
contagion are taken into account, we can better assess the probability of a crisis in this fast changing
environment. The validity of an improved EWS hinges on the reliability of the measures on the
vulnerability of an economy to various shocks, most notably “fundamentals -based contagion.”
The possibility of contagion is measured by four channels and incorporated into the composite
vulnerability index with other economic fundamentals. In this manner, it is feasible to gauge the
possibility that an economy undergoes significant adjustment pressure on the exchange rate. The proposed
early warning system for a currency crisis consists of three parts. Using a signal approach, the set of
leading indicators proved to be useful in predicting previous episodes of a currency crisis in Korea.
Second, a composite indicator approach was particularly effective in assessing the current level of
vulnerability to the currency crisis, as well as providing useful information on the likelihood of unusual
movements in exchange market pressures in the future. Accordingly, a set of composite leading indices
with a low noise-signal ratio is expected to retain predictive power if proper changes are made in
accordance with rapidly changing market trends. Third, the possibility of contagion is given significant
attention. Most notably, we measure the vulnerability against Japanese shock by considering four
contagion channels. It turned out that contagion is a salient feature of today’s transmission channel and the
level of vulnerability determines the probability of crisis in a nonlinear fashion. An EWS in Asia region
needs to consider this feature of complex contagion channels to retain its predictive power.
For now, Japanese banks cannot be a direct cause of contagion, however, the expected linkage will be
more indirect, complex, and gradual. The results of this study show that a newly constructed EWS should
be able to pick up warning signals with improved accuracy. When Japan is in trouble, its related regions
are subject to serious contagion, and this fact can become even more serious when most countries in the
region compete in the US market. It is likely that shocks will be transmitted through stock and exchange
market channels to result in competitive devaluation. And contagion remains the most significant factor in
explaining synchronized business cycle within the region. Accordingly, it is important that countries in
Asia need to diversify their line of credit to avoid the common lender problem and also diversify their
trade link in various channels as well as strengthening their fundamentals.
References
Glick, R. and A. Rose, “Contagion and Trade: Why are Currency Crises Regional?” NBER Working
Paper no.6806, 1998.
Eichengreen, B., A. Rose, and C. Wyplosz, “Contagious Currency Crisis,” NBER Working Paper no.5681,
1996.
２６
Sogang IIAS Research Series on International Affairs Vol.3
２７
Gerlach, S. and F.Smets, “Contagious Speculative Attack”, European Journal of Political Economy 11, 563, 1995.
Kaminsky G. and C.Reinhart, “On Crises, Contagion and Confusion,” Mimeo., George Washington
University and University of Maryland, 1998.
Song, Chi-Young, “Causes of Contagion Effect: The Case of East Asian Financial Crises”, Korea Money
and Finance Association Papers, vol.5, no.1, 1-42, 2000.
Kaminsky G. and S.Schmukler, What Triggers Market Jitters, A Chronicle of Asian Crisis, Mimeo,
World Bank 1999.
Baig, T. and I.Goldfajn, Financial Market Contagion in the Asian Crisis, IMF Staff Papers 46. no.2, 1999.
Yoo, J.S and M.J. Kim, Contagion and Reverse Contagion:The Case of the Korean Financial Crisis,
Journal of Economic Research 3, 21-40, 1998.
Calvo, G.A., and E.G. Mendoza, 1996, “Mexico’s Balance-of-Payments Crisis: A Chronicle of a Death
Foretold,” Journal of International Economics 41, pp.235-264.
Calvo, G., M. Goldstein, and E. Hochreiter, 1996, Private Capital Flows to Emerging Markets after the
Mexican Crisis, Institute for International Economics.
Calvo, G., and C.M. Reinhart, 1996, “Capital flows to Latin America: Is there Evidence of Contagion
Effects?” in Private Capital Flows to Emerging Markets After the Mexican Crisis, eds. Calvo, G., M.
Goldstein, and E. Hochreiter, Institute of International Economics, pp.151-171.
Change. R. and A. Velasco, 1998, “The Asian Liquidity Crisis,” NBER Working Paper No. 6796.
Choi, G., 1999, “The Korean experience with financial crisis: A Chronology,” Financial Research
Papers 99-06. Korea Institute of Finance.
Choi, G. et. al., 2002, “The Current Household Debt Situation and Its Policy Implications,” Policy
Seminar Paper, Korea Institute of Finance.
Cole, H., and T.J. Kehoe, 1996, “Self-fulfilling Debt Crisis,” Federal Reserve Bank of Minneapolis. Staff
Report 210.
Corsetti, G., P. Pesenti, and N. Roubini, 1998a, “Paper Tigers” A Model of the Asian Crisis,” NBER
Working Paper No. 6783, November.
Corsetti, G., P. Pesenti, and N. Roubini, 1998b, “What Caused the Asian Currency and Financial Crisis,”
NBER Working Paper No. 6834, December.
Edwards, S., 1989, Real Exchange Rates, Devaluation, and Adjustment: Exchange Rate Policy in
Developing Countries. MIT Press.
Eichengreen, B., A. Rose, and C. Wyplosz, 1996, “Contagious Currency Crises,” NBER Working Paper
No. 5681, July.
Eichengreen, B., A. Rose, and C. Wyplosz, 1995, “Exchange Market Mayhem: the Antecedents and
Aftermath of Speculative Attacks.” Economic Policy,Vol. 21, pp. 249-312.
Fischer, S., 1998, “The IMF and the Asian Crisis.” Forum Fund Lecture at UCLA, Los Angeles, March.
Frances, P.H., Periodicity and Stochastic Trends in Economic Time Series, Oxford University Press,
Oxford. 1996.
Frankel, J., and A. Rose, 1996, “Currency Crashes in Emerging Markets: an Empirical Treatment,”
International Finance Discussion Paper No. 534 (Washington: Board of Governors of the Federal Reserve).
Garber, P., 1996, “Comment.” NBER Macroeconomics Annual, pp. 403-406.
Gerlach, S., and F. Smets, 1995, “Contagious Speculative Attacks,” European Journal of Political
２７
Sogang IIAS Research Series on International Affairs Vol.3
２８
Economy 11, pp. 45-63.
Grether, D.M., and G.S. Maddala, 1982, Econometric Methods and Applications, Vol. 2, Elgar.
Kaminsky, G. and C.M.Reinhart, 1999, Bank Lending and Contagion: Evidence from the Asian Crisis,
Mimeo.
Kaminsky, G., S. Lizondo, and C.M. Reinhart, 1997, “Leading Indicators of Currency Crises,” IMF
working paper 97/79.
Kaminsky, G., and C.M. Reinhart, 1996, “The Twin Crisis: The Causes of Banking and Balance-ofPayments Crisis,” International Finance Discussion Paper No. 544. Board of Governors of the Federal
Reserve, March (also published in American Economic Review, June 1999).
Krugman, P., 1979, “A Model of Balance-of-Payments Crises,” Journal of Money, Credit, and Banking 11,
pp.311-325.
Krugman, P., 1996 “Are Currency Crises Self-fulfilling?” NBER Macroeconomics Annual, pp. 345-378.
Krugman, P., 1998, “What Happened to Asia?” web home page.
Krugman, P., 1999, “Balance Sheets, the Transfer Problem, and Financial Crises.” web home page. 1999.
Maddala, G.S., and I. Kim, 1998, Unit Roots, Cointegration and Structural Change, Cambridge Univ.
Press.
Masson, P., 1998, “Contagion: Monsoonal Effects, Spillovers, and Jumps between Multiple Equilibria,”
IMF Working Paper 98/142.
Obstfeld, M., 1994, “The Logic of Currency Crises,” NBER Working Paper No. 4640.
Park, W., and G. Choi, 1998a, “Predicting financial crisis using the signals approach (in Korean)” Korean
Econometric Review 9.
__________________, 1998b, “Causes of the Korean financial crisis and predictability ( in Korean)”
Panel Studies on the Korean Economy, vol.4, no.2.
Park, Y.C., and C. Song, 1999, “Financial Contagion in the East Asian Crisis: With Special Reference to
Korea.” manuscript.
Radelet, S., and J. Sachs, 1998, “The East Asian Financial Crisis: Diagnosis, Remedies, Prospects,”
Brookings Papers on Economic Activity 1, pp. 1-74.
Radelet, S., and J. Sachs, 1999, “What Have We Learned, So far, From the Asian Financial Crisis.”
manuscript.
Robinson, P.M., 1982, “On the Asymptotic Properties of Estimators of Models Containing Limited
Dependent Variables,” Econometrica, Vol.50, pp. 27-41.
Rose, A.K., 1998, “Constructing and Using an Early Warning System: Methodology and an Application to
Korea,” manuscript.
Sachs, J., A. Tornell, and A. Velasco, 1996a, “Financial Crises in Emerging Markets: the Lessons from
1995,” Brookings Papers on Economic Activity 1, pp.147-198.
Sachs, J., A. Tornell, and A. Velasco, 1996b, “The Mexican Peso Crisis: Sudden Death or Death
Foretold,” Journal of International Economics 41, pp. 265-283.
Salant, S., and D. Henderson, 1978, “Market Anticipation of Government Policy and the Price of Gold,”
Journal of Political Economy 86, pp. 627-648.
Shin, I., and Y. Wang, 1999, “How to Sequence Capital Market Liberalization: Lessons from the Korean
Experience,” Manuscript, December.
２８
Sogang IIAS Research Series on International Affairs Vol.3
２９
Wang, Y., 1999, “The Asian Financial Crisis and the Need for Regional Financial Cooperation,”
KIEP Working Paper No. 99-14, Korea Institute for International Economic Policy.
２９