Applied Econometrics and International Development Vol (2015)

Transcription

1 ARE EXPORTS AND IMPORTS OF SAUDI ARABIA COINTEGRATED? AN EMPIRICAL STUDY HAQUE, M.I. * Abstract The objective of this study is to examine the long run cointegration between exports and imports of Saudi Arabia from Using Johnson s approach of cointegration, this study finds that exports and imports converge towards equilibrium in the long run implying that the trade policy is being managed well as per its comparative advantage and there is both long run and short run causality running from exports to import. This study prominently improves upon the results of the only other study on Saudi Arabia (to the author s best of knowledge) by including the Vector Error Correction Model (VECM). This study also advocates caution while using EViews6 with smaller datasets. JEL Codes: C22, C87, F14, 024, O53 Keywords: Exports, Imports, Cointegration, Saudi Arabia 1. Introduction The conventional wisdom of economics proposes that everything is fine in an economy if there are no productivity shocks of permanent nature and no distortion of policies. Then, there is a natural tendency towards a long run relationship between exports and imports. This view was further substantiated by Richard and Tiwari (2013) when they advocated that predictions were reliable from policy perspectives when a country had a sustainable trade balance. The pioneering work of studying the empirical relationship between exports and imports could be attributed to Husted (1992) who studied the external imbalances of United States and the long run tendency of the country s current account balance by estimating cointegrating regressions between exports and imports for the period using quarter wise data. Using Engle-Granger tests between different measures of exports and imports he found that the current account moved to zero till 1983 after which there was a structural shift in trade leading to a tendency for a deficit over $100 billion in the long run. He made a simple theoretical foundation for a small open economy which possessed an ability to produce and export, without government intervention, and consumers had accessibility of international funds. The budget constraint for the current period is C 0 = Y 0 +B 0 I 0 (1+r 0 ) B -1 ; where C 0 is the current consumption, Y 0 is current output, I 0 is current investment, r is the international rate of interest and (1+r 0 ) B -1 is the initial debt size. After using several assumptions the final equation showing the relationship between exports and imports is derived, which is as follows: Xt = α + b*mmt + et; where, Xt is exports, MMt is imports plus rtbt-1 and et is the error term. Here the null hypothesis was that the economy s intertemporal budget constraint is satisfied for which b had to be equal to 1 and et term had to be stationary which implied that X and MM were cointegrated. * Mohammad Imdadul Haque, College of Business Administration, Al Kharj, P.O.Box:165 Prince Sattam bin Abdulaziz University, Saudi Arabia. dr.m.i.haque@gmail.com

2 Later, Bahmani-Oskooee (1994), Arize (2002), Naranyn and Naranyn (2005) and several other studies stated that the presence of cointegration between exports and imports imply that the country was not violating its intertemporal budget constraint, and if there was any trade deficit, it would be a short run phenomenon and was sustainable in the long run. Further it implied that the macroeconomic policies were effective in leading to convergence of exports and imports. In contrast, there is an absence of cointegration between exports and imports and it implies the growth in international indebtness is not sustainable in the long run and in due course the difference between exports and imports as a percentage of Gross Domestic Product (GDP) would increase without bounds. Further, as per Irandoust and Ericsson (2004) the presence of cointegration between exports and imports also points out at the absence of productivity gap between the country s economy and the remaining world. Further it hinted at the absence of permanent technological shocks to the country s economy. The country of interest in this study is Saudi Arabia, an oil-based economy, which is one of the largest producers and exporters of oil. It imports both consumer and capital goods, but capital goods have been very important since the first oil boom in the 1970s because of the rapid increase in infrastructure development projects. In fact with the export of oil and increased revenues there in, Saudi Arabia financed its expansion of the domestic manufacturing sector which facilitated the industrialization process. This has been evident not only by large investments in oil extraction and processing infrastructure but also in electricity, road, telecommunication, airports, ports, hospitals, universities and desalination plants. This huge expenditure in fact saved the country from the Dutch disease syndrome whereby a resource rich country experiences deindustrialization and poor improvements in infrastructure. It s true that the industrial base of Saudi Arabia is insufficient to meet the demand of its population hence it depends hugely on imports but it s also true that the country has made significant strides in diversifying its production towards domestic appliances, textiles, furniture, foodstuff and likewise. But, as the production structure is centered on oil related industry, Saudi Arabia s prime item for imports are transport and machinery equipments followed by clothing, furniture, food and beverages. As part of the Saudization program, small and medium enterprises (SMEs) are being encouraged, which obviously has to depend heavily on imported equipment. The private sector is also continuously encouraged by making investment a profitable opportunity through huge investments in infrastructure and other social overhead investments, for which again imported raw materials are needed. According to the 48 th Annual report of Saudi Arabian Monetary Agency (SAMA) in 2012 the current account surplus was billion SAR and the ratio of merchandise trade to its GDP was 76.4% and oil exports increased by 6.1 percent and non-oil exports by 8.1 percent. Important non-oil exports are petrochemicals, construction materials; agriculture, animal and food products and lastly other goods including re-exports. Many a restructuring and institutional reforms are in progress making way towards economic base diversification and development of export of non-oil items. Similarly, imports were increased by 18.2 percent. The items of imports in sequence of their relative percentages are machines, appliances and equipment (26.4), followed by transport equipment (17.7), foodstuffs (13.9), metal and their products(13.8), chemical and metal products (13.6). A country like Saudi Arabia 112

3 Haque, M.I. Are Exports And Imports of Saudi Arabia Cointegrated? An Empirical Study with such a strong external sector would prove to be a good case for studying the relationship between exports and imports. The later part of the paper is structured as the following: Section II presents a review of past literature on the subject, Section III highlights the importance of this study, Section IV discusses the data, estimation technique and empirical results and finally Section V concludes the study. 2. Review of past literature As this research is aimed at studying the relationship between exports and imports in Saudi Arabia, prior studies are sought in this respect where Saudi Arabia or at the least any other GCC country is mentioned. The very first study worth mentioning is of Rammadhan and Naseeb (2008) which studied the presence of long run relationship between imports and oil exports in four of the GCC countries namely, Saudi Arabia, United Arab Emirates, Kuwait and Oman between 1967 and Using Johansen cointegration over the annual data for the aforesaid period, the study suggested at the balance in trade between oil exports and imports in the long run implying that the trade policies of these countries were effective. The Johansen regression coefficient was close to one for Saudi Arabia, Oman and UAE, while in the same study no such relationship was found for Kuwait. In another study, Al Khulaifi (2013) found a long run cointegration relationship between exports and imports in Qatar using annual data from He also used the technique of Johnson s cointegration. As exports and imports were found to be integrated of the same order and were cointegrated, error correction was used to study causality. The study established a long run one directional causality from imports to exports. The error-correction term s coefficient was negative and significant when exports were the dependent variable and indicated that around 29% of disequilibrium is corrected every year. This study concluded that imports and exports had a long run stable relationship, and the country did not violate its international budget line and its economic policies were effective at the external front. Besides these two studies no other study has been found exclusively focused on Saudi Arabia or other countries in the region of Gulf Cooperation Council (GCC). Among other studies, Arize (2002) would be stated first as he included some countries of the Middle East and North Africa (MENA) region. He tried to find the relationship between exports and imports using Johansen cointegration and Stock and Watson cointegration using quarterly data from 1973 to 1998 of 50 Organization for Economic Co-operation and Development (OECD) and developing countries. He found long run cointegration relationship for 35 countries, among which 31 countries had a positive export coefficient. Further using exclusion test he found that 86% of the sample countries had positive and significant cointegrating coefficient. This study included 5 countries from the Middle East region. He also used Stock and Watson cointegrating test to substantiate his findings and the results were consistent with the Johnson s results. Further, on the basis of LR statistics, the study found out that for 73% of the countries under study one unit of imports was balanced by one unit of exports and vice versa which indicated long run trade balance. Further, he used SupF test of Hansen to test for structural stability and indicated at general stability of the long run parameter estimates. An interesting finding of his study was that the Middle East, Europe and Latin American counties had unstable cointegrating relationships. Another observation 113

4 of this study was that exports and imports were cointegrated for all, be it, low income, middle income or high income countries. Next, in a relatively new study, Husein (2014) studied the relationship between exports and imports for nine Middle East and North Africa (MENA) countries using autoregressive distributed lag (ARDL) cointegration of Pesaran. For four of the countries there was a long run cointegrating relationship long run, and it was significant in three of these countries. He viewed that the presence of cointegration is only a necessary condition while the value of long run coefficient at unity is the sufficient condition to satisfy the intertemporal budget constraint. The long run coefficient is unity for two of the countries which implied that current account deficit is sustainable in the long run. This would lead to a one unit of import being balanced by a one unit of exports leading to a balance in the long run trade. The estimates of ECT are negative and significant implying that short run imbalances, where exports and imports drift in the short run, eventually get corrected. Further he used cumulative sum (CUSUM) and cumulative sum of square (CUMUSQ) test and found the estimated parameters to be stable. In another related study, Tang (2006b) found a long run cointegrating relationship between exports and imports in 9 Organization of Islamic Cooperation (OIC) countries out of the total 27 sample countries by using Gregory and Hansen cointegration tests on the annual data from (though some countries had a different data set). Other than the above mentioned studies some other studies were also reviewed which analyzed one country at a time or at the most two countries. Keong (et al, 2004) found a cointegrating long-run relationship between exports and imports in Malaysia for the period by using annual data. The cointegrating vectors which were estimated were positive and close to unity, implying that the country adhered to the international budget constraint. At the same time the government has been successful in stabilizing the balance of trade and the country s economic policies are successful towards the convergence of exports and imports in the long run. The short run fluctuations between exports and imports were not sustainable in the long run as it would finally converge towards a state of equilibrium. Next, Dumitriu (et al, 2008) found a cointegrating long run relationship between exports and imports for Romania using monthly data between 2008 and 2014 using Engle-Granger cointegration method. But the vector error correction model (VECM) did not have a significant exactness which according to the author was due to less number of observations. Nevertheless, his impulse response functions show that imports and exports mutually influence each other. Theoretically this relationship between exports and imports is because Romania imports raw materials which are used in productions and are eventually exported. Next, Narayan and Narayan (2005) studied the long run relationship using bounds test for cointegration between export and import for 22 developing countries from using ARDL, DOLS, Philip Hansen and Engle Granger and found the long run elasticities to be positive and significant for four of the countries. The presence of cointegration fulfilled the necessary condition towards the satisfaction of economy s intertemporal budget constraint but not sufficient condition as the coefficient in the long run was less than one. For this purpose, parameter stability tests of SupF, MeanF and Lc of Hansen were done and it established that the parameters were stable in the long run. Next, Upendra (2007) found a cointegrating long run relationship between exports and imports in India by using annual data for the 114

5 Haque, M.I. Are Exports And Imports of Saudi Arabia Cointegrated? An Empirical Study period and The study found that export s elasticity with respect to imports was little more than one, indicating that the ratio of exports to imports would increase to some extent with an increase in imports. He opined that the changes in exports corrects to changes in imports in that very year as the first ECT was negative but insignificant. This according to him implied that the amount of disequilibrium among the values in the short run and the values in the long run values in lagged periods were neither corrected nor extended, meaning that there was no disturbance. As there was equilibrium both in long run and short run, this indicated that the trade policy was successful in sustaining the balance in exports and exports. According to the second ECT a change in imports responded to a deviation from the long run equilibrium and indicated that 27% of disequilibrium was corrected each year. This indicated that the trade policy should be reviewed so that the disequilibrium between the long run and short run was removed rapidly and equilibrium was maintained. Next, Konya and Singh (2008) studied the relationship between exports and imports for India using Johnson test and Saikkonen-Lütkepohl cointegration (SLCOIN) using annual data for the period and with a one-time structural break from When the structural break was included Johnson test indicated at no cointegration and when the structural break was not taken into consideration exports and imports were cointegrated. Further, taking into consideration India s shift from fixed to floating exchange rate in , the study concluded that there was no cointegrating relationship between exports and imports in India. Next, Tiwari (2011a) studied the relationship between exports and imports for India and China using monthly data for the period by using Gregory-Hansen cointegration test which indicated that there was cointegration between the exports and imports for India but not for China. But, Saikkonen and Lütkepohl cointegration tests indicated presence of cointegration for both the countries. Next, Rahman (2011) studied the cointegration between exports and imports for Indonesia and Malaysia using yearly data for the period He used both two-step Engle granger and Johansen procedures. Both the processes indicated cointegrating relationship for Malaysia but not for Indonesia. Also, Wald s test was used to test whether the estimated equation s slope coefficient was equal to one or not and found that the cointegration between Malaysian export and import was not meaningful. Further CUSUM and CUSUMSQ indicated that the parameters were nearly constant for Malaysia. And lastly, Ramakrishna and Sadeghi (2013) studied the relationship between exports and imports in India and Iran using yearly data for the period using Engel-Granger cointegration. The estimated elasticity of exports with respect to import in the long run was 1.00 and 0.81 for India and Iran respectively. And the error correction model indicated that the any disequilibrium between long run and short run periods would be corrected by 37% and 43% each year for India and Iran, respectively. 3. Importance of the study This information on the cointegration between exports and imports is crucial in analyzing the effectiveness of current policies and designing of future macroeconomic policies (Mukhtar and Rahed, 2010). The importance of this study stems from the fact that the region of Gulf Cooperation Council (GCC) has been relatively neglected in empirical researches with very few studies concentrated on this region. In fact there 115

6 was only one full-fledged research on Qatar by Al Khulaifi and in another study four of GCC countries were included by Rammadhan and Naseeb (2008). Apart from this, among GCC countries, only Kuwait was included by Arize (2002). In fact, for the country of interest, that is, Saudi Arabia, only one study by Rammadhan and Naseeb (2008) was found relevant and the data included in the study was for the time period In the review of literature done for this paper, no other study pertaining to Saudi Arabia was found. Another strong reason for this current study is that there is a difference in results for the same country in different studies. For example, for Malaysia Arize (2002) found no long run cointegration relationship from while Ahmad et al. (2003) found cointegration from Similarly, Tang (2003a) found cointegration from and Koeng (et al, 2004) found cointegration from But later, Tang and Mohammad (2005) found no cointegration from Also, Tiwari (2013b) did not find cointegration from For Iran, Arize (2002) and Husein found cointegration whereas Tang (2006b) found no cointegration between exports and imports. Similarly, Tiwari (2011a), Upendra, Ramakrishna and Sadeghi (2013) of India found cointegration while Konya and Singh (2008) had mixed results. Further, these studies were applied for different years of data; hence the need arises to study the relationship between exports and imports till the latest data available for an oil exporting country like Saudi Arabia. Also, important is the fact that the sample country is predominantly an oil exporting country and the result of this study would apply to other oil exporting countries. 4. Data, Estimation technique and Empirical results Annual data has been used for the period to which has been taken from the annual report of Saudi Arabian Monetary Agency (SAMA). On the basis of the methodological process of the reviewed studies this study aims to find the relationship between export and import using cointegration. In all the studies reviewed, cointegration has been used to study the relationship between exports and exports. Engle and Granger (1987) advocated using cointegration to test the interrelationship between economic variables. At first, based on the observation of Sultan and Haque (2011) the natural log of the data on exports and imports will be used as it leads to the interpretation of the coefficients directly as the elasticity of the dependent variable with respect to independent variable which remains constant for the entire data set and, also, this transformation takes care of the problems of heteroscadisticity and multicollinearity. Second, the time series properties of the data will be tested. If the data is stationary, Ordinary Least Squares (OLS) method can only be used to study the relationship, lest it gives spurious results. If the variables under study are not stationary at level but integrated as the same order, there will be a long run relationship when there is cointegration between the variables. Variables are said to be cointegrated if the linear combination of the variables under study is stationary. Once the presence of cointegration is observed then the Vector Error Correction Model (VECM) is estimated to observe the short run dynamics of the relationship. But before conducting the test for cointegration the appropriate lag length needs to be determined for which all the criteria of the likes of Akaike Information Criteria (AIC) will be used. For studying the order of integration, augmented Dicky-Fuller (ADF) test and Philips- 116

7 Haque, M.I. Are Exports And Imports of Saudi Arabia Cointegrated? An Empirical Study Perron (PP) tests will be applied. Further, to test for the presence of cointegration, Johansen approach (1988) of cointegration will be used. If there is evidence of cointegration, the VECM will be estimated where the error correction term (ECT) is generated, the coefficient of which is the adjustment effect and the impact multipliers which are the coefficients of difference lagged regressors. For empirical testing Eviews6 is used. The results show that both the variables are nonstationary at level and integrated at level. This justifies the usage of Johansen s cointegration. But first, lag length of 2 is decided using LR, FPE, AIC, SC and HQ through VAR. Results show presence of at least one cointegration equation. This is evident through both Trace statistics and Maximum Eigen statistics. Max Eigen values and Trace statistics show the presence of at the least one cointegrating relationship. Once the presence of cointegration is ascertained the VECM is calculated to establish causality. The ECT should be negative and significant. But the ECT is negative only when Quadratic Deterministic Trend option is chosen among all the five options. Further when the VECM for lag 2 is tested, the coefficient of the ECT is but the probability value is 2.22, that is more than 5% percent, which implies that it is not significant. This implies that there is no long run causality running from export to import. And when lag of 3 is taken; the ECT becomes negative and significant indicating the presence of long run causality from exports to import. Also, there is still no evidence of long run causality from imports to exports. Next, for short run causality Wald s test is used. Here, the restrictions is that the coefficients of the lagged values of explanatory variables are zero, that is, c(4)=c(5)=0, which means there is no short run causality from import to export. Here as both the probability value of the F statistics and Chi square statistic is more than 5% hence the null hypothesis that c4 and c5 is jointly equal to 0 is accepted, implying that there is no short run causality. Further, there is no problem of heteroscadisticity as the probability of observed R square is more than 5% and also the model is normally distributed as the probability of Jarque- Bera is more than 5%. But, while analyzing the residuals an issue is encountered with, that is, the probability value of the observed R square of Breusch-Godfrey Serial Correlation LM Test, which is used for testing serial correlation, is more than 5%, indicating at the presence of the problem of serial correlation. This may be because of taking lag of 3 in our model. As the result given by EViews6 was not having significant exactness, the test of cointegration was re-run using statistical software named Stata12. (See annexure) The estimated values of Trace Statistics and Max Statistics are compared with critical values to accept/reject the null hypothesis. Here the null hypothesis is that all the rank specified in the regression results are the null hypothesis. The null hypothesis is accepted when, Trace or Max statistics is more than the critical value, and the null hypothesis is rejected when the Trace or Max statistics is less than its critical value. In the result output there is one cointegration ( in the case of Rank 1), meaning that the variables are cointegrated among each other or they have long run association ship with each other. So it can be concluded that there is a long run relationship between the two variables. And, if there is cointegration, the ECM estimates will be significant. Hence the variables are coinetgrated, the VECM of the model is estimated. 117

8 Two separate models are estimated to check the running causality from one into another. In the first model, export is the dependent variable and in the second model import is the dependent variable. Also, for each of the above case there can be two types of causality, short run and long run long run. For the long run causality, in the estimated VECM output, the coefficient of ECM must be significant with negative sign. For the short run causality it is seen whether the lag of independent terms (includes order of lag 1 and 2) jointly influence the dependent variable or not. And, for the short run causality, the null hypothesis is that the coefficients in specific equation are zero and the alternate hypothesis is that they are not. Further to check for serial correlation in the variables the Langrange Multiplier (LM) test is estimated, with the null hypothesis that there is no autocorrelation at lag order and the alternate hypothesis of presence of autocorrelation Table 1a: Stationary tests-export (EViews) Test Lag length criteria t-statistic Prob Constant ADF SIC Constant, Linear Trend ADF SIC None ADF SIC Constant ADF SIC Constant, Linear Trend ADF SIC None ADF SIC Constant Phillips-Perron N-W Constant, Linear Trend Phillips-Perron N-W None Phillips-Perron N-W Constant Phillips-Perron N-W Constant, Linear Trend Phillips-Perron N-W None Phillips-Perron N-W Table 1b: Stationary tests-import (EViews) Test Lag length criteria t-statistic Prob Constant ADF SIC Constant, Linear Trend ADF SIC None ADF SIC Constant ADF SIC Constant, Linear Trend ADF SIC None ADF SIC Constant Phillips-Perron N-W Constant, Linear Trend Phillips-Perron N-W None Phillips-Perron N-W Constant Phillips-Perron N-W Constant, Linear Trend Phillips-Perron N-W None Phillips-Perron N-W

9 Haque, M.I. Are Exports And Imports of Saudi Arabia Cointegrated? An Empirical Study Table 2: Lag structure (EViews) Lag LogL LR FPE AIC SC HQ NA * * * * * * indicates lag order selected by the criterion. LR: sequential modified LR test statistic (each test at 5% level); FPE: Final prediction error; AIC: Akaike information criterion; SC: Schwarz information criterion; HQ: Hannan-Quinn information criterion Table 3a: Cointegration-Max-Eigen statistics (EViews) Max- Eigen Statistics 0.05 Critical value Trend assumption Hypothesized no. of CE(s) Prob No deterministic trend None No deterministic trend At most No deterministic trend (restricted constant) None* No deterministic trend (restricted constant) At most Linear deterministic trend None* Linear deterministic trend At most 1* Linear deterministic trend (restricted) None Linear deterministic trend (restricted) At most 1* Quadratic deterministic trend None Quadratic deterministic trend At most 1* Table 3b: Cointegration-Trace statistics (EViews) Trend assumption Hypothesized no. of CE(s) Trace Statistics 0.05 Critical Value Prob. No deterministic trend None* No deterministic trend At most No deterministic trend (restricted constant) None* No deterministic trend (restricted constant) At most Linear deterministic trend None* Linear deterministic trend At most 1* Linear deterministic trend (restricted) None* Linear deterministic trend (restricted) At most 1* Quadratic deterministic trend None* Quadratic deterministic trend At most 1*

10 Table 4: Error correction term (EViews) D(X) D(M) No deterministic trend No deterministic trend (restricted constant) Linear deterministic trend Linear deterministic trend (restricted) Quadratic deterministic trend Table 5a: Estimating coefficients-1 (EViews) Variable Coefficient Std. Error t-statistic Prob. C(1) C(2) C(3) C(4) C(5) C(6) C(7) D(LNX) = C(1)*( LNX(-1) *LNM(-1) *@TREND(1) ) + C(2)*D(LNX(-1)) + C(3)*D(LNX(-2)) + C(4)*D(LNM(-1)) + C(5)*D(LNM(-2)) + C(6) + C(7)*@TREND(1) Table 5b: Estimating coefficients-2 (EViews) Variable Coefficient Std. Error t-statistic Prob. C(1) C(2) C(3) C(4) C(5) C(6) C(7) D(LNX) = C(1)*( LNX(-1) *LNM(-1) *@TREND(1) ) + C(2)*D(LNX(-1)) + C(3)*D(LNX(-2)) + C(4)*D(LNX(-3)) + C(5)*D(LNX(-4)) + C(6)*D(LNM(-1)) + C(7) *D(LNM(-2)) + C(8)*D(LNM(-3)) + C(9)*D(LNM(-4)) + C(10) + C(11) *@TREND(1) Table 6: Wald s Test (EViews) Test Statistic Value df Probability F-statistic (4, 30) Chi-square

11 Haque, M.I. Are Exports And Imports of Saudi Arabia Cointegrated? An Empirical Study Table 7a: Breusch-Godfrey Serial Correlation LM Test (EViews) F-statistic Prob. F(4,26) Obs*R-squared Prob. Chi-Square(4) Table 7b: Heteroskedasticity Test: Breusch-Pagan-Godfrey(EViews) F-statistic Prob. F(10,30) Obs*R-squared Prob. Chi-Square(10) Scaled explained SS Prob. Chi-Square(10) Table 7c: Test for normality (EViews) Jarque-Bera Probability First, in the first model when export is the dependent variable the coefficient of ECT has a positive sign ( ) which implies that there is no evidence of long run causality running from import to export. Next, for short run causality, using Granger Causality, it is tested whether the lag of independent terms jointly influence the dependent variables or not. As the probability values are greater than 0.05, it implies that there is no short run causality running from import to export. So, it can be said that there is neither short run nor long run causality running from import to export. And then, in the LM test the probability value is greater than 0.05, which means that the null hypothesis cannot be rejected, implying that there is no evidence of auto correlation as such. Next, in the second model when import is the dependent variable the value of ECT is and the probability value is As the coefficient of ECT has a negative sign and is also significant, hence it implies that there is long run causality running from export to import. For short run causality, in Granger Causality test the required chi square test statistics is 7.23 and the probability value is Here, it is tested whether the lag of independent terms jointly influence the dependent variables, for which the probability value is less than 0.05, implying that there is a short run causality running from export to import. And finally, in the LM test the probability value of chi square statistics is at lag 1 and at lag 2. As both the probability values are greater than 0.05, which means that the null hypothesis is rejected, implying that there is no auto correlation as such. Consequently, this study s important findings are that the cointegration coefficient, beta, is exactly identified and 47% of the disequilibrium between long run and short run is corrected each year. This is an improvement over the only other study 121

12 on Saudi Arabia by Rammadhan and Naseeb (2008) wherein they also found cointegration between exports and imports but there was neither any reference to the VECM, nor to the subsequent percentage of disequilibrium between long run and short run, being corrected each year. 5. Conclusion In the case of Saudi Arabia, exports and imports are cointegrated amongst each other, that is, they have long run association with each other. There are both, a short run as well as long run causality running from export to import, while causality running from import to export either in the short run or in the long run is missing. A plausible explanation could be that import does not cause exports as Saudi Arabia mainly exports oil and relate products. Now this sector is a capital intensive sector which mainly requires a onetime capital investment while setting the plant. It's not the case where it has to continuously import raw materials which are to be processed and exported. This also indicates that the huge consumption sector pertaining to food, beverages, textiles which is for internal consumption of the country and not specifically used for exports. And it can also be said that the heavy tools and machinery that is imported is used in manufacturing sector which being in nascent stage is just not sufficient to produce surplus so as to export. Obviously, when a country exports, then it gets the required foreign exchange to import, though this relation may not be specifically reflected here as money as such is not included in the model. But it reflects on two important aspects. First, Saudi Arabia is working as per its comparative advantage. It is producing what it can produce best and rest of the things it imports. Obviously a country cannot produce everything it requires and that also goes against the notion of comparative and relative advantage. As an illustration Saudi Arabia is using its resources to produce oil and not textiles, hence it has to import textiles. Second, import behavior also does depend on export as say Saudi Arabia is concentrating on oil and related industries, it needs tools and machineries and other capital goods that are required in the setting up of oil related industries. Had Saudi Arabia not being producing oil, it would not had the need to import these oil related capital goods. Another important observation is that the E-Views6 software suggested a lag of 2, but at this lag ECT is not significant. This goes contrary to the theory that when there is cointegration, ECT should be negative and significant. And when the lag is changed to 3, the result is found to be significant. But software Stata12, gives a proper result, with a negative and significant ECT at lag 2 itself. Although much cannot be said from this difference in result on the same data set, but this study recommends Stata for smaller data sets. Finally, taking cue from Bahmani-Oskooee (1994), Irandoust and Ericsson (2004) and Richard and Tiwari (2013) it can be concluded that as there is cointegration between exports and imports in Saudi Arabia, exports and imports have a tendency to converge towards equilibrium in the long run; the country is not in violation of its intertemporal budget constraint; country s macroeconomic policies are effective in restoring long run equilibrium; there are no permanent technology or productivity or policy shocks and lastly, the economy is being managed well. 122

13 Haque, M.I. Are Exports And Imports of Saudi Arabia Cointegrated? An Empirical Study References Arize, A. C. (2002). Imports and Exports in 50 Countries Test of Cointegration and Structural Breaks. International Review of Economics and Finance, 11, Abdulla S. Al-Khulaifi (2013). Exports and Imports in Qatar: Evidence from Cointegration and Error Correction Model. Asian Economic and Financial Review, 3(9), Ahmad, Z. B., Lau, E., & Fountas, S. (2003). On the Sustainability of Current Account Deficits: Evidence from Four ASEAN countries. Journal of Asian Economics, 14, Bahmani-Oskooee, M. (1994). Are Imports and Exports of Australia Cointegrated, Journal of Economic Integration, 9(4), Dumitriu, R., Nistor, C., & Stefanescu, R. (2008). Cointegration and Causality between Romanian Exports and Imports. Annals of the University of Petrosani, Economics, 8(1), Engle, R.F. & Granger, C.W.J. (1987). Cointegration and Error Correction: Representation, Estimation and Testing. Econometrica, 55, Husein, J. (2014). Are Exports And Imports Cointegrated? Evidence from Nine MENA Countries, Applied Econometrics and International Development, 14(1), Husted, S. (1992). The Emerging U.S. Current Account Deficit in the 1980s: A Cointegration Analysis. Review of Economics and Statistics, 74, Irandoust, M. & Ericsson.J. (2004). Are Imports and Exports Cointegrated? An International Comparison. Metroeconomica, 55, Keong, C. C., Choo, S. S. & Yusop, Z. (2004). Are Malaysian Exports and Imports Cointegrated? Sunway College Journal, 1, Konya, L. & Singh J.P. (2008). Are Indian Exports and Imports Cointegrated? Applied Econometrics and International Development, 8(2), Mohammad, H. A., & Tang, T. C. (2000). Aggregate Imports and Expenditure Components in Malaysia: A Cointegration and Error Correction Analysis. ASEAN Economic Bulletin, 17(3), Mukhtar, T. & Rasheed, S. (2010). Testing Long Run Relationship between Exports and Imports from Pakistan. Journal of Economic Cooperation and Development, 31(1), Narayan, P. K. & Narayan, S. (2005). Are Exports and Imports Cointegrated? Evidence from 22 Least Developed Countries, Applied Economics Letters, 12, Rahman, M.Z. (2011). Existence of Export-Imports Cointegration: A Study on Indonesia and Malaysia. International Business Research, 4(3) Ramakrishna, G. & Sadeghi, A. (2013). The Long Run Relationship between Exports and Imports: The Experience of India and Iran. International Journal of Contemporary Issues. 1 (2), Rammadhan, M & Naseeb, A. (2008). The Long Run Relationship between Oil Exports and Aggregate Imports in the GCC: Cointegration Analysis, Journal of Economic Cooperation, 29 (2), Richard, O.O. & Tiwari, A.K. (2014). The Sustainability of Trade Accounts of the ASEAN-5 Countries. Journal of Chinese Economic and Foreign Trade Studies, 7(1),

14 Sultan, Z & Haque, M.I. (2011). Estimating a Cointegrating Relationship between India's Growth, Investments and Trade, International Journal of Economics and Finance, 3(4), Tang, T. C. (2003a). Are Imports and Exports of the Five ASEAN Economies Cointegrated? An Empirical Study. International Journal of Management, 20(1), Tang, T. C. (2006b). Are Imports and Exports in the OIC Member Countries Cointegrated? A Reexamination, IIUM Journal of Economics and Management, 14, Tiwari, A.K. (2011a). Are Exports and Imports Cointegrated in India and China? An Empirical Analysis, Economics Bulletin, 31(1), Tiwari, A.K. (2013b). Are Trade Deficits Sustainable? Evidence from the ASEANfive. International Journal of Social Economics, 40(1), Upender, M. (2007). Long Run Equilibrium between India s Exports and Imports during 1949/ /05, Applied Econometrics and International Development, 7(1), Annexure on line at the journal Website: 124

15 Haque, M.I. Are Exports And Imports of Saudi Arabia Cointegrated? An Empirical Study Annexure Table 8. Cointegration (Stata) COINTEGRATION (STATA): JOHANSHEN TEST FOR COINTEGRATION TABLE: TRACE AND MAX STATISTICS Trace Statistics Maximum rank Parms LL Eigenvalue Trace statistic 5% critical value * Max-Statistics Maximum rank Parms LL Eigenvalue Trace statistic 5% critical value * Maximum rank Parms LL Eigenvalue Trace statistic 5% critical value Note: Trace/Max statistics > critical value, implies that we reject the Null Hypothesis and when Trace/Max statistics < critical value, implies that we cannot reject the Null Hypothesis. Regression result confirmed that there is one cointegration ( in the case of Rank 1) meaning that our variables are cointegrated among each other or they have long run association ship with each other. TABLE: VECTOR ERROR-CORRECTION MODEL: EXPORT AS A DEPENDENT VARIABLE 125 No. of observations 43 AIC Log likelihood HQIC Det(Sigma_ml) 1.28E+18 SBIC Parms RMSE R-sq. chi2 P>chi2 D_export D_import D_export Coef. Std. Err. z P> z [95% Conf. Interval] _ce1 L export

16 LD L2D import LD L2D Constant D_import Coef. Std. Err. z P> z [95% Conf. Interval] _ce1 L export LD L2D import LD L2D Constant Note: Where Ce1 represents coefficient of ECM, (which is also known as cointegration equation) and LD and L2D represents the lag order of 1 and 2 with respect to the variables. No evidence of LR causality as such. TABLE: COINTEGRATING EQUATION Cointegrating Equation Parms chi2 P>chi2 _ce Identification: beta is exactly identified; Johansen normalization restriction imposed beta Coef. Std. Err. z P> z [95% Conf.. Interval] export import constant TEST OF HYPOTHESIS: DETECTION OF SHORT RUN CAUSALITY: GRANJER CAUSALITY TEST Test ([D_export]: LD.import L2D.import) (1) [D_export] LD.import = 0 (2) [D_export] L2D.import = 0 (3) Chi2 (2) = 3.79 (4) Prob > chi2 = Test of Hypothesis Ho: Coefficients in specific equation are zero H1: They are not 126

17 Haque, M.I. Are Exports And Imports of Saudi Arabia Cointegrated? An Empirical Study Note: As the coefficient of ECT is significant as well as have negative sign it shows that there is a LR causality running from export to import, and Prob. values is greater than 0.05, means that they are equal to zero, meaning that there is no Short run causality running from import to export. There is no SR as well as LR causality running from Import to Export. TABLE: VECTOR ERROR-CORRECTION MODEL: IMPORT AS A DEPENDENT VARIABLE No. of observation 43 AIC Log likelihood HQI Det(Sigma_ml) 1.28E+18 SBI Equation Parms RMSE R-sq. chi2 P>chi2 D_import D_export D_import Coef. Std. Err. z P> z [95% Con Interval] _ce1 L import LD L2D export LD L2D _cons D_export Coef. Std. Err. z P> z [95% Con Interval] _ce1 L import LD L2D export LD L2D Constant Where Ce1 represents coefficient of ECM, (which is also known as cointegration equation) and LD and L2D represents the lag order of 1 and 2 with respect to the variables. 127

18 TABLE: SERIAL CORRELATION: LANGRANGE MULTIPLIER TEST We can also check for Serial Correlation between the variables using Langrange Multiplier Test Ho: No Auto-correlation at lag order H1: Presence of Auto Correlation Lagrange multiplier test for Serial Correlation lag chi2 Df. Prob. > chi Note: Probability values is greater than 0.05, means that we cannot reject the null hypothesis, there is no auto correlation as such. TABLE: COINTEGRATING EQUATIONS Cointegrating Equation Parms chi2 P>chi2 _ce Identification: beta is exactly identified; Johansen normalization restriction imposed beta Coef. Std. Err. z P> z [95% Conf. Interval] _ce1 import export _cons TEST OF HYPOTHESIS: DETECTION OF SHORT RUN CAUSALITY: GRANJER CAUSALITY TEST lag chi2 Df. Prob. > chi test ([D_import]: LD. export L2D.export) (1) [D_import] LD. export = 0 (2) [D_import] L2D.export = 0 (3) Chi2 (2) = 7.23 (4) Prob > chi2 = Test of hypothesis Ho: Coefficients in specific equation are zero H1: They are not Note: Prob values is less than 0.05, means that they are not equal to zero, there is a Short run causality running from export to import. As the coefficient of ECT is significant as well as have negative sign shows that there is a long run causality running from export to import. 128

19 Haque, M.I. Are Exports And Imports of Saudi Arabia Cointegrated? An Empirical Study Table 9: Data (48 th Annual Report of SAMA, published on ) TABLE : FOREIGN TRADE 129 (Million Riyals) Year Exports (1) Percentage Imports Change (2) Percentage Change , , , , , , , , , , , , ,26, , ,04, , ,35, , ,53, , ,38, , ,13, , ,62, ,00, ,05, ,19, ,71, ,39, ,58, ,35, ,32, ,18, , , , , , , , , ,06, , ,66, , ,78, ,08, ,88, ,24, ,58, ,05, ,59, , ,87, ,05, ,27, ,03, ,27, ,07,

20 1998 1,45, ,12, ,90, ,04, ,90, ,13, ,54, ,16, ,71, ,21, ,49, ,56, ,72, ,77, ,77, ,22, ,91, ,61, ,74, ,38, ,75, ,31, ,21, ,58, ,41, ,00, ,67, ,93, (3) 14,56, ,83, (4) 14,09, ,30, (1) Includes Re-exports. (2) CIF. (3) Revised. (4) Provisional. Source: Central Department of Statistics & Information, Ministry of Economy and Planning. Journal published by the EAAEDS: 130