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1、Abstract:ThisarticlecollectsaseriesquarterlydataofChina’sGDPfrom1992to2010,andweusethemethodoffactordecompositiontocollectthelong-termincreasingtrendandseasonality,thenuseARMAmodeltofittheresiduals,doanalysistogetthefinalmodelanduseittogenerateashort-termGDP-forecastofchina
2、.Keywords:factordecomposition;ARMAmodel;GDPforecast；1.Introduction1.1BackgroundFrom1978,sincethereformandopeningup,china’seconomyisdevelopingrapidlyandsteadily.AfterjoiningtheWTO,thedevelopingspeedhasreachedanewlevel.GDP(GrossDomesticProduct),whichisthebasisofnationaleconom
3、icproductionofstatisticalindicators,canbeusedtoreflectacountry’seconomy.ItisthecoreofStatisticalindicatorsinthenationaleconomy.GDPcombinesresponsesofthemostbasicaspectsofmacroeconomic,cannotonlymeasuretheoverallnationaloutputandincomescale,butalsocanexploretheeconomicfluctu
4、ationsandcycles.Hence,itisofgreatimportancetofitandanalyzeGDPaccuratelyforexploringacountry’smacroeconomicstrend.TheaimofthisarticleistogenerateaGDPforecastmodelanduseittopredictthefutureGDPofchina.1.2MethodAlotofmethodshavebeenusedtoanalysiseconomyphenomenon,timeseriesanal
5、ysisisoneofthemostefficientmethods.Atimeseriesisacollectionofobservationsofwell-defineddataitemsobtainedthroughrepeatedmeasurementsovertime.Time-seriesmethodsuseeconomictheorymainlyasaguidetovariableselection,andrelyonpastpatternsinthedatatopredictthefuture.Anobservedtimese
6、riescanbedecomposedintothreecomponents:thetrend(longtermdirection),theseasonal(systematic,calendarrelatedmovements)andtheirregular(unsystematic,shorttermfluctuations).Whenthesefactorsoccur,wecanusethemethodofdecomposition,fromwhichcanwecollectusefulinformationofthedata,wede
7、fineditasfactordecompositionhere.Thetrendcomponenttypicallyrepresentsthelongertermdevelopmentsofthetimeseriesofinterestandisoftenspecifiedasasmoothfunctionoftime.Therecurringbutpersistentlychangingpatternswithintheyearsarecapturedbytheseasonalcomponent.Itisquitecommoninecon
8、omictimeseries,whenitoccurs,weshoulduseseasonaladjustmentmethod.Seasonaladjustment
