Global COE Hi-Stat Discussion Paper Series 083

Research Unit for Statisticaland Empirical Analysis in Social Sciences (Hi-Stat)

Stability of East Asian Currencies during
the Global Financial Crisis

Hi-Stat Discussion Paper

Junko Shimizu
Eiji Ogawa

September 2009

Hi-Stat
Institute of Economic Research
Hitotsubashi University
2-1 Naka, Kunitatchi Tokyo, 186-8601 Japan
http://gcoe.ier.hit-u.ac.jp

Stability of East Asian Currencies during the Global Financial Crisis*
September, 2009
Junko Shimizu‡ (Senshu University)
Eiji Ogawa† (Hitotsubashi University)
Abstract
In this study, we investigate the movements of the nominal effective exchange rates(NEER) of East Asian currencies and the Asian Monetary Unit (AMU), which is theweighted average of East Asian currencies, during the course of the global financial
crisis. We found that the NEER were more stable in countries that adopted the currency
basket system even during the financial crisis. Comparisons made between the NEER
and a combination of the AMU and AMU Deviation Indicators show intra-regional
exchange rates among the East Asian currencies, and that there have been strong
relationships between them before and after the global financial crisis. Accordingly,
monitoring both the AMU and the AMU Deviation Indicators is effective in stabilizing
the NEER of East Asian currencies. In this respect, our findings indicate that the AMU
Deviation Indicators as well as the AMU will play a very important role in thesurveillance of the stability of intra-regional exchange rates.
Keyword: currency basket system, effective exchange rate, global financial crisis, East
Asian currencies
JEL Classification: F31, F36* This paper is a revised version of the paper presented at the Fifth Asia-Pacific Economic

Association Annual Conference at the University of California, Santa Cruz, on June 27–28,
2009. The authors are grateful to Shin-ichi Fukuda for his valuable comments.
Associate Professor at the School of Commerce, Senshu University
E-mail: jshimizu@isc.senshu-u.ac.jp†
Professor at the Graduate School of Commerce and Management, Hitotsubashi University
E-mail: ogawa.eiji@srv.cc.hit-u.ac.jp‡

1. Introduction
The global financial crisis that started in the United States in the summer of 2007
has had a great impact on domestic as well as Asian economies. The crisis also raised
the possibility of growing production networks in East Asia undergoing large-scale
restructuring. Large currency fluctuations, not only against the US dollar but also
against currencies of neighboring countries, are undesirable for Asian countries. It isessential to transition into a system that stabilizes intra-regional exchange rates within
Asia while allowing those values to fluctuate against the US dollar and the euro in orderto determine the economic impact of exchange rate fluctuations on intra-regional trade.
In this paper, we present a report of our investigation on the movements of nominal
exchange rates, nominal effective exchange rates (NEER) of East Asian countries, and
the Asian Monetary Unit (AMU), which is the weighted average of Asian currencies, as
proposed by Ogawa and Shimizu (2005), during the course of the recent global financial
crisis. We focus on analyzing the differences among these three kinds of exchange rate
data in order to determine what kind of currency regime is desirable to stabilize the
NEER for each of the East Asian currencies affected by the financial crisis. In addition,
we investigate the relationships among the NEER, the AMU, and the AMU Deviation
Indicators for each of the East Asian countries, which have been studied by Ogawa andShimizu (2005).
The AMU is the weighted average of East Asian currencies while the AMU
Deviation Indicators show how much each of the East Asian currencies deviates from abenchmark rate in terms of the AMU. Both the AMU and the AMU Deviation Indicators
are considered measurements for surveillance under the Chiang Mai Initiative andcoordinated exchange rate policies of East Asian countries. If the movements of the2

AMU Deviation Indicators for each of the East Asian currencies are strongly related totheir NEER, monitoring the indicators and keeping them within a certain band isconsidered to be an effective exchange rate policy for the region. Ogawa and Shimizu(2006) have already investigated the relationships among the NEER, the AMU, and theAMU Deviation Indicators. In this paper, we extend the sample period to include theperiod of the global financial crisis in order to conduct the same analysis to determine
possible changes in the relationships among these three factors.
The rest of the paper is organized as follows: Section 2 contains an overview ofprevious research on desirable currency regimes in East Asian countries; Section 3
investigates Asian currency movements during the global financial crisis; Section 4
focuses on the volatilities of the NEER of each of the East Asian currencies, so as tocompare the relationships between their weights of the effective exchange rates in East
Asian countries and their currency regimes; Section 5 investigates the relationships
among the NEER, AMU, and AMU Deviation Indicators for each of the East Asiancurrencies; Section 6 describes how to use the AMU Deviation Indicators to promote
regional exchange rate coordination; and Section 7 summarizes the results and presents
a conclusion.

2. What is a desirable currency regime for East Asia?
Although the Asian currency crisis of 1997 taught us the important lesson that thede facto dollar peg is dangerous for East Asian countries, the monetary authorities ofthese countries still tend to choose this system rather than the currency basket peg
system. As McKinnon (2000) and Ogawa (2002, 2008) pointed out, the link of East3

Asian countries with the US dollar has continued even after the Chinese currency
regime reform of July 2005.1 Ogawa (2008) presented empirical results showing thatthe monetary authority of China continues to stabilize the Chinese yuan against the US
dollar despite making announcements of adopting a managed floating exchange rate
system with reference to a currency basket, while links between the home currency anda currency basket are found in some East Asian countries. Such a coordination failure
regarding exchange rate policies among the authorities of the East Asian countries canincrease the volatility and misalignments of the intra-regional exchange rates of theircurrencies.
With the growing dependency of intra-regional trade in East Asian countries, whatis essentially needed is a currency system that reduces exchange rate risks ininternational trade and investments within the region. One way to achieve this is tocreate a common currency basket through the joint efforts of the monetary authorities of
all East Asian countries. Ogawa and Shimizu (2005) proposed the AMU as the weighted
average of thirteen East Asian currencies (the ASEAN countries along with China,
Japan, and South Korea) and developed AMU Deviation Indicators for a surveillance
process under the Chiang Mai Initiative. The AMU Deviation Indicators are used as abenchmark so that the monetary authorities of the East Asian countries can coordinate
regarding the exchange rate policies such that each of the East Asian currencies do notdeviate from the common currency basket or the AMU. In this way, the countries canachieve stability of intra-regional exchange rates with joint floating against outsidecurrencies, which include the US dollar and the euro.
Some East Asian countries such as Singapore, China, and Malaysia (from July

1

Ogawa and Ito (2000) regarded these movements as a kind of coordination failure.

4

2005), actually adopted a currency system near the BBC rule. 2 As an indicative
proposal, Ogawa and Shimizu (2007) presented a step-by-step approach to move fromthe individual currency basket system to a common currency basket system in East Asia.
Ma and McCauley (2008) also discussed that intra-Asian exchange rate stability might
be based on similar national policies of managing currencies against their respective
baskets.
On the other hand, McKinnon (2005) proposed the so-called “East Asian dollar
standard” according to which East Asian countries should coordinate their policies tokeep their exchange rates stable against the US dollar. He described the collective
macroeconomic consequences of all East Asian governments individually opting to peg
to the US dollar. According to McKinnon, East Asian countries should coordinate theirpolicies to keep their exchange rates stable against the US dollar. McKinnon and
Schnabel (2009) also suggested that China should rigidly maintain the nominal peg of
the Chinese yuan to the US dollar in order to maintain monetary and financial stability.
In a normal period, most of the Asian currencies are strongly correlated with the
US dollar and are, in other words, stable vis-à-vis the US dollar. However, incomparison, these currencies fluctuate vis-à-vis the euro and the Japanese yen.
Accordingly, their effective exchange rates are not stable. The Bank of Thailand clearlystates on their website that they aim to ensure the value of the Thai baht under thecondition of “maintaining national competitiveness, as measured through not just the
US Dollar but the nominal effective exchange rate, which includes currencies ofimportant trading partners for Thai economy.”
2

The BBC rule, where BBC stands for basket, band, and crawling, proposed by Williamson (2000),is the pegging of a currency to the central rate of a currency basket (basket) within a pre-determinedband from a central rate (band) and adjusting its central rate in order to neutralize inflationdifferential (crawling).

5After the bankruptcy of the Lehman Brothers on September 15, 2008, a number of
Asian currencies sharply depreciated vis-à-vis the US dollar, with the Japanese yen and
the Chinese yuan being notable exceptions. The monetary authorities of East Asian
countries have recognized that stability against the US dollar is no longer enough fortheir economies. They should now determine which option is more desirable for theregions⎯to stabilize their exchange rates against the US dollar or against a currency
basket. Moreover, they should also consider coordinating their exchange rate policies
with each of the other East Asian countries as a way to make progress.

3. Exchange rate movements during the global financial crisis
Let us begin by studying the latest movements in Asian currencies vis-à-vis the US
dollar. Figure 1 shows the index of Asian currencies vis-à-vis the US dollar (January
2008 = 100) from January 2008 to March 2009. Since September 2008, Asiancurrencies have been depreciating sharply against the US dollar as a result of the sell-off
of local currencies accompanying the capital outflows related to deleveraging by US
and European financial institutions. The only exception has been the Japanese yen,which has appreciated substantially against the US dollar. The Chinese yuan has stayed
relatively stable in this period due to its strong relationship with the US dollar. Evidently,
China’s monetary authority adopted a de facto dollar peg policy.The Singapore dollar
and the Malaysia ringgit have also not depreciated largely against the US dollar due totheir currency basket system. The South Korean won has had a larger depreciation thanany other Asian currency. Other Asian currencies, particularly the Thai baht, have also
lost value due to the subprime crisis and fallout from the Lehman Brothers’ bankruptcy.
6

Next, we compare the volatilities of the AMU, which is the weighted average of
East Asian currencies, and each East Asian currency vis-à-vis the US dollar, the euro,
and the Japanese yen. We calculate the standard deviation of the daily nominal
exchange rates by year. All of the exchange rates have been downloaded from
Datastream, while the AMU is available on the RIETI.3 Figure 2 shows the volatilities
of nominal exchange rates vis-à-vis the US dollar. Basically, there are large fluctuationsin floating currencies (the Japanese yen, the South Korean won, the Indonesian rupiah)and comparatively small fluctuations in de facto US dollar-pegged currencies (theChinese yuan) and currency basket-pegged currencies (the Singapore dollar). The
standard deviation of the AMU is the second lowest in 2006-2008. Most of the East
Asian currencies fluctuate more against the US dollar than the AMU, with the exceptionof the Chinese yuan.
Figure 3 shows the volatilities of nominal exchange rates vis-à-vis the euro. As awhole, the volatilities of Asian currencies vis-à-vis the euro are higher than thosevis-à-vis the US dollar. The AMU is the second lowest while the Singapore dollar was
the lowest. The fluctuation of the Malaysian ringgit is also relatively lower comparedwith other East Asian currencies. Figure 4 shows the volatilities of nominal exchange
rates vis-à-vis the Japanese yen. In this case, the AMU is the lowest relative to the East
Asian currencies while the Chinese yuan is the second lowest.
As a whole, we can summarize the above results as follows: the volatilities of theexchange rates of East Asian currencies vis-à-vis the three major currencies increased
sharply in 2008. However, there were comparatively smaller fluctuations in currency
basket-targeted currencies (the Singapore dollar and the Malaysian ringgit) especially
3

RIETI is the Research Institute of Economy, Trade, and Industries. Daily data on the AMU and theAMU Deviation Indicators is freely available on the RIETI website (http://www.rieti.go.jp/).

7vis-à-vis the euro and the Japanese yen, with the volatilities of the AMU being lower
than most of the East Asian currencies.

4. The NEER of East Asian currencies

In this section, we investigate movements in the NEER of the East Asiancurrencies. Monthly data on the NEER are downloaded from BIS (2005 = 100). Figure
5 shows the movements in the NEER of the East Asian currencies from January 2000 to
March 2009. Figure 5 tells us that the NEER of the Chinese yuan has fluctuated even
before the Chinese currency regime reform in July 2005. Since mid-2007, the NEER
started to fluctuate more widely for most of the East Asian countries. Since September
2008, the NEER of the Japanese yen and the Chinese yuan have appreciated sharply
while that of the South Korean won has depreciated dramatically.
Why did the NEER of some East Asian currencies exhibit such a volatilefluctuation during the global financial crisis? In order to answer this question, we must
begin with checking the weights on the effective exchange rates of trade-countercountries. Figure 6 shows the weights of an effective exchange rate for the East Asiancurrencies in 2005–2007, according to BIS statistics.4 As Ma and McCauley (2008)
pointed out, we find that patterns of the weights in effective exchange rates are similar
among all the East Asian currencies. Weights on the US dollar are between 12.1% inIndonesia and 21.0% in China. Weights on the euro are between 16.1% in Indonesia and24.1% in China. Weights on the East Asian currencies (the Japanese yen, the Chinese
yuan, the HK dollar, the South Korean won, the ASEAN currencies, and the Taiwanese
4

BIS revises the effective exchange rate weights every two years.

8

dollar) are between 47.1% in Japan and 68.63% in Taiwan. The weight on the East
Asian currencies is the lowest in China (40.7%) because this does not include a weighton its home currency. We also observe that the weight on the US dollar is not thehighest for all of the East Asian currencies. The weight on the euro is the highest for the
Chinese yuan. The weight on the Chinese yuan (and the HK dollar) is the highest for theJapanese yen, the South Korea won, and the Taiwanese dollar. The weight on theJapanese yen is the highest for the Thai baht, the Philippine peso, and the Hong Kong
dollar. The weight on the ASEAN currencies is the highest for the Singapore dollar, theMalaysian ringgit, and the Indonesian rupiah. These results indicate that the weights ofthe East Asian currencies are high for the East Asian currencies. It means that theireffective exchange rates might be stable if their intra-regional bilateral exchange rates
are stable against each other.
We now investigate the relationships between the weights on East Asian currencies
in terms of their effective exchange rates and the volatilities of the NEER for each of theEast Asian currencies. To do so, we plotted a scatter diagram with the extent of thevolatilities of the NEER (on a monthly basis) on the vertical axis and the effective
exchange rate weights on East Asian currencies on the horizontal axis. The volatility of
the NEER is calculated as a standard deviation of the monthly data on the NEER. We
divided the sample period into two sub-sample periods⎯a normal period from January
2000 to December 2006 and the period of the global financial crisis from January 2007
to March 2009.
Figure 7 shows the results of this analysis. In the normal period, we can find noclear relationship between the weights on the East Asian currencies in the NEER and thevolatilities of the NEER. However, during the period of the global financial crisis, the9volatilities of the NEER were smaller than 5% when the weights on the East Asiancurrencies in the NEER were approximately above 60%, with the exception of theIndonesian rupiah. Furthermore, the volatilities of the NEER were approximately above
7% when the weights on the East Asian currencies in the NEER were smaller than 55%.
This implies that when the weights on the East Asian currencies in the NEER are higher,
the volatilities of the NEER become lower. In other words, the NEER of East Asiancurrencies with high weights on the US dollar and the euro were relatively more volatile
than those of the others.
Next, we investigate how the currency regime affects the volatilities of the NEER. It
is often said that the currency regimes vary among the East Asian countries. We
compare the volatilities of the NEER in the normal period with those during the global
financial crisis and thereby investigate their relationships with the currency regimes.
Table 1 shows the current exchange rate policy of East Asian countries. Only themonetary authority of Hong Kong has adopted the hard peg system or “currency board.”
Five countries have adopted a managed floating exchange rate system while three
countries have adopted a free floating exchange rate system. However, theseclassifications only show their de jour currency regime. In order to find out their defacto currency regime, we apply the estimation methodology of Frankel and Wei (1994),
which estimates the coefficients of the implicit basket weights of each East Asiancurrency on three anchor currencies⎯the US dollar, the euro, and the Japanese yen.5
The estimated equation is as follows:

e&i / Sfr = a0 + a1 ⋅ e&USD / Sfr + a 2 ⋅ e&Euro / Sfr + a3 ⋅ e& JPY / Sfr + ε ,5Frankel and Wei (2007) confirmed that the de facto regime in China remained pegged to the dollar
throughout 2005. However, they indicated that there was a modest but steady increase in flexibility
subsequently.

10where e&i / Sfr is the rate of change in the daily exchange rate of the currency i in termsof the Swiss franc, which is a numeraire currency.6 The value e&USD / Sfr is the rate ofchange in the daily exchange rate of the US dollar in terms of the Swiss franc, e&Euro / Sfr
is the rate of change in the daily exchange rate of the euro in terms of the Swiss franc,
and e&JPY / Sfr is the rate of change in the daily exchange rate of the Japanese yen in termsof the Swiss franc.
In the above equation, the coefficients a1, a2, a3 are interpreted as weights of thethree anchor currencies in an implicit basket peg system. If these coefficients are
significantly estimated and they are positive then it means that currency i pegs to abasket of the three major currencies. If only the coefficient a1 is significantly estimatedand close to one whereas all others are not significant then it is identified that thecurrency i pegs to the US dollar. In this way, we analyzed nine East Asian currencies(the five ASEAN currencies, the Chinese yuan, the South Korean won, the Hong Kong
dollar, and the New Taiwan dollar). The sample period was from January 2007 to theend of May 2009. We estimated the above equation every six months, so a total of fivesub-sample periods were analyzed. All daily exchange rates were derived from
Datastream.
The results are presented in Table 2. We found that the Chinese yuan was still
pegged to the US dollar even after China announced its exchange rate reforms in July
2005. Its coefficients of the US dollar were 98% during the sample period, except forthe second sub-sample period (July 2007 to December 2007), and its size of adjusted
R-squared was also very high. These results indicate that the Chinese yuan has
6

When analyzing the Asian currencies, the Swiss franc is usually used as a numeraire currency.

11

continued its strong linkage with the US dollar even during the global financial crisis.
All other East Asian currencies, except for the Indonesian rupiah and the South Koreanwon, also showed a strong linkage with the US dollar with US dollar coefficients above
80% during the financial crisis. On the other hand, the Singapore dollar pegged to a
currency basket with the US dollar and the euro throughout the sample period. Except
for the Chinese yuan and the Hong Kong dollar, the other East Asian currencies pegged
to a currency basket with the US dollar and the euro in most of the sub-sample periods.
Some of the Japanese yen’s coefficients were significantly estimated; however, most ofthem were negative.
From the above results, we can see how the de facto currency regime affects thevolatilities of the NEER. Figure 8 shows the scatter diagram that indicates therelationship between the de facto currency regime and the volatilities of the NEER. The
vertical axis indicates the size of the volatilities of the NEER (on a monthly basis) while
the horizontal axis indicates the de facto currency regime arranged from a hard peg (theHong Kong dollar) to a free floating exchange rate system (the Japanese yen). Between
the Hong Kong dollar and the Japanese yen, we see the rest of the East Asian currencies
arranged by size of US dollar coefficient.
In the normal period (January 2000 to December 2006), the volatility of the NEERof the Singapore dollar was at its lowest. The volatilities of the NEER of the US
dollar-pegging countries such as Hong Kong, China, and Taiwan were higher thanSingapore. The volatilities of the NEER of the free-floating countries were higher thanthose of the other countries. During the global financial crisis (January 2007 to March2009), the volatilities of the NEER of the Japanese yen, the South Korean won(free-floating countries), and the Chinese yuan increased. It is noteworthy that the12volatility of the NEER of the Singapore dollar did not change. Additionally, thevolatilities of the NEER of the Malaysian ringgit, the Thai baht, and the New Taiwan
dollar decreased. This implies that the currency basket system could keep the NEER
stable or lower even during the global financial crisis.
Considering these results collectively, we found that the NEER of the country
whose effective exchange rate’s weights on the East Asian currencies are high (Taiwan
and Hong Kong) and that executes a currency basket system (Singapore, Malaysia,
Thailand, and Taiwan), which was stable during the global financial crisis. However,those countries whose effective exchange rate’s weight on the US dollar and the euro
are relatively high (like Japan, China, and South Korea) should adopt a currency basket
type exchange rate policy in order to stabilize their NEER.

5. The relationship between the NEER, the AMU, and the AMU Deviation
Indicators
Ogawa and Shimizu (2005) proposed the creation of an Asian Monetary Unit
(AMU) as the weighted average of all East Asian currencies and calculated AMU
Deviation Indicators that show how much each of the East Asian currencies deviatesfrom a benchmark rate in terms of the AMU. Both the AMU and the AMU Deviation
Indicators are considered to support coordinated exchange rate policies in East Asia.
Ogawa and Shimizu (2006) investigated the relationship between the NEER of the
AMU composite currencies and the AMU and AMU Deviation Indicators. If the
movements of the AMU Deviation Indicators are strongly related to their NEER,
monitoring these indicators and keeping them within a certain band is considered to be13

an effective exchange rate policy in the region. Ogawa and Shimizu (2006) used data
during the sample period from January 1999 to December 2004 and found strong
relationships between the AMU Deviation Indicators and the effective exchange rates,
except in the case of some currencies.7
In this study, we extended the sample period to include the period of the global
financial crisis and conducted the same empirical analysis. We regressed the monthly
percentage change of the NEER on the monthly percentage change of the AMU and themonthly difference of its AMU Deviation Indicator for each of the East Asian currencies
to investigate how the movement of the AMU and each AMU Deviation Indicator
explains the movement in the NEER for each of the East Asian currencies.8 We
estimated the following regression equation:

Δ(log EERi ) = α 0 + α 0 ⋅ Δ(log AMU ) + α 0 ⋅ Δ( AMUDI i )We divided the entire sample period (1/2000-3/2009) into two sub-sample periods: thenormal period (January 2000 to December 2006) and the period of the global financial
crisis (January 2007 to March 2009).
Table 3 shows the results of this analysis. Both the coefficient of the AMU and theAMU Deviation Indicators are significant and positive. The adjusted R-squared are alsohigh in both sub-sample periods. Even in the global financial crisis period, thecoefficients of the AMU and the AMU Deviation Indicators are significant and positive.
7

In Ogawa and Shimizu (2006), the coefficients of the AMU are significant and positive for theJapanese yen and the Chinese yuan, and the coefficients of the AMU Deviation Indicator are positiveand significant for the eight East Asian currencies.
8
We conducted this regression analysis not in level but in percent change because the data on
nominal effective exchange rates, the AMU, and the AMU Deviation Indicator is not stationary inlevel but is stationary in percent of change (in 1st difference for the AMU Deviation Indicator). We
transposed the data on the AMU Deviation Indicators into first difference since they are quoted interms of percent of change.
14

In China, Indonesia, Japan, and South Korea, the coefficients of the AMU Deviation
Indicators are higher during the global financial crisis than during the normal period.
These results imply that a coordinated exchange rate policy by monitoring the AMU andthe AMU Deviation Indicators would be effective to stabilize the NEER of the East
Asian currencies.

6. Coordinated exchange rate policies with the AMU and the AMU
Deviation Indicator
How can we promote coordinated exchange rate policies by using the AMU andthe AMU Deviation Indicators? Ogawa and Shimizu (2007) proposed the following
step-by-step approach to achieve regional monetary coordination:•

Step 1:¾ Policy dialogue about exchange rates and exchange rate policies¾ Surveillance using the AMU and the AMU Deviation Indicators in economic
reviews and policy dialogues•

Step 2:¾ Establishing a managed floating exchange rate system with reference to anindividual currency basket¾ Surveillance using the AMU Deviation Indicators

We have recognized that policy dialogue especially concerning coordinated exchange
rate policies in East Asian countries are needed in order to achieve regional policy
coordination. Under the current circumstances, however, it is difficult to even begin thisprocess because the governments of these countries do not agree on the coordinated15exchange rate policies. So do we need a policy consensus at all? Some East Asian
countries have already adopted the individual currency basket system, as mentioned in
the previous section. In addition, we found that the NEER of these currencies werestable even during the global financial crisis. As Ma and McCauley (2008) pointed out,
coordination is not a necessary condition to reduce intra-Asian currency volatilities; thefirst and second steps might be executed now if each of the monetary authorities are toadopt a policy that keeps their own effective exchange rates stable.
For example, we can show a coordinated exchange rate policy by using the AMU
Deviation Indicators. Figure 9 shows the movement of the AMU Deviation Indicatorsfrom January 2000 to March 2009. When we determined +/-15% as a fluctuation bandof the AMU Deviation Indicators, which is the same as the currency band of the
Exchange Rate Mechanism (ERM) under the European Monetary System (EMS) after
1992 and the ERM II, except for the Danish crone, we found that all of the East Asiancurrencies except for the Philippine peso and the Lao kip fell within the band from 2000
to mid-2005. This means that the exchange rates of the East Asian currencies were
naturally managed within the band without any coordinated exchange rate policies.
However, since 2006, the AMU Deviation Indicator of the South Korean won has
started to appreciate beyond the uppermost band level of 15%, while at the same time
the AMU Deviation Indicator of the Japanese yen has fallen below zero. The AMU
Deviation Indicators of the Thai baht and the Singapore dollar have also followed theSouth Korean won.
What motivated those currencies to deviate from the benchmark? It is found thatyen carry trades between the Japanese yen and the appreciating currencies destabilized
the AMU Deviation Indicators (Ogawa and Yoshimi (2009)). These phenomena suggest

16that coordinated monetary policies should also be considered along with coordinatedexchange rate policies. Table 4 shows the latest policy interest rate and money market
rate (for 3 months) in East Asian countries. There are still large differences between thelowest country (Japan) and the highest country (Indonesia). However, the differences
between the 3 months’ rates are reducing due to the latest global financial crisis. This isa good opportunity to discuss coordinated monetary policies as well as the coordinatedexchange rate policies.

7. Conclusion
In this study, we investigated the movement of nominal exchange rates, the NEER
of East Asian currencies, and the AMU during the recent global financial crisis. We
found that the volatilities of the exchange rates of the East Asian currencies vis-à-vis thethree major currencies increased sharply in 2008. However, there are comparatively
small fluctuations in basket-pegged currencies especially vis-à-vis the euro and theJapanese yen. Moreover, the volatilities of the AMU were mostly lower than those of
the East Asian currencies. We also found that the NEER of most of the East Asiancurrencies have started to fluctuate since 2007. Since September 2008, the NEER of theJapanese yen and the Chinese yuan have increased sharply while the NEER of the South
Korean won has depreciated dramatically. The relationship between the NEER’s
volatilities and weights on the East Asia currencies in terms of the effective exchange
rate suggests that when the weights on the East Asian currencies are higher, thevolatilities of the NEER reduce. We also found that a currency basket system could
stabilize the NEER even during a global financial crisis.

17

An analysis of the relationship between the NEER, the AMU, and the AMU
Deviation Indicator showed a strong relationship between the NEER of East Asiancurrencies and the AMU and AMU Deviation Indicators. These relationships remainedlargely unchanged during the global financial crisis. Accordingly, monitoring both the
AMU and the AMU Deviation Indicators is effective in stabilizing the NEER of the East
Asian currencies.
Under current circumstances, the individual basket system is desirable for Asian
countries. Because weights in the NEER are more or less similar among all the East
Asian currencies, a similar policy of stabilizing the home currency against their NEER
can, for a while, lead to a coordinated exchange rate policy without any consensus. In
the future, however, coordinated monetary policies should also be considered with thecoordinated exchange rate policies.
Turmoil in the U.S. financial markets is still expected to have significant impacts
on East Asian countries. Although the direct impact of the global financial crisis was
relatively small in East Asia, the region has begun experiencing significant subprime
mortgage fallout with domestic economies affected by declining exports to the UnitedStates, falling stock prices, and so forth. Sudden changes in capital flows caused by the
global financial crisis have had a large effect on foreign exchange rates as well. Under
these circumstances, it is necessary to keep a close eye on foreign exchange rate
movements. What must also be kept in mind are currency measurements in terms ofeffective exchange rates rather than focusing solely on their nominal exchange ratevis-à-vis the US dollar. In this respect, the AMU Deviation Indicators, which show
intra-regional exchange rates among the East Asian currencies, play a very important
role.

18

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Ogawa, E., and J., Shimizu, 2005, “AMU deviation indicator for coordinated exchange
rate policies in East Asia,” RIETI Discussion Paper, No.05-E-017.

Ogawa, E., and J., Shimizu, 2006a, “Stabilization of effective exchange rates undercommon currency basket systems,” Journal of the Japanese and International

Economies, vol.20, No.4, 590-611.

Ogawa, E., and J., Shimizu, 2006b, “AMU Deviation Indicators for CoordinatedExchange Rate Policies in East Asia and their Relationships with Effective Exchange
Rates,” World Economy, vol.29, Issue 12, 1691-1708.

Ogawa, E., and J., Shimizu, 2007, “Progress toward a Common Currency Basket
System in East Asia,” RIETI Discussion Paper Series, 06-E-038.

Ogawa, E., and T., Yoshimi, 2008, “Widening Deviation among East Asian Currencies,”

RIETI Discussion Paper Series, 08-E -010.

Ogawa, E., and T., Yoshimi, 2009, “Analysis on β and σ Convergences of East
Asian Currencies,” RIETI Discussion Paper Series, 09-E-018.

20

Figure 1. Changes in the Exchange Rates of Asian Currencies Against the US dollar
Changes in the exchange rates of Asian currencies against the US$

Exchange rate
（2008/1/3＝100）（Jan2008=100）

160

CHINESE YUAN

150
INDONESIANRUPIAH140

depreciation

JAPANESE YEN

130
120

SOUTH KOREAN
WON

110

MALAYSIAN
RINGGIT

100

PHILIPPINE PESO

90
SINGAPORE $80

appreciation

THAI BAHT
09
ry
-

08
r-

ua
Ja
n

m
ce

De

No

ve
m

be

be

r-

r0

08

8

8
O

ct
ob
e

r0

8

be

t0

te
m

Se
p

Au

gu
s

lyJu

-0

08

8

8
ne
Ju

ay

-0

08
M

08

ril
Ap

har
c
M

ry
-

08

08
ua

Fe

br

ar
y-

Ja
nu

Ja

nu

ar
y-

08

70

（Source：Datastream）

Figure 2. Foreign Exchange Volatilities vis-à-vis the US dollar
Foreign Exchange Volatilities vis-à-vis the US dollar(standard deviation of daily exchange rates, %)
1.80%
1.60%
1.40%
1.20%
1.00%
0.80%
0.60%
0.40%
0.20%
0.00%
AMU
China
Indonesia
Japan
South Korea
Malaysia
Philippines
Singapore
Thailand

2000
0.22%
0.00%
1.00%
0.62%
0.55%
0.00%
0.61%
0.22%
0.48%

2001
0.22%
0.00%
1.34%
0.62%
0.52%
0.01%
0.87%
0.28%
0.30%

2002
0.23%
0.00%
0.71%
0.62%
0.59%
0.02%
0.41%
0.27%
0.45%

2003
0.19%
0.00%
0.44%
0.51%
0.56%
0.03%
0.39%
0.26%
0.31%

2004
0.22%
0.00%
0.53%
0.61%
0.39%
0.02%
0.19%
0.29%
0.26%

2005
0.23%
0.13%
0.75%
0.53%
0.43%
0.15%
0.26%
0.28%
0.29%

2006
0.19%
0.07%
0.62%
0.49%
0.40%
0.39%
0.41%
0.24%
0.39%

2007
0.17%
0.10%
0.40%
0.60%
0.29%
0.29%
0.48%
0.23%
0.85%

2008
0.31%
0.14%
0.90%
1.04%
1.67%
0.44%
0.60%
0.48%
0.72%

Source: Datastream(Author’s calculations.)

21

Figure 3. Foreign Exchange Volatilities vis-à-vis the euro
Foreign Exchange Volatilities vis-à-vis the euro
(standard deviation of daily exchange rates, %)
1.60%
1.40%
1.20%
1.00%
0.80%
0.60%
0.40%
0.20%
AMU
China
Indonesia
Japan
South Korea
Malaysia
Philippines
Singapore
Thailand

2000
0.78%
0.72%
1.31%
0.97%
0.99%
0.72%
0.97%
0.74%
0.89%

2001
0.70%
0.69%
1.59%
0.82%
0.92%
0.69%
1.15%
0.70%
0.76%

2002
0.49%
0.55%
0.82%
0.63%
0.72%
0.55%
0.61%
0.52%
0.59%

2003
0.54%
0.59%
0.70%
0.62%
0.76%
0.59%
0.70%
0.53%
0.59%

2004
0.58%
0.64%
0.76%
0.68%
0.68%
0.64%
0.63%
0.53%
0.60%

2005
0.46%
0.55%
0.86%
0.50%
0.54%
0.56%
0.56%
0.46%
0.51%

2006
0.41%
0.47%
0.69%
0.47%
0.56%
0.58%
0.58%
0.42%
0.53%

2007
0.35%
0.36%
0.48%
0.66%
0.41%
0.39%
0.58%
0.33%
0.92%

2008
0.82%
0.86%
1.31%
1.29%
1.64%
0.83%
0.93%
0.70%
1.05%

Figure 4. Foreign Exchange Volatilities vis-à-vis the Japanese yen
Foreign Exchange Volatilities vis-à-vis the Japanese yen(standard deviation of daily exchange rates, %)
2.50%

2.00%

1.50%

1.00%

0.50%

0.00%
AMU
China
Indonesia
South Korea
Malaysia
Philippines
Singapore
Thailand

2000
0.43%
0.62%
1.13%
0.76%
0.62%
0.91%
0.58%
0.70%

2001
0.43%
0.62%
1.50%
0.68%
0.62%
1.02%
0.54%
0.58%

2002
0.42%
0.62%
0.90%
0.72%
0.62%
0.68%
0.47%
0.65%

2003
0.35%
0.51%
0.62%
0.67%
0.51%
0.62%
0.43%
0.48%

2004
0.40%
0.61%
0.70%
0.61%
0.61%
0.59%
0.45%
0.52%

2005
0.33%
0.51%
0.84%
0.52%
0.55%
0.52%
0.37%
0.44%

2006
0.34%
0.49%
0.75%
0.57%
0.57%
0.60%
0.37%
0.54%

2007
0.48%
0.61%
0.76%
0.68%
0.68%
0.77%
0.68%
1.06%

2008
0.84%
1.05%
1.40%
2.13%
1.14%
1.22%
1.19%
1.27%

Source : Datastream(Author’s calculations.)

22

Figure 5. The NEER of East Asian Currencies
The Nominal Effective Exchange Rates of East Asian currencies(BIS, 2005=100)(2005=100)

150

China

Indonesia

Japan

South Korea

Malaysia

Philippines

Singapore

ThailandHong Kong

Taiwan

140
130
120
110
100
90
80
70

Ja
nu
ar
ySe M 00
pt ayem 0
b 0
Ja ernu 00
arySe M 01
pt ayem 0
b 1
Ja ernu 01
arySe M 02
pt ayem 0
b 2
Ja ernu 02
arySe M 03pt ayem 0
b 3
Ja ernu 03
arySe M 04
pt ayem 0
b 4
Ja ernu 04
arySe M 05
pt ayem 0
b 5
Ja ernu 05
arySe M 06a
pt yem 0
b 6
Ja ernu 06
arySe M 07
pt ayem 0
b 7
Ja ernu 07
arySe M 08
pt ayem 0
b 8
Ja ernu 08
ar
y09

60

Source: BIS

Figure 6. BIS Effective Exchange Rate Weights (2005-2007)

Indonesia : BIS Effective Exchange rate
weights (2005-2007)

China : BIS Effective Exchange rate
weights (2005-2007)
ROW, 14.1

ROW, 10.4

US, 12.1

Taiwan, 3.0
ASEAN,
24.7
Korea, 4.9
China+HK,
11.9

EU, 17.2

Japan, 15.8

Taiwan,6.6

US, 21.0

ASEAN,
8.3
Korea, 8.2
China+HK,
Japan,
0.8
16.8

EU, 24.1

23

Figure 6 (continued)
Japan : BIS Effective Exchange rate
weights (2005-2007)

South Korea : BIS Effective Exchange
rate weights (2005-2007)
ROW, 11.9
Taiwan, 4.0

ROW, 12.1
Taiwan, 4.1

US, 20.5

ASEAN,
11.9

ASEAN,
8.3,

EU, 20.4

Korea, 6.9
China+HK,
24.2,

Singapore : BIS Effective Exchange rate
weights (2005-2007)

ASEAN,
19.6

US, 15.1

EU, 17.7

Japan,
11.9

Philippines : BIS Effective Exchange
rate weights (2005-2007)

US, 18.1

ASEAN,
14.8
EU, 16.1
Korea, 6.1
China+HK,
13.2

Malaysia : BIS Effective Exchange rate
weights (2005-2007)

Taiwan,4.6
ASEAN,
19.4

US, 18.1

EU, 16.6

China+HK,
14.4

Japan,
13.3

Thailand : BIS Effective Exchange rate
weights (2005-2007)

ROW, 10.7

ROW, 6.6
Taiwan, 5.6

Japan,
18.5

Korea, 4.9

Korea, 5.4
China+HK,
17.3

EU, 19.1

ROW, 8.7

ROW, 8.1
Taiwan,5.0

China+HK,
22.5

US, 15.8

Taiwan, 4.0
ASEAN,
14.9

US, 13.0
EU, 16.2

Korea, 4.3
Japan, 19.5

China+HK,
15.0

Japan,
21.9

24

Figure 6 (continued)
Taiwan : BIS Effective Exchange rate
weights (2005-2007)

ROW, 8.9
ASEAN,
10.4
Korea, 7.2

China+HK,
21.6

US, 15.7

Hong Kong : BIS Effective Exchange rate
weights (2005-2007)

ROW, 13.0

US, 10.9

Taiwan,4.9

EU, 13.1

ASEAN,
27.6

Japan,
13.2

EU, 15.7

Japan,
20.6

Korea, 4.9 China+HK,
12.4(Source: BIS)

25

Figure 7. NEER Volatilities and NEER Weights in Asia
NEER Vo lat ilit y an d NEER W e igh t s o n Asia
(1 / 2 0 0 0 - 1 2 / 2 0 0 6 )NEER Volatilities

14
12

Phillippines

10

Indonesia

8
Korea

6

China

Japan

Hong Kong
Malaysia
ThailandTaiwan42Singapore

0
40

45

50

55

60

65

70

NEER Weights on Asia (%)

NEER Vo lat ilit y an d NEER W e igh t s o n Asia
(1 / 2 0 0 7 - 3 / 2 0 0 9 )
16
Korea

14
NEER Volatilities

12
Japan
10
8

Indonesia
China

6
4

Phillippines
Hong Kong

Malaysia

2

ThailandSingapore

0
40

50

60

Taiwan70

NEER Weights on Asia (%)(Author’s calculations)26

Figure 8. NEER Volatilities and the De-facto Currency Regime
NEER Vo latilitie s an d Cu r r e n c y R e gime
(1 / 2 0 0 0 - 1 2 / 2 0 0 6 )
14.00
12.00

Philippines

NEER Volatiliteis

10.00

Indonesia

8.00

Korea
6.00

Japan

China

4.00

Hong Kong

Malaysia Taiwan
Thailand

2.00

Singapore

0.00

Free
0 Float2

4

6Peg
10 to US$
128

NEER Vo lat ilit ie s an d Cu r r e n c y R e gime
(1 / 2 0 0 7 - 3 / 2 0 0 9 )

16
Korea
14
12
NEER Volatilities

Japan
10
8

Indonesia
China

6
Philippines
4

Hong Kong
Malaysia

2

TaiwanSingaporeThailand
00 Float 2
Free

4

6

8

Peg10to US$12(Author’s calculations)27

Jan-00
Mar-00
May-00Jul-00
Sep-00
Nov-00
Jan-01Mar-01
May-01
Jul-01
Sep-01
Nov-01
Jan-02Mar-02
May-02
Jul-02
Sep-02
Nov-02Jan-03Mar-03May-03
Jul-0 3
Sep-03
Nov-03Jan-04Mar-04
May-04
Jul-04
Sep-04
Nov-04Jan-05Mar-05
May-0 5Jul-05
Sep-05
Nov-05Jan-06Mar-06
May-06
Jul-06
Sep-06
Nov- 06
Jan-07Mar-0 7
May-07
Jul-07Se p-0 7
Nov-07Jan -08
Mar-08May-08
Jul-08
Sep-08Nov-08Jan-09Mar-09Figure 9. AMU Deviation Indicators (Jan 2000-Mar 2009)
Figure 2. Nominal AMU Deviation Indicators(benchmark year=2000/2001,basket weight=2003-2005,daily)(%)

50
Brunei Darussalam
Japan
MyanmarVietnam
CambodiaSouth Korea
Philippines
China P.R.
LaosSingapore
Indonesia
Malaysia
Thailand

40

30

20

10

0

+/- 15%
Fluctuation
band

-10

-20

-30

-40

(Source: RIETI)

28

Table 1. Exchange Rate Policy in East Asian Countries
Exchange rate policy
Hong Kong
TaiwanCurrency Board
Managed Float (reference to a currency basket)

ChinaManaged Float (reference to a currency basket)

Malaysia
ThailandManaged Float (reference to a currency basket)
Managed Float

South Korea

Managed Float

Philippines
Indonesia
Japan

Free Float
Free Float
Free Float

Degree offluctuation
lowesthighestSource: Central Bank website

29

Table 2.
Country

China

Indonesia

Korea

Malaysia

Philippines

1/02/2007 to 6/29/2007
Variable
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
(0.0364) 0.0015(0.0192) -0.0077(0.0204) -0.0380(0.0333)C-0.0195 *** (0.0075) 0.0192
USD
0.9857 *** (0.0267) 0.7650 *** (0.1292) 0.7725 *** (0.0680) 0.8647 *** (0.0724) 0.8316 *** (0.1182)
EURO-0.0305(0.0485) 0.6350 *** (0.2343) 0.3468 *** (0.1233) 0.4590 *** (0.1312) 0.3162(0.2142)JPY-0.0213(0.0179) -0.1031(0.0865) -0.0454(0.0455) -0.0124(0.0485) -0.0401(0.0791)
Adj. R2
0.94950.42580.69470.73220.4533
7/02/2007 to 12/31/2007
Variable
Coef.
Std.dev.
Coef.
Std.dev.
C-0.0270 ** (0.0104) 0.0423(0.0328)
USD
0.9231 *** (0.0276) 0.7789 *** (0.0875)
EURO
0.0412(0.0469) 0.5280 *** (0.1486)
JPY-0.0013(0.0165) -0.0243(0.0523)
Adj. R2
0.93550.5984Singapore

ThailandHong Kong

Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
0.0040(0.0133) -0.1024(0.0741) 0.0037(0.0030)
0.7660 *** (0.0472) 1.1783 *** (0.2629) 0.9935 *** (0.0107)
0.3246 *** (0.0855) -0.5599(0.4765) -0.0202(0.0194)
0.0651 *** (0.0316) 0.2233(0.1760) -0.0091(0.0072)
0.83810.2204
0.9918

TaiwanCoef.
Std.dev.
0.0074(0.0160)
0.8935 *** (0.0567)
0.0902(0.1028)0.0113(0.0379)
0.7919Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
0.0223(0.0284) -0.0104(0.0249) -0.0788(0.0506) -0.0347(0.0195) -0.0449(0.0763) -0.0014(0.0044) -0.0069(0.0129)0.8256 *** (0.0756) 0.6483 *** (0.0663) 0.8602 *** (0.1348) 0.7723 *** (0.0520) 0.8448 *** (0.2035) 0.9933 *** (0.0116) 0.9515 *** (0.0345)
0.5694 *** (0.1285) 0.7523 *** (0.1126) 0.4425 * (0.2290) 0.3629 *** (0.0883) 0.0093(0.3457) 0.0019(0.0198) 0.0620(0.0586)
0.0450(0.0452) 0.0614(0.0396) -0.0138(0.0805) -0.1395 *** (0.0310) -0.2348 * (0.1216) 0.0001(0.0070) -0.0177(0.0206)
0.70400.72230.40480.77720.15020.98930.90801/01/2008 to 6/30/2008
Variable
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
C-0.0473 *** (0.0107) -0.0142(0.0252) 0.0809(0.0574) -0.0106(0.0471)
USD
0.9835 *** (0.0205) 0.9455 *** (0.0480) 1.0752 *** (0.1093) 0.8688 *** (0.0897)
EURO-0.0408(0.0348) 0.1145(0.0816) 0.3174 * (0.1857) 0.1483(0.1524)JPY
0.0166(0.0180) 0.0357(0.0422) -0.1829 * (0.0960) 0.1571 ** (0.0788)
Adj. R2
0.97600.88580.65550.6835

Coef.
Std.dev.
Coef.
Std.dev.
0.0524(0.0651) -0.0281(0.0244)
0.9911 *** (0.1241) 0.7705 *** (0.0465)
0.0352(0.2108) 0.2099 *** (0.0789)
0.2622 ** (0.1090) -0.0800 * (0.0408)
0.59140.8476

7/01/2008 to 12/31/2008
Variable
Coef.
Std.dev.
C-0.0078(0.0123)USD
0.9879 *** (0.0152)
EURO
0.0325(0.0204)
JPY-0.0129(0.0105)
Adj. R2
0.9824

Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
0.0125(0.0488) -0.0026(0.0414) 0.0167(0.0260) -0.0041(0.0035) 0.0413(0.0284)0.8068 *** (0.0604) 0.7524 *** (0.0512) 0.8718 *** (0.0322) 0.9914 *** (0.0044) 0.8632 *** (0.0352)
0.4580 *** (0.0809) 0.3496 *** (0.0687) 0.1447 *** (0.0431) 0.0014(0.0058) 0.1859 *** (0.0471)
0.0253(0.0415) -0.0834 ** (0.0352) -0.0005(0.0221) 0.0053 * (0.0030) -0.0133(0.0242)0.76670.76140.91330.9986
0.8965

Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
0.1389(0.1081) 0.0167(0.1839) 0.0230(0.0384)
1.1242 *** (0.1338) 0.5987 *** (0.2276) 0.8573 *** (0.0475)
0.0360(0.1793) 1.2976 *** (0.3050) 0.2116 *** (0.0637)
0.0084(0.0920) -0.2048(0.1566) -0.0203(0.0327)
0.48660.22560.8244

Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
0.0852(0.0951) 0.0006(0.0041) -0.0480(0.0260)
0.9683 *** (0.1811) 0.9864 *** (0.0078) 0.9614 *** (0.0496)
0.0103(0.3077) -0.0058(0.0133) 0.0863 *** (0.0842)
0.1919(0.1591) 0.0102 * (0.0069) -0.0410(0.0436)0.37000.99650.8738

1/01/2009 to 5/29/2009
Variable
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
Coef.
Std.dev.
C
0.0007(0.0034) -0.0621(0.0704) 0.0168(0.1266) 0.0194(0.0445) 0.0021(0.0461) 0.0133(0.0439) -0.0110(0.0242) 0.0001(0.0014) -0.0002(0.0358)
USD
0.9831 *** (0.0049) 0.8620 *** (0.0999) 0.7491 *** (0.1794) 0.8613 *** (0.0631) 0.9788 *** (0.0654) 0.8459 *** (0.0622) 0.8294 *** (0.0343) 0.9970 *** (0.0020) 0.8619 *** (0.0508)
EURO
0.0067(0.0072) 0.0098(0.1475) 0.4415 * (0.2650) 0.2767 *** (0.0931) 0.1673 * (0.0966) 0.2152 ** (0.0919) 0.1339 *** (0.0506) -0.0009(0.0030) 0.1896 ** (0.0750)
JPY
0.0011(0.0040) -0.0586(0.0813) -0.2806 * (0.1462) -0.1377 *** (0.0514) -0.1119 ** (0.0533) -0.0542(0.0507) 0.0145(0.0279) 0.0021(0.0017) -0.0749 * (0.0413)
Adj. R2
0.99870.5585
0.19800.75750.79050.77520.92350.99980.8375
Author's calculation. Autuor's calculation. Significance level: *90%, **95%, ***99%.

Table 3. Relationship between the NEER, the AMU, and the AMU Deviation Indicators
Sample period 1/2000-12/2006 obsevations 83
China
VariableC

Coef.

-0.0324

DLOG(AMU) 0.6405
D(AMUDI)
Adj. R2

Indonesia

Std.error Coef.

(0.0260) -0.0014*** (0.0366)

Japan

Std.error Coef.

0.4326(0.0542) -0.0242*** (0.0633)

South Korea

Std.error Coef.

0.5803

Std.error(0.0231) -0.0153** * (0.0304)

0.4445(0.0289)*** (0.0372)

1.4079 *** (0.0338) 1.0342 *** (0.0172) 1.1228 ** * (0.0201) 0.9843 *** (0.0249)
0.9561

0.97880.98590.9725

Sample period 1/2007-3/2009 obsevations 27
China
VariableC

Indonesia

Japan

South Korea

Coef.

Std.error Coef.

Std.error Coef.

Std.error Coef.

Std.error-0.0740(0.1270) 0.0602(0.1096) 0.0670(0.1129) 0.0816(0.0993)

DLOG(AMU) 1.1124 *** (0.1710) 0.3362 ** (0.1508) 0.5017 ** (0.2169) 0.4192 *** (0.1347)
D(AMUDI)
Adj. R2

1.5831 *** (0.1357) 1.1621 *** (0.0398) 1.2862 ** * (0.0643) 1.0979 *** (0.0324)
0.83830.9722

0.97380.9813

Autuor's calculation. Significance level: *90%, **95%, ***99%.

Sample period 1/2000-12/2006 obsevations 83
Malaysia
VariableC

Coef.

-0.0094

DLOG(AMU) 0.4783
D(AMUDI)
Adj. R2

Philippines

Std.error Coef.

(0.0183) 0.0234*** (0.0252)

0.3258Singapore

Std.error Coef.

(0.0320) -0.0089*** (0.0367)

ThailandStd.error Coef.

0.4171

Std.error(0.0207) -0.0165** * (0.0257)

0.3127(0.0333)*** (0.0392)

1.1854 *** (0.0237) 1.1390 *** (0.0224) 0.9812 ** * (0.0337) 0.9367 *** (0.0317)
0.96940.96940.91450.9151

Sample period 1/2007-3/2009 obsevations 27
Malaysia
Variable
C

Philippines

Singapore

Coef.

Std.error Coef.

Std.error Coef.

0.0525(0.0886) 0.0967(0.0819) 0.1396*

ThailandStd.error Coef.

Std.error(0.0766) -0.0427(0.1949)

DLOG(AMU) 0.4774 *** (0.1239) 0.3451 *** (0.1102) 0.3402 ** * (0.1209) 0.4911 *D(AMUDI)
Adj. R2(0.2623)

0.7914 *** (0.0836) 1.0488 *** (0.0469) 0.5515 ** * (0.0796) 0.2563 *** (0.0769)
0.77230.9507

Autuor's calculation. Significance level: *90%, **95%, ***99%.

0.64310.3133

Table 4. Policy Rate and 3-month Market Rate
Policy Rate

3 month Market Rate

China

2.25
5.31

1year Deposit Rate
1year Lending Rate

1.207

SHIBOR

Indonesia

7.25

Bank Indonesia Rate

8.22

JIBOR

Japan

0.10

Target O/N call rate

0.567

TIBOR

South Korea

2.00

BOK Base Rate

2.41

KORIBOR

Malaysia

2.00

O/N Policy Rate

2.12

KLIBOR

Philippines

4.50
6.50

BSP O/N Borrowing Rate
BSP O/N Lending Rate

3.688

PHIBOR

0.5

SIBOR

1.425

BKIBORn.a.

Singapore
Thailand

1.25

1day Repurchase Rate

Source: AsianBondOnlines (ADB), All data are as of May 2009.

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