Causality Analysis of the Impact of Foreign Direct Investment on GDP in Nigeria.

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1 Available online a hp:// Nigerian Journal of Basic and Applied Science (211), 19(1): 92 ISSN Causaliy Analysis of he Impac of Foreign Direc Invesmen on GDP in Nigeria. 1 A.Z. Faruku, 2 B.K. Asare, 2 M. Yakubu and 1 L. Shehu 1 Dep. of Mahemaics and Compuer Science, Waziri Umaru Federal polyechnic, Birnin Kebbi. 2 Deparmen of Mahemaics, Usmanu Danfodiyo Universiy, Sokoo [Corresponding Auhor: ABSTRACT: This sudy used a Coinegraion VAR model o sudy he Conemporaneous Long run dynamics of he impac of foreign direc Invesmen (FDI) on Growh Domesics Producs (GDP) wih oher four macroeconomic variables in he Nigerian Economy for he period of January 197 o December 24. The Uni Roo Tes suggess ha all he variables are inegraed of order 1. The VAR (3) model were appropriaely Idenified using AIC informaion crieria and he VECM (2) model wih coinegraion relaion of exacly one.the sudy furher invesigae he causal relaionship using he Granger Causaliy analysis of VECM which indicaes a unidirecional causal relaionship beween GDP and FPI a 5% as in inline wih oher sudies of Basu e al.(23). The resuls of Granger Causaliy Analysis also show ha some of he variables are Granger Causal of one anoher, a 5% level of significance. Having esablished he fac ha foreign direc invesmen has posiive impac on growh domesic produc, governmen should sraegize policies ha would enhance foreign direc invesmen in Nigeria. Key Words: Coinegraion, VAR, VECM, and Granger Causaliy INTRODUCTION The inroducion of co inegraion echniques in modeling and analyzing macro economics variables has remendously changed he naure and direcion of modeling of macro economics sysem (or sub sysems). I provides an alernaive means o assess he exen o which he variables under consideraion are inegraed. Specifically, if GDP, FDI and four oher macro economic variables are inegraed of order one, hen, hey will be coinegraed or have a long run equilibrium relaionship.the co inegraion relaions are used as a ool for discussing he exisence of longrun economic relaions and various hypoheses are hen esed in view of he saisical variaions of he daa. The use of Vecor Auoregressive Models (VAR) and Vecor Error Correcion Models (VECM) for analyzing dynamic relaionships among financial variables has become common in he lieraure, (Granger 1981; Engle and Granger, 1987; MacDonald and Power, 1995; Barnhill, e al., 2).The populariy of hese models has been associaed wih he realizaion ha relaionships among financial variables are so complex ha radiional imeseries models have failed o fully capure. The manifesaion of economic crises in mos of developing counries including Nigeria in he lae 197s and early 198s made he auhoriies of hese counries o change heir aenion oward macro economic policy and is relaion o economic growh by increasing effor oward aracing foreign direc invesmen (Adeolu, 27). Caves (1996) observes ha he raionale for increased effors o arac more FDI sems from he belief ha FDI has several posiive effecs. Among hese are produciviy gains, echnology ransfers, and he inroducion of new processes, managerial skills and knowhow in he domesic marke, employee raining, inernaional producion neworks, and access o markes. However, here have been some sudies on invesmen and growh in Nigeria wih varying resuls and submissions. Ariyo (1998) sudied he invesmen rend and is impac on Nigerias economic growh over he years. He found ha only privae domesic invesmen consisenly conribued o raising GDP growh raes during he period considered ( ). Furhermore, here is no reliable evidence ha all he invesmen variables included in his analysis have any percepible influence on economic growh. He herefore suggess he need for an insiuional rearrangemen ha recognizes and proecs he ineres of major parners in he developmen of he economy. Oyinlola (1995) concepualized foreign capial o include foreign loans, direc foreign invesmens and expor earnings. Adelegan (2) explored he seemingly unrelaed regression model o examine he impac of FDI on economic growh in Nigeria and found ou ha FDI is proconsumpion and proimpor and negaively relaed o gross domesic invesmen.
2 Faruku e al.: Causaliy Analysis of he Impac of Foreign Direc Invesmen on GDP in Nigeria Akinlo (24) found ha foreign capial has a small and no saisically significan effec on economic growh in Nigeria. The objecive of his sudy is, herefore o conduc Engle Granger Causaliy es o invesigae he impac of foreign direc invesmens on gross domesic produc in Nigeria, using Vecor error correcion Model (VECM) echniques. Review of he causal Relaionship beween FDI and GDP: One of he mos imporan conceps of causaliy was inroduced by Granger (1969) and has become quie popular in he economic lieraure. This sudy specifically is ineresed in he lieraure ha focused more direcly on he causal relaionships beween FDI and growh and, a leas, six sudies have esed for Granger causaliy beween he wo series using differen samples and esimaion echniques. Zhang (21) looks a 11 counries on a counrybycounry basis, dividing he counries according o he ime series properies of he daa. Tess for long run causaliy based on an error correcion model, indicae a srong Grangercausal relaionship beween FDI and GDPgrowh. For six counies where here is no coinegraion relaionship beween he log of FDI and growh, only one counry exhibied Granger causaliy from FDI o growh. Chowdhury and Mavroas (23) ake a slighly differen roue by esing for Granger causaliy using he Toda and Yamamoo (1995) specificaion, hereby overcoming possible preesing problems in relaion o ess for coinegraion beween series. Using daa from 1969 o 2, hey find ha FDI does no Granger cause GDP in Chile, whereas here is a bidirecional causaliy beween GDP and FDI in Malaysia and Thailand. Finally he sudy by Basu e al. (23) addresses he quesion of he woway link beween growh and FDI. Allowing for counry specific coinegraing vecors as well as individual counry and ime fixed effecs hey find a coinegraed relaionship beween FDI and growh using a panel of 23 counries. Basu e al. emphasize rade openness as a crucial deerminan for he impac of FDI on GDP; hey find woway causaliy beween FDI and growh in open economies, boh in he shor and he long run, whereas he long run causaliy is unidirecional from GDP o FDI in relaively closed economies. MATERIALS AND METHODS The deailed overview of procedures and mehodology o be implemened in his research work is hereby presened. The heoreical model, which also serves as a basic frame work of our saisical analysis, is he Vecor Auoregressive model of order p, which is denoed by VAR (P) and is given by Y = + D + ψ + φ Y + φ Y + + φ Y + ε p p (2.1) Equaion (2.1) can be wrien as φ L Y = + D + ψ + ε ( ) Where φ ( L) n j = 1 φ L, j= 1 Y =(Y,Y...,Y ) j ' 1 2 k is a se of k h ime series variables, is he consan erm, D is he regressors associaed wih deerminisic erms, ψ is he seasonal dummies and srucural ' breaks and ε = ( ε1, ε2,..., ε k ) is an unobserved zero means independen whie noise process wih ime invarian and posiive definie E ε ε ' = Σ and covariance marix ( ) ( ) k P φ L = 1 φ L φ L... φ L is a marix of a lag polynomial wih k x k coefficien marices, φ j, j = 1,2,...,p. When ineres cenre on coinegraion relaion he more convenien model o use is Vecor Error Correcion model (VECM) which is given by: y = π y + Γ y Γ y + + Dψ + ε p 1 p+ 1 (2.2) Where π = (I n φ1 φ2... φp ) and ' Γ j = ( φi φ p ) for (i = 1,2,...,p1) Since Y does no conain sochasic reads by our assumpion ha all variances should be I(1), he mean erm π X 1 is he only one which includes I(1) variables. Hence, πy i 1 mus also bei () husi conain he coinegraion relaions. The Γ j (j = 1,2,..., 1p ) are ofen referred as he shor run erm while πy 1 is someimes called he long run erm. The model in (2.2) is abbreviaed as VECM (P1). p 1
3 Nigerian Journal of Basic and Applied Science (211), 19(1): 92 Uni Roo and Saionariy Tess: Quie a number of uni roo es have been developed wih a view o deermining wheher he series are saionary, in his research we consider wo ess ha es he null hypohesis of Uni Roo agains he alernaive of saionary. These are: Augmened Dickey Fuller (ADF) Uni Roo Tes and he Dickey FullerGeneralized Leas Square (DFGLS) Tes. And KPSS Tes wih he null hypohesis of Saionariy agains alernaive of Uni Roo. VAR Lag Order by Selecion Crierion and Coinegraion Tes: The following crieria are ofen used: (i) This is he Akaike informaion crierion Akaike. (1974) (ii) (iii) Alernaives are he Bayesian crierion of Gideon (1978) ( p) T 1 ln T SC = ln u + m T = 1 T he crierion developed by Edward and Quinn (1979) 2 ( p) T 1 2 AIC = ln u + m T = 1 T T ( p) 1 2ln(ln T ) HQ = ln u + m T = 1 T There are several mehods available for conducing he coinegraion es. The mos widely used mehods include he residual based Engle and Granger (1987) es and Maximum likelihood base Johansen (1991) es. Model Checking: Once a model has been specified is adequacy is usually checked wih a series of ess. There is need o implemen some of he saisic es in order o obain valid and accurae resuls. Mos of hese model checking ools are based on he residuals of he model. These includes: Auoregressive Condiion HeeroskedasicLagrange Muliplier (Arch Lm), Breusch Godfrey Lagrange Muliplier (Lm) Tes, Pormaneau Tes for Auocorrelaion, and Jarque Bera Tes of Normaliy. 2 2 Sabiliy Analysis: Parameers are consan hrough ou he sample period, is a key assumpion in economeric models. In his sudy he recursive residuals es ha is CUSUM TEST are adoped o check he validiy of his assumpion. The Cusum Tes: The Cusum es according o Brown e al. (1975) cied in Lukepohl e al. (25) is based on he cumulaive sum of recursive residuals. The es plos he cumulaive sum ogeher wih he 95% criical line. The es finds parameer insabiliy if he cumulaive sum goes ouside he area beween he wo criical lines, up o a paricular period. T Wr CUSUM =, r = k + 1,..., T s r= k+ 1 Where W is he recursive model, s is he sandard error of he regression fied o all T sample poin, k is he number of coefficien o be esimaed. The significance of any deparure from he zero line is assessed by reference o a pair of 95% significance lines. The disance which increases wih Movemen wr ouside he criical lines is suggesing coefficien insabiliy. On he oher hand he CUSUM square es is based on he saisic CUSUM SQ = T r= k + 1 T r= k + 1 If he CUSUM SQ cross he pair of 95% criical lines i indicae he srucural insabiliy. w w The Granger Causaliy Analysis: The causaliy concep inroduce by Granger (1969) is perhaps he mos widely discussed form of causaliy in he economerics lieraures, Granger defines a variable y o be cause by anoher ime series variables x if he former variables can be prediced using pas values of x in addiion o he all oher relevan informaion needless o say, he correc esimaion procedure would be o include all 2 r 2 r 11
4 Faruku e al.: Causaliy Analysis of he Impac of Foreign Direc Invesmen on GDP in Nigeria independen variables indicaed by he relevan economic heory. Excluding appropriae variables may yields irrelevan and useless resuls. Granger considers a sysem of he general form. p y1 α11 α12 y1 1 u1 = CD + + y2 = 1 α21 α22 y2 1 u2 In he model se up, y 1 does no Granger cause y 2 if and only if α 2i =, i = 1,2,..., p In oher words, can help forecas y Granger cause x if x. if y does no cause and x does no cause y hen boh y x y and x are independen.if y cause x and x cause y, i said ha feedback exis beween x and y. A Wald es saisic divided by he number of resricion is used in conjuncion wih an F disribuion for esing he resricion (Lueikepohl (1991). If he F saisic is greaer han he criical value for an F disribuion, hen null hypohesis is rejeced, ha y does no Granger cause x. The role of y and x can y. reverse o es Granger causaliy from x o If he ime series variable are no saionary bu inegraed of he same order ha is I(1) and coinegraed. Granger causaliy is implemened by specifying PH order VECM follows. p X β1 α11 α12 X 1 X 1 u1 = + + Π + Y β α α Y Y u 2 = X 1 Where is an error correcion erm drive Y 1 from long run coinegraing relaion ship, u1 and u 2 are serially independen errors wih mean zero and finie covariance marix x. The decision crieria is ha accep H (no causal relaion ship beween variables) if p value is greaer han he significance level, oherwise we rejec he null hypohesis and accep he alernaive hypohesis (here exis causal relaionship beween variables) if p value is less han significance levelα. Daa Analysis: Our arge in his paper is o esablish wheher here is causaliy relaion ship beween he Gross domesic produc (GDP) and Foreign direc invesmen in Nigeria(he emphasis is on GDP and FDI). The daa for he analysis consis of annual observaions of six macro economic variables in he Nigerian economy for he period of : IFR = Inflaion rae (measure by consumer price index), FDI= Foreign Direc invesmen, GDP= Real Gross domesic produc, INR= Ineres rae, COP= Crude oil producion, ENC = Energy consumpion, obained from he cenral bank of saisical bullein vol. 16, 25 for he period of Two saisical sofwares are used for he empirical daa analysis namely Grel and Jmuli. Time Plo of he Variables: The ime series plo of all he variables are carried ou where by each variable is ploed agains ime. These plos are shown in Figures 1 and 2. These plos were hen examined (as we can see he enire plos have no seasonaliy), he variables are no covariance saionary. The plos of wo variables are rending up ward. We ake he log in order o sabilize heir variances (GDP=l_GDP, FDI=l_FDI). The plo of he variables shows ha he series are no mean revering. 12
5 Nigerian Journal of Basic and Applied Science (211), 19(1): 92 ENC l_gdp l_fpi d_enc d_l_gdp d_l_fpi Fig. 1: Plos of Variables a Levels and Firs Difference COP 1e INR IFR d_cop d_inr d_ifr 45 Fig. 2: Plos of Variables a levels and Firs Difference 13
6 Faruku e al.: Causaliy Analysis of he Impac of Foreign Direc Invesmen on GDP in Nigeria Deerminaion he Lag Order of he Variables: In his sudy he ADF es down procedure is applied o deermine he lag order of each variable, he maximum lag of 1 o 1 is used in his sudy. The resuls are as in Table 1. Variable IFR has Lag order of 1 for i o be saionary in he uni roo es. The variable loggdp has Lag order of for i o be saionary in he uni roo es. The variable log FPI has Lag order of for i o be saionary in he uni roo es. The variable INR has lag order of 1 for i o be saionary. Variable COP has lag order of and 3 for i o be saionary in he uni roo es. Variable ENC has lag order of 1 for i o be saionary in he uni roo es. Uni Roo Tes: Tables 1 and 2 summarize he resuls of uni roo es. From he resuls, all he variables are non saionary a levels bu saionary in he firs difference since criical values are less han es saisics a he levels bu criical values are greaer han es saisics in he firs difference for boh ADF and ADF  GLS es leading o non rejecion of null hypohesis a hese levels bu null hypohesis is rejeced a firs difference. Hence he series are inegraed of order one (1). Also KPSS es (Table 3) rejec he null hypohesis a levels bu null hypohesis is acceped a firs difference Table 1: The ADF uni roo es for idenificaion of order of inegraion of he variables Level Firs Difference Var Trend sa Cons Cons & Cons Cons &Trend `IFR LnGDP LnFPI INR COP ENC Criical Val 5% 1% Table 2: ADF GLS Tes for idenificaion of order of inegraion Levels Firs Difference VAR Trend Cons Cons & Cons Treand Cons & IFR Log GDP Log FPI INR COP ENC % %
7 Nigerian Journal of Basic and Applied Science (211), 19(1): 92 Table 3: KPSS Uni Roo Tes for idenificaion of order of inegraion levels Firs Difference Var Cons Cons & Trend Cons Cons & Trend IFR LnGDP LnFPI INR COP ENC Criical 5% val VAR Model Idenificaion We esimae VAR model of l_gdp, IFR, l_fdi, INR, COP and ENC. Wih number of lags order of 3 bases on informaion crieria he values of AIC, HQC, and BIC are given by he resul in Table 4. VAR sysem, maximum lag order 3, he aserisks below indicae he bes (ha is, minimized) values of he respecive informaion crieria, AIC = Akaike crierion, BIC = Schwarz Bayesian crierion and HQC = HannanQuinn crierion. Table 4: Lag order selecion lags loglik p(lr) AIC BIC HQC * * * We use AIC Crieria o obain he mos parsimonious model for he daa. Afer deermining he order of VAR model he nex sage consis of deermining he inclusion or exclusion of he consan marices, D and ψ as in he following model. l _ GDP φ φ φ φ φ φ l _ GDP l _ FDI IFR = + INR COP ENC φ φ φ φ φ φ l _ GDP ' ' ' ' ' ' ' ' ' ' ' ' φ21 φ22 φ23 φ24 φ25 φ26 l _ FDI 1 φ2 1 φ2 2 φ2 3 φ2 4 φ2 5 φ2 6 l _ FDI 2 ' ' ' ' ' ' 3 φ31 φ32 φ33 φ34 φ35 φ IFR 1 φ3 1 φ3 2 φ3 3 φ3 4 φ3 5 φ3 6 IFR 2 + ' ' ' ' ' ' φ41 φ42 φ43 φ44 φ45 φ46 INR 1 φ4 1 φ4 2 φ4 3 φ4 4 φ4 5 φ4 6 INR 2 ' ' ' ' ' ' 5 φ51 φ52 φ53 φ54 φ55 φ 56 COP φ5 1 φ5 2 φ5 3 φ5 4 φ5 5 φ5 6 COP 2 ' ' ' ' ' ' 6 φ61 φ62 φ63 φ64 φ65 φ 66 ENC φ6 1 φ6 2 φ6 3 φ6 4 φ6 5 φ6 6 ENC φ1 1 φ1 2 φ1 3 φ1 4 φ1 5 φ 1 6 l _ GDP 3 ε φ21 φ2 2 φ2 3 φ2 4 φ2 5 φ2 6 l _ FDI 3 ε φ31 φ3 2 φ3 3 φ3 4 φ3 5 φ 3 6 IFR 3 ε φ41 φ4 2 φ4 3 φ4 4 φ4 5 φ4 6 INR 3 ε φ51 φ5 2 φ5 3 φ5 4 φ5 5 φ 5 6 COP 3 ε φ61 φ6 2 φ6 3 φ6 4 φ6 5 φ 6 6 ENC 3 ε 6 From he model above, we noe ha in his model (i) here are no exogenous variables, (ii) here is a consan erm bu no rend or dummy variables for eiher seasonaliy or srucural breaks and (iii) he number of endogenous lag is 3. The absence of dummy variables is easily explain; ess shows ha (a) he periodiciy of he macroeconomic variables is 1 and (b) here are no srucural breaks in he daa. Hence, srucural breaks and seasonal dummies should no be included in he VAR model. Johansen Tes for Coinegraion Rank: We have applied Johansen race es and maximum likelihood max es in order o deermine he Coinegraion rank of our variables since i is one of he condiions o model wih VECM ha here mus be Coinegraion relaionship. The resuls for he es are presened in he Table 5. 15
8 Faruku e al.: Causaliy Analysis of he Impac of Foreign Direc Invesmen on GDP in Nigeria Table 5: Johanson Tes for coinegraion rank Rank Eigenvalue Trace p es value Lmax es pvalue From Table 5 resuls, he coinegraing rank is 1 base on he p value of race es since he firs null hypohesis ha can no be rejeced is a rank 1. Resuls of Coinegraion Relaions β = and α = The above resuls show ha he coinegraion relaion wih resriced consan is ec = GDP.873FPI.115INR.3IFR.6ENC.COP or ML GDP = FPI +.115INR +.3IFR +.6ENC The equaion above can be inerpreed as follows: he coefficien.873 of he value of Foreign Direc Invesmen in Nigeria (FPI) is he esimaed ou pu elasiciy because Gross Domesic Produc (GDP) and Foreign Direc Invesmen (FPI) boh appear in logarihms (Lukepohl, 25). For a 1% GDP increase obained in Nigeria will induce a similar.115% increase in ineres rae(inr),.3% inflaion rae(ifr),.6% energy consumpion (ENC) and.% of crude oil producion(cop). VECM (2) Represenaion: The VECM represenaion of he VAR 3 model is given in equaion below. The complee VECM (2) Equaion can represen as follows: G D P.4 87 G D P F D I.86 1 F D I IN R IN R = IF R IF R E N C E N C C O P C O P G D P F D I IN R IF R E N C C O P G D P 2 U F D I 2 U IN R 2 U IF R 2 U E N C 2 U C O P 2 U [ ] 16
9 Nigerian Journal of Basic and Applied Science (211), 19(1): 92 VECM Model Checking: The following ess o he residuals are applied o check for he adequacy of our VECM model (i) he Pormaneau LB es, Godfrey LM es for auocorrelaion,(ii)auoregressive condiional Heeroskedasic LM es for ARCH effec and (ii) Jarque Bera es for Normaliy. The resuls are summarised in Tables 6 and 7. The resuls of Table 6 show ha he null hypohesis of no serial auocorrelaion and condiional Heeroskedasiciy will be acceped for pormaneau LB es and ARCH LM es since here p values are greaer ahn he significance values of.5 and.1 for he 5% and 1% significan levels. However, null hypohesis is rejeced for Godfrey LM Tes. The Table 7 above es also shows ha he hree of he residuals are normal while he res are no oo far from normaliy, hence hey can be regarded as adequae. Cusum and Cusum Sq Tes for Sabiliy: These wo ess are applied o examine he sabiliy of he long run coefficien ogeher wih shor run dynamic (Pearson and Pearson, 1997).CUSUM and CUSUM SQ es is propose by Brown, Durbin and Evans (1975). The es is applied o he residuals of all variables in he VECM model. If he plo of he CUSUM saisics says wihin he criical bound of 95% level of significance represened by a pair of sraigh lines drawn a 95% level of significance he null hypohesis concerning all coefficiens in he error correcion model canno be rejeced. If any of he lines is crossed. The null hypohesis of coefficien consancy a 95% level of significance will be rejeced. A CUSUMSQ es is based on he square recursive residuals; a similar procedure is used o carryou he es Table 6: Resuls of VECM es for serial correlaion and ARCH effec Residuals P values Decisions Pormaneau LB.6997 Accep Tes H Godfrey LM Tes. Rejec H ARCH LM Tes.1168 Accep H Table 7: Resuls of VECM Jaque Bera and Shapiro  Wilk es for Normaliy Jaque Bera es Shapiro Wilk es Residuals P P Decisions Value Value U Accep H U Rejeced H U Accep H U Rejec H U Rejec H U Accep H Figures 34 are a graphical represenaion of CUSUM and CUSUMSQ plos respecively which are applied o he error correcion model seleced by he adjused R 2 crierion. CUSUM plos of he variables do no cross criical bounds which indicae ha no evidence of any significan insabiliy. However, in CUSUMSQ plo of Fig. 4 hree plos slighly cross he criical bound indicaing sligh insabiliy of hese variables. Fig. 3: Plos of Residuals CUSUM 17
10 Faruku e al.: Causaliy Analysis of he Impac of Foreign Direc Invesmen on GDP in Nigeria Fig.4: Plos of Residuals CUSUMSQ Causaliy Analysis: Resuls for he analysis of causaliy are presened and he causaliy beween he variables if any and he direcion of he causaliy of he sysems is deermined using Granger Causaliy es. The resuls of he es are presened in Table 8. The resuls esimaed show. ha a 5% all he variables are Granger no causal for GDP. However here is unidirecional causaliy beween FPI and GDP, INR and GDP and, ha is wha happens beween INF and FPI, and ENC and COP. Bu here is bi direcion causaliy beween FPI and INR Table 8: Resuls of Granger Causaliy Analysis Null hypohesis F sa pvalue Decision rule GDP does no Granger Cause FPI rejec null a 5% FPI does no Granger Cause GDP do no rejec null GDP does no Granger Cause INR do no rejec null INR does no Granger Cause GDP rejec null GDP does no Granger Cause IFR do no rejec null IFR does no Granger Cause GDP do no rejec null GDP does no Granger Cause ENC do no rejec null ENC does no Granger Cause GDP do no rejec null GDP does no Granger Cause COP do no rejec null COP does no Granger Cause GDP do no rejec null FPI does no Grander Cause INR rejec null INR does no Granger Cause FPI rejec null FPI does no Granger Cause IFR rejec null IFR does no Granger Cause FPI do no rejec null FPI does no Granger Cause IFR do no rejec null ENC does no Granger Cause FPI do no rejec null FPI does no Granger Cause COP do no rejec null COP does no Granger Cause FPI do no rejec null IFR does no Granger Cause INR do no rejec null INR does no Granger Cause IFR rejec null a 5% ENC does no Granger Cause COP rejec null COP does no Granger Cause ENC do no rejec null ENC does no Granger Cause IFR do no rejec null IFR does no Granger Cause ENC do no rejec null ENC does no Granger Cause INR do no rejec null INR does no Granger Cause ENC do no rejec null CONCLUSION In his sudy we have presened an analysis of he coinegaion beween he Foreign Direc Invesmen (FDI) and Growh Domesic Produc (GDP) wih four oher macroeconomic variables in Nigeria using he daa obained from cenral bank saisical Bullein 25 for he period of 197 o 24. The ADF Tes, ADF GLS Tes 18
11 Nigerian Journal of Basic and Applied Science (211), 19(1): 92 and KPSS es shows ha all he six variables are inegraed of order one. VAR 3 and VECM 2 model are chosen base on Akaike crierion he johansen es show ha VECM 2 has a coinegraion relaionship wih rank of 1. Furher he Granger Causaliy Analysis shows a unidirecional causal relaionship beween GDP and FDI his is inline wih oher sudies of Basu e al.(23) and wih four oher macro economic variables. The resuls suppor he heoreical conenion and give srong suppor o he hypohesis ha FDI inflows have impac on GDP. In conclusion, our economeric esimaes of he impac of FDI on GDP model for Nigeria sugges ha here exiss a long run relaionship beween FDI, and GDP. Precisely, hese findings sugges ha he conribuion of FDI o Nigerians economic growh is abou.873 and all oher variables have long run relaionship wih posiive conribuion in he growh model excep IFR which has negaive impac as expeced Uremadu (28). RECOMMENDATIONS The following recommendaions were made a) Having esablished he fac ha foreign direc invesmen has posiive impac on growh domesic produc, governmen should sraegize policies ha would enhance foreign direc invesmen in Nigeria. b) Foreign Direc invesmen should be seen, no as an end in iself, bu as a means of supporing oher developmen iniiaives such as povery reducion or he Millennium Developmen Goals. c) Governmen should arge he foreign invesors which are mos likely o respond, such as he naional Diasporas. REFERENCES Adeolu, B.A. (27). FDI and Economic Growh: Evidence from Nigeria. AERC Research paper 165. African Economic Research Consorium, Nairobi, Kenya. Adelegan, J.O. (2). Foreign direc invesmen and economic growh in Nigeria: A seemingly unrelaed model. African Review of Money, Finance and Banking, Supplemenary issue of Savings and Developmen 2:525. Milan, Ialy. Akaike, H. (1974). New look a hesaisical model idenificaion, Insiue of saisical mahemaics, Minaoku, Japan Akinlo, A. (24). FDI and Economic Growh in Nigeria. An Empirical Invesigaion. J. Policy Modeling 26: Ariyo, A. (1998). Invesmen and Nigerias economic growh. In Invesmen in he Growh. Process Proceedings of Nigerian Economic Sociey Annual Conference 1998: Ibadan, Nigeria. Barnhill, T.M., Jouz, F.L. and Maxwell, W.F. (2). Facors affecing he yields on noninvesmen grade bond indices: A coinegraion analysis. J. Empirical Fin. 7: Basu, P., Chakrabory, C. and Reagle, D. (23). Liberalizaion, FDI, and Growh in Developing Counries: A Panel Coinegraion Approach. Econ. Inquiry, 41: Brown, R. L., Durbin, J., and Evans, J. M. (1975), Techniques for Tesing he Consancy of Regression Relaionships over Time, J. Royal Sais. Soc., Series B, 39: Caves, R.E. (1996). Mulinaional Enerprise and Economic Analysis. 2nd edn. Cambridge: Cambridge Universiy Press. CBN (25). Saisical Bullein. Cenral Bank of Nigeria, Volume Choe, J.I. (23). Do foreign direc invesmen and gross domesic invesmen promoe economic growh? Rev. Dev. Econ. 7: Chowdhury, A. and Mavroas, G. (23). FDI & growh: Wha causes wha? Paper presened a he UNU/WIDER conference on Sharing Global Prosperiy, Sepember 23, Helsinki, Finland. De Mello, L.R. (1999). Foreign direc invesmenled growh: Evidence from ime series and panel daa. Oxford Econ. Papers, 51: Dickey, D.A., and Fuller, W.A. (1979). Disribuion of he Esimaors for Auoregressive Time Series wih a Uni Roo. J. Am. Sais. Assoc. 74: Edward, J.H and Quinn, B.G. (1979). The deerminaion of he order of an auoregression. J. Royal Sais. Soc. Series B 41: 19{
12 Faruku e al.: Causaliy Analysis of he Impac of Foreign Direc Invesmen on GDP in Nigeria Engle, R.F. (1982). Auoregressive condiional Heroscedasiciy wih Esimaes of he variance of unied kingdoms inflaions, Economerica. 5: Engle, R.F. and Granger, C.W.J (1987). Coinegraion and error correcion: Represenaion, esimaion and esing. Economerica 55: Gideon, S. (1978). Esimaing he dimension of a model. The Annals Sais. 6: Granger, C.W.J.(1969) Invesing Causal Relaions by Economeric Models and cross Specral mehods. Economerica 37: Granger, C.W.J. (1981). Some properies of ime series daa and heir use in economeric model specificaion, J. Economerics 23: Johansen, S. (1991). Esimaion and hypohesis esing of coinegraing vecor in Gaussian vecor auoregression models. Economerica 59: Lukepohl, H. (1991). Inroducion o Muliple Time Series Analysis, Berlin: Springer Verlag. Lukepohl, H. (25). New Inroducion o Muliple Time Series Analysis, Berlin: Springer, Verlag. MacDonald, R. and Power, D. (1995). Sock prices, dividends and reenion: Longerm relaionships and shorerm dynamics. J. Empirical Finance 2: Odozi, V.A. (1995). An Overview of Foreign Invesmen, CBN Research Deparmen Occasional Paper, No. 11 (June) Oyinlola, O. (1995). Exernal capial and economic developmen in Nigeria ( ). The Niger. J. Econ. Soc. Sud. 37(2&3): Pesaran, M. H. and Pesaran, B. (1997). Working wih Micro_ 4.: Ineracive Economeric Analysi Oxford Universiy Press, Oxford. Phillips, P.C.B. and Perron, P. (1988). Tesing for a Uni Roo in Time Series Regression, Biomerika, 75: Toda, H.Y. and Yamamoo, T. (1995). Saisical Inference in Vecor Auoregressions wih Possible Inegraed Processes. J. Economerics 66: Zhang, K.H. (21). Does foreign direc invesmen promoe economic growh? Evidence from Eas Asia and Lain America, Conemp. Econ. Policy, 19:
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