MODELING AND FORECASTING THE TEXTILE PRICE INDEX USING SEMI-NONPARAMETRIC REGRESSION TECHNIQUE

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1 Ierol Jourl of Iovve Mgeme Iformo & Produco ISME Ierol c 4 ISSN Volume 5 Numer Mrch 4 PP MODELING ND FORECSTING THE TEXTILE PRICE INDEX USING SEMI-NONPRMETRIC REGRESSION TECHNIQUE JINGHUI HE ING XU Sho Xg College of rs d Sceces Shoxg 3 Ch heh53@63.com Reserch Isue of Quve Ecoomcs heg Gogshg Uvers Hghou 38 Ch gxu@hoo.com.c STRCT. The Texles Prce Idex (TPI) s kd of dex h mesures he exle prces rded Ch Texle C ol. The TPI forecsg s mpor for oh rde pres. I hs vesgo e collec vrous fcors hch perhps fluece he TPI from he dusrl ecoom po of ve d hose re rough ou of sock mrke. The he oprmerc ph desg s emploed. sed o me ph fcors hch fluece he exle mrke sgfcl mog he colleced fcors re exrced d defed her ddhs oprmerc regresso h Locl-Cos Les-Squres esmo d Locl-Ler Les-Squre esmo respecvel. Fll e forecs he TPI he oprmerc ph desg. d comprso h prmerc regresso shos h he oprmerc ph desg s more ccure. Keords: Locl-Cos Les-Squres; Locl-Ler; Les-Squres; Les-Squre; Cross-Vldo; Ph Desg; Forecsg. Iroduco. Forecsg s of gre mporce m res especll ecoom. esdes ecoom heores sscl ools lke Mulple Regresso Techques d Tme Seres lss re he ver ell ul mehodologes used for forecsg he seres. g e l. (7) keso d Oh () Sock d Wso (999) d Sock d Wso (8) forecs flo exesos of he Phllps curve. The geerl frmeork volves depede vrle such s flo (or he chge flo) d explor vrles cludg lgs of flo he uemplome re d oher predcors (Koop d Korols ). Koop d Korols () forecs qurerl US flo sed o he geerled Phllps curve usg ecoomerc mehods h corpore dmc model vergg h llos for coeffces d hus he ere forecsg model o chge over me. The dmc model vergg leds o susl forecsg mprovemes over smple echmrk regressos. Lee () evlues hree lerve flo forecsg models uvre me-seres (RIM) model Phllps curve model d ïve model for seleced umer of flo-rgeed coures d fds h hese models geere more ccure forecss of flo re for he perod follog he dopo

2 9 JINGHUI HE ND ING XU flo rgeg polc. Furhermore ou-of-he-smple flo forecss geered RIM model re more ccure h hose geered he oher o forecsg models for mos coures especll for he perod follog he dopo of flo rgeg polc. esdes clsscl sscl mehods echques used egeerg res efore d e proposed d mg echques such s Neurl Neork d Suppor Vecor Mche re roduced ecoom. Sh e l. (9) predced he moveme of he Kore sock mrke usg ck-propgo Neurl Neork (PN) d Suppor Vecor Mche (SVM). The resul of he expermes s h predco ccurc usg SVM s eer h h usg PN. Hug d Wu (8) propose hrd model h comes vele-sed feure exrcos h he relevce vecor mche (RVM) models o forecs sock dces. The me seres of explor vrles re decomposed usg some vele ses d he exrced me-scle feures serve s pus of RVM o perform he oprmerc regresso d forecsg. Compred h rdol forecsg models her proposed mehod performs es h s he roo-me-squred forecsg errors re sgfcl reduced. Vsl d h () emplo Neurl Neorks d sscl echques o model d forecs he dl sock mrke prces d compre he o resuls of he o models MPE MSE d RMSE. The resuls sho h Neurl Neorks he red h suffce d proper pus d h proper rchecure c predc he sock mrke prces ell. Sscl echque hough ell ul u her forecsg l s reduced s he seres ecome complex. Geerll el proposed models or mehods re much eer h orgl oes. u Roodposh e l. () use he log model rfcl eurl eork d mulple dscrm lss o forecs prce mpulo of socks of compes prese Tehr sock exchge. The resul s h here s o cosderle dfferece mog forecsg poer of he hree models. Eveull here s ohg good or d ou he mehods h s mpor s h hch oe s more ppropre o descre he specfc oecs. Ch s Keqo Texle Idex (Keqo Idex) cludes exles prce dex exles prosper dex exles foreg rde prce dex d order dex. Ths pper focuses o exles prce dex hose cosues s r merls dex gre cloh dex pprel frc dex home exle dex d fsho ccessores dex. There re m polcl ecoomcl eve clmc fcors h m ffec exles prce dex's red d voll drecl or drecl u o ll of hem re sscll ssoced h he dex's chge. We r o selec relev oes s ell s def he mechsm ho he fcors ork lerl or o-lerl oprmerc pproches h re roduced Peer Hll Q L d Jeffre S. Rce (7). I s ecessr o delee rrelev vrles for o resos. I s ell-ko h oprmerc mehod s ffeced he so-clled "curse of dmesol" cused he sprs of d hgh-dmesol spces resulg decrese fses chevle res of covergece of regresso fuco esmors ord her rge curve s he dmeso of he regressor vecor creses. O he oher hd our fl rge s o forecs he exle prce dex h he seleced model less regressors ll mke he forecsg more effce. Our pper s cosruced ccordg o he follog les. Seco s model prepro 9

3 MODELING ND FORECSTING THE TEXTILE PRICE INDEX 9 hch s ho o choose he ph ledg o he curve d l seleco of prox vrles h m fluece he depede vrle's red d voll. Seco 3 s he emprcl resuls of ph desg vrle seleco d defco. Seco 4 s he mproved esmo of he model hch s more ccure d he dex forecsg furhermore comprso h he ler model. The fl seco cocludes.. Prox Vrles d Mehodolog. Texle prces re flueced m fcors. From he ve of he dusrl ecoom he fcors clude demd cos d echologcl ovo. The ecoomc oom cosse dex sds for he demd for exle coo prce crude ol prce d lor cos sd for he cos of exle dusr d lor producv or vesme reserch d developme for echologcl ovo. Moreover s pr of he ecoom exle dusr s flueced he mcroecoomc evrome evl. Smlr o sock mrke four specs re cosdered o ork exle mrke; he re suppl of moe flo eres res lo of fcl eerprse d level of exchge re d so o. d he vll of oservos mus e uder cosdero. Fll fouree vrles re chose s l oes o e deermed heher relev or rrelev ler or o-ler. The vrles re possle phs for he dex o chge log. ove ll me s he sc ph. The proxes d oo re s lsed elo. Texle prces mohl verge dex; Tme; The ecoomc oom cosse dex (996); The mohl verge crude ol prce (dollrs per rrel); 3 Coo dex (ces per kg); 4 Suppl of moe (M); 5 Cosumer prce dex ( er erler ); 6 Rel prce dex ( er erler ); 7 Producer prce dex ( er erler ); 8 echmrk oe-er depos re (ul percege re) %; 9 Eerprse deposs fcl suos (oe hudred mllo u RM); Svg deposs fcl suos (oe hudred mllo u RM); Shor-erm lo from fcl suos (oe hudred mllo u RM); Medum d log erm los from fcl suos (oe hudred mllo u RM); 3 Level of exchge re RM/US$ (u); 4 Edg se foreg exchge reserves (oe hudred mllo US dollrs). The depede vrle s exle prce dex hch s me seres. The depede vrles re mcroecoomc vrles s cross-seco d s ell s lgged depede vrles. Pug lgged depede vrles s ler vrles he model s exeso o clsscl semprmerc model hs pper. Th s g ε () ( ) ( ) ( ) 9

4 9 JINGHUI HE ND ING XU 9 Where g (). s he exle prce dex s fouree-dmeso vecor sdg for severl mcroecoomc fcors clled corol vrles. d re he h oservo. g s uko d m e uko forever so h ll e esmed oprmerc regresso. d re uko fucos. ccordg o Tlor's heorem he c e pproxmed ler fucos such h (3) pu () (3) o () d le he () c e rere s ε. We c esme mmg he follog h m. For smplc e plce X { } h h h W dg 4 3 T 4 3. The he soluo s W X WX X T T T. u he ddh o ever corol vrles s sll uko so e use p l h.6 σ o clcule he h ddh hch σ s he h vrle's smple sdrd devo (STDEV) l s he kerel fuco's order p s he umer of he corol vrles d s he smple se. ( ) T s esmed frs s esmo s ( ) T. Wh he purpose of g e plug T () such h g (4) Le he (4) ecomes g (5)

5 MODELING ND FORECSTING THE TEXTILE PRICE INDEX 93 (5) c e esmed Locl-Cos Les-Squre (LCLS) d he corol vrles ddhs re specfed Les-Squre Cross-Vldo (LSCV) mehod. s resul e ge he ddhs of (). We use Theorem. Peer Hll Q L d Jeffre S. Rce (7) for oprmerc regresso o selec corol vrles relev o he exle prce dex d delee rrelev oes smuleousl f he relve ddhs re lrge eough for exmple lrger h o mes he STDEV. fer h () s reesmed he (4) d (5) re go. Gve (5) s g (6) We esme (6) g usg Locl-Ler Les-squre (LLLS) d he ddhs re specfed LSCV. If cer corol vrle's ddh s lrge eough he relve vrle s hough h s fluece o he exle prce dex s ler. 3. The Emprcl Resuls of Vrle Seleco d Idefco. The smple perod s from J. 8 o J. he umer of oservos s 49. The exle prce dex d s doloded from he ese of Texle Idex Ch Keqo he suppl of moe d echmrk oe-er depos re re from People's d of Ch d he ohers re from DRCNET Sscl Dse Ssem. fe of mssg d re supplemeed cuc sple erpolo fuco mehod. Our frs gol s o deerme hch corol vrles fluece he exle prce dex's red d voll sgfcl. Specfcll e use oprmerc mehods o deerme he relevce of ech corol vrle d heher or o eers he model lerl. The e use he seleced equo o forecs he ex erm dex vlue hle he regressors' vlues re gve. Our ddhs of ever corol vrles for he smple re preseed Tle. The ddhs he le come from esmo LCLS. The ls colum s o mes he STDEV of he smple. Here e c oserve hch vrles re relev d hch re rrelev. We oe h he ecoomc oom cosse dex coo dex suppl of moe eerprse deposs fcl suos svg deposs fcl suos shor-erm lo from fcl suos medum d log erm los from fcl suos level of exchge re d edg se foreg exchge reserves re smoohed ou ecuse her ddhs re lrge eough compred h her o mes of he STDEV respecvel. The oher vrles re hus cosdered o e relev erms of he esmo of he exle prce dex. Tle gves he ddhs from he LLLS esmo. Ths me here re 5 corol vrles remed he re he mohl verge crude ol prce cosumer prce dex rel prce dex producer prce dex d echmrk oe-er depos re. Here e c deerme o vrles cosumer prce dex d producer prce dex o ler vrles he model ecuse he hve ddhs h re more h ce he se of her STDEV respecvel. 93

6 94 JINGHUI HE ND ING XU TLE. ddhs usg locl-cos les-squre esmo Vrle ddh Tce he STDEV The ecoomc oom cosse dex 6.5e The mohl verge crude ol prce Coo dex 3.69e Suppl of moe 4.47e Cosumer prce dex Rel prce dex Producer prce dex.9.98 echmrk oe-er depos re.3.36 Eerprse deposs fcl suos.83e Svg deposs fcl suos 3.75e 8.8 Shor-erm lo from fcl suos.9e Medum d log erm los from fcl suos 3.e Level of exchge re 3.95e Edg se foreg exchge reserves.65e9 36. TLE. ddhs usg locl-ler les-squre esmo Vrle ddh Tce he STDEV The mohl verge crude ol prce Cosumer prce dex Rel prce dex Producer prce dex echmrk oe-er depos re.3.36 I hs seco he emprcl resul s h here re fve corol vrles relev o exle prce dex o ou of he fve re ler d he ohers re o-ler. 4. Furher Emprcl Resuls. I seco 3 he coeffces model () ( ) ( ) re me-vrg he re fucos o u her lc expressos re uko so h he hve ee pproxmed ler fucos s sho (3). I order for coveece emprcl sud s cos. I he prevous seco s he med of he smple perod. The prolem s h he more he po fr from he greer error. s med e le chge h he me of smple po such h he oe degree erm (3) s ls ero d cos re dffere log h. ccordg o he resuls seco 3 here re four ler vrles he re o lgged depede vrles cosumer prce dex d producer prce dex d four corol vrles he re me he mohl verge crude ol prce rel prce dex d echmrk oe-er depos re h s me ph d ddol vrle ph. The four coss' esmos re preseed he ppedx h s esmed oservos from J 8 o prl. To compre he oprmerc ph desg mehod h prmerc oe e emplo hem o forecs he exle prce dex Ju d Jul h he oservos from J 8 94

7 MODELING ND FORECSTING THE TEXTILE PRICE INDEX 95 o M. The exle prce s he depede vrle; o of s lgged vrles d he l 4 vrles re he regressors. The esmos d relve sscs re preseed Tle 3. TLE 3. The esmos of he prmerc model Vrle Coeffce Sd. Error -Ssc Pro. The frs-lgged depede The secod-lgged depede The ecoomc oom cosse dex The mohl verge crude ol prce Coo dex Suppl of moe.86e-5.7e Cosumer prce dex Rel prce dex Producer prce dex echmrk oe-er depos re Eerprse deposs fcl suos.3e E Svg deposs fcl suos -.54E-5.58E Shor-erm lo from fcl suos -.4E-6.7E Medum d log erm los from fcl suos -3.66E-6 3.7E Level of exchge re Edg se foreg exchge reserves dused R-squred.97. ecuse he regressors clude he depede's lgged vrles s possle h here s coemporeous correlo eee he depede vrles d he sochsc dsurce. u he Perso correlo coeffces eee oe- o- d hree-lgged-erm depede d he resdul seres of he regresso equo re.9.74 d -. respecvel. Whe he sgfcce level s 5% s sll c' e reeced h he correlo coeffces equl o ero. I mes h he rdom dsurce hs o relo o he rdom depede vrles d he esmors of he coeffces re used d cosse. We use he equo o forecs he dex Jue d Jul. The resul s sho Tle 3. Nex e forecs he dex Jue d Jul he oprmerc ph desg model. Wh he esmo of he coeffces M o esme hose ug. d 53 he esmo s (7) g T 5 7 T 6 8 T 53 (7) The o forecsg resuls re preseed Tle 3. We c fd h oprmerc ph desg model's forecsg s more ccure h h of he prmerc model. 95

8 96 JINGHUI HE ND ING XU De The rel vlues TLE 4. The forecsg h o models Forecsg h prmerc model Forecsg h Ph Desg Jue Jul I order o forecs he dex ug. e use he oservos from J 8 o Jul o esme he coss Jul meg s Jul. (8) s he equo. 7 ( T ) g ( ) T 6 8 T 55 (8) I Jul he fve prs o he rgh sde of (8) re d respecvel hch mes he ler pr s more egh h he o-ler pr. I lgh of he prevous resul e do suo smulo s forecsg o he dex vlue ug. preseed Tle 4. We use he esmo of he coeffces Jul o esme hose ug.. Suo The mohl verge crude ol prce TLE 5. The suo smulo Cosumer prce dex Rel prce dex Producer prce dex echmrk oe-er depos re The exle prce dex Cocluso. The prcpl gol of he prese reserch s o offer model o forecs he exle prce dex Ch's Texle Mrke. Therefore sed o seleced vrles such s mohl verge crude ol prce cosumer prce dex rel prce dex producer prce dex d echmrk oe-er depos re re roduced s relev fcors h exle prce dex oprmerc ph desg d s defed h cosumer prce dex d producer prce dex fluece he depede ler per sll oprmerc pproch. ecuse of he lgged effec of he exle prce dex he lgged s emploed s ler depede vrles. Therefore e cosruc ph desg model h four ler depede vrles d four corol vrle mel o-ler depede vrles. Emprcl ess sho h he oprmerc ph desg model s much eer h prmerc model o ol sscl ccurc u lso he l of forecsg shor erm. ls suo smulo s pu forrd ccordg o he srucure of he model s pplco. 96

9 MODELING ND FORECSTING THE TEXTILE PRICE INDEX 97 REFERENCES []. keso d L. Oh () re phllps curves useful for forecsg flo? Federl Reserve k of Mepols Qurerl Reve vol.5 pp. -. []. g G. eker d M. We (7) Do mcro vrles sse mrkes or surves forecs flo eer? Jourl of Moer Ecoomcs vol. 54 pp [3] D. Hederso J. C. Ppgeorgou d C. F. Prmeer () Groh emprcs hou prmeers The Ecoomc Jourl vol. pp [4] F. R. Roodposh M. F. Shms d H. Kordloue () Forecsg sock prce mpulo cpl mrke World cdem of Scece Egeerg d Techolog vol. (8) pp.5-6. [5] G. Koop d D. Korols () Forecsg flo usg dmc model vergg Ierol Ecoomc Reve vol. 53 pp [6] J. Q. F d T. Hug (5) Profle lkelhood fereces o semprmerc vrg-coeffce prll ler models eroull vol. o.6 pp [7] J. S. Rce d Q. L (4) Noprmerc esmo of regresso fucos h oh cegorcl d couous d Jourl of Ecoomercs vol.9 pp [8] J. Sock d M. Wso (999) Forecsg flo Jourl of Moer Ecoomcs vol. 44 pp [9] J. Sock d M. Wso (8) Phllps curve flo forecss NER Workg Pper No. 43. [] K. S. Vsl d. K. h() lss of he performce of rfcl eurl eork echque for sock mrke forecsg Ierol Jourl o Compuer Scece d Egeerg vol. () pp.4-9. [] P. Hll Q. L d J. Rce (7) Noprmerc esmo of regresso fucos he presece of rrelev regressors The Reve Ecoomcs d Sscs vol. (89) pp [] Q. L d J. S. Rce (3) Noprmerc esmo of dsruos h cegorcl d couous d Jourl of Mulvre lss vol. (86) pp [3] Q. L d J. Rce (4) Noprmerc esmo of regresso fucos h oh cegorcl d couous d Jourl of Ecoomercs vol. (9) pp [4] S. C. Hug d T. K. Wu (8) Comg vele-sed feure exrcos h relevce vecor mches for Sock Idex Forecsg Exper Ssems vol. 5 pp [5] U. Lee () Forecsg flo for flo-rgeed coures: comprso of he predcve performce of lerve flo forecsg models usess & Ecoomc Sudes vol. 8 pp [6]. G. Sh S. S. Prk d D. S. Jg(9) comprso of forecsg he dex of he kore sock mrke Compuol Mehods Scece d Egeerg dvces Compuol Scece vol. pp ppedx Texle Prce Idex(-) Texle Prce Idex(-) Cosumer Prce Idex Producer Prce Idex

10 98 JINGHUI HE ND ING XU