The impact of exchange rate on bilateral trade between vietnam and china

304 | ICUEH2017

The impact of exchange rate on
bilateral trade between Vietnam and
China
VO THANH THU
University of Economics HCMC –

TRAN QUOC KHANH CUONG
Van Hien University –

Abstract
The goal of this paper is to investigate the short term and long term
relationship between exchange rate and trade balance on the trade
balance between Vietnam and China. Differing multivariate methods
such as Johansen Cointegraion test, Vector Error Correction Model and
monthly time series data spans from 2011:1 to 2015:12 have been
employed. The results prove the relationship among trade balance, real
exchange rate, domestic and foreign output or ML condition hold. The
positive coefficient implies that the devaluation of Vietnamese currency
will improve the bilateral trade between Vietnam and China. Last but
not least, the prominent aim of this paper is to prove the existence of
Purchasing Power Parity between Vietnam and China hold before
examining the effect of real exchange rate to trade balance.
Keywords: PPP; VECM; exchange rate; trade balance; ML condition.

1. Introduction
Özkan (2013) states that real exchange rate plays an important
role in the macroeconomic such as economic development,
sustainable growth, especially in the trade balance. The trade
balance is a component of Gross Domestic Product (GDP). GDP which

will increase if trade of balance is surplus, and decrease if trade of
balance is deficit. In recent years, Vietnam almost has a trade deficit
with China. The exchange rate between Vietnam and China has been
considering as a reason for trade deficit. Vietnam is in need to
depreciate its currency because exchange rate plays a crucial role in
the economy. This problem is very important because exchange rate
plays an important role in the economy, especially in emerging
market such as Vietnam (Stone et al., 2009). It will effect on inflation
targeting which is one of the urgent issues in Vietnam in recent
years.


Vo Thanh Thu & Tran Quoc Khanh
Cuong | 305

According to Marshall-Learner (ML) condition or J Curve, the
exchange rate is vital in the trade balance. Both of them state
that if the currency is depreciation, with the condition that adding
the absolute value of the elasticity of export and import more
than one, the trade balance will increase in the long run. The
authors often use the formula to check the relationship of
exchange rate and trade balance as follow:
*

TB = f(RER, Y, Y ) where RER is real exchange rate and is
calculated with the assumption Purchasing Power Parity between two
countries is hold. However, in the reality, many studies have proven
PPP between two countries does not hold such as: Assaf (2006),
Doğanlar (2006). This is the limitation of papers when the authors do
not prove

PPP hold. Therefore, in this paper, PPP is proved hold in the long
term before calculating the RER.

The next part of this study include: section 2 briefly discusses
the literature review; section 3 presents the model specification,
section 4 presents the results and discussion.
2. Literature review
2.1. The purchasing power parity approach (PPP)
The PPP was first studied by the Salamanca School in Span in
the 16th century. At that time, PPP was basically means that when
we changed to the common currency, the price level of every
country should be the same (Rogoff, 1996).
Cassel introduced the term purchasing power parity (PPP) in 1918.
After that, PPP became the benchmark for a center bank to build up
the exchange rate and for scholars to study exchange rate
determinant. The model of PPP of Cassel became the inspiration for
Balassa and Samuelson to set up their models in 1964. They
independently worked and gave the final explanation why absolute
PPP became the good theory of exchange rate (Asea and Corden,
1994). The reason is that the relative price of each good in different
countries should be equal to the same price when changing into the
same currency.

The PPP has two versions, including absolute and relative PPP
(Balassa, 1964). According to the first version, Krugman et al.
(2012), define that absolute PPP implies that the exchange rate of
pair countries equal to the ratio of the price level of these
countries. This mean:

st = pt/

∗
"


306 | ICUEH2017

Shapiro (1983) states that the relative PPP implies the ratio of
domestic to foreign prices would equal the ratio change in the
equilibrium exchange rate. This states that there is a constant k
which has the relationship between price level and the equilibrium
exchange rate,
st = k*pt/

∗
"

In the empirical studies, checking the validity of PPP by unit
root test was popular in 1980s based on Dickey and Fuller
approach, nevertheless, this approach has low power (Ender and
Granger, 1998).
After Johansen (1988) develops a method of conducting VECM,
which becomes the benchmark model for many authors test PPP
approach. There are some papers have proved PPP hold such as
Yazgan (2003), Doğanlar et al.(2009), Kim (2011), Kim & Jei
(2013), Jovita Gudan (2016), and some papers do not such as
Basher et al. (2004), Doğanlar (2006).
2.2. Marshall – Lerner condition
According to Bahmani-Oskooee (1991), Marshall – Lerner was

that if the currency depreciated, the trade balance would improve
in the long run with the condition that the sum of the absolute
value of the elasticity of export and import is more than one.
Assuming that the condition is satisfied, the appreciation of home
country makes imported goods from abroad cheaper, thus, the
consumers of Home country buy more. Foreign consumer finds
imported goods are more expensive and they buy less than before
appreciation. As Consequence, Home country has trade deficit.
Nevertheless, if Home country is depreciated, an opposite effect
would be taken place and Home country would enjoy trade
surplus with the rest of the world.
Furthermore, the condition states that devaluation of currency
has positive effects on the trade balance if the total of the
absolute value of the elasticity of export and import is larger than
one. For that reason, the effects on trade balance rely upon the
elasticity of price.
However, the disadvantage of the Marshall – Lerner condition is
that it can not explain why the trade deficit occurs in the short run
after currency depreciation. The reason why trade is deficit, which
happens in the short run, was explained by Akbostanci in 2004. Most
exporters and importers have signed the contract before
depreciation. In the short


Vo Thanh Thu & Tran Quoc Khanh
Cuong | 307

run, the quantity of export and import does not change much;
nevertheless, the depreciation makes the imported goods cost
more in domestic currency. Therefore, the value of imported

goods rises while exported products do not change a lot. As a
result, trade balance becomes deficit.
Seeking for the relationship between trade balance and
exchange rate is one of the most interested topics in international
trade. There have been many authors such as Rose, Yellen,
Bahmani-Oskooee, Arize, Shahbaz have conducted researches in
many countries from developing to developed one. The common
techniques, which are applied, are Johnsen cointegration (1988)
technique such as Bahmani-Oskooee (1991), Onafowora (2003)
etc., and Autoregressive Distributed Lags (ARDL) such as Narayan
(2006), Shahbaz et al., (2012) etc.
Matesanz and Fugarolas (2009) examined the relationship
between trade balance and exchange rate in Argentina from 1962
to 2005. The results indicated that the most important thing is
that the trade balance of Argentina was supported by Argentina
currency undervaluation. As a result, M-L condition took place in
Argentina. Last but not least, in their paper, they argued that the
coefficient of real exchange rate can be positive or negative. If the
coefficient is positive, the M-L condition will hold, this means that
when a currency is devaluated, trade balance will increase, or vice
versa.
The conclusions for J curve or M-L Condition are very different.
While any researchers such as Bahmani-Oskooee (1991), Shirvani
and Wilbratte (1997), Narayan (2006) claim that that there is only
the long run relationship between trade balance and exchange
rate, Rose and Yellen (1988) and Rose (1990), Rahman et al.,
(1997) insist that there is no relationship between the two factors.
Some papers indicate that if real exchange rate is depreciation, it
will lead to trade balance deterioration such as Arora et al., (2003)
and Shahbaz et al., (2012)

3. Model specification
Model for purchasing power parity approach
Take log from the equation (1) we have:


∗

Log(st) = log(pt) – log(p% )


308 | ICUEH2017
where: s is natural log exchange rate of VN, p t and p
and CPI of China respectively.

∗

%

is the natural log CPI of VN

If all variables mean reverting, the real exchange rate is
calculated by the PPP approach following the equation:
qt = st + pt* - pt
where all variables are log form, s is log exchange rate of VN, pt and p
and CPI of China respectively.

∗
%

is the log CPI of VN

Model for trade balance

Determining the relationship of exchange rate, GDP Vietnam
and GDP China with trade balance follow the equation:
∗

Ln(TB) = α0 + α1ln(Q) + α2ln(Yt) + α3ln(Y% ) + εt

where TB is trade balance and is defined as the ratio of export to
import, Q is the real exchange rate defined as the relative price of
domestic to foreign goods or RER = P/ (SP*) whe5re: S is nominal
exchange rate, P is domestic price index and P* is foreign price
index.
∗

Yt and Y%
process.

are Vietnam real income and China real income respectively. ε t is white noise

The expected signs of the coefficient of real exchange rate can
be positive or negative. α1 is positive if the real exchange rate of
VND depreciation encourages exporting goods and reduces
imported goods, then increase trade balance, or Marshall Lerner
condition holds. If α1 is negative, the M-L does not hold or
depreciate of VND which makes trade balance worsen.
The expected sign of the coefficient of Vietnam real income will
be negative. When Vietnam income increases, Vietnamese
imports more goods and services from China, therefore, trade

balance will decrease or α2 < 0. Similarly, the expected sign of
the coefficient of China real income will be positive. When China
income increases, Chinese imports more goods and services from
Vietnam, therefore, trade balance of Vietnam will increase or α 3 >
0.
Because of the limitation of data, the index of industrial
production (IIP) will be used to replace for real income as a proxy.


Vo Thanh Thu & Tran Quoc Khanh
Cuong | 309

Doing VEC Model follows the steps:
Step 1: Testing unit root test based on ADF test.
VECM requires variables are stationary and therefore all-time
series express no spurious regression. Augmented Dickey-Fuller
test whether each variable stationary or not.
Step 2: Using Johansen (1988) test to test the cointegration of
these variables.
Using Johansen (1988) technique with maximum likelihood to
test cointegration. The precondition before doing this test is
determine lag order p.
Optimal lag must be chosen before conducting Johansen (1988)
procedure. In view package, there are five lags length criteria
which have the same power. Therefore, if there are more than 1
lag criteria, every lag is used for every case in VECM.
Step 3: Running VECM
VECM can be written as:
7
7

7
∗
∆
+ 68, 68, 68, "56
2∆ ln "56 +
2∆ ln "56 +
2∆ ln
, = /+
,

where ∆ is the first difference operator, is the speed of adjustment coefficient of long run, TB is trade balance, Q is the real
exchange rate, Y is IIP of Vietnam, Y* is IIP of China and , is white noise.

The estimating coingtegration relationship of the function 5
reflects the long run relationship of parameters. And the equation
6 yields a short run and long run relationship among variables
(Matesanz and Fugarolas, 2009).
is the speed of adjustment coefficient of long run. If is
negative in sign and signification, there is long run causality
running from dependent variables to the independent variable. In
other words, the real exchange rate, Vietnam income and China
income impact on bilateral trade between Vietnam and China.
Wald test is used to test whether short run causality between
exchange rate and trade balance takes place.


310 | ICUEH2017

3.1. Data for PPP approach
Nominal exchange rate (is defined as the number of units of

domestic currency per unit of foreign currency), consumer price
index of Vietnam and consumer price index of China are in terms
of logarithm form and data spans from 2011:1 to 2015:12.
Nominal exchange rate was collected from Thomson Reuter,
Consumer Price Index of Vietnam, base year = 2010, was
collected from IFS and Consumer price index of China, base year
= 201, was collected from OECD.
3.2.

Data for trade balance

This procedure needs real exchange rate, trade balance
between Vietnam and China, industrial production index (as a
proxy of GDP) of Vietnam and China. All variables are natural
logarithm. Data was collected from IFS (export, import) and ERIC
(IIPVN, IIPCN, base year: 2010 and are calculated by the authors)
indicator system spans from 2011:1 to 2015:12.
4. Results and discussion
4.1. PPP approach
Unit root test
The Augmented Dickey Fuller test is used to check the
stationary of consumer price index of Vietnam (CPIVN), consumer
price index of China (CPICN) and nominal exchange rate (S)
between Vietnam and China. All variables have log form.
Mackinon (1996) which is available in Eview 8 package software is
used as the critical value.
Table 1
Unit root test for PPP approach
Variables
CPICN

CPIVN
S
Note: *, ** indicate significant at 5% and 1% levels respectively.


Vo Thanh Thu & Tran Quoc Khanh
Cuong | 311

Table 1 reports the results of unit root test for time series of
consumer price index of Vietnam (CPIVN), consumer price index of
China (CPICN) and nominal exchange rate (S) between Vietnam
and China. As the table suggests, all variables have t-statistic
greater than the critical value at level. As the consequence, all
variables have unit root or nonstationary at level.
On the contrary, at the first difference of S and CPICN have the
t-statistic smaller than critical value at 1%. Therefore, they do not
have unit root or stationary at the first difference. Similarly, CPIVN
has t-statistic smaller than the critical value at 5% so that it is
stationary at the first difference.
As being analyzed above, all variables are nonstationary at
level and stationary at first difference, therefore they cointegrated
at I(1) or same order. As a result, Johansen (1988) procedure is
examined to investigate the cointegration among these time
series.
Optimal lags for VECM
Table 2
Lag criteria for PPP approach
Criterion
Lag
LR: sequential modified LR test statistic

FPE: Final prediction error
AIC: Akaike information criterion
SC: Schwarz information criterion
HQ: Hannan-Quinn information criterion

Table 2 illustrates criterion for choosing lag 1. In other words, 1lag was chosen for conducting Johansen (1988) procedure or
testing cointegration of three variables.
Johansen (1988) procedure for cointegration test
For the reason all variables are cointegrated at the first order
I(1), Johansen (1988) cointegration with 1 lag is conducted to test
the long run relationship among variables.


312 | ICUEH2017

Table 3
Johansen cointegration test with 1 lags

Number
of Ces

*

None
At most 1
At most 2

Table 3 presents the Johansen (1988) cointegration test. The
results indicate Trace test statistically significant at 5% because
the statistic is greater than the critical value of 5%. As

consequence, the null hypothesis of r = 0 is rejected. R = 0
implies one cointegration equation in the long run. That is the
reason why VECM can be used to find out the long run relationship
of three variables.
Table 4
The speed of adjustment coefficient of long run
λ

Table 4 equals -0.479592and probability equals 0.001. Error
Correction Term is negative and significant in sign. For this reason,
variables take place relationship in the long run or all variables
come back to mean. As a result, real exchange rate is calculated
followed this formula: q = s + p* - p with all variables have
logarithm.
4.2. The impact of the exchange rate on trade balance
Unit root test
Similarity of PPP approach, the Augmented Dickey Fuller test is
used to check the stationary of real exchange rate (Q), industrial
production index of China (IIP CN), industrial production index of
Vietnam (IIP VN) and trade balance (TB). All variables have the


natural log form. Mackinon (1996) which is available in Eview 8
package software, is used as the critical value as well


Table 5
Unit root test on time series

Variables

TB
Q
IIP VN
IIP CN
Note: ** indicate significant at 1% levels. TB and Q test unit root with “Exogenous:
Constant, Linear Trend”

The table 5 reports the results of unit root test for time series of
trade balance (TB), real exchange rate between Vietnam and
China, industrial production index of Vietnam (IIP VN) and
industrial production index of China (IIPCN). The table 5 illustrates
that all variables have a t-statistic greater than the critical value
at level. As the consequence, all variables have unit root or
nonstationary at level. On the contrary, at the first difference, all
variables have the t-statistic smaller than the critical value of 1%.
Therefore, all variables have not unit root or stationary at the first
difference.
To sum up, all variables nonstationary at level and stationary at
the first difference; therefore, they cointegrated at I(1). This is the
reason why Johansen (1988) procedure can be used to examine
the cointegration among these time series.
4.3. Optimal lags for VECM
Table 8 Lag selection of VECM
Criteria
Lags

Table 6 suggests that five criteria choose two lags differently, 1
and 8. Therefore, in this paper, all of lags were used for

conducting VECM. Choosing the best model is based on the
diagnostic check after running VECM.


314 | ICUEH2017

Table 7
Diagnostic check for every lag
Lags

Serial Correlation
1
8

+: good
-: not good

Table 7 presents the diagnostic check and normality test of 2
lags after conducting VECM. The most important of diagnostic
check is serial correlation. As table 7 illustrates, there is only lag 1
satisfied serial correlation and other tests as well. That is the
reason why conducting VECM with 1 lag is the best model.
Johansen procedure for cointegration test for the impact
of exchange rate on
trade balance
Because all variables are cointegrated at the first order I(1),
Johansen (1988) cointegration with 1 lag can be used to seek for the
long run relationship among variables.

Table 8
Johansen cointegration test with 1 lags

Number
of Ces

None
At most 1
At most 2
At most 3

Table 8 suggests the Johansen (1988) cointegration test. The
results indicate both Trace test and Eigenvalue test statistically
significant at 5% because the statistic is greater than the critical
value of 5%. As a result, the null hypothesis of r = 0 and r = 1 is
rejected. This implies at least 1 cointegration equations in the long


run or all variables have long run relationship. This model
concentrates on factors which effect on trade balance, for


Vo Thanh Thu & Tran Quoc Khanh
Cuong | 315

that reason first equation is focused on investigating the role of
the exchange rate in the
trade balance:
Table 9
VECM test with 1 lags

D(TB) = C(1)*( TB(-1) + 0.628543515991*RER(-1) 1.40013175523*IIPVN(-1) + 3.74657529993*IIPCN(-1)
- 5.24314357486 ) + C(2)*D(TB(-1)) + C(3)*D(RER(-1))
+ C(4)*D(IIPVN(-1)) + C(5)*D(IIPCN(-1)) + C(6)
C(1)
C(2)
C(3)
C(4)
C(5)
C(6)

Table 9 suggests the normalized cointegration coefficients.
TB = - 5.24 + 0.63*RER - 1.4*IIPVN + 3.75*IIPCN
The result indicates Q and IIPCN have positive sign, IIPVN has
the negative sign. These signs imply that:
The coefficient of real exchange rate is positive, for that reason,
trade balance increases 0.63 % when the depreciation of
Vietnam’s currency is 1%. The coefficient of IIPVN is negative,
thus trade balance would decrease 1.4% when GDP Vietnam
increase 1%. Finally, when GDP of China increases 1%, Vietnam
will take trade surplus 3.75%.
The impact of exchange rate on trade balance in long
run
Table 10
The speed of adjustment coefficient of long run
λ

Table 10 suggests the impact of exchange rate on trade balance
in the long run. The result indicates equals -0.22 and probability
equals 0.001. As a result, the relationship between exchange rate
and trade balance occurs in the long run, as well as IIPVN and IIP

China.


316 | ICUEH2017

The impact of independent variales in short run
Using Wald test to test the short run relationship between the
real exchange rate and trade balance:
Null hypothesis: µj = 0, (j = 1,p)

Alternative hypothesis: At least one µj ≠ 0.

Table 11

Wald test for the short run relationship
Variables
RER
IIPVN
IIPCN

Table 11 presents the probability of chi square for three
independent variables. The probability of IIPVN and IIPCN are
smaller than 5%. Therefore, the null hypothesis can be rejected,
which implies the relationship among the IIPVN, IIPCN and trade
balance occur in the short run. The coefficients state that when
IIPVN grows 1%, TB declines 0.89% while IIPCN grows 1%, TB
increases 1.55%
On the contrast, the probability of Q is 0.31 and larger than 5%.
Therefore, the null hypothesis cannot be rejected, which implies
the relationship between the real exchange rate and trade

balance does not occur in the short run.
In short, the robustness check of VECM with 1 lag is the best
model. The results indicate PPP hold between Vietnam and China,
based on this conclusion; Q is calculated through PPP approach.
There is the existence of the long run relationship between Vietnam
and China in the trade balance and the relationship does not happen
in the short run. Hence, ML condition holds and J curve does not exist
between two countries. Besides that, IIPVN and IIPCN affect on trade
balance in the short term and long term as well.

Finally, because ML condition holds between two countries,
Vietnam should devaluate its currency to cure the trade deficit.


Vo Thanh Thu & Tran Quoc Khanh
Cuong | 317

References
Akbostanci, E. (2004). Dynamics of the Trade Balance The Turkish J-Curve.
Emerging Market Finance and Trade, 40(5), 57 – 73. Retrieved from:
/>referrer=parent&backto=issue,4,5;journal,74,84;linkingpublicationresults,1:
111024,1
Arize, C. A. (1994). Cointegration Test of a Long-Run Relation between the Real
Effective Exchange Rate and the Trade Balance. International Economic
Journal, 8(3), 1-9. doi: 10.1080/10168739400000001
Arora, S., Bahmani-Oskooee, M. & Goswami, G. (2003). Bilateral J-curve
between India and her trading partners. Applied Economics, 35(9), 10371041. doi:10.1080/0003684032000102172
Asea, P. K. & Corden, W. M. (1994). The Balassa-Samuelson model: an overview.
Review of international
economics, 2(3), 191 – 200. doi: 10.1111/j.1467-9396.1994.tb00040.x

Assaf, A. (2006). Nonstationarity in real exchange rates using unit root tests
with a level shift at unknown time. International Review of Economics and
Finance, 17(2), 269–278. doi:10.1016/j.iref.2006.08.008
Bahmani-Oskooee, M. (1991). Is there a long run relation between trade
balance and real effective exchange rate of LDCs? Economics Letters, 36(4),
403 – 407. doi:10.1016/0165-1765(91)90206-Z
Balassa, B. (1964). The Purchasing-Power Parity doctrine: a reappraisal. Journal of
Political Economy, 72(6),

584 – 596. Retrieved from: />Basher, S. A. & M. Mohsin., 2004. PPP Tests in Cointegrated Panels: Evidence
from Asian Developing Countries. Applied Economics Letters, 11 (3), pp.163166.
Doğanlar, M. (2006). Long-run validity of purchasing power parity and
cointegration analysis for Central Asian countries. Applied Economics
Letters, 13, 457 – 461.
Doğanlar, M., H. Bal & M. Özmen (2009). Testing Long-Run Validity of
Purchasing Power Parity for Selected Emerging Market Economies. Applied
Economics Letters, 16 (14), 1443-1448.
Enders, W., Granger, C.W.J. (1998). Unit Root Tests and Asymmetric
Adjustmentwith an Example Using the Term Structure of Interest Rates.
Journal of Business and Economics Statistics, 16, 304–311.
Gomes, F. A. R. and L. S. Paz (2005). Can real exchange rate devaluation
improve trade balance? The 1990-1998 Brazilian case. Applied Economics
Letters, 12, 525-528.
Johansen, S. (1988). Statistical Analysis of Cointegrated Vectors. Journal of
Economic Dynamics and Control, 12(2-3), 231 -254. doi:10.1016/01651889(88)90041-3
Jovita G., 2016. Modelling and forecasting exchange rate. Lithuanian Journal of
Statistics, 55(1), pp.19 – 30.

Kim, H-G., 2011. VECM Estimations of the PPP Reversion Rate Revisited. Journal
of Macroeconomics. doi:

10.1016/j.jmacro.2011.10.004
Kim, H-G. & S. Y. Jei, 2013. Empirical Test for Purchasing Power Parity Using a
Time-Varying Parameter Model: Japan and Korea Cases. Applied Economics
Letters, 20 (6), pp.525-529.
Krugman, R. P., & Obstfeld, M., and Melitz, J. M (2012). Price levels and the
exchange rate in the long run.
In S. Yagan (Ed.), International Economics theory and policy, (pp. 385 – 386).
Pearson Education.


318 | ICUEH2017

Matesanz, D. & Fugarolas, G. (2009). Exchange rate policy and trade balance: a
cointegration analysis of the Argentine experience since 1962. Applied
Economics, 41(20), 2571-2582. doi: 10.1080/00036840701222660
Narayan, K. P. (2006). Examining the relationship between trade balance and
exchange rate: the case of China's trade with the USA. Applied Economics
Letters. 13(8), 507-510. doi: 10.1080/13504850500400488
Onafowara, O. (2003). Exchange rate and trade balance in East Asia: is there a J
curve?
Economics
Bulletin,
5(18),
1
–
13.
Retrieved
from:

/>Özkan, F. (2013). Comparing the forecasting performance of neural network and
purchasing power parity:

The case of Turkey. Economic Modelling, 31, 752–758.
doi:10.1016/j.econmod.2013.01.010
Rogoff, K. (1996). The Purchasing Parity Puzzle. Journal of Economic Literature,
34,
647
–
668.
Retrieved
from:
/>Rose, K. A. (1990). The role of exchange rates in a popular model of
international trade does the ‘Marshall-Lerner’ condition hold? Journal of
International
Economics,
30(34),
301
–
316.
doi:10.1016/00221996(91)90024-Z
Rose, K. A, & Yellen, L. J. (1998). Is there a J curve? Journal of Monetary
Economics, 24(1), 53 – 68. doi:
10.1016/0304-3932(89)90016-0
Stone, M. (2009). The role of exchange rate in inflation-targeting emerging
economies.
IMF
Occasional
Paper,
267.

Retrieved
from:
/>Shahbaz, M., Jalil, A. & Islam, F. (2012) Real Exchange Rate Changes and the
Trade Balance: The Evidence
from Pakistan. The International Trade Journal, 26(2), 139-153. doi:
10.1080/08853908.2012.657588
Shirvani, H. & Wilbratte, B. (1997). The Relationship between the Real
Exchange Rate and the Trade Balance: An Empirical Reassessment.
International
Economic
Journal.
11(1),
39-50.
doi:10.1080/10168739700000003
Yazgan, E. (2003). The Purchasing Power Parity Hypothesis for a High Inflation
Country: A Re-Examination of the Case of Turkey, Applied Economics Letters,
10 (3), 143-147