A Cointegration Analysis on Trade Behaviour in Selected ASEAN Countries Using Dynamic Ols and Johansen Maximum Likelihood Approaches NOR’AZNIN ABU BAKAR Faculty of Economics Universiti Utara Malaysia ABSTRACT This paper aims to analyse the trade behaviour of four selected ASEAN countries (based on their export/import products) by using a co-integration analysis. The demand for exports and imports are estimated for the period before the currency crisis erupted (1963-1995), using the dynamic OLS (DOLS) method. The Johansen Maximum Likelihood (JML) approach is also employed to compare the results obtained. Results show that foreign income has a significant impact on export demand, suggesting that foreign disturbance in the form of economic activities is likely to be transmitted to these countries. The Marshall Lerner conditions are easily met for the case of Malaysia and Thailand (DOLS and JML). For Indonesia and the Philippines, the sum of the price elasticities of exports and imports demands are less than unity, this can be explained by the J-curve, in which the currency depreciation will first worsen the trade balance before it improves and it takes time to affect the trade balance. ABSTRAK Kertas kerja ini bertujuan untuk menganalisa gelagat perdagangan bagi empat negara ASEAN terpilih (berdasarkan kepada barangan eksport/import). Permintaan eksport dan import dianggarkan untuk jangka masa 1963-1995 iaitu sebelum berlakunya krisis mata wang. Kaedah Johansen Maximum Likelihood juga digunakan untuk membandingkan keputusan yang diperolehi. Hasil kajian menunjukkan bahawa pendapatan asing mempunyai pengaruh yang signifikan ke atas permintaan eksport, mencadangkan kejutan luar dalam bentuk aktiviti ekonomi dipindahkan ke negara-negara tersebut. Keadaan Marshall-Lerner dapat dipenuhi dengan mudah untuk kes negara Malaysia dan Thailand (kaedah DOLS dan JML). Untuk kes Indonesia dan Filipina, jumlah keanjalan harga eksport dan import adalah lebih kecil dari satu. Ini dapat dijelaskan dengan keluk J, di mana penurunan nilai mata wang akan memburukkan lagi imbangan perdagangan sebelum ianya pulih dan ini akan mengambil masa untuk mempengaruhi imbangan perdagangan. INTRODUCTION The literature has quite extensively dealt with the estimations of the price and income elasticities of exports and imports demand. The models mostly use a simple OLS method to estimate the price and income elastic ties of exports and imports demand. The problem with this time series analy- sis is that we cannot draw general conclusions from the results of a particular time series analy- sis as the estimated parameters in the static OLS are subject to bias in small samples since the lagged terms are ignored (see Banerjee, A., Galbraith, J. W., & Hendry, D. (1993)). One way Malaysian Management Journal 8 (1), 11-24 (2004)
Transcript
A Cointegration Analysis on Trade Behaviour in Selected ASEANCountries Using Dynamic Ols and Johansen Maximum Likelihood
Approaches
NOR’AZNIN ABU BAKARFaculty of Economics
Universiti Utara Malaysia
ABSTRACT
This paper aims to analyse the trade behaviour of four selected ASEAN countries (based on theirexport/import products) by using a co-integration analysis. The demand for exports and imports areestimated for the period before the currency crisis erupted (1963-1995), using the dynamic OLS (DOLS)method. The Johansen Maximum Likelihood (JML) approach is also employed to compare the resultsobtained. Results show that foreign income has a significant impact on export demand, suggesting thatforeign disturbance in the form of economic activities is likely to be transmitted to these countries. TheMarshall Lerner conditions are easily met for the case of Malaysia and Thailand (DOLS and JML).For Indonesia and the Philippines, the sum of the price elasticities of exports and imports demands areless than unity, this can be explained by the J-curve, in which the currency depreciation will firstworsen the trade balance before it improves and it takes time to affect the trade balance.
ABSTRAK
Kertas kerja ini bertujuan untuk menganalisa gelagat perdagangan bagi empat negara ASEAN terpilih(berdasarkan kepada barangan eksport/import). Permintaan eksport dan import dianggarkan untukjangka masa 1963-1995 iaitu sebelum berlakunya krisis mata wang. Kaedah Johansen MaximumLikelihood juga digunakan untuk membandingkan keputusan yang diperolehi. Hasil kajian menunjukkanbahawa pendapatan asing mempunyai pengaruh yang signifikan ke atas permintaan eksport,mencadangkan kejutan luar dalam bentuk aktiviti ekonomi dipindahkan ke negara-negara tersebut.Keadaan Marshall-Lerner dapat dipenuhi dengan mudah untuk kes negara Malaysia dan Thailand(kaedah DOLS dan JML). Untuk kes Indonesia dan Filipina, jumlah keanjalan harga eksport danimport adalah lebih kecil dari satu. Ini dapat dijelaskan dengan keluk J, di mana penurunan nilai matawang akan memburukkan lagi imbangan perdagangan sebelum ianya pulih dan ini akan mengambilmasa untuk mempengaruhi imbangan perdagangan.
INTRODUCTION
The literature has quite extensively dealt with theestimations of the price and income elasticities ofexports and imports demand. The models mostlyuse a simple OLS method to estimate the priceand income elastic ties of exports and imports
demand. The problem with this time series analy-sis is that we cannot draw general conclusionsfrom the results of a particular time series analy-sis as the estimated parameters in the static OLSare subject to bias in small samples since thelagged terms are ignored (see Banerjee, A.,Galbraith, J. W., & Hendry, D. (1993)). One way
Malaysian Management Journal 8 (1), 11-24 (2004)
http
://m
mj.u
um.e
du.m
y
12
to tackle this problem is by using the dynamicOLS method in which lagged and leading valuesof the first differences of the I (1) variables areincluded.
The Johansen Maximum Likelihood ap-proach can also be used as it provides direct esti-mates of the cointegrating vectors and allows test-ing the number of cointegrating vectors. However,in practice, the Johansen approach also has a fewdisadvantages. First, if the sample size is small,the estimates obtained for cointegrating vector bmay not be well determined. Second, if thecointegrating vector is not a unique one, there willbe an identification problem and it may be diffi-cult to disentangle economically meaningfulcointegrating vectors. As a consequence, a strat-egy is to use both these approaches and comparethe results.
The responsiveness of trade flows to rela-tive price changes is the main concern in formu-lating an exchange rate policy to correct the tradeimbalance. If the sum of export and import de-mand is greater than unity, it indicates that a de-preciation or devaluation will have a favourableeffects on the trade balance as it satisfies theMarshall-Lerner condition. However, exchangerate policy is always accompanied by other mac-roeconomic policies that is, fiscal or monetarypolicies, as it is difficult to measure the effects ofone policy without controlling for the others (seeTang, 2003). Therefore, the need to combine theeffects of all the policies on trade balance are nec-essary. In some situations, trade balance worsensbefore it improves in response to depreciation; thisis known as the J curve effect which due to thelow price elasticity of demand for exports andimports in the immediate aftermath of an exchangerate change.
The purpose of this paper is to estimatethe price and income elasticities of the four se-lected ASEAN countries’ demand for exports andimports. Countries that are selected are based oncharacteristics of their export/import products.This study can be justified as follows:
i) It differs from most earlier studies thatis, Bond (1985); Cline (1984); Goldstein
& Khan (1982); Marquez of McNeilly(1988); Mustacelli (1994); Muscatelli, V.A.; Stevensen, A. A., & Montagna, C.(1995a). These studies used static longrun regressions in which the estimatedparameters in the static long run OLS aresubject to bias in small samples sincelagged terms are ignored. This study usesa dynamic OLS to avoid this problem.Estimates taken from the conditional er-ror-correction model are equivalent tofull-information maximum likelihoodestimates and therefore asymptoticallynormal, allowing standard inference. Onthe contrary, for the static regressioncase, the t ratios have non-standard dis-tributions even asymptotically (seeBaffes, J., Elbadawi, I. A., & O’ Connell,S. A. , 1999).
ii) By adopting the cointegration method,the problem of spurious regression isavoided as variables involved in bothexport and import demands are non-sta-tionary in their levels. The maximumlikelihood approach is also employed toconfirm results obtained from the dy-namic OLS method. However, theJohansen procedure has serious limita-tions where it deteriorates dramaticallyin small samples, generating estimateswith ‘fat tails’ (frequent outliers). There-fore results from the dynamic OLSmethod will be the main focus.
iii) The findings of this study provide em-pirical evidence that suggests that theexchange rate policy (i.e. Malaysia andThailand) is effective to correct the tradebalance deficit as the Marshall-Lernercondition is met.
LITERATURE REVIEW
The issue of price and income elasticities has beenreceived much attention recently. Several meth-ods have been used to estimate price and incomeelasticities of export and import demand. Studies
Malaysian Management Journal 8 (1), 11-24 (2004)
http
://m
mj.u
um.e
du.m
y
13
done by Bond (1985), Cline (1984), Goldstein &Khan (1982), Muscatelli (1994, 1995a), Marquezand McNeilly (1988), and O’Neill and Ross(1991) have supported the conventional view,which states that the price elasticities of demandfor newly industrialised countries’ (NICs) exportsare small. However, the world income elasticityof demand for the NIC’s exports is significant and,high. Conversely, others such as Riedel (1984;1988; 1989), Athukorala and Riedel (1996), havecriticised the conventional view, and have foundthat income elasticities are insignificant and theprice elasticities of export demand are infinite.
Argument regarding the size ofelasticities of export is the issue of normalisation.As argued by Riedel, (1989) by using the con-ventional approach for which export volumes aremodelled as a demand equation, that depends onthe domestic price relative to world price, and onworld income, the price elasticities of demand tendto be low and the income elasticities of demandtend to be very high. Therefore, it is argued thatthe export demand function should be normalisedfor price rather than for quantity. Mustacelli(1994) used the Phillips-Hansen method to testRiedel’s data, and found that the price elasticityof demand is actually low and income elasticitiesare high. Also, according to them, by using a moredynamic specification model of demand and sup-ply, apparently the normalisation paradox disap-pears.
For the Malaysian case, a study done byTang (2003) found that exports and imports ofMalaysia are cointegrated. Thus macroeconomicpolicies are effective to bring export and importinto long run equilibrium. A study done byMohamad and Tang (2000), examines the long runrelationship between aggregate imports and ex-penditure components of five ASEAN countriesusing the Johansen multivariate cointegrationanalysis. By using disaggregating demand vari-able in its components avoids the possibility ofaggregate bias. Their findings showed that in thecase of Malaysia, the import demand iscointegrated with its determinants and import de-mand is elastic with respect to relative prices. TheMarshall Lerner condition is met, suggesting that
devaluation is effective in correcting balance ofpayments disequilibrium.
As stated above, the issue of the aggre-gation level needs to be taken into account. Ag-gregation across different commodity groups, ordifferent countries, must be well determined. Dif-ferent groups of commodity can be aggregatedonly if the pattern of their export is comparable.Therefore in this study, ASEAN countries that arechosen are those with similar trade characteris-tics and trade directions.
METHOD OF ESTIMATION
Theoretical Specification of the Export and Im-port FunctionsThe world demand for exports and imports fromASEAN are specified in log linear forms as fol-lows:
log Qxt d = a
0 + a
1 log (Px/Pw)
t + a
2 log Yw
t +
a3 log Gci
t + ux
t (1)
a1 < 0, a
2 > 0, a
3 > 0
log Qmt
d = b0 + b
1 log (Pm/GP)
t + b
2 log Yb
t +
vmt
(2) b
1 < 0, b
2 > 0
Where ux, v
m, are the error terms, a
0 and b
0 are the
constant terms and:
Qx
= Export of goodsPx = Price of exportsPw = Price of world exportsYw = Scale variableGci = Export composition indexQ
m= Import of goods
Pm = Price of home country importsGP = Domestic price levelYb. = Real income of home country
The model which is referred to as the‘equilibrium’ model assumes the simplifying as-sumption that there are no lags in the system sothat the adjustment of export and import quanti-ties and prices to their respective equilibrium val-
Malaysian Management Journal 8 (1), 11-24 (2004)
http
://m
mj.u
um.e
du.m
y
14
ues is instantaneous. The commonly used log lin-ear functional form is employed instead of the lin-ear one as it implies that the elasticities are con-stant.
The demand for exports (equation 1) isdependant upon the relative price of exports withrespect to the world price (Px/Pw), the scale vari-able (Yw) which captures world demand condi-tions and the export composition index (Gci). Theprice is assumed to be homogenous in the longrun so that demand depends only on relative pricesand the scale variable. The choice of the scalevariable may vary; some authors use (tradeweighted) world income as a scale variable [Khan(1974); Goldstein & Khan (1978); Aspe &Giavazzi (1982); Marquez & McNeilly (1988)]while others, for example, Muscatelli et al. (1995),use trade weighted imports of the country’s ex-port destination as a scale variable. In this study,world income is used as a scale variable. The co-efficients of a
1 and
a
2 are the price and income
elasticities of foreign demand for home countryexports and are expected to be negative and posi-tive respectively. The export composition indexis included in the export demand equation, as thecommodity type effects are implicitly captured bythe income and price effects if they are not in-cluded in the equation. The coefficient a
3 is ex-
pected to be positive.The demand for imports (equation 2) is
dependant upon the relative price of imports withrespect to the general price level (Pm/GP), andthe real income of the home country (Yb). Coef-ficients b
1 and b
2 are expected to be negative and
positive respectively.The study uses annual data for the pe-
riod of 1963-1995, specifically before the occur-rence of the financial crisis. The description andthe computations of variables (i.e. Qx, Qm, Pw,Yw, and Gci) are given in the Appendix.
INTEGRATION ANDCOINTEGRATION TESTS
The Dickey-Fuller (DF) and an AugmentedDickey-Fuller (ADF) tests are used in this study
to test for integration levels. These are both t testsand rely on rejecting the hypothesis that the se-ries is a random walk in favour of stationarity. Byusing the ADF and DF tests, the data is tested tosee whether all variables are non-stationary. TheDF/ADF test for the unit roots for both export andimport equations for the ASEAN countries areshown in Table 1 and 2.
The Engle-Granger is widely used to es-timate the long-run regression. However, the es-timated parameters in the static long run OLS aresubject to bias in small samples since lagged termsare ignored (see Banerjee, A., Galbraith, J. W., &Hendry, D. (1993)). One way to correct this prob-lem is by including dynamic components (i.e. dif-ferences and lagged) to the cointegration(Cuthbertson, K., Hall, S. G., & Taylor, M. P.(1992).
By applying the dynamic OLS (DOLS),the potential of simultaneity bias and small sam-ple bias among regressors is tackled that is, theinclusion of lagged and leading values of the firstdifferences of the I (1) variables (see Phillips &Loretan (1991), and Saikkonen (1991)). There istrade-off involved with lag length choice in thegeneral time series regression model; using toofew lags can decreases forecast accuracy becausevaluable information is lost, but adding lags in-creases estimation uncertainty. The choice of lagsmust balance the benefit of using additional in-formation against the cost of estimating the addi-tional coefficients.
One way to determine the number of lagsto include is to use the F-statistic to test joint hy-potheses that set of coefficients equal zero. Infor-mation criteria, that is, the BIC and AIC can beused to estimate the number of lags and variablesin the time series. The model with the lowest valueof the AIC (or BIC) is the preferred model. Theexport demand and import demand equations areestimated to include up to j=±3 leads and lags.Insignificant leads and lags will be dropped. Therobust standard errors facilitate valid inferencesto be made upon the coefficients of the variablesentering as regressors in levels. Based on the dy-namic OLS method, the long run export demandand import demand equations are as follows;
Notes to table: All variables are in log.Variables are as follows; total export index (Q
xd), relative price (Px/Pw), a weighted (by the share of exports)
average of the trade partners GDP (Yw) and export composition index (Gci). Variables are as follows; total importindex (Q
md), relative price (Pm/Gp) and the real income (Yb). ADF critical value for level is –3.5468 and ADF
critical value for 1st difference is –3.5514.
All econometric computations have been carried out by Microfit 4.0 Version (see Pesaran & Pesaran, (1997). Inmost of the cases, the intercept terms are included in the relevant DF and ADF equations. An augmentation of oneseems sufficient to secure lack of autocorrelation of the error terms, however, in some cases, no augmentation was
Notes to table: All variables are in logVariables are as follows; total import index (Q
md), relative price (Pm/Gp) and the real income (Yb). ADF critical
value for level is –3.5468 and ADF critical value for 1st difference is –3.5514.
All econometric computations have been carried out by Microfit 4.0 Version (see Pesaran & Pesaran, (1997). Inmost of the cases, the intercept terms are included in the relevant DF and ADF equations. An augmentation of oneseems to sufficient to secure lack of autocorrelation in the error terms, however, in some cases, no augmentationwas necessary.
RESULTS
The OLS Residual-Based TestTable 3 reports the ADF residual based test re-sults for cointegration for the export demand equa-tions. Table 2, in Charemza and Deadman (1992),provides approximate critical values for thecointegration test for 30 observations with m=3at 5 percent level of significance which are -3.71(lower bound) and –3.50 (upper bound). The nullhypothesis of no cointegration is rejected if thevalue were below –3.71; and is not rejected if thevalue were above –3.50. Values between –3.71 and
–3.50 lie in the inconclusive region. Based on thetest statistics, the null hypothesis of nocointegration for the corresponding residual ob-tained from the long run export demand equationcan be rejected at 5 percent level of significance(i.e. Malaysia and Indonesia). However, forThailand’s long run export demand equation, thecorresponding residual obtained from the equa-tion is in the ‘inconclusive region’ at 5 percentlevel of significance although the null of nocointegration can be rejected at 10 percent levelof significance. For the case of the Philippines thenull of no cointegration can also be rejected at 10percent level of significance.
Malaysian Management Journal 8 (1), 11-24 (2004)
http
://m
mj.u
um.e
du.m
y
17
For the import demand equation, the nullhypothesis of no cointegration at 5 percent levelof significance is rejected (i.e. Malaysia and In-donesia). For the Philippines, the null hypothesisof no cointegration at 10 percent level of signifi-cance is rejected. For Thailand, the correspond-ing residual obtained from the equation is slightlybelow the upper bound critical value. However, itis assumed that all variables are cointegrated asthe standard tests are over-cautious in rejectionof the null hypothesis of no cointegration. Thisemphasizes type 1 error whereas type 2 error, thatis, failing to reject the null when it is false, is moreimportant here. Consequently, we should be gen-erous in interpreting the statistics. Accordingly,
all variables involved in the equations arecointegrated, or, in short, the long run relation-ships among variables are not spurious. This isshown in Table 4.
The CRDW is used to see whether allthe variables are cointegrated. Engle and Yoo(1987), provide a CRDW critical value for n=50;the two variables case is 0.78 at 5 percent level ofsignificance and 0.69 at 10 percent level of sig-nificance. By looking at the CRDW test statis-tics, the value of CRDW for Malaysia’s exportdemand is 1.42, which is larger than the 5 percentcritical value and therefore the null of nocointegration is rejected.
Table 3:ADF Residual-based Test for Cointegration The Long-run Export Equations
Test Statistics Critical Values*DF ADF(1) 5% 10%
U L U LMalaysia -4.24 -4.33 -3.50 -3.71 -3.16 -3.33Indonesia -2.67 -3.90 -3.50 -3.71 -3.16 -3.33Thailand -3.58 -3.64 -3.50 -3.71 -3.16 -3.33Philippines -3.62 -3.27 -3.50 -3.71 -3.16 -3.33
Notes to table:*The critical values are obtained from Charemza and Deadman (1992) with 30 numbers of observation and m=3.One also can refer to other sources of critical value tables i.e. MacKinnon (1991), Engle-Granger (1987, Tables IIand III), Engle and Yoo (1987).
Table 4:ADF Residual-based Test for Cointegration The Long-run Import Equations
Test Statistics Critical Values*DF ADF(1) 5% 10%
U L U LMalaysia -2.99 -3.69 -3.15 -3.31 -2.80 -2.96Indonesia -2.13 -3.29 -3.15 -3.31 -2.80 -2.96Thailand -1.79 -2.34 -3.15 -3.31 -2.80 -2.96Philippines -1.89 -2.80 -3.15 -3.31 -2.80 -2.96
Notes to table;*The critical values are obtained from Charemza and Deadman (1992) with 30 numbers of observation and m=2.One also can refer to other sources of critical value tables i.e. MacKinnon (1991), Engle-Granger (1987, Tables IIand III), Engle and Yoo (1987).
Malaysian Management Journal 8 (1), 11-24 (2004)
http
://m
mj.u
um.e
du.m
y
18
The DOLSTable 5 shows the dynamic OLS parameter esti-mates of the long-run export demand with all vari-ables in levels, along with their approximate as-ymptotic standard errors for all countries. Basedon the results obtained, for most cases both thelong run income and price elasticities have cor-rect signs as anticipated. The long run incomeelasticities vary from 0.15 (Philippines) to 1.37(Thailand). In all cases, they are significant. Thelong-run price elasticities vary from –0.26 (Indo-nesia) to –2.41 (Thailand). As the export compo-
sition index is only significant for Malaysia, it isdropped for the other three countries.
The price elasticities in the import de-mand equations are correctly signed and are sig-nificant. The long run price elasticity of importdemand vary from –0.27 (Philippines) to –1.50(Thailand). The income variable was also correctlysigned and significant for all cases. The long runincome elasticities vary from 0.35 (Philippines)to 0.90 (Malaysia). Table 6 reports the results forimport demand equations that show the correctsigns for both income and price elasticities.
The Johansen Maximum Likelihood ApproachBy applying the Johansen Maximum Likelihoodapproach (see Johansen, (1991), cointegration arefound for all countries. Information from the un-restricted VAR model is used to determine theorder of the VAR. The Schwarz Bayesian Crite-rion (SBC), and the Akaike Information Criterion(AIC) were used to determine the optimal laglength. The log-likelihood ratio statistics were thenused for testing zero restrictions on the coefficientsof a subset of deterministic/exogenous variable;the presence of an intercept could not be rejected.
The results of the Johansen-Juseliuscointegration tests for both exports and importsare shown in Tables 7 and 8. The trace statisticsand the eigenvalue (maximum) tests show thatthere exists only one cointegrating relationship.The Johansen Likelihood ratio statistics were usedto determine the number of cointegrating vectors,r. Both the maximal eigenvalue and the trace testswere used, testing the null hypothesis of rcointegrating vectors for r = 0, followed by r ≤ 1and r ≤ 2.
Table 7:The Johansen Maximum Likelihood Cointegration Test - Exports
Malaysia: Cointegration with Unrestricted Intercepts and No Trends in the VAR (k=2)Eigenvalue λ
For the export demand equation, in mostcases the maximal eigenvalue test (l-max test) in-dicates that the null hypothesis of zerocointegrating vectors is rejected at 95 percent criti-cal value except for the case of the Philippines.(see Pesaran & Pesaran, 1997). The trace test con-firms that there is only one cointegrating relation-ship among the variables for all countries exceptfor the case of the Philippines. However, basedon the choice of the number of cointegrating rela-tions using model selection criteria, both theAkaike Information Criteria (AIC) and theHannan-Quinn Criteria (HQC) select onecointegrating relationship.
For the import demand equation, themaximal eigenvalue test and the trace test, indi-cate that the null hypothesis of zero cointegratingvectors is rejected at 90 percent critical value ex-cept for the case of the Philippines and Indonesia.Nevertheless, based on the choice of the numberof cointegrating relations using model selectioncriteria, the Schwarz Bayesian Criteria (SBC) se-lects one cointegrating relationship for both thePhilippines and Indonesia. The estimation of thenormalized cointegrating vector then is obtainedas the existence of the relationship among the vari-ables is accepted. This is shown in Table 9.
Malaysian Management Journal 8 (1), 11-24 (2004)
http
://m
mj.u
um.e
du.m
y
21
For most of the cases, the price and in-come elasticities of export demand are all correctlysigned. In the Malaysian case, the long run priceand income elasticities are –0.35 and 0.20 respec-tively. They are both statistically significant. Theexport composition index also has the predictedsign and is also significant with the value of 1.71.In the Indonesian case, the long run price and in-come elasticities are -0.3 and 0.67, respectivelyand both are statistically significant. For the caseof Thailand, the price and income elasticities havethe predicted sign and both are significant. Thelong run price elasticity is –2.69 and the long runincome elasticity is 1.43. For the Philippines, the
long run price elasticity is –0.25 and the long runincome elasticity is 0.17. They are both correctlysigned and significant. A restriction is imposedon the export composition index (GCI) that a4 =0, obviously for the Malaysian case, the c2 is sta-tistically significant, and therefore the null hypoth-esis of no relationship between the export demandand the export composition index is rejected. Forthe import demand equations, in all cases the priceand income elasticities are all correctly signed andare significant (see table 9). These results suggestthat both relative price and real income are cru-cial in determining import demand.
Table 9:Results from the DOLS and the Johansen VAR Approaches
This paper provides estimation of price and in-come elasticities of export and import demandusing both dynamic OLS and Johansen MaximumLikelihood approaches. The cointegration analy-sis is employed to ensure that regressions are notspurious. Results show that both the price and in-come elasticity of exports and imports demand,have correct signs as anticipated and significant.The inelasticity of export demand for most coun-tries is expected, as the bulk of these countriesexports are in the form of strategic raw materialsused for industrial purposes.
Different estimates of the priceelasticities of export demand function leads todifferent implications for trade policies. As arguedby Athukorala and Riedel (1990), if priceelasticities really were low, then standard tradetheory would suggest that policy-makers in de-veloping countries should have advocated exporttaxes in place for export promotion. However, lib-eralization of trade can lead to a massive boost toexport growth rates in developing countries; thatis, the Turkish experiences in the 1980s.
There are also implications for (real)exchange rate of cost competitiveness policy. Sup-pose that the price elasticities of demand are in-deed low, one would expect a policy of allowinga real depreciation to generate a rather small ex-pansion of the varieties produced in ASEAN coun-tries. But lower wage costs will attract producersof new varieties to the ASEAN countries, thusboosting supply and demand at the same time.Therefore a real depreciation policy should notbe seen as a way of cheapening supply, which will,of itself attract purchasers.
Based on the results obtained, one canobserve that foreign income is a significant vari-able in the export demand equation, suggestingthat foreign disturbance in the form of fluctuationin foreign economic activities is likely to be trans-mitted to those countries. The Marshall-Lernerconditions are met for Malaysia and Thailand asthe sum of their price elasticity of export and im-port demand are greater than unity (both DOLS
and Johansen Maximum Likelihood approaches),suggesting that appreciations (depreciations) inexchange rates can worsen (improve) the currentaccount in a period of one year. For the case ofthe Philippines and Indonesia, however, the sumof the price elasticities of exports and imports areless than unity. This can be explained by the J-curve, in which export and import demands tendto be relatively inelastic due to the existence oflags. The J-curve also shows that currency depre-ciation will first worsen the trade balance beforeit improves and it takes time to affect the currentaccount. As mentioned earlier, the exchange ratepolicy is always accompanied by other macroeco-nomic policies, as it is difficult to assess the ef-fects of one policy without controlling for the oth-ers.
REFERENCES
Aspe, P., & Giavazzi, F. (1982). The short runbehaviour of prices and output in theexportable sector: The case of Germanmachinery. Journal of International Eco-nomics, 12, 83-93.
Baffes, J., Elbadawi, I. A., & O’ Connell, S. A.(1999). Single-equation estimation of theequilibrium real exchange rate in Hinkle,Lawrence E., & Peter, J. Montiel: Ex-change rate misalignment: Concepts andmeasurement for developing countries.Oxford: Oxford University Press.
Banerjee, A., Galbraith, J. W., & Hendry, D.(1993). Cointegration and the economet-ric analysis of non-stationary data. Ox-ford: Oxford University Press.
Bond, M. (1985). Export demand and supply forgroups of non-oil developing countries.IMF Staff Papers, 32, 56-77.
Malaysian Management Journal 8 (1), 11-24 (2004)
http
://m
mj.u
um.e
du.m
y
23
Cline, W. R. (1984). International debt systemicrisk and policy response. Mass: Institutefor International Economics. MIT Press:Cambridge.
Charemza, W. W., & Deadman, D. F. (1992). Newdirections in econometric practice: Gen-eral to specific modelling, cointegrationand vector autoregression. Aldershot:Edward Elgar.
Cuthbertson, K., Hall, S. G., & Taylor, M. P.(1992). Applied econometric techniques.New York: Phillip Allan.
Engle, R. F., & Yoo, B. S. (1987). Forecasting andtesting in cointegrated systems. Journalof Econometrics, 35, 143-59.
Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Repre-sentation, estimation, and testing.Econometrica, 55, 251-276.
Goldstein, M., & Khan, M. S. (1978). The supplyand demand for exports: A simultaneousapproach. Review of Economics and Sta-tistics, 60, 275-86.
________(1982). Effects of slow down in indus-trial countries a growth in non-oil devel-oping countries. IMF Occasional Paper,12.
Houthhakker, H. S., & Stephen, M. (1969). In-come and price elasiticities in worldtrade. The Review of Economics and Sta-tistics, 51, 111-125.
Johansen, S. (1991). Estimation and hypothesistesting of cointegration vectors inGaussian vector autogressive model.Econometrica, 59, 1551-1580.
Khan, M. S. (1974). Import and exports demandin developing countries. IMF Staff Pa-per. 21, 169-210.
Marquez, J., & McNeilly, C. (1988). Income andprice elasticities for exports of develop-ing countries. Review of Economics andStatistics, 70, 306-314.
MacKinnon, J. G. (1991). Critical values for inte-gration tests in Long Run Economic Re-lationships: Reading in Co-Integration.R. F. Engle & C. W. J. Granger (Eds.)Oxford: Oxford University Press.
Muscatelli, V. A. (1994). Demand and Supply fac-tors in the determination of NIE Exports,a reply. Economic Journal, 104, 1415-1417.
Muscatelli, V. A., Stevensen, A. A., & Montagna,C. (1995a) An analysis of thedisaggregated manufacturing exports ofthe Asian NIEs to EEC, USA, and Ja-pan. Applied Economics, 27, 17-24.
Muscatelli, V. A. (1995b). Modelling aggregatemanufactured exports for some Asiannewly industrialized economies. Reviewof Economics and Statistics, 77, 147-155.
Mohamad Haji Alias, & Tang Tuck Cheong(2000). Aggregate imports and expendi-ture components in Malaysia: Acointegration and error correction analy-sis. Presented in Monash UniversityMalaysia International Symposium onMalaysia Business in the New Era, 23-24 Feb, 2000.
O’Neill, H. M., & Ross, W. (1991). Exchange ratesand South Korea exports to OECD coun-tries. Applied Economics, 23, 1227-1236.
Pesaran, B. H., & Pesaran, B. (1997). Microfit:An interactive econometric softwarepackage (user manual). Oxford: OxfordUniversity Press.
Philip, P. C. B., & Loretan, M. (1991). Estimat-ing long-run economic equilibria. Reviewof Economic Studies, 58, 407-436.
Malaysian Management Journal 8 (1), 11-24 (2004)
http
://m
mj.u
um.e
du.m
y
24
Riedel, J. (1984). Trade as the engine of growthin developing countries, revisited. Eco-nomic Journal, 94, 56-73.
_________ (1988). The demand for LDC exportsof manufactures: Estimates from HongKong. The Economic Journal, 98, 138-148.
_________(1989). The demand for LDC exportsof manufactures: Estimates from HongKong: A rejoinder. The Economic Jour-nal, 99, 467-470.
Saikkonen, P. (1991). Asymptotically efficientestimation of co-integration regressions.Econometric Theory, 7, 1-21.
Tang Tuck Cheong (2003). Are imports and ex-ports of the five ASEAN economies co-integrated? An empirical Study. Interna-tional Journal of Management, 20 (1),88-91
APPENDIX
The Computation of the Variables of Export andImport Demand.All data required for the estimation were gath-ered and verified from various issues of the Inter-national Financial Statistics, and the World Ta-bles of the World Bank. The trade share statisticsused to compute the foreign variable were takenfrom the United Nations Yearbook of InternationalTrade Statistics. The data is defined as below, andthey are in the indexes of the base year 1990. Alldata is expressed in US dollars.
Qx = Index of the volume of exports(1990=100) calculated by using thefollowing formulaQx = EXUS/PxWhere EXUS and Px are exports inUS dollars and export price indexi nUS dollar term respectively.
Qm = Index of the volume of imports(1990=100) calculated by using thefollowing formula;Qm = IMUS/PmWhere IMUS and PM are imports inUS dollars and import price index inUS dollar term respectively.
Pw = index of the world export price(1990=100) calculated by using themethod of Houthakker and Magee(1969) and Goldstein and Khan(1978).
Yw = the trade-weighted ‘world’ real in-come, calculated as a weighted aver-age of real incomes of five major ex-port partners of each country. Ex-pressed as an index (1990=100) fac-ing the country (see Houthakker andMagee, 1969).
GCI = The export composition index
The index is constructed as follows. The exportsgood is divided into four groups (C
1,….C
4).
C1
= Total exports of agricultural products andcrude material
C2
= Total exports of traditional manufactur-ing sectors
C3
= Total exports of scale intensive sectorsC
4= Total exports of specialised supply and
science based sectors
Following Muscatelli et al. (1995b) the exportcomposition indexes is constructed using the for-mula below. The index GCI lies over interval (0,1).The weights chosen are a
