OilpricefluctuationsandtheirimpactonthemacroeconomicvariablesofKuwait：acasestudyusingaVARmodelSUMMARYInthisstudy，avectorautoregressionmodel(VAR)andavectorerrorcorrectionmodel(VECM)wereestimatedtoexaminetheimpactofoilpricefluctuationsonsevenkeymacroeconomicvariablesfortheKuwaitieconomy.Quarterlydatafortheperiod1984-1998wereutilized.Theoreticallyandempiricallyspeaking，VECMissuperiortotheVARapproach.Also，theresultscorrespondingtotheVECMmodelareclosertocommonsense.However，theestimatedmodelsindicateahighdegreeofinterrelationbetweenmajormacroeconomicvariables.Theempiricalresultshighlightthecausalityrunningfromtheoilpricesandoilrevenues，togovernmentdevelopmentandcurrentexpenditureandthentowardsothervariables.Forthemostpart，theempiricalevidenceindicatesthatoilpriceshocksandhenceoilrevenueshaveanotableimpactongovernmentexpenditure，bothdevelopmentandcurrent.However，governmentdevelopmentexpenditurehasbeeninfluencedrelativelymore.TheresultsalsopointoutthesignificanceoftheCPIinexplaininganotablepartofthevariationsofbothtypesofgovernmentexpenditure.Ontheotherhand，thevariationsinvalueofimportsaremostlyaccountedforbyoilrevenuefluctuationsandthenbythefluctuationingovernmentdevelopmentexpenditures.Also，theresultsfromtheVECMapproachindicatethatasignificantpartofLM2varianceisexplainedbythevarianceinoilrevenue.Itreachesabout46percentinthe10thquarter，evenmorethanitsownvariations.KEYWORDS：vectorautoregression(VAR);oilfluctuation;Kuwait1.INTRODUCTIONThepost-1973effectsoftheoilboomontheeconomiesofAraboilproducingcountrieshavebeendiverse，thoughonbalance，manyofthosegovernmentsmightlookbackontheperiod1973–1986asamixedblessing.Incomeontheoilaccountcertainlyroserapidly，butsodidpriceinflation，wageratesandrelianceonforeignlabor.Aboveall，thegrowthoftheoilsectorasacontributortonationalincometendedtoreducetheroleofnonoilsectorstoinsignificanceinmostArabstatesoftheGulf.Thisphenomenonhasbeentermedintheliterature‘theDutchDisease’.Dramaticrisesinpercapitaincomewerethefruitsofrisingoilrevenuesalone，eveninthecaseofthelargermorediversifiedeconomiesoftheGulfsuchasIran(Al-Abbasi，1991).ThereisagreatdealoftheoreticalandempiricalliteraturescrutinizingvariousaspectsoftheDutchDiseaseeconomiessuchasCordonandNeary(1982)，Hamilton(1983)，NearyandvanWijnbergen(1986)，Fardmanesh(1991)，VanWijnbergen(1984)，GelbandAssociates(1988)andTayloretal.(1986)tonameafew.Recently，severalempiricalstudieshavebeenpublishedonAraboilproducingcountries.Forinstance，Taher(1987)studiedtheimpactsofchangesintheworldoilpricesonthedifferentsectorsoftheSaudieconomy.Furthermore，Al-Mutawa(1991)andAl-MutawaandCuddington(1994)analysedtheeffectsofoilshocksandmacroeconomicpolicychangesfortheUAE.Theresultsshowedthat，inthecaseofUAE，anoil-quantityboomledtohigherwelfaregainsthananoil-priceboom.Moreover，anoil-priceorquantitybustalwaysledtolowereconomicgrowthandcreatedawelfareloss.Also，Al-Mutairi(1993)attemptedtoidentifythesourcesofoutputfluctuationsandthedynamicresponseoftheeconomytochangesinkeymacroeconomicvariablesforKuwait.Hisempiricalresultssuggestedthatforshorthorizonsofoneandtwoyears，shockstotheoilpriceaccountformorethan50percentofthevarianceofGDP.However，atlongerhorizonsofthreeyearsandmore，theseshocksareseentobeunimportantininducingGDPfluctuations，accountingonlyforlessthan10percentofthevariance.Shocksofreal-governmentexpenditurewerealsofoundtohaveasignificantroleincausingGDPfluctuations.Kuwaitisatypicalexampleofanoil-basedeconomy.Theoilsectorcontributesovertwo-thirdsofGDPandover90percentofexports.AlthoughKuwaittrieshardtolessenitsdependenceonoilthroughthedevelopmentofanon-oilsector，itssuccesshassofarbeen，atthebest，verymodest.Therealproblemisthatoilpricesandhenceoilrevenuesareexogenouslydetermined.AsamemberofOPEC，Kuwaithasnocontroloverthepriceofitscrudeoilandatleasttheoreticallyspeakingcannotexceeditsassignedproductionquota.TheobjectivesofthisstudyaretoinvestigatetheimpactsofoilpricefluctuationsonkeymacroeconomicvariablesoftheKuwaitieconomy，toexaminethedirectionofcausalityandtodeterminethesignificanceofsuchimpacts.Thiswillcertainlyenhanceourunderstandingofhowinternationaloilpricefluctuationsimpactkeymacroeconomicvariablesandthedynamicresponseoftheseeconomicvariables，includingpolicyvariablessuchasgovernmentexpenditureandmoneysupply.Inthisstudy，theanalysisiscarriedoutusingtwodifferentmodels，namely，thevectorautoregres-sionmodel(VAR)andthevectorerrorcorrectionmodel(VECM).TheVARtechniqueisappropriateinthiscasebecauseofitsabilitytocharacterizethedynamicstructureofthemodelaswellasitsabilitytoavoidimposingexcessiveidentifyingrestrictionsassociatedwithdifferenteconomictheories.TheuseofVARinmacroeconomicshasgeneratedmuchempiricalevidence，givingfundamentalsupporttomanyeconomictheories(seeBlanchardandWatson，1984，Bernanke，1986amongothers).Inthenextsection，abriefreviewoftheliteratureispresentedfollowedbytheVARmodelalongwiththedatautilized.Theempiricalresultsandtheirinterpretationaregiveninsectionfour，followedbytheconclusions.2.THEMODEL2.1.ThebackgroundofVARmethodologyTheVARsystemisbasedonempiricalregularitiesembeddedinthedata.TheVARmodelmaybeviewedasasystemofreducedformequationsinwhicheachoftheendogenousvariablesisregressedonitsownlaggedvaluesandthelaggedvaluesofallothervariablesinthesystem.AnnvariableVARsystemcanbewrittenasA(l)Yt=A+Ut(1)A(l)=l-A1l-A2l2-Amlm(2)whereYtisann×1vectorofmacroeconomicvariables，Aisann×1vectorofconstraints，andUtisann×1vectorofrandomvariables，eachofwhichisseriallyuncorrelatedwithconstantvarianceandzeromean.Equation(2)isann×nmatrixofnormalizedpolynomialsinthelagoperatorlwiththefirstentryofeachpolynomialonA'sbeingunity.Sincetheerrorterms(Ut)intheabovemodelareseriallyuncorrelated，anordinary-least-squares(OLS)techniquewouldbeappropriatetoestimatethismodel.However，beforeestimatingtheparametersofthemodelA(l)meaningfully，onemustlimitthelengthofthelaginthepolynomials.Iflisthelaglength，thenumberofcoefficientstobeestimatedisn(nl+c)，wherecisthenumberofconstants.IntheVARmodelabove，thecurrentinnovations(Ut)areunanticipatedbutbecomepartoftheinformationsetinthenextperiod.Thisimpliesthattheanticipatedimpactofavariableiscapturedinthecoefficientsoflaggedpolynomialswhiletheresidualscaptureunforeseencontem-poraneousevents.Therefore，animportantfeatureoftheVARmethodologyistheuseoftheestimatedresiduals，calledVARinnovations，indynamicanalysis.Unlikeinconventionaleconomicmodelling，theseVARinnovationsaretreatedasaninherentpartofthesystem.Inordertoanalysetheimpactofunanticipatedpolicyshocksonthemacroeconomicvariablesinamoreconvenientandcomprehensiveway，Sims(1980)proposedtheuseofimpulseresponsefunctions(IRFs)andforecasterrorvariancedecompositions(FEVDs).IRFsandFEVDsareobtainedfromamovingaveragerepresentationoftheVARmodel[Equations(1)and(2)]asshownbelowYt=Constant+Ht(l)U(3)AndH(l)=I+Htl+H2l(4)WhereHisthecoefficientmatrixofthemovingaveragerepresentationwhichcanbeobtainedbysuccessivesubstitutioninEquations(1)and(2).TheelementsoftheHmatrixtracetheresponseovertimeofavariableiduetoaunitshockgiventovariablej.Infact，theseimpulseresponsefunctionswillprovidethemeanstoanalysethedynamicbehaviourofthemacroeconomicvariablesduetounanticipatedshocksintheexogenousvariables.Havingderivedthevariance-covariancematrixfromthemoving-averagerepresentation，theFEVDscanbeconstructed.FEVDsrepresentthedecompositionofforecasterrorvariancesandthereforegiveestimatesofthecontributionsofdistinctinnovationstothevariances.Thus，theycanbeinterpretedasshowingtheportionofvarianceinthepredictionforeachvariableinthesystemthatisattributabletoitsowninnovationsandtoshockstoothervariablesinthesystem.2.2.VectorerrorcorrectionmethodologyDickeyandFuller(1979)haveemphasizedthenecessityofanalysingthetime-seriespropertiesofthevariablesbeforetheirrelationshipcanbeestablished.Thisisnecessarybecauseifthevariablesinquestionarenonstationary，thentheestimatedequationswillyieldspuriousandmisleadingregressionresults.Ifthevariablesinarelationshiparestationarythenitisgenerallytruethatanylinearcombinationofthesevariablesissaidtobecointegrated.Johansen’stest(1991，1995)iscommonlyusedtotestforcointegrationbetweenmorethantwotimeseries.Italsoprovidesestimatesofthepossiblelong-termrelationships，i.e.theparametersoftherelationshipsthatensurecointegration.Inthisstudy，avectorerrorcorrectionmodel(VECM)wasalsoestimated.TheVECMisbasicallyaVARsystemthatbuildsonJohansen'stestforcointegrationandisusuallyreferredtointheliteraturesastherestrictedVAR.2.3.TheestimatedmodelanddataThefirststepinestimatingaVARmodelistomakeachoiceofthemacroeconomicvariablesthatareessentialfortheanalysis.ThevariablesconsistofoneexternalshockmeasuredbyinnovationsinthepriceofKuwaitiblendcrudeoil，threekeymacroeconomicvariables，oilrevenues，theconsumerpriceindex，(CPI)andthevalueofimportsandthreepolicyvariables，MoneySupplyM2，governmentcurrentexpenditureandgovernmentdevelopmentexpenditure.Thenotationsofthesevariablesareasfollow：OILP=OilPriceofKuwaitiBlendCrudeOILR=OilRevenue EXDEV=GovernmentDevelopmentExpenditureEXCON=GovernmentCurrentExpenditureCPI=ConsumerPriceIndexM2=MoneyDemand(M2Definition)IMPORTS=ValueofImportsofGoods&ServicesQuarterlydatafortheperiod1984：1-1998：4wereutilizedinthisstudy.ThedatafortheperiodoftheIraqioccupationandtheliberationofKuwaitwereremovedfromthetimeseriesforobviousreasons(1990-1991).AlldataarefromtheQuarterlyMonetaryStatisticsoftheCentralBankofKuwaitandOPEC’sMonthlyBulletin.Similartothepreviousstudies，allthevariablesareexpressedinlogarithmicform.Thiscanbepartiallyjustifiedbythefactthatlogarithmicformstendtoreducethescaleofthevariables，whichisadesirablequalitywhenanalysingthetime-seriespropertiesofthevariablesbeforetheirrelationshipcanbeestablished.Itisalsoausefultoolinprovidingestimatesofthepossiblelong-termrelationships，i.e.theparametersoftherelationshipsthatensureco-integration.AveryimportantpointthatshouldbementionedhereisthatthemajorshortcomingoftheVARapproachisitslackoftheoreticalsubstance(CoolyandLeRoy，1985;Leamer，1985).Inresponsetothiscriticism，BlanchardandWatson(1984)andBernanke(1986)developedprocedures，calledthestructuralvectorautoregression(SVAR)approach，whichcombinesthefeaturesofthetraditionalstructuralmodellingwiththoseoftheVARmethodology.ThemajoradvantageofusingSVARcomesfromthefactthatstandardVARdisturbancesaregenerallycharacterizedbycontemporaneouscorrelations.Inthepresenceofsuchcorrelations，theresponseofthesystem，indicatedbyIRFs，toaninnovationinoneofthevariablesisinfacttheresponsetoinnovationsinallthosevariablesthatarecontemporaneouslycorrelatedwithit.Similarly，theabilityofFEVDstoquantifytherelativecontributionsofspecificsourcesofvariationisconfoundedinthepresenceofthiscorrelation.However，instandardVARmethodologythiscontemporaneouscorrelationispurgedbytheCholeskyorthogonalizationprocedure.Forthemostpart，theCholeskyprocedureimplicitlyassumesrecursivityintheVARmodelasitisestimated.Althoughtheoreticalconsiderationsmayhelpindeterminingthisorderingandex-postsensitivityanalysismayfurtherhelpprovideinsightsregardingappropriateordering，itremainslargelyatthediscretionofthemodeller.Thefollowingorderingofequationswasadoptedinthisstudy;LOILP，LOILR，LEXEDEV，LEXCON，LCPI，LM2andLIMPORTS.Generallyspeaking，thisorderingreflectsthefactthatoilpriceshaveaninfluenceonoilrevenuesandthenonalltheothervariablesinthemodel.However，thebehaviorofoilpricesandtosomeextentoilrevenuearetheleastdeterminedbyothervariablesincludedinthemodel.ThisisquiteaplausibleassumptionbecausetheoilpricesandhenceoilrevenueswhichconsistofoilexportrevenuesandnetfactorincomefromabroadarelargelydeterminedbytheworldmarketconditionsratherthanwithintheKuwaitiEconomy.Similarly，thisorderingassumesthatthegovernmentexpenditureislargelydeterminedbythelevelofoilrevenueswhichagainisquiteaplausibleassumptionconsideringthedominantroleofthepublicsectorindrivingtheKuwaitieconomy.Itisalsosensibletoassumethatthevalueofimportsislargelydependentonthelevelofgovernmentexpenditure.Sincetheonlyvariablesincludedarethosesuggestedbyeconomictheory，andsincetheoreticalconsiderationsareimportantinselectingtheorderingusedhere，theSVARisnotfollowedinthisstudy.Nevertheless，theapproachutilizedherecanbeconsideredtobeinthespiritoftheSVARapproach.3.THEEMPIRICALRESULTSFirst，theVARtechniquerequiresstationarydata，thuseachseriesshouldbeexaminedforstationarity.TableIgivesthenonstationarytestforallthetime-series，usingtheconventionalDicky-Fullertest(DF)，itsaugmentedversion(ADF)andPhillips-Parront-tests.Thesetestsincludeaconstantbutnotimetrend，asrecommendedbyDickeyandFuller(1979).First，thereportedt-statistics，whencomparedwiththecriticalvaluesobtainedbyEngleandYoo(1987)，indicatethatalmostalltheseries，exceptCPI，M2andIMPORTS，arestationaryinthelevelsasshownbytheDF，ADFandPhillips-Perront-tests.Thesetestsarereappliedafterdifferencingallterms.Thet-statisticsonthelaggedfirst-differencetermsindicatethat，forallseriesthenullhypothesisisrejected，thatistosay，allseriesarefirstdifferencesstationary.However，intransformingavariable，ausualquestionarisesastowhetheroneshouldusethevariablesinthesysteminlevelsorindifferences.Theoverallguidelineisthatifthereareknumberofcointegratingvectoramongthevariablesusedinthesystem，thenVARcouldbemodelledwithkstationaryandn-kdifferencesoforiginalvariables.Butifallthevariablesinthesystemarenonstationary，usingaVARinlevelsisappropriate.Ontheotherhand，estimatingaVARinthelevelsinthecaseofcointegrationmayleadtotheomissionofimportantconstraints.Inthiscontext，Doanetal.(1984)notedthatdifferencingavariableis‘important'inthecaseofBox-JenkinsARIMAModelling.Doanetal.alsoobservedthatitisnotdesirabletodosoinVARmodels.Fuller(1976)hasalsoshownthatdifferencingthedatamaynotproduceanygainsofarasthe‘asymptoticefficiency’oftheVARisconcerned‘evenifitisappropriate’.Moreover，Fullerhasarguedthatdifferencingavariable‘throwsinformationaway'whileproducingnosignificantgain.Thus，followingDoanandFuller’sargument，thelevelratherthanthedifferencewasutilizedhere.Second，theestimationofaVARmodelrequirestheexplicitchoiceoflaglengthintheequationsofthemodel.FollowingJudgeetal.(1988)andMcMillin(1988)，Akaike’sAICcriterionisusedtodeterminethelaglengthoftheVARmodel.Thechosenlaglengthisonethatminimizesthefollowing：AIC(n)=Indet∑+(2d2n)/Twheredisthenumberofvariablesinthemodel，Tthesamplesizeand∑nanestimateoftheresiduals’variance-covariancematrix∑nobtainedwithaVAR(n).Themaximumlaglengthissetatfivequarters，consideringthesamplesizeandnumberofvariablesinthemodel.Amaximumlagofgreaterthanfivequarterswouldreducethedegreesoffreedomforestimationunacceptably.TheresultofemployingthistechniqueissummarizedinTableII，whichshowsthecorrespondingAICvalues.ItcanbeseenthattheAICcriterionisminimizedfororder4.Thissuggeststhat，forthisstudy，theVARmodelshouldbeoforder4.ThenextstepistoestimatetheVAR.Theestimatesalongwiththeirt-valuesarereportedinTableIII.AlthoughtheestimatesofindividualcoefficientsinVARdonothaveastraightforwardinterpretation，aglanceatthetablegenerallyshowsthatmostofthet-valuesaresignificant(exceptfortheCPIequation)andalmostalloftheequationshavehighR-squares.Italsoconfirmstheassertionthatoilpricesareexogenouslydeterminedthanothervariablesincludedinthemodel.However，oilrevenueequationhasalargernumberofsignificantt-valuesthancurrentexpenditureandCPI.3.1.VariancedecompositionTableIVpresentsthevariancedecompositionforthe10-quartersforecasts.TableIVshowsthatinitiallythevariationsinallofthevariablesaretypicallyexplainedbythevariables’owntrends.Thatistosay，atthebeginning，thehistoricaltrendofeachvariableexplainsalargepartofitsownvariations.Forthemostpart，aftertenquarters，about60percentofthevarianceinoilpricesisexplainedbythevariableitselfwhichisindicativeofitsexogenousnature.Ontheotherhand，oilrevenueexplainedabout93percentofitsownvariationsatthefirstquarterandabout20percentatthe10thquarter.Moreover，variationinoilpricesaccountforabout45percentofthevariationinoilrevenuesstartingatthesecondquarterandthroughtothetenth.Thisshowsthatthecausalityisrunningfromoilpricestooilrevenues.Similarresultsarealsoevidentforgovernmentdevelopmentandcurrentexpenditures.Overatimeperiod，about15-17percentofthevarianceingovernmentexpenditures(developmentandcurrent)isaccountedforbythevariationsintheoilrevenues.Furthermore，lookingatthevariancedecompositioninthegovernmentexpenditures(developmentandcurrent)itisobservedthatfollowingtheirownvariationsandoilrevenues，theLCPIaccountforanotablepartoftheexpenditures’variance.TheCPIaccountsforonefifthofthecurrentexpenditurevariationsandabout15percentofthedevelopmentexpenditure.Thisisquiteaplausibleresultandveryapparentinthecaseofcurrentexpenditure.Ontheotherhand，itisworthnotingthattheothervariablethatalsopicksupasignificantpartofthevariationsingovernmentdevelopmentexpenditureisthevalueofimports.Itaccountsforabout16percent.LookingatthevariancedecompositionofM2，itisapparentthatanoticeablepartofitsvarianceisexplainedbythevarianceintheCPI(about33percent)，evenmorethanitsownvariations.Also，oilpricesandoilrevenue，respectively，accountforabout23and13percentofitsvariations.Theseresultssuggestanimportantroleformoneysupply.Moreover，overthetimeperiod，theresultsshowthat25-45percentofthevarianceinthevalueofimportsisaccountedforbythevariationinoilrevenuesalone.Othervariablesincludedinthemodelthatexertsignificantinfluenceonthebehaviourofimportsarethetwotypesofgovernmentexpenditurebutinparticular，thedevelopmentexpenditure.3.2.ImpulseresponsesFigure1displaystheImpulseResponseFunctions，whichareessentiallythedynamicmultipliers.Sincetheprimaryinterestistoseetheresponseofmajormacroeconomicvariablestotheshocksgiventotheoilrevenuesandthentothegovernmentexpenditure，onlytentimeperiodsarereported.AninspectionofFigure1revealsthatinnovationintheoilpricesandhenceoilrevenuehasasimilareffectonmostofthevariablesinthemodel.Generally，mostofthesevariablesshowanincreaseinthefirstquarter.Thisincreasecontinuesinthesecondandthirdquarterandthenitgraduallytapersoffoverthesuccessivequarters.TheonlyexceptionsaretheCPIandthevalueofimportsandM2.ThismaybeattributabletotheshortcomingsinthedatasetusedtoestimatetheVAR.RecallthatLCPI，LM2andLIMPORTSwerefoundtobenon-stationaryinthelevel.3.3.EstimationofthevectorerrorcorrectionmodelSincemostofthevariablesincludedinthemodelpertaintostationarytimeseriesdataexceptLCPI，LM2andLIMPORTS，Johansen’stest(1991，1995)wasappliedtocheckforcointegratingvectors.Thetestindicatedthattherearefourcointegratingvectors.Therefore，avectorerrorcorrectionmodeliswarranted.AvectorerrorcorrectionmodelisaVARthatbuild-incointegration.Eachco-integratingequationaddstheparametersassociatedwiththeterminvolvinglevelsoftheserieswhichneedstobeaddedtoeachequationintheVAR.Thereisasequenceofnestedmodelsinthisframework.TheJohansentestprocedurecomputesthelikelihoodratioforeachaddedco-integratingequation.OnthebasisofJohansen’stest，aVectorerrorcorrectionmodel(VECM)wasestimated.Fourco-integratingequationswereestimatedusingthesamesevenvariablesthatwereusedintheVAR.However，sincetheresultsofestimatingtheVECMdonothaveadirectinterpretation，theyarenotreportedhere.3.4.VariancedecompositionThevariancedecompositionresultscorrespondingtotheestimatedVECMarepresentedinTableV.TheyarebasedonthesameorderingaswasusedintheVAR.ComparingtheseresultswiththeVARshowsthatwhilethequalitativenatureofmacroeconomiclinkagesremainsalmostthesame，theintensityofinteractionbetweenthevariablesissignificantlyhigherwhenco-integrationhasbeenaccountedfor.Forexample，lookingatthevariancedecompositionoftheoilrevenues，itshowsthatvariableslikegovernmentdevelopmentandcurrentexpenditureshaveasubstantiallylargersharewhencomparedwiththeVARresultswhichincreasedfrom14percenttoabout40percent.Similarly，theoilrevenuehaspickeduparelativelylargerproportionofthevariationinthegovernmentcurrentexpenditureaswellasthevalueofimports，especiallyduringthefirst4-6quarters.However，theresultsindicatethatvariationsinLCPI，LM2andLIMPORTS，after7-10quarters，aremainlyexplainedbychangesinoilrevenuealone.Inparticular，thevariancedecompositionofLM2indicatesthatasignificantpartofitsvarianceisexplainedbythevariationsinoilrevenues(about46percentafter10quarters)，evenmorethanitsownvariations.Ontheotherhand，contrarytotheresultfromVAR，LCPIaccountsforonly7percent.Empiricallyspeaking，theVECMmodelshowsarelativelyhigherdegreeofstatisticalsignificance.Theoreticallyspeaking，thisisbecauseityieldsacloserinteractionbetweenmacroeconomicvariablesthanwhattheVARindicated.3.5.ImpulseresponsefunctionsFigure2displaystheimpulseresponsefunctionscorrespondingtotheVECMmodel.Figure2indicatesthatinnovationsintheoilpricesandoilrevenuehaveasimilarimpactonthevariablesincludedinthemodel.However，similartotheVAR，mostofthevariablesshowanincreaseforthefirstfewquartersthenitgraduallytapersoffoverthesuccessivequarterswiththeexceptionofCPI，valueofimportsandLM2.ComparingtheseIRFswiththosecorrespondingtotheVARversionrevealsthatittakesalittlelongerforthemultipliersintheVECMversiontoreachtheleveloftheVARversion.WhiletheygenerallyreachedtheirpeakintheVARversioninabout6-7quarters，ittookthem8-9quarterstoreachalmostthesamelevelintheVECMversion.4.CONCLUSIONSANDSOMEPOLICYIMPLICATIONSTheprimarygoalofthispaperwastoinvestigatehowmacroeconomicvariablesreacttofluctuationsintheworldoilprices.Therefore，twodifferentversionshavebeenestimated，namely，theVARandtheVECM.Whilethequalitativenatureofmacroeconomiclinkagesremainsalmostthesameinthetwomodels，theintensityofinteractionbetweenthevariablesissignificantlyhigherwhencointegrationhasbeenaccountedfor.Thus，quantitativelythetwomodelsgiveresultsthataresignificantlydifferentfromeachother.However，empirically，theVECMgivesbetterresultsbecauseityieldsacloserinteractionbetweenmacroeconomicvariablesthanbytheVARestimation.TheresultscorrespondingtotheVECMarealsoclosertocommonsense.Nevertheless，thetwoversionsestimatedindicatedanotabledegreeofinterrelationbetweenthemajormacroeconomicvariables.Theresultshavehighlightedthecausalityrunningfromoilpricestowardsoilrevenuesandthentowardsgovernmentexpenditureandothervariables.However，furtherassessmentoftherelationshipbetweenthesevariables，basedonorthogonalinnovations，leadustobelievethatoilpriceshocksdoimpactmacroeconomicvariablesinKuwaitandinparticular，viagovernmentdevelopmentandcurrentexpenditures.Theevaluationofthedecompositionofthevarianceofgovernmentexpendituressuggeststhatoilrevenuefluctuationsaccountforanotablepartespeciallyinthecaseofdevelopmentexpenditure.Thisresultisnotsurprisingandisactuallyconsistentwithwhatisexpectedinacountryinwhichthegovernmentisthesoleownerofthemainnationalincomesource，theoilandgasindustry.Thus，governmentexpenditurebecomesthemajordeterminantofthelevelofeconomicactivityandthemechanismbywhichthegovernmentcaneffectthecircularflowofincomewithintheeconomy.Whatissurprising，however，isthatonewouldexpecttheimpactofoilshockstobemuchstrongerandinparticular，inthecaseofcurrentgovernmentexpenditure.However，thismaybeexplainedbythefactthatoverthelastthreedecades，thegovernmenthasaccumulatedcapitalreserve(surplus)whichisregularlyusedtofinancecurrentgovernmentcommitments，especiallyintimesoflowoilrevenue