Stock Market Development And Economic Growth

Transcription

1 Amercan Journal of Appled Scences 6 (): 93-94, 9 ISSN Scence Publcaons Sock Marke Developmen And Economc Growh Ahanasos Vazakds and Anonos Adamopoulos Deparmen of Appled Informacs, Unversy of Macedona, 56 Egnaas Sree, P.O. Box 59, 54 6, Thessalonk, Greece Absrac: Problem saemen:ths sudy nvesgaed he causal relaonshp beween sock marke developmen and economc growh for France for he perod usng a Vecor Error Correcon Model (VECM). Quesons were rased wheher sock marke developmen causes economc growh or reversely akng no accoun he negave effec of neres rae. Sock marke developmen s esmaed by he general sock marke ndex. The objecve of hs sudy was o examne he causal relaonshps beween hese varables usng Granger causaly ess based on a Vecor Error Correcon Model (VECM). Approach: To acheve hs objecve un roo ess were carred ou for all me seres daa n her levels and her frs dfferences. Johansen co-negraon analyss was appled o examne wheher he varables are co-negraed of he same order akng no accoun he maxmum egenvalues and race sascs ess. A vecor error correcon model was seleced o nvesgae he long-run relaonshp beween sock marke developmen and economc growh. Fnally, Granger causaly es was appled n order o fnd he drecon of causaly beween he examned varables of he esmaed model. Resuls: A shor-run ncrease economc growh of per % leaded o an ncrease of sock marke ndex per.4% n France, whle an ncrease of neres rae per % leaded o a decrease of sock marke ndex per.64% n France. The esmaed coeffcen of error correcon erm found sascally sgnfcan wh a negave sgn, whch confrmed ha here was no any problem n he long-run equlbrum beween he examned varables. The resuls of Granger causaly ess ndcaed ha economc growh causes sock marke developmen n France. Concluson: Therefore, can be nferred ha economc growh has a posve effec on sock marke developmen, whle neres rae has a negave effec on sock marke developmen n France. Key words: Sock marke developmen, economc growh, granger causaly INTRODUCTION The relaonshp beween economc growh and sock marke developmen has been he subjec of nensve heorecal and emprcal sudes. The queson s wheher sock marke developmen causes economc growh or reversely. The man objecve of hs sudy was o nvesgae he causal relaonshp beween economc growh and sock marke developmen akng no accoun he negave effec of neres rae. Sock marke developmen has played a crucal role n some economes n promong economc growh [,]. Sock markes conrbue o he moblzaon of domesc savngs by enhancng he se of fnancal nsrumens avalable o savers o dversfy her porfolos. In dong so hey provde an mporan source Effcen sock markes provde gudelnes as a mean o keep approprae moneary polcy hrough he ssuance and repurchase of governmen secures n he lqud marke, whch s an mporan sep owards fnancal lberalzaon. Smlarly, well-organzed and acve sock markes could modfy he paern of demand for money and would help creae lqudy ha evenually enhances economc growh [3]. A well funconng and lqud sock marke, ha allows nvesors o dversfy away unsysemac rsk, wll ncrease he margnal producvy of capal [4]. Anoher mporan aspec hrough whch sock marke developmen may nfluence economc growh s rsk dversfcaon. Obsfeld [5] suggess ha nernaonal rsk sharng hrough nernaonally negraed sock markes mproves he allocaon of of nvesmen capal a relavely low cos. Correspondng Auhor: Ahanasos Vazakds, Deparmen of Appled Informacs, Unversy of Macedona, 56 Egnaas Sree, P.O. Box 59, 54 6, Thessalonk, Greece 93

2 resources and acceleraes he process of economc growh. In he models of Levne [6], Bencvenga and Smh [7] and San-Paul [8] sock markes mprove frm effcency by elmnang he premaure lqudaon of frm capal, enhancng he qualy of nvesmens and herefore ncreasng enhance economc growh. Enhanced sock marke lqudy reduces he dsncenves for nvesng n long-duraon and hgher-reurn projecs, snce nvesors can easly sell her sake n he projec before maures and s expeced o boos producvy growh [9]. Durng lqudy shocks, nvesors can sell her shares o anoher agen. Sock markes may also promoe growh by ncreasng he proporon of resources allocaed o frms. Through he dversfcaon of producvy rsk, even rsk-averse nvesors can nves n frms. Porfolo dversfcaon, hrough he sock marke, may have an addonal growh effec by encouragng specalzaon of producon [8]. The model hypohess predcs ha economc growh faclaes sock marke developmen akng no accoun he negave effec of neres rae on sock marke developmen and economc growh. Ths sudy has wo objecves: To examne he long run relaonshp among economc growh, neres rae and sock marke developmen To apply Granger causaly es based on a vecor error correcon model n order o examne he causal relaonshps beween he examned varables akng no accoun Johansen co-negraon analyss Am. J. Appled Sc., 6 (): 93-94, 9 adoped o esmae he effecs of economc growh and neres rae on sock marke developmen. The use of hs mehodology predcs he cumulave effecs akng no accoun he dynamc response among sock marke developmen and he oher examned varables [, 3]. In order o es he causal relaonshps, he followng mulvarae model s o be esmaed Eq. : LSM = f ( LGDP, LR ) () GDP = The gross domesc produc SM = The general sock marke ndex R = The neres rae L = The symbol of logarhm Followng he emprcal sudy of [] he varable of economc Growh (GDP) s measured by he rae of change of real GDP. The general sock marke ndex s used as a proxy for he sock marke developmen. The general Sock Marke ndex (SM) expresses beer he sock exchange marke akng no accoun he effec of neres Rae (R) [, 4-6]. The daa ha are used n hs analyss are annual coverng he perod for France, regardng as a base year and are obaned from nernaonal fnancal sascs yearbook [7]. All daa are expressed n her logarhms n order o nclude he prolferave effec of me seres and are symbolzed wh he leer L precedng each varable name. The economerc compuer sofware Evews 5. s used for he esmaon of he model. Un Roo Tess: For unvarae me seres analyss The remander of he sudy proceeds as follows: nvolvng sochasc rends, Phllps-Perron (PP) and Inally he daa and he specfcaon of he mulvarae Kwakowsk e al. [] (KPSS) un roo ess are calculaed VAR model are descrbed. For hs purpose saonary for ndvdual seres o provde evdence as o wheher he es and Johansen co-negraon analyss are examned varables are negraed. Ths s followed by a mulvarae akng no accoun he esmaon of vecor error co-negraon analyss. correcon model. Phllps and Perron (PP) [8] es s an exenson of he Fnally, Granger causaly es s appled n order o Dckey-Fuller (DF) es [9], whch makes he semparamerc correcon for auocorrelaon and s more fnd he drecon of causaly beween he examned robus n he case of weakly auocorrelaon and varables of he esmaed model. The emprcal resuls heeroskedasc regresson resduals. Accordng o Cho [], are presened analycally and some dscusson ssues he Phllps-Perron es appears o be more powerful han resuled from hs emprcal sudy are developed he ADF es for he aggregae daa. shorly, whle he fnal conclusons are summarzed Alhough he Phllps-Perron (PP) es gves relavely. dfferen lag profles for he examned varables (me seres) and somemes n lower levels of sgnfcance, MATERIALS AND METHODS he man concluson s qualavely he same as repored by he Dckey-Fuller (DF) es. Snce he null Daa and Specfcaon Model: In hs sudy he hypohess n he Augmened Dckey-Fuller es s ha mehod of Vecor Auoregressve Model (VAR) s a me seres conans a un roo, hs hypohess s 933

3 acceped unless here s srong evdence agans. However, hs approach may have low power agans saonary near un roo processes. The Phllps-Perron as ced n Laopods and Sawhney [35] un roo es s very general and can be used n he presence of heeroscedasc and auocorrelaed nnovaons s specfed as follows Eq. : -T ln( + r) = α + β + δ ln( + r ) + ζ - Am. J. Appled Sc., 6 (): 93-94, 9 () For =,,..,T where r denoes neres rae a me, (-T/) s a me rend and T s he sample sze. Equaon Tess Three Hypoheses: The frs hypohess s ha he seres conans a un roo wh a drf wh a drf and a me rend: H : δ =. The second hypohess s ha he seres conans a un roo bu whou a me rend: H :β =, δ =. The hrd hypohess s ha he seres conans a un roo bu 3 whou a drf or a me rend: H : a =, β =, δ =. The sascs ha are used o es each hypohess are Z( δ ), Z(Φ ), Z(Φ 3 ), respecvely and her correspondng equaons are as follows as ced n Laopods and Sawhney [35] Eq. a-e: σ ( Τl ) 3 Z( δ ) = σ σ -σ / / σ Tl 3 4D xxσ Tl Τ σ Z( Φ 3) = Φ 3 ( στl σ ) σtl στl 6 Τ T( δ ) σ σ 48D xx ( Τl ) σ Z( Φ ) = Φ ( σ Τl σ ) σ Tl 3σ Τl Τ σ Φ = 6 Τ T( δ ) σ σ 48D xx ( ( ) ) r-r σ - 3 σ ( ) Τ σ σ Φ = 3σ ( Τl ) (a) (b) (c) (d) (e) And σ s he OLS resdual varance, σ s he varance under he parcular hypohess for he sandard -es for δ =. D xx s he deermnan of he (X'X), where X s he T 3 marx of explanaory varables n Eq.. Fnally, σ Τl s a conssen esmaor of he varance of ζ and s compued as follows Eq. f: defned as: 934 T ( ( ) T s / l + ) ζζ s ζ = = s= (f) σ = + Τl = T T where, s and l are he lag runcaon numbers and s<l. The esmaor σ Tl s conssen under general condons because allows for effecs of serally correlaed and heerogeneously dsrbued nnovaons. The hree sascs are evaluaed under varous lags (l = o ). Followng he sudy of Chang [36], Kwakowsk e al. [] presen a es where he null hypohess saes ha he seres s saonary. The KPSS es complemens he Augmened Dckey-Fuller es n ha concerns regardng he power of eher es can be addressed by comparng he sgnfcance of sascs from boh ess. A saonary seres has sgnfcan Augmened Dckey-Fuller sascs and nsgnfcan KPSS sascs. Accordng o Kwakowsk e al. [], he es of ΚPSS assumes ha a me seres can be composed no hree componens, a deermnsc me rend, a random walk and a saonary error Eq. 3: y = δ + r + ε (3) where, r s a random walk r = r - + u The u s d (, σ u ). The saonary hypohess mples ha σ u =. Under he null, y, s saonary around a consan (δ = ) or rend-saonary (δ ). In pracce, one smply runs a regresson of y over a consan (n he case of levelsaonary) ore a consan plus a me rend (n he case of rend-saonary). Usng he resduals, e, from hs regresson, one compues he LM sasc Eq. 3a-d: T ε = LM = T S / S (3a) where, S ε s he esmae of varance of ε : (3b) = S = e, =,, T The dsrbuon of LM s non-sandard: he es s an upper al es and lmng values are provded by Kwakowsk [], va Mone Carlo smulaon. To allow weaker assumpons abou he behavour of ε, one can rely, followng Phllps [] on he Newey [3] esmae of he long-run varance of ε whch s

4 Am. J. Appled Sc., 6 (): 93-94, 9 T l T = + k = s= = s+ (3c) S (l) T e T w(s,l) e e where, w(s,l) = - s / (l+). In hs case he es becomes: T = ν = T S / S (l) (3d) Whch s he one consdered here. Obvously he value of he es wll depend upon he choce of he lag runcaon parameer, l. Here we use he sample auocorrelaon funcon of e o deermne he maxmum value of he lag lengh l. The KPSS sasc ess for a relave lagruncaon parameer (l), n accordance wh he defaul Barle kernel esmaon mehod (snce s unknown how many lagged resduals should be used o consruc a conssen esmaor of he resdual varance), rejecs he null hypohess n he levels of he examned varables for he relave lag-runcaon parameer (l). Therefore he combned resuls (PP, KPSS) from all ess can be characerzed as negraed of order one, I(). The economerc sofware Evews whch s used o conduc he PP, KPSS ess, repors he smulaed crcal values based on response surfaces. The resuls of he Phllps and Perron [8] and Kwakowsk e al. [] for each varable appear n Table. If he me seres (varables) are non-saonary n her levels, hey can be negraed wh negraon of order, when her frs dfferences are saonary. wo or more varables o crcumven he problems assocaed wh he radonal regresson mehods used n prevous sudes on hs ssue. Therefore, he Johansen mehod apples he maxmum lkelhood procedure o deermne he presence of co-negraed vecors n nonsaonary me seres. Accordng o Chang and Caudll [37], Johansen [7] and Oserwald-Lenum [8] propose wo es sascs for esng he number of co-negraed vecors (or he rank of Π): The race (λ race ) and he maxmum egenvalue (λ max ) sascs. The Lkelhood Rao sasc (LR) for he race es (λ race ) as suggesed by [7] s Eq. 4: p λ r = T ln( λ ) race ( ) ˆλ = r+ (4) = The larges esmaed value of h characersc roo (egenvalue) obaned from he esmaed Π marx R =,,, p- T = The number of usable observaons The λ race sasc ess he null hypohess ha he number of dsnc characersc roos s less han or equal o r, (where r s,, or ) agans he general alernave. In hs sasc λ race wll be small when he values of he characersc roos are closer o zero (and s value wll be large n relaon o he values of he characersc roos whch are furher from zero). Alernavely, he maxmum egenvalue (λ max ) sasc as suggesed by Johansen s Eq. 5: ( ) Johansen co-inegraon Analyss: Snce has been deermned ha he varables under examnaon are λ max r, r + = T ln( λ r+ ) (5) negraed of order, hen he co-negraed es s The λ max sasc ess he null hypohess ha he performed. The esng hypohess s he null of non-conegraon number of r co-negraed vecors s r agans he agans he alernave ha s he exsence alernave of (r+) co-negraed vecors. Thus, he null of co-negraed usng he Johansen maxmum hypohess r = s esed agans he alernave ha r = lkelhood procedure [4, 5]., r = agans he alernave r = and so forh. If he Followng he sudy of Chang and Caudll [37], esmaed value of he characersc roo s close o zero, hen he λ οnce a un roo has been confrmed for a daa seres, max wll be small. I s well known ha Johansen s co-negraon he queson s wheher here exss a long-run ess are very sensve o he choce of lag lengh. equlbrum relaonshp among varables. Accordng Frsly, a VAR model s fed o he me seres daa o [6], a se of varables, Y s sad o be co-negraed n order o fnd an approprae lag srucure. The of order (d, b)-denoed CI(d, b)-f Y s negraed of Schwarz Creron (SC) [9] and he Lkelhood Rao order d and here exss a vecor, β, such ha β Y s (LR) es are used o selec he number of lags negraed of order (d-b). requred n he co-negraon es. The Schwarz Co-negraon ess n hs sudy are conduced Creron (SC) and he Lkelhood Rao (LR) es usng he mehod developed by [4, 7]. The mulvarae suggesed ha he value p = 3 s he approprae [4, 5] co-negraon echnques developed by usng a specfcaon for he order of VAR model for France. maxmum lkelhood esmaon procedure allows Table shows he resuls from he Johansen conegraon researchers o esmae smulaneously models nvolvng es. 935

5 Am. J. Appled Sc., 6 (): 93-94, 9 Table : PP, KPSS un roo ess PP_ es sa KPSS es sa Varables Z(Φ 3) Z(Φ ) Z( δ) h c h In levels LSM -.9* **,*. (for k = ) (for k = ) (for k = ) (for l = 6) (for l = 4) LGDP -5.76***,**,* -4.39***,**,* **,*.**,* (for k = ) (for k = 4) (for k = 3) (for l = 6) (for l = 5) LR *,.**,* (for k = ) (for k = ) (for k = ) (for l = 5) (for l = 5) In rs dfferences LSM ***,**,*.***,** (for k = ) (for k = ) (for k = ) (for l = ) (for l = 9) LGDP -.5*** -3.3*** ***,** (for k = 7) (for k = 9) (for k = ) (for l = 5) (for l = ) LR ***.**,* (for k = ) (for k = ) (for k = ) (for l = 5) (for l = 7) Z(Φ 3), Z(Φ ), Z( δ): The PP sascs; h c and h : The KPSS sascs; k, l = bandwdh lenghs: Newey-Wes usng Barle kernel; The crcal values a, 5 and % are -.6, -.94, -.6, for Z(Φ 3), -3.59, -.93, -.6 for Z(Φ ) and for -4.9, -3.5, -3.9 for Z( δ), respecvely. The crcal values a, 5 and % are.73,.46 and.34 for h c and.,.4 and. for h respecvely (Kwakowsk e al. [] Table ). ***, **, *: Indcae ha hose values are no conssen wh relave hypoheses a he, 5 and % levels of sgnfcance relavely Table : Johansen co-negraon ess (LSM, LGDP, LR) Johansen es sascs Tesng Crcal value Crcal value Hypohess λ race.5 [prob]** λ max.5 [prob]** None* [.] [.] A mos.9.3 [.] [.9] A mos [.] [.] Trace es and maxmum egenvalue ess ndcae co-negrang eqn(s) a he.5 level. *: Denoes rejecon of he hypohess a he.5 level; **: MacKnnon-Haug-Mchels [34] p-values Vecor Error Correcon Model: Snce he varables ncluded n he VAR model are found o be conegraed, he nex sep s o specfy and esmae a Vecor Error Correcon Model (VECM) ncludng he error correcon erm o nvesgae dynamc behavor of he model. Once he equlbrum condons are mposed, he VEC model descrbes how he examned model s adjusng n each me perod owards s longrun equlbrum sae. Followng he sudy of Chang and Caudll [37], snce he varables are supposed o be co-negraed, hen n he shor run, devaons from hs long-run equlbrum wll feed back on he changes n he dependen varables n order o force her movemens owards he long-run equlbrum sae. Hence, he co-negraed vecors from whch he error correcon erms are derved are each ndcang an ndependen drecon where a sable meanngful long-run equlbrum sae exss. The VEC specfcaon forces he long-run behavor of he endogenous varables o converge o her co-negraed relaonshps, whle accommodaes shor-run dynamcs. The dynamc specfcaon of he model allows he deleon of he nsgnfcan varables, whle he error correcon erm s reaned. The sze of he error correcon erm ndcaes he speed of adjusmen of any dsequlbrum owards a long-run equlbrum sae [3]. The error-correcon model wh he compued -values of he regresson coeffcens n parenheses s repored n Table 3. The fnal form of he Error-Correcon Model (ECM) was seleced accordng o he approach suggesed by Hendry [3]. The general form of he Vecor Error Correcon Model (VECM) s he followng one Eq. 6: relaonshp [6]. 936 n LSM = β LSM + β LGDP + - n β LR + λ EC + ε 3 n (6) = The frs dfference operaor EC - = The error correcon erm lagged one perod λ = The shor-run coeffcen of he error correcon erm (-<λ<) = The whe nose erm ε Granger Causaly Tess: Granger causaly s used for esng he long-run relaonshp beween fnancal developmen and economc growh. The Granger procedure s seleced because consss he more powerful and smpler way of esng causal

6 Am. J. Appled Sc., 6 (): 93-94, 9 Table 3: Vecor error correcon model LGDP LSM LSM = LR --. ec - (.8) (.) (.83) (-.79) (-.6) [.85] [.8] [.4] [.8] [.4] R =.3 DW =.96 Noes: [ ]: I denoe he probably levels; : Denoes he frs dfferences of he varables; R : Coeffcen of deermnaon; DW: Durbn-Wason sasc Table 4: Parwse Granger causaly ess Counry: France Sample: Lags: Null hypohess: F-Sa [Prob Causal relaon LGDP does no granger cause LSM 6.9 [.] LGDP LSM LSM does no granger cause LGDP.98 [.383] LR does no granger cause LSM 4.3 [.] LGDP LSM LSM does no granger cause LR 5.66 [.7] LR does no granger cause LGDP.8 [.833] LGDP LR LGDP does no granger cause LR 6.37 [.4] The followng bvarae model s esmaed Eq. 7 and 8: k Y = a + a Y + b X + u j j j j j= j= k (7) k X = a + a X + b Y + u j j j j j= j= k (8) Y = The dependen X = The explanaory varable u = A zero mean whe nose error erm n Eq. 7 whle X = The dependen Y = The explanaory varable n Eq. 8 In order o es he above hypoheses he usual Wald F-sasc es s ulzed, whch has he followng form: q = The lag lengh The hypoheses n hs es are he followng Eq. 9 and : H : X does no Granger cause Y,.e., a { α, α,... α } =,f F < crcal value of F k c H : X does Granger cause Y,.e., And: { α, α,. α },f F > crcal value of F k c H : Y does no Granger cause X,.e., a { β, β,... β } =,f F < crcal value of F k c H : Y does Granger cause X,.e., [3, 33] (9) { β, β,. βk}, f F c > crcal value of F () The resuls relaed o he exsence of Granger causal relaonshps among economc growh, sock marke developmen, cred marke developmen and producvy appear n Table 4. (RSSR RSS U) / q F = RSS / (T q ) U RSS U = The sum of squared resduals from he complee (unresrced) equaon RSS R = The sum of squared resduals from he equaon under he assumpon ha a se of varables s redundan, when he resrcons are mposed, (resrced equaon) T = The sample sze RESULTS The observed -sascs fal o rejec he null hypohess of he presence of a un roo for all varables n her levels confrmng ha hey are non-saonary a 5% levels of sgnfcance (Table ). However, he resuls of he PP and KPSS ess show ha he null hypohess of he presence of a un roo s rejeced for all varables when hey are ransformed no her frs dfferences (Table ). Therefore, all seres ha are used for he esmaon are non-saonary n her levels, bu saonary and negraed of order one I(), n her frs 937

7 dfferences. These varables can be co-negraed as well, f here are one or more lnear combnaons among he varables ha are saonary. The number of sascally sgnfcan conegraed vecors for France s equal o (Table ) and s he followng Eq. : LSM =.644 * LGDP.4645* LR () The co-negraon vecor of he model of France has rank r<n (n = 3). The process of esmang he rank r s relaed wh he assessmen of egenvalues, whch are he followng for France: λ =.44 Am. J. Appled Sc., 6 (): 93-94, 9, λ =.7, λ 3 =.6, (Table ). For France, crcal values for he race sasc defned by Eq. 4 are 34.9 for none conegrang vecors and.9 for a mos one vecor,.65 for a mos wo vecors a he.5 level of sgnfcance as repored by [34], whle crcal values for he maxmum egenvalue es sasc defned by Eq. 5 are 3.89 for none co-negrang vecors, 7.64 for a mos one vecor and.65 for a mos wo vecors respecvely (Table ). Then an error-correcon model wh he compued -values of he regresson coeffcens n parenheses s esmaed. The dynamc specfcaon of he model allows he deleon of he nsgnfcan varables, whle he error correcon erm s reaned. A shor-run ncrease of economc growh per % nduces an ncrease of sock marke ndex per.% n France, whle an ncrease of neres rae per % nduces an decrease of sock marke ndex per.6% n France The esmaed coeffcen of EC - s sascally sgnfcan and has a negave sgn, whch confrms ha here s no any a problem n he long-run equlbrum relaon beween he ndependen and dependen varables n 5% level of sgnfcance, bu s relavely value (-.) for France shows a sasfacory rae of convergence o he equlbrum sae per perod (Table 3). Accordng o Granger causaly ess here s a undreconal causal relaonshp beween economc growh and sock marke developmen wh drecon from economc growh o sock marke developmen, a blaeral causaly beween neres rae and sock marke developmen and fnally a undreconal causal relaonshp beween economc growh and neres rae wh drecon from economc growh o neres rae (Table 4). DISCUSSION ndex. The sgnfcance of he emprcal resuls s dependen on he varables under esmaon. Mos emprcal sudes examne he relaonshp beween economc growh and sock marke developmen usng dfferen esmaon measures. The mos represenave esmaon measures for sock marke developmen are he general sock marke ndex and sock marke capalzaon or sock marke lqudy. The general sock marke ndex expresses he rend of sock marke developmen n conjuncon wh he nvesmen growh and he low neres rae. Theory provdes conflcng aspecs for he mpac of sock marke developmen on economc growh or reversely. Less emprcal sudes have concenraed on examnng he reverse relaonshp beween economc growh and sock marke developmen akng no accoun he effec of neres rae. Sock markes gve lenders mmedae access o her funds whle smulaneously offerng borrowers a long-erm supply of capal. By faclang dversfycaon, fnancal nermedares allow he economy o nves relavely more n he rsky producve echnology. Whou sock markes, nvesors facng lqudy shocks are forced o whdraw funds nvesed n long-erm nvesmen projecs. Invesors also wan o dversfy producvy rsk assocaed wh ndvdual nvesmen projecs. Ths spurs economc growh. The resuls of hs sudy are agreed wh he sudes of [] and [3]. The drecon of causal relaonshp beween sock marke developmen and economc growh s regarded as an mporan ssue under consderaon n fuure emprcal sudes. However, more neres should be focused on he comparave analyss of emprcal resuls for he res of European Unon members-saes. CONCLUSION Ths sudy employs wh he relaonshp beween sock marke developmen and economc growh for France, usng annually daa for he perod For unvarae me seres analyss nvolvng sochasc rends, Phllps-Perron (PP) and Kwakowsk e al. [] (KPSS) un roo ess are calculaed for ndvdual seres o provde evdence as o wheher he varables are negraed. The emprcal analyss suggesed ha he varables ha deermne sock marke developmen presen a un roo. Therefore, all seres are saonary and negraed of order one I(), n her frs dfferences. Snce has been deermned ha he varables under examnaon The model of sock marke developmen s manly characerzed by he effec of economc growh and neres rae. Sock marke developmen s deermned by he rend of general sock marke are saonary and negraed of order, hen he 938

8 Johansen co-negraon analyss s performed akng no accoun he maxmum lkelhood procedure. The shor run dynamcs of he model s suded by analyzng how each varable n a co-negraed sysem responds or correcs self o he resdual or error from he co-negrang vecor. Ths jusfes he use of he erm error correcon mechansm. The Error Correcon (EC) erm, pcks up he speed of adjusmen of each varable n response o a devaon from he seady sae equlbrum. The dynamc specfcaon of he model suggess deleon of he nsgnfcan varables whle he error correcon erm s reaned. The VEC specfcaon forces he long-run behavour of he endogenous varables o converge o her conegrang relaon-shps, whle accommodaes he shor-run dynamcs. A shor-run ncrease of economc growh per % leaded o an ncrease of sock marke ndex per.4% n France, whle an ncrease of neres rae per % leaded o a decrease of sock marke ndex per.64% n France. Furhermore, Granger causaly ess ndcaed ha economc growh causes sock marke developmen and neres rae, whle here s a blaeral causaly beween sock marke developmen and neres rae for France. Therefore, can be nferred ha economc growh has a posve effec on sock marke developmen akng no accoun he negave effec of neres rae on sock marke developmen and economc growh. REFERENCES. Demrguc-Kun, A. and R. Levne, 996. Sock markes corporae fnance and economc growh. World B. Econ. Rev., : 3-4. hp://wber.oxfordjournals.org/cg/reprn///3.pdf. Levne, R. and S. Zervos, 998. Sock markes, banks and economc growh. Am. Econ. Rev., 88: hp://deas.repec.org/a/aea/aecrev/v88y9983p hml 3. Caporale, G., A. Cpolln and P. Demerades, 5. Moneary polcy and he exchange rae durng he Asan crss: Idenfcaon hrough heeroscedascy. J. In. M. Fnance, 4: hp://deas.repec.org/p/lec/leecon/-.hml 4. Pagano, M., 993. Fnancal markes and growh: An overvew. Eur. Econ. Rev., 37: hp://deas.repec.org/a/eee/eecrev/v37y993-3p63-6.hml 5. Obsfeld, M., 994. Rsk-akng, global dversfcaon and growh. Am. Econ. Rev., 84: hp://deas.repec.org/a/aea/aecrev/v84y9945p3-9.hml Am. J. Appled Sc., 6 (): 93-94, Levne, R., 99. Sock markes, growh and ax polcy. J. Fnance, 46: hp://deas.repec.org/a/bla/jfnan/v46y994p hml 7. Bencvenga, V., B. Smh and R. Sarr, 996. Equy markes, ransacon coss and capal accumulaon: An llusraon. World B. Econ. Rev., : hp://deas.repec.org/a/oup/wbecrv/vy996p 4-65.hml 8. San-Paul, G., 99. Technologcal choce, fnancal markes and economc developmen. Eur. Econ. Rev., 36: hp://deas.repec.org/a/eee/eecrev/v36y994p hml 9. Bencvenga, V. and B. Smh, 99. Fnancal nermedaon and endogenous growh. Rev. Econ. Sud., 58: hp://deas.repec.org/a/bla/resud/v58y99p95-9.hml. Κaos, Α., G. Pekos, E. Kasoul and C. Bazos, 996. Savng-nvesmen equlbrum n he European Unon: An economc polcy exercse. Rv. In. Sc. Econ. Com., 43: 8-7. hp:// po=scheda&codce=6. Kng, R. and R. Levne, 993. Fnance and growh: Schumpeer mgh be rgh. Q. J. Econ., 8: hp://deas.repec.org/a/pr/qjecon/v8y9933p hml. Levne, R., N. Loyaza and T. Beck,. Fnancal nermedaon and growh: Causaly and causes. J. Moneary Econ., 46: hp://deas.repec.org/a/eee/moneco/v46yp3-77.hml 3. Shan, J., 5. Does fnancal developmen lead economc growh? A vecor auo-regresson apprasal. Appled Econ., 37: hp://deas.repec.org/a/af/applec/v37y5p hml 4. Neuwerburgh, S., F. Buelens and L. Cuyvers, 6. Sock marke developmen and economc growh n Belgum. Explor. Econ. Hsory, 43: DOI:.6/j.eeh Kng, R. and R. Levne, 993. Fnance and growh: Schumpeer mgh be rgh. Q. J. Econ., 8: hp://deas.repec.org/a/pr/qjecon/v8y9933p hml 6. Vazakds, A., 6. Tesng smple versus Dmson marke models: The case of Ahens Sock Exchange. In. Res. J. Fnance Econ., : hp:// Vazakds.pdf

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