An Investigation of the Long-Run and Causal Relationships between Economy Performance, Investment and Port Sector Productivity in Cote d Ivoire

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1 Open Journal of Socal Scences, 205, 3, Publshed Onlne Aprl 205 n ScRes. hp:// hp://dx.do.org/0.4236/jss An Invesgaon of he Long-Run and Causal Relaonshps beween Economy Performance, Invesmen and Por Secor Producvy n Coe d Ivore Chna Flora Carne Angub School of Economcs and Managemen, Shangha Marme Unversy, Shangha, Chna Emal: angubcarne@homal.com Receved 25 February 205; acceped 28 March 205; publshed 3 March 205 Copyrgh 205 by auhor and Scenfc Research Publshng Inc. Ths work s lcensed under he Creave Commons Arbuon Inernaonal Lcense (CC BY). hp://creavecommons.org/lcenses/by/4.0/ Absrac Ths sudy used he Auoregressve Dsrbued Lag (ARDL) Bounds esng approach and Toda- Yamamoo Non-granger causaly es o analyze respecvely he long-run and causal relaonshps among economy performance, foregn drec nvesmen, domesc nvesmen and por secor producon oupu n Coe d Ivore over he perod The emprcal resuls llusrae ha economy performance, foregn drec nvesmen and domesc nvesmen are sgnfcan n explanng he producvy of por secor. Therefore, he sudy suggess focusng on nvesmen sraeges ha nvolve prvae (foregn and domesc) parcpaon n projecs dedcaed o mprove he safey, qualy of operaons n he secor and ranspor connecvy. Keywords Por Producvy, Economy Performance, Foregn Drec Invesmen, Domesc Invesmen, ARDL Approach, Toda-Yamamoo Causaly Tes. Inroducon By connecng sea and land ranspor for he shpmen of commodes n huge quanes a lower cos all over he world, por plays a crucal role n promong naonal economy. Transpor nfrasrucure n general nfluences he growh of he economy []. For nsance, n case of nadequae nfrasrucures n por secor, s supply capacy would fal o mee he demand from he economy [2]. Indeed, bolenecks and delays due o he poor condons of he secor nfrasrucures would hnder he acves of he oher secors and negavely affec he How o ce hs paper: Angub, C.F.C. (205) An Invesgaon of he Long-Run and Causal Relaonshps beween Economy Performance, Invesmen and Por Secor Producvy n Coe d Ivore. Open Journal of Socal Scences, 3, hp://dx.do.org/0.4236/jss

2 C. F. C. Angub economy producvy. On he oher hand, effecve ranspor nfrasrucures reduce congeson and have mulpler effecs on developmen. Seapor represens an mporan ndusral and commercal ool for marme counres economc growh. I provdes employmen and revenue for governmen and busnesses [3]. In Coe d Ivore, more han 9% of he volume of rade s carred by sea and more han 70% represens he ndusral [4]. Furhermore, Ivoran por conrbued o more han 85% of he cusoms axes collecons [4]. Accordngly, por s expeced o be a sraegc ool of growh for he counry economy. Many emprcal sudes ha specfcally explore he relaonshp beween por and economy growh have been done. In developed counres, researchers [5] poned ou ha por acves no only connec marme counres bu have mulpler effecs on he economy by ncreasng employmen for he local populaon, ax revenues for he local governmen and smulang he oher secors of he economy. Conversely, scholars [6] and [7] suggesed ha regonal economy performance has an mpac on por producvy. For example, explorng he relaonshp beween por hroughpu and economc acves usng daa from Anwerp (Belgum) por secor, researchers [7] dscovered ha Belgum economy performance as well as ha of her hnerland counres has a grea nfluence on por producon oupu. A sudy based on a pooled-ols (Ordnary Leas Square) model n Germany, proved ha por producvy oupu s posvely assocaed wh regonal per capa GDP (Gross Domesc Produc), however he causaly runnng from por o GDP has no been esablshed [8]. From hese sudes a cause and effec relaonshp beween por and economc performance s observed n boh drecons. In oher words, por plays a crucal role n promong he economy growh, whle he economc performance of he marme counry or regon s beleved o be a caalys for he growh of por secor. Alhough, he exsence of lnkage beween por producvy and economy performance has been recognzed n he scenfc debae, he exac mpac relaonshp s sll unclear and nfluenced by many relevan facors. I s beleved ha nvesmen and economy performance conrbue o susan por producvy [9]. Hence, nvesmen has o be ncluded n por producvy analyss o gan beer undersandng of he nerplay beween seapor producon and economy performance. Measurng he mpac of long dock nvesmen o economy growh, he researchers [0] found ha addng % o he cargo loaded capacy lead o abou 0.43% ncrease n economy producvy. Thus, nvesmen has conrbued o he growh of por capacy whch led o he economy growh. By ulzng a Cobb-Douglass producon funcon o model he relaonshp beween por, foregn drec nvesmen (FDI) and economy growh n Chna, scholars [] demonsraed ha FDI and gross produc value of ndusry have conrbued o promoe he conaner hroughpu of Shenzhen and Guangzhou Pors. Smlarly, researchers [2] consderng por acves as economc producon and economy growh, labor force, foregn drec nvesmen and fxed asses nvesmen as facors of producon bul por producon funcon. The regresson analyss carred, revealed ha boh economy growh and labor force have a sgnfcan mpac on por producvy whle he effecs of fxed asse nvesmen and FDI have been found of low sgnfcance. The poor condons of por secor n Afrca and parcularly n Coe d Ivore requre massve nvesmen on nfrasrucures n order o cope wh he growng demand of he upcomng economy growh [3]. In Ngera, he repor of [4] on FDI nflows has revealed foregn drec nvesmen as a promnen form of nvesmen and an aracve polcy opon n Afrcan por secor. The successful experence of FDI nflows n Ngera por nfrasrucures confrmed he posve effec of FDI on ranspor nfrasrucure developmen. In addon, analyzng he mpac of FDI on he producon of manufacurng frms, researcher [5] susaned ha foregn enerprses are more compeve han he domesc frms. An nvesgaon conduced n Venezuelan frms proved he posve correlaon beween FDI and he producvy of foregn companes whereas has been found negavely correlaed o he performance of he domesc frms n he same ndusry [6]. Usng Vecor Error Correcon Model, Scholars [7] demonsraed ha domesc nvesmen n ranspor nfrasrucure wll lead o he growh of he Indan economy. These fndngs mply ha nvesmen n por secor usng foregn capal s a sraegc ool o enhance producvy. The relaonshp beween por, economy growh and nvesmen has ganed a growng neres n he scenfc dscusson. In conras, emprcal sudes explorng he mpac of economy performance, foregn drec nvesmen and domesc nvesmen on por producvy n developng counres are o our knowledge lmed. Furhermore, pas nvesgaon evdenced conflced resuls relaed o many facors such as he capably of he counry n enablng economc developmen, he dfference n he qualy levels of ranspor nfrasrucure, he dfference n mehodology and daa used [8]. Hence, performed hs sudy can provde nsgh no he role played by economy performance, foregn drec nvesmen and domesc nvesmen n promong por secor growh n Ivoran conex and fll he gap n he leraure. The paper s organzed no fve secons. The nex 30

3 C. F. C. Angub secon wo and hree descrbe he daa, model specfcaon and he mehodology adoped, respecvely. Secon four repors he emprcal resuls, whle he las secon concludes he paper. 2. Daa Descrpon and Model Specfcaon 2.. Daa Descrpon Ths sudy explores he long-run and causal relaonshps beween por, economy performance foregn drec nvesmen (FDI) and Domesc nvesmen (DI) usng Coe d Ivore annual me seres daa over he perod Por producon (PP) s capured by Por hroughpu whereas Real Gross Domesc Produc (GDP) s he proxy for economy performance. FDI s he value of real gross foregn drec nvesmen nflows and Domesc nvesmen (DI) s proxy by he real value of gross fxed capal formaon. Labor (L) measured n erms of labor force. DUM s he dummy varable used o capure he effec of polcal nsably. The daa are colleced from World Developmen Indcaor, excep por hroughpu obaned from he deparmen of sascs of Ivoran pors Model Specfcaon In order o assess he effecs of economy performance, foregn drec nvesmen and domesc nvesmen on por producvy, he sudy employs hree facors aggregae producon funcon o buld por producon model. The sandard form of he hree facors producon funcon can be expressed as: (,, ) Y = Af K L D () where Y denoes he aggregae producon of por secor a me, and A, K, L and D denoe he oal facor producvy, he capal npu, he labor npu and he land npu n he secor n perod respecvely. Followng he approach proposed by [2], s assumed ha economy performance; foregn drec nvesmen and domesc nvesmen are facors affecng por producon. The performance of he economy represens he capal facor whereas boh foregn nvesmen and domesc nvesmen are used o capure land npu. Accordngly, we modeled he followng por producon funcon as: Equaon (2) can be developed as: (,,, ) PP = A f GDP L FDI DI (2) PP = A GDP L FDI DI (3) α β η λ A dummy varable DUM has been ncluded n he model o capure he polcal nsably. The value s n he year of he nsably and 0 oherwse. Thus, Equaon (3) becomes: PP = A GDP L FDI DI DUM (4) α β η λ δ By akng he naural logs of boh sdes, an esmable funcon s obaned as follows: ln PP = a + αln GDP + βln L + ηln FDI + λln DI + δdum + ε (5) where all varables and coeffcens are defned as earler. a s a consan parameer and error erm. 3. Mehodology 3.. Conegraon Tes ε he whe nose The Auoregressve Dsrbued Lag (ARDL) bounds esng procedure based on F es s used o examne he long-run relaonshp among por producon oupu, economy performance, foregn drec nvesmen and domesc nvesmen. The model developed by [9] has many advanages over he convenonal mulvarae conegraon mehod such as maxmum lkelhood conegraon procedures nroduced by [20]. One of he man advanages s ha he bounds esng mehodology can be appled rrespecve of wheher he regressors are saonary a level (I(0)) or negraed of order one (I()) and does no nvolve un-roo pre-esng for he varables [9]. Neverheless, requres esng he saonary of he varables o ensure ha none of he seres s negraed 3

4 C. F. C. Angub of order 2. Unlke he Johansen conegraon procedures, he ARDL approach s suable for small sample sze sudy [2]. Therefore, n order o apply he F es, he bounds esng modellng framework nvolves esmang he followng equaon: ln PP = a + λ ln PP + λ ln GDP + λ ln L + λ ln FDI + λ ln DI p q q2 + φ ln PP + ψ ln GDP + γ ln L = = = q3 q4 + ω ln FDI + ϕ ln DI + ηdum + ε = = where λ are he long-run elascy coeffcens, a 0 he drf, ε he error erm and s he frs dfference operaor. The ARDL bounds es for conegraon sars wh he esmaon of Equaon (6) usng he ordnary leas square (OLS) mehod afer selecng he opmal lag lengh of he model usng eher he Akake Informaon creron (AIC) or he Schwarz Informaon creron (SIC). The F es s performed by consranng he esmaed coeffcens of lagged level varables equal o zero. Therefore, he null hypohess for no conegraon beween he varables of neres agans he alernave s defned as: H : λ = λ = λ = λ = λ = H : λ λ λ λ λ 0 a PP =. The compued F-sascs are compared o he crcal bounds value repored by [2] for small sample sze sudy. If he compued F-sasc s greaer han he crcal upper bound value, hen he null hypohess of no conegraon s rejeced. If he compued F-sasc s lower han he crcal lower bound value, hen he null hypohess s acceped. Neverheless, when he compued F-sasc falls nsde he crcal lower and upper bound values, a conclusve decson canno be made abou he conegraon saus whou knowng he order of negraon of he underlyng regressors. The es whch normalzes on Υ (dependen varable) s denoed F ( PP \ GDP, L, FDI, DI ) In he case of conegraon relaonshp beween he varables, frsly, he ARDL (,,,, ) model s esmaed as follows: q q2 ln PP = a + λ ln PP + λ ln GDP + λ ln L + λ ln FDI = = = = q4 + λ ln DI + θdum + ε = p 4 q (6) pq q q q long-run Second, he shor-run dynamc parameers are goen by esmang an error correcon model assocaed wh he long-run esmaes. Ths s specfed as follows: q q2 ln PP = a + φ ln PP + ψ ln GDP + γ ln L + ω ln FDI 2 = = = = q4 + ϕ ln DI + ηdum + ρ ECT + µ = p where ρ he coeffcen of he error correcon erm (ECT), represens he speed of adjusmen of he model o he long-erm equlbrum. ϕ, ψ, γ, ω, φ are he shor-run elascy coeffcens Causaly Analyss The sandard Granger-causaly es s conduced beween wo me seres o deermne wheher one varable can be employed o predc anoher [22]. However, he mehodology has some lmaons. The granger es s desgned o handle causaly drecon beween wo varables, so as poned ou by scholar [23], negleced he effec of oher relevan varables n he esmaon may produce spurous resuls. In addon, snce, here s a leas one-way causaon n he case of conegraon among varables, spurous causaly may be denfed n he absence of long-run equlbrum relaonshp [23]. In order, o cope wh hese lmaons, he sudy adoped he q3 (7) (8) 32

5 C. F. C. Angub Toda and Yamamoo procedure [24] based on Granger-non causaly model augmened wh exra lags deermned by he maxmum order of negraon of he varables of neres. The echnque requres n he frs sage o defne he approprae lag lengh m for he vecor auoregressve (VAR) model accordng o Akake Informaon Creron (AIC), or Schwarz Informaon Creron (SIC) and hen, selec he maxmum order of negraon (d max ) for he varables n he sysem. In order o es for he causaly he procedures recommended by [24], requre esmang he followng VAR (m + d max ) model: m m+ dmax ln PP = α + β ln PP + β ln PP + λ ln GDP = = m+ = m+ dmax m m+ dmax m + λ ln GDP + θ ln L + θ ln L + η ln FDI = m+ = = m+ = m+ dmax m m+ dmax + η ln FDI + ϕ ln DI + ϕ ln DI + ε = m+ = = m+ where all varables are as prevously defned. α, β, λ, θ, η and ϕ are parameers of he model and he resdual. We esmaed Equaon (9) consderng each of he varables n urn as he dependen varable. We expressed he null hypohess of no causal relaonshp agans he alernave of presence of causaly wh respec o he sysem equaons. When lnpp s he dependen varable n he VAR sysem as specfed n Equaon (9), he null hypohess of no causal relaonshp from lngdp o lnpp, from lnl o lnpp, from lnfdi o lnpp, from lndi o lnpp nvolve ha λ = 0, θ = 0, η = 0 and ϕ = 0 respecvely. 4. Emprcal Resuls 4.. Conegraon Before performng, he conegraon es, we examned he order of negraon of he me seres by usng he Augmened Dcker fuller (ADF) un roo es o ensure ha none of he varables s saonary a second dfference and hen avod spurous resuls. The resuls summarzed n Table reveal ha all he varables are negraed of order one, mplyng ha he ARDL bounds es for conegraon s vald. The ARDL bounds esng procedure s conduced consderng each varable as a dependen varable n he ARDL-OLS regressons. As proposed by researcher [25], a maxmum of 2 lags s seleced for our annual daa. The bounds es resuls are gven n Table 2. When Por producon oupu s he dependen varable, he compued F-sascs, , s hgher han he upper bound crcal value a % level. Furhermore, when economy performance s he dependen varable, he F-sasc compued, s hgher han he upper bound crcal value 4.7 a 5% level. Hence, he null hypoheses of no conegraon are rejeced. These fndngs ndcae ha here exs long run relaonshp beween he varables when he regressons are normalzed on boh Por and economy performance. In lne wh he producon funcon developed for hs sudy, we seleced Por producon oupu as he dependen varable. Havng deermned he exsence of conegraon relaonshp beween por, economy performance, foregn drec nvesmen, domesc nvesmen and labor, we esmaed he long-run and he shor-run parameers. The esmaed long-run coeffcens by normalzng on por are presened n Table 3. In he long run, domesc nvesmen has a posve and sgnfcan mpac on por producon. A percenage ncrease n domesc nvesmen has conrbued o abou 0.35% ncrease n por growh all hngs beng equal. However, he Longerm coeffcens for oher varables namely economy performance, foregn drec nvesmen, labor force and polcal nsably dummy were found sascally nsgnfcan whn he convenonal % - 0% -probably. The shor-run elascy coeffcens assocaed wh he long-run relaonshps are esmaed usng an error correcon model (ECM). The esmaed resuls are repored n Table 4. The error correcon erm (ECT) coeffcen esmaed ( 0.73) s hghly sgnfcan a % level wh he expeced sgn and ndcaes a hgh speed of adjusmen o long-run equlbrum afer a shock. Ths mples ha almos 73% of dsequlbrum caused by he prevous year s shock s adjused back o he long-run equlbrum n he curren year. The shor-run lag-one and lag-wo coeffcens of foregn drec nvesmen are sgnfcan a 5% and % level respecvely, alhough he Long-erm coeffcen was found no sgnfcan. The conrbuon from FDI s abou 0.06% n he shor-run lagone perod and shor-run lag-wo perod elascy s 0.09%. m (9) 33

6 C. F. C. Angub Table. Augmened Dcker-Fuller un roo es resuls. Seres ADF Tes Value Crcal Value % 5% 0% Oucome lnpp Non saonary lnpp *** Saonary lngdp Non saonary lngdp ** Saonary lnfdi Non saonary lnfdi ** Saonary lndi Non saonary lndi *** Saonary lnl Non saonary lnl *** Saonary Noes: frs dfference operaor. *** ( ** ) denoe rejecon of he null hypohess of un roo a % and 5% level of sgnfcance. Table 2. Bounds es resuls for conegraon relaonshp. Dependen varable F-Sasc Oucome F PP (PP\GDP FDI DI L) Conegraon F GDP (GDP\PP FDI DI L) Conegraon F FDI (FDI\GDP PP DI L) No conegraon F DI (DI\FDI GDP PP L) No conegraon F L (L\DI FDI GDP PP) No conegraon Noes: Asympoc crcal value bounds are obaned from appendx A, A2 case II of [2]: Inercep and no rend for k = 4 and N = 34. Lower bound I (0) = 4.65 (2.957) and Upper bound = (4.7) a % (5%) sgnfcance level. Table 3. Esmaed long-run (ARDL) coeffcens. Dependen varable: PP Regressor Coeffcen -sasc p-value C lngdp lnfdi lndi *** lnl DUM Noes: *** denoes % sgnfcance level. Moreover, n he shor-run lag-2 perod, he esmaed elascy of economy performance (.75%) and labor ( 4.9%) are negavely sgned and sascally sgnfcan a % and 0% level respecvely, whereas economy performance and labor force were no sascally sgnfcan n he long run. The resuls of he dagnosc es appled on he ECM model, gven n Table 5, llusrae ha he model passes he Jarque-Bera normaly es and here are no evdence of seral correlaon and heeroscedascy a 5% level. 34

7 C. F. C. Angub Table 4. Error correcon esmaes of por producon model. Dependen varable: PP Regressor Coeffcen -sasc p-value C lnpp( ) lnpp( 2) lngdp( ) lngdp( 2) *** lnfdi( ) ** 0.03 lnfdi( 2) *** * lndi( ) ** lndi( 2) lnl( ) lnl( 2) * DUM ECT( ) *** R-squared = Adjused R-square = F-sasc = Prob(F-sasc) = D-W sasc = Noes: frs dfference operaor. *** ( ** ) * sgnfcance a %, 5% and 0% level. Table 5. Dagnosc ess from he ARDL error correcon model. Null hypohess Tes sascs p-value No seral correlaon Normaly Homoscedascy No ms-specfcaon The cumulave sum of recursve resdual (CUSUM) and of squares resdual (CUSUMQ) plo dsplayed n Fgure, shows he sably of he parameers of he ECM model over he sample perod. The red lnes denoe crcal bounds a 5% sgnfcance level Causaly Tes Resuls The emprcal resuls of Toda-Yamamoo Granger non-causaly es are summarzed n Table 6. The esmaed resuls ndcae ha here s bdreconal causaly beween por and economy performance. Smlarly, a recprocal causal relaonshp exss beween por and foregn drec nvesmen. The causaons runnng from por o economy performance, from economy performance o por, from por o FDI and from FDI o por are deermned a he 0% (χ = 7.44), % (χ = 5.8), 0% (χ = 7.04) and 0% (χ = 6.79) levels of sgnfcance respecvely. On he oher hand, here s one-way causal effec gong from domesc nvesmen o por, from economy performance o FDI, from FDI o domesc nvesmen, from labor force o por, from labor force o economy. performance and from labor force o FDI found a 5% (χ = 0.26), 0% (χ = 6.30), 5% (χ = 8.48), % (χ = 7.); % (χ = 24.84) and % (χ = 4.74) level respecvely. Snce here s non-causaly runnng from he oher varables o labor force, he resuls has been dropped from Table Concluson and Polcy Implcaons In hs paper, economerc approaches have been used o nvesgae he long-run and causal relaonshps beween 35

8 C. F. C. Angub CUSUM 5% Sgnfcance CUSUM of Squares 5% Sgnfcance Fgure. Plo of CUSUM and CUSUMQ for coeffcens for ARDL ECM model. Table 6. Toda-Yamamoo Granger non-causaly es resuls. Dependen varable Excluded varables Ch-Square p-value lngdp *** lnfdi * lnpp lndi ** lnl *** All value aken ogeher lnpp * lnfdi lngdp lndi lnl *** All value aken ogeher lngdp * lnpp * lnfdi lndi lnl *** All value aken ogeher lngdp lnfdi ** lndi lnpp lnl All value aken ogeher Noes: *** ( ** ) * ndcae he rejecon of null hypohess (no causaly) a %, 5% and 0% sgnfcance level. economy performance, foregn drec nvesmen, domesc nvesmen and por secor producvy n Ivoran conex over he perod of The sudy used he bounds esng (ARDL) approach for conegraon o deermne he long-run and shor-run relaonshps beween he varables of neres. The Bounds es resuls mply ha here s a long-erm relaonshp beween he varables of he sudy when por producon oupu s adoped as dependen varable (normalzed). In addon, s found ha domesc nvesmen has a long-erm effec on por producvy. Conversely, 36

9 C. F. C. Angub foregn drec nvesmen and Economy performance do no have a long-erm mpac on por producon, bu her esmaed shor-erm coeffcens provde evdence of shor-run effecs. The negave sgn of shor-run lag-wo perod of GDP reveals he overcapacy ssues facng by Ivoran por secor. The relavely poor nfrasrucures condons of por secor n Coe d Ivore mpede s supply capacy regardng he growng demand from he economy performance. Neverheless, foregn parcpaon posvely nfluences por producvy n he shor run, confrmng he poenal role of FDI n enhancng producvy. Consequenly, Toda-Yamamoo causaly approach has been appled o explore he drecon of causaon among he varables. The fndngs obaned from he causaly es ndcae evdence of recprocal causaly relaon among por and economy performance and on he oher hand, beween por and FDI. Moreover, here s undreconal causaon gong from domesc nvesmen o por, from economy performance o FDI, from FDI o domesc nvesmen, from labor force o por, from labor force o economy performance and from labor force o FDI. The emprcal resuls show ha economy performance, foregn drec nvesmen and domesc nvesmen are mporan n explanng por secor growh n Ivory Coas. Therefore, he sudy suggess focusng on nvesmen sraeges ha nvolve prvae (foregn and domesc) parcpaon n projecs dedcaed o mprove he safey, qualy of operaons n he por secor and o boos ranspor connecvy. References [] Ebers, R. (2000) Undersandng he Impac of Transporaon on Economc Developmen. In: Transporaon Research Board Conference, Transporaon n he New Mllennum, Vol. 30, p hp://rd.rb.org/vew.aspx?d= [2] Moon, S.H. (995) Por Economc Impac Model (PIM) and Is Plannng Applcaons. Marme Polcy and Managemen, 22, hp://dx.do.org/0.080/ [3] Segesmund, P., Kruse, C.J., Prozz, J.P., Alsup, R. and Harrson, R. (2008) Gude o he Economc Value of Texas Pors. No P. hp://rd.rb.org/vew.aspx?d= [4] World Bank (203) Coe d Ivore Jon Saff Advsory Noe on he Naonal Developmen Plan World Bank, Washngon DC. [5] Fndley, D.J., Small, P.J.D., Tran, W., Heller, A., Ber, S.A., Searcy, S.E. and Hall Jr., W.W. (20) Economc Conrbuon of he Norh Carolna Pors. hp:// [6] Ducrue, C. (2009) Por Regons and Globalzaon. Pors n Proxmy: Compeon and Coordnaon among Adjacen Seapors, [7] Vanourve, T. (200) Explorng he Lnk beween Por Throughpu and Economc Acvy: Some Commens on Space- and Tme-Relaed Issues. In: 50h European Congress of he Regonal Scence Assocaon Inernaonal (ERSA Congress 200): Susanable Regonal Growh and Developmen n he Creave Knowledge Economy, European Regonal Scence Assocaon (ERSA), Belgum. hp://bblo.ugen.be/publcaon/05554/fle/ [8] Bredenbach, P. and Mze, T. (203) The Long Shadow of Por Infrasrucure n Germany Cause or Consequence of Regonal Prospery? Avalable a SSRN [9] Rodrgue, J.P. (200) Marme Transporaon: Drvers for he Shppng and Por Indusres. In: Inernaonal Transpor Forumon Transpor and Innovaon: Unleashng he Poenal, Lepzg, May, Forum Paper 2, 23 p. [0] Tukan, M., Achmad, T. and Wdjaya, S. (202) Selecon of Plo Pors and Effec of Long Dock Invesmens o Economc Growh an Island. Academc Research Inernaonal ISSN-L, [] Zhang, G.Q., Zhang, N. and Wang, Q.Y. (2005) Conaner Pors Developmen and Regonal Economc Growh: An Emprcal Research on he Pearl Rver Dela Regon of Chna. Proceedngs of he Easern Asa Socey for Transporaon Sudes, 5, [2] Cheung, S.M.S. and Yp, T.L. (2009) Analyss on Por-Cy Growhs n Chna. Inernaonal Forum on Shppng, Pors and Arpors (IFSPA) 2009-Pos-Fnancal Tsunam: The Way Forward for Shppng, Transpor and Inernaonal Trade, Hong Kong, May 2009, [3] Foser, V. and Pushak, N. (20) Coe d Ivore s Infrasrucure: A Connenal Perspecve. World Bank Polcy Research Workng Paper Seres, Washngon DC. [4] UNCTAD (20) Bes Pracces n Invesmen for Developmen How o Ulze FDI o Improve Transpor Infrasrucure-Pors: Lessons from Ngera. UNCTAD/DIAE/PCB/8, Uned Naons, ISBN [5] Khawar, M. (2003) Producvy and Foregn Drec Invesmen Evdence from Mexco. Journal of Economc Sudes, 37

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