Proceedings of Applied International Business Conference 2008
TERMS-OF-TRADE AND TRADE BALANCE IN SELECTED ASIAN NEWLY
INDUSTRIALISED ECONOMIES
Wong Hock Tsen ψ
Universiti Malaysia Sabah, Malaysia
Abstract
This study examines the impact of terms-of-trade on trade balance in selected Asian Newly Industrialised
Economies. The results the Johansen (1988) (J) cointegration method show that there is a long-run
relationship between trade balance and terms-of-trade. More specifically, an increase in terms-of-trade will
lead to a decrease in trade balance in these economies. Generally, the results of the Hansen (1992) (H)
parameter stability tests show that relationship between trade balance and terms-of-trade is stable, except
Korea. For Korea and Hong Kong, terms-of-trade is found to Granger cause trade balance and not vice
versa. However, there is no Granger causality between terms-of-trade and trade balance is found for
Singapore. Generally, terms-of-trade has some predictive power on trade balance for small open
economies.
Keywords: Terms-of-trade; Trade balance; Asian Newly Industrialised Economies; Granger causality.
JEL Classification Codes: F1; C32; B22.
1. Introduction
The Harberger-Laursen-Metzler (HLM) effect (Harberger, 1950; Laursen and Metzler, 1950) states that an
increase in terms-of-trade will lead to an increase in trade balance. This can be explained by an increase in
terms-of-trade, which will lead to a change in value of exports more than a change in value of imports and
thus, trade balance will increase. There are many empirical studies on the impact of terms-of-trade on trade
balance (Hoque, 1995; Dibooglu, 2000; Otto, 2003; Wong, 2006). However, the empirical results are
mixed. An increase in terms-of-trade could lead to an increase or a decrease in trade balance. Bouakez and
Kano (2008) examine the HLM effect in an intertemporal model for Australia, Canada, and the United
Kingdom and find that a change in terms-of-trade does not affect current account in a significant way.
Generally, terms-of-trade is found to have little impact on current account and the impact of terms-of-trade
volatility on current account is argued to be an important channel. Eicher, Schubert, and Turnovsky (2007:
2-3) develop a theoretical model to show that the impact of terms-of-trade on current account depends on
the credit status of an economy. If an economy is a debtor, a decrease in terms-of-trade will lead to a
decrease in economic growth and thus, a decline in debt that causes an increase in current account, which is
contradict to the HLM effect. If an economy is a creditor, a decrease in terms-of-trade will lead to an
increase in economic growth and thus, a decline in the holdings of foreign assets that causes a decrease in
current account, which leads to the HLM effect. Huang and Meng (2007) develop a dynamic small open
economy model with imperfect world capital market assumption to examine the impact of permanent
terms-of-trade on current account. The model, amongst others, shows that an increase in unanticipated
permanent terms-of-trade will lead to an increase in current account.
The relationship between trade balance and terms-of-trade is argued to depend on the duration of the termsof-trade shock (Ostry and Reinhart, 1992). Sachs (1981) argues that an increase in permanent terms-oftrade, which will lead to an increase in income and consumption at about the same level and thus, no
change in saving and trade balance. Conversely, an increase in temporary terms-of-trade will lead to an
increase in income but consumption will increase less because of intertemporal consumption smoothing.
This will lead to an increase in saving and trade balance. Otto (2003) employs a structural vector
ψ
Corresponding author. Wong Hock Tsen. School of Business and Economics, Universiti Malaysia Sabah,
Locked Bag No. 2073, 88999 Kota Kinabalu, Sabah, Malaysia. E-mail: [email protected]
Proceedings of Applied International Business Conference 2008
autoregression (SVAR) model, which includes trade balance, terms-of-trade, and real output, to examine
the HLM effect for a number of developing and small Organisation for Economic Co-operation and
Development (OECD) economies. The sample period is generally from 1960 to 1997. The results show that
there is the HLM effect. An immediate effect of a positive shock to terms-of-trade is an increase in trade
balance. This finding is similar across both developing and small OECD economies. However, trade
balance is reduced when the terms-of-trade shock become more persistence (Mendoza, 1992; Mendoza,
1995).
The impact of terms-of-trade on trade balance is argued to depend on the response of consumption, which
depends on consumption preferences. The response of consumption pattern to the temporary terms-of-trade
shock could be definitive and sometime ambiguous. Conversely, the response of consumption pattern to the
permanent terms-of-trade shock could be ambiguous. On the whole, the response of saving and trade
balance depends on consumption patterns in an economy and therefore ambiguous, particularly a change in
permanent terms-of-trade because there is enough time for a change in consumption pattern. In summary,
the HLM effect is ambiguous and it is an empirical matter (Okiti, 2003: 16).
This study examines the impact of terms-of-trade on trade balance in selected Asian Newly Industrialised
Economies, namely Korea, Hong Kong, and Singapore. These economies are chosen because they are
small open economy. The openness to international trade, namely exports plus imports to Gross Domestic
Product (GDP), of these economies are more than hundred. International trade is important to these
economies and thus, knowing the impact of terms-of-trade on trade balance of these economies is
important. Furthermore, the impact of terms-of-trade on trade balance is said to be relatively significant for
a small open economy than for a ‘close’ economy. This study also examines Granger causality between
trade balance and terms-of-trade, and between trade balance and terms-of-trade volatility.
The rest of this article is structured as follows. Section 2 provides a literature review of terms-of-trade and
trade balance. Section 3 explains the methodology and data in this study. Section 4 discusses the empirical
results. Section 5 gives some concluding remarks.
2. Literature review
Harberger (1950) and Laursen and Metzler (1950) show an increase in terms-of-trade would lead to an
increase in trade balance and vice versa. This analysis is based on the Keynesian consumption function. An
improvement in terms-of-trade raises national income of an economy, that is, domestic output measured in
terms of importable or in terms of the true consumption bundle increased. However with a short-run
marginal propensity to consume less then unity, there is a less than proportional increase in consumption
spending. As a result, the level of private saving is increased. If other things remain constant, this would
lead to an improvement in trade balance of an economy (Otto, 2003: 157).
The relationship between terms-of-trade and trade balance is also discussed in an intertemporal optimising
framework with certainty or uncertainty. One finding of the relationship between terms-of-trade and trade
balance in an intertemporal optimising framework with certainty is that the contemporaneous response of
trade balance to terms-of-trade shock depends on the persistence of the shock. The shock that produces
transitory changes in terms-of-trade would lead to the HLM effect. Nonetheless, as the effect of the shock
becomes more persistent the HLM effect is reduced. In the standard two-period model of a small open
economy, permanent changes in terms-of-trade have no effect on trade balance (Sachs, 1981; Otto, 2003:
157).
Otto (2003) employs a SVAR model to examine the HLM effect for a number of small open developing
and developed economies. The sample period is typically from 1960 to 1997. The variables included in the
SVAR model are trade balance, terms-of-trade, and real output. On the whole, the results show that there is
the HLM effect. For the vast majority of 55 small open economies examined, an immediate effect of a
positive shock to terms-of-trade is an increase in trade balance. This finding is similar across both
developing and small OECD economies. However, trade balance is reduced when terms-of-trade shocks
become more persistence. The variance decompositions for trade balance indicate that on average terms-oftrade shocks are marginally more important in explaining fluctuations in trade balance of developing
economies than developed economies.
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Proceedings of Applied International Business Conference 2008
Kouassi et al. (1999) investigate the relationship between current account balance and terms-of-trade
within a context of VECM for Cote-d’Ivoire over the period from 1960 to 1995. They include current
account balance, terms-of-trade, domestic income, foreign income, and foreign interest in the VECM. The
results indicate that there is a long-run relationship between terms-of-trade and current account balance.
Moreover, current account balance is found to Granger cause terms-of-trade and not vice versa. Finally,
dynamic simulations indicate that a significant portion of fluctuations in terms-of-trade is explained by
current account balance. The finding that terms-of-trade is explained by current account balance is
contradicted with the findings of Otto (2003).
3. Methodology and data
The Dickey and Fuller (1979) (DF) and Phillips and Perron (1988) (PP) unit root test statistics are used to
examine the stationarity of the data. The Johansen (1988) (J) cointegration method is used to examine the
long-run relationship between trade balance and terms-of-trade. The Hansen (1992) (H) parameter stability
tests are used to examine the stability of the long-run relationship between trade balance and terms-oftrade. When series are cointegrated, the Granger causality test is implemented as follows:
∆ log TBt = β10 +
p
∑
β11i ∆ log TOTt −i +
i =1
∆ log TOTt = β 20 +
p
∑β
12 i ∆ log TBt −i
+ β13 EC1,t −1 + u1,t
(1)
i =1
p
∑
β 21i ∆ log TBt −i +
i =1
p
∑β
22 i ∆ log TOTt −i
+ β 23 EC2,t −1 + u2,t
(2)
i =1
where ∆ is the first difference operator, log is the natural logarithm, TBt is trade balance, TOTt is terms-oftrade, ECi,t-1 (i = 1, 2) is the one period lag of the disturbance term obtained from the cointegrating
regression, and ui,t (i = 1, 2) is a disturbance term. For the joint test of lag variables of ∆ log TOTt in
equation (1) is significantly different from zero, it implies that terms-of-trade Granger causes trade balance.
For the joint test of lag variables of ∆ log TBt in equation (2) is significantly different from zero, it implies
that trade balance Granger causes terms-of-trade.
In this study, terms-of-trade volatility is estimated by an Autoregressive Conditional Heteroscedasticity
(ARCH) model. More specifically, the ARCH model proposed by Engle (1982) is estimated as follows:
q
∑α u
ht = µ1 +
2
i t −i
(3)
i =1
where µ1 is a drift parameter and u2t is the squared disturbance obtained from the conditional variance
equation. The drift parameter, µ1 is assumed to be greater than zero (µ1 > 0) whilst the coefficients, αi (i =
1, … , q) are assumed to be greater than or equal to zero (αi ≥ 0, i = 1, … , q), since ut is a random variable
and the square of ut can not be negative. For µ1 > 0 and αi ≥ 0 (i = 1, … , q), the ht is positive. For sum of
q
the coefficients,
∑
α i is less than or equal to one or all the roots of 1 −
i =1
q
∑α ,
i
that is,
i =1
1 − α1 z − ... − α q z q = 0 lie outside the unit cycle, the model is to be stable. The unconditional variance of ut
µ1
(σ2) is given by σ 2 =
.1
q
1−
∑α
i
i =1
1
The ARCH model is selected after it is found to be better than the Generalised ARCH (GARCH) model.
More specifically, the ARCH(1) model is used to estimate from the natural logarithm of terms-of-trade.
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Proceedings of Applied International Business Conference 2008
The impact of terms-of-trade volatility (VTOTt) on trade balance is examined by replacing terms-of-trade
with terms-of-trade volatility and excluding the one period lag of the disturbance term as terms-of-trade
volatility is a stationary series in equation (1) or equation (2).
In this study, two measures of trade balance are used. One (TBt) is defined as (Xt / Mt), where Xt is the value
of exports and Mt is the value of imports. The other one (TBYt) is defined as (Xt / Mt) / Yt, where Yt is GDP.
The use of trade balance to GDP as a measurement of trade balance is to examine the impact of terms-oftrade on trade balance in terms of the whole economy. Terms-of-trade (TOTt) is defined as (Px,t / Pm,t) ×
100, where Px,t is the exports price index (2000 = 100) and Pm,t is the imports price index (2000 = 100).
The data were obtained from International Financial Statistics, International Monetary Fund (IFS, IMF).
For Korea, the sample is over the period from 1963, quarter I to 1996, quarter IV.2 For Hong Kong, the
sample is over the period from 1973, quarter I to 2006, quarter III. For Singapore, the sample is over the
period from 1979, quarter I to 2006, quarter III. Figure 1 shows that trade balance and terms-of-trade
tended to move in the same direction.
Korea
Hong Kong
Singapore
Figure 1: The plots of the natural logarithms of trade balance and terms-of-trade
Notes: TOT denotes the natural logarithm of terms-of-trade. TB denotes the natural logarithm of trade
balance. Source: IFS, IMF.
2
For Korea, this study examine a period until 1996, quarter IV with the aim to exclude Asian Financial
crisis, 1997-1998, which could affect the estimation result.
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Proceedings of Applied International Business Conference 2008
4. Empirical results and discussions
The results of the DF and PP unit root test statistics are reported in Table 1. The lag length used to estimate
the DF unit root test statistics is based on Schwarz Bayesian criterion (SBC). The lag length used to
compute the PP unit root test statistics is based on Newey-West Bandwidth, with the maximum lag length
is set to twelve. Generally, the DF and PP unit root test statistics show that all series are non-stationary in
level but becoming stationary after taking the first difference, except terms-of-trade volatility, trade balance
(TBt, TBYt) of Korea, trade balance (TBYt) and terms-of-trade of Hong Kong, and trade balance (TBt, TBYt),
and terms-of-trade of Singapore.3 However, these variables could be considered as borderline cases. Thus,
in this study, all the variables are said to be integrated of order one.
Table 1: The results of the Dickey and Fuller (1979) (DF) and Phillips and Perron (1988) (PP) unit
root test statistics
tγ - No Trend
Z(tγ) – No trend
tγ - Trend
Z(tγ) – Trend
Korea
-3.0345*(2)
-2.7184(6)
-2.8880(1)
-3.1293(7)
1og TBt
-15.7017**(0)
-16.6304**(6)
-11.4574**(1)
-17.0386**(5)
∆ 1og TBt
-1.8392(7)
-4.5590**(10)
-2.8038(8)
-7.2557**(9)
1og TBYt
-5.7958**(3)
-24.5905**(8)
-5.8516**(3)
-24.6061**(8)
∆ 1og TBYt
-2.0679(2)
-2.1356(6)
-2.1879(2)
-2.2258(6)
1og TOTt
-8.3634**(0)
-12.9497**(6)
-8.3485**(0)
-12.9688**(6)
∆ 1og TOTt
-7.0136**(0)
-11.8746**(4)
-7.1545**(0)
-11.8489**(4)
VTOTt
-12.4328**(1)
-44.9490**(12)
-12.3851**(1)
-44.8200**(12)
∆ VTOTt
Hong Kong
-3.0815*(4)
-3.0274*(2)
-2.5453(8)
-3.2120(8)
1og TBt
-3.6409**(7)
-10.5204**(10)
-3.9526**(7)
-13.7691**(12)
∆ 1og TBt
-2.9019(9)
-2.1353(3)
-2.2072(8)
-2.4538(3)
1og TBYt
-3.8171**(7)
-12.1274**(3)
-4.2327**(7)
-12.1314**(3)
∆ 1og TBYt
-4.8213**(0)
-4.5176**(12)
-4.7558**(0)
-3.3391(2)
1og TOTt
-9.7342**(1)
-11.7026**(12)
-9.7347**(1)
-10.4484**(10)
∆ 1og TOTt
-9.7272**(0)
-9.9197**(5)
-10.0945**(0)
-10.1000**(12)
VTOTt
-11.1632**(2)
-37.9615**(12)
-11.1276**(2)
-38.0885**(12)
∆ VTOTt
Singapore
1og TBt
-0.9080(1)
-1.0208(2)
-3.4655*(1)
-4.8759**(6)
-15.0718**(0)
-15.6939**(2)
-15.0046**(0)
-15.1758**(1)
∆ 1og TBt
-0.1566(2)
-0.6467(2)
-3.1957(1)
-4.4870**(6)
1og TBYt
-10.8918**(1)
-15.6591**(2)
-10.8748**(1)
-15.6241**(2)
∆1og TBYt
-0.2799(0)
0.8721(6)
-2.7115(0)
-4.2546**(6)
1og TOTt
-11.8899**(0)
-10.9207**(6)
-11.8430**(0)
-11.2543**(6)
∆ 1og TOTt
-9.1605**(0)
-9.1188**(5)
-9.2717**(0)
-9.2093**(6)
VTOTt
-9.0251**(3)
-32.6484**(12)
-8.9782**(3)
-32.5205**(12)
∆ VTOTt
Notes: tγ is the DF t-statistic. Z(tγ) is the PP t-statistic. No Trend denotes the DF or PP t-statistics is estimated based on
the model including an intercept. Trend denotes the DF or PP t-statistics is estimated based on the model including an
intercept and a time trend. Values in parentheses are the lag length used in the estimation of the DF or PP unit root test
statistic. Critical values can be obtained from MacKinnon (1996). ** (*) denotes significance at the 1% (5%) level.
3
For trade balance (TBt) of Korea, the DF (No Trend) unit root test statistic shows that it is a stationary
series whilst the DF (Trend) and PP (No Trend, Trend) unit root test statistics show that there is a unit root.
For trade balance (TBYt) of Korea, the DF (No Trend, Trend) root test statistics show that there is a unit
root whilst the PP (No Trend, Trend) unit root test statistics (Trend) show that it is a stationary series. For
trade balance (TBt) of Hong Kong, the DF (No Trend) and PP (No Trend) unit root test statistics show that
it is a stationary series whilst the DF (Trend) and PP (Trend) unit root test statistics show that there is a unit
root. For terms-of-trade of Hong Kong, the DF (No Trend, Trend) and PP (No Trend) unit root test
statistics show that it is a stationary series whilst the PP (Trend) unit root test statistic shows that there is a
unit root. For trade balance (TBt) of Singapore, the DF (Trend) and PP (Trend) unit root test statistics show
that it is a stationary series whilst the DF (No Trend) and PP (No Trend) unit root test statistics show that
there is a unit root. For trade balance (TBYt) and terms-of-trade of Singapore, the DF (No Trend, Trend) and
PP (No Trend) unit root test statistics show that there is a unit root whilst the PP (Trend) unit root test
statistic shows that it is a stationary series.
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Proceedings of Applied International Business Conference 2008
The results of the J cointegration method are reported in Table 2. The λMax and λTrace test statistics are
computed with restricted intercepts and no trends. The lag length of the vector autoregressive (VAR),
which is used to compute the λMax and λTrace test statistics, is based on SBC. For the two measure of trade
balance (TBt and TBYt), the λMax and λTrace test statistics generally show that there is a long-run relationship
between trade balance and terms-of-trade, except trade balance and trade balance (TBYt) of Korea.
However, it could be considered to have a cointegrating vector. The results of the cointegrating vector
normalised by trade balance are reported in Table 3. Trade balance and terms-of-trade are found to be
negatively cointegrated. On the whole, the likelihood ratio test statistic, which tests the coefficient of termsof-trade is zero is rejected. This implies that terms-of-trade is important to be included in the estimation.
The results of the H parameter stability tests, namely the supF, meanF, and Lc statistics are reported in
Table 4. The supF is analogous to the recursive Chow test, and the meanF, and Lc statistics are tests for
cointegration against the alternative of the parameter vector following a random walk (Hansen, 1992). All
the tests statistics are not rejected, except Korea. Generally, this implies that there is stable long-run
relationship between trade balance and terms-of-trade. The results of the normalised cointegrating vector
show that an increase in terms-of-trade will lead to a decrease in trade balance in the long run, which
implies that there is no HLM effect. This finding is consistent with the postulation of Obsfeld (1982) that
an increase in terms-of-trade will lead to a decrease in trade balance in the long run. Otto (2003) also
reports that an immediate effect of a positive shock to terms-of-trade is an increase in trade balance, but the
effect reduces when terms-of-trade shock becomes more persistence. Hoque (1995) and Kouassi et al.
(1998, 1999), amongst others also find that current account balance and terms-of-trade are cointegrated.
Table 2: The results of the Johansen (1988) likelihood ratio test statistics
λMax Test Statistic
λTrace Test Statistic
H0:
r=0
r<= 1
r=0
H a:
r=1
r= 2
r≥1
r<= 1
r≥2
TBt
Korea
15.99*
2.42
18.41*
2.42
Hong Kong
25.81*
5.09
30.90*
5.09
Singapore
17.61*
0.74
18.34*
0.74
TBYt
Korea
11.64
1.90
13.54
1.90
Hong Kong
29.27*
5.31
34.58*
5.31
Singapore
17.21*
0.60
17.81*
0.60
c.v.
14.88
8.07
17.86
8.07
Notes: For Korea, VAR = 3 is used in the estimation. For Hong Kong, VAR = 5 is used in the estimation.
For Singapore, VAR = 2 is used in the estimation. * denotes significance at the 95% critical value.
Table 3: The results of the normalised cointegrating vector
TBt
Korea
Hong Kong
Singapore
1og TBt = - 2.2227 1og TOTt
(5.8755)*
1og TBt = - 35.6267 1og TOTt
(19.1900)**
1og TBt = - 0.8998 1og TOTt
(13.5920)**
TBYt
Korea
1og TBYt = - 0.6760 1og TOTt
(6.8813)**
Hong Kong
1og TBYt = - 17.7424 1og TOTt
(20.4801)**
Singapore
1og TBYt = - 1.4130 1og TOTt
(12.8441)**
Notes: For Korea, VAR = 3 is used in the estimation. For Hong Kong, VAR = 5 is used in the estimation.
For Singapore, VAR = 2 is used in the estimation. Values in the parentheses are the likelihood ratio test
statistic to test terms-of-trade is zero. ** (*) denotes significance at the 1% (5%) level.
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Proceedings of Applied International Business Conference 2008
Table 4: The results of Hansen (1992) (H) parameter stability tests
SupF
LC
MeanF
TBt
Korea
21.4934**
2.1746**
13.4927**
Hong Kong
7.2891
0.5561
3.7843
Singapore
6.3888
0.1644
2.0053
TBYt
Korea
26.4773**
3.0241**
18.0787**
Hong Kong
5.4734
0.3197
2.1556
Singapore
6.1092
0.1674
1.9339
Notes: The H parameter stability tests are estimated by including a constant in the regression equation. **
denotes significance at the 1% level.
The results of the Granger causality test are reported in Table 5. The lag length used to compute the
Granger causality test statistic is based on SBC. For trade balance (TBt) of Korea and Hong Kong, terms-oftrade is found to Granger cause trade balance and not vice versa. Moreover, there is some evidence that
terms-of-trade volatility Granger causes trade balance. For Singapore, there is no evidence that terms-oftrade Granger causes trade balance or vice versa. Moreover, there is no evidence terms-of-trade volatility
Granger causes trade balance or vice versa. For trade balance (TBYt) of Korea, terms-of-trade is found to
Granger cause trade balance and not vice versa. For Hong Kong, terms-of-trade volatility is found to
Granger cause trade balance (TBYt). For Singapore, there is no relationship between terms-of-trade and
trade balance (TBYt). The finding that terms-of-trade Granger causes trade balance and not vice versa is
contradict with the finding of Kouassi et al. (1999) but it is consistent with the general belief that terms-oftrade of a small open economy affects its trade balance and not vice versa. Bouakez and Kano (2008) report
that terms-of-trade has little impact on current account and terms-of-trade volatility is argued have a
significant impact on current account. The impact of terms-of-trade on trade balance when trade balance is
measured as the difference between exports and imports is generally larger than when trade balance is
measured as a ratio to GDP. Generally, this study finds some evidence that there is relationship between
trade balance and terms-of-trade.
Table 5: The results of the Granger causality test
∆ log TOT → ∆ log TB
∆ log TB → ∆ 1og TOT
Korea
8.6363*
1.5074
Hong Kong
22.4698**
3.3181
Singapore
1.0990
0.8647
VTOT → ∆ log TB
∆ log TB → VTOT
Korea
15.2003**
3.2592
Hong Kong
84.5993**
2.0456
Singapore
0.0030
0.2957
∆ log TOT → ∆ log TBY
∆ log TBY → ∆ 1og TOT
Korea
8.6115**
1.6422
Hong Kong
1.6342
0.3671
Singapore
0.7846
0.5340
VTOT → ∆ log TBY
∆ log TBY → VTOT
Korea
0.0056
0.2456
Hong Kong
8.9098**
1.3927
Singapore
0.0039
0.0022
Notes: The arrow “→” denotes no Granger causality. VTOT denotes terms-of-trade volatility. ** (*)
denotes significance at the 1% (5%) level.
5. Concluding remarks
This study has examined the impact of terms-of-trade on trade balance in selected Asian Newly
Industrialised Economies. Moreover, this study has examined Granger causality between trade balance and
terms-of-trade, and Granger causality between terms-of-trade volatility to trade balance. The DF and PP
unit root test statistics show that all series are non-stationary in level but becoming stationary after taking
the first difference, except terms-of-trade volatility. The results of the J cointegration method show that
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Proceedings of Applied International Business Conference 2008
trade balance and terms-of-trade are cointegrated. In other words, there is a long-run relationship between
trade balance and terms-of-trade. Moreover, in the long run, an increase in terms-of-trade will lead to a
decrease in trade balance. Generally, the results of the H parameter stability tests show that relationship
between trade balance and terms-of-trade is stable, except Korea. For Korea and Hong Kong, terms-oftrade is found to Granger cause trade balance and not vice versa, and there is some evidence that terms-oftrade volatility Granger causes trade balance. However, there is no Granger causality between terms-oftrade and trade balance is found for Singapore. The impact of terms-of-trade on trade balance is generally
more significant when trade balance is measured as the different between exports and imports. Generally,
this study finds some evidence that there is relationship between trade balance and terms-of-trade. Termsof-trade has some predictive power on trade balance for small open economies.
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