The Predictive Power of the Term Structures of Interest Rates

The Predictive Power of the Term Structures of Interest
Rates: Evidences for the Developed and Asian Emerging
Markets
Ming-Hsiang Chen
Department of Finance
National Chung Cheng University
Kai-Li Wang 1
Department of Finance
Tunghai University, Taiwan
Meng-Feng Yen
Department of Accountancy and Graduate Institute of Finance
National Cheng Kung University, TAIWAN
Abstract:
Researchers of term structure have often suggested that yield spread contains
information about the real activities. In this paper, we examined the output-the
domestic spread and the output –the spread of U.S. relationship across five Asian
emerging countries including Korea, Malaysia, Singapore, Taiwan and Thailand.
Then, we further decomposed the spread into two effects: the pure expectation effect
and the term premium and examine their influences. From the results, we found that
the spread of United States are more important than the domestic spread in the
forecast for the future growth of economy and the spread of U.S. contain the
information of the economic growth independent to the other economic indicator
and money policy in most Asian emerging countries. The results also show that the
domestic expectation effect and term premium effect contained little information
about the economic activities and the expectation effect of United States doesn’t
have information for the economic activities as well. Conversely, the term premium
effect of United States has consistently predictive power in most Asian emerging
countries. For the spread of United States, the term premium effects are important
than the expectation effect in the forecast of economic growth.
1 Corresponding Author: Kai-Li Wang, Department of Finance, Tunghai University, Taichung 407,
Taiwan. Tel: 886-4-2359-0121 ext. 3588; Fax: 886-4-23506835; E-mail:kaiwang@thu.edu.tw.
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I. Introduction
The term structure of interest rates, i.e., the yield curve, has long been of
interest to market analyst, policy-makers and academic economists for forecasting
future economic activity. Central banks have recently been paying increasing
attention to the term structure of interest rates as a monetary policy indicator because
large evidences appear that yield curves contain information about the future path of
economic variables. Numerous authors have documented that the yield spread, the
difference in yields between long-term and short-term interest, is driven by
expectations of participants in the financial markets. As a result, the yield spread
essentially contains valuable information about future real activity that is
independent from information about current or future monetary policy.
In terms of forecasting, the fact that the term spread for forecasting future
economic activity has been well establish by Harvey (1989), who offered a sounder
theoretical structure for forecast of term spread in economic growth. They showed a
positive slope of yield curve with an increased in the expected economic condition,
and concluded that this relationship is independent of monetary policy. Estrella and
Hardouvelis (1991) used real GNP growth in United States to examine the predictive
ability of the term spread. The results show that term spread has significant
predictive power on output growth, consumption, and investment. Plosser and
Rouwenhorst (1994) found the term structure has significant predictive for economic
growth in three industrial countries. However, there is no conclusive finding that the
yield spread consistently contains information in explaining future economic activity.
For example, Plosser and Rouwenhorst(1994) found the evidence that yield spreads
contain useful information to forecast real economic activities in United States,
Canada and Germany, but not in France and UK. Harvey (1991) and Kim and
Limpaphayom (1997) examined G-7 economies and concluded that the yield spread
does not consistently contain information about future economic activity.
Hamilton and Kim (2002) addressed the theoretical model toward the nature of
the term spread. They nicely presented that the spread’s forecasting contribution
attributed to two effects: an expectation effect shows a sign of the public’s
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expectation of the future economic activities and the term premium effect represents
the risk of investments in alternative assets. They find that both factors are relevant
for predicting real GDP growth but the respective contributions differ. The
contributions are similar at short horizons but the effect of expected future short
rates is much more important than the term premium for predicting GDP more than
two years ahead. Nakaota (2005) followed Hamilton and Kim (2002) to investigate
whether the term spread has information about future economic growth in Japan.
Comprising expectation effect and term premium effect, the results show that the
expectation effect is relatively more important regarding the predictability of
economic activity.
Why does the yield spread does not consistently help forecast economic
activity On reviewing this literature, several issues arise. First, the predictive content
of the spread may not be robust in all countries, suggesting regime factors may matter
in this issue. Second, to further understand the nature of the term spread and avoid
potential aggregation bias, the benefits to decompose spread component into
expectation effect and term premium effect is substantial. Third, the advantage to
consider the information contained in foreign term spreads in explaining the future
domestic economic growth. Forth, the importance for policy and practical
participants to understand whether the nature of yield spread contain relatively more
useful information about future economic activity when compared with other
variables. These key points in charting our empirical road ahead. In this paper, we
offer a new look at the spread effect and future economic activity relationship that,
for the first time to the best of our knowledge, attends to each of these four issues
simultaneously. We describe the details as follows.
First, the relationship between the yield spread and future economic activity
may not be robust between emerging and developed countries. This topic is of
particular salience to Asian emerging countries which have experienced remarkable
economic growth over the past decades and provide a particularly rich policy
context in which interest rates markets have taken on increasing importance in these
economies. While most previous studies in this topic examine developed markets
such as USA, European markets, Canada and Australia, it is of interest to see the
3

evidence from emerging markets. In this paper, we contribute to the literature by
investigating the usefulness of term spreads on the predictive content of Asian
emerging markets. Given the different economic structures between developed and
developing countries, we attempt to answer the questions that whether there exists
regime differences between developing Asian and G7 markets for the usefulness of
term spreads in explaining the likelihood of future economics. The cross-country
variation of the information the term spread contains might be due to differences in
the regulations of different financial markets, which may cause interest rates not to
reflect accurately financial market participants’ expectations about the future course
of the economy (Kim and Limpaphayom, 1997; Bernard and Gerlach, 1998) 2 . This
paper begins with a review and comparison of the forecasting usefulness of spread
for the forecast of economic activity in Asian and G7 economies ,while additional
information, such as monetary policy (Anderson and Vahid, 2001) and oil prices
(Hamilton and Kim, 2002) are considered. In addition, to further capture of the
nature of the term structure, following Hamilton and Kim (2002), we decomposed
the empirical contribution of the term spread into a factor related to expected
changes in short-term rates and a factor related to the term premium. We intend to
differentiate which factor plays more statistically important role for predicting future
economics across the developing Asian and developed G7 markets.
Another consideration is to examine the effect of foreign yield spread on the
determination of future domestic economy. The foreign term structures might exhibit
predictive content for real economic activity in other country. Current literatures
primarily focus on the usefulness of the domestic yield spread as predictor of real
domestic economic activity; nevertheless few studies have addressed this question.
One of the contributions in the present paper, however, is to answer the question
whether the slope of foreign term structures helps predict economic growth in the
domestic economy. This topic is essential to contemporary economic policy in
middle-income economies heavily dependent on international trade. As the close
relationships between Asian countries and the U.S., any news about economic
2 Kim and Limpaphayom (1997), Bernard and Gerlach (1998) Nakaota (2005) found that the tight
regulation of Japanese financial markets weakened the explaining power of term spread for the
economic growth.
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fundamentals in the U.S. economy might contain implications for Asian markets.
Consequently, it seems natural to examine whether the changes in the U.S.
yield spread provides insights in predicting the economic growth in Asian countries.
If Asian investors recognize this styled fact, they might infer the prospect of
domestic economic activity through the foreign yield spread information from U.S.
economy. To address this potential international yield spread channel, we take a
further step toward building a understanding whether the spread of United States
generally add significant information useful for predicting future activity in Asian
and G7 economies. We provide, what we believe the first time, to decompose the
contribution of the U.S. term spread into a factor related to expected changes in
short-term rates and a factor related to the term premium, and examine their
potential effects on economic activity of Asian and G7 markets, respectively. In
particular, we compare the region difference across them. That is the topical
innovation of this paper.
In this vein, the paper represents a substantial step forward in applying
empirical modeling tools that explicitly account for information aspects of domestic
and foreign spread on economic growth. Our research contributes to the literature by
underscoring and differentiating the importance of both domestic and foreign spread
effects on future growth across developing Asian and G7 economies. Understanding
the nature of both yield spreads is critical for policymakers and market participants
with developing more informed decisions toward future economic prospective. This
will prove particularly helpful as policymakers using the term structure to conduct
monetary policy and make tactical policy decisions.
The remaining contributions of this work are organized as follows. Section II
discusses the data and presents overview of general methodological considerations.
Section III demonstrates the empirical results and discusses the region difference.
Finally, section IV concludes the main results.
II. Data and Methodology
Data
Our empirical investigation targets five newly industrialized Asian countries,
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including Korea, Singapore, Taiwan, Malaysia and Thailand 3 , which have
experienced liberalization in policies designed to facilitate cross-country investing
and international capital flows. To analyze the effect of term spread on different
economic structures, we further investigate the predictability of the yield spread on
the evidences of developed G7 markets, including United States, Canada, U.K.,
France, Germany, Italy, and Japan. One advantage of our focus on these countries is
based on their similar economic structures within each its own regime, which
provides a consistent contextual foundation for economic policy as a basis to
evaluate and compare the effect of term spread on economic activity.
A related aggregation issue concerns the frequency of the data used in
estimation. Due largely the data limitations, most studies employ lower frequency
quarterly or annual series to examine the spread and economic relationship.
However, temporal aggregation may make identifying any true term spread and
economic condition more difficult. When one uses higher frequency data, as the
literature increasingly acknowledges is preferable to better describe the dynamic
relationship and to improve the forecasting ability of relevant variables. As such, in
order to increase sampling frequency the present analysis uses monthly data
covering the examined period, including the index of industrial production,
consumer price index, treasury bill rate, long-term government bond yield, money
supply, and crude oil price taken from IFS (International Financial Statistics)
database. The detailed data descriptions for each variable are described in the
appendix 1.
The Domestic and Foreign Spread as a Predictor for Real Economic Activity
Following Estrella and Hardouvelis (1991), Estrella and Mishkin (1997),
Haubrich and Dombrosky (1996), Bonser and Morley (1997), Dotsey (1998), and
Hamilton and Kim (2002), the strategy to examine the predictability of the yield
spread over future real activity is to regress the one to forty-eight months ahead
growth in real industrial production on the contemporaneous term spread.
y
k
t
= α
0
+ β1Spreadt
+ εt
. (1)
3 One concern to select these Asian countries is due to data limitations in locating the long and short
interest rates.
6

k
y
t
(
t + k t
= 1200/ k)[log(
y y )], where
Spread
t
= i
L
t
− i
S
t
Following Plosser and Rouwenhorst (1994), we calculate the growth of the
industrial production index to represent the economic activities. The dependent
variable (
k
y
t
) in the basic long-horizon regression is the annualized percentage
change in real industrial production over next k months; where
y + denotes the
real industrial production index in month t+k. The k-period change in the logarithm
of industrial output is multiplied by ( 1200 / k ) to ensure that the percentage growth
rate is expressed in annualized terms. In addition, we use two interest rates to
construct the slope of yield curve, the long-term government bond rate i L
t
, and
t
k
short-term rate
S
i
t
. Both
i and i S are annualized bond equivalent yields, where
L
t
t
L
t
S
t
i − i represents the slope of the yield curve.
Our sampling period is monthly, but the forecasting horizon k varies beginning
from one and continues until it doesn’t contain the predictive power. The
overlapping of forecasting horizons creates special econometric problems. The data
overlapping causes a moving average error term of order k-1, where k is the
forecasting horizon. The moving average does not affect the consistency of the OLS
regression coefficients but indeed affect the efficiency of the OLS standard errors.
For correct inferences, the OLS standard errors need to be adjusted. We use the
technique of Newey and West (1987) to correct errors.
When one uses higher frequency data, then it becomes less clear what lag
structure one ought to employ. Our approach is to let the data speak for themselves.
We use established statistical methods to test for appropriate lag structures.
Furthermore, the econometric literature generally supports the use of autoregressive
moving average (ARMA) specifications as a convenient, reduced form method of
capturing rational expectations processes of uncertain lag structure (Feige and
Pearce 1976, Nerlove, Grether and Carvalho1979, Wallis 1980). We follow that
tradition. Our empirical results are generally consistent with Hamilton and Kim’s
(2002) findings that one period lagged real industrial production growth contains
most promising information for future activity. Consequently, y 1 t −1
is included in
the estimated equation:
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y
k
1
t
= α
0
+ β1Spreadt
+ β2
yt
−1
+ εt
. (2)
Several studies, including those by Estrella and Hardouvelis (1991), Plosser
and Rouwenhorst (1994), Estrella and Mishkin (1997), Dotsey (1998), Mcmillan
(2002) and Hamilton and Kim (2002) have examined whether the yield spread
contains useful additional information beyond that of other economic variables, they
found that the yield spread has additional information beyond that contained in
monetary policy. In contrast that their studies primarily focus on developed countries,
we direct our attention on Asian emerging economics and compare the region
difference between G7 and Asian countries. Following Hamilton and Kim (2002) the
subsequent equation takes into consideration the influence of the change of crude
price ( Δ opt
) and the growth of money supply ( Δ mt
). It is of our interest to evaluate
whether term spreads are more informative than other economic variables about
future real economic conditions.
y
k
1
t
= α
0
+ β1Spreadt
+ β
2Δmt
+ β
3Δopt
+ β
4
yt−
1
+ ε
t
. (3)
One of our purposes in this paper is to investigate whether U.S. term structures
have predictive content for Asian and G7 real economic growth rates. We attempt to
examine the difference for the information context of U.S. spread on Asia and G7
regions in the predictive power of future economics. To evaluate the U.S. foreign
term spreads are helpful for predicting future real economic growth, we replace the
domestic spread variable ( Spread ) at equation (3) as the spread of United States
( SP _ US ) at equation (4).
t
y
k
t
1
= α
0
+ β1SP
_ USt
+ β
2Δmt
+ β
3Δopt
+ β
4
yt−
1
+ ε
t
. (4)
The Expectation and Term Premium Effects for Real Economic Activity
Hamilton and Kim (2002) argued that term structure is determined by the
market participant’s expectation of future short-term yield and a term premium. The
relationship between the yield spread and the future economic activity could be
explained either by the future change in expected short rates (the expectation effect)
or the change in the term premium (the term premium effect). The pure expectation
effect is composed of interest rates for a shorter period and the term premium is
8

comprised of interest rates for a longer period and. More specifically, the
explanations of the term structure to forecast economic activity could be
implemented by that the spread signals future expected short rates. In that condition,
there is positive association between the spread and the future growth of outputs
results from the expectations hypothesis of the term spread and the short-term
influence of monetary policy. Furthermore, the spread has another important factor:
term premium that is a sign of the risk of investments in alternative assets. Term
premium on long-term bonds represent rewards to bear risk of holding longer term
bonds that imply a long-term economic concept. The higher the risk premium, the
larger GDP growth is expected to be in the future. Hamilton and Kim (2002) found
both of the two effects make statistically important contributions in forecast future
economy.
To examine further in which particular factor the information about future
economic activity is included. It would be useful to be able to decompose the
spread's forecasting contribution into an expectations effect and a term premium
effect. In comparing which effect provides more information contexts to predict
future economic activity, our interests focus on the region difference between Asian
and G7 economics. The decomposition of the contribution of term structure into the
two factors is summarized as follows:
First, let i L
t
and i S
t
denote the n-period interest rate (long-term rate) and the
one-period interest rate (short-term rate), respectively.
1
i E i + TP = Expectation effect + Term premium effect, (5)
n
L
= ∑ − 1
t
n j = 0
S
t t + j
t
where
E +
represents the market’s expectation at time t of the value of
i S
t t j
S
i
t + j
. The
term premium
TP
t
could represent the sum of a liquidity premium and a risk
premium.
The spread can also be written:
1
i E i + TP . (6)
n
L S
t
− it
= ∑ − 1
(
n j=
0
S S
t t+ j
−i
t
)
t
Eq. (6) implies that the spread can be split into two terms. The first term is on the
right hand side of equation (6) is the difference between expected short-term over
9

next n periods and the current one. The second term is the time-varying term
premium. In order to know that either the first term or the second term is a source of
predictability, Eq. (7) is rewritten as:
n−1
n−1
L S 1 S S L 1 S
i
t
− it
= ( ∑ Etit+ j
−i
t
) + ( it
− ∑ Etit+
j
) . (7)
n
n
j=
0
Substitution into Eq. (1):
j=
0
y
k
t
1
1
= α ∑ +
n−1
n−1
S S
L
S
0
+ γ
1(
∑ Etit+ j
−i
t
) + γ
2
( it
− Etit+
j
) ε
t
. (8)
n j=
0
n j=
0
Expression (8) decomposes the contribution of the spread into the expectation
n 1
n 1
1 S S
L 1 S
effect ( Etit
+ j
− it
) , and the term premium effect ( i
t
− Etit
+ j
) , which allow
n
n ∑− j=
0
these two components to have different implications for future real activities. Then
Eq. (8) can also be expressed to:
1
1
y α + e . (9)
∑ −
j=0
n−1
n−1
k
S S
L
S
1
t
=
0
+ γ1( ∑ Etit
+ j
−i
t
) + γ
2(
it
− ∑ Etit
+ j
) + γ
3yt
−1
n j = 0
n j = 0
t
At the first, let
ω
t+ n
denote the error in forecasting future short-term rates:
1 1
ω E i , (10)
n−1
n−1
s
t + n
= ∑it
+ j
− ∑
n j = 1 n j = 1
s
t t + j
where
u
t
= e t
+ ( γ
2
− γ
1)
ωt+
n
,
then
e
t
= u t
− ( γ
2
− γ
1)
ωt+
n
= u
t
n−1
n−1
n−1
n−1
1 s 1 s 1 s 1
2 ∑it+ j
+ γ
2 ∑ Etit+
j
+ γ
1 ∑it+
j
− γ
1 ∑
n j=
0 n j=
0 n j=
0 n j=
0
− γ E i . (11)
s
t t+
j
Substitution into Eq. (9), then (9) can be written:
1
1
y γ + u . (12)
n−1
n−1
k
s s
n
s
1
t
=
0
+ γ
1( ∑it+ j
− it
) + γ
2
( it
− ∑it+
j
) + γ
3
yt−
1
n i=
0
n j=
0
In rational expectations, the error term
u
t
would be uncorrelated with any variable
at any time t. Consequently, (12) can be regressed by instrumental variable
estimation with any variables dated t or earlier as instruments.
One concern this paper is to investigate whether the spread of United States
contains information about the domestic economic growth in Asian emerging
t
10

countries and then compare the results with them in developed G7 countries. We
attempt to decompose the contribution of the U.S. term spread into a factor related to
expected changes in short-term rates and a factor related to the term premium. We
examine and compare their effects on economic growth of Asian and G7 markets,
respectively. Consequently, we replaced the interest rate of United States to
substitute the domestic interest rate and we get Eq. (13)
L
r
t
,
1
1
y γ + u . (13)
n−1
n−1
k
s s
n
s
1
t
=
0
+ γ1( ∑rt
+ j
− rt
) + γ
2(
rt
− ∑rt
+ j
) + γ
3yt
−1
n i=
0
n j = 0
S
r
t
denoted the n-period interest rate (long-term rate) of United States and the
one-period interest rate (short-term rate) of United States, respectively.
t
IV. Empirical results
The Predictability of Real Economic Activity Using the Domestic Term Spread
First, using solely the domestic term spread as a regressor, Table 1-1 and 1-2
reported the results estimated in Eq. (3) for G7 and Asian countries, respectively. It
is shown that the domestic spread of U.S. make heavy contribution to predict U.S.
economic activities for all horizons ahead. For Canada, the results showed that the
domestic spread explain the real economic activities in the period for three and four
years ahead. As to U.K., German and France, the domestic spread adds substantially
improvement to describe the future output changes for most periods ahead. However,
from the results of Italy, the coefficients enter insignificantly for all horizons ahead.
For Japan, we found the coefficients of the domestic spread appear significantly
negative from two to three years ahead. 4 In summary, with the exception of Italy
and Japan, our results provided evidences of the potential usefulness of term spread
as indicators for output activity in United States, Canada, U.K., France and Germany
when the growth of monetary supply and the other economic indicators are
concerned. This suggests the domestic spreads generally contain useful information
to predict economic trends in G7 5 .
4 Kim and Limpaphayom (1997) also found that the spread of Japan had the negative effect to the
real activities. They argued this is due to that interest rate were heavily regulated in Japan.
5 It is similar to that of Estrella and Mishkin (1995b), who found that the yield spread predicts
relatively well for United States and Germany, and to a less significant level in the Italy.
11

Regarding the effect of domestic spread on Asian economics, Table 1-2 shows
that the domestic spread of Korea, Malaysia, Taiwan and Thailand generally don’t
exhibit predictability for future real activities. Exception to this is Singapore, which
show that the domestic spread is the one could predict the real activities in the future
from six months to four years ahead. Generally, we found the domestic spreads
appear not to contain significant information toward the future economic activities
in Asian countries except in Singapore. Overall, in contrast to G7 economies, we
found the domestic spread in Asia exhibit less influence to predict future economic
trends.
The Predictability of Real Economic Activity Using the Term Spread of United
States
Then, we discuss the effects of the U.S. spread on the future economic
activities in G7 and Asian countries as shown at Table 2-1 and Table 2-2,
respectively. From the results of U.K. at Table 2-1, the coefficients on the future
economic activity appear significant from one to three years ahead. In Canada and
Italy, the estimated coefficients of the foreign spread are statistically significant at
5% level for four and three years ahead, respectively. Despite this, however, in
Germany, the coefficients show significantly negative estimations for most horizon
periods. In the case of France and Japan, the U.S. spread never enters significantly in
the regression. In contrast that the domestic spreads contain considerably significant
insights to signal future economic activity in G7 countries, it can be found in the
results that the spread of United States contribute less predictive power on G7
economies 6 . As the results, we generally found, in G7 countries, the domestic
spreads essentially exhibit more information useful for predicting future output than
that of the spread of United States.
The estimation results of U.S. spread on Asian countries are reported at Table
2-2. In Taiwan and Malaysia, the coefficients of the U.S. spread consistently exhibit
statistically forecasting power toward the economic activities for most horizons. In
Korea, the coefficients of the U.S. spread are significantly positive as one looks
6 By way of comparison, our results are consistent with the findings of Bernard and Gerlach (1998)
that the spread of United States had limited explaining power on the economic activity in France and
Italy, and negative relation to German.
12

from three to four years ahead. As to Singapore, U.S. contains information to
explain its economic prospects for one year ahead. In Thailand, the spread of United
States could significantly predict the future economic activities over one and two
years ahead. As a whole, we striking found that the spread of United States included
substantially information about future economic growth for Asian economies. In
these countries, the spread of United States contained insights to foresee their future
economic outlook and the relationship is independent of monetary policy and other
economic indicators. This comparison validates the potential of using foreign
spreads rather than domestic spread to better capture the future economic activity in
Asian emerging markets. In particular, Singapore is the only one, for which both U.S.
and domestic spread contain explanatory power to predict economic trend. By
comparing the prediction duration of horizons between U.S. spread and domestic
spread, it turns out that that U.S. spread seems to carry capacity cover longer
duration of horizons in predicting future economic than that of domestic spread.
The Predictive Power of the Domestic Pure Expectation and Term Premium
Hypothesis
Next, we review the hypothesis on the relationship between the domestic yield
spread and future economic activity in terms of the expectation effect and the term
premium effect. Table 3-1 shows the estimates of the Eq. (12) in G7. In United
States, we found that the estimated coefficients on the term premium appear to be
positive at 5% significance level for all periods ahead, while the estimated
coefficients of the expected short-term rate are significant only for horizons from
one month to one year ahead. For U.K., the coefficients of the term premium effect
are statistically significant and positively effective from one year to four years ahead;
however, the coefficients of the expectation effect turn statistically positive only for
one year ahead. In the results of Canada, while the estimated coefficients of the
expected short-term rate enter significance at 5% level only for six months ahead,
the estimated coefficients on the term premium enter significantly from three to four
years ahead. In France, the term premium effect show positive at 5% significant
level for most horizons ahead, as the expectation effect doesn’t enter any
significance for any periods. In Germany, both estimations of expected short-term
13

ate and the term premium rate are statistically significant and positive for most
periods. With respect to Italy and Japan, while the coefficients of the risk premium
never enter significantly for any horizons ahead, the significant coefficients on the
expected short-term rate are all negative. In general, for United State, U.K. Canada,
France and German, we find both factors are relevant for predicting future economic
growth but the respective contributions differ. The contributions in all G7 countries
except Italy and Japan, are generally similar at short horizons but the effect of term
premium provide more potentials, in light of more significant estimations, for
predicting future economic growth than that of the expected short-run effect. In
particular, our evidences indicate that the term premium tend to offer capacity
covering longer durations of horizons in predicting G7 economic activities.
Table 3-2 presents the estimates of the Eq. (12) in Asian countries. In Korea,
Malaysia, Thailand and Taiwan, the estimated coefficients of expected short-term
rate and the term premium are not consistently positive and statistically significant
for future economic growth. Singapore is the only exception to reveal that the
expectation effect exhibit significantly predictive power for one month and one year
ahead, whereas the term premium still doesn’t show significantly explanatory ability
at any time. Reviewing the results in Asian countries, the results suggest the findings
that both domestic expectation and term premium effect generally add limited
information in predicting future economic activities, which is consistent with our
previous observations that domestic spreads contain little signal for the domestic
economic activity.
The Predictive Power of the Pure Expectation and Term Premium Hypothesis
of United States
Then, we would investigate whether the expectation effect and the term
premium effect of United States have predictive power for the real activities in the
G7 countries. The results of Eq. (13) are reported in the Table 4-1 and Table 4-2 for
G7 and Asian countries, respectively. Overall, the results of U.K., Canada and Japan
entered some statistically significant coefficients of the expectation effect and term
premium in the regression, suggesting both factors, to some extent, providing
capability in predicting future economic activity. As to Germany and France, the
coefficients on the expectation effect and term premium effect of United States
14

emain either negative or insignificant for each horizon ahead. 7 As to Japan, the
coefficients on the expected rate of United States are significantly positive for six
and twelve months ahead, while the term premium of United States turn
insignificantly for any periods ahead.
The results of U.S. expectation and term premium effect on Asian countries
were reported at Table 4-2. In Korea, Singapore, Taiwan and Thailand, in contrast
that the information from the expectation effects of United States is irrelevant to
Asian economic growth at any time, the coefficients of the term premium remain a
statistically significant influence for predicting future economics. As to Malaysia,
we found that the information of the expectation effect and term premium effect of
United States are statistically useful for forecasting future activity for most horizons
ahead. Of importance, our evidences highlight the crucial role of the term premium
of U.S. in forecasting Asian economic activity. As we pointed out at the beginning,
the term premium on long-term bonds represents rewards to bear risk of holding
longer term bonds. This suggests the term premium effect contains more long term
information than that of pure expectation effect. Our results provide the evidence
that Asian investors are more concern about long-term economics prospects in U.S..
As our best understanding, this paper makes the first observations that the term
premium plays the more substantial role in disclosing the long run economic activity
than that of the pure expectation effect in Asian economics.
Regional Differences
It is noteworthy that our results show the influence of the two factors varying
across regions. We found the domestic spreads contain more predictive information
for the economic activity in G7 countries, while the spread of United States contain
information useful for predicting domestic condition in Asian countries. In some
countries, the output-spread relationships are even negatively significant. The
empirical results raise the question of what the sources of the observed differences in
7 In France, the insignificant estimations of expectation and term premium effects is apparently
consistent with the previous findings that the spread of United States doesn’t have any influence on
the economic activities. For Germany, the negative estimations of term premium effect of United
States on the economic activities is also consistent with the previous results that the spread of United
States show negative influences on economic activity.
15

the predictive ability of the spreads are. Three explanations come readily to mind.
One explanation is the differences of the regulations in different financial
markets. Kim and Limpaphayom (1997), Bernard and Gerlach (1998), Nakaota
(2005) found that the tight regulation of Japanese financial markets weakened the
explaining power for the economic growth. Bernard and Gerlach (1998) argued that
the cross-country variation of the information the term spread contains may be due
to differences in the rules of financial markets. These differences may cause that
interest rates not properly reflect market participants’ expectations about the future
course of the economy. Therefore, the financial markets in Asia, which were
relatively heavy regulated by authority, provide one possible explanation why the
spread is limited to reflect future economic conditions. However, interest rates in
United States, Canada, United Kingdom, France and Germany have been relatively
freely determined in the financial markets, for which these countries provide further
evidence of the potential usefulness of term spreads as indicators for monetary
policy purposes. The exception to this is Japan, this might due to the fact that more
regulations of Japanese financial markets imposed weakened the explaining power
for the economic growth (Kim and Limpaphayom, 1997; Bernard and Gerlach, 1998;
Nakaota, 2005).
Alternatively, Plosser and Rouwenhorst (1994) argued that the cross-country
variation of the predictive power of term spread might be affected by the nature of
inflation. He stated that one would predict that the term spread should be a better
indicator of future real activities in countries with low and stable inflation because
variations in the nominal spread sometimes might be associated primarily with
temporary movements in the underlying factors. The standard deviations of inflation
rates of Asian and G7 countries are reported in Table 5. From the results we found
that, compared to the results of G7, the variability of inflation rate in five Asian
countries is evident in the higher standard deviation. The more variant and unstable
rate of inflation in Asian countries provides another alternative to explain why the
domestic spread contains little information for future economic condition in Asian
countries. On the other hand, we found that the domestic spread have more
consistent explaining power in the countries with lower variance of inflation rate
like United States, Canada, United Kingdoms, France, and Germany. Italy and Japan
16

are the two exceptions with relatively higher variance of inflation rate, for which
both countries added limited information toward future economic growth. The
results are consistent to the argument of Plosser and Rouwenhorst (1994) that the
domestic spread should be a better indicator of future real activities in countries with
low and stable inflation.
Bernard and Gerlach (1998) indicated the choice of exchange rate regime might
influence the information content of the term structure. Foreign exchange market
pressures might force policy-makers to raise short-term interest rates to keep up the
exchange rate parity. This may be particularly useful for countries operating under
fixed exchange rates, where speculative pressures in the foreign exchange market
can generate large swings in term spreads. Because such increases are likely to be
large and temporary, it is not necessarily tightly linked to the future state of the
economy. Consequently, exchange-market-induced changes in interest rates offer
another possibility for the lack of a significant relationship between the term
structure and the future economic activities. Table 6 shows the exchange regime in
five Asian countries during sample periods. 8 We found that the exchange regime in
five Asian countries are almost less flexible (fixed or immediate) compared with the
exchange regime in G7 (almost floating or joint floating). As a result, the regional
difference in exchange rate regime provides another alternative to explain the
observations that the useless of the term spread as a predictor of future real
economic conditions in Asia. On the contrast, we found that the domestic spread had
more consistently explaining power in the countries whose exchange regime is more
flexible (floating and joint floating) just like Canada, United Kingdoms, United
States France and Germany. In Italy whose exchange regime was less flexible, the
domestic spread didn’t have consistent influence for the real activities. One
exception is Japan whose exchange regime is floating, however, more regulation in
8 The data of exchange regime were obtained from IMF website. We adopt new classification (de
facto exchange rate regimes) by IMF after 1999, which categorizes a country’s exchange rate regime
into thirteen categories (the detail information about the names and definitions of exchange rate
regimes can be found out in the website of IMF). Because Taiwan is not a member of IMF, the
arrangement may be ambiguous. We took the data and the classification of exchange regime from the
Central bank of Taiwan (CBC) and international economics website. Then, we follow Frankel,
Schmukler and Serven (2000) to condense the categories in the original source into three broader
exchange regimes: fixed (Conventional fixed pegged to basket or single currency), intermediate
(crawling pegs, managed floating), floating (independent floating or joint floating).
17

the financial markets.
In Asian countries, due to more financial market regulations, less flexible
exchange regime and more variant inflation rate, the domestic spreads contained less
information as leading indicators for future economic growth. Moreover, following
the long and close relations with U.S., it is found that U.S. term spreads is more
informative about the likelihood of Asian economic activity than that of domestic
term spread. This issue has not yet been addressed for these countries yet.
6. Conclusion
This paper study the ability of the term structure to predict economic condition
in G7 and Asian countries, including United States, Canada, United Kingdoms,
France, Germany, Italy and Japan; and Korea, Malaysia, Singapore, Taiwan and
Thailand; respectively. Four findings deserve attentions.
First: with the exception to Italy and Japan, our results provided evidences of
the potential usefulness of term spread as indicators for output activity in G7
countries when the growth of monetary supply and the other economic indicators are
concerned. While further research might be needed, it seems that less flexible in
exchange arte regime and more regulations in financial markets are possible
explanation for the limited spread information context for Italy and Japan,
respectively.
In contrast to G7 economies, the domestic spread in Asia exhibit less influence
to predict future economic trends. Investigation the domestic spread effect on G7
and Asian economics, our results indicated that domestic spread tend to appear
considerable predictability in explaining future economic activity in G7 than that in
Asian countries.
Second, in contrast that the domestic spreads contain more significant insights
to signal future economic activity in G7 countries, it can be found that the spread of
United States contribute less predictive power on most G7 economies. On the other
hand, we striking found that the spread of United States included substantially
information about future economic growth in Asian economies. We found that the
spread of United States appear considerable predictability of future economic
activity than that of domestic spreads in Asian countries. The ability to forecast
18

economic growth in advance makes the U.S. spread a particularly desirable indicator
for monetary policy purposes in Asian countries.
Third, for United State, U.K. Canada, France and German, we find both
domestic expectation effect and term premium effect are relevant for predicting
future economic growth but the respective contributions differ. In all G7 countries
except Italy and Japan, the contributions are generally similar at short horizons but
the effect of term premium provide more potentials for predicting future economic
growth than that of the expected short-run effect. In particular, our evidences
indicate that the term premium tend to offer capacity covering longer durations of
horizons in predicting G7 economic activities.
On the contrary, reviewing the results in Asian countries, the results indicated
that both domestic expectation and term premium effect generally add limited
information in predicting future economic activities.
Forth, as to the results of U.K., Canada and Japan, the expectation effect and
term premium of United States have predictive power for the real activities in the
regression, suggesting both factors, to some extent, providing capability in
predicting future economic activity.
Furthermore, investigation the decomposition of domestic and U.S. spread on
Asian countries, we strikingly found the term premium of United States have
substantially predictive power in Asian emerging countries, whereas the expectation
effect of United States show relatively limited predictive power on the economic
activities except in Malaysia. Our estimations underscore the crucial role of the term
premium effect of United States in the predictive power of Asian future economic
growth. As our best understanding, this paper makes the first observations that the
term premium of U.S. plays the more substantial role in disclosing the long run
economic activity than that of the pure expectation effect in Asian economics.
19

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21

Table 1-1 Predicting Real Growth of Industrial Production Index Using The
Domestic Yield Spread in G7 Countries
k
Model: y α + β Spread + β Δm
+ β Δop
+ β y + ε
K α
0
t
= 0 1 t 2 t 3 t 4
1 t−1
t
1
Spread
t y
t−1
Δ mt
Δ opt
United States
1 -5.68 (.00) *** 2.77 (.00) *** -0.26 (.00) *** -0.78 (.62) 0.12 (.17)
6 -4.75 (.00) *** 2.45 (.00) *** -0.03 (.00) *** -0.87 (.17) -0.10 (.00) ***
12 -4.36 (.00) *** 2.23 (.00) *** 0.02 (.00) *** -0.88 (.14) *** -0.10 (.00) ***
24 -3.63 (.00) *** 1.81 (.00) *** 0.01 (.04) ** -1.34 (.02) ** -0.09 (.00) ***
36 -2.86 (.00) *** 1.16 (.00) *** 0.01 (.18) -1.30 (.01) *** -0.07 (.00) ***
48 -2.41 (.00) *** 0.82 (.00) *** 0.00 (.28) -1.36 (.00) *** -0.06 (.00) ***
Canada
1 2.40 (.74) 3.68 (.20) -0.37 (.00) *** -12.58 (.00) *** 1.36 (.04) **
6 -2.25 (.41) 1.12 (.25) -0.09 (.00) *** 0.82 (.11) 0.27 (.01) ***
12 -0.70 (.75) 0.81 (.30) 0.00 (.74) -0.04 (.80) 0.02 (.74)
24 -0.29 (.83) 0.70 (.14) 0.00 (.61) -0.10 (.35) -0.05 (.17)
36 -1.37 (.03) ** 1.23 (.00) *** 0.00 (.54) -0.01 (.92) -0.03 (.32)
48 -1.16 (.01) ** 1.20 (.00) *** 0.00 (.31) 0.01 (.96) -0.01 (.69)
UK
1 1.04 (.77) 1.00(.62) -0.42 (.00) *** -10.43(.00) *** 0.27(.65)
6 -3.38(.01) *** 1.44 (.05) ** -0.06(.00) *** 0.46(.02) ** 0.31 (.00) ***
12 -2.84 (.00) *** 1.12 (.00) *** 0.00 (.09) * -0.06 (.44) -0.04 (.09) *
24 -2.80 (.00) *** 0.88 (.00) *** -0.01 (.00) *** -0.09 (.12) -0.03 (.10) *
36 -2.72 (.00) *** 0.61 (.00) *** -0.01 (.00) *** -0.08 (.11) -0.02 (.40)
48 -2.55 (.00) *** 0.39 (.00) *** 0.01 (.00) *** -0.04 (.28) 0.00 (.94)
France
1 -8.71 (.15) 3.49 (.39) -0.27 (.00) *** -0.11 (.90) 1.88 (.05) **
6 -6.77 (.01) *** 2.61 (.14) -0.08 (.00) *** 0.45 (.00) *** 0.18 (.50)
12 -5.26 (.00) *** 1.66(.01) *** 0.00(.58) -0.02(.36) -0.12(.00) ***
24 -4.85 (.00) *** 0.95(.02) ** 0.00(.28) -0.02(.18) -0.09(.01) ***
36 -4.72(.00) *** 0.69(.00) *** 0.00(.47) -0.02(.58) -0.07(.01) ***
48 -4.73(.00) *** 0.64(.04) ** 0.00(.29) -0.02(.11) -0.06(.04) **
Germany
1 -7.78 (.52) 5.08 (.42) -0.17 (.01) *** -0.45 (.97) 1.06 (.50)
6 -6.72 (.00) *** 3.94 (.01) *** -0.05 (.00) *** 0.06 (.97) 0.37 (.05) **
12 -6.43 (.00) *** 3.37 (.00) *** 0.00 (.77) 0.82 (.16) -0.11 (.11)
24 -4.77 (.00) *** 2.57 (.00) *** 0.00 (.42) 0.88 (.08) ** -0.05 (.42)
36 -3.33 (.00) *** 2.13 (.00) *** 0.00 (.39) 0.45 (.19) -0.03 (.48)
48 -2.78 (.00) *** 1.83 (.00) *** 0.00 (.28) 0.49 (.05) ** -0.01 (.72)
Italy
1 -8.22 (.51) -5.73 (.60) -0.48 (.00) *** -1.29 (.66) 4.49 (.09) *
6 -6.87 (.07) * -0.21 (.94) -0.08 (.00) *** 1.30 (.00) *** 1.22 (.01) ***
12 -6.00 (.00) *** -0.53 (.35) 0.00 (.89) -0.07 (.42) -0.06 (.20)
24 -5.7 (.00) *** -0.98 (.06) * 0.00 (.80) -0.09 (.22) -0.10 (.04) **
36 -5.67 (.00) *** -0.97 (.07) * 0.00 (.83) -0.09 (.14) -0.10 (.02)
48 -5.45 (.00) *** -0.85 (.11) 0.00 (.83) -0.10 (.08) -0.09 (.05)
Japan
1 4.93 (.34) -0.16 (.93) -0.20 (.00) *** -5.74 (.00) *** 0.11 (.81)
6 3.10 (.18) -1.04 (.26) -0.05 (.00) *** -0.35 (.03) ** 0.01 (.95)
12 2.87 (.09) * -1.03 (.12) 0.01 (.05) ** -0.09 (.21) -0.13 (.23)
24 2.04 (.07) * -0.78(.05) ** 0.00 (.20) -0.06 (.28) -0.12 (.03) **
36 1.45 (.09) * -0.64 (.04) ** 0.00 (.27) -0.05 (.26) -0.10(.01) ***
48 0.79 (.24) -0.46 (.07) * 0.00(.09) * -0.07 (.08) * -0.08 (.00) ***
Note: The symbols *** , ** , and * denote the statistical significance at the 1%, 5%, and 10% level, respectively.
22

Table 1-2 Predicting Real Growth of Industrial Production Index Using The
Domestic Yield Spread in Asian Countries
k
1
Model: y α + β Spread + β Δm
+ β Δop
+ β y + ε
K α
0
t
=
0 1
t 2 t 3 t 4 t−1
Spread
t
m
1
y Δ
t−1
t
Δ
t
Korea
1 8.04 (.04) *** -1.04 (.24) -0.23(.00) *** 0.34 (.57) -0.18 (.71)
6 0.97 (.73) 1.53 (.14) -0.06 (.00) *** 0.09 (.39) -0.04 (.79)
12 6.08 (.01) *** -0.61 (.17) -0.01 (.08) * 0.00 (.94) -0.06 (.42)
24 5.30 (.00) *** -0.31 (.37) -0.01 (.11) -0.01 (.81) -0.10 (.04) **
36 4.66 (.00) *** -0.09 (.65) 0.00 (.53) -0.03 (.37) -0.05 (.07) *
48 3.79 (.00) *** 0.14 (.36) 0.00 (.18) -0.00 (.77) -0.05 (.05) **
Malaysia
1 11.75 (.01) *** -2.50 (.54) -0.47 (.00) *** -2.99 (.00) *** 0.82 (.17)
6 4.43 (.04) ** 0.45 (.81) -0.08 (.00) *** 0.21 (.51) 0.35 (.04) **
12 5.49 (.00) *** -1.00 (.49) -0.01 (.36) 0.22 (.14) 0.25 (.02) **
24 5.66 (.00) *** -0.66 (.49) -0.01 (.01) *** -0.19 (.15) 0.00 (.94)
36 5.10 (.00) *** -0.45 (.40) -0.01 (.00) *** -0.06 (.44) -0.01 (.87)
48 5.05 (.00) *** -0.80 (.05) ** -0.01 (.00) *** -0.01 (.81) 0.04 (.12)
Singapore
1 -0.06 (.74) 0.08 (.46) 0.00 (.98) -0.07 (.07) * 0.00 (.43)
6 -0.12 (.01) *** 0.08 (.00) *** -0.14 (.00) *** 0.00 (.62) 0.01 (.00) ***
12 -0.06 (.00) *** 0.04 (.01) *** -0.05 (.00) *** 0.00 (.30) 0.00 (.08) *
24 -0.03 (.03) ** 0.02 (.01) *** -0.02 (.02) ** 0.00 (.91) 0.00(.05) **
36 -0.02 (.03) ** 0.01 (.01) *** -0.01 (.00) *** 0.00 (.94) 0.00 (.03) **
48 -0.01 (.10) * 0.01 (.05) ** -0.01 (.00) *** 0.00 (.96) 0.00 (.07) *
Taiwan
1 3.90 (.71) 8.63 (.45) -0.53 (.00)*** -8.78 (.03)** 0.47 (.73)
6 3.24 (.25) -0.14 (.96) -0.10 (.00)*** 0.48 (.39) 0.06 (.79)
12 4.83 (.00) -2.15 (.09)* -0.01 (.03)** 0.15 (.64) 0.05 (.62)
24 5.18 (.00) -3.56 (.00)*** -0.01 (.11) 0.12 (.37) -0.07 (.11)
36 3.08 (.00)*** -0.23 (.78) 0.00 (.99) -0.04 (.65) -0.04 (.30)
48 2.88 (.00) -0.27 (.65) 0.00 (.61) 0.13 (.22) 0.06 (.14)
Thailand
1 3.20 (.49) 1.09 (.56) -0.36 (.00)*** 2.77 (.03) -0.55 (.31)
6 6.74 (.01)*** -0.19 (.83) -0.07 (.00)*** -0.22 (.38) 0.14 (.42)
12 6.51 (.00)*** -0.40 (.16) -0.01 (.10)* -0.03 (.79) -0.05 (.39)
24 5.99 (.00)*** -0.36 (.10)* -0.01 (.05)** -0.07 (.37) -0.06 (.10)*
36 5.45 (.00)*** -0.15 (.45) -0.01 (.03)** -0.07 (.25) -0.04 (.16)
48 5.10 (.00)*** -0.40 (.04)** 0.00 (.09)* -0.04 (.41) -0.01 (.76)
Note: The symbols *** , ** , and * denote the statistical significance at the 1%, 5%, and 10% level, respectively.
t
op
23

Table 2-1 Predicting Real Growth of Industrial Production Index Using The
Yield Spread of United States in G7 Countries
k
1
y α + β SP US + β Δm
+ β Δop
+ β y + ε
k α
0
t
=
0 1
_
t 2 t 3 t 4 t−1
SP _ US
m
1
y Δ
t−1
t
Δ
t
UK
1 0.55 (.93) 0.33 (.92) -0.42 (.00) *** -10.41 (.00) *** 0.26 (.66)
6 -6.02 (.01) *** 1.51 (.17) -0.06 (.00) *** 0.49 (.02) 0.30 (.01) ***
12 -4.55 (.00) *** 0.99 (.02) ** 0.00 (.23) -0.03 (.73) -0.05 (.19)
24 -4.64 (.00) *** 1.08 (.01) *** -0.01 (.00) *** -0.07 (.32) -0.03 (.17)
36 -3.91(.00) *** 0.71 (.03) ** -0.01 (.00) *** -0.06 (.25) -0.02 (.33)
48 -3.41 (.00) *** 0.52 (.08) * 0.00 (.00) *** -0.03 (.47) 0.00 (.89)
Canada
1 10.89 (.30) -0.68 (.90) -0.37 (.00) *** -12.50 (.00) *** 1.38 (.07) *
6 -0.59 (.81) 0.40 (.72) -0.09 (.00) *** 0.84 (.11) 0.26 (.01) ***
12 0.41 (.53) 0.33 (.33) 0.00 (.93) -0.02 (.92) 0.02 (.75)
24 0.96 (.46) 0.06 (.93) 0.00 (.73) -0.09 (.42) -0.05 (.13)
36 0.01 (.99) 0.75 (.19) 0.00 (.95) 0.01 (.92) -0.04 (.15)
48 -0.89 (.04) ** 1.97 (.00) *** 0.00 (.63) -0.02 (.84) -0.04 (.03) **
France
1 -7.06 (.41) 1.36 (.75) -0.29 (.00) *** -0.59 (.54) 1.81 (.07) *
6 -6.27 (.10) * 1.39 (.46) -0.08 (.00) *** 0.50 (.00) *** 0.15 (.58)
12 -4.58 (.00) *** 0.82 (.18) 0.00 (.39) -0.01 (.81) -0.14 (.00) ***
24 -4.36 (.00) *** 0.68 (.14) 0.00 (.28) -0.01 (.34) -0.10 (.00) ***
36 -3.91 (.00) *** 0.33 (.41) 0.00 (.26) -0.02 (.13) -0.08 (.00) ***
48 -3.88 (.00) *** 0.29 (.43) 0.00 (.28) -0.02 (.14) -0.08 (.00) ***
Germany
1 7.25 (.65) -4.45 (.46) -0.17 (.01) *** -1.10 (.92) 1.26 (.43)
6 4.25 (.19) -3.11 (.05) ** -0.05 (.00) *** -0.43 (.79) 0.53 (.01) ***
12 3.64 (.00) *** -3.00 (.00) *** 0.00 (.66) 0.38 (.42) 0.02 (.76)
24 3.17 (.00) *** -2.42 (.00) *** 0.00 (.62) 0.55 (.23) 0.06 (.30)
36 2.75 (.00) *** -1.75 (.00) *** 0.00 (.48) 0.18 (.55) 0.06 (.23)
48 1.89 (.00) *** -1.23 (.00) *** 0.00 (.48) 0.27 (.26) 0.06 (.16)
Italy
1 -10.71 (.35) 2.71 (.69) -0.48 (.00) *** -2.29 (.36) 2.77 (.17)
6 -11.29 (.00) *** 2.94 (.15) -0.09 (.00) *** 1.64 (.00) *** 0.71 (.08) *
12 -6.85 (.00) *** 1.32 (.11) 0.00 (.68) -0.04 (.64) -0.16 (.03) **
24 -6.59 (.00) *** 1.14 (.09) * 0.00 (.65) -0.08 (.20) -0.15 (.00) ***
36 -6.45 (.00) *** 0.92 (.10) ** 0.00 (.55) -0.08 (.18) -0.12 (.00) ***
48 -6.37 (.00) *** 0.80 (.13) 0.00 (.45) -0.11 (.04) ** -0.12 (.00) ***
Japan
1 3.48 (.29) 1.12 (.45) -0.19 (.00) *** -5.97 (.00) *** 0.11 (.81)
6 -1.62 (.43) 1.50 (.10) * -0.05 (.00) *** -0.32 (.03) ** 0.01 (.92)
12 -1.44 (.39) 1.28 (.08) * 0.01 (.05) ** -0.06 (.32) -0.13 (.19)
24 -0.60 (.63) 0.73 (.16) 0.00 (.32) -0.04 (.50) -0.13 (.01) ***
36 -0.21 (.82) 0.38 (.36) 0.00 (.37) -0.03 (.48) -0.10 (.00) ***
48 0.05 (.96) 0.07 (.84) 0.00 (.16) -0.05 (.20) -0.09 (.00) ***
Note: The symbols *** , ** , and * denote the statistical significance at the 1%, 5%, and 10% level, respectively.
t
op
24

Table 2-2 Predicting Real Growth of Industrial Production Index Using The
Yield Spread of United States in Asian Countries
y
k α
0
k
1
t
= α
0
+ β1SP
_ USt
+ β
2Δmt
+ β
3Δopt
+ β
4
yt−
1
+ ε
t
1
SP _ US y Δ m
t−1
t
Δ opt
Korea
1 3.40 (.48) 0.60 (.77) -0.23 (.00) *** 0.30 (.62) -0.17 (.72)
6 0.97 (.73) 1.53 (.14) -0.06 (.00) *** 0.09 (.39) -0.04 (.79)
12 1.92 (.35) 1.12 (.13) -0.01 (.13) -0.03 (.61) -0.06 (.47)
24 2.56 (.06) * 0.93 (.08) * -0.01 (.15) -0.03 (.56) -0.10 (.06) *
36 2.96 (.00) *** 0.80 (.05) ** 0.00 (.53) -0.04 (.23) -0.06 (.07) *
48 3.68 (.00) *** 0.39 (.03) ** 0.00 (.32) -0.01 (.85) -0.05 (.07) *
Malaysia
1 4.43 (.36) 4.74 (.02) ** -0.45 (.00) *** -6.34 (.00) *** 0.42 (.30)
6 -0.85 (.70) 3.41 (.00) *** -0.07 (.00) *** -0.16 (.50) -0.07 (.70)
12 -0.79 (.57) 3.16 (.00) *** -0.01 (.01) *** -0.08 (.51) 0.02 (.74)
24 0.38 (.51) 2.69 (.00) *** -0.01 (.01) *** -0.28 (.01) *** -0.04 (.36)
36 1.48 (.05) ** 1.98 (.00) *** -0.01 (.00) *** -0.19 (.01) *** -0.06 (.21)
48 2.24 (.00) *** 1.56 (.00) *** -0.01 (.00) *** -0.17 (.01) *** -0.05 (.04) **
Singapore
1 -0.01 (.86) 0.01 (.66) -0.47 (.00) *** -0.01 (.26) 0.00 (.79)
6 -0.01 (.63) 0.01 (.35) -0.07 (.00) *** 0.00 (.36) 0.00 (.62)
12 -0.01 (.18) 0.01 (.03) ** -0.04 (.00) *** 0.00 (.53) 0.00 (.82)
24 -0.01 (.04) ** 0.00 (.08) * -0.02 (.00) *** 0.00 (.85) 0.00 (.55)
36 0.00 (.28) 0.00 (.19) -0.02(.00) *** 0.00 (.28) 0.00 (.81)
48 0.00 (.32) 0.00 (.46) -0.01(.00) *** 0.00 (.32) 0.00 (.98)
Taiwan
1 3.81 (.49) 7.78 (.00)*** -0.43 (.00)*** -9.23 (.00)*** -0.87 (.07)*
6 -5.44 (.08)* 5.23 (.00)*** -0.09 (.00)*** -0.24 (.26) -0.33 (.00)***
12 -4.24 (.07)* 4.18 (.00)*** -0.01 (.03)** -0.15 (.39) -0.18 (.01)***
24 -1.07 (.46) 1.99 (.00)*** -0.01 (.02)** -0.12 (.36) -0.10 (.03)**
36 0.24 (.83) 1.07 (.03)** 0.00 (.13) -0.16 (.01)*** -0.05 (.15)
48 2.76 (.00)*** -0.29 (.46) 0.00 (.23) -0.11 (.02)** -0.01 (.83)
Thailand
1 -1.38 (.85) 2.89 (.37) -0.36 (.00)*** 2.79 (.02)** -0.53 (.31)
6 2.32 (.50) 2.27 (.13) -0.07 (.00)*** -0.20 (.37) 0.13 (.46)
12 3.11 (.00)*** 1.66 (.00)*** -0.01 (.22) -0.01 (.89) -0.06 (.24)
24 3.40 (.00)*** 1.34 (.00)*** -0.01 (.04)** -0.06 (.40) -0.07 (.08)*
36 4.09 (.00)*** 0.75 (.09)* -0.01 (.02)** -0.06 (.30) -0.04 (.15)
48 5.28 (.00)*** -0.15 (.72) 0.00 (.12) -0.05 (.35) -0.02 (.53)
Note: The symbols *** , ** , and * denote the statistical significance at the 1%, 5%, and 10% level, respectively.
25

Table 3-1 Predicting Real Growth of Industrial Production Index Uusing The
Decomposition of the Domestic Yield Spread in G7
n−1
n−1
k 1 s s
n 1 s
1
y
t
= γ
0
+ γ
1( ∑it+ j
− it
) + γ
2
( it
− ∑it+
j
) + γ
3
yt−
1
+ ut
n
n
i=
0
k
n 1
1 s s
γ
0
( ∑ − n 1
n 1
i t + j
− it
) ( ∑ − s
1
i
t
− it+
j
) y
t−1
n i=
0
n j=0
United States
1 -5.30 (.00) *** 4.79 (.00) *** 2.38 (.00) *** -0.27 (.00) ***
6 -4.85 (.00) *** 3.89 (.00) *** 2.21 (.00) *** -0.04 (.00) ***
12 -4.77 (.00) *** 2.05 (.00) *** 2.20 (.00) *** 0.02 (.00) ***
24 -4.38 (.00) *** 0.28 (.50) 1.86 (.00) *** 0.01 (.00) ***
36 -3.56 (.00) *** -0.31 (.49) 1.20 (.00) *** 0.01 (.01) ***
48 -3.02 (.00) *** -0.21 (.57) 0.79 (.00) *** 0.01 (.04) **
UK
1 -5.02 (.06) * -0.30 (.86) -1.04 (.47) -0.16 (.00) ***
6 -5.19 (.00) *** 1.08 (.21) -0.41 (.64) -0.08 (.00) ***
12 -3.01 (.00) *** 0.71 (.02) ** 1.26 (.00) *** 0.00 (.07) *
24 -3.18 (.00) *** -0.06 (.77) 1.21 (.00) *** -0.01 (.00) ***
36 -3.14 (.00) *** -0.39 (.00) *** 0.95 (.00) *** -0.01 (.00) ***
48 -2.89 (.00) *** -0.46 (.00) *** 0.68 (.00) *** 0.00 (.00) ***
Canada
1 -1.87 (.79) 10.04 (.10) * 2.04 (.50) -0.32 (.00) ***
6 2.15 (.25 ) 5.28 (.03) ** -0.39 (.67) -0.09 (.00) ***
12 -0.18 (.94) 1.78 (.08) * 0.65 (.41) 0.00 (.59)
24 -0.27 (.85) 0.95 (.20) 0.66 (.19) 0.00 (.40)
36 -1.48 (.03) ** 1.07 (.08) * 1.26 (.00) *** 0.00 (.45)
48 -1.62 (.00) *** 0.14 (.71) 1.30 (.00) *** 0.00 (.64)
France
1 -6.84 (.25) 1.70 (.76) 2.55 (.51) -0.29 (.00) ***
6 -6.17 (.02) ** 2.36 (.35) 2.70 (.08) * -0.07 (.00) ***
12 -5.58 (.00) *** 0.81 (.31) 2.25 (.00) *** 0.00 (.36)
24 -5.29 (.00) *** -0.33 (.46) 1.75 (.00) *** 0.00 (.11)
36 -5.02 (.00) *** -0.27 (.53) 1.30 (.00) *** 0.00 (.10) *
48 -5.00 (.00) *** -0.26 (.49) 1.19 (.00) *** 0.00 (.12)
Germany
1 -6.48 (.38) 9.25 (.35) 5.01 (.27) -0.20 (.00) ***
6 -4.11 (.09) * 9.58 (.00) *** 3.21 (.03) ** -0.05(.00) ***
12 -4.40 (.02) ** 5.64 (.00) *** 3.01 (.01) *** 0.00 (.41)
24 -4.49 (.00) *** 1.29 (.15) 2.76 (.00) *** 0.00 (.36)
36 -3.39 (.00) *** 1.15 (.02) ** 2.26 (.00) *** 0.00 (.23)
48 -2.79 (.00) *** 0.80 (.07) * 1.95 (.00) *** 0.00 (.16)
Italy
1 -8.63 (.40) -2.58 (.83) -0.35 (.96) -0.49 (.00) ***
6 -7.26 (.04) -1.27 (.71) 2.01 (.40) -0.08 (.00) ***
12 -5.91 (.00) *** -0.80 (.35) 0.48 (.35) 0.00 (.97)
24 -5.90(.00) *** -2.17 (.01) *** 0.05 (.91) 0.00 (.95)
36 -5.72 (.00) *** -1.96 (.02) ** -0.17 (.73) 0.00 (.99)
48 -5.54 (.00) *** -1.67 (.04) ** -0.27 (.60) 0.00 (.92)
Japan
1 1.54 (.77) 2.02 (.78) -0.47 (.81) -0.35 (.00) ***
6 2.39 (.30) -2.53 (.39) -0.90 (.31) -0.06 (.00) ***
12 1.99 (.24) -4.35 (.09) * -0.81 (.19) 0.01 (.05) **
24 0.94 (.46) -4.66 (.02) ** -0.49 (.22) 0.00 (.19)
36 0.34 (.73) -4.04 (.00) *** -0.33 (.28) 0.00 (.22)
48 -0.28 (.72) -3.41 (.00) *** -0.17 (.50) 0.00 (.13)
Note: The symbols *** , ** , and * denote the statistical significance at the 1%, 5%, and 10% level, respectively.
j=
0
26

Table 3-2 Predicting real growth of industrial production index (IP) using the
decomposition of the domestic yield spread in Asian countries
1
1
y + u
n−1
n−1
k
s s
n
s
1
t
= γ
0
+ γ
1( ∑it+ j
− it
) + γ
2
( it
− ∑it+
j
) + γ
3
yt−
1
n i=
0
n j=
0
k 0
n 1
1 s s
γ ( i t j
− it
)
n
∑ −
i=
0
1
n 1
n
(
)
+ ∑ − s
1
it
− it+
j y
t−1
n j=0
Korea
1 9.48 (.02) ** -0.81 (.77) -1.38 (.13) -0.25 (.00) ***
6 6.36 (.02) ** -1.27 (.28) -0.76 (.17) -0.06 (.00) ***
12 5.62 (.01) *** -1.59 (.05) ** -0.54 (.16) -0.01 (.06) *
24 4.93 (.00) *** -0.97 (.11) -0.25 (.39) -0.01 (.08) *
36 4.49 (.00) *** -0.32 (.33) -0.06 (.71) 0.00 (.42)
48 3.72 (.00) *** -0.16 (.52) 0.14 (.28) 0.00 (.14)
Malaysia
1 8.12 (.07) * -3.49 (.65) -1.05 (.80) -0.46 (.00) ***
6 3.78 (.12) -0.62 (.83) 1.36 (.54) -0.08 (.00) ***
12 4.48 (.02) ** -3.55 (.02) ** 0.14 (.94) -0.01 (.52)
24 5.03 (.00) *** -2.03 (.06) * -0.24 (.82) -0.01 (.01) ***
36 4.83 (.00) *** -1.07 (.12 ) -0.27 (.65) -0.01 (.00) ***
48 4.61 (.00) *** -1.73 (.01) *** -0.43 (.27) -0.01 (.00) ***
Singapore
1 -0.04 (.80) 0.32 (.01) *** 0.03 (.78) -0.17 (.05) **
6 -0.07 (.37) -0.02 (.45) 0.04 (.46) -0.06 (.05) **
12 0.04 (.25) 0.02 (.02) ** -0.02 (.29) -0.05 (.00) ***
24 0.03 (.36) 0.00 (.79) -0.01 (.35) -0.02 (.00) ***
36 0.01 (.37) 0.01 (.17) -0.01 (.42) -0.01 (.00) ***
48 0.01 (.56) 0.00 (.70) 0.00 (.76) -0.01 (.00) ***
Taiwan
1 3.51 (.81) 9.03 (.65) 3.49 (.78) -0.48 (.00) ***
6 5.22 (.21) 2.80 (.49) -0.75 (.82) -0.10 (.00) ***
12 4.10 (.00) *** -2.81 (.09) * -1.36 (.28) -0.01 (.03) **
24 6.37 (.00) *** -2.73 (.00) *** -4.56 (.00) *** -0.01 (.05) **
36 4.46 (.00) *** 1.41 (.14) -1.81 (.01) *** 0.00 (.90)
48 2.14 (.01) *** -0.32 (.59) 1.23 (.44) 0.00 (.41)
Thailand
1 5.92 (.28) 2.18 (.54) 0.73 (.72) -0.36 (.00) ***
6 5.62 (.04) ** -1.39 (.36) -0.11 (.91) -0.07 (.00) ***
12 5.67 (.00) *** -1.61 (.01) *** -0.35 (.28) -0.01 (.16)
24 5.61 (.00) *** -0.56 (.15) -0.43 (.08)* -0.01 (.03) **
36 5.20 (.00) *** -0.19 (.60) -0.21 (.33) -0.01 (.05) **
48 4.84 (.00) *** -0.66 (.05) ** -0.42 (.04) ** 0.00 (.13)
Note: The symbols *** , ** , and * denote the statistical significance at the 1%, 5%, and 10% level, respectively.
t
27

Table 4-1 Predicting Real Growth of Industrial Production Index Using The
Decomposition of The Yield Spread of United States in G7
Countries
n−1
n−1
k 1 s s
n 1 s
1
y
t
= γ
0
+ γ
1( ∑ rt
+ j
− rt
) + γ
2
( rt
− ∑ rt
+ j
) + γ
3
yt−
1
+ ut
n
n
UK
k 0
i=
0
n 1
1 s s
γ ( r t j
− rt
)
n
∑ −
i=
0
28
j=
0
1
n 1
n
+
( ∑ − s
1
r
t
− rt
+ j
) y
t−1
n j=0
1 -3.21 (.63) 4.49 (.46) -0.01 (1.00) -0.31 (.00) ***
6 -5.62 (.03) ** 1.84 (.31) 1.48 (.22) -0.06 (.00) ***
12 -4.31 (.00) *** 1.49 (.03) ** 0.89 (.05) ** 0.00 (.16)
24 -4.84 (.00) *** 0.68 (.31) 1.15 (.00) *** -0.01 (.00) ***
36 -4.38 (.00) *** -0.30 (.65) 0.90 (.01) *** -0.01 (.00) ***
48 -3.90 (.00) *** -0.50 (.38) 0.75 (.01) *** 0.00 (.00) ***
Canada
1 2.60 (.66) 6.20 (.30) -0.69 (.82) -0.32 (.00) ***
6 2.15 (.25) 5.28 (.03) ** -0.39 (.67) -0.09 (.00) ***
12 2.12 (.13) 4.07 (.00) *** -0.35(.58) 0.00 (.50)
24 1.54 (.22) 1.61 (.19) -0.18 (.72) 0.00 (.35)
36 0.42 (.62) 1.57 (.04) ** 0.56 (.27) 0.00 (.56)
48 -1.08 (.17) 1.62 (.01) *** 2.06 (.00) *** 0.00 (.48)
France
1 -4.43 (.58) -2.52 (.75) 0.06 (.99) -0.30 (.00) ***
6 -5.27 (.13) 0.92 (.73) 1.21 (.46) -0.08 (.00) ***
12 -4.35 (.00) *** 0.71 (.39) 0.82 (.15) 0.00 (.32)
24 -4.34 (.00) *** -0.06 (.92) 0.78 (.09) * 0.00 (.21)
36 -3.96 (.00) *** -0.43 (.46) 0.46 (.25) 0.00 (.17)
48 -3.86 (.00) *** -0.31 (.53) 0.35 (.36) 0.00 (.18)
Germany
1 6.73 (.35) 1.12(.87) -3.71 (.25) -0.20 (.00) ***
6 3.02 (.11) -3.55 (.01) *** -1.93 (.08) * -0.05 (.00) ***
12 3.15 (.00) *** -3.54 (.00) *** -1.91 (.00) *** 0.00 (.44)
24 2.22 (.00) *** -1.84 (.01) *** -1.46 (.00) *** 0.00 (.17)
36 1.50 (.01) *** -1.00 (.02) ** -1.03 (.00) *** 0.00 (.23)
48 1.48 (.00) *** -1.01 (.00) *** -1.01 (.00) *** 0.00 (.11)
Italy
1 -7.50 (.42) 0.36 (.98) 0.29 (.96) -0.48 (.00) ***
6 -7.11 (.04) ** 3.23 (.27) 1.29 (.48) -0.08 (.00) ***
12 -6.41 (.00) *** 2.31 (.05) ** 1.09 (.15) 0.00 (.66)
24 -6.60 (.00) *** 0.72 (.42) 1.18 (.07) ** 0.00 (.63)
36 -6.53 (.00) *** 0.23 (.77) 1.04 (.07) ** 0.00 (.51)
48 -6.49 (.00) *** 0.10 (.88) 0.92 (.09) * 0.00 (.45)
Japan
1 -1.58 (.63) 3.65 (.19) 1.58 (.32) -0.35 (.00) ***
6 -1.42 (.49) 3.76 (.01) *** 1.23 (.18) -0.06 (.00) ***
12 -1.41 (.44) 2.52 (.00) *** 1.19 (.14) 0.01 (.04) **
24 -0.86 (.54) 0.53 (.41) 0.84 (.16) 0.00 (.19)
36 -0.45 (.67) 0.02 (.98) 0.48 (.28) 0.00 (.23)
48 -0.15 (.87) -0.03 (.95) 0.15 (.70) 0.00 (.16)
Note: The symbols *** , ** , and * denote the statistical significance at the 1%, 5%, and 10% level, respectively.

Korea
Table 4-2 Predicting real growth of industrial production index (IP) using
the decomposition of the yield spread of United States in Asian Countries
Malaysia
1
1
y + u
n−1
n−1
k
s s
n
s
1
t
= γ
0
+ γ
1( ∑ rt
+ j
− rt
) + γ
2
( rt
− ∑ rt
+ j
) + γ
3
yt−
1
n i=
0
n j=
0
k 0
n 1
1 s s
γ ( r t j
− rt
)
n
∑ −
i=
0
1
n 1
n
+
( ∑ − s
1
r
t
− rt
+ j
) y
t−1
n j=0
1 2.15 (.69) -1.42 (.61) 1.11 (.60) -0.25 (.00) ***
6 1.03 (.75) 1.59 (.28) 1.52 (.19) -0.06 (.00) ***
12 1.55 (.50) 0.57 (.46) 1.25 (.14) -0.01 (.10) *
24 1.79 (.22) -0.23 (.71) 1.21 (.04) ** -0.01 (.08) *
36 2.55 (.01) *** 0.20 (.66) 0.94 (.03) ** 0.00 (.35)
48 3.28 (.00) *** -0.20 (.67) 0.56 (.10) * 0.00 (.07) *
1 -0.17 (.96) 4.80 (.25) 3.93 (.03) ** -0.42 (.00)
6 -0.37 (.86) 5.94 (.02) ** 3.03 (.00) *** -0.07 (.00)
12 -0.55 (.70) 4.03 (.00) *** 2.99 (.00) *** -0.01 (.01) ***
24 -0.16 (.87) 1.94 (.00) *** 2.81(.00) *** -0.01 (.00) ***
36 0.83 (.27) 0.77 (.10) * 2.22 (.00) *** -0.01 (.00) ***
48 1.62 (.01) *** 0.35 (.31) 1.81 (.00) *** -0.01 (.00) ***
Singapore
1 -0.01 (.91) -0.01 (.67) 0.00 (.86) -0.34 (.00) ***
6 0.00 (.87) -0.01 (.20) 0.00 (.78) -0.07 (.00)
12 -0.01 (.27) -0.01 (.25) 0.01 (.05) ** -0.04 (.00) ***
24 -0.01 (.21) 0.00 (.33) 0.00 (.05) ** -0.02 (.00) ***
36 0.00 (.32) 0.00 (.54) 0.00 (.07) * -0.01 (.00) ***
48 0.00 (.74) 0.00 (.13) 0.00 (.33) -0.01 (.00) ***
Taiwan
1 -8.14 (.19) 5.03 (.29) 7.40 (.01) *** -0.43 (.00) ***
6 5.22 (.21) 2.80 (.49) -0.75 (.82) -0.10 (.00) ***
12 -5.50 (.04) ** 1.73 (.10) * 4.71 (.00) *** -0.01 (.03) **
24 -2.45 (.08) * -1.45 (.13) 2.67 (.00) *** -0.01 (.01) ***
36 -0.52 (.62) -1.10 (.16) 1.42 (.00) *** 0.00 (.06) **
48 2.27 (.01) *** -1.72 (.01) *** -0.07 (.85) 0.00 (.17)
Thailand
1 2.67 (.75) 4.91 (.42) 2.12 (.58) -0.36 (.00) ***
6 0.81 (.84) 1.69 (.60) 2.61 (.13) -0.08 (.00) ***
12 1.93 (.33) 0.92 (.40) 1.94 (.01) *** -0.01 (.14)
24 2.18 (.08) * -0.27 (.76) 1.69 (.00) *** -0.01 (.04) **
36 3.16 (.00) *** -0.56 (.47) 1.03 (.01) *** -0.01 (.06) *
48 4.53 (.00) *** -1.12 (.20) 0.08 (.84) 0.00 (.20)
Note: The symbols *** , ** , and * denote the statistical significance at the 1%, 5%, and 10% level, respectively.
t
29

Table 5: The Standard Deviation of Inflation Rate
Standard Deviation in G7 countries
US UK CANADA FRANCE GERMANY ITALY JAPAN
Std. Dev. 0.31 0.43 0.29 0.39 0.31 0.49 0.69
standard deviation in Asian countries
KOREA MALAYSIA SINGAPORE TAIWAN THAILAND
Std. Dev. 0.71 0.50 0.34 0.88 0.70
Table 6 Exchange rate Regimes in G7 countries
Country Period Exchange rate regime Aggregate
United States 1/1975-8/2005 Independent floating Floating
United
Kingdom
1/1975-9/1990 Independent floating Floating
10/1990-8/1992 Pegged within a horizontal band Joint Floating
9/1992-8/2005 Independent floating Floating
France
1/1979-12/1997 Pegged within a horizontal band Joint Floating
12/1998-8/2005 Currency union Joint Floating
Germany
1/1979-12/1997 Pegged within a horizontal band Joint Floating
12/1998-8/2005 Currency union Joint Floating
Italy
1/1979-8/1990 Crawling pegs Intermediate
2/1990-8/1992 Pegged within a horizontal band Joint Floating
9/1992-9/1996 Managed floating Intermediate
10/1996-12/1998 Other conventional fixed pegged
to single currency
Fixed
1/1999-8/2005 Currency union Joint Floating
Japan 1/1975-8/2005 Independent floating Floating
Data sources: IMF website
30

Table 6. Exchange Rate Regimes in Asian countries
Country Period Exchange rate regime Aggregate
Korea
1/1975-2/1980 Conventional fixed pegged Fixed
to single currency
3/1980-2/1990 Conventional fixed pegged Fixed
to basket
3/1990-6/1997 Tightly managed floating Intermediate
7/1997-8/2005 Independent floating Floating
Malaysia
Singapore
1/1975~6/1997 Conventional fixed pegged
to basket
7/1997~8/2005 Conventional fixed pegged
to single currency
1/1975~12/1984 Conventional fixed pegged
to basket
Fixed
Fixed
Fixed
1/1985-8/2005 Other managed floating Intermediate
Taiwan
1/1979~3/1989 Tightly managed floating
4/1989~8/2005 Other managed floating
(official or more actual)
Intermediate
Thailand
1/1975~6/1997 Conventional fixed pegged Fixed
to basket
7/1997~8/2005 Other managed floating Intermediate
Data source: IMF website.
31

Appendix 1 Data description and Source
Long-term rate
G7 countries
United States
Canada
United Kingdom
France
Germany
Italy
Japan
Asian countries
Korea
Malaysia
Singapore
Taiwan
Thailand
Series Type Sample period Data source
10 years government bond yield
10 years government long-term bond yield
20 years government bond yield
Government bond yield
Government bond yield
Government bond yield
10 year government bond yield
01/1957- 08/2005 IFS
01/1976- 08/2005 IFS
01/1957- 07/2005 IFS
01/1957- 08/2005 IFS
01/1957- 08/2005 IFS
01/1958-08/2005 IFS
10/1966-07/2007 IFS
5 year government bond yield
05/1973- 06/2005 IFS
5 years government bonds yield
01/1957- 07/2005 IFS
5 years government bonds yield 01/1988- 11/2005
Monetary Authority of
Singapore
10 year government bond rates
12/1995- 10/2005 TEJ
Government bond Yield
12/1979- 08/2005 IFS
32

Short-term rate
Series Type Sample period Data source
G7 countries
United States 3 months treasury bill rate 01/1964- 08/2005 IFS
Canada 3 months treasury bill 01/1957- 08/2005 IFS
United Kingdom 3 months treasury bill rate 01/1964- 07/2005 IFS
France 3 months treasury bill rate 01/1970- 10/2004 IFS
Germany Treasury bill rate 01/1975- 08/2005 IFS
Italy 3 months treasury bill rate 03/1977-08/2005 IFS
Japan 3 months bank deposit rate 01/1957-07/2005 IFS
Asian countries
Korea Time deposit rate 01/1969- 06/2005 IFS
Malaysia 3-month treasury bill rate 02/1992- 07/2005 IFS
Singapore Treasury bill rate 04/1973- 08/2005 TEJ
Taiwan 3 month time deposits rates 12/1970- 12/2005 TEJ
Thailand 3 months time deposit rate 07/1978- 10/2005 IFS
33

Industrial production index
G7 countries
United States
Canada
United Kingdom
France
Germany
Italy
Japan
Asian countries
Korea
Malaysia
Singapore
Taiwan
Thailand
Series Type Sample period Data source
Industrial production index (base year
2000=100)
Industrial production index (base year
2000=100)
Industrial production index (base year
2000=100)
Industrial production index (base year
2000=100)
Industrial production index (base year
2000=100)
Industrial production index (base year
2000=100)
Industrial production index (base year
2000=100)
Industrial production index (base year
2000=100)
Industrial production index (base year
2000=100)
Manufacturing production index (base year
2000=100)
Industrial production index (base year
2001=100)
Manufacturing production index (base year
2000=100)
01/1957- 08/2005 IFS
01/1995- 08/2005 IFS
01/1957- 08/2005 IFS
01/1957- 08/2005 IFS
01/1958- 08/2005 IFS
01/1957-08/2005 IFS
01/1957-07/2005 IFS
01/1980- 07/2005 IFS
01/1971- 07/2005 IFS
01/1961- 06/2003 TEJ
01/1971- 08/2003 TEJ
01/1987- /2005 TEJ
34

Consumer Prices Index
Series Type Sample period Data source
G7 countries
United States
Consumer prices index (base year 2000=100)
01/1957- 08/2005 IFS
Canada
Consumer prices index (base year 2000=100)
01/1957- 08/2005 IFS
United Kingdom
Consumer prices index- (base year 2000=100)
01/1957- 08/2005 IFS
France
Consumer prices index (base year 2000=100)
01/1957- 08/2004 IFS
Germany
Consumer prices index (base year 2000=100)
01/1991- 08/2005 IFS
Italy
Consumer prices index (base year 2000=100)
01/1957-08/2005 IFS
Japan
Consumer prices index (base year 2000=100)
01/1957-07/2005 IFS
Asian countries
Korea Consumer prices index (base year 2000= 100) 01/1970- 08/2005 IFS
Malaysia Consumer prices index ( base year 000=100) 01/1957- 07/2005 IFS
Singapore Consumer prices index (base year 2000=100) 01/1961- 07/2005 IFS
Taiwan Consumer price index (base year 2001=100) 01/1959- 10/2005 TEJ
Thailand Consumer prices index (base year 2000=100) 01/1957- 08/2005 IFS
35

Data description of money supply
Series Type Sample period Data source
G7 countries
United States Monetary aggregates (M1) 01/1987- 08/2005 TEJ
Canada Money Supply 01/1961- 01/2005 TEJ
United Kingdom Money supply (M0) 01/1987- 03/2005 TEJ
France Money supply (M1) 01/1961- 12/1998 TEJ
Germany Money supply 01/1961- 12/1998 IFS
Italy Money supply 01/1961-12/1998 TEJ
Japan Monetary aggregates (M1) 01/1964- 03/2005 TEJ
Asian
Korea
Malaysia
Singapore
Taiwan
Money supply (M1)
Money Supply (M1)
Money Supply (M1)
Money Supply (M1)
01/1961- 12/2004
01/1960- 12/2004
06/1969- 01/2005
07/1961- 08/2004
Thailand Money Supply (M1) 01/1961- 01/2005 TEJ
Data description of oil price
Describer Sample period of oil price Data source of oil price
Oil price 3 SPOT PRICE INDEX 01/1957- 08/2005 IFS
TEJ
TEJ
TEJ
TEJ
36