would the implementation of the gold dinar affect trade among oic countries

Would Implementation of the Gold Dinar Affect trade Among oIc countries?

M. Luthfi Hamidi

Abstract: This study attempts to analyze whether the implementation of the gold dinar proposal would affect trade among oIc members, since gold is considered a more stable currency, as it is less risky than fiat money. Empirical results produced by this study prove that fiat money, particularly real exchange rate of the Us dollar against gold, has an absolutely negative impact on developing countries’ exports. Although its direct effect on trade is very low, the variable itself is statistically significant at 5% level of significance. In contrast, those involved in the gold dinar trade bloc will likely increase their respective intra-trade by more than 2 units. In other words, the gold dinar bloc offers to those members a trade-creating effect. This effect is more robust than the benefit generated by the outstanding economic bloc within oIc including AmU and cEAU. furthermore, gold dinar also generates considerable efficiency in terms of trade payment. If six leading oIc exporting countries join in the gold dinar

bloc, trade efficiency in terms of payment will be around 76.68%.

JEL Classification: F02, F10, F36, E42, P45.

I. IntroductionThe gold dinar has been a controversial issue among oIc member states ever since the former Prime minister of malaysia, mahathir mohammad,

M. Luthfi Hamidi, Bank muamalat Indonesia (BmI), and lecturer in Islamic Business at the University of Paramadina, Jakarta, Indonesia.

This paper is a shorter version of the author’s master dissertation submitted to markfield Institute of Higher Education, leicester, UK. The author would like to thank to Dr. mehmet Asutay for his supervision and insightful comments during completing this work. The author wishes to extend his thanks to Dr. mustafa Edwin nasution for his suggestion on the econometric estimation procedure.

© 2009, international association for islamic economics

Review of Islamic Economics, vol. 13, no. 1, 2009, pp. 31–68.

32 Review of Islamic Economics, vol. 13, no. 1, 2009

initiated public discussion of the proposal in 2001, arguing that the gold dinar would boost inter-oIc trade.

That trade is certainly extremely low. one of the striking factors inhibiting such trade is high exchange rate volatility of the member states’ domestic currencies so that, in order to reduce that risk, most of them use ‘hard’ currency such as the Us dollar in international trade. But that does not altogether remove the risk since the dollar, like other fiat money, also tends to fluctuate in value: the notion of gold dinar is therefore seen as an attractive alternative since its value is expected to be more stable than fiat money.

The important question that needs to be asked and properly answered is whether the gold dinar really would affect trade among the member states of the oIc. Unless there is a positive answer, the gold dinar will remain a wish or fantasy and not become a reality. This paper attempts to evaluate and examine the gold dinar issue from several standpoints. firstly, it seeks to assess whether the gold dinar would be a stable currency and whether it would (or not) have a significant impact on trade. for this reason, the performance of gold is contrasted with that of the dollar and other hard currencies such as the Dm and Yen. secondly, the paper tries to evaluate whether a gold dinar trade bloc is likely (or not) to trigger a trade-creating effect1 which can increase trade among its members. finally, if the first two questions are answered positively, the further task is to calculate how much gold is required to support the trade and then to determine whether the member states own sufficient gold reserves.

II. Literature Review

2.1. trade in the Islamic worldIn the Islamic tradition, trade has not only been the way to obtain reciprocal benefits for the parties involved, but also a primary means to spread Islamic teachings to different parts of the world. It has also played an important role in unifying the Islamic world.2 Thus, the failure of trading among Islamic countries implies disunity among them and is a signal of the weakened bargaining power they have at their disposal in relation with other countries.

The establishment in 1972 of the organization of Islamic conference (oIc) prompted a hope that muslim countries that share similar political and economic interests would cooperate. The oIc was also intended to

33Review of Islamic Economics, vol. 13, no. 1, 2009

serve as a forum where the problems faced by muslim countries could be tackled by them together. Among other concerns, the issue of trade gained priority in oIc as trade volume among muslim countries was and remains very low, even though most of the muslim countries are blessed with abundant natural resources. In 2003, the trade amongst muslim countries was only around 13% of the total trade. This is the highest record during the last five years (see Table 1).

table 1: trade among oIc Member countries (Us million dollar)

trade 2003 2002 2001 2000 1999

Total intra-trade 151,272 123,972 115,793 109,376 83,402

Total trade 1,153,847 947,629 907,947 919,203 751,098

Percentage 13.11 13.08 12.75 11.89 11.1

Source: sEsrTcIc statistics

In general there is an incremental trade growth of oIc members, but most of it is dominated by oil and relies on primary commodity exports (Table 2a and Table 2b) while being heavily dependent on industrialized countries for the import of manufactured products (Table 3). That, in turn, makes the muslim countries dependent on and enormously affected by the world economy, and they are, in consequence, subordinate to the economy of the industrialized world (shalaby, 1988:90).

table 2a: share of oil to the total export for the oIc Leading exporters (%)

no. countries 2002 2001 2000 1999

1 saudi Arabia 89 90 92 85

2 UAE 92 - - -

3 malaysia 9 9.7 9.6 7

4 Indonesia 24 25.3 25 23

5 Turkey 1.9 1.4 1 1

6 Pakistan 1.9 2 1 1

7 nigeria 100 99.6 98.9 99

8 Iran 86 84 91.2 75.7

9 Kuwait - 79 79 90.2

10 syria 72 76 76.3 68



table 2b: share of Primary commodity to the total export of the oIc

Leading exporters (%)

no. countries 2002 2001 2000 1999


2 UAE 96 - - -3 malaysia 21 20 19.6 20

4 Indonesia 46 44 43 46

5 Turkey 14.5 15.1 15 16

6 Pakistan 53 50 47 53

7 nigeria 97 97.2 98 98

8 Iran 91 90 93 -9 Kuwait - 80 80 91.5

10 syria 93 92 92.2 92.6


table 3: share of Manufactures to the total Imports of the oIc top ten

exporters (%)

no. countries 2002 2001 2000 1999


2 UAE 86 - - -3 malaysia 83 83 83.9 85

4 Indonesia 59 61 61 69

5 Turkey 68 67 70 73

6 Pakistan 53 50 47 53

7 nigeria 76 76 76 67

8 Iran 82 76 73 -9 Kuwait - 79 79 79

10 syria 64 65 65 59

source: sEsrTcIc statistics

2.2. economic cooperation among oIc countriesEconomic cooperation among oIc member countries is believed to be a way forward to overcome the obstacles inhibiting trade flow. A significant achievement in 1978 was the establishment of The Islamic chamber of commerce, Industry and commodity Exchange (IccIcE)3 in Karachi. furthermore, the focus on economic cooperation has improved consistently since the founding of The Islamic centre for Development of Trade (IcDT)4 in casablanca in 1981.


full economic cooperation gained momentum once there has been a proposal to establish an Islamic common market (Icm). The Icm will be a kind of vehicle based on ideological unity to bridge the gap among muslim countries with the main target to facilitate optimal intra-Islamic utilization of their resources (sadeq, 1996: 39). The Icm is considerably more complex than a free Trade Area (fTA)5 or customs Union (cU),6 since it encourages cooperation not only in the trading of goods, but also in regard to mobility of factors of production. Thus, the Icm is to be characterized by free movement of capital, labour, service, as well as entrepreneurship (satiroglu, 1996: 6; nienhaus, 1996; 91; sadeq, 1996: 44; Alatas, 1987: 32).

some scholars hold that the establishment of the Icm will overcome trade barriers and enhance effective economic cooperation. on the other hand, few of those scholars have taken care to point out that the low level of intra-trade among oIc members is a result of the low level of their development (Bhuyan, 1996:26). According to Bhuyan, the establishment of economic cooperation among the members should be a catalyst to accelerate their industrialization rather than directly to improve the level of trade.

Another concern in light of the establishment of the Icm is its applicability. It is believed that the Icm is a long-term target that needs to be consistently adhered to. regrettably, however, the future of the Icm is unclear since there is barely even a definite timetable agreed, among the members, to formalize the work of Icm.7 Instead of planning to move together gradually as a step closer towards Icm goals, some of oIc members have been reluctant to remove the barriers to free movement of capital and labour which protect their national interest (nienhaus, 1996:101).

2.3. the impact of currency volatility on trade currency volatility is considered to be one of the barriers to increase trade. many of the developed countries adopted a floating rate regime on their national currency in 1973. since the inception of that regime, the industrialized countries have experienced a significant decline in their economic growth. Between 1960 and 1973, their average yearly growth rate was 4.4%, while, during 1973–1990, it dropped to 1.3% (Grauwe, 1998:240).

The decline in economic growth can be traced to the change that has taken place in international trade since the floating exchange regime. Because the variability of exchange rate increases uncertainty, it leads investors to reduce risk by shifting a part of their international trade into domestic trade. This in turn hits the international trade and results in slowdown in growth.


one may argue that the agents are free to utilize hedging facilities to protect themselves against loss. However, since this facility is not without cost, it means that any resulting gains or benefits are set off against the losses or drawbacks (Grauwe, 1998:241).

recent studies provide more robust evidence with respect to the effect on trade of the currency volatility. A study on G-38 exchange rate volatility suggests that one percentage increase in that rate decreases real exports of developing countries by, on average, about 2 percent (Esquivel and larrain, 2002). vergil (2002) examines trade flows between Turkey and its trade partners and finds that exchange rate volatility has a significant negative effect on trade. Arize et al. (2004) came up with the same result. They investigated exchange rate volatility in eight latin American countries and report that the exchange rate has a significant negative impact on export demand both in the short and long run.

III. Methodology

3.1. Measuring exchange rate volatility and modelling its impact on tradeone of the most common measures to capture time-varying volatility on exchange rates is Generalized Autoregressive conditional Heteroscedasticity, known as the GARCH model, developed by Bollerslev (as cited by verbeek, 2000:266). This model has been employed in previous studies such as mcKenzie (1998) and vergil (2002).

Another way to measure exchange rate volatility is coefficient of variation (CV) of exchange rate. Esquivel and larrain (2002) define exchange rate volatility as the time-varying twelve-month coefficient of variation (CV) of the real exchange rate. This method is actually used to indicate a dispersion of the real exchange rate. The formula to calculate CV can be written as follows:

�

CVt +m =

1

m(ε t + i−1 −ε )2

i=1

m

∑

1

2

ε

(1)

where m is the order of moving average and ε is the mean of the bilateral exchange rate between month t and t+m-1. In this study, CV will be used to measure the level of volatility of exchange rate, which can then be utilized to predict its impact on trade. since in this study annual data is used, the

−


moving average method is perhaps no longer relevant. Instead of using the formula given above, this study proposes to calculate CV based on the following formula:

(2)

where, x is an individual value, n is the number of observations (test values) and x is the mean of n values. In other words, CV is calculated by dividing standard deviation by mean value (chou, 1965:107; see also Kane, 1969:78).

Esquivel and larrain (2002) investigate the impact of the volatility of G-3 currencies on developing countries trade. They propose a model to estimate the exports of developing countries as a function in the following form:

X = f (world demand, bilateral dollar real exchange rate, G-3 currency), which can be expressed as follows:

(3)

where Xt denotes exports of country t, GDP

w represents the real world GDP,

RERUS

is bilateral real exchange rate in terms of the dollar and the variables VOL are the coefficients of variation (cv) of the G-3 real exchange rates. In this study, the model will be utilized with subtle modification by introducing variable D

dollar/gold in the model. Besides, a model based on pure exchange rate

will also be assessed.

Model 1:

(4)

Model 2: (5)

Model 3: (6)

where VG represents volatility values based on the GARCH technique, VC is volatility values based on the coefficient of variance (CV) method, and RER represents the absolute values of real exchange rate of the respective


countries. Xt is total export of developing countries, in dollar millions.

GDPw

is world’s Gross Domestic Product in dollar millions. Ddollar/gold

is real exchange rate of dollar in terms of gold, while DM

DM/dollar and Y

yen/dollar are real

exchange rate of DM and yen with respect to the dollar. GDP

w represents the scale economy of the world. It is expected to be

positive since the larger the value of GDPw, the larger the value of exports

will be. Ddollar/gold

, DMDM/dollar

and Yyen/dollar

represent risk which may occur as a result of exchange rate variability in international trade. These are expected to be inversely correlated with the exports. Increase in the exchange rate volatility will likely decrease the volume of exports.

3.2. the gravity model to capture trade-creating effectone of the famous econometric models to assess trade between countries is the gravity model, developed by Tinbergen (1962) and Poyhonen (1963). The simple gravity model introduces trade between two countries as a function of their gross national product (GNP) or gross domestic product (GDP), and the distance between them, usually calculated as the distance between their respective capital cities. The volume of trade should positively correlate with their respective GDP and income per capita, since a country with considerably large GDP will tend to trade more than the one with a small GDP. Greater distance between them should reduce trade volume, since it incurs transportation and information costs.

Employing the gravity model, many researchers have observed the effect of common currency on trade. recent research by Glick and rose (2002) suggest that participation in a currency union has doubled trade and is statistically significant. However, Glick and rose’s work is challenged by other researchers. Pakko and wall (2001), for instance, also use the gravity model but find that the trade-creating effect of common currency is definitely lower then the findings of Glick and rose.

As for oIc member countries, Bendjilali (2000) suggests an empirical gravity model for these countries by adding a variable of IDB’s import trade financing operations to country i, while Hassan and Islam (2001) employ the basic gravity model to assess whether there is (or not) a significant trade-creating effect from implementing a trade bloc among oIc members. In this study, that model is modified by introducing a gold dinar trade bloc. The model can be written as follows:

log(TRADEijt

) = α ± β1log(GDP

it*GDP

jt) ± β

2log(PCI

it*PCI

jt) ± β

3log(DISTANCE

ij) (7)

± β4(BORDERij) ± β

5(BLOC

ij) ± ε

ij


for simplicity, the above equation is rewritten as follows:

(8)

Trade is expected to increase with the size of domestic economy G (GDP), per capita income Y (PCI), common border B (BORDER), joining in the same trade bloc (BLOC) and to decline with distance D (DISTANCE). coefficient of β

1, β

2, β

4, and β

5 should be positive, while β

3 should be negative.

3.3. Measuring the amount of gold to serve trade and its generated efficiencyonce the gold dinar is implemented, one may ask: How much gold is required to support the trade? How much efficiency can be generated?

Yakcop (2002a and 2002b) introduces the Bilateral Payment Agreement (BPA) model, which can be extended into a multilateral Payment Agreement (mPA) to illustrate how trade will be facilitated by gold dinar. furthermore, meera and larbani (2004) develop an efficient trade matrix to indicate the detail of trade conducted by gold dinar.

In this study, the mPA scheme is utilized. It is essential to introduce the BPA scheme first before turning to further steps. let us say malaysia and Indonesia sign a BPA scheme whereby trade balances will be settled up in quarterly periods. Both countries agree that trade will be denominated in gold dinars, one unit being defined as one troy ounce of gold. Bank negara will pay malaysian exporters in ringgit, based on the ringgit/gold dinar exchange rate prevailing at the date of export. likewise, malaysian importers have to pay ringgit to Bank negara to the same amount of their import value. meanwhile, Bank Indonesia will also do the same for Indonesia’s exporters and importers. At the end of the first quarter, the trade cycle is ended, the total export from malaysia to Indonesia, say, is 3 million gold dinar and the total export from Indonesia to malaysia is worth 2.5 million gold dinar (Table 4).

table 4: Gold Dinar settlement by BPA scheme

Gold Dinar (million)

Export to malaysia Indonesia Total Export net Payment

malaysia 2.5 2.5 -0.5

Indonesia 3 3 0.5

Total Import 3 2.5 5.5


Table 4 shows that at the end of the quarter, malaysia has a trade deficit of 0.5 million gold dinar, while Indonesia has a surplus of 0.5 million gold dinar. Accordingly, Bank negara as central bank will pay Bank Indonesia 0.5 million gold dinar. Initially, it is agreed that both of them have a gold custodian account in Bank of England, for instance. Then the actual payment can be transferred into the account of Bank Indonesia in Bank of England. It is interesting to note that only a small amount of 0.5 million gold dinar is able to support the total trade value of 5.5 million gold dinar.

This scheme will be more efficient, if other participants join and therefore the mechanism of payment will use the mPA scheme which in essentials is the same as the BPA, but involves more members. from the above sample we can calculate the amount of gold dinar to support trade by simple equation as follows:

(1) Gold required to last trade:

(9)

where, Xi and I

i represent the total export and import of country i to its

trading partners, in millions of gold dinar. n is number of countries involved in the transaction (the economic bloc).

(2) The efficiency generated from gold can be written as:

(10)

where TVT stands for total value of trade and Np is the net payment.

3.4. Data source and definition The statistical data in this study is mainly obtained from three sources: (i) statistical, Economic and social research and Training centre for Islamic countries (sEsrTcIc) for all data pertaining to oIc member countries; (ii) Direction of Trade statistics, which is prepared quarterly by Imf for data particularly related to detail intra-trade (export and import) among members; (iii) United nations conference on Trade and Development (UncTAD) for data particularly related to export volume of developing countries.


In addition, some data is retrieved from other sources, such as the distance between capital cities among oIc member countries, which is easily accessed in (http://www.wcrl.ars.usda.gov/cec/java/capitals.htm). Data relating to the exchange rates of DM and Yen against dollar and dollar in terms of gold are obtained from www.econstats.com and Global financial Data, respectively.

The definition of each of the selected variables in the models is as follows:

Exports (X): Data show the f.o.b. (free on board) value of goods provided to the rest of the world valued in Us dollars. Export of Developing Countries (X) is total export generated from developing countries.

GDP (G): GDP is defined as the sum of the gross value-added by all resident and non-resident producers in the economy plus indirect taxes and minus any subsidies not included in the value of the products, in Us dollars. GDP World (GDP

w) is the sum of total GDP generated from all countries in the

world. GDP Per Capita Income (Y) is calculated by dividing GDP by the mid-year population. The following charts represent GDP of oIc countries (GDP OIC), exports of developing countries (X), and GDP

w.

Real Exchange Rate (RER): It is the exchange rate of one particular country compared with another at a particular point in time, taking into account their respective inflation. one of the common measures to calculate RER is by adjusting nominal exchange rate by the ratio of the foreign price level to the domestic. Due to availability of data, in this study RER is computed by indexing, that is, creating an index. The first year of observation, namely 1972, is taken as the base value, with the first exchange rate value for that year, say x, equated to 100. mathematically this can be simply written as follows:

(11)

where, xt is real exchange rate at time t, and x

0 is real exchange rate at the

base year which is 100. Yyen/dollar

and DMDM/dollar

represent the bilateral real exchange rate of yen and Dm with respect to the dollar, while D

dollar/gold

illustrates the real exchange rate of dollar in terms of gold price. These are displayed in figures 1, 2, and 3.


Figure 1: Real exchange Rate Yen/UsD

Figure 2: Real exchange Rate DM/UsD

Figure 3: Real exchange Rate UsD/Gold

Source: www.econstats.com and Global financial Data

TRADEijt

(T): the bilateral trade comprising total exports and imports between countries i and j at time t in dollar.


DISTANCEij

(D): The distance in kilometres between two countries (i.e. between the capital cities i and j).

BORDERij

(B): A dummy variable, which takes a value of 1 if two countries have a common border and zero otherwise.

BLOCKij: A dummy variable, which takes a value of 1 if one country joins in

the trade bloc, and zero otherwise. The trade blocs to be evaluated are those within oIc countries. A new trade bloc, namely the gold dinar trade bloc, will be introduced.

IV. empirical Result

4.1. exchange rate volatility and its impact on tradeAs discussed in the previous section, volatility of exchange rate is evaluated by computing coefficient of variance (cv). The results are depicted in figures 4, 5, and 6.

Figure 4: Volatility Dollar/Gold (coefficient of Variance Method)

Figure 5: Volatility DM/Dollar (coefficient of Variance Method)


Figure 6: Volatility Yen/Dollar (coefficient of Variance Method)

recalling the model described in the previous section, there are three models presented which refer to equation 4, 5, and 6. By conducting unit root test, we found the variable(s) in model 1 (see Table 5) and model 3 (see Table 7) to indicate a non-stationary feature.

table 5: Unit Root test for Model 1

Variables test statistics & critical Values Adjusted

Levels 1st differences Regression

ADF cV(5%) ADF cV(5%) Variable

LX -4.0662(0) -3.5796 - - -

L(GDPw) -4.0121(1) -3.5943 - - -

VG(D) -3.7158(0) -2.9665 - - -

VG(DM) -3.3137(1) -2.9706 - - -

VG(Y) -1.9079(3) -2.9798 -6.365 -2.9706 DvG(Y)


Variablestest statistics & critical Values

Levels

ADF cV(5%)

LX -4.0662(0) -3.5796

L(GDPw) -4.0121(1) -3.5943

Vc(D) -4.1887(1) -2.9706

Vc(DM) -4.1713(0) -2.9665

Vc(Y) -3.2690(3) -2.9798



test statistics & critical Values Adjusted

Variables Levels 1st differences Regression

ADF cV(5%) ADF cV(5%) Variable

lX -4.0662(0) -3.5796 - - -

l(GDPw) -4.0121(1) -3.5943 - - -

rEr(D) -8.3549(0) -2.9665 - - -

rEr(Dm) -2.6850(0) -2.9665 -4.0074 -2.9706 DrEr(Dm)

rEr(Y) -2.0152(0) -2.9798 -3.5134 -2.9800 DrEr(Y)

Given this condition, the regression results may be misleading and incorrect (Koop, 2000:152). Thus, while the regression for model 2 remains the same, model 1 and 3 need to be adjusted as follows:

Model 1:(11)

Model 3 (12)

The ols results for all models are set out in Tables 8, 9, 10 and 11.

table 8: Regression Result for Model 1

no. Variablesexpected Results

Actual Results

coefficient t-statsignificant level

1 Intercept - - -25.5887 -10.6263 0.000 *2 logGDPw + + 2.3057 16.6202 0.000 *3 vG(D) - - -.6627E-4 -3.3867 0.002 *4 vG(Dm) - - -.3940E-4 -1.7939 0.085 **5 ∆ vG(Y)

- + .4733E-4 1.9730 0.060 **

Notes: ‘*’ indicates significance at α=5% (two-tailed); ‘**’ indicates significance at α=10% (2 tailed)


no. Variablesexpected Results

Actual Results


1 Intercept - - -27.2689 -9.4127 0.000 *2 logGDPw + + 2.4022 14.1914 0.000 *3 vc(D) - - -0.018090 -3.4178 0.002 *4 vc(Dm) - - -0.007324 -0.39427 0.6975 vc(Y) - - -0.008019 -0.5504 0.584

Note: ‘*’ indicates significance at α=5% (two-tailed)



no Variablesexpected Results

Actual Results


1 Intercept - - -26.9085 -12.2342 0.000 *

2 logGDPw + + 2.3827 18.6695 0.000 *3 rEr(D) - - -0.009723 -3.2855 0.003 *4 ∆ rEr(Dm)

- + -0.010074 2.5180 0.019 **

5 ∆ rEr (Y)- + 0.001525 .36465 0.719

Notes: ‘*’ indicates significance at α=5% (2 tailed); ‘**’ indicates significance at α=10% (2 tailed)

table 11: overall results Models 1, 2, and 3

no. Variables Model 1 Model 2 Model 3

1 2R 0.96230 0.95033 0.96163

2 2R 0.95602 0.94238 0.95523

3 f statistics 153.1557 119.5711 150.3674

4 Dw statistics 0.80718 0.91669 1.1093

As can be seen from Tables 11, 12 and 13, the individual variable performs well. The coefficient of determination of each model ( 2R ) also indicates that the explanatory variables in each model are able to explain more than 95 percent of variation taking place in the dependent variable. Besides, the models also demonstrate overall significance as indicated by high F-statistics. The overall coefficient of variables is statistically significant even with one percent level of significance. However, the models may encounter severe serial autocorrelation since their DW statistics are terribly low (Table 11). some remedies are taken to completely remove the problem from the equation by transforming the variables into first differences form. Thus, the above model is revised as follows:

Model 1 (13)

Model 2 (14)

Model 3 (15)

The regression results of the above models are presented in Table 12.


table 12: Regression Results of the Revised Models

no.Model 1GARcH

estimatedValues

Model 2coef. of Variance

estimatedValues

Model 3ReR

estimatedValues

1Dependentvariable

∆log Xt

Dependentvariable

∆log Xt

Dependentvariable

∆log Xt

2 Intercept-.004693

(-.06248)Intercept

0.071721

(1.0246)Intercept

0.093767

(1.6045)

3 ∆log GDPW

3.7468

(1.6984)∆log GDP

W

0.66625

(0.31141)∆log GDP

W

0.11494

(0.06396)

4 ∆VG (D)-0.3111E-4

(-1.5566)∆VC (D)

-0.011259

(-2.5102)∆RER (D)

-0.0099251

(-3.1461)

5 ∆VG (DM)-0.9410E-5

(-0.33142)∆VC(DM)

-0.009850

(-0.66785)∆RER (DM)

-0.0028690

(-0.71586)

6 ∆VG (Y)0.1647E-4

(0.54677)∆VC (Y)

0.018811

(1.3252)∆RER (Y)

0.0072179

(1.9074)

7 2R 0.19624 0.29622 0.48737

8 2R 0.062277 0.17893 0.40193

9 f-statistics 1.4649 2.5254 5.7044

10Dw-statistics

1.2342 1.6194 2.0846

Note: figures in parentheses are t-statistics

The revised models are able impressively to increase Dw statistics, which is a signal of improvement in dealing with problem of serial autocorrelation. However, 2R and f-statistics decrease sharply. The low of

2R indicates that the explanatory variables no longer have strong power to explain the independent variable, which was not the case in the original model. meanwhile, the low F-statistics (except for model 3) illustrate that the coefficient of variables as a whole are likely having no statistical significance. Accordingly, model 3 is chosen as the final model and will be analysed subsequently.

The equation for the revised model (model 3) can be written as follows:

∆logXt = 0.093767 + 0.11494∆logGDP

w – 0.0099251∆RER

Dollar/Gold (16)

– 0.002869∆RERDM/Dollar

+ 0.0072179∆RERYen/Dollar

Two of the most noteworthy outcomes from equation 13 are that, if world GDP increases by one unit, holding other variables constant,


the exports of developing countries also increase slightly by 0.114 units. Inversely, if the dollar real exchange rate in terms of gold rises by one point, the exports of developing countries decrease by 0.009 units. The variable of RER

dollar/gold is statistically significant at 5% level of significance. However,

its impact on trade as indicated by the coefficient (0.009) is considered low. similarly, a one point increase in the real exchange rate of Dm against dollar (RER

DM/dollar) has an inverse effect on developing countries’ exports by

a mere 0.002 units (ceteris paribus). In addition, the variable is statistically insignificant.

These low effects on trade are definitely interesting since other previous researchers – Esquivel and larrain (2002) for instance – reported a significant impact. They reported that each one-unit increase in the volatility of Dm against dollar reduces developing countries’ exports by around 2 percent. The difference may be caused by the data for developing countries. In this study, aggregate data of developing countries’ exports, which is time series data, is used whereas Esquivel and larrain used panel data (individual data) of developing countries’ exports. moreover, in this study the regression model chosen is based on the differenced form, while their study was based on logarithmic form. The latter, as presented in the previous section, did not work well, since it contains severe serial correlation problems.

surprisingly, the variable of real exchange rate of yen against dollar (RER

yen/dollar) in this study has positive effect on trade. A one point increase

in RERyen/dollar

tends to increase developing countries’ exports by 0.007 units. Even though the impact is considerably low, the variable itself is statistically significant at 10% level of significance. The positive sign on this variable is the same as in Esquivel and larrain’s results. However, they did not give any special attention to why the sign of this variable is not as expected. This anomaly might emerge because the yen actually is a less influential currency for developing countries. The share of yen in the global currency in 2002 and 2003 is only 5.2 and 4.8 percent respectively (Table 13), while the share of Dm, which has merged into the euro, is 19.3 and 19.7 percent respectively in the same year. Perhaps, most of the developing countries in Africa tend to use European currency including Dm (euro) rather than yen. It is reasonable to argue that they tend to maintain their trade partnership with European countries rather than with Japan for reasons of geographical proximity.


table 13: official Foreign exchange Reserve: currency share (%)

currency 2000 2001 2002 2003

Us dollar 66.6 66.9 63.5 63.8Euro 16.3 16.7 19.3 19.7Japanese yen 6.2 5.5 5.2 4.8Pound sterling 3.8 4 4.4 4.4swiss franc 0.5 0.5 0.6 0.4Unspecified currency 6.6 6.4 7.1 6.8

Source: European central Bank (2005)

In general, the model has no strong explanatory power as indicated by its low 2R . That is a mere 48%, implying that the selected explanatory variables within the model can only explain 48% of the variation taking place in the dependent variable. However, this is still acceptable since, in the financial field, 2R is rarely impressive. furthermore, the model as a whole is statistically significant at 5% level of significance, as illustrated by its high f-statistics. In addition the model is also free of the serial autocorrelation problem. However, the model contains heteroscedasticity problem. This does not destroy the unbiasedness and consistency of the estimations, but these are no longer efficient (Gujarati, 1995:381).

4.2. Gold dinar’s trade creating effect: empirical result from gravity modelThe gravity model utilized in this study contains eight explanatory variables, namely GDP (the product of GDP’s country i and country j), Y (the product of their per capita income), D (DISTANCE between their capital cities), and dummy variables B (BORDER), GOLD9 (Gold Dinar Trade Bloc), CAEU10, AMU11, and D-812.

log(T) = a ± b1 log GDP ± b2

logY ± b

3 logD ± b

4 B ± b

5GOLD ± b

6CARU (17)

± b7 D8 ± b

8 AMU

The complete set of regression results is presented in Table 14.


table 14: Regression Results of Gravity Model

no.original model

estimated Values

observation 31

1 Dependent variable log(T)

2 Intercept-4.0686

(-.44709)

3 logGDP.4001

(1.2348)

4 logY.12409

(.33743)

5 logD-.5176

(-.9495)

6 B2.3309

(2.1959)

7 GolD1.6537

(1.9665)

8 cAEU.4534

(.6658)

9 D-81.9810

(1.9943)

10 AmU.16978

(.1684)

11 2R .82133

12 f-statistics 12.6415

13 Dw-statistics 1.8634

Note: figure in parentheses are t-statistics

The model can be expressed in the equation as follows:

log(T) = –4.0686 + 0.4001logGDP + 0.12409logY – 0.51762logD + 2.3309B

+1.6537GOLD + 1.45349CAEU + 1.9810D8 + 0.16978AMU

The estimation of equation 17 suggests that an increase in one unit of GDP and per capita income will tend to increase trade by 2.5 and 1.33 units respectively.13 on the other hand, a one point additional distance between countries will likely decrease trade by 3.23 units.14 However these variables are statistically insignificant. Thus within a 5% level of significance, only variable B (BORDER) is statistically significant. If we extend the level of significance to 10%, variable GOLD and D8 are also statistically significant (Table 15).


table 15: the Property of t-test for the equation 17

Variables tcal

ttab

(a=5%) Decision ttab

a=10% Decision

LogGDP 1.2348 2.079 Insignificant 1.7207 Insignificant

LogY 0.33743 2.079 Insignificant 1.7207 Insignificant

LogD -0.9495 2.079 Insignificant 1.7207 Insignificant

B 2.1959 2.079 significant 1.7207 significant

GoLD 1.9665 2.079 Insignificant 1.7207 significant

cAeU 0.6658 2.079 Insignificant 1.7207 Insignificant

D-8 1.9943 2.079 Insignificant 1.7207 significant

AMU 0.1684 2.079 Insignificant 1.7207 Insignificant

Note: n=30, k=9, n-k=21, for a=5% or 0.025(two tails) ttab

value = 2.079; a=10% or 0.05(two tails) t

tab value =1.7207

Another point from the model is that having the same border and participation in a trade bloc supports greater volume of trade. In the case of sharing the same border, trade is increased by 2.3 units, whereas those involved in gold dinar trade bloc will likely enjoy an increase in their trade by 1.65 units. A similar result prevails for those in CAEU, D8, and AMU trade blocs with an increase in trade of 1.45, 1.9, and 0.16 units, respectively. These positive impacts on trade as a result of joining trade blocs is similar with Hassan and Islam’s (2001) study. It also proves that joining in a trade bloc will open a trade-creating effect. one interesting result here is conformity of each sign. The actual sign for all of the variables does confirm with those expected. It is a bit different with Hassan and Islam’s (2001) study, which finds per capita income is negatively correlated with bilateral trade.

The 2R value is 82% which means that the model has a high explanatory power, and indicates that it has high goodness of fit. The explanatory variables selected in the model can simultaneously explain 82% of the variation taking place in the model. However, the model contains heteroscedasticity problem. multicollinearity may also arise since some of its variables are statistically insignificant with low t-statistics including variable per capita income (Y) and two trade blocs namely CAEU and AMU. Perhaps, this is not surprising as variable Y is gained from the GDP value divided by the respective population of each country. similarly, few of the members of CAEU are involved in the D8 group. In this respect, it is sensible to omit these three variables from the equation presented in the revised model, and the new results can be seen in Table 16.


table 16: Regression results of the revised model

no.Revised model

estimated values

observation 31

1 Dependent variable log(T)

2 Intercept-9.5117

(-1.3793)

3 logGDP.80253

(4.0997)

4 logD-.60904

(-1.2415)

5 B1.9587

(2.1096)

6 GolD2.1136

(2.7355)

7 2R .78287

8 f-statistics 23.4353

9 Dw-statistics 2.1948

note: figure in parentheses are t-statistics

The equation of the model can be written as follows:

(18)

It can be seen that the reduced model performs better, as illustrated by improving statistically significant variables (see Table 16). Another interesting finding is the effect of gold if it were implemented as the international currency for trade. recalling equation 18 and its statistical summary, it can be seen that only the distance variable (D) is statistically insignificant. However, the sign of the variable is as predicted before. The insignificant variable is a bit surprising since other researchers (Bendjilali, 2000, and Hassan and Islam, 2001) reported that distance is statistically significant. other variables such as GDP and border (B) are statistically significant too. These results strengthen the previous studies.

The distinction of this study stems from the introduction of the gold dinar trade bloc variable, something not witnessed in other studies. Those involved in this bloc would enjoy an increase of their respective intra-trade of more than 2 units. moreover, this variable is statistically significant at 5% level of significance, which is further convincing evidence.


In general, the model also demonstrates a highly desirable explanatory efficiency, as the selected explanatory variables are indeed able to explain more than 78% of variation taking place in the dependent variable. The high f-statistics illustrate that the overall model is statistically significant even at 1% level of significance. In addition, the model is also free from serious error derived from the serial correlation error and multicollinearity problem. It may be deduced that the model used here is quite impressive.

4.3. the amount of gold dinars needed to support tradeAs mentioned earlier, it is possible to calculate the quantity of gold dinars needed to support trade simply by calculating the volume of trade, whether it produces surplus or deficit. In presenting the gravity model, we said that the gold dinar trade bloc is assumed to consist of six leading oIc exporting countries. They are saudi Arabia, UAE, malaysia, Indonesia, Turkey, and Pakistan. Table 17 shows their respective trade (export and import).

table 17: the trade among six Leading oIc exporting countries in 2002 (Million Dollar)

export tosaudi Arabia

UAe Malaysia Indonesia turkey Pakistantotal export

saudi A 1695 343 1003 716 1196 4953

UAe 490 3827 105 92 1198 5712

Malaysia 370 835 1586 221 486 3498

Indonesia 475 720 2030 238 265 3728

turkey 535 440 113 28 52 1168

Pakistan 390 837 64 81 110 1482

total Import

2260 4527 6377 2803 1377 3197 20541

Source: Imf, Direction of Trade statistics Yearbook, 2003

In 2002, total trade among these six countries was more than 20.5 billion dollars. UAE is at the top rank of exporting countries with total exports of around 5.7 billion dollars, while malaysia is in the top rank of importing countries with total imports of more than 6.3 billion dollars. It is noteworthy that Turkey holds the lowest position both in terms of import and export, perhaps because it tends to trade with its European partners rather than muslim countries.


from Table 17, the amount of gold dinars required to facilitate the respective trade of these countries can be estimated. The first thing needing to be taken into account is the gold price in the prevailing year which is in 2002. According to Global financial Data, the price of one troy ounce of gold in 2002 was 346.7 dollar. Hence, for instance, the total imports and exports of saudi Arabia are equivalent to 14.28 and 6.51 million gold dinars, respectively. (This is worked out by dividing column (1) and (2) by 346.7 (see Table 18). The net payment for saudi Arabia is thus equal to 7.76 million gold dinars which is obtained by subtracting the figure in column (4) from that in column (3). The amount of gold needed to support the trade is then equal to 59.2 million gold dinars. This amount is equal to 13.4 million troy ounces of gold or around 4.292 tons of gold (see Table 19).

4.4. the efficiency of the gold dinarThe last stage of the calculation is to calculate the efficiency that would be generated if the gold dinar were to be implemented. recall equation 10:

Efficiency = (10)

from Table 18 the amount of net payment (Np) is the same with the amount of gold dinar payable (or receivable), which is 13.8 million gold dinar. Total value of trade (TVT) is the total amount of trade in the conventional sense (if gold dinar would not be implemented), which is 20,541 million dollars or equal to 59.2 million gold dinars. Hence the efficiency generated from implementing the gold dinar is:

Efficiency = x 100 = 76.68 %

This figure 76.68% implies that the six leading exporting countries enjoy the trade by only paying the remaining (around 23.31%) at the end of the year. In other words, if the gold dinar were implemented, they could save almost 4/5 of their budget for other economic allocations. It is indeed a giant step forward that should encourage prosperity among the member countries in the gold dinar trade bloc.


table 18: total trade of six Leading exporting countries, 2002

(Million Gold Dinar)

countries

Million Dollar Million Gold Dinar

Approximationexport Import export Importnet Payment

(1) (2) (3) (4) (3)-(4)

saudi A 4953 2260 14.286 6.5186 7.767522 7.7

UAe 5712 4527 16.475 13.0574 3.417941 3.4

Malaysia 3498 6377 10.089 18.3934 -8.30401 -8.3

Indonesia 3728 2803 10.752 8.0848 2.6680125 2.7

turkey 1168 1377 3.3689 3.97173 -0.6028267 -0.6

Pakistan 1482 3197 4.2745 9.22123 -4.9466397 -4.9

total 59.247 59.247 0 0


table 19: Gold Required to support trade (million gold dinar, troy ounce,

and ton units)

Deficit by countries

GoldDinar

surplusGold Dinar Gold

Dinar total trade

Gold Required

Payable countries Receivable troy ounce ton

Malaysia -8.3 saudi A 7.7

59.215 13,800,000 4,29216

UAe 3.4

turkey -0.6 Indonesia 2.7

Pakistan -4.9

total -13.8 13.8


V. DiscussionThe first question, whether the variability of exchange rate – particularly dollars in terms of gold – has significant impact on trade, has already been answered. As can be seen from equation 13, the model shows that an additional one point on the exchange rate variability of the dollar in respect of gold (RER

dollar/gold) tends to decrease the value of developing

countries’ exports by 0.009 units (holding other explanatory variables as constant). The variable of RER

dollar/gold is statistically significant at 5% level

of significance. This is further proof that exchange rate variability tends to decrease trade. However, its impact on trade as indicated by the coefficient (0.009) is considered low and inconsistent with what the relevant literature leads one to expect.

The establishment of a Gold Dinar Trade Bloc (GDTB), proposed for the first time in this study, indicates a new hope for oIc members since members of this bloc would enjoy an increase of their respective intra-trade by more than 2 units. It is an initial indicator that a GDTB would be more fruitful than other existing trade blocs among oIc countries. moreover, this variable is statistically significant at 5% level of significance, which is further convincing evidence.

The model also promises the hope for oIc member countries of making enormous budget savings. Assuming that the six leading countries of oIc are to be GDTB members, the value of their intra-trade in 2002 stands at 20.5 billion dollars or almost 60 million gold dinars. However, those taking part would not need to supply gold dinars in the same amount as the total value of their trade, but only the amount of the net difference, namely 13.8 million gold dinars. In other words, they would only pay for around 23.31% of the total amount payable if paid in the conventional way using dollars. Thus, the efficiency generated by using the gold dinar is around 76.68%.

That figure would be even higher if the trade between the mentioned member countries were to become larger. If, for instance, ten leading exporting countries within the oIc agreed to settle their trade in gold dinars (i.e. if four additional countries join to the bloc17), the efficiency will increase. In 2002, for the total trade among the 10 leading exporting countries of 32.2 billion dollars (equivalent to 92.98 million gold dinar, see Table 20), the net payment would be only 18.51 million gold dinars. In other words, the efficiency generated would be 80.09%.18


table 20: total Intra-trade of ten Leading exporting countries, 2002

(Million Dollar and Gold Dinar)

countries

Million Dollar Million Gold DinarApproxi-mation

export Import export Import netpayment

(1) (2) (3) (4) (3)-(4)

saudi A. 5593 2560.11 16.1321 7.384223 8.74788001 8.74

UAE 8202 6606.31 23.65734 19.05483 4.60250937 4.6

malaysia 3895 6547.77 11.2345 18.88598 -7.6514854 -7.65

Indonesia 4284 4521.08 12.3565 13.04032 -0.6838189 -0.68

Turkey 1922 2835.27 5.543698 8.177877 -2.6341794 -2.63

Pakistan 1637 4087.42 4.721661 11.7895 -7.0678396 -7.06

nigeria 1200 541 3.461206 1.560427 1.90077877 1.9

Iran 3056 2356.08 8.814537 6.795731 2.01880588 2.02

Kuwait 1608 1173.67 4.638016 3.385261 1.25275454 1.25

syria 840.71 1009 2.424892 2.910297 -0.4854052 -0.48

Total 32237.71 32237.71 92.98445 92.98445 0


This figure implies that the ten leading exporting countries only need one fifth of their current budget to support their trade. They can allocate another 80% of the budget to other economic purposes. Hence, using the gold dinar would be a breakthrough that could enhance prosperity among the countries involved in the gold dinar trade bloc.

5.1. transmission how gold dinar would increase tradeThe following strategies are available to oIc members which trade among themselves (see figure 7):

firstly, exporters/importers can use their domestic currency. This is possible for those who enjoy relatively low volatility of their respective national currency, which is the case only for a few countries, perhaps only some of the oil-exporting ones. Hence, it is assumed that these few countries may enjoy more trade than other oIc member countries.

The second strategy is that a hard currency such as the dollar takes the place of the national currencies. Although hard currencies mostly have a stable exchange rate, it does not necessarily follow that they are free from risk. To remove risk completely from the business, there is no choice but to hedge, for which additional costs are entailed. The trade would still be a


normal trade in the sense that although they have to pay an additional cost for hedging, still they can predict their costs and benefits.

finally, some exporters/importers have no opportunity to use hedging facilities since these are not available in many developing countries (meera and larbani, 2004). Thus, there is no choice in these countries except to use the dollar, without hedging. This can worsen the uncertainty of business, which in turn restrains exporters/importers from doing business, thus leading to less trade.

Figure 7: Domestic currency vs Hard currency and Its Impact on trade


once the gold dinar is established as the common currency for payment for trade, some advantages could arise for participants. Joining in a common currency, according to Grauwe (2000:58), will remove the uncertainty risk due to volatility of the exchange rate. In the case of gold dinar, meera (2004) contends that gold dinar payment will totally eliminate exchange rate risk. There is no need for a trader to hedge currency to minimize risk, because hedging cost is fixed against the gold dinar itself. furthermore, transaction cost will be minimized since it can be affected electronically (see figure 8).

Figure 8: the Mechanism of How Gold is estimated to Increase trade

Along with the benefits just mentioned, the gold dinar would improve trade in three ways:

firstly, the relative stability of gold may influence in two fronts (Izhar and Asutay, 2005): the fluctuation of general prices is relatively controllable, thus inflation should be relatively low; there is no opportunity to create


unlimited money, since this will be subject to availability of gold. Hence, there will be harmonization between the real sector and the monetary sector. As a result, the phenomenon of appreciation or depreciation will be relatively manageable.

secondly, as discussed earlier, implementing the gold dinar based on mPA will provide massive efficiency in term of the amount of gold to sustain the trade. In addition, since the members of the gold dinar bloc will support each other, the trade-creating effect is expected to take place. Given this situation, the gold dinar may serve as an optimum currency if more countries are expected to join. on his famous optimum currency area (ocA) theory, mundell (1977a; 1977b) states that implementation of ocA would also reduce transaction costs in trade. He affirms that “the more countries join a currency area, the more efficient it will be”. The more oIc members are involved, the more efficient it will be. from the empirical results, we have already demonstrated that the efficiency of the GDTB increases from 76.68% to 80.09% after four other countries joining in the bloc.

finally, aside from economic factors, the success of international trade is basically also determined by political bargaining. The success of the gold dinar will constitute an immense capital with which to negotiate with developed countries, especially in respect of unfair trade practices. It is no secret that the industrialized countries use their position in the world Trade organization (wTo) to protect their interests. stiglitz (2002:244) points out that some of them demonstrate a hypocritical attitude by advocating the opening up of markets in developing countries while keeping their own markets closed to the produce and products of developing countries, such as textiles and agriculture. Hence, successful implementation of the gold dinar will be the source of a new energy and confidence among oIc countries so that they have a better bargaining position to deal with their trade partners, particularly developed counties. This will produce incentives which encourage not just intra-trade but also inter-trade.

5.2. Why does the idea not get off the ground? The trade-creating effect and efficiency generated by GDTB so far are convincing. why then does the idea not move towards becoming a reality? It may be argued that implementation is difficult due to inadequate gold reserves in the countries concerned. As we just calculated for the year 2002, the net payment was around 13.8 million gold dinars or the equivalent of 4,292 tons of gold. This entails vast reserves, beyond the capacity of the oIc


member countries (see Table 24). In 2002, total gold reserves held by the deficit countries in the trade bloc was a mere 314.5 tons of gold.

table 21: Gold Dinar Required for Intra-trade and Gold Reserve

Kept by central Bank in 2002

countries Gold Required (ton)20 Gold Reserve (ton)21

malaysia 2,581 36.4

Turkey 186.6 116.5

Pakistan 1,525 65.1

total 4,293 218.0

At first glance, looking at Table 21, those countries could not effect their trade based on the gold dinar on account of a lack of gold reserves. However, this is not the case in fact since all of those countries do hold adequate reserves in dollars. malaysia, for example, in 2002 held over 34 billion dollars in its reserve account. That amount is equal to 3,070 tons of gold. other countries also recorded large amounts of total reserves in dollars (see Table 22). In other words, basically, these countries are able to implement the gold dinar by converting a part of their dollar reserves into gold, the potential of which depicted in Table 23.

table 22: countries’ total Reserve in 2002 and Its Value in Gold

countriesReserve Minus Gold22

(Million Dollar)Reserve Value

(Million Gold Dinar)Reserve Value

(ton Gold)

malaysia 34,221 98.7 30,699

Turkey 27,068 78.07 24,282

Pakistan 8,078 23.29 7,244

total 69,367 200.06 62,225

table 23: Potential Gold Reserve (ton) and Gold needed

to settle transaction (%)

countriesGold Required

(ton)Actual Gold

Reserve (ton)Potential

Gold ReserveGold needed

to serve %

malaysia 2,581 98.7 30,699 8.4

Turkey 186.6 78.07 24,282 0.76

Pakistan 1,525 23.29 7,244 21.0

total 4,293 200.06 62,225


As an illustration, malaysia in 2002 had a reserve 34,221 million dollar. If malaysia would convert this reserve totally to gold, then they would have potential gold reserve equal to 30,699 ton gold. Theoretically, although malaysia has had to pay 2,581 ton gold because of its suffer trade deficit with its trade partners, still this deficit can be easily settled since it was only 8.4% of its giant potential gold reserve (see Table 22 and 23).

5.3. conclusionThis study has attempted to find whether and how the implementation of the gold dinar proposal would affect trade among oIc members. The findings from the empirical analysis and available evidence from the literature help to answer this challenging question. The following remarks can be made in light of the available evidence and the findings:

(i) The gold dinar is considered to be more stable than fiat money, i.e., the Us dollar. The term ‘stable’ here has the practical sense of ‘low volatility’, whereas the dollar is considerably more volatile. Empirical results produced by this study prove that in terms of gold, dollar tends to depreciate and its real exchange rate (rEr) volatility has an absolutely negative impact on developing countries’ exports. The variable is statistically significant at 5% level of significance, as explained previously. However, its direct impact on trade is very low as illustrated by its coefficient (0.009), as shown earlier. Thus, the findings are inconsistent with the hypothesis explored in this study.

(ii) Establishing a gold dinar trade bloc will likely encourage intra-trade among oIc members. Empirical results in this study suggests that those involved in the bloc will enjoy an increase of more than 2 units of their respective intra-trade. This is indeed a very convincing result, since the variable is also consistently statistically significant in various models tested at 5% level of significance. In other words, the gold dinar bloc is an economic bloc which offers to its members a trade-creating effect. This effect is more robust than those generated by currently existing economic blocs within the oIc, including AmU and cEAU.

(iii) Another interesting finding for those joining the gold dinar bloc is the efficiency generated by it. Empirical results in this study demonstrate that if six countries selected would join in the gold dinar bloc, trade efficiency in terms of payments will be around 76.68%. which implies that they only need to pay the remaining 23.32% at the end of the trade


period. This figure becomes larger if the number of member countries is increased. A simulation by adding another four countries (making the total number of countries involved 10) showed that the efficiency increases to almost 80%. such an improvement is perhaps because the selected countries are the top ten leading exporting countries within the oIc. Perhaps, this efficiency will tend to diminish slightly if the additional joining countries do not have any significant intra-trade.

(iv) from these three basic explanations, it may be deduced that the implementation of the gold dinar proposal will be a move forward for muslim countries, in the sense that it will bring many economic advantages. Their respective trade tends to increase. Unfortunately, the project is likely not feasible since there are insufficient gold reserves held by the members. If this can be tackled, perhaps the gold dinar would become the main tool, not just to unite muslim countries but also to disseminate economic cooperation and foster prosperity among them.

5.4. RecommendationInsufficient gold reserves held by most of Islamic countries will be the most serious critical problem to be handled. To confront this shortage, former malaysian Prime minister mahathir suggested that those taking part in gold dinar trade should help each other by purchasing some materials from the poorest gold reserve countries thus enabling them to participate in the trade (mahathir, 2002). This probably would render a little help.Alternatively, this study recommends two points:

(i) At the starting stage, use of the gold dinar can be restricted to facilitate trade between member governments excluding private trade. There are two advantages in this strategy: firstly, the amount of trade will be reduced, that is, each member may hold sufficient gold stocks to sustain their respective government’s trade; secondly, the administration is likely to be less complex since the trade is fully backed by the government.

(ii) The level of gold reserves can be improved by converting a significant part of the country’s dollar reserves into gold. Almost all of the countries assumed to be in the gold dinar have massive reserves in dollars. Thus, by converting up to half of the dollar reserve into gold, the insufficiency of gold stock to sustain trade can be met.


Notes

1. That trade-creating effect (as opposed to trade-diverting effect) occurs when some domestic production in a member state of the trade bloc is replaced by lower cost imports from other members. see salvatore (2001:328-329).

2. Trade was the main vehicle for the spread of Islamic teaching from Andalusia (spain) to the cape of Good Hope in Africa and to the malay Peninsula. see, for example, Yakcop (2002a).

3. IccIcE is intended to promote trade, commerce and industrial cooperation.4. At the official level this idea was first launched by Bangladesh in the second summit

meeting of oIc Heads of states, held in Taif in 1981. A year later, the issue has gained more attention once morocco again sounded the need to shape Icm in the Third General Assembly of the Islamic chamber of commerce (Icc) held in casablanca. finally, the fourth General Assembly of the Icc held in Jakarta in 1983, repeated the importance of establishing an Icm (Harjono as cited in sadeq, 1996:49). IcDT is intended to encourage regular commercial contacts and promote the harmonization of commercial and investment policies among member countries.

5. The most striking feature of an fTA is the removal of existing restrictions on trade among the regional members (satiroglu, 1986:5).

6. It is the next step after fTA has been established. custom Union entails, as well as removal of trade barriers, a common external trade policy to both members and non-members (satiroglu, 2000).

7. one of the successful aspects of the implementation of the euro was the establishment of a definite time table, which had to be adhered to by EU members. ratification of the maastricht Treaty was meant to signal the beginning of the EU’s integration. see, for example, Jovanovic (1997:18) and Keis (1997:42).

8. G-3 refers to the three major economic powers, namely UsA, Japan, and Germany.9. The six leading exporting countries are assumed to join this bloc. They are saudi

Arabia, UAE, malaysia, Indonesia, Turkey, and Pakistan.10. The council of Arab Economic Unity was established in 1957. It consists of Egypt, Iraq,

libya, Jordan, Kuwait, mauritania, somalia, sudan, syria, UAE, and Yemen. In this study four countries, namely Iraq, mauritania, somalia, and sudan, were excluded due to unavailability of data.

11. The Arab maghrib Union (AmU) was established in 1987, comprising five countries: Algeria, libya, mauritania, morocco, and Tunisia. Again, due to incomplete data, mauritania and morocco were excluded.

12. The D-8 was founded in 1997. It unites the eight countries of Bangladesh, Egypt, Indonesia, Iran, malaysia, nigeria, Pakistan, and Turkey. All these countries are included in the study.

13. since it is a double log model, the antilog value is employed. The antilogs of 0.4 and 0.12 are 2.51 and 1.33, respectively.

14. Antilog of 0.5176 is 3.293

15. Total trade = 20541 million dollar

16. 1 troy ounce = 0.311035 kilogram 13,800,000 troy ounce = 4292283 kilogram = 4,292 ton 17. It is assumed that nigeria, Iran, Kuwait, and syria are involved in the bloc.


18. The complete calculation is as follows: net payment = Np = (8.74+4.6+1.9+2.02+1.25) million gold dinars = 18.51 million gold dinars Total value of Trade =TvT = 92.98 million gold dinars

(TVT-Np)x100 (92.98-18.51) x 100 Efficiency = = TVT 92.98

= 80.09%

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