Long-Run Relationship and Causality between Foreign Direct Investment and Growth: Evidence from Ten African Countries

Transcription

1 Inernaonal Journal of Economcs and Fnance Long-Run Relaonshp and Causaly beween Foregn Drec Invesmen and Growh: Evdence from Ten Afrcan Counres Loesse Jacques ESSO Ecole Naonale Supéreure de Sasque e d Econome Applquée (ENSEA), Côe d Ivore Cellule d Analyse de Polques Economques du CIRES (CAPEC), Côe d Ivore Cenre Ivoren de Recherches Economques e Socales (CIRES), Côe d Ivore Tel: , Fax: E-mal: LJ.esso@gmal.com Absrac The am of hs paper s o re-examne he relaonshp beween foregn drec nvesmen and economc growh n he case of en Sub-Saharan Afrcan counres. To hs end, we use wo newly economerc approaches, namely he Pesaran e al. () approach o conegraon and he procedure for non-causaly es of Toda and Yamamoo (995). We use daa from he 8 World Invesmen Repor daase of he UNCTAD, he Afrcan Developmen Bank (8) and he World Bank (8) from 97 o 7. We show ha here s a posve long-run relaonshp beween foregn drec nvesmen and economc growh n Angola, Coe d'ivore, Kenya, Lbera, Senegal and Souh Afrca. However, foregn drec nvesmen sgnfcanly causes economc growh n Angola, Coe d'ivore and Kenya, whle growh causes foregn drec nvesmen n Lbera and Souh Afrca. Keywords: FDI, Growh, Conegraon, Causaly, Sub-Saharan Afrca JEL Classfcaon: C3, F.. Inroducon Foregn drec nvesmen (FDI) n developng counres has ncreased sgnfcanly over he las 5 years. Toal FDI rose from some US $4 bllon n 98, o US $8 bllon n 999, before fallng back o US $5 bllon n 3 (Busse and Hefeker, 7). However, he effors by Sub-Saharan Afrcan counres o arac FDI for growh and developmen are far from adequae. Snce 97, FDI nflows no Sub-Saharan Afrcan counres ncreased modesly. Average nflows o he regon s pu a US$.9 bllon n , US$3. bllon n , US$6. bllon n and o $8.3 bllon n FDI nflows o Sub-Saharan Afrcan counres have dropped from percen n o nne percen n 985, fve percen n and o less han four percen n 996- (Abdulah, 7). Snce mos counres n Sub-Saharan Afrca are recoverng from a long sagnaon afer he mplemenaon of macroeconomc reform programmes, are FDI nflows effecvely mporan o accelerae growh raes o be able o move he majory of her people ou of povery? The role of FDI n he growh process of boh ndusral and developng counres has for long been a opc of nense debae. The relaonshp has been suded by explanng four man channels: () deermnans of growh, () deermnans of FDI, () role of mul-naonal frms n hos counres, and (v) drecon of causaly beween he wo varables. The relaonshp beween FDI and economc growh s one of he hornes areas n he presen debae. There s a wde specrum of vews on FDI from hose who see uncrcally as conrbung o economc growh n all crcumsances o hose, largely from he an-globalsaon movemen, who conclude ha FDI s perncous o naonal developmen. FDI has many effecs, whch vary sgnfcanly by he secor n whch he FDI s made and by he ype of hos counry. A he frm level, several sudes provded evdence of echnologcal spllover and mproved plan producvy. A he macro level, FDI nflows n developng counres end o crowd n oher nvesmen and are assocaed wh an overall ncrease n oal nvesmen. Mos sudes found ha FDI nflows led o hgher per capa GDP, ncrease economc growh rae and hgher producvy growh. As noed by De Mello (997), wo channels have been advanced o explan he posve mpac of FDI on growh. Frs, hrough capal accumulaon n he recpen counry, FDI s expeced o be growh-enhancng by encouragng he ncorporaon of new npus and foregn echnologes n he producon funcon of he recpen economy. Second, hrough echnology ransfer, FDI s expeced o ncrease he exsng sock of knowledge n he recpen economy hrough labour ranng and skll acquson (Borenszen e al., 998; Masromarco and Ghosh, 9), on he one hand and hrough he nroducon of alernave managemen pracces and organzaon arrangemens, on he oher. Essenally, he exen o whch FDI s growh-enhancng depends on he economc and echnologcal condons of he hos counry. For example, Borenszen e al. (998) sugges ha here s a srong complemenary effec beween FDI and human capal, ha s, he conrbuon of FDI o economc growh s enhanced by s neracon wh he 68

2 Inernaonal Journal of Economcs and Fnance Vol., No. ; May level of human capal n he hos counry. Moreover, he magnude of he FDI-growh lnk depends on he degree of complemenary and subsuon beween FDI and domesc nvesmen (De Mello, 999), and depends on nsuonal maers, such as he recpen economy s rade regme, legslaon, polcal sably, urbanzaon rae (Hsao and Shen, 3), ec. However, sudes n he lne of Carcovc and Levne (3) do no lend suppor o he vew ha FDI promoes growh. Moreover, Hanson () has found weak evdence ha FDI generaes posve spllovers for hos counres. Recenly, comprehensve dscussons a he frm level have been provded by Gorg and Greenaway (4). Anoher srand of he leraure has focused more drecly on he causal relaonshps beween FDI and growh. For example, Chowdhury and Mavroas (6) examnes he causal relaonshp beween FDI and economc growh by usng me-seres daa coverng he perod 969- for hree developng counres, namely Chle, Malaysa and Thaland. They follow he Toda and Yamamoo causaly es approach. Ther emprcal fndngs clearly sugges ha GDP causes FDI n he case of Chle and no vce versa, whle for boh Malaysa and Thaland, here s srong evdence of a b-dreconal causaly beween he wo varables. Furhermore, n Hansen and Rand (6), he causal relaonshp beween FDI and GDP s analysed n a sample of 3 developng counres coverng he perod 97-. Ther conclusons regardng he drecon of causaon beween he wo varables seem o vary sgnfcanly dependng on he economerc approach adoped and he sample used. In addon, lookng a me seres on counres, Zhang () evdences srong Granger-causal relaonshp beween FDI and GDP growh. In summary, despe he ruly enormous amoun of research ha has been underaken on FDI here reman serous mehodologcal ssues. Moreover, probably due o relavely small level of foregn drec nvesmen o Afrca, when compared wh oher regons, e.g. Lan Amerca and Asa, no many sudes have been repored on he effecs of FDI on economc growh. The am of hs paper s o conrbue o he emprcal leraure on he relaonshp beween foregn drec nvesmen and economc growh, for en Sub-Saharan Afrcan counres, namely Angola, Cameroon, Congo, Coe d Ivore, Ghana, Kenya, Lbera, Ngera, Senegal and Souh Afrca. To hs end, we employ wo newly nroduced mehods n appled economcs: he Pesaran e al. () approach o conegraon and he Toda and Yamamoo (995) causaly procedure. The Pesaran e al. () approach has a leas wo major advanages over he radonal approaches (Engle and Granger, Johansen) used by a wde range of sudes. The frs advanage s ha s applcable rrespecve of wheher he underlyng regressors are purely saonary, purely negraed or muually conegraed. The second advanage s ha has superor sascal properes n small samples. The bounds es s relavely more effcen n small sample daa szes as s he case n mos emprcal sudes on Afrcan counres. Furhermore, Toda and Yamamoo (995) propose an neresng ye smple procedure requrng he esmaon of an augmened vecor auoregressve (VAR) whch guaranees he asympoc dsrbuon of he Wald sasc, snce he esng procedure s robus o he negraon and conegraon properes of he process. Daa are derved from UNCTAD (8), he Afrcan Developmen Bank (8) and he 8 World Developmen Indcaors of he World Bank (8), and span from 97 o 7. The remander of hs paper s organzed as follows. Secon hghlghs he economerc framework. In he Secon, we presen he man resuls of hs sudy. We fnsh by he concluson.. The economerc framework Ths secon hghlghs he economerc model used o sudy conegraon and causaly beween economc growh and FDI. We use he Pesaran e al. () conegraon approach and he Toda and Yamamoo (995) causaly esng procedure.. Daa and varables Ths paper uses annual me seres daa on en Sub-Saharan Afrcan counres, namely, Angola, Cameroon, Congo, Coe d'ivore, Ghana, Kenya, Lbera, Ngera, Senegal, and Souh Afrca. These Afrcan counres benef large foregn drec nvesmen nflows and are characerzed by hgh levels of he per capa gross domesc produc durng he las wo decades. In addon, hese counres are vewed as havng srong prospecs over he near erm n aracng large volumes of global FDI flows because of a successful mplemenaon of reforms. Tha s why hs sudy focuses on hese en Afrcan counres. The seres comprse yearly observaons beween 97 and 7, namely real gross domesc produc per capa (GDPC) as a measure for economc growh and he rao of foregn drec nvesmen (FDI) nflows o GDP (RFDI). Daa on real GDP per capa and GDP are from he 8 World Developmen Indcaors of he World Bank (8) and from he Seleced 69

3 Inernaonal Journal of Economcs and Fnance Sascs on Afrcan Counres of he Afrcan Developmen Bank (8), and me seres on FDI nflows come from he 8 World Invesmen Repor Daase of he Uned Naons Conference on Trade and Developmen (UNCTAD, 8). Mos Afrcan counres, snce years, depend largely on he expor of commodes lke cocoa, coffee, rubber and mneral resources. However, effors have been made o ncrease economc acvy, ncomes and general welfare. Economc reforms largely been amed a aracng FDI. As par of he mos Afrcan governmens effor o arac FDI, varous polces and nsuonal srucures have been developed n many counres. For nsance, he Srucural Adjusmen Programme has underaken from he md 98s hrough o he early 99s was no jus amed a economc resrucurng bu also promong FDI nflows. Ths sudy res o quanfy he relaonshp beween FDI and growh and examnes wheher FDI s mporan for growh n he en Sub-Saharan Afrcan counres consdered here.. The conegraon approach Economerc leraure proposes dfferen mehodologcal alernaves o emprcally analyse he long-run relaonshps and dynamc neracons beween wo or more me-seres varables. The mos wdely used mehods nclude he wo-sep procedure of Engle and Granger (987) and he full nformaon maxmum lkelhood-based approach due o Johansen (988) and Johansen and Juselus (99). All hese mehods requre ha he varables under nvesgaon are negraed of order one. Ths nevably nvolves a sep of saonary pre-esng, hus nroducng a ceran degree of uncerany no he analyss. In addon, hese ess suffer from low power and do no have good small sample properes (Cheung and La, 993; Harrs, 995). Due o hese problems, hs sudy makes use of a newly developed approach o conegraon ha has become popular n recen years. The bounds esng approach o conegraon was orgnally nroduced by Pesaran and Shn (999) and furher exended by Pesaran e al. (). The bounds esng approach o conegraon has a leas wo major advanages over he Johansen and Juselus (99) approach used by a wde range of sudes (Mash and Mash ; Narayan and Peng, 7). The frs advanage s ha s applcable rrespecve of wheher he underlyng regressors are purely I(), purely I() or muually conegraed. The second advanage s ha has superor sascal properes n small samples. The bounds es s relavely more effcen n small sample daa szes as s he case n mos emprcal sudes on Afrcan counres. Esmaes derved from Johansen-Juselus mehod of conegraon are no robus when subjeced o small sample szes such as ha n he presen sudy. To search for possble long run relaonshps amongs he varables, namely gross domesc produc per capa (GDPC) and he rao of foregn drec nvesmen o GDP, we employ he bounds esng approach o conegraon suggesed by Pesaran e al. (). For noaonal smplcy, we denoe by RFDI he rao of foregn drec nvesmen nflows o GDP. Ths nvolves esmang he followng unresrced error correcon model (UECM): ( GDPC ) = α + α ln( GDPC ) + α ln( RFDI ) + β Δ ln( GDPC ) + γ Δ ln( RFDI ) + ε Δ ln () where he α s ( =,, ), β s ( =,,..., p ), γ s ( =,,,..., p ) are he parameers of he model. The srucural lags are deermned by usng mnmum Akake (AIC) and Schwarz Bayesan (SC) nformaon crera. To depc he presence of conegraon he esmaed coeffcens of lagged level varables are resrced equal o zero. Thus he null hypohess for no conegraon beween GDP per capa and he rao of FDI o GDP accordng o equaon () s: H α = α () : = The F-es sasc has a non-sandard dsrbuon whch depends upon () wheher varables ncluded n he auoregressve dsrbued lags (ARDL) model are I() or I(), () he number of regressors, () wheher he ARDL model conans an nercep and/or a rend, and (v) he sample sze. Thus, he compued F-sasc s compared wh wo asympoc crcal values abulaed by Pesaran e al. () or Narayan (5) for sample szes rangng from 3 observaons o 8 observaons. The lower crcal value assumes ha all he regressors are I(), whle he upper crcal value assumes ha hey are I(). Therefore, f he compued F-sasc s greaer han he upper crcal value, he null of no conegraon s rejeced and we conclude ha he rao of FDI o GDP and he real GDP per capa share a long-run level relaonshp. If he calculaed F-sasc s below he lower crcal value, hen he null hypohess of no conegraon canno be rejeced regardless of he orders of p = p = 7

4 Inernaonal Journal of Economcs and Fnance Vol., No. ; May negraon of he varables. On he oher hand, f falls nsde he crcal values bounds, he es s nconclusve unless we know he order of negraon of he underlyng varables. If a conegraon relaonshp s observed beween he seres, Bardsen (989) mehod wll be used o compue he shor and long run coeffcens. From he esmaon of (), he long-run coeffcen s compued as he coeffcen of he one lagged level explanaory varable dvded by he coeffcen of he one lagged level dependen varable and hen mulples wh a negave sgn. Thus, under he alernave of neres α and α, he long-run level relaonshp beween he real GDP per capa (GDPC) and he rao of FDI o GDP (RFDI) s descrbed as follows: where ϑ α = and α.3 The causaly analyss ( GDPC ) = ϑ + ϑ ln( RFDI ) + ω ln (3) ϑ α =, and α ω s a saonary process wh mean zero. The Granger causaly es s convenonally conduced by esmang vecor auoregressve (VAR) models. Based upon he Granger Represenaon Theorem, Granger (986) shows ha f a par of I() seres are conegraed here mus be a undreconal causaon n eher way. If he seres are no I(), or are negraed of dfferen orders, no es for a long run relaonshp s usually carred ou. However, gven ha un roo and conegraon ess have low power agans he alernave, hese ess can be nappropae and can suffer from pre-esng bas. If he daa are negraed bu no conegraed, hen causaly ess can be conduced by usng he frs dfferenced daa o acheve saonary. Granger non-causaly es n an unresrced VAR model can be smply conduced by esng wheher some parameers are jonly zero, usually by a sandard Wald sasc (or F-sasc). Phllps and Toda (993) show ha he asympoc dsrbuon of he es n he unresrced case nvolves nusance parameers and nonsandard dsrbuons. An alernave procedure o he esmaon of an unresrced VAR consss of ransformng an esmaed error correcon model (ECM) no levels VAR form and hen applyng he Wald ype es for lnear resrcons. Toda and Yamamoo (995) propose an neresng ye smple procedure requrng he esmaon of an augmened VAR whch guaranees he asympoc dsrbuon of he Wald sasc (an asympoc χ -dsrbuon), snce he esng procedure s robus o he negraon and conegraon properes of he process. We use a bvarae VAR ( m + d max ) comprsed of GDP per capa and he rao of foregn drec nvesmen nflows o GDP, followng Yamada (998), and examne he non-causaly beween FDI and economc growh: m dmax m m dmax Y = ϕ + ψ Y + ψ Y + ϕ F + + ϕ F + ν = = = = (4) m dmax m m dmax F = χ + η F + η F + χ Y + + χ Y + ν = = = = (5) where Y = ln( GDPC ), F = ln( RFDI ), ϕ s, ψ s, η s, and χ s are he parameers of he model; d max s he maxmum order of negraon suspeced o occur n he sysem; ν ~ N (, Σ ν ) and ν ~ N (, Σ ν ) are he resduals of he model and Σ ν and Σ ν he covarance marces of ν and ν, respecvely. The null of non-causaly from FDI o growh can be expressed as : ϕ =,,,..., m. Le ( ϕ ϕ,..., ) H = ϕ = vec, ϕ m be he vecor of he frs m VAR coeffcens. For a suable chosen R, he Modfed Wald Sasc for esng H s: ( R Σˆ R ') R ϕ W = T ˆ' ϕ R ' ˆ ν (6) where ϕˆ s he ordnary leas squares esmae for he coeffcen ϕ and Σˆ ν s a conssen esmae for he asympoc covarance marx of T ( ˆ ϕ ϕ) degrees of freedom.. The es sasc s asympocally dsrbued as a χ wh m 7

5 Inernaonal Journal of Economcs and Fnance Two seps are nvolved wh mplemenng he procedure. The frs sep ncludes he deermnaon of he lag lengh ( m ) and he second one s he selecon of he maxmum order of negraon ( d max ) for he varables n he sysem. Measures such as he Akake Informaon Creron (AIC), Schwarz Informaon Creron (SC), Fnal Predcon Error (FPE) and Hannan-Qunn (HQ) Informaon Creron can be used o deermne he approprae lag order of he VAR. In hs paper, we use Akake Informaon Creron (AIC) and Schwarz Informaon Creron (SC) o selec he opmal lag o nclude n models. We use he Augmened Dckey-Fuller ess o deermne he maxmum order of negraon. 3. The emprcal resuls Whle he bounds es for conegraon s applcable rrespecve of wheher he varables are negraed of order one or order zero, s mporan o esablsh ha he varables are no negraed of an order hgher han one. Our second reason for conducng un roo ess s o deermne he exra lags o be added o he vecor auoregressve (VAR) model for he Toda and Yamamoo es. To asceran he order of negraon, we apply he Augmened Dckey-Fuller (ADF) es. The ess are performed on a counry-by-counry bass. Table repors he man resuls of he ADF es. I s shown ha GDP per capa s negraed of order one for all counres, a he 5% sgnfcance level. The rao of FDI o GDP s negraed of order one for Cameroon, Congo, Coe d Ivore, Ghana, Ngera, Senegal and Souh Afrca whle s saonary n Angola, Kenya and Lbera, a 5% level. Hence, for he en counres, VAR models wll add only one exra lag for he mplemenaon of he causaly ess. [Inser Table Here] Followng he modellng approach descrbed earler, we deermne he approprae lag lengh and compue he bounds F-sascs. Akake and Schwarz Bayesan Informaon crera are used o selec he opmal order of lags o nclude n he unresrced error correcon models. Models are esmaed for p =,,,..., 6. Table provdes resuls abou he bounds ess F-sasc, opmal lags seleced by AIC and SC, and Lagrange mulpler sascs for esng he hypohess of no resdual seral correlaon agans order as denoed by χ (). The Akake and Schwarz nformaon crera seleced lag orders ranked beween and 4. The χ () sascs also sugges no seral correlaon agans order for hese lag lenghs seleced by AIC and SC. The bounds es for conegraon nvolves he comparson of he compued F-sascs agans he 5% crcal values, whch are abulaed by Pesaran e al. () or Narayan (5). Table shows ha he F-sasc s hgher han he upper bounds crcal value for Angola and Coe d Ivore a he 5% sgnfcance level and for Kenya a % level, when he dependen varable s GDP per capa n dfference. For he seven oher counres, namely, Cameroon, Congo, Ghana, Lbera, Nger, Senegal and Souh Afrca, when he dependen varable s GDP per capa n dfference, F-sascs le below he lower bounds crcal value. These economerc resuls ndcae ha here s a long-run relaonshp beween FDI nflows and economc growh n hree counres ou of en, whch are Angola, Coe d Ivore and Kenya, when growh s he dependen varable. However, s shown ha here s a long-run relaonshp beween FDI and growh a.5 n Lbera, Senegal and Souh Afrca when he dependen varable s he rao of FDI o GDP, because for hese counres F-sascs are hgher han 5% upper-bound crcal values. [Inser Table Here] Conssen wh he bounds es resuls, as summarzed n able, we proceed o he esmaon of he long-run relaonshp usng equaon (3), only n he case of he counres where a conegrang relaonshp s esablshed. Long-run effecs of FDI on economc growh are provded by able 3. The Barden s equaon resuls sugges sascally sgnfcan and negave error correcon erms n he case of Angola, Coe d Ivore and Kenya, ndcang ha convergence o long-run equlbrum afer a shock o FDI s very moderae for economc growh n Kenya and Coe d Ivore, and que mporan for growh n Angola. For nsance, he coeffcen -.56 (n he case of Angola) suggess ha a devaon from he long-run equlbrum level of GDP n curren year s correced by abou 56 percen n he nex year. Moreover, long-run elasces of FDI on economc growh are posve and sgnfcan a 5% for Angola and Coe d Ivore, bu s no sgnfcan for Kenya. These resuls evdence ha foregn drec nvesmen nflows n Angola and Coe d Ivore are growh enhancng n he long-run. Ths posve long-run elascy s also found by Adams (9) usng a panel daa approach on 4 Sub-Saharan Afrcan counres ncludng our sample wh excepon of Lbera; and by Balasubramanyam e al. (996) esng for he Bhagwa s hypohess (her sample ncludes Coe d Ivore, Ghana, Kenya and Ngera), accordng o whch he benefcal effec of FDI, n erms of enhanced economc growh, s sronger n hose counres whch pursue an ouwardly orened rade polcy han s n hose counres adopng an nwardly orened polcy. However, Adams (9) esmaes he effec of FDI shares n GDP on real growh raes, and does no consder 7

6 Inernaonal Journal of Economcs and Fnance Vol., No. ; May he presence of panel un roo n varables. Our long-run elasces are hgher han ha evdenced by De Mello (999) n he case of non-oecd counres ncludng Coe d Ivore (. and.3), and vary whn counres. Moreover, our resuls abou Ngera are suppored by he work led by Aknlo (4) who fnds no sgnfcan effec of foregn capal on growh. Table 3 also ndcaes sgnfcan and negave error correcon erms n he case of Lbera, Senegal and Souh Afrca where hgh growh rae end o promoe FDI nflows. The FDI-led effec of growh s sascally sgnfcan n Senegal and Souh Afrca, even f hs effec seems very low n Senegal. In Souh Afrca economc growh mpacs FDI mporanly. [Inser Table 3 Here] As prevously menoned, o se he sage for he Toda-Yamamoo es, he order of negraon of he varables s nally deermned usng he augmened Dckey-Fuller (ADF) es. Then, we deermne he approprae lag srucures o nclude n he vecor auoregressve models usng Akake and Schwarz Bayesan Informaon Crera. Table 4 repors he opmal lag orders and Wald sascs for he Toda and Yamamoo causaly es. I s shown ha he approprae lag order s 4 n Angola, 5 n Coe d Ivore, 4 n Kenya, n Lbera and Souh Afrca. We fnd ha for he hree counres where here s a long-run conegrang relaonshp,.e. Angola, Coe d Ivore and Kenya, FDI causes growh a he 5% sgnfcance level. Furhermore, n Lbera and Souh Afrca, economc growh causes FDI nflows a %. These resuls are conssen wh recen sudes on he lnk beween FDI and growh. For example, Hansen and Rand (6) usng daa on 3 counres ncludng Cameroon, Coe d Ivore, Ghana, Kenya, Ngera and Souh Afrca, show he exsence of a b-dreconal causaly beween GDP and FDI nflows. However, her resuls are based on mean group esmaes. Hence, her conclusons are no counry-specfc. [Inser Table 4 Here] 4. Concludng remarks Ths sudy has conrbued o he conegrang and causal relaonshp beween foregn drec nvesmen and economc growh n he case of en Sub-Saharan Afrcan counres. To hs end, we use wo recen economerc procedures whch are he Pesaran e al. () approach o conegraon and he procedure for non-causaly es popularzed by Toda and Yamamoo (995). We buld unresrced error correcon models and compue bounds F-sascs o es for he absence of a long-run relaonshp beween foregn drec nvesmen and growh. We also consruc vecor auoregressve models and compue modfed Wald sascs o es for he non-causaly beween FDI and economc growh. Daa are from he Afrcan Developmen Bank (8), he World Bank (8) and he UNCTAD (8), and cover he perod We show ha here s a long-run relaonshp beween foregn drec nvesmen and economc growh n Angola, Coe d'ivore, Kenya, Lbera, Senegal and Souh Afrca. In addon, he long-run effec of foregn drec nvesmen on growh s posve and sascally sgnfcan n Angola and Coe d'ivore, bu s no sgnfcan n Kenya. Moreover, GDP mpacs FDI sgnfcanly and posvely n Senegal and Souh Afrca. Concluson abou causaly s ha foregn drec nvesmen sgnfcanly causes economc growh n Angola, Coe d'ivore and Kenya. In vew of our fndngs, he convenonal vew whch seems o sugges ha he drecon of causaly runs from FDI o economc growh s confrmed n Angola, Coe d Ivore and Kenya, bu no n Lbera and Souh Afrca where growh causes FDI nflows. The polcy mplcaons of our fndngs are sraghforward. To manan a susanable economc growh, Angola, Coe d Ivore and Kenya have o be encouraged and suppored o arac more foregn drec nvesmen. In furher sudes, aenon needs o be gven o he overall role of growh as a crucal deermnan of FDI along wh he qualy of human capal, nfrasrucure, nsuons, governance and ax sysems n Sub-Saharan Afrcan counres. References Abdula, D. N. (7). Aracng foregn drec nvesmen for growh and developmen n Sub-Saharan Afrca: Polcy opons and sraegc alernaves. Afrca Developmen, XXXII, -3. Adams, S. (9). Foregn drec nvesmen, domesc nvesmen, and economc growh n Sub-Saharan Afrca. Journal of Polcy Modelng, do:.6/j.jpolmod Afrcan Developmen Bank. (8). Seleced Sascs on Afrcan Counres. Afrcan Developmen Bank, XXVII. 73

7 Inernaonal Journal of Economcs and Fnance Aknlo, A. E. (4). Foregn drec nvesmen and growh n Ngera: An emprcal nvesgaon. Journal of Polcy Modelng, 6, Balasubramanyam, V., Salsu, M. & Sapsford, D. (996). FDI and growh n EP and IS counres. Economc Journal, 6, 9-5. Bardsen, G (989). Esmaon of long-run coeffcens n error-correcon models. Oxford Bullen of Economcs and Sascs, 5, Borenszen, E., De Gregoro, J. & Lee, J-W. (998). How does foregn drec nvesmen affec economc growh? Journal of Inernaonal Economcs, 45, Busse, M. & Hefeker, C. (7). Polcal rsk, nsuons and foregn drec nvesmen. European Journal of Polcal Economy, 3, Carkovc, M. & Levne, R. (3). Does foregn drec nvesmen accelerae economc growh? Unversy of Mnnesoa Workng Paper, Mnneapols. Cheung, Y-W. & La, K. S., (993). Fne-sample szes of Johansen s lkelhood rao es for conegraon. Oxford Bullen of Economcs and Sascs, 55, Chowdhury, A. & Mavroas, G. (6). FDI and growh: Wha causes wha? World Economy, 9, 9-9. De Mello, L. R. (997). Foregn drec nvesmen n developng counres and growh: A selecve survey. Journal of Developmen Sudes, 34, -34. De Mello, L. R. (999). FDI-led growh: Evdence from me seres and panel daa. Oxford Economc Papers, 5, Engle, R. F. & Granger, C. W. J. (987). Co-negraon and error correcon: Represenaon, esmaon, and esng. Economerca, 55, Gorg, H. & Greenaway, D. (4). Much ado abou nohng? Do domesc frms really benef from foregn drec nvesmen? World Bank Research Observer, 9, Granger, C. W. (986). Developmens n he sudy of co-negraed economc varables. Oxford Bullen of Economcs and Sascs, 48, 3-8. Hansen, H. & Rand, J. (6). On he causal lnks beween FDI and growh n developng counres. World Economy, 9, -4. Hanson, G. (). Should counres promoe foregn drec nvesmen? UNCTAD: G-4 Dscusson Paper Seres No. 9, UNCTAD, Geneva. Harrs, R. (995). Usng Conegraon Analyss n Economerc Modellng. London: Prence Hall/Harveser Wheasheaf. Hsao, C. & Shen, Y. (3). Foregn drec nvesmen and economc growh: he mporance of nsuons and urbanzaon. Economc Developmen and Culural Change, 5, Johansen, S. & Juselus, K. (99). Maxmum lkelhood esmaon and nferences on conegraon wh applcaons o he demand for money. Oxford Bullen of Economcs and Sascs, 5, 69-. Johansen, S. (988). Sascal analyss of conegraon vecors. Journal of Economc Dynamcs and Conrol,, Mash, A. M. M. & Mash, R. (). The dynamcs of ferly, famly plannng and female educaon n a developng economy. Appled Economcs, 3, Masromarco, C. & Ghosh, S. (9). Foregn capal, human capal, and effcency: A sochasc froner analyss for developng counres. World Developmen, 37, Narayan, P. K. & Peng, X. (7). Japan s ferly ranson: Emprcal evdence from bounds esng approach o conegraon. Japan and he World Economy, 9, Narayan, P. K. (5). The relaonshp beween savng and nvesmen for Japan. Japan and he World Economy, 7, Pesaran, M. H. & Shn, Y. (999). An auoregressve dsrbued lag modellng approach o conegraon analyss. In S. Srom (Ed.), Economercs and Economc Theory n he h Cenury (Chaper ). The Ragnar Frsch Cenennal Symposum, Cambrdge: Cambrdge Unversy Press. 74

8 Inernaonal Journal of Economcs and Fnance Vol., No. ; May Pesaran, M. H., Shn, Y. & Smh, R. J. (). Bounds esng approaches o he analyss of level relaonshps. Journal of Appled Economercs, 6, Phllps, P. C. B. & Toda, H. Y. (993). Lm heory n conegraed vecor auoregressons. Economerc Theory, 9, Toda, H. Y. & Yamamoo, T. (995). Sascal nference n vecor auoregressons wh possbly negraed processes. Journal of Economercs, 66, 5-5. UNCTAD. (8). World Invesmen Repor 8 Daa. New York: Uned Naons Conference on Trade and Developmen, Uned Naons. World Bank. (8). 8 World Developmen Indcaors. Washngon, D.C.: World Bank. Yamada, H. (998). A noe on he causaly beween expor and producvy: an emprcal re-examnaon. Economcs Leers, 6, -4. Zhang, K. H. (). Does foregn drec nvesmen promoe economc growh? Evdence from Eas Asa and Lan Amerca. Conemporary Economc Polcy, 9, Table. Resuls for un roo ess Counres Samples Levels Frs dfferences GDPC RFDI GDPC RFDI d max Angola (-3.59) * (-.95) * (-3.59) -- Cameroon (-3.55) -.57 (-.95) -4.7 * (-3.54) -.95 * (-.95) Congo, Rep (-3.54).73 (-.96) * (-3.54) -7.3 * (-.96) Coe d'ivore (-3.54) -.5 (-.94) -4. * (-3.54) -6.4 * (-.95) Ghana (-3.56).5 (-.94) * (-3.54) * (-.95) Kenya (-3.54) * (-.95) -4.8 * (-3.54) -- Lbera (-.95) -5.7 * (-.94) -3.9 * (-.95) -- Ngera (-3.55) -.5 (-.94) * (-3.55) -8. * (-.95) Senegal (-.94) -.7 (-.95) * (-3.54) -3. * (-.95) Souh Afrca (-3.54) -.44 (-.95) -4.3 * (-3.54) * (-.95) Noes: * denoes rejecon of he null hypohess of un roo he a 5% level. Crcal values a.5 are n parenhess. GDPC and RFDI are GDP per capa and he rao of FDI nflows o GDP, respecvely. 75

9 Inernaonal Journal of Economcs and Fnance Table. Bounds es F-sascs. Sample: 97-7 Endogenous Counres varable Lags ( ) χ F-sasc Oucome Angola GDPC Conegraon a.5 RFDI No conegraon Cameroon GDPC No conegraon RFDI.3.3 No conegraon Congo, Rep. GDPC..6 No conegraon RFDI No conegraon Coe d'ivore GDPC Conegraon a.5 RFDI.9.96 No conegraon Ghana GDPC.3.9 No conegraon RFDI No conegraon Kenya GDPC Conegraon a. RFDI.9.7 No conegraon Lbera GDPC.4.33 No conegraon RFDI. 6.8 Conegraon a.5 Ngera GDPC No conegraon RFDI No conegraon Senegal GDPC No conegraon RFDI Conegraon a.5 Souh Afrca GDPC No conegraon RFDI Conegraon a.5 Noes: χ () s an LM sasc for esng no resdual seral correlaon agans order. GDPC and RFDI are GDP per capa and he rao of FDI nflows o GDP, respecvely. s he dfference operaor. Table 3. Esmaed long-run coeffcens of FDI, Sample: Counres Endogenous varable EC(-) a Long-run effecs Angola GDPC -.56 (-5.7).6 (.4) Cameroon Congo, Rep Coe d'ivore GDPC -.36 (-4.).76 (6.73) Ghana Kenya GDPC -.5 (-3.66) 3.5 (.6) Lbera RFDI -.98 (-5.69).8 (.8) Ngera Senegal RFDI -. (-6.44).7 (4.55) Souh Afrca RFDI -.8 (-6.93).8 (3.7) Noes: a EC(-) s he coeffcen esmae for he lagged error correcon erm. ndcaes sgnfcance a he 5% level. Numbers n parenhess are -sascs. GDPC and RFDI are GDP per capa and he rao of FDI nflows o GDP, respecvely. 76

10 Inernaonal Journal of Economcs and Fnance Vol., No. ; May Table 4. Toda and Yamamoo non-causaly es resuls, Sample: 97-7 Counres Lags RFDI doesn cause GDPC GDPC doesn cause RFDI Wald Sasc P-value Wald Sasc P-value Angola 4.3 * Cameroon Congo, Rep Coe d'ivore 5.39 * Ghana Kenya 4.43 * Lbera ** Ngera Senegal Souh Afrca ** Noes: * ndcaes rejecon of he null a he 5% level. ** ndcaes rejecon of he null a he % level. GDPC and RFDI are GDP per capa and he rao of FDI nflows o GDP, respecvely. 77