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                       Asian Finance & Banking Review; Vol. 3, No. 1; 2019 

                                       ISSN 2576-1161   E-ISSN 2576-1188 

Research Article               Published by Centre for Research on Islamic Banking & Finance and Business, USA 

 

     44 
 

Controlling Parallel Exchange Market by Monetary Targeting and 

Anti-Inflationary Policies 

 

Bijan Bidabad
1
 

Abstract 

In this paper, the triangular relationship between money, price, and foreign exchange 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 

 Prices affect 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 

Mixed monetary-exchange policy making is one of the important problems in macro-economic planning. If 

monetary and exchange policies are selected independently, one policy may neutralize the effects of the other, and 

other goals such as price stabilization may not be fulfilled. Therefore, selection of the mixed policies in this regard is 

one of the fundamental subjects in obtaining economic stabilization goals. For this reason, the present study will 

consider mixed policies of controlling liquidity and exchange rate for obtaining inflation control. Therefore, two 

major policies of monetary and exchange rate targeting are regarded as a base, and price stabilization policy is 

introduced from the mutual relationship of the two mixed policies. 

Since usually for applying a policy, we have to use only one instrument, controlling the general level of prices by 

one policy variable faces difficulty from a mathematical point of view because this means to solve an equation with 

two unknowns. The solution for unknown variables is achieved through a combination of possible solutions. 

Keeping this in mind, and regarding that our policy variable in this discussion is liquidity which has a direct effect 

on both our targeted exchange rate and targeted inflation rate variables, therefore, obtaining one target, 

automatically achieves the other target; but the only remaining problem is the effect on the second target is not as 

much as we wished a priori. In other words, it means that if liquidity decreases A percent, the decrease in the 

exchange rate and the inflation rate will be B percent and C percent respectively. Therefore, in order to reach target 

B, we can use the variable A, but the figure for C will be obligatory (automatically) defined. But since the targets 

                                                             
1 (B.A., M.Sc., Ph.D., Post-Doc.) Research Professor of Economics, Monetary and Banking Research Academy,      

.http://www.bidabad.com       bijan@bidabad.combidabad@yahoo.com     

http://www.bidabad.com/
mailto:bijan@bidabad.com


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45 
                           

have the same direction, reaching B is accompanied by somehow of reaching target C, which is not as much as the 

policymaker intended.  

In order to obtain predefined amounts for B and C, the policy variables should be increased to two. This means that 

we have to change simultaneously the two variables of liquidity and foreign exchange supply in order to control the 

two variables of the value of the national currency (exchange rate) and inflation rate. In this case, the number of 

instrumental variables is equal to the number of target variables, and the problem has a solution from a mathematical 

point of view. Therefore, we select two main lines for our study, which are practically based upon our two target 

variables. These two axes are as follows: 

 Inflation targeting policies 

 Exchange rate targeting policies 

 

Several surveys have been carried out about inflation targeting, and this policy is regarded as a recognized method 

for controlling inflation. The basis of this policy is using monetary instruments to control liquidity in order to 

achieve an optimum rate of inflation. The abstract of these concepts is presented by a joint paper of M. Mojarrad and 

B. Bidabad in 1997. There are many documented guidelines about targeting the exchange rate, which is described in 

the collection of trade and exchange rate policies of governments and central banks around the world for controlling 

the supply of foreign exchange. They are all somehow connected to the supply of foreign exchange, but in this 

paper, we will only consider the direct interference of the central bank as an instrument of foreign exchange supply 

control. 

2. Inflation targeting and monetary policy in Iran (IR) 

There are many discussions between economists about inflation with the meaning of a rapid and sustained increase 

in prices from its reasons and sources, its economic importance, its control and its effects on other economic 

variables points of view, which are not mentioned in this paper. There are also many studies in Iran about inflation, 

its causes, and effects. Most of these studies confirm that inflation in Iran is a monetary phenomenon, and other 

factors such as those concerning supply side, or cost-push inflation have fewer effects on the increase of general 

price level. More explicitly, we can say that although inflation sources of supply-side have had short-run effects on 

prices, in the long run, inflation in Iran has been demand pull2. On the basis of many studies, we can conclude that 

about 99% of long-run price changes were caused by the increase in liquidity. In other words, they confirm the 

monetary nature of inflation in the country and consider the control of liquidity as the only way for controlling 

inflation. Regarding different studies conducted in Iran, we realize that Monetary Transmission Mechanism which is 

the affecting method of monetary policy and liquidity on the real sector of the economy which almost has had no 

effects, because it couldn't create any motivation through decreasing the rate of interest of banking loans. In other 

words, liquidity can only affect the demand through price increases. This notion opens the way for Iran's 

policymakers in targeting inflation via controlling the liquidity without worrying about the depression of the supply 

side. In other words, now we can claim that the decrease in liquidity will not cause production decrease. It is clear 

that all these concepts are considered in the domain of long term analyses.  

Before recent five years plans, we practically didn’t have any targeting policy as in comparison with other countries 

for controlling the inflation but during first and second development plans of 1989-93 and 1995-1999; we observe 

some targeting for controlling the inflation. These targeting in the text of the plan's aims are specified as a defined 

rate of inflation as a target. 

We have some similarities with other countries in targeting. In general, the practices of other countries show that the 

targeting plan for controlling inflation is in the medium term framework. Regarding the goals of the first and second 

development plan, we see similar policies for medium-term goals. The second plan, which was arranged on the 

bases of the stability of internal and external sectors from the stability of prices and balance of payments points of 

view, had a target rate of 12.4% for the annual inflation rate. Of course, regarding the special position of our country 

from a dependency point of view on oil income and oil shocks and various international problems, it seems that if 

                                                             
2 - Komijani and Bidabad, 1990, 1991 and 1992. http://www.bidabad.com/ 

http://www.bidabad.com/


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46 
                           

this goal was set in a range which could cover the effects of foreign fluctuations, it would increase the credibility of 

targeting for controlling the inflation. In this regard, we can mention the deep affectability of monetary policy from 

fiscal policy and considering the experience of other countries for controlling inflation; this concept will be very 

important.    

In the third development plan, the views of the planners on economic problems were changed in general, and 

therefore, they didn’t use classic methods for planning in determining quantitative goals. That is why we can’t 

perceive their views on inflation targeting. The third plan was in general concerned about structural reforms and did 

not discuss the details of quantitative goals. 

Considering all above concepts, there is also another important principle in other countries which is considered as 

the reason for their success, and it is credibility, acceptability and the belief of private sector about targeting policies 

for controlling inflation for which unfortunately no important step has been taken about this concept in Iran. The 

other problem is the responsiveness of the monetary authorities to defined goals. It seems that the central bank 

should not surpass its legal authorities. Surpassing credit ceilings reduces the responsiveness of the central bank to 

the concerned authorities. Keeping these ceilings in other countries is strictly regarded by policymakers of other 

countries. If the central bank pursuit only ad hoc and day-to-day policies, it cannot achieve the predefined goals. 

It is also clear that in order to a complete success in conducting monetary policies, necessary conditions should be 

available so that all monetary tools could be used. The study of previous conditions and backgrounds shows that the 

central bank could not use some of her legal monetary instruments effectively. These include open market 

operations, discount window, reserve requirement ratio, and the interest rates of bank loans and credits. All these 

instruments could not be used thoroughly or partially because of their own reasons. 

3. Exchange rate targeting policy   

As it was mentioned, 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. 



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47 
                           

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 spill over 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 usuric 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 



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48 
                           

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 Rial, 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 

                     

Year sale of foreign exchange in the 

parallel market (Billion Rials) 

1982 0.00 

1983 5.70 

1984 34.50 

1985 88.70 

1986 17.90 

1987 87.00 

1988 141.50 

1989 744.30 

1990 2256.80 

1991 2510.70 

1992 4078.00 

1993 4775.00 

1994 0.00 

1995 2765.00 

1996 5407.00 

1997 10428.70 

1998 6021.90 

1999 18532.20 

2000 39323.50 

2001 52445.10 

 

The table above shows the amount of foreign exchange sold in the parallel market from 1982 to 2001.  Since the 

Central Bank has sold foreign exchange at different rates during this period, we have only the amounts in Rial term 

(not in Dollars). 



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49 
                           

In the macro-econometric model of Iran3, 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. 

4. The relationship between the exchange rate in the parallel market and liquidity  

Perhaps the most important and famous view about the method of defining the parity of exchange rate is to consider 

it as a price which is defined by the intersection of supply and demand of foreign exchange in the market. This view 

is regarded as the view of the balance of payments for determining the exchange rate because the supply and 

demand of foreign exchange is created through the transactions registered in the balance of payments. Balance of 

payments has two main different parts of current account and capital account. The current account includes the 

difference between imports and exports of goods and services and the net value of other received and payments such 

as compensations, gifts and etc. in connection with foreigners. If in this account imports exceed exports, it is said 

that the account is facing a deficit and vice versa. It is clear that this account is not necessarily always in balance. If 

this account is facing a deficit, it will be compensated by other accounts. This deficit means that the expenses abroad 

have been more than earnings from abroad. 

One way of compensating this deficit is by the use of the capital account. In other words, this deficit will be 

deducted from the existing capital, or some amount of capital equal with the deficit has been transferred out of the 

country, so that brings the balance of payments to the equilibrium position. If there are no other transactions in the 

capital account, in order to keep the balance of payments, we have to import foreign capital as much as a deficit in 

the form of foreign loans, or the decrease of foreign exchange reserves or investment permissions to foreigners, etc. 

In other words, if a country faces a deficit in the balance of payments, it means that the reserves and assets of the 

country have been decreased. The monetary view of the balance of payments with emphasize on capital account 

practically defines the role of the balance of payments in determining the exchange rate. In simpler words, this view 

says that when the balance of payments is facing a deficit, the foreign assets will decrease equally. The importers go 

to the foreign exchange market according to their previous demand function, but since the supply of foreign 

exchange has been decreased as much as the deficit of balance of payments, the exchange rate increases. This 

increases the price of imported goods and therefore, decreases the demand for import; moreover, since export has 

become more profitable, exports will increase and leads to a new balance of payments and new exchange rate.        

Here, the important thing is the amount of demand for import and the supply of export which specify this 

mechanism. Both of these functions are the result of domestic and external prices. In other words, whenever external 

prices do not change, and internal prices increase, the demand for import increases, and the supply for export 

decreases. These changes in import and export, through changes in the balance of payments and changes in the 

amount of foreign reserves, will cause changes in the foreign exchange rate. In other words, when domestic prices 

increase, the purchasing power decreases, but the demand for imported goods increases in comparison with domestic 

goods, which has now a higher price. Practically this situation causes an increase in the foreign exchange rate. An 

increase in the supply of national money has also a similar effect on the demand for the foreign exchange rate in the 

same way. The increase in national money supply will increase gross domestic expenditures, and domestic prices 

and the demand for imported goods will increase, and exports will decrease. Because as it was mentioned before, the 

demand for imports and the supply of exports are functions of domestic and external prices. The increase in demand 

for imports and the decline in the supply of exports will lead to a balance of payments deficit, which means an 

increase in demand for foreign currency because of the import increase. The interaction between the national 

currency and foreign exchange in the market for exchanging national money into the foreign exchange will 

ultimately lead to the increase of foreign exchange rate. In the second round, this increase will lead to the adjustment 

of the balance of payments and with higher prices and a higher rate of foreign exchange; a new equilibrium will be 

achieved in the economy. This phenomenon has been prevailing in the economy of Iran after the revolution. The 

permanent increase in the money supply has practically increased domestic prices and has decreased the purchasing 

power and caused the devaluation of the national currency. Several pieces of research confirm this phenomenon4. 

                                                             
3 - Bidabad, 1996. http://www.bidabad.com/  
4 - Komijani and Bidabad, 1990, 1991, and 1992. http://www.bidabad.com/ 

http://www.bidabad.com/
http://www.bidabad.com/


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50 
                           

There are also several papers showing that the permanent increase in the supply of money has caused the slow to 

lose the value of the national currency5. In these papers, an econometric model for Iran has been evaluated, and this 

hypothesis has been tested. Unfortunately, because of poor data available about the balance of payments, testing this 

hypothesis faces difficulties. Some of the problems of the balance of payments data have been described in annual 

economic reports of the Central Bank and papers written by the author in 1994 and 1995. In the research carried out 

by the author and Komijani (1992), the relationship of Dollar rate in the parallel market and balance of payments has 

been shown through econometric models. These researches show the strong descriptive effect of the balance of 

payments variable on the variations of the foreign exchange rate in the parallel market. But in spite of these 

confirmations, because of data problems of the balance of payments, the calculation results are very sensitive to 

every single year data, and by increasing or decreasing a single observation, the results of calculations will change 

very much.  

In the continuation of the above-mentioned researches about the testing this hypothesis whether the continuous 

increase in the parity rate of Dollar with Rial in the parallel market is because of the increase of liquidity, various 

calculations have been carried out6. This calculation shows that by an increase of one trillion Rial of liquidity, the 

exchange rate in the parallel market increases 37.5 Rials. The results of the regression of this calculation describe 96 

percent of the variations. That is to say, that 96 percent of the changes in the foreign exchange rate in the parallel 

market is due to the increase in liquidity.  

Sometimes, economic analysts doubt that the increase of foreign exchange rate is the cause of the increase in 

liquidity and prices. In this regard, they believe that external shocks in the foreign exchange revenues are practically 

the reason for this increase, or the devaluation policy of the government has increased liquidity and prices.  

In order to check the direction of causality, we conduct the following test. The aim of this test is first to find out 

whether the increase in the foreign exchange rate has caused an increase in liquidity? Secondly, is it true that the 

increase in the foreign exchange rate has caused prices to increase? In other words, which one is the cause and 

which one is the effect? To do this, Granger-Sims causality test has been carried out on monthly data. First, we test 

the causality of liquidity and the rate of foreign exchange in the parallel market. Then we test the causality of 

liquidity and price level. This shows that price level is not the main reason for the increase of liquidity, while, the 

increase of liquidity is the main source of the general price increase.   

In short, from the above discussions, we conclude that the increase of liquidity not only increases the price level in 

Iran but also has caused an increase in the foreign exchange rate. In other words, the increase of liquidity in the 

country is the cause of decreasing the purchasing power of the national currency, and the decrease of parity rate of 

Rial against foreign exchanges. Therefore, the only way for stabilizing exchange rate is the controlling of liquidity. 

Otherwise, other temporary policies such as those conducted in the previous two decades, are not considered proper 

policies, because although those policies could have positive effects on the market, in the long run, will ruin the 

infrastructure for investment7. Therefore, considering the above discussions, the foreign exchange market should be 

controlled through mixed exchange and monetary policies. 

5. 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 DF8 and ADF9 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: 

 Foreign Exchange Rate 
 Consumer Price Index 

                                                             
5 - Komijani and Bidabad, 1992, and Bidabad, 1994. http://www.bidabad.com/ 
6 - Bidabad, 1994. http://www.bidabad.com/ 
7 - Economic security and obstacles facing investment (Bidabad, 1995). http://www.bidabad.com/ 
8 - Dickey-Fuller. 
9 - Augmented Dickey-Fuller. 

http://www.bidabad.com/
http://www.bidabad.com/
http://www.bidabad.com/


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51 
                           

 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: 

 The logarithm of most of the series increases stationarity 

 Some monetary series and prices needed 12 months difference 

 Therefore, the following variables can be regarded as I(1)  variables 

 D(Log(Dollar), ,12) 

 D(Log(CPI), ,12) 

 D(Log(M2), ,12) 

 

6. 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 ECM10. 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. 

7. 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 the 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 can not affect the past or the present time. The test is a kind of VAR(k) test: 

 

tjt

K

j

jjt

X

j

jt

tjt

k

j

jjt

k

i

ijt

eYXaX

eYXaY

2

1

2

1

220

1

1

1

1

10





























   

                                                             
10 - Error Correction Model. 



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52 
                           

Upon the above equations, we can evaluate the following different cases: 

1. If  11 12 1, , ... , 0k    and 21 22 2{ , ,..., } 0k    , there is a one-way causality relationship from X 

to Y. 

2. If  11 12 1, , ... , 0k     and 21 22 2{ , ,..., } 0k    , there is a one-way causality relationship 

from Y to X.  

3. If   0,...,, 11211 k and 21 22 2{ , ,..., } 0k    , there is a two ways causality relationship 

between Y and X. 

In order 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.  

8. 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 first order difference of Dollar rate series with 12 months seasonal adjustment       (ddollar) 

 The first order difference of liquidity with 12 months of seasonal adjustment (dm2112) 

  The first order difference of consumer price index with 12 months seasonal adjustment (dcpi112) 

 

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: 

 The change in Dollar rate, after at least 1 month, will lead to a change in liquidity. 

  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. 

 Changes in prices affect liquidity after a lag of 8 months to 2 years. 

 Liquidity changes will affect prices after 1 year. 



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53 
                           

With 12 to 24 

months lag After 9 to 24 

months lag 

With 2 to 24 

months lag 

Always 

 Price changes affect the Dollar rate after 1 month. 

 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 

 

      

                       With 23 to 24 months lag  

 

                              

 

 

 

 

 

     

 

Simple F-Statistics 

Number 

of Lags 

ddollar112 

does not 

Granger 

cause 

dm2112 

dm2112 

does not 

Granger 

cause 

ddollar112 

dcpi112 

does not 

Granger 

cause 

dm2112 

dm2112 

does not 

Granger 

cause 

dcpi112 

dcpi112 

does not 

Granger 

cause 

ddollar112 

ddollar112 

does not 

Granger 

cause 

dcpi112 

1 2.754 3.292 0.148 0.250 2.257 6.882 

2 3.980 1.220 0.268 0.784 8.270 4.553 

3 6.872 1.444 0.071 0.459 5.796 2.950 

4 5.729 0.857 0.868 0.356 4.901 3.784 

5 4.883 1.116 1.408 1.157 6.056 3.440 

6 4.091 1.626 1.285 1.291 5.095 3.334 

7 4.776 1.379 1.302 1.267 5.383 4.325 

8 4.221 1.150 1.347 0.961 5.225 3.775 

9 4.345 1.780 3.038 0.930 4.265 4.127 

10 4.244 1.747 2.715 0.818 3.790 3.657 

11 3.918 1.649 2.496 1.175 3.367 4.448 

12 3.700 0.742 2.176 1.859 2.456 2.577 

13 3.403 0.694 2.137 1.863 2.335 2.509 

14 3.157 0.671 2.036 2.014 2.473 2.339 

15 2.780 0.637 2.075 1.739 2.198 2.622 

16 2.541 0.696 2.173 1.959 2.232 2.250 

17 2.505 0.715 2.197 1.849 2.107 2.102 

Liquidity Dollar RATE 

Prices 



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54 
                           

18 2.345 0.801 2.433 1.815 2.227 2.057 

19 2.294 0.943 2.546 1.699 2.095 1.992 

20 2.320 1.097 2.382 1.558 1.998 1.852 

21 2.419 1.050 1.997 1.629 2.063 1.866 

22 2.753 1.142 1.801 1.628 2.185 1.907 

23 2.500 1.620 1.732 1.640 2.190 1.862 

24 2.363 1.633 1.634 1.697 1.591 1.597 

 

 

 

Simple Probability 

Number 

of Lags 

ddollar11

2 does not 

Granger 

cause 

dm2112 

dm2112 

does not 

Granger 

cause 

ddollar112 

dcpi112 

does not 

Granger 

cause 

dm2112 

dm2112 

does not 

Granger 

cause 

dcpi112 

dcpi112 

does not 

Granger 

cause 

ddollar112 

ddollar11

2 does not 

Granger 

cause 

dcpi112 

1 0.098 0.071 0.700 0.617 0.134 0.009 

2 0.020 0.297 0.764 0.457 0.000 0.011 

3 0.000 0.231 0.975 0.710 0.000 0.034 

4 0.000 0.490 0.483 0.839 0.000 0.005 

5 0.000 0.353 0.223 0.332 0.000 0.005 

6 0.000 0.143 0.266 0.263 0.000 0.004 

7 0.000 0.217 0.251 0.268 0.000 0.000 

8 0.000 0.333 0.222 0.467 0.000 0.000 

9 0.000 0.076 0.002 0.499 0.000 0.000 

10 0.000 0.075 0.004 0.611 0.000 0.000 

11 0.000 0.091 0.006 0.307 0.000 0.000 

12 0.000 0.707 0.014 0.042 0.006 0.004 

13 0.000 0.766 0.014 0.037 0.007 0.004 

14 0.000 0.799 0.017 0.019 0.003 0.006 

15 0.000 0.839 0.013 0.048 0.009 0.001 

16 0.001 0.793 0.007 0.018 0.006 0.006 

Simple

0.000

1.000

2.000

3.000

4.000

5.000

6.000

7.000

8.000

9.000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Lags

F 
st

at
is

tic

ddollar112 does not Granger cause dm2112

dm2112 does not Granger cause ddollar112

dcpi112 does not Granger cause dm2112

dm2112 does not Granger cause dcpi112

dcpi112 does not Granger cause ddollar112

ddollar112 does not Granger cause dcpi112



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55 
                           

17 0.001 0.782 0.006 0.026 0.010 0.010 

18 0.003 0.695 0.001 0.027 0.005 0.011 

19 0.003 0.531 0.000 0.041 0.008 0.013 

20 0.002 0.361 0.001 0.070 0.011 0.022 

21 0.001 0.411 0.009 0.049 0.008 0.019 

22 0.000 0.314 0.021 0.047 0.004 0.015 

23 0.000 0.051 0.027 0.042 0.003 0.017 

24 0.001 0.047 0.041 0.030 0.056 0.055 

 

The same study regarding the logarithms of the variables gives the following conclusions: 

 Change of Dollar rate affects liquidity after 3 to 5 months. 

 Change of liquidity does not affect the Dollar rate. 

 Price changes after 3 months affect liquidity. 

 Liquidity change does not affect prices. 

 Price changes after 6 to 11 months and also after 13 to 15 months causes changes in the Dollar rate. 
 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: 

 

                                            With 3 to 5 months lag 

 

 

 

 

                                                                                        

 

 

 

Simple

0.000

0.200

0.400

0.600

0.800

1.000

1.200

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Lags

Pr
ob

ab
ili

ty

ddollar112 does not Granger cause dm2112

dm2112 does not Granger cause ddollar112

dcpi112 does not Granger cause dm2112

dm2112 does not Granger cause dcpi112

dcpi112 does not Granger cause ddollar112

ddollar112 does not Granger cause dcpi112

Liquidity Dollar 

rate  

Prices 



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56 
                           

 

Log F-Statistics 

No. 

of 

Lags 

Dlogdollar112 

does not 

Granger 

cause 

dlogm2112 

dlogm2112 

does not 

Granger 

cause 

dlogdollar112 

dlogcpi112 

does not 

Granger 

cause 

dlogm2112 

dlogm2112 

does not 

Granger 

cause 

dlogcpi112 

dlogcpi112 

does not 

Granger 

cause 

dlogdollar112 

dlogdollar112 

does not 

Granger 

cause 

dlogcpi112 

1 0.640 0.025 3.308 0.374 0.441 0.274 

2 1.910 1.789 1.586 0.226 0.273 1.323 

3 4.043 1.127 2.737 0.405 1.006 1.093 

4 3.175 0.814 2.097 0.341 0.686 0.879 

5 2.397 1.061 1.734 0.923 1.811 1.007 

6 1.966 0.972 1.408 0.763 2.467 1.271 

7 1.809 0.959 1.351 0.643 2.368 1.007 

8 1.614 0.945 1.166 0.527 2.274 0.920 

9 1.752 0.921 1.552 0.570 2.102 0.836 

10 1.544 1.029 1.393 0.629 2.449 0.881 

11 1.425 1.661 1.263 0.917 2.120 2.077 

12 0.875 0.874 0.826 0.413 1.455 1.519 

13 0.742 0.796 0.851 0.385 1.920 2.059 

14 0.660 0.722 0.697 0.483 1.823 1.819 

15 0.644 0.731 0.721 0.475 2.180 2.779 

16 0.593 0.823 0.780 0.540 1.555 2.759 

17 0.698 0.773 0.855 0.480 1.475 2.558 

18 0.720 0.769 0.910 0.560 1.580 2.193 

19 0.693 0.854 0.854 0.559 1.521 2.185 

20 0.687 0.816 0.834 0.559 1.383 2.114 

21 0.712 0.777 0.805 0.584 1.323 2.126 

22 0.701 0.761 0.814 0.602 1.323 2.379 

23 0.595 0.752 0.914 0.541 1.509 2.569 

24 0.599 0.840 0.796 0.561 0.965 2.398 

 

 

Logarithm

0.000

0.500

1.000

1.500

2.000

2.500

3.000

3.500

4.000

4.500

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Lags

F s
tat

ist
ics

dlogdollar112 does not Granger cause dlogm2112

dlogm2112 does not Granger cause dlogdollar112

dlogcpi112 does not Granger cause dlogm2112

dlogm2112 does not Granger cause dlogcpi112

dlogcpi112 does not Granger cause dlogdollar112

dlogdollar112 does not Granger cause dlogcpi112



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57 
                           

 

 

 

Logarithm

0.000

0.200

0.400

0.600

0.800

1.000

1.200

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Lags

Pr
ob

ab
ili

ty

dlogdollar112 does not Granger cause dlogm2112

dlogm2112 does not Granger cause dlogdollar112

dlogcpi112 does not Granger cause dlogm2112

dlogm2112 does not Granger cause dlogcpi112

dlogcpi112 does not Granger cause dlogdollar112

dlogdollar112 does not Granger cause dlogcpi112

Log Probability 

No. 

of 

Lags 

dlogdollar112 

does not 

Granger 

cause 

dlogm2112 

dlogm2112 

does not 

Granger 

cause 

dlogdollar112 

dlogcpi112 

does not 

Granger 

cause 

dlogm2112 

dlogm2112 

does not 

Granger 

cause 

dlogcpi112 

dlogcpi112 

does not 

Granger 

cause 

dlogdollar112 

dlogdollar112 

does not 

Granger 

cause 

dlogcpi112 

1 0.424 0.872 0.070 0.541 0.507 0.600 

2 0.151 0.170 0.207 0.797 0.761 0.268 

3 0.008 0.339 0.044 0.749 0.391 0.353 

4 0.015 0.517 0.082 0.849 0.602 0.477 

5 0.039 0.383 0.128 0.467 0.113 0.415 

6 0.073 0.445 0.213 0.599 0.026 0.273 

7 0.088 0.462 0.228 0.719 0.025 0.427 

8 0.124 0.480 0.321 0.834 0.025 0.501 

9 0.081 0.507 0.133 0.819 0.032 0.583 

10 0.129 0.421 0.186 0.787 0.009 0.552 

11 0.167 0.087 0.249 0.525 0.022 0.025 

12 0.573 0.573 0.623 0.956 0.147 0.123 

13 0.718 0.663 0.604 0.973 0.032 0.020 

14 0.808 0.748 0.774 0.939 0.040 0.041 

15 0.833 0.748 0.759 0.950 0.009 0.000 

16 0.884 0.656 0.705 0.921 0.090 0.000 

17 0.799 0.720 0.627 0.958 0.113 0.001 

18 0.784 0.732 0.566 0.922 0.075 0.006 

19 0.819 0.638 0.638 0.929 0.089 0.005 

20 0.831 0.689 0.669 0.934 0.143 0.007 

21 0.812 0.740 0.709 0.923 0.174 0.006 

22 0.829 0.764 0.703 0.917 0.172 0.001 

23 0.923 0.781 0.579 0.956 0.082 0.000 

24 0.925 0.678 0.736 0.949 0.516 0.001 



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58 
                           

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 11 th 



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59 
                           

month of 1998 and afterward is one, and for other times is zero. The long term regression results regarding the 

structural changes in foreign exchange rates and graphs are presented on the next pages. 

 

Dependent Variable: DOLLAR 

Method: Least Squares 

Sample(adjusted): 1365:01 1380:12 

Included observations: 192 after adjusting endpoints 

DOLLAR=C(1)*M2+C(2)*DUMMY8000+C(3)*DUMMY8000*M2+C(4) 

 Coefficient Std. Error t-Statistic Prob.   

C(1) 0.039448 0.000673 58.65213 0.0000 

C(2) 8738.370 269.5357 32.42008 0.0000 

C(3) -0.043906 0.001354 -32.42936 0.0000 

C(4) 511.6349 43.06389 11.88083 0.0000 

R-squared 0.984707     Mean dependent var 3590.353 

Adjusted R-squared 0.984463     S.D. dependent var 2774.293 

S.E. of regression 345.8132     Akaike info criterion 14.55029 

Sum squared resid 22482313     Schwarz criterion 14.61815 

Log-likelihood -1392.828     Durbin-Watson stat 0.358974 

 

 
 

Dependent Variable: M2 

Method: Least Squares 

Sample(adjusted): 1365:01 1380:12 

Included observations: 192 after adjusting endpoints 

M2=C(11)*CPI+C(12)+C(13)*DUMMY8000+C(14)*DUMMY8000*CPI 

 Coefficien

t 

Std. Error t-Statistic Prob.   

C(11) 1194.194 14.32809 83.34637 0.0000 

C(12) -2595.321 790.6147 -3.282662 0.0012 

C(13) -212425.6 9423.653 -22.54175 0.0000 

C(14) 1565.863 60.77294 25.76579 0.0000 

R-squared 0.994373     Mean dependent var 82963.88 

Adjusted R-squared 0.994283     S.D. dependent var 81166.19 

S.E. of regression 6137.162     Akaike info criterion 20.30273 

Sum squared resid 7.08E+09     Schwarz criterion 20.37059 

Log-likelihood -1945.062     Durbin-Watson stat 0.295806 

 

-1000

0

1000

2000

3000

0

2000

4000

6000

8000

10000

66 68 70 72 74 76 78 80

Residual Actual Fitted



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60 
                           

 
 

Dependent Variable: CPI 

Method: Least Squares 

Sample(adjusted): 1365:01 1380:12 

Included observations: 192 after adjusting endpoints 

CPI=(C(21)+C(22)*DUMMY8000)*DOLLAR+(C(23)+C(24) 

        *DUMMY8000)*M2+C(25)+C(26)*DUMMY8000 

 Coefficien

t 

Std. Error t-Statistic Prob.   

C(21) 0.006521 0.000650 10.02795 0.0000 

C(22) -0.007401 0.001988 -3.722975 0.0003 

C(23) 0.000572 2.63E-05 21.75495 0.0000 

C(24) -0.000231 2.93E-05 -7.896540 0.0000 

C(25) -0.741588 0.492289 -1.506408 0.1337 

C(26) 90.81921 17.52777 5.181447 0.0000 

R-squared 0.997358     Mean dependent var 65.82188 

Adjusted R-squared 0.997287     S.D. dependent var 55.94090 

S.E. of regression 2.913712     Akaike info criterion 5.007484 

Sum squared resid 1579.087     Schwarz criterion 5.109281 

Log-likelihood -474.7185     Durbin-Watson stat 0.290870 

 

 
 

 

-20000

-10000

0

10000

20000

30000

0

100000

200000

300000

400000

66 68 70 72 74 76 78 80

Residual Actual Fitted

-15

-10

-5

0

5

10

0

50

100

150

200

66 68 70 72 74 76 78 80

Residual Actual Fitted

0

40

80

120

160

200

0 100000 200000 300000 400000

Liquidity

C
on

su
m

er
 P

ric
e 

In
de

x

0

2000

4000

6000

8000

10000

0 100000 200000 300000 400000

Liquidity

D
o

lla
r 

R
ia

l e
xc

h
a

n
g

e
 r

a
te

0

40

80

120

160

200

0 5000 10000

Dollar Rial exchange rate

Co
ns

um
er

 P
ric

e 
In

de
x



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61 
                           

9. Further study of co-integration 

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. This study is shown in the next graphs. 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. 
 

Dependent Variable: D(RESEQ1) 

Method: Least Squares 

Sample(adjusted): 1365:02 1380:12 

Included observations: 191 after adjusting endpoints 

Variable Coefficien

t 

Std. Error t-Statistic Prob.   

RESEQ1(-1) -0.179557 0.041502 -4.326501 0.0000 

R-squared 0.089617     Mean dependent var 1.756606 

Adjusted R-squared 0.089617     S.D. dependent var 206.0912 

S.E. of regression 196.6398     Akaike info criterion 13.40585 

Sum squared resid 7346772.     Schwarz criterion 13.42287 

Log-likelihood -1279.258     Durbin-Watson stat 1.546716 

 

 
 

Dependent Variable: D(RESEQ2) 

Method: Least Squares 

Sample(adjusted): 1365:02 1380:12 

Included observations: 191 after adjusting endpoints 

Variable Coefficien
t 

Std. Error t-Statistic Prob.   

RESEQ2(-1) -0.137304 0.038807 -3.538106 0.0005 

R-squared 0.061448     Mean dependent var 65.24131 

Adjusted R-squared 0.061448     S.D. dependent var 3319.627 

S.E. of regression 3216.017     Akaike info criterion 18.99490 

Sum squared resid 1.97E+09     Schwarz criterion 19.01192 

Log-likelihood -1813.013     Durbin-Watson stat 2.149772 

 

-1200

-800

-400

0

400

800

1200

-1500

-1000

-500

0

500

1000

66 68 70 72 74 76 78 80

Residual Actual Fitted



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62 
                           

 
Dependent Variable: D(RESEQ3) 

Method: Least Squares 

Sample(adjusted): 1365:02 1380:12 

Included observations: 191 after adjusting endpoints 

Variable Coefficien

t 

Std. Error t-Statistic Prob.   

RESEQ3(-1) -0.143351 0.037861 -3.786216 0.0002 

R-squared 0.070105     Mean dependent var -

0.011469 

Adjusted R-squared 0.070105     S.D. dependent var 1.554762 

S.E. of regression 1.499273     Akaike info criterion 3.653060 

Sum squared resid 427.0858     Schwarz criterion 3.670087 

Log-likelihood -347.8672     Durbin-Watson stat 2.238935 

 

 
10. 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 Iran11 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 

                                                             
11 - Bidabad, 1996. http://www.bidabad.com/ 

-20000

-10000

0

10000

20000

-20000

-10000

0

10000

20000

66 68 70 72 74 76 78 80

Residual Actual Fitted

-8

-4

0

4

8

-8

-4

0

4

8

66 68 70 72 74 76 78 80

Residual Actual Fitted

http://www.bidabad.com/


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63 
                           

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 a 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, which is 

shown in the next table.           

   

Sample: 1365:01 1381:12 

Included observations: 67 

Correlations are asymptotically consistent approximations 

D(DOLLAR),D(DOLLARSAL
E)(-i) 

D(DOLLAR),D(DOLLARSAL
E)(+i) 

i   lag  lead 

         .*| .       |          .*| .       | 0 -
0.140

7 

-
0.140

7 

         . | .       |          . | .       | 1 -

0.026

9 

-

0.038

1 

         . |*.       |          . | .       | 2 0.074

5 

-

0.011

0 

         . | .       |          . |*.       | 3 -

0.010

9 

0.107

9 

         .*| .       |          .*| .       | 4 -

0.045

4 

-

0.101

7 

         .*| .       |          .*| .       | 5 -

0.136

5 

-

0.067

5 

         . | .       |          . |*.       | 6 0.047

5 

0.064

1 

         .*| .       |          .*| .       | 7 -

0.105
3 

-

0.063
2 

         . |*.       |          . | .       | 8 0.108
4 

0.019
0 

         . | .       |          .*| .       | 9 0.028

0 

-

0.108

1 

         **| .       |          .*| .       | 1

0 

-

0.204

8 

-

0.078

9 

         . |*.       |          . | .       | 1

1 

0.114

2 

-

0.027

1 

         . |**       |          . |*.       | 1

2 

0.160

5 

0.050

1 

         . | .       |          . | .       | 1

3 

0.000

5 

0.031

6 

         .*| .       |          **| .       | 1

4 

-

0.065

-

0.165



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64 
                           

5 0 

         . | .       |          . | .       | 1

5 

0.021

8 

-

0.000

1 

         . |*.       |          .*| .       | 1

6 

0.126

6 

-

0.047

6 

         . |*.       |          .*| .       | 1

7 

0.055

0 

-

0.068

9 

         . | .       |          . |*.       | 1

8 

0.008

6 

0.074

7 

         . | .       |          **| .       | 1

9 

-

0.028

8 

-

0.189

2 

         . | .       |          .*| .       | 2

0 

-

0.000

4 

-

0.074

6 

         . | .       |          .*| .       | 2
1 

0.032
4 

-
0.095

7 

         . |*.       |          . |*.       | 2

2 

0.067

8 

0.099

3 

         . | .       |          . |*.       | 2

3 

0.038

7 

0.050

0 

         .*| .       |          **| .       | 2

4 

-

0.044

0 

-

0.192

8 

         . | .       |          .*| .       | 2

5 

0.002

5 

-

0.129

9 

         . |*.       |          . | .       | 2

6 

0.090

9 

-

0.006

9 

         . | .       |          . |*.       | 2

7 

0.008

6 

0.123

6 

         . | .       |          **| .       | 2

8 

0.011

2 

-

0.153

3 

 

Sample: 1365:01 1381:12 

Included observations: 203 

Correlations are asymptotically consistent approximations 

D(DOLLAR),D(M2)(-i) D(DOLLAR),D(M2)(+i) i   lag  lead 

          *|.        |           *|.        | 0 -

0.063

7 

-

0.063

7 

          .|.        |           *|.        | 1 -

0.003

2 

-

0.104

6 

          .|*        |           .|.        | 2 0.073

5 

0.029

0 

          .|.        |           .|*        | 3 0.001 0.094



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65 
                           

8 5 

          *|.        |           *|.        | 4 -

0.042

7 

-

0.079

5 

          .|.        |           .|.        | 5 -

0.039

4 

-

0.022

8 

          .|.        |           .|.        | 6 -

0.011

6 

0.021

5 

          *|.        |           *|.        | 7 -

0.047

8 

-

0.097

2 

          .|.        |           *|.        | 8 0.016

5 

-

0.056

5 

          .|.        |           .|.        | 9 0.020

2 

-

0.026
5 

          *|.        |           .|*        | 1

0 

-

0.066

8 

0.060

6 

          *|.        |           *|.        | 1

1 

-

0.054

7 

-

0.060

8 

          .|.        |           .|.        | 1

2 

0.015

4 

-

0.040

8 

          .|.        |           *|.        | 1

3 

-

0.024

6 

-

0.043

2 

          .|.        |           .|.        | 1

4 

0.037

1 

-

0.009

6 

          .|.        |           .|.        | 1

5 

-

0.016

7 

-

0.030

3 

          .|.        |           *|.        | 1

6 

-

0.028
4 

-

0.056
8 

          .|.        |           .|.        | 1
7 

-
0.030

6 

0.008
6 

          .|.        |           .|*        | 1

8 

0.028

7 

0.051

4 

          *|.        |           *|.        | 1

9 

-

0.056

6 

-

0.043

0 

          .|.        |           *|.        | 2

0 

0.031

4 

-

0.069

1 

          .|.        |           .|.        | 2

1 

0.042

3 

-

0.014

6 



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66 
                           

          .|.        |           .|**       | 2

2 

-

0.035

0 

0.177

0 

          .|.        |           .|*        | 2

3 

0.036

4 

0.062

5 

          .|.        |           .|*        | 2

4 

0.025

3 

0.095

1 

          .|.        |           *|.        | 2

5 

-

0.011

0 

-

0.041

3 

          .|.        |           .|.        | 2

6 

0.028

0 

0.045

9 

          .|.        |           .|*        | 2

7 

0.015

5 

0.105

2 

          .|.        |           .|*        | 2

8 

0.023

0 

0.054

9 

          .|.        |           .|.        | 2

9 

-

0.012

1 

0.049

1 

          .|.        |           .|*        | 3

0 

0.007

3 

0.081

2 

          .|.        |           .|.        | 3
1 

-
0.036

3 

-
0.022

0 

          .|.        |           .|.        | 3

2 

0.007

5 

0.020

6 

          .|.        |           .|*        | 3

3 

0.018

5 

0.122

7 

          .|.        |           .|**       | 3

4 

-

0.023

9 

0.243

9 

          .|.        |           .|*        | 3

5 

-

0.005

9 

0.050

5 

          .|.        |           .|*        | 3

6 

-

0.021

0 

0.088

3 

 

Sample: 1365:01 1381:12 

Included observations: 47 

Correlations are asymptotically consistent approximations 

D(DOLLAR),DNFAD(-i) D(DOLLAR),DNFAD(+i) i   lag  lead 

        .  |  .      |         .  |  .      | 0 -

0.030

6 

-

0.030

6 

        .  |  .      |         .  |  .      | 1 -

0.038

5 

-

0.038

6 

        .  |  .      |         .  |  .      | 2 -

0.030

7 

0.035

4 

        .  |  .      |         .  |  .      | 3 - 0.012



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67 
                           

0.026

1 

4 

        .  |  .      |         .  |  .      | 4 0.040

4 

-

0.025

3 

        .  |  .      |         .  |  .      | 5 0.047

1 

-

0.040

8 

        .  |  .      |         .  |  .      | 6 -

0.020

7 

-

0.011

8 

        .  |  .      |         .  |  .      | 7 -

0.010

1 

0.036

8 

        .  |  .      |         .  |* .      | 8 0.016

3 

0.054

9 

        .  |  .      |         . *|  .      | 9 0.038

3 

-

0.127

5 

        .  |  .      |         .**|  .      | 1

0 

0.029

6 

-

0.181

8 

        .  |* .      |         .  |* .      | 1

1 

0.051

7 

0.059

1 

        .  |  .      |         .  |**.      | 1

2 

-

0.018

6 

0.187

7 

        .  |  .      |         .  |* .      | 1

3 

0.015

2 

0.073

9 

        .  |  .      |         .  |  .      | 1

4 

0.023

9 

0.042

0 

        .  |  .      |         .  |* .      | 1

5 

-

0.010

9 

0.098

4 

        .  |  .      |         .  |* .      | 1

6 

0.008

5 

0.078

8 

        .  |  .      |         .  |**.      | 1

7 

0.008

3 

0.182

9 

        .  |  .      |         .  |**.      | 1

8 

-

0.007

0 

0.210

9 

        .  |  .      |         .**|  .      | 1

9 

-

0.001

8 

-

0.209

9 

        .  |  .      |       *****|  .      | 2

0 

0.002

4 

-

0.516

7 

 

 



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68 
                           

11. Simulation 

The analysis of the long-run relationship between selling foreign exchange in the parallel market, liquidity, and 

cumulative balance of payments with foreign exchange is shown by a regression. This analysis, which is based upon 

annual data contain these variables: 

Irem = the parity rate of one Dollar with Rial 

Irm2v = liquidity (billion Rials) 

Irboptd = balance of payments (million $) 

Irgrdsv = sale of foreign exchange in the market (billion Rials) 

Ird99 = the dummy variable (equal to one in 1998) 

Dependent Variable: IREM 

Method: Least Squares 

Date: 05/17/04   Time: 11:01 

Sample(adjusted): 1960 2001 

Included observations: 42 after adjusting endpoints 

IREM =IREM(-1)+B(20011)*(IRM2V-IRM2V(-1))+B(20012)*IRBOPD 

        +B(20013)*IRGRDSV+B(20014)*IRD99 

 Coefficien

t 

Std. Error t-Statistic Prob.   

B(20011) 0.055541 0.005340 10.40160 0.0000 

B(20012) -0.032592 0.016491 -1.976378 0.0554 

B(20013) -0.079829 0.008465 -9.430504 0.0000 

B(20014) 1935.572 215.1956 8.994478 0.0000 

R-squared 0.993304     Mean dependent var 1455.924 

Adjusted R-squared 0.992775     S.D. dependent var 2421.946 

S.E. of regression 205.8675     Akaike info criterion 13.58274 

Sum squared resid 1610495.     Schwarz criterion 13.74823 

Log-likelihood -281.2374     Durbin-Watson stat 2.310237 

 

The results show that in the short run, regulating foreign exchange rate by instruments such as selling foreign 

exchange in the market or by controlling liquidity is not possible, but in the long run, it is possible. For further study, 

consider these scenarios: 

Scenario 0 (baseline): solving the equation with real exogenous variables 

Scenario 1: 10 percent increase in liquidity (irm2v*1.1) 

Scenario 2: 10 percent increase in selling foreign exchange in the market (irgdsv*1.1) 

Scenario 3: one billion $ increase in the balance of payments (irbopd +1000) 

-1200

-800

-400

0

400

800

-2000

0

2000

4000

6000

8000

10000

60 65 70 75 80 85 90 95 00

Residual Actual Fitted



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69 
                           

These scenarios are defined by 0, 1, 2, and 3 in the next table, which are baseline solution and other mentioned 

solutions, respectively. The results of dynamic simulation show that a 10 percent increase in liquidity, causes 16.7 

percent increase in the foreign exchange rate and a 10 percent increase in the foreign exchange sale in the parallel 

market will reduce the foreign exchange rate by 6.1 percent. This simulation has been carried out for 4 years (1998-

2001). The results are presented in the next tables and graphs. 

Baseline solution 

 1998 1999 2000 2001 

IRBOPD -1572 1845 6529 4760 

IREM_0 (Baseline) 5613.

4 

7646.1 7171.1 6460.0 

IRGRDSV 6022 18532 39324 52445 

IRM2V 16040

2 

192689 249111 320957 

Scenario 1 

 1998 1999 2000 2001 

IRBOPD -1572 1845 6529 4760 

IREM_1 (Scenario 1) 6391.

6 

8580.9 8379.6 8017.1 

IRGRDSV 6022 18532 39324 52445 

IRM2V_1 (Scenario 1) 17644

2 

211958 274022 353053 

Scenario 2 

 1998 1999 2000 2001 

IRBOPD -1572 1845 6529 4760 

IREM_2 (Scenario 2) 5566.

5 

7454.6 6672.8 5552.6 

IRGRDSV_2 (Scenario 2) 6624 20385 43256 57690 

IRM2V 16040

2 

192689 249111 320957 

Scenario 3 

 1998 1999 2000 2001 

IRBOPD_3 (Scenario 3) -572 2845 7529 5760 

IREM_3 (Scenario 3) 5591.

3 

7601.9 7104.7 6371.5 

IRGRDSV 6022 18532 39324 52445 

IRM2V 16040

2 

192689 249111 320957 

The simulated figures of the foreign exchange rate in the three scenarios 

 1998 1999 2000 2001 

IREM 6468.4 8657.7 8188.1 8008.4 

IREM_0 (Baseline) 5613.4 7646.1 7171.1 6460.0 

IREM_1 (Scenario 1) 6391.6 8580.9 8379.6 8017.1 

IREM_2 (Scenario 2) 5566.5 7454.6 6672.8 5552.6 

IREM_3 (Scenario 3) 5591.3 7601.9 7104.7 6371.5 

 



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70 
                           

 

The percentage change of foreign exchange rate in the parallel market in each scenario, relative to the results of the 

baseline solution is shown in the following table: 

 1998 1999 2000 2001 average 

IREM_P_CHANGE_1 (Scenario 1) 13.9 12.2 16.9 24.1 16.7 

IREM_P_CHANGE_2 (Scenario 2) -0.8 -2.5 -6.9 -14.0 6.0 

IREM_P_CHANGE_3 (Scenario 3) -0.39 -0.58 -0.93 -1.37 0.8 

 

12. 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, 

5500

6000

6500

7000

7500

8000

8500

9000

1998 1999 2000 2001

IREM (Baseline)

IREM (Scenario 1)

IREM_2

IREM_3



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71 
                           

by the policy of selling foreign exchange and controlling the liquidity and the balance of payments, we can control 

the foreign exchange market.  

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( ارتباط اجزاء منابع و مصارف بانكها با بخشهاي پولي، ارزي و مالي و مغايرتهاي موجود در گزارش اقتصادي و ترازنامه 1373بيدآباد، بيژن )

 بانك مركزي، وزارت امور اقتصادي و دارايي، معاونت امور اقتصادي.

الي گزارش اقتصادي و ترازنامه بانك مركزي، معاونت اقتصادي و (، برخي ناهمخوانيها در حسابهاي پولي، ارزي و م1374بيدآباد، بيژن )

 تكنولوژي، مركز تحقيقات استراتژيك، نهاد رياست جمهوري.

 -6صفحات  – 84هاي اقتصاد شمارة  ( بررسي اجمالي اثرات سياست فروش ارز در بازار غيررسمي اسعار خارجي، مجله تازه1377بيژن بيدآباد )

بانكي، بانك مركزي ايران.. پژوهشكدة پولي و 4  

http://www.bcentral.c1/Estudios/DTBC/69/dtbc69.pdf


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www.cribfb.com/journal/index.php/asfbr                                       Asian Finance & Banking Review                                                 Vol. 3, No. 1; 2019 

 

73 
                           

گذاري در ايران، مركز پژوهشهاي مجلس شوراي اسالمي.  ( امنيت اقتصادي و مروري بر موانع سرمايه1374بيژن بيدآباد )  

اقتصاد از مجموعه مسائل اقتصاد كالن  4باشند؟ گزارش  ( آيا ابزارهاي پولي بانك مركزي در كنترل حجم نقدينگي كافي مي1374بيژن بيدآباد )

 ايران، مركز تحقيقات استراتژيك نهاد رياست جمهوري.

از مجموعه مسائل اقتصاد  3( آيا تورم در ايران به غير از افزايش حجم نقدينگي علت اساسي ديگري نيز دارد، گزارش شماره 1374بيژن بيدآباد )

 كالن، مركز تحقيقات استراتژيك نهاد رياست جمهوري. 

از مجموعة مسائل  2شود؟ گزارش شمارة  آيا كاهش تورم در اثر كاهش رشد نقدينگي سبب كاهش رشد اقتصادي در ايران مي (1374بيژن بيدآباد )

 اقتصاد كالن ايران، مركز تحقيقات استراتژيك نهاد رياست جمهوري. 

. 4زي ايران. ويرايش ( الگوي اقتصاد سنجي كالن ايران، مؤسسه تحقيقات پولي و بانكي، بانك مرك1375بيژن بيدآباد )  

از مجموعه مسائل اقتصاد كالن  8گذاري را داشت؟ گزارش شمارة  توان انتظار افزايش سرمايه ( آيا بدون امنيت اقتصادي مي1375بيژن بيدآباد )

 ايران، مركز تحقيقات استراتژيك نهاد رياست جمهوري. 

پذيري حصول اهداف برنامه پنجساله اول توسعه اقتصادي، اجتماعي  اقتصاد ايران و امكان ( تبيين پولي تورم در1369كميجاني، اكبر و بيژن بيدآباد )

 و فرهنگي جمهوري اسالمي ايران، وزارت امور اقتصادي و دارايي، معاونت امور اقتصادي. 

طرح تحقيقاتي مرحله اول وزارت امور  ( سياستهاي پولي مناسب جهت تثبيت فعاليتهاي اقتصادي در ايران،1370كميجاني، اكبر و بيژن بيدآباد )

 اقتصادي و دارايي، معاونت امور اقتصادي. 

( سياستهاي پولي و ارزي مناسب جهت تثبيت فعاليتهاي اقتصادي در ايران، طرح تحقيقاتي مرحله دوم، وزارت 1371كميجاني، اكبر و بيژن بيدآباد )

 .امور اقتصادي و دارايي، معاونت امور اقتصادي

گذاري براي كنترل تورم در ايران، ششمين كنفرانس سياستهاي پولي و ارزي، مؤسسه  ( سياست هدف1376، محمد جعفر و بيژن بيدآباد )مجرد

 تحقيقات پولي و بانكي، بانك مركزي جمهوري اسالمي ايران. 

 

 

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