Prediction of US Export to China.docx

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PredictionofUSExporttoChina

西南财经大学

SouthwesternUniversityofFinanceandEconomics

商科研究方法II

论文题目:

PredictionofU.SExporttoChina

学生

姓名：

郭宏宇

所在学院：

国际商学院

专业：

国际经济与贸易

学号：

41110024

2014年6月

PredictionofU.SExporttoChina

GuoHong-yu

（TheSouthwestUniversityofFinanceandEconomics，Internationaleconomicsandtrade）

Abstract:

ChinaandAmericaisthelargesttradingpartner.SinceChina’saccessiontoWTO,thevolumeoftradebetweenChinaandAmericahaverisensharply.However,therearestillsometradebarriersandfrictionbetweentwocountries.TheresearchbasedontradebetweenAmericaandChinaisimportanttothetwocountrieseventheworldeconomy.IselecttheU.SexporttoChinaasdependentvariableandusedistributedlagmodeltoforecasttheU.Sexport.

Keywords:

U.SexporttoChina；Q-test；

1.Introduction

1.1Motivation（BackgroundandSignificanceofTopics）

AmericaandChinaarethefirsttwolargesteconomicentitiesintheworld.Atthesametime,chinaandAmericaisalsothelargesttradingpartner.Forecastingtheexportandimportvolumeininternationaltradeistheprerequisiteofagovernment’spolicy-makingandguidanceforahealthierinternationaltradedevelopment.SinceChina’saccessiontoWTO,thevolumeoftradebetweenChinaandAmericahaverisensharply.However,therearestillsometradebarriersandfrictionbetweentwocountries.TheresearchbasedontradebetweenAmericaandChinaisimportanttothetwocountrieseventheworldeconomy.Here,IselecttheU.SexporttoChinaasdependentvariableandusedistributedlagmodeltoforecasttheU.Sexport.

1.2Literaturereview

MostofliteraturessetupARMAmodelstopredictfutureexports.AndmanyprofessorspointoutthatARMAmodelisusefulinshort-runforecastratherthanlong-runwhichmayhavefiercevolatility.RonaldL.Coccariinvestigatedtheresultsofafewdifferentmodelsin“AlternativeModelsforForecastingU.S.Exports”（RonaldL.Coccari,1998）.HepointedoutthatOneobviousconclusionfromthisanalysisisthatforecastevaluationshouldnotberegardedasaprocedureforacceptingoneforecastingmodeltotheexclusionofothers.XiaoZ&GongKinvestigatedacombinedforecastingapproachbasedonfuzzysoftsets（XiaoZ&GongK,2007）,whichpointedoutthatacombinedforecastingapproachbasedonfuzzysoftsetsisapromisingforecastingapproach.DiamantopoulosAandWinklhoferH.researchedthetechniqueutilizationanditsimpactonforecastaccuracy,thepaperpointedthat“inordertoimproveforecastaccuracy,attentionneedstobefocusedbeyondthequestionoftechniqueselection”.（DiamantopoulosA&WinklhoferH.,2003）.Eachalternativemethodusuallycontainsavaluablepieceofinformationthatmaybeusedbycombiningallavailableforecastsintoacomposite.OnemightsimplywanttousethetrendandseasonalmodelsincetherewasfoundtobesuchastrongtrendcomponentinU.S.exports.Italsorevealstheobviousdependencyofexportsuponpreviouslaggedobservations（especiallyathreequarterlag）,andthusasimpleautoregressiveschemeseemsappropriate.

2.Data

2.1Datasource

IfindmonthlydataofexportfromtheUStoChinaandforeignexchangeratebetweentheUSandChinainthewebsiteFederalReserveEconomicData（FRED）.TheyareseasonallyadjusteddatafromJanuary1985toAugust2013.ButChinaisofficiallynotaWTO（WorldTradeOrganization）memberuntilDecember2001.SoIdropthedatawhichispreviousthanJanuary2002andfocusonthelaterones.Andthedataisseasonallyadjusted.

2.2Datadescription

Iplotthepointsofexportandexchangerateandgetthefollowinggraph.Andwecanseethattherearetrendbothintheexportandexchangerate.

ThenImakeanAugmentedDickey-Fuller（ADF）testtoseeifthereisunitrootinthedataoritisstationary.First,Itestthedataofexport.

Theabovestataresultsshowthatexportisstationary,butthereisunitrootinexchangerateasshownbelow.

Soitneedtomakedifferenceofexchangeratetoget

Zt=ert-ert-1

Andthentestifit’sstationary.Theresultisasbelowandit’sstationary.

3.Model

3.1Modelselection

Exportisaffectedbychangeinexchangerate.Asintheeconomictheory,whenacountry’scurrencyappreciates（risesinvaluerelativetoothercurrencies）,thecountry’sgoodsabroadbecomemoreexpensiveandforeigngoodsinthatcountrybecomecheaper（holdingdomesticpricesconstantinthetwocountries）.Sothecountryexportsless.From2002to2005,thedecreaseofexchangeratebetweentheUSdollarandothercurrencieshelpedUSindustriesexportmoreandsellmoregoods.Theimpactofexchangerateonexportshouldbeaccountedfor.

Forexport,firstlyItakethelag,itisstillstationary.ThenIremovethelineartrendfromlogexportandgettheresidual.Nextisidentifycycleintheresidual.AutocorrelationgraphhasatrailPartialautocorrelationgraphhasatruncation.SoitisanARmodel.

Andit’sknownthatpreviousvolumeofexporthaveimpactonlattervolumeofexport.SoIcombinetheAR（p）modelofexportanddistributedlagmodelofexportondifferenceofexchangerate.Andthenumberofdistributedlagsisq.Thespecificnumberofpandqshouldbeidentifiedtofindthetruemodel.

3.2Modelspecification

ThentheauthorusetheinformationcriteriaAICandBICtogetthespecificnumberofpintheARmodel.Finally,theresultshowedthatAICandBICisthesmallestwhenpequals13

Asforthedifferenceofexchangerate（z）,thetrendofexchangeratehasbeenremovedwhenmakethedifference.SotheauthorjustmaketheautoregressiveofZonitslagsandthenuseAICandBICtofindthenumberoflags.Finally,Igetqequals1thatiswiththesmallestAICandBIC.Zt=α+βZt-1.Thisisthegraphofdifferenceofexchangerate（z）.

Throughthepreviousprocess,thetruemodelIfoundisbelow:

lnexportt=α0+α1t+γZt-1+β1lnexportt-1+β2lnexportt-2+β3lnexportt-3+β4lnexportt-4+β5lnexportt-5+β6lnexportt-6+β7nexportt-7+β8lnexportt-8+β9lnexportt-9+β10lnexportt-10+β11lnexportt-11+β12lnexportt-12+β13lnexportt-13

Thegraphaboveistheregressionresultusingclassicalstandarderror.TheR2isprettyhigh,whichiscloseto1.Asfortheeffectofexchangerateonexport,ImakeaGrangerCausalitytestandderivethefollowingresult.P-valueissmall（p=0.0210）,sowecanrejecthypothesisofnon-causalityandindicatethatdifferenceofexchangeratedoespredictivelycauseln（export）andhelptopredictit.

3.3Modeltest

First,theauthortestsiftheerrortermofthewholemodeliswhitenoise.Therearetwomethods.ThefirstoneisQ-test.

Theresult0.7205showsitiswhitenoise.

Forsecondmethod,theauthorderivestheautocorrelationofresidualsfromthestata.Andwecanmakeaconclusionthattheerrortermiswhitenoise.efromthegraph.

Second,theauthorusestheWhiteTesttoseeifthereisheterokedasticityinthemodel.Thenderivethefollowingresult.TheP-valueis0.4583,sowecannotrejectthehypothesisofhomoskedasticity.

4.Resultsandforecasts

4.1Evaluatingtheresults

Aftersettingupthemodel,wecanuseittogeneratethefittedvaluesandcomparetheresultwiththeactualvaluestomakesurethatthemodelreallyfitthehistoricaldatawell.Basically,theforecastmodelisagoodoneknownfromthefollowinggraph.

4.2Makingforecast

Theauthorusesthemodelderivedtoestimateone-step-aheadtotwelve-step-aheadpointandintervalforecast.

one-step-aheadforecast

Yt+1=α0+α1t+γZt+β1yt+.....β13yt-12

fromtwototwelvestep-aheadforecast,theforecasterrorisnotWN,itisMA（h-1）.sinceitiscorrelated,theauthoruseanewwaytogetbetterresults.

Yt+2=α0+α1t+γ1Zt+γ2Zt-1+β1yt+.....β13yt-12

Yt+12=α0+α1t+γ1Zt+....γ12Zt-12+β1yt+.....β13yt-12

Theresultsareasfollows.

5.Conclusion

Thispaperanalyzetheexportdatafrom2002m1andestablishAR（13）modelwithtrendanddistributedlagsofexchangerate.Thensuccessfullypredicttheexportinthefutureyear.

Accordingtoourprediction,theexportincreasesteadilyinthenextyear.Thepredictionconformstotherealityforthefollowingreasons.

Forthefirstplace,afterthefinancialcrisisin2008,theglobaleconomystepintoanewbusinesscycle.Incurrentstage,theeconomyofU.S.isrecoveringanddevelopingatafastspeed.Thegoodeconomicconditionwilldefinitelypromoteexportasawhole.

Secondly,withthetrendofglobalization,Chinaismakingmorepoliciestofacilitateinternationaltrade.IthaslaunchedShanghaiPilotFree-TradeZoneonSeptember29,2013.What’smore,itwillcontinuetoestablishTianjinPilotFree-TradeZoneduringnextyear.Theseopenreformationsdefinitelylowerthebarriersoftrade.U.ScanexporttoChinamoreeasily.AndtheconsumptiondemandinChinawillbecomelargerandlarger.

Thirdly,thelastingdepreciationofdollarstoyuanmakeU.SgoodscheaperinChina.Thistrendwillcontinue,forthesimplereasonthatChina,asanew-borninternationaleconomyafterattendingWTO,isplayinganincreasinglyimportantrolearoundtheworld.Thedemandforcurrencyyuanissurgingrapidly.

Finally,themaingoodsthatU.SexportstoChinaarehigh-techproductssuchaselectronicproductsandfinancialservices.Nowadays,thesekindsofindustriesarefacingunprecedentedopportunitiestoboom.EspeciallyinU.S,whereitisabundantinhigh-techhumancapital,theseindustriescangrowfasterandcontributealargeportiontoexport.

REFERENCE

ClementsMP,SmithJ.Evaluatingtheforecastdensitiesoflinearandnon‐linearmodels:

applicationstooutputgrowthandunemployment[J].JournalofForecasting,2000,19（4）:

255-276.

CoccariRL.Alternative