Triangular Causality and Controlling Parallel
Exchange Market
Bijan Bidabad[1]
Abstract
In
this paper, the triangular relationship of money, price, and foreign exchange
in a causality context are studied. It is concluded that regulating the
exchange rate by volume of liquidity in a period of less than a year is not
possible, but in annual and biannual analyses we can regulate the exchange rate
through controlling the liquidity. In other words, in the long run, the
exchange rate is affected by liquidity and price level, but in the short run,
the price level has only temporary effects on the exchange rate. The results of
the study show that: liquidity affects the exchange rate in the long run; price
affects the liquidity in the long run; in the long run, liquidity and exchange
rate affect prices.
�Our results show that injection of foreign
exchange into the parallel exchange market with different lags has little
effects with different directions on the exchange rate. The same result is true
for the relationship between liquidity and dollar rate. In other words, in
spite of the long run relationship between exchange rate and liquidity, we
cannot justify this relationship in the short run. The same is true with the
balance of payments position and exchange rate in the short run.
By
simulating the relationship between injecting (selling) foreign exchange in the
parallel exchange market, liquidity and the cumulative balance of payments all
with exchange rate, we can conclude that in the short run, regulating exchange
rate by instruments such as selling exchange in the parallel market or
controlling the liquidity is not possible, but in the long run, conducting
foreign exchange sale policy and controlling the liquidity and the balance of
payments position can control the exchange market.
Keywords: Foreign exchange, Money supply
targeting, Monetary policy, Market control, Exchange rate policy
1. Introduction
All
policies that are to somehow related to exchange rate control can be related to
exchange rate targeting, and most of the economic policies are to somehow
related to foreign exchange. But at this moment, we are focused on the supply
of foreign exchange for controlling the exchange rate. The generality of this
discussion is prevailing in exchange rate management policies, but here we only
study the open market policy conducted on foreign exchange by monetary
authorities in the parallel market. This policy is called �sale of foreign
exchange in the parallel (free) market� and was adopted for the period of 1989
to 2001.
In
general, it is clear that whenever governments try to control prices through
non-economic measures which are in confliction with supply and demand
mechanism, automatically a parallel market is developed. The emergence of the
parallel exchange market in the previous two decades is not exempted from this
general rule. Governments consider parallel markets as an obstacle for
implementing their policies, but we should accept that parallel markets are the
results of the government policies. In other words, whenever we do not follow
the inherent rules of economics, we should be waiting for the emergence
parallel market in the same field of policymaking.
Before
the revolution, the foreign exchange parallel market was negligible. Very few
amounts of foreign exchange were transacted in exchange offices at a price
which followed the exchange rate of the banking system, so these exchange
offices pegged their rates between of bid and offer rates of the banking rates.
In other words, their bid rate was a little more than the bid rate of the
banking system, and their offer rate was a little lower than the banking offer
rates. This method of pricing helped them to survive; in other words, their
profit margin was between the profit margins of the banks. After the revolution,
banks developed regulations on exchange sale, which was considered as a
restriction for the supply of foreign exchange. The restricted supply
practically pushed up the rates, but the government kept banking rates
unchanged, which caused to develop a parallel market with higher rates. Because
of the unordinary conditions of post-revolution, the gap between the parallel
market and banking rates widened. The government tried several times to control
this market with new regulations. The extent of these regulations went so far
to consider the dealers of the parallel market as trouble-makers, or economic
terrorists and heavy penalties were developed for them, and police and security
forces were used against this market, but the government had little success in eliminating
this market.
One
of the policies applied against this market was government interference in the
market by direct sale of foreign exchange in order to increase the supply and
decrease the parallel rates. This policy was conducted in several ways so that
the banking system also sold foreign exchange with special rates and
conditions. Sometimes the central bank gave official permissions to private
foreign exchange offices and sold foreign exchange through these offices. In
some exceptional cases, the brokers of the central bank sold foreign exchange
on the nearby main streets. These decisions were made on the bases of the
analysis of the decision makers of those days, but the main principle behind
these decisions was injecting foreign exchange into the market in order to
decrease the parallel rates and achieve income in Rial terms.
The
main precondition for applying this policy is the acceptance of an unofficial
foreign exchange market. In some years, the policymakers were so radical that
they considered the dealers of the parallel market as smugglers and punished
them very severely, which suggests that this policy was not developed very
well. We should accept that during the scarcity of foreign exchange supply with
fixed rate regime, this is a natural phenomenon, and the market mechanism
creates it automatically. The best method of dealing with this market is
accepting it for the first time. This means that we should legally accept the
transactions through this market and even consider it as an economic activity
and prevent any noise from it and in the next phase automatically try to
marginalize it by applying policies and adopting reforms in foreign exchange
management. If the foreign exchange system tends to unify, the management of
the system becomes transparent. In other words, all transactions of goods and
services should be done in single rates, and the rate of the parallel market
will, at last, be within the margins of official rate fluctuations.
Since
the prices of many items of goods and services are affected by the foreign
exchange rate in the parallel market and its fluctuations will cause the
fluctuation of the prices of goods and services, the stabilization of the
foreign exchange rate in the parallel market will cause partial stabilization
in goods and services market. The injections of foreign exchange into the
parallel market for stabilization will spillover into other markets.
After
the revolution in Iran, the volume of money in circulation has had an
increasing trend. Economic theories demonstrate that this increase will lead to
depreciation of money, in other words, when the volume of Rial is increased, we
should expect that the value of Rial is to be reduced against foreign
currencies, or its parity rate decreases. We have practically seen this event
in the past few decades. The increase of the volume of Rial from 2613 billion
in 1996 to 320957 billion Rials at the end of 2001 can be the main cause of the
increase of parity rate of American Dollar from 70 Rials to 8000 Rials. Econometric
researches also confirm this finding.
The
policy of selling foreign exchange in the parallel market not only increases
the supply of foreign exchange, but also decreases the amount Rial in the
market, both of which will strengthen the national currency. Most of the
increases of the amount of liquidity after the revolution have been the result
of the expansion of monetary base through the increases of government sector
debts to the banking system. The details of this phenomenon have been described
in several pieces of research, but here we consider that the mentioned results
are sufficient to be used and not to be retested. The increase of the
government sector�s debt to the banking system has been created through
financing budget deficit by borrowing from the banking system, which is similar
to seignorage of extra money by expanding the monetary base. The policy of
selling foreign exchange in the parallel market can be regarded as a method for
partially financing the budget deficit. In this way, the government can finance
the budget deficit by selling foreign exchange in the parallel market at
unofficial prices without obligation of borrowing from the banking system. In
other words, without increasing the liquidity (in spite of borrowing from the
banking system), this policy can finance the budget deficit.
Price
increase and inflation in Iran has a monetary source. Many studies confirm this
hypothesis. The increase in money supply causes an increase in general price
level instead of increasing the supply of goods and services in the economy.
Regarding this concept, it could be said that the policy of selling foreign
exchange in the parallel market will decrease the price level through the
decreasing foreign exchange rate which causes to decrease the price of imported
commodities which use foreign exchange from the parallel market sources, and
also through decrease of liquidity which has a deflationary effect.
After
the approval of the Usury-Free Banking Law, since bond has usury nature, it
cannot be applied as a policy tool for changing the amount of money in
circulation. In the western economies, central banks conduct open market
operations by buying and selling bonds, and decrease or increase the amount of
money in circulation and thereby, affect the interest rates and investment
thereafter. But as it was mentioned earlier, since it is not possible to use
bonds, it is not possible to conduct open market operations. The government
interference in the parallel exchange market affects liquidity, and if the government
buys, as well as selling foreign exchange in this market, these activities will
be more similar with open market operations, and therefore, it is possible to
affect interest rate in the parallel market by applying this policy. Of course,
this kind of operation is not completely in accordance with open market
operation, but when other monetary instruments are not efficient enough, or
applicable, this policy is of great help to monetary authorities.
After
this explanation, we return to the policy of selling foreign exchange in the
parallel market. This policy confirms the followings:
� The
parallel market is implicitly accepted
� It is
a step towards exchange rate unification
� It
helps to stabilize the rates of foreign exchange
� It
decreases the amount of available Rials, and thereof strengthens the national
currency
� It
can partially finance the budget deficit
� This
policy has deflationary effects
� �It can be regarded as a monetary tool for open
market operations
�������������������
In the macro-econometric model of Iran[2], the
effect of selling foreign exchange in the parallel market has been studied. The
calculations show that by selling foreign exchange equal to one thousand
billion Rials, the exchange rate of the parallel market decline will be 65
Rials.
2. Time series analysis
In this section, we test the time series for
stationarity, to be used in the next sections. The following variables have
been tested for unit root. All data are monthly series. Several tests such as
DF[3] and
ADF[4] have
been used, and by using correlogram, auto-correlation, and partial correlation,
the necessary differences were extracted to make the series stationary. Tests
have been carried out on the followings variables:
1.
Foreign exchange
rate
2.
Consumer price
index
3.
Liquidity (the
broad definition of money M2)
�According to the
studies, the following table has been prepared which shows the changes for
making the stationery of the variables
Variable �������������������������������������������������������Changes made to make the series
stationary�����������������
Exchange rate [D(DOLLAR)]������������������������ First order difference
Consumer price index [D(CPI)]���������������������� First order difference
Liquidity DLOGM2112=D(log(M2),1,12)���� First order difference and 12 months
difference on logarithm
After doing changes to make the series stationary, we
concluded that:
1.
The logarithm of
most of the series increases stationarity
2.
Some monetary
series and prices needed 12 months difference
3.
Therefore, the
following variables can be regarded as I(1)� variables
�
D(Log(Dollar), ,12)
�
D(Log(CPI), ,12)
�
D(Log(M2),
,12)
3. Causality between the main variables
The previous studies and the assumptions of the present
study are based on the tight relationship between monetary variables, foreign
exchange rate, and prices. In this section, we use causality tests on these
variables. In other words, we want to test the direction of the effect on the
foreign exchange rate by the monetary variable and general price level.
By the previous section, we found out the different
orders to make the necessary time series stationary. Now we use these results.
Before evaluating the causality between the variables, in order to find the
correct form of Granger relationship, we have to check for their
co-integration.
If the residual of long term regression of the two
variables are stationary, or in other words, they have not a unit root, the two
variables are co-integrated. If so, their simple difference will not be enough
for regression, and therefore, the model should be used as ECM[5].
Although this correction can explain the short variations of the model around
the long term trend by inserting an error item which has been obtained from the
long run equation, it adds its own problems to the model. For example, if the
specification of the model is not strictly supported by economic theory, the
results of the Error Correction Model will have conceptual problems.
4. Theoretical dynamic causality among variables
When we define a regression, we implicitly presuppose
that what variable or variables explain another variable which is defined as a
dependent variable. It means that we define the causality relationship in
which, by changing a variable, the dependent variable will change. This
causality relationship can be a one-way relationship or two ways. If X causes
Y, but Y has no effect on X, it is a one-way relationship. But if X
affects Y, and Y affects X, then we have a two-ways or polar relationship. One
of the methods for the causality test is the Granger test. This test is based
on this concept that the future cannot affect the past or the present time. The
test is a kind of VAR(k) test:
�
Upon the above equations, we can evaluate the following
different cases:
1.
If
2.
If
3.
If
To
test the above hypothesis, we use F statistics. This test will be carried out
after testing for stationarity and making variables stationary before further
use.
In
order to find the causality relationship between the main variables, the
triangle below is important. That is to say, we want to know which of the three
variables of the foreign exchange rate, price, and liquidity is the cause of
changes in other variables and how deep this effect is and then, find out which
variable works as a catalyst.
�������������� Liquidity
���������������������� Foreign exchange
rate��
5.Triangular Causality
To
solve the model, we explain the triangular causality relationship. We want to
know how the three variables, X, Y, and Z, affect each other. On the basis of
previous definitions, we define:
1. One
way chain relationship if:
a- X
affects Y
b- Y
does not affect X
c- Y
affects Z
d- Z
does not affect T
e- X
affects Z (through Y)
f-
Z does not affect Z
We
say that there is a one-way relationship from X to Y and to Z:
For
example, rain (X) increases water (Y), and water grows the plants (Z).
2. Two
to one, one-way relationship if:
a- X does
not affect Y
b- Y
affects X
c- X
affects Z
d- Z
does not affect X
e- Y
affects Z
f-
Z does not affect Y
We
say both X and Y affect Z:
������������
Y
For example, rain (X) and sunshine (Y)
cause plants (Z) grow.
3- Causality relationship with, or
without catalyst, if:
a- X affects Y
b- Y does not affect X
c- Y affects Z
d- Z does not affect Y
e- X affects Z (with, or without catalyst)
f- Z does not affect Z
We say that there is a one-way
relationship from X to Y and Z. That is to say:
�������������������� X
���������������������������������������� Z
��������������� Y
For
example, rain (X) causes the growth of plants (Z) and increase of humidity (Y),
and humidity (Y) also helps the growth of plants.
4-
Annular causality relationship, if:
�a- X affects
Y
�b- Y does not
affect X
�c- Y affects
Z
�d- Z does not
affect Y
�e- X does not
affect Z
�f- Z affects
X
�
�����������������������������
���������������� Y
For
example, income (X), causes investment (Y) and investment (Y) creates employment
(Z), and employment again creates more income (X).
5- Annular one-way causality relationship with
partial feedback, if:
a-
X affects Y
b-
Y does not affect X
c-
Y affects Z
d-
Z affects Y
e-
X affects Z (indirectly)
f-
Z does not affect X
6-
Annular causality relationship with complete feedback, if:
a-
X affects Y
b-
Y affects X
c-
Y affects Z
d-
Z affects Y
e-
X affects Z (indirectly)
f-
Z does not affect X (indirectly)
For
example, humidity (X) causes plants (Y) to grow, and the growth of plants
causes the increase of humidity (X). But the growth of plants (Y) creates
natural fertilizer (Z), and fertilizer causes more growth of plants (Y), and
the creation of natural fertilizer also directly increases the humidity (Z).
7- The
causality effect of one to two with one feedback, if:
a- ���X affects Y
b- Y
does not affect X
c- ���Y affects Z
d- Z
affects Y
e- ��X affects Z
f- ��Z does not affect X (directly)
������������� X
8- Causality effect of one on two (with
two feedbacks), if:
�����
a- X affects Y
�����
b- Y affects X
�����
c- Y affects Z
�����
d- Z affects Y
�����
e- X affects Z (directly)
�����
f- Z does not affect X (directly)
9- Annular causality effect with one
feedback, if:
������
a- X does not affect Y (directly)
������
b- Y affects X
������
c- T does not affect Z (directly)
���
���d- Z affects Y
������
e- X affects Z (directly)
�����
f-� Z affects X (directly)
�����������
�Z����������������������������� Y
10-
Annular causality with complete feedback, if:
a- X
affects Y (direct and indirectly)
b- Y
affects X (direct and indirectly)
c- Y
affects Z (direct and indirectly)
d- Z
affects Y (direct and indirectly)
e- X
affects Z (direct and indirectly)
f- Z
affects X (direct and indirectly)
������������������� �������X
� Z������������������ Y
6. The dynamic causality among variables (practical)�
Regarding
the mentioned cases in the previous section, by using the Granger
causality test, we test the variables two by two and with different lags. The
first group of tests includes testing causality among three variables in a
range of 1 to 24 lags:
The
second group of tests is similar to the first group with one difference that
the logarithms of variables are used instead of the original ones.
The
summary of the results of these tests is presented in the next tables and
diagrams. The table of F statistics defines the probability of accepting the
null hypothesis. This hypothesis is defined as follows:
H0:� The variable one is not the cause of the
second variable.
H1:
The variable one is the cause of the second variable.
If
the calculated F is greater than F in the table, we reject the null hypothesis,
and if the calculated F is smaller than F in the table, we accept the null
hypothesis.
The
following table gives F statistics for a large number of observations (more
than 120 in this case) and the degree of freedom of the denominator equal to 5
percent and 1 percent level of significance:
F
statistics for a number of observations over 120 and degree of freedom of
numerator (lag)
24 |
20 |
15 |
12 |
10 |
9 |
8 |
7 |
6 |
5 |
4 |
3 |
2 |
1 |
Lags |
1.52 |
1.57 |
1.67 |
1.75 |
1.83 |
1.88 |
1.94 |
2.01 |
2.10 |
2.21 |
2.37 |
2.60 |
3.00 |
3.84 |
5%
level of significance F |
1.79 |
1.88 |
2.04 |
2.18 |
2.32 |
2.41 |
2.51 |
2.64 |
2.80 |
3.02 |
3.32 |
3.78 |
4.61 |
6.63 |
1%
level of significance F |
���
By
considering the next tables and the graphs for a simple non-logarithmic model,
we conclude:
1- The
change in Dollar rate, after at least 1 month, will lead to a change in
liquidity.
2- The
change in liquidity will affect Dollar rate after 1 month, and its further
effects appear after 9 to 11 months and again after 2 years changes the Dollar
rate.
3- Changes
in prices affect liquidity after a lag of 8 months to 2 years.
4- Liquidity
changes will affect prices after 1 year.
5- Price
changes affect the Dollar rate after 1 month.
6- Changes
in Dollar rate affect CPI in every lag.
In
short, with the analysis of the above conclusions, at 95% of significance
level, we can draw the following diagram:
������������������������ ��������������With 3 to 5 months lag
Liquidity Dollar RATE Prices
����
���������������������� With 23 to 24 months lag
With
2 to 24 months lag
Always With
12 to 24 months lag After 9 to 24 months lag
��
The
same study regarding the logarithms of the variables gives the following
conclusions:
1-
Change of Dollar
rate affects liquidity after 3 to 5 months.
2-
Change of liquidity
does not affect the Dollar rate.
3-
Price changes after
3 months affect liquidity.
4-
Liquidity change
does not affect prices.
5-
Price changes after
6 to 11 months and also after 13 to 15 months causes changes in the Dollar
rate.
6-
Changes in Dollar
rate causes changes in prices after 11 months.
In short, the above conclusions can be shown at a 95% level of significance
in the diagram below
Liquidity Dollar Rate Prices
�������������������������������������������
With 3 to 5 months lag
After 3 months lag After 6 to 15 months lag
��������������������������������������������������������������������������������������
With 11 to 24 months lag
Adding up the above results, we can draw the following
diagram for short term analysis:
��� ������������������������������������������������������
The following diagram is for more than a year analysis:
�����������������������������������������������������������������
The above diagrams show that
foreign exchange rate cannot be regulated by changing liquidity in less than a
month, and the results show that only the general price level can affect this
variable. But in one to two years of analysis, the foreign exchange rate can be
regulated by liquidity control. In other words, the long run trend of the
foreign exchange rate is affected by liquidity and price level changes, but
since price changes have also short term effects on the foreign exchange rate,
therefore, we can change this hypothesis in error correction model as follows:
Foreign exchange rate = long
term function (price level, liquidity) + error
If in the first order
stationary condition of the three variables of the foreign exchange rate,
liquidity, and price level, the co-integrated regression creates stationary
error, we follow the error correction model.
After the study of the foreign
exchange rate, liquidity, and price index variables and making them stationary,
we follow the model with stationary variables. With the estimation of long-run
function, we realized that the existing co-linearity between liquidity and CPI,
practically the obtained weights are not as they were expected and therefore,
it is not possible to follow error correction model. On the basis of obtained
graphs and results for long-run effects, we consider the three following
relationships:
EQ1: DOLLAR=C(1)*M2+ C(2)*DUMMY8000 + C(3)*DUMMY8000*M2 +
C(4) + reseq1
EQ2: M2= C(11)*CPI+C(12)
+C(13)*DUMMY8000+C(14)*DUMMY8000*CPI+ reseq2
EQ3: CPI=
(C(21)+C(22)*DUMMY8000)*DOLLAR+(C(23)+C(24)*DUMMY8000)*M2�
���������������� +C(25)+ C(26) *DUMMY8000 +
reseq3
These equations show the mathematical
causality relationship between our variables. Regarding the existence of high
co-linearity between liquidity and price level, the price variable has been
omitted from the first equation. In order to consider the policies for fixing
Dollar rate at 8000 Rials, the dummy variable �dummy8000� has been introduced
into the model which affects the intercept, as well as the slope. The amount of
this dummy from the 11th month of 1998 and afterward is one, and for
other times is zero.
In order to study the co-integration and concluding
whether the mentioned relationships are long term relationships or not, we
regress the first order difference of the residuals of each regression to its
own lag. In this way, we conduct the unit root test. The results of these tests
with the study of MacKinnon show that all three equations have long term
nature. In other words:
� Liquidity affects the foreign exchange rate in the long
run.
� Prices affect liquidity in the long run.
� In the long run, both liquidity and Dollar rate affect
prices.
7. Selling foreign exchange
One of the variables which have not been used here is the
selling of foreign exchange in the parallel market. As it was mentioned, the
application of this policy can affect the monetary and exchange sectors of the
economy. Unfortunately, the monthly data for this variable is not available;
the annual data as budget information is available in the central bank reports.
These figures have been presented in the previous sections of this paper.
Studies show the relationship between this variable and the foreign exchange
rate in the parallel market. The Macro-econometric model of Iran[6]
shows that there is a significant relationship between selling foreign exchange
in the parallel market and Dollar rate in that market. The following
relationship has been defined in that model:
Dollar
rate=f(selling exchange in parallel market, liquidity, cumulative balance of
payments)
The above study showed that it is not possible to find a
significant relationship for the above function in the short run, even though
this function is statistically satisfactory. The reason for that is perhaps the
lack of monthly data series of selling foreign exchange for a long period. As
it was mentioned, there is a long term relationship between these variables; a
concrete short-run relationship has not been found. The cross-correlogram below
shows: selling foreign exchange with different lags has little effects with
different directions on the parity rate of Rial. The next graph shows the same
conclusion for the relationship between liquidity and Dollar rate. In other
words, in spite of the existence of the relationship in the long run, it is not
possible to define such a relationship in the short run. The same is understood
for the position of balance of payments and the foreign exchange rate in the
short run.
�
8. Conclusion
In this paper, our goal was to
find out the effects of changes in Money on the foreign exchange rate in the
short run and long run. In other words, we were looking to find out if we can
change foreign exchange rate by changing the liquidity? On the other hand, what
is the effect of the price, which has an important catalyst role in this
interaction? Therefore, we looked for the triangular relationship between
money, prices, and foreign exchange rate, through which we can reach foreign
exchange rate control policies.
Calculations show that regulating
foreign exchange rate by changing the amount of liquidity for a period of less
than one year is not possible, and only the general level of prices can affect
this variable. But in annual and biannual analysis, we can say that the control
of the foreign exchange rate can be achieved through changes in liquidity. In
other words, the long run trend of the foreign exchange rate is defined by
liquidity and price level, but prices have also short term effect on the Dollar
rate.
In the co-integration analysis,
we checked whether the above relationships are credible for the long run or
not. We concluded that:
� Liquidity
affects Dollar rate in the long run
� Prices
affect liquidity in the long run
� In
the long run, liquidity and Dollar rate affect the price level
The long-run analysis with annual
data shows that there is a significant relationship between selling foreign
exchange in the parallel market. In other words, the Dollar rate is a function
of the cumulative balance of payments, liquidity, and the amount of Dollar sold
in the parallel market. The short-run analysis of the relationships shows that
we cannot find a statistically significant relationship in this regard. In
other words, there is only a long-run relationship between the variables, and
there is not a clear short term relationship for them. The studies show that
selling Dollars in the market with different lags have small effects on the
Dollar rate in volatile directions. The same is true with the relationship of
Dollar rate and liquidity. That is to say, in spite of the existence of a
long-run relationship between Dollar rate and liquidity, we cannot find this
relationship for the short run. The same is true for the relationship between
the balance of payments and liquidity in the short run.
By simulation of the amount of
foreign exchange sold in the parallel market, liquidity, and cumulative balance
of payments with Dollar rate, we can conclude that controlling foreign exchange
rate in the short run by using tools such as selling foreign exchange in the
parallel market or controlling the liquidity is not possible, but in the long
run, by the policy of selling foreign exchange and controlling the liquidity
and the balance of payments, we can control the foreign exchange market.���
References
Bidabad, Bijan, General
monetary equilibrium. Lap Lambert Academic Publishing, OmniScriptum GmbH
& Co. KG, ISBN: 978-3-659-54045-5,
Spring 2014.
Bidabad, Bijan, Parallel
Exchange Market Control by Monetary Targeting and Complementary Policies.
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[1]
(B.A., M.Sc., Ph.D., Post-Doc.) Research Professor of Economics, Monetary and
Banking Research Academy,����� [email protected] ����[email protected]������ http://www.bidabad.com.
This paper is the summary of the
project: Bijan Bidabad, Parallel Exchange
Market Control by Monetary Targeting and Complementary Policies. Monetary and
Banking Research Academy, Central Bank of Iran, Tehran, Iran. http://www.bidabad.com/doc/exchange-control.pdf
http://www.bidabad.com/������������ [email protected] �����������[email protected]
[2] - Bidabad, 1996. Http://www.bidabad.com/
[3] - Dickey-Fuller.�
[4] - Augmented Dickey-Fuller.
[5] - Error Correction Model.
[6] - Bidabad, 1996. http://www.bidabad.com/