Journal of Chemical and Pharmaceutical Research, 2014, 6(5): Research Article

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Avalable onlne www.jocpr.com Journal of Chemcal and Pharmaceucal Research, 04, 6(5):830-836 Research Arcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 Emprcal analyss for he mpac of RMB real effecve exchange rae on foregn drec nvesmen n Chna Wenrong Pan * and Yu Song Jangx Unversy of Fnance and Economcs School of Sascs, Nanchang, Chna ABSTRACT In hs paper, from he perspecve of RMB exchange rae reform, he mpac s suded of RMB real effecve exchange rae on FDI (Foregn Drec Invesmen) n Chna from January 997 o December 03. In he long run, here s an equlbrum relaonshp beween RMB real effecve exchange rae and FDI. The mpac of RMB real effecve exchange rae on FDI was no affeced unl he promulgaon of he reform polcy from July 005. Tha s, only afer he reform, RMB exchange rae had a sgnfcan Granger causaly on FDI and he apprecaon of RMB can promoe FDI nflow. Key words: Exchange rae reform; RMB real effecve exchange rae; FDI INTRODUCTION Chna began o arac FDI from he begnnng of 970s. Wh he furher developmen of reform and openng, he FDI acually ulzed has been ncreasng connually and rsen from 9. bllon US dollars n 983 o.76 rllon US dollars n 03 (Naonal Bureau of Sascs n Chna). To say he leas, FDI has played an mporan role n promong economc growh n Chna. On one hand, FDI allows for a more effcen allocaon of resources for he nvesng frm n he home counry; on he oher hand, he hos counry can benef from nowledge ransfers and spllovers as well as ncng compeon and ncreased producvy []. As FDI s n he caegory of nernaonal capal, exchangng s ndspensable beween dfferen currences n he process of nernaonal capal flows []. In recen years, wh he expandng of global FDI scale and an ncreasng number of counres mplemenng he floang exchange rae polcy, he mpac of exchange rae on FDI has araced more and more aenon from researchers and polcymaers. Alhough a lo of wor has been done n he area of exchange rae movemens and FDI, here s sll no consensus eher n heory or emprcal sudes. Mos researchers beleve ha he currency apprecaon n he hos counry s no conducve o he flow of FDI and he deprecaon can promoe FDI nflow. In he heores of Kohlhagen (977) and Cushman (988), he deprecaon of hos-counry currency can reduce he producon cos and ransnaonal merger and acquson cos, and hus smulae FDI. On he assumpon of mperfec capal mares, Froo and Sen (99) develop a model and show ha he deprecaon of hos-counry currency, by sysemacally lowerng he relave wealh of domesc agens, can lead o he ncrease of FDI acquson. A smlar heorecal resul comes from Blongen (997) who plausbly shows how he real currency deprecaon n he recevng counry ncreases FDI acquson o hs counry. Emprcal evdence n a number of sudes has revealed he correcness of he above-menoned heores [3-9]. By conras, Campa (993) derves, under Dx s (989) real opons framewor, a negave effec of real hos-counry currency deprecaon on FDI [0]. He beleves ha he mulnaonal corporaon s overseas nvesmen decson depends on s fuure earnngs expecaon. The sronger he currency of a counry s, he hgher he fuure earnngs expecaon s, and hus more FDI can be araced. A number of emprcal evdence has 830

Wenrong Pan and Yu Song J. Chem. Pharm. Res., 04, 6(5):830-836 confrmed he predcon [-3]. Unle oher people, Hymer (960) nsss n hs heory based on he perfec capal mares ha he mpac of exchange rae on FDI s no sgnfcan [4]. Emprcal fndng from Trevno e al. (00) shows ha he domesc producon scale, he degree of marezaon and he consumer prce ndex (CPI) are he mporan facors of FDI; whereas he exchange rae s no [5]. Smlar resuls can be found n Dewener (995) and Pan (003) [6-7]. However, none of sudes ncludng Benassy-Quere e al. (00) and Chen e al.(006) are able o denfy a sascally sgnfcan effec of hos-counry currency valuaon on FDI [8-9]. There are wo possble reasons for he resuls n he sudes above. Frs, he mpac of exchange raes on FDI s dfferen for dfferen ndusres, whch s verfed by Froo and Sen (99) n emprcal evdence. So he analyss based on aggregae daa s probably o resul n aggregaon bas. Second, he macro and mcro economc envronmens n many counres change over me, and hey more or less nfluence he effec of exchange rae on FDI. For nsance, Jeannere (005) pons ou ha he mulnaonal corporaon can, wh he developmen of world s fnancal dervave nsrumens, compleely allocae he asses reasonably all over he world o avod he rs of exchange rae change [0]. In hs paper, we conduced emprcal sascal analyses on he mpac of RMB real effecve exchange rae on FDI n Chna. As we all now, RMB exchange rae has been adjusng snce he reform and openng. In 98, Chna sared o mplemen a dual exchange rae polcy. The nex managed floang exchange rae polcy based on mare supply and demand was esablshed n 994. In 997, he RMB exchange rae was, n order o cope wh he Asan fnancal crss, pegged o he US dollar. Snce July 005, Chna has mplemened he managed floang exchange rae polcy whch s no only based on mare supply and demand bu also referenced o a base of currences. Then we can no help asng, wh he connuous adjusmen of he exchange rae, wheher he mpac of exchange rae on FDI was affeced by he reform of exchange rae polcy? If so, when exacly dd occur? Compared wh oher sudes, here are he followng nnovaons n hs paper. Frs, alhough many scholars a home and abroad suded he mpac of exchange rae on FDI, so far no sudes examnng he change of he mpac can be seen from he perspecve of exchange rae reform. Tha s o say, wh he nroducon of he relaed polcy, he exchange rae behaves dfferenly and he mpac followed on FDI may be dfferen. Because RMB exchange rae has become more elasc snce July 005, we chose he reform polcy as our research objec. Second, wh he promulgaon of he reform polcy, he mpac may be affeced before or afer he reform. Accordngly, Chow breapon es was, whch verfes he change of he mpac, used o denfy when exacly occurred. Las bu no he leas, more or less exss auocorrelaon when esablshng he model of me seres, so we performed Box-Jenns ARMA(p,q) model o elmnae he auocorrelaon n he co-negraon model. EXPERIMENTAL SECTION Tme seres used here are monhly observaons of FDI acually ulzed n Chna and RMB real effecve exchange rae(reer) from January 997 o December 03. RMB real effecve exchange rae s an ndex, whose rse means currency apprecaon and fall means currency deprecaon [3]. We colleced he daa of RMB real effecve exchange rae from he webse of Ban for Inernaonal Selemens www.bs.org/. The daa of FDI acually ulzed was obaned from Chna Economc Informaon Newor sascs daabase. Due o clmae, cusom or oher economcal facors, he monhly economc sascal seres conans seasonal changes. I s hard o clearly undersand he acual changes n he daa, so he seasonal adjusmen should be conduced before he emprcal analyss. The X- seasonal adjusmen mehod was employed. Fg. Plos of FDI (00 Mllon US Dollars) n he Orgnal Scale, n he Adjused Scale and n he Log Scale 83

Wenrong Pan and Yu Song J. Chem. Pharm. Res., 04, 6(5):830-836 Fg. Plos of RMB Real Effecve Exchange Rae n he Orgnal Scale, n he Adjused Scale and n he Log Scale Daa were log-ransformed before modelng o sablze he varably. The plos of FDI me seres n orgnal scale, n adjused scale and n log-scale are shown n Fgure. The me seres for RMB real effecve exchange rae are shown n Fgure. 3. Emprcal Mehods 3. Chow Breapon Tes Chow Breapon Tes s used o examne he sably of he model srucure. Suppose wo subsamples are expressed by n and n, and T = n + n. The mulple regresson model s esablshed as: y = θ 0 + θx + L+ θ x + µ. Then he model can be esmaed wh n and n observaons, respecvely. The null hypohess H s: he regresson coeffcens are correspondngly equal. The es sasc s defned as 0 [ SSET ( SSE + SSE)]/( + ) F = () ( SSE + SSE ) /( T ) Where s he number of ndependen varables; T beng he number of all observaons; SSE, T SSE and SSE beng he hree sum squared resdual of regresson model wh T, n and n observaons, respecvely. Under he confdence probablyα, f F Fα ( +, T ), hen he null hypohess H should be rejeced. Tha s o say, 0 he regresson coeffcens are no correspondngly equal and here s a srucural change n he model. 3. Augmened Dcey-Fuller es In order o avod spurous regresson and ge he vald sascal nference, he es of me seres sably s essenal. Augmened Dcey-Fuller es s he man ool for hs objecve and hus can be used o deermne he un roo order. I can be compleed hrough he followng hree models: X m = δ X + β X + ε m X = α + δx + β X + ε X = α + β + δx + β X + ε m Where X s he me seres beng esed; beng he frs-dfference operaor; beng he me rend; m beng he opmal lag lengh whch s deermned by Aae Informaon Crera (AIC); () (3) (4) ε beng he whe nose dsurbance erm. The null hypohess of ADF un-roo es β = s esed agans he alernave hypohess β <. If he null hypohess s rejeced, hen he me seres X s saonary. 3.3 Co-negraon Tes Engle and Granger (987) noe ha even hough economc me seres mgh be descrbed as a random wal process s possble ha he lnear combnaons of he seres would converge o equlbrum over me []. They proposed 83

Wenrong Pan and Yu Song J. Chem. Pharm. Res., 04, 6(5):830-836 co-negraon models for mulvarae and non-saonary me seres commonly observed n economerc sudes. Usng our wo me seres, a smple co-negraon model n log scale s defned as L ( FDI ) = β + β L( REER ) + ε (5) 0 In expresson (5), FDI s he foregn drec nvesmen n Chna and REER s RMB real effecve exchange rae. In above model, hese wo me seres can be non-saonary, bu he lnear relaonshp (co-negraon) would mae he nnovaons, ε, ndependen and dencally dsrbued. We can perform he ADF es on ε o valdae he model. 3.4 Granger-causaly Tes The co-negraon es ells us wheher a long-run equlbrum exss beween A and B, bu we have no dea abou he drecon beween he wo varables. The Granger-causaly es can be used o solve hs problem. The Granger causaly model s as below: Y = φ + αy + β X + µ X = φ + λ X + δy + µ Where (6) α,δ (7) are he regresson coeffcens for lag lengh of, µ Y ; β, λ beng regresson coeffcens of lag lengh of X ; µ beng he whe noses. In judgng wheher X s he Granger cause for Y, he null hypohess and also he resrced condon s: β = 0, =,.... The es sasc s: ( SSE SSE) / F = (8) SSE /( T ) Where SSE, SSE are he sum squared resdual of regresson equaon by Orgnal Leas Square (OLS) mehod under resrced and unresrced condon, respecvely; T beng he number of observaons of me seres Y ; beng he number of regresson coeffcens β. Under he confdence probablyα, f F > F, hen he null hypohess α should be rejeced. Tha s, X s he Granger cause for Y. In addon o he above menoned mehods, n our analyss, o esmae he parameers β0 and β n model (5), ordnary leas squares (OLS) mehod was used. Furhermore, we performed Box-Jenns ARMA(p,q) model o elmnae he auocorrelaon n model (5) []. Our sascal analyses were carred ou usng Evews 8.0. RESULTS The plos of FDI and RMB real effecve exchange rae ndcae ha he measuremens were all from non-saonary processes n he orgnal scale, n he adjused scale and n he log scale. I s also evden ha rends of hese me seres were more sable n he log-scale (Fgures.-). The resuls from ADF es ell us ha boh of log ransformed FDI and RMB real effecve exchange rae exs un roo a a sgnfcance level 0.05. However, he ADF ess were sgnfcan n he frs dfference, ndcang ha he dfferences of hese wo me seres were saonary (Table.). Table. Resuls from Augmened Dcey-Fuller es Varable ADF Tes AEG (5%) (C,T,N) LFDI -.7 -.88 (C,0,) LFDI -4.7** -.94 (0,0,) LREER -0.7 -.88 (C,0,) LREER -.05** -.94 (0,0,0) Noe: ** denoes ha sascal sgnfcance a 5% level. C represens he nercep,t represens he me rend and N represens he opmal lag lengh. In Table.(a), he Granger causaly of log ransformed RMB real effecve exchange rae on FDI was no sascally sgnfcan. I mgh have resuled from he non-saonary of hese wo me seres. When he ess were j j 833

Wenrong Pan and Yu Song J. Chem. Pharm. Res., 04, 6(5):830-836 conduced on he dfferences of hese wo me seres, we were able o observe sascally sgnfcan resuls a a sgnfcance level 0.. Table. Resuls from Granger Causaly Tes (a) Null Hypohess: F-Sasc P-value LREER does no Granger Cause LFDI 0.958 0.4878 LFDI does no Granger Cause LREER.588 0.44 LREER does no Granger Cause LFDI.9477 0.0646* LFDI does no Granger Cause LREER.6696 0.90 Noe: * denoes ha sascal sgnfcance a 0% level. (b) Tme Inerval Null Hypohess: F-Sasc Jan,997-Jun,005 LREER does no Granger Cause LFDI.0086 LFDI does no Granger Cause LREER 0.8659 Jul,005-Dec,03 LREER does no Granger Cause LFDI 5.400*** LFDI does no Granger Cause LREER.3703 Noe: *** denoes ha sascal sgnfcance a % level. To assess he goodness of f of he co-negraon model (5), we performed he Augmened Dcey-Fuller es on he resdual for co-negraon model of he log ransformed me seres. The es sasc was -.87. We rejeced he null hypohess of un roo for he resdual a a sgnfcance level 0.0. Tha s o say, here s an equlbrum relaonshp beween RMB real effecve exchange rae and FDI n he long run. However, he adjused R = 0. 305 and DW value was 0.3, ndcang ha exss serous auocorrelaon n he nnovaons ε. In order o elmnae he auocorrelaon, we employed ARMA(p, q) model o ε. Fgure 3 ells us ha ε was he second order auocorrelaon. Tha s, ε α + α ε + α + v v s ndependen and dencally dsrbued). As a resul of = 0 ε ( hs adjusmen, he adjused R = 0. 85 and he auocorrelaon was elmnaed (DW value was.0). Accordngly, he model was mproved. Fg. 3 Correlogram of Resduals From Fgure 4 we can see ha F sasc s greaer han he crcal value a a sgnfcance level 0.0, ndcang ha he mpac of RMB real effecve exchange rae on FDI was no affeced unl he promulgaon of he reform polcy from July 005. The resul from Table.(b) llusraes ha only afer he reform, he exchange rae had a sgnfcan Granger causaly on FDI. Before he reform, he esmae of β was no sascally dfferen from zero (p < 0.05) n he mproved model. Afer ha, was sgnfcan a a sgnfcance level 0.0 and β =. 65, ndcang ha FDI would ncrease by.65 log uns for one log un ncrease n RMB real effecve exchange rae. 834

Wenrong Pan and Yu Song J. Chem. Pharm. Res., 04, 6(5):830-836 Fg.4 Resuls from Chow Breapon Tes CONCLUSION In hs paper, we frs appled a co-negraon model o esablsh he lnear relaonshp of RMB real effecve exchange rae and FDI n Chna, and hen employed ARMA(p, q) model o elmnae he auocorrelaon n he co-negraon model. Fnally, Chow breapon es was used o examne wheher he reform of RMB exchange rae polcy from July 005 affecs he mpac of RMB real effecve exchange rae on FDI and when exacly occurred. Our resuls ndcaed ha here s an equlbrum relaonshp beween RMB real effecve exchange rae and FDI n he long run. The mpac of RMB real effecve exchange rae on FDI was no affeced unl he promulgaon of he reform. Only afer he reform, he mpac was sgnfcan and FDI was posvely assocaed wh RMB real effecve exchange rae. Tha s o say, he apprecaon of RMB can promoe FDI nflow, whch s conssen wh he heory of Campa(993). One possble reason why he mpac was no sgnfcan before he reform s ha he exchange rae n Chnese fnancal mare was fxed, wh srong nervenon from Chnese cenral governmen. In oher word, before he reform, RMB exchange rae was under he regulaon of governmen, so as FDI, flowng o he ndusres and regons n erms of governmen drecon. Snce he reform, he exchange rae has become more elasc, and hen he mpac on FDI has become dfferen. Ths sudy may be underpowered due o he sgnfcance level 0. n assessng he Granger causaly of RMB real effecve exchange rae on FDI. I s no surprsng o rejec he null hypohess snce would be beer and more powerful f he es was used o he me seres afer he reform(he Granger causaly was sgnfcan a a sgnfcance level 0.0, Table. (b)). Acnowledgmens The wor descrbed n hs paper was suppored by a gran from he Humanes and Socal Scences Foundaon of he Educaon Commsson of Chna (No. YJA90007) and he Naonal Naural Scence Foundaon of Chna (No. 760). REFERENCES [] Chrsan W. S., & Udo Broll. Revew World Economc. 009, 45: 53-530. [] Sun L. The Research on he Deermnaon of FDI n Terms of RMB Exchange Rae [D]. Bejng: Chna Youh Unversy For Polcal Scences. 0(In Chnese). [3] Cushman D.O. The Revew of Economcs and Sascs. 988, : 3-334. [4] Blongen, Bruce A. Amercan Economc Revew. 997, 87(3): 447 465. [5] Froo K., & Sen C. Quarerly Journal of Economcs.99, 4: 9-7. [6] Kohlhagen, S. W. Souhern Economc Journal. 977, 36: 373-389. [7] Klen M. W., & Rosenge E. S. Journal of Inernaonal Economcs. 994, 36(3): 373-389. [8] Xng Y. Q. Chna Economc Revew. 005, 7: 98-09. [9] Yu J. P. & Zhao J. World Economy Sudy. 007, : 37-4 (In Chnese). [0] Campa M. The Revew of Economcs and Sascs. 993, 4: 64-6. [] MacDermo Raymond. The Inernaonal Trade Journal. 008, : 3-6. [] Yang Y. Journal of Specal Zone Economy. 03, :79-8 (In Chnese). [3] Zhao Q. Analyss of FDI Inflow n Chna n Conex of RMB Exchange Rae Reforms. Economc Problem. 0, : 96-99 (In Chnese). [4] Hymer S. H. Inernaonal Operaon of Naonal Frm: A Sudy of Drec Foregn Invesmen [D]. Cambrdge: Massachuses Insue of Technology, 960. [5] Trevno, L. J., Danels, J. D., & Arbelaez, H. Transnaonal Corporaons. 00, : 9-48. [6] Dewener, K. L. Journal of Busness. 995, 68: 405-433. [7] Pan Y. G. Journal of Busness Research. 003, 56: 89-833. [8] Benassy-Quere, A., Fonaagne, L., & Lahreche-Revl, A. Journal of he Japanese and Inernaonal Economcs. 835

Wenrong Pan and Yu Song J. Chem. Pharm. Res., 04, 6(5):830-836 00, 5:78-98. [9] Chen K. M., Rau H. H. & Ln C. C. The Developng Economes. 006, 9: 69-87. [0] Jeannere A. Does Exchange Rae Volaly Really Depress Foregn Drec Invesmen n OECD Counres? Worng Paper, Inernaonal Cener for Fnancal Asse Managemen and Engneerng. Swzerland: Unversy of Lausanne, 005. [] Engle, R., & Granger, C. W. J. Co-negraon and Error Correcon: Represenaon, Esmaon, Tesng. Economerc. 987, 55: 5-76. [] Box G. E. P., Jenns G. M., & Rensel G. C. Tme Seres Analyss: Forecasng and Conrol. 4h edon. Wley, New Yor, 008. 836