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POTENTIAL BENEFITS TO THE STATE OF QATAR FROM MEMBERSHIP IN THE GCC CUSTOMS UNION METWALLY, Mokhtar M.

University of Qatar Abstract

This paper uses cointegration and regression analyses to assess potential benefits to the State of Qatar from the recently established Customs Union between the six member states of the Gulf Cooperation Council (GCC): Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and the United Arab Emirates. This assessment is based on an analysis of the long-term relationship between Qatar Intra-trade with other members of the GCC and Qatar total trade.

The regression results suggest that Qatar total intra- trade with both Saudi Arabia and the United Arab Emirates grew at a much faster rate than Qatar total trade with non-GCC members during the period 1980-2000. Hence, the postulates of the theory of customs unions gradually become increasingly more relevant to Qatar trade with Saudi Arabia and the United Arab Emirates. On the other hand, the past growth of Qatar intra-trade with Bahrain, Kuwait and Oman suggests that Qatar economic integration with these three members is not likely to increase Qatar’s economic welfare if the current path of intra-trade growth continues.

JEL classification: C5, F1, N75, O53

Keywords: Gulf Cooperation Council, Intra-trade of Qatar

Mail: [email protected] This study is part of a major research project conducted by the National Center for Economic Research at the University of Qatar. The Center is financially sponsored by Qatar National Bank.

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1. Introduction

The Gulf Cooperation Council (GCC) was established, as a Free-Trade Area, in 1979 with the ultimate aim of creating a political union between its six members, namely Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and United Arab Emirates. Almost 23 years have passed since the creation of the GCC, yet no attempt was made to assess its impact on the economic welfare of individual members.

The present study attempts to fill in this gap in the literature by analysing the long term relationship between Qatar intra-trade with the other five members.

The importance of this study stems from the fact that the six members of the GCC have just announced the establishment of a customs union between them to take effect as from 1st January 2003.

The state of Qatar was selected as a case study for two reasons: First, Qatar is the smallest member state in terms of population yet the richest in terms of average per capita income.

Hence, it is legitimate to enquire if Qatar has economically benefited from being a member of the GCC Free-Trade Area. Secondly, Very little is known about the performance of Qatar’s trade sector.

This study attempts to throw some light on the relevant issues and opens the door for further needed research. The methodology used in this study can be applied to other members of the GCC to assess the potential impact of the customs union on their economies.

Qatar’s exports of goods, mainly oil and natural gas, has been stable around an average of approximately 3.5 billion US dollars during the period 1990-1997, these exports increased by approximately 50% per annum between 1998 and 2000. They reached a peak level of 11.4 billion US dollars in the year 2000, or 71 percent of Qatar GDP in that year. Available statistics also suggest that Qatar’s total imports in 2000 were less than 3.3 billion US dollars or approximately 20 percent of Qatar GDP in that year.

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Hence, Qatar was left with a healthy trade surplus of approximately 8.2 billion US dollars or 50 percent of Qatar GDP in that year. However, this is an exceptional year, affected by the sharp rise in oil prices. The trade balance during the period 1990-1998 never reached 2 US billion dollars or 12.5 percent of Qatar GDP (IMF, 2001).

Qatar’s total exports to other members of the GCC, though still a small proportion of total Qatar’s exports, have increased seven- fold over the two decades following the creation of the GCC Free- Trade Area. However, the growth in Qatar’s exports to various GCC members has not been uniform.

Most Qatar’s exports to other GCC members consist of Plastics, Iron and steel, oils and gas (natural and manufactured).

Qatar’s imports from the GCC enjoyed a six-fold increase over the last two decades. These imports accounted for 14.8 percent of total Qatar imports in 2000. Here again, the rate of growth was not uniform amongst various GCC members. Qatar’s imports from Saudi Arabia and the United Arab Emirates enjoyed much higher growth than Qatar’s imports from the other three GCC States.

Over 80 percent of Qatar’s imports from the GCC come from Saudi Arabia and the United Arab Emirates. Both Oman and Kuwait do not seem to be successful in penetrating the Qatari markets.

Qatar’s main imports from the GCC consist of metalliferous ores and non-ferrous metals from Bahrain, electric machinery from Kuwait and Oman, dairy products, vegetables and fruits, non-metallic mineral manufactures, manufactures of metals and general industrial machinery from Saudi Arabia and non-metallic mineral manufactures, iron and steel, and miscellaneous manufactured articles from the United Arab Emirates.

The aim of this paper is to test if there is a long-term relationship between Qatar intra-trade with other members of the GCC and Qatar total trade with non- GCC countries. If such a relationship exists, this would suggest that the two variables do not

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drift too far apart from each other over time. In other words there is evidence of cointegration between the two variables.

However if there is no evidence of cointegration, the relative magnitude of Qatar intra-trade with its GCC partners may be increasing or decreasing over-time. If there is evidence of an increase in the relative magnitude of intra-trade with other GCC partners, this would suggest that the customs union between the GCC countries is more likely to raise welfare of the State of Qatar as time goes on.

The paper is divided into three sections. Section 1 uses Johansen technique to test for long-term relationship between Qatar intra-trade with other members of the GCC and Qatar total trade.

Regression analysis is used in Section 2 to examine the pattern of behaviour of Qatar intra-trade with the GCC. Finally, section 3 summarises the main conclusions of the paper.

2. Cointegration tests of long-term relationship between Qatar intra-trade with GCC countries and Qatar total trade

If a long-run relationship exists between Qatar intra-trade with other members of the GCC and Qatar total trade with non-GCC countries, the two variables must form a unique integrating vector. In order to test for cointegration, and in particular to investigate whether a unique cointegrating vector can be identified, we have employed the maximum likelihood estimation technique developed by Johansen (1988) and Johansen and Juselius (1990). This approach does not have the now well-docume+nted drawbacks of the Engle and Granger (1987) approach to cointegration and can be used in a multivariate setting to establish the numbers of distinct cointerating vectors (Maddala and Kim, 1998 and Neg and Perron, 1997).

The first step in implementing this approach is to test for the order of cointegration of each variable included in the model. It is a common practice to apply the Augmented Dickey – Fuller Test (ADF) given by the following equation for variable Z.

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Zt = α + βZt-1 + Σk i=1 τi ∆ Z t-1 + ωt,

Where, ω is an error term (Dickey and Fuller, 1979 and Dickey and Rossana, 1994)).

The cumulative distribution of the ADF test statistic is provided by Mackinnon (1991). If the calculated statistics is less than its critical value, then Z is said to be stationary or 1(0).

Table 1 represents the results of the Augmented Dickey – Fuller test. It is clear that the calculated ADF statistic for the variables representing Qatar intra-trade with other members of the GCC and with non-GCC countries is less than its critical value only for the differenced variables. This indicates non-stationarity of these variables at the level and that the variables have achieved stationarity after being differenced once. Thus, the variables are integrated of order one, I(1). This fact enables us to conduct the cointegration analysis. (Johansen, 1988).

Table 1. Unit Root Tests of Qatar Total Trade with Non- GCC Countries and Qatar Intra-Trade with Members of the GCC

Variable log (QT) log (QT) ∆log (QT)

Qatar intra-trade with Bahrain -2.1910 -5.2833 Qatar intra-trade with Kuwait -2.1102 -4.3454 Qatar intra-trade with Oman -1.7908 -4.3559 Qatar intra-trade with Saudi Arabia -2.3113 -6.7677 Qatar intra-trade with UAE -2.3916 -6.5845 Qatar intra-trade with all GCC -1.8491 -6.0030 Qatar total trade with non-GCC Countries -2.3547 -5.3699

Note: 74 observations used in the estimation of all ADF regressions. Sample period from 1981Q1 to 2000Q2. The Dickey-Fuller regressions include an intercept and a linear trend 95% critical value for the augmented Dickey-Fuller statistic = -3.4713

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We are now in the position to carry out the cointegration tests proposed by the Johansen technique. This technique suggests a maximum likelihood estimation procedure that provides two test statistics for determining the number of cointegrating vectors as well as estimate of all cointegrating vectors that could exist among a set of variables.

The Johansen’s maximum likelihood method specifies three cases: (i) the case of non-trended variables. This case assumes that there are no deterministic trend in the variables and the underlying date generating process (DGP). (ii) trended variables with no trend in DGP. This case assumes that all variables have deterministic trend term in the DGP. (iii) trended variables with trend in DGP. This case assumes that variables as well as DGP have deterministic trend.

Since the variables show steadily rising trends, the relevant options are cases (ii) and (iii). Both of these options yield the same test statistics, but are subject to slightly different critical values (Li and Maddala, 1995 and Johansen, 1995).

The trended case, with no trend in DGP, which has higher critical values, was considered in this analysis (Wickens, 1996). The first step is to specify a lag length for the VAR, which, on the basis of the likelihood ratio test proposed by Maddala and Kim (1998), was set at four periods. Tables 2-1 to 2-6 give the cointegration results for the relationship between Qatar intra-trade with other members of the GCC and Qatar total trade with non-GCC countries.

The following conclusions can be derived from the statistical results:

1. The LR tests based on maximal eigenvalue of the stochastic matrix and the trace of the stochastic matrix (Table 2-1) suggest that the null hypothesis of no cointegration cannot be rejected for Qatar intra-trade with all other GCC members combined.

Thus, there is no evidence of long-term relationship between Qatar intra-trade with all GCC members and Qatar total trade with non- GCC countries. In other words, Qatar intra-trade with the GCC and

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Qatar total trade with non-GCC countries drifted apart from each other more and more as time went on.

2. The LR tests based on maximal eigenvalue of the stochastic matrix and the trace of the stochastic matrix (Tables 2-2, 2- 5 and 2-6) suggest that the null hypothesis of no cointegration cannot be rejected for Qatar intra-trade with Bahrain, Saudi Arabia and the United Arab Emirates. Thus, there is no evidence of long-term relationship between Qatar intra-trade with those three GCC members and Qatar total trade with non-GCC countries.

3. The LR tests based on maximal eigenvalue of the stochastic matrix and the trace of the stochastic matrix (Tables 2-3 and 2-4) suggest that the null hypothesis of no cointegration should be rejected for Qatar intra-trade with Kuwait and Oman. Thus, there is evidence of long-term relationship between Qatar intra-trade with those two GCC members and Qatar total trade with non-GCC countries. In other words, intra-trade of Qatar with each of Kuwait and Oman and Qatar total trade with non-GCC countries, did not drift too far apart from each other over time.

Table 2-1. Results of Cointegration Analysis for Qatar Total Trade with non-GCC Countries (TT) and Intra-Trade with All Other Members of the GCC (ITGCC).

Cointegration with unrestricted intercepts and restricted trends in the VAR.

1.Cointegration LR Test Based on Maximal Eigenvalue of the Stochastic Matrix

74observations from 1981Q1 to 2000Q2. Order of VAR = 4

.

List of variables included in the cointegrating vector

:

ITGCC TT Trend List of eigenvalues in descending order

:

. 18167 . 066905

0.00

Null Alternative Statistic 95% Critical Value 90% Critical Value r = 0 r = 1 11.1044 19.2200 17.1800 r<= 1 r = 2 6.0080 12.3900 10.5500

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2.Cointegration LR Test Based on Trace of the Stochastic Matrix 74observations from 1981Q1 to 2000Q2. Order of VAR = 4

.

List of variables included in the cointegrating vector

:

ITGCC TT Trend List of eigenvalues in descending order

:

. 18167 . 066905

0.00

Null Alternative Statistic 95% Critical Value 90% Critical Value r = 0 r>= 1 18.3346 25.7700 23.0800

r<= 1 r = 2 6.0080 12.3900 10.5500

Table 2-2. Results of Cointegration Analysis for Qatar Total Trade with non-GCC Countries (TT) and Intra-Trade with Bahrain (ITB).

Cointegration with unrestricted intercepts and restricted trends in the VAR 1.Cointegration LR Test Based on Maximal Eigenvalue of the Stochastic Matrix

74observations from 1981Q1 to 2000Q2. Order of VAR = 4

.

List of variables included in the cointegrating vector

:

ITB TT Trend

List of eigenvalues in descending order

: . 18167 . 066905

0.00

Null Alternative Statistic 95% Critical Value 90% Critical Value r = 0 r = 1 14.5243 19.2200 17.1800

r<= 1 r = 2 4.3136 12.3900 10.5500

2.Cointegration LR Test Based on Trace of the Stochastic Matrix 74observations from 1981Q1 to 2000Q2. Order of VAR = 4

.

List of variables included in the cointegrating vector

:

ITB TT Trend

List of eigenvalues in descending order

: . 18167 . 066905

0.00

Null Alternative Statistic 95% Critical Value 90% Critical Value r = 0 r>= 1 21.0399 25.7700 23.0800

r<= 1 r = 2 4.3136 12.3900 10.5500

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Table 2-3.Results of Cointegration Analysis for Qatar Total Trade with non-GCC Countries (TT) and Intra-Trade with Kuwait (ITK).

Cointegration with unrestricted intercepts and restricted trends in the VAR 1. Cointegration LR Test Based on Maximal Eigenvalue of the Stochastic Matrix

74observations from 1981Q1 to 2000Q2. Order of VAR = 4

.

List of variables included in the cointegrating vector

:

ITK TT Trend

List of eigenvalues in descending order

: . 26279 . 10260 . 0000

Null Alternative Statistic 95% Critical Value 90% Critical Value r = 0 r = 1 23.7810 19.2200 17.1800

r<= 1 r = 2 8.4441 12.3900 10.5500

2. Cointegration LR Test Based on Trace of the Stochastic Matrix 74observations from 1981Q1 to 2000Q2. Order of VAR = 4

.

List of variables included in the cointegrating vector

:

ITK TT Trend

List of eigenvalues in descending order

: . 26279 . 10260 . 0000

Null Alternative Statistic 95% Critical Value 90% Critical Value r = 0 r>= 1 32.2251 25.7700 23.0800

r<= 1 r = 2 8.4441 12.3900 10.5500

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Table 2-4. Results of Cointegration Analysis for Qatar Total Trade with non-GCC Countries (TT) and Intra-Trade with Oman (ITO).

Cointegration with unrestricted intercepts and restricted trends in the VAR

1.Cointegration LR Test Based on Maximal Eigenvalue of the Stochastic Matrix

74observations from 1981Q1 to 2000Q2. Order of VAR = 4

.

List of variables included in the cointegrating vector

:

ITO TT Trend

List of eigenvalues in descending order

: . 23047 . 060381 .

0000

Null Alternative Statistic 95% Critical Value 90% Critical Value r = 0 r = 1 20.4342 19.2200 17.1800

r<= 1 r = 2 4.8579 12.3900 10.5500

2. Cointegration LR Test Based on Trace of the Stochastic Matrix 74 observations from 1981Q1 to 2000Q2. Order of VAR = 4

.

List of variables included in the cointegrating vector

:

ITO TT Trend

List of eigenvalues in descending order

: . 23047 . 060381 .

0000

Null Alternative Statistic 95% Critical Value 90% Critical Value r = 0 r>= 1 27.2922 25.7700 23.0800

r<= 1 r = 2 4.8579 12.3900 10.5500

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Table 2-5.Results of Cointegration Analysis for Qatar Total Trade with non-GCC Countries (TT) and Intra-Trade with Saudi Arabia (ITS).

Cointegration with unrestricted intercepts and restricted trends in the VAR 1.Cointegration LR Test Based on Maximal Eigenvalue of the Stochastic Matrix

74observations from 1981Q1 to 2000Q2. Order of VAR = 4

.

List of variables included in the cointegrating vector

:

ITS TT Trend

List of eigenvalues in descending order

: . 18167 . 066905

0.00

Null Alternative Statistic 95% Critical Value 90% Critical Value r = 0 r = 1 14.2186 19.2200 17.1800

r<= 1 r = 2 5.5490 12.3900 10.5500

2.Cointegration LR Test Based on Trace of the Stochastic Matrix 74observations from 1981Q1 to 2000Q2. Order of VAR = 4

.

List of variables included in the cointegrating vector

:

ITS TT Trend

List of eigenvalues in descending order

: . 18167 . 066905

0.00

Null Alternative Statistic 95% Critical Value 90% Critical Value r = 0 r>= 1 20.1416 25.7700 23.0800

r<= 1 r = 2 5.5490 12.3900 10.5500

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Table 2-6.Results of Cointegration Analysis for Qatar Total Trade with non- GCC Countries (TT) and Intra-Trade with United Arab Emirates (ITUAE).

Cointegration with unrestricted intercepts and restricted trends in the VAR

1.Cointegration LR Test Based on Maximal Eigenvalue of the Stochastic Matrix

74observations from 1981Q1 to 2000Q2. Order of VAR = 4

.

List of variables included in the cointegrating vector

:

ITUAE TT Trend List of eigenvalues in descending order

:

. 10966 . 093489

0.00

Null Alternative Statistic 95% Critical Value 90% Critical Value r = 0 r = 1 9.0600 19.2200 17.1800

r<= 1 r = 2 7.6559 12.3900 10.5500

2.Cointegration LR Test Based on Trace of the Stochastic Matrix 74observations from 1981Q1 to 2000Q2. Order of VAR = 4

.

List of variables included in the cointegrating vector

:

ITUAE TT Trend List of eigenvalues in descending order

:

. 10966 . 093489

0.00

Null Alternative Statistic 95% Critical Value 90% Critical Value r = 0 r>= 1 16.7159 25.7700 23.0800

r<= 1 r = 2 7.6559 12.3900 10.5500

2. Patterns of Growth of Total Trade and Intra-Trade of GCC Countries

The results of cointegration analysis suggest that there is no evidence of long-term relationship between Qatar intra-trade with all GCC members combined and Qatar total trade with non-GCC countries. The results of cointegration analysis also suggest that there is no evidence of long-term relationship between Qatar intra-trade with Bahrain, Saudi Arabia and the United Arab Emirates and Qatar total trade with non-GCC countries. These results indicate that Qatar

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total trade and its intra-trade with some GCC members have been drifting apart from each other more and more over the last two decades. This could imply that the relative magnitude of Qatar intra- trade with its GCC partners may be increasing or decreasing over- time. The question is: how did the two variables drift apart? In other words, did intra-trade grow faster than trade with other countries?

This section attempts to answer this question.

If Qatar intra-trade with GCC countries is increasing faster than its total trade with other countries, the postulates of the theory of customs unions gradually become increasingly more relevant to Qatar trade with other GCC members (Lipsey, 1957 and Meade, 1955).

Figure 1 depicts the trends in Qatar Intra-trade with GCC Members (IT) and total Qatar trade with other Countries (TTO). A log transformation was applied to the two variables in order to highlight their time-path. It can be seen that Qatar intra trade with its GCC partners is growing much faster than Qatar total trade with non- GCC members since the creation of the GCC Free=Trade Area.

The behavior of the ratio of Qatar intra-trade with other members of the GCC to Qatar total trade with other Countries (IT/TTO) is depicted in Figure 2. It can be inferred that the percentage of Qatar trade with its GCC partners to Qatar total trade has been increasing since 1980.

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Graph 1

Trends in Qatar Intra-trade with GCC Members (IT) and Total Trade with other Countries (TTO)

Transforms: natural log TIME

1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985 1984 1983 1982 10

9

8

7

6

5 4

IT TTO

Graph 2

Ratio of Qatar Intra-Trade with members of the GCC to Qatar Trade with other Countries (IT/TTO)

TIME

1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985 1984 1983 1982

ITTTO

.14 .12 .10 .08 .06 .04 .02 0.00

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The information given by figures 1 and 2 together with the results of cointegration analysis suggest that Qatar intra-trade with all other GCC members combined may have been increasing faster that Qatar total trade with non-GCC members.

To test these findings and also check if the same conclusion applies to individual GCC trading partners, a number of regression models have been tested(1).

We compared the (constant proportional) rates of growth of Qatar intra-trade with other GCC members (QIT) with that of Qatar total trade with non-GCC members (QTT). We also tested the behavior of the share of Qatar intra-trade with other members of the GCC to Qatar total trade over time.

Table 3 summarizes the relevant regression results for all GCC countries combined and for the three GCC partners, for which the null hypothesis of no cointegration could not be rejected. These results relate to the period 1980-2000. It can be seen that :

1. Qatar intra-trade with all GCC members grew at a constant proportional rate of approximately 12.2%, while Qatar total trade with non-GCC members grew at a rate of only 8.2% per annum during the period 1980-2000.

2. The share of Qatar intra-trade with GCC countries to total Qatar trade has been increasing by approximately 0.4% annually during the period 1980-2000

The following two models were tested to estimate the (constant- proportional) rates of growth:

Ln (QIT) t = α + g1 t + µ1t (1) Ln (QT) t = α + g 2 t + µ2 t (2)

Where, g1 and g2 represent the proportional (constant) rate of growth, i.e g1 = { (d (QIT) / dt) ( 1/(QIT)}

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and

g2 = { (d (QT) / dt) ( 1/(QT)}

If Qatar intra-trade (QIT) with other GCC members grows faster than Qatar trade with non –GCC countries (QT), we would expect g1 › g2. (Gujarati, 2002) The following model was used to test the behavior of the share of intra-trade to total trade over time

(QIT / QT) t = α + h t + µ3t (3)

If the coefficient “h” were positive and statistically significant, this would indicate that intra-trade grows faster than total trade.

1.

Qatar total intra- trade with Bahrain did not show any significant growth over the period 1980-2000. Also, the share of Qatar intra-trade with Bahrain to total Qatar trade has not increased to any significant extent over time since the creation of the GCC.

2.

Qatar total intra- trade with Saudi Arabia grew at a much faster rate (14.2%) than Qatar total trade with non-GCC members (8.2%).

Also, the share of Qatar intra-trade with Saudi Arabia to total Qatar trade has been increasing over time since the creation of the GCC.

The regression results suggest that this share increased by approximately 0.67 percent annually during the period 1980-2000.

3.

Qatar total intra- trade with the United Arab Emirates grew at a constant proportional rate of approximately 18.4 per cent, compared to the growth rate of Qatar total trade with non-GCC members of only 8.2 percent per annum during the period 1980-2000. Moreover, the share of Qatar intra-trade with the United Arab Emirates to total Qatar trade increased by approximately 0.82 percent annually during the same period.

The results of regression analysis suggest that the postulates of the theory of customs unions gradually become increasingly more relevant to Qatar trade with Saudi Arabia and the United Arab Emirates.

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However, the past growth of Qatar intra-trade with Bahrain, Kuwait and Oman suggests that Qatar economic integration with these three members is not likely to increase its economic welfare if the current path of intra-trade growth continues.

Table 3. Regression Results of growth and Performance of Qatar intra-trade with other GCC Members

Variables Growth(%) Change(%)

Non-GCC 8.2 (11.8)*

All GCC 12.2 (18.6)* 0.40 (37.5)*

Bahrain 7.1 (1.875) 0.22 (1.756) Saudi Arabia 14.2 (32.3)* 0.67 (41.9)*

UAE 18.4 (14.8)* 0.82 (30.7)*

Notes: Figures in parentheses are t-values.

* Indicates that the coefficient is statistically significant

3. Conclusions

The main conclusions of this paper may be summarized in the following:

1. The LR tests based on maximal eigenvalue of the stochastic matrix and the trace of the stochastic matrix suggest that the null hypothesis of no cointegration cannot be rejected for Qatar intra-trade with all other GCC members combined.. Thus, there is no evidence of long-term relationship between Qatar intra-trade with all GCC members and Qatar total trade with non-GCC countries.

2. The LR tests based on maximal eigenvalue of the stochastic matrix and the trace of the stochastic matrix suggest that the null hypothesis of no cointegration cannot be rejected for Qatar intra-trade with Bahrain, Saudi Arabia and the United Arab Emirates.

Thus, there is no evidence of long-term relationship between Qatar

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intra-trade with those three GCC members and Qatar total trade with non-GCC countries.

3. The LR tests based on maximal eigenvalue of the stochastic matrix and the trace of the stochastic matrix suggest that the null hypothesis of no cointegration should be rejected for Qatar intra-trade with Kuwait and Oman. Thus, there is evidence of long- term relationship between Qatar intra-trade with those two GCC members and Qatar total trade with non-GCC countries.

4. Qatar intra-trade with both Saudi Arabia and the United Arab Emirates grew much faster than Qatar total trade with non-GCC countries during the period 1980-2000.

5. The postulates of the theory of customs unions gradually become increasingly more relevant to Qatar trade with Saudi Arabia and the United Arab Emirates.

6. The past growth of Qatar intra-trade with Bahrain, Kuwait and Oman suggests that Qatar economic integration with these three members is not likely the increase their economic welfare if the current path of intra-trade growth continues.

Bibliography

Dickey, D. and Fuller, W. A.(1979). “Distribution of the Estimates for Auto regressive Time Series with a Unit Root”. Journal of the American Statistical Association, Vol. 74, June, pp. 427-31.

Dickey, D. A. and Rossana, R. J.(1994), ‘Practitioners’ Corner’, Cointegrated Time Series: A Guide to Estimation and Hypothesis Testing, Oxford Bulletin of Economies and Statistics, 56, pp. 325-53.

Engle, R. F. and Granger, C. W.(1987). “Co-Integration and Error Correction: Representation, Estimation and Testing”, Econometrics, Vol. 55, March, pp. 143-159.

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Gujarati, D. N.(2002). “Basic Econometrics”. McGraw-Hill Book Co., Singapore.

IMF(2001). “International financial Statistics 2001 Yearbook”.

Washington, D. C., IMF

Johansen, S.(1988). “Statistical Analysis of Cointegration Vectors”.

Journal of Economic Dynamic and Control, Vol. 12, July, pp. 231- 254.

Johansen, S. and Juselius, K.(1990). “Maximum Likelihood Estimation and Inference on cointegration with Applications to the Demand for Money”, Oxford Bulletin of Economics and Statistics, 52, pp. 169-201.

Johansen, S. (1995). “Likelihood Based Inference on Cointegration In the Vector autoregressive Model”. Oxford University Press, Oxford.

Li, H. and Maddala, G. S.(1995). “Estimating Long-run Relationship in Economics: Some Comments and Further Results”. Manuscript, Ohio State University.

Lipsey, R. G.(1957). “The Theory of Customs Unions: Trade Diversion and Welfare”. Economica, New Series, Vol. 24, February.

Maddala, G. S. and In – Moo Kim(1998). “Unit Roots, cointegration and Structural Change”. Cambridge University Press.

Mackinnon, J. J.(1991). “Critical Values for Cointegration Tests” in Long-run Economic Relationships: Readings in Cointegration, ed. R.

F. Engle and C. W. Granger, Oxford, Oxford University Press, pp.

267-276.

Meade, J. E.(1955). “The Theory of Customs Unions”. Amsterdam, North Holland

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Ng. S. and Perron, P.(1997). “Estimation and Inference in Nearly Un balanced Nearly Cointegrated Systems”. Journal of Econometrics, 79, pp. 53-81.

Wickens, M. R.(1996). “Interpreting Cointegrating Vectors and Common Stochastic Trends”. Journal of Econometrics, 74, pp. 255- 271.

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