MALAYSIAN FOREIGN DIRECT INVESTMENT AND GROWTH: DOES STABILITY MATTER? Jarita Duasa 1

Transcription

1 Journal of Economic Cooperaion, 8, (007), MALAYSIAN FOREIGN DIRECT INVESTMENT AND GROWTH: DOES STABILITY MATTER? Jaria Duasa 1 The objecive of he paper is wofold. Firs, is o examine causal relaionship beween foreign direc invesmen (FDI) and economic growh in Malaysia and second, o look a he impac of FDI on he sabiliy of economic growh and he impac of growh on sabiliy of FDI. Using ime series daa, he paper implemens he recen Toda and Yamamoo s (1995) non-causaliy es o esablish he direcion of causaion beween he wo variables. In addiion, he impac of FDI on sabiliy/volailiy of economic growh and impac of growh on sabiliy of FDI are esed using Generalised Auoregressive Condiional Heeroskedasiciy (GARCH) model. The sudy found no srong evidence of causal relaionship beween FDI and economic growh. However, he analysis found evidence ha he flow of FDI conribues o less volailiy of economic growh and he growh also conribues o less volailiy of FDI flow. This indicaes ha, in he case of Malaysia, FDI does no cause economic growh, vice versa, bu FDI does conribue o sabiliy of growh as growh conribues o sabiliy of FDI. Thus policies ensuring he sabiliy of boh FDI and growh are imporan for long-run susainabiliy of Malaysian economy. 1. Inroducion The relaionship beween foreign direc invesmen (FDI) and economic growh has moivaed many empirical lieraures focusing on boh indusrial and developing counries. Neoclassical models of growh as well as endogenous growh models provide he basis for mos of he 1 Assisan Professor a he Deparmen of Economics, Kuliyyah of Economics and Managemen Sciences a Inernaional Islamic Universiy, Malaysia.

2 84 Journal of Economic Cooperaion empirical work on he FDI-growh relaionship. The relaionship has been sudied from four main channels: (i) he deerminans of growh, (ii) he deerminans of FDI, (iii) role of mulinaional firms in hos counries, and (iv) direcion of causaliy beween he wo variables. Fry (1996), for example, examines he effecs of FDI inflows on a group of six Asian economies (Indonesian, Korea, Malaysia, Philippines, Singapore, and Thailand). He examines five channels hrough which FDI aciviy may affec he balance of paymens (savings, invesmens, expors, impors and economic growh) and found a posiive effec of FDI on he firs four variables, wih a lagged response for expors. Bu he said findings could no simply be generalized. The balance of paymen effec of FDI aciviy varies across counries and depends on he purpose on invesmens, he naure of he aciviy, and he age of he projec. There is no solid ground o make one believe ha foreign firms conribue more or less o he balance of paymen of he hos counry han domesic firms. Case sudies comparing he expor performance of local and foreign firms show a mixed paern. For insance, Willmore (1986) found foreign firms o be more expor oriened han heir mached Brazilian firms. Chen (1983) found no difference in he expor performance of Malaysia and foreign firm. Cohen (1975) found foreign firms o be more expor oriened in Korea; domesic firms are more expor oriened in Singapore, and no difference in he expor performance of foreign and domesic firms in Thailand. Besides, FDI can affec growh by he generaion of produciviy spillovers. Blomsrom (1986) found evidence ha FDI has led a significan posiive spillover effecs on he labour produciviy of domesic firms and he rae of growh of domesic produciviy in Mexico. Similar evidence also found in mos of oher Lain counries. In case of Malaysia, i is generally assumed ha he flood of FDI ino he counry over he las 0 years has resuled in moderae o srong growh performance for he counry. The belief is ha, he FDI generaed he growh. However, he causaliy could ake place a he opposie direcion. FDI possibly is deermined by he growh as higher income would moivae foreign firms o inves more ino he counry. Chowdhury and Mavroas (005), for example, find a bi-direcional causaliy beween GDP and FDI for boh counries Malaysia and Thailand over he period of Bu for Chile, here exis only uni-direcional of causaliy, ha is, GDP causes FDI.

3 Malaysian Foreign Direc Invesmen and Growh 85 This sudy aemps o devoe aenion again on his direcion of causaliy beween GDP and FDI however wih differen sample period. In addiion, i is also expeced ha flow of one variable (eiher FDI or GDP) could deermine some degree of sabiliy/volailiy of anoher variable. For example, he FDI flows o he counry could probably he bes explanaion for he sabiliy of he counry s economic growh or probably he performance of he counry hrough economic growh will bes explain he sabiliy/volailiy of FDI ino he counry. For hese purposes, we use an innovaive economeric mehodology o sudy he direcion of causaliy beween he wo variables, FDI and economic growh, namely he Toda-Yamamoo es for causaliy (Toda and Yamamoo, 1995) and we also use GARCH mehod of esimaion o observe he impac of FDI on sabiliy of economic growh and he impac of economic growh on sabiliy of FDI. I is hope ha his mehodology will allow us o derive much more robus conclusions compared o he exising empirical work on he causaliy beween FDI and growh which uses sandard Granger-causaliy-ype ess o deec he direcion of causaliy. Moreover, he analysis of sabiliy will enhance he undersanding of non-linear relaionship beween hese wo variables in he conex of variabiliy/flucuaion of he series raher han assuming ha he relaionship of he series is linear. The srucure of his paper is as follows. Secion discusses deails of he Toda-Yamamoo approach o es for causaliy as well as GARCH mehod of esimaion for he analysis of he sabiliy of FDI and GDP. Daa relaed o our empirical work is also discussed in his secion. Secion 3 presens he empirical findings and secion 4 concludes.. Mehodology Quarerly daa from Malaysia are used in esimaion. Boh, he foreign direc invesmen (FDI) and gross domesic produc (GDP), as a measure of growh, are in million Ringgi Malaysia (RM). The sample period runs from he firs quarer of 1990 o he fourh quarer of 00, which comprises of 5 observaions. The variables are expressed in heir logarihmic ransformaion and all daa are in real erm. Sources of daa are Inernaional Financial Saisic (IFS) CD-ROM, he Asian Developmen Bank s websie, ( ) and Bank Negara Malaysia (BNM) Bullein.

4 86 Journal of Economic Cooperaion For causaliy es, he paper implemens he more recen Toda and Yamamoo s (1995) non-causaliy es o esablish he direcion of causaion beween he wo variables. In mos previous sudies, he firsdifferenced VAR model of Granger s causaliy es was exensively used. However, he uni roo and coinegraion ess are usually required before esing for causaliy. This migh conribue o possible prees biases due o he sensiiviy of saionary or coinegraion ess. The prees biases migh be severe as he power of uni roo ess is known o be very low and ess for coinegraing rank in Johansen (1991) are no very reliable for finie samples (see Reimers(199) and Toda and Yamamoo(1995)). Taken hese limiaions cauiously, herefore, we use alernaive approach o es for noncausaliy developed by Toda and Yamamoo(1995). In his es, we ignore any possible non-saionariy or coinegraion beween series. The Toda and Yamamoo(1995) procedure essenially suggess he deerminaion of he d-max, namely, he maximal order of inegraion of he series in he model, and o inenionally over-fi he causaliy es underlying model wih addiional d-max lags so ha he VAR order is now p = k + d, where k is he opimal lag order. This modified version of he Granger causaliy es is employed o esablish a causal relaionship beween GDP and FDI in his sudy. The es is done by esimaing a wo-equaion sysem: k+ d max k + d max = + β i GDP i + δ i FDI i i= 1 i= 1 GDP α 1 + µ (1) FDI k + d max k+ d max = + φi GDP i + θ i FDI i i= 1 i= 1 α + ν () where d-max is he maximal order of inegraion of he series in he sysem and µ and ν are error correcion erms ha are assumed o be whie noise. The Wald ess were hen applied o he firs k coefficien marices using he sandard χ -saisics. The null hypohesis se for equaion (1) is δ i = 0 i k and for equaion () is φ i = 0 i k. From equaion (1), FDI Granger-causes GDP if is null hypohesis is rejeced and from equaion (), GDP Granger-causes FDI if is null hypohesis is rejeced. Unidirecional causaliy will occur beween wo variables if eiher null hypohesis of equaion (1) or () is rejeced.

5 Malaysian Foreign Direc Invesmen and Growh 87 Bidirecional causaliy exised if boh null hypoheses are rejeced and no causaliy exised if neiher null hypohesis of equaion (1) nor equaion () is rejeced. The lag selecion is a crucial sep in his non-causaliy es especially when heory and saisical resuls indicae a small number of lags in he VAR componen (Yamada and Toda, 1998). To choose he opimum lag lengh (k), he Akaike Informaion crierion (AIC) and Final Predicion Error (FPE) are implemened. For sabiliy analysis, he GARCH model is used which consiss of esimaing wo equaions joinly. In he firs equaion, he dependen variable is he change or he log change of he series (eiher GDP or FDI) and he independen variable includes, in principle, a range of variables ha effec changes in dependen variables and hey may include lagged values of dependen variables as well. The error erm in his equaion will be expeced o have a mean zero and a ime-varying variance. The firs equaion is known as he mean equaion. In general, say for growh equaion, i could be an ARMA( Auoregressive Moving Average Model) model such as he following ARMA(1,1): LGDP = θ + β + 1 LGDP 1 + β u + β3u 1 η (3) where LGDP is he growh of GDP, u is uncorrelaed random error of AR (Auoregressive) model and η is he error erm and is ime period. The second equaion o be esimaed is he variance equaion iself. I is assumed ha he variance ( h ) depends on lagged squared values of he firs equaion s error erm on is own lagged values and possibly on oher variables (X ). This second equaion is known as he condiional variance equaion, ha is h = α + δ 1η 1 + δ h j + δ 3 X (4) where h is variance of equaion (1), is ime period, j is ime lag and X could be log-differenced of FDI ( LFDI). If his is he case, equaion (4) could be rewrien as: h = α + δ 1η 1 + δ h j + δ 3 LFDI (5)

6 88 Journal of Economic Cooperaion a which, in his equaion (5), we could observe he impac of FDI flows on sabiliy/volailiy of GDP hrough coefficien δ 3. If he coefficien is negaive and significan, i implies ha he flow of FDI conribues o less volailiy or more sabiliy of GDP. On he oher hand, he significan posiive value of he coefficien would imply ha FDI flow conribues o higher volailiy of GDP. We could also es he impac of GDP on volailiy of FDI by jus changing he dependen and independen variables in equaion (3) and (5). In his case, LFDI would replace he dependen variable in equaion (3) and LGDP would replace he independen variable in equaion (5). Specifically, his es will regress he following mean (any ARMA model suied, for example, ARMA(1,1)) and variance equaions: LFDI = * * * * θ + β1 LFDI 1 + β u + β 3u 1 + η (6) * h * α δ η δ + δ LGDP (7) * * * * = h j 3 in which he posiive value of δ 3 * implies ha GDP conribues o higher volailiy of FDI and negaive value of δ 3 * implies GDP conribues o less volailiy of FDI. Before esimaing equaions (3) and (5) or equaions (6) and (7), daa series are o be inspeced for heir saionary. This is done by using Augmened Dickey Fuller (ADF) and Phillip-Perron (P-P) uni roo ess. The saionary series are hen esed for non-lineariy in order o assess he presen of possibly some non-linear srucure wihin he daa which allow us o use he GARCH model. In his process, he BDS es is used as i is hough of as pormaneau es of non-lineariy. The BDS es is a powerful ool for deecing serial dependence in ime series. I ess he null hypohesis of independen and idenically disribued (i.i.d.) agains an unspecified alernaive. This es can es nonlineariy provided ha any linear dependence has been removed from he daa, for example, using radiional ARIMA-ype models or aking he firs difference of naural logarihms. BDS es was firs devised by W.A. Brock, W.Decher and J. Scheinkman in 1987 (Brock, Decher and Scheinkman, 1987).

7 Malaysian Foreign Direc Invesmen and Growh 89 For his sudy, we will use he ARMA model of he ime series which developed by using general-o-specific approach. The BDS es is used o choose he good fi of ARMA model. If he null hypohesis is rejeced, i implies some hidden non-linear srucure in he series. Then, we can proceed by developing he GARCH model. A specific GARCH model is seleced base on, again, he es of i.i.d. on residuals of he model using he BDS es. If he null hypohesis of i.i.d. in residuals is failed o be rejeced for he specified GARCH model, he model is considered as suiable for he series. 3. Resuls 3.1. Causaliy es The resuls of causaliy es are repored in hree seps. Firs, we es for he order of inegraion for boh GDP and FDI in Malaysia. Second, we find ou he opimum lag srucure using he Akaike Informaion crierion (AIC) and Final Predicion Error (FPE). Lasly, we conduc Wald es o analyze non-causaliy beween variables FDI and GDP. Prior o Toda-Yamamoo non-causaliy es, he order of inegraion of he variables is iniially deermined using he ADF and P-P uni roo ess. The resuls are given in Table 1. LGDP and LFDI are he logarihm of gross domesic produc and foreign direc invesmen, respecively. The resuls show ha he GDP and he FDI series for Malaysia are I (1) as he null hypohesis of a uni roo is no rejeced for he level series bu rejeced a he firs differenced series. Therefore, i is concluded ha all variables included in his sudy are inegraed of order one.

8 90 Journal of Economic Cooperaion Table 1: Uni Roo Tess Augmened Dickey Fuller and Phillip-Perron ess Variable ADF es saisic (wih rend and inercep) Level Firs Difference P-P es saisic (wih rend and inercep) Level Firs Difference Gross Domesic Produc[LGDP] ** *** Foreign Direc Invesmen *** *** [LFDI] Noe: *** significan a 1% level ** significan a 5% level * significan a 10% level Given ha boh series were found o be inegraed of order one, we specify he model by deermining he opimal lag lengh of all level variables in he model. The opimum lag lengh (k), chosen by AIC and FPE is found o be 5 (i.e. 1.5 year). Before examining he causaliy es, a series of diagnosic es are implemened o assure ha he underlying assumpion hold. The resuls from Breaush-Godrey Serial Correlaion LM es indicae ha boh equaion (1) and () have no problem of serial correlaion. The Toda-Yamamoo es involves he addiion of one exra lag of each of he variables o each equaion and he use of Wald es is o see if he coefficiens of he lagged oher variables (excluding he addiional one) are joinly zero in he equaion. The resuls of he Wald es are given in Table. The resuls show ha here is no evidence of causaliy beween GDP and FDI as he null hypoheses of no causaliy for boh equaions are no rejeced a any convenional level of significance.

9 Malaysian Foreign Direc Invesmen and Growh 91 Table : Toda-Yamamoo es resuls Equaion Wald es (χ ) FDI (in GDP equaion).358 (0.798) GDP (in FDI equaion) (0.99) Noe: The figures in parenheses are he p-values. b. Volailiy/sabiliy es Since he non-causaliy es implies no causaliy beween FDI and GDP wihin he period of sudy, we expec ha he series would beer be modeled using non-linear raher han linear model. The reason for considering non-linear model is he observaion ha probably he series display ypical nonlinear characerisics especially when here are ouliers such as during he 1997 financial crisis and he implemenaion of capial ouflow conrols a year afer he crisis broke ou. In ligh of his view, he nonlinear model of GARCH is esablished for he series, in which, he impac of one variable on he volailiy of anoher variable could be observed. As menioned in he previous secion, prior o he esimaion of model, uni roo es has o be done for boh series o ensure heir saionariy. The resuls as displayed in Table 1 have shown ha he original/level series are non-saionary. However, when he series are ransformed ino log and differenced once hey are saionary as he null hypoheses are rejeced a 5% level of significance. Using he ransformed series (log and difference once), he ARMA model is developed for each series o aemp possible fi model for he daa. This is done by using general-o-specific approach. The ARMA model for each FDI and GDP series is displayed on Table 3.

10 9 Journal of Economic Cooperaion Table: 3 ARMA models for FDI and GDP series Series ARMA model Diagnosic es GDP FDI LGDP = α α α α α Adj. R = 0 + 1GARCH+ LGDP 4 + 3u + 3u JBnormal = 8.655*** Far = Farch = Fhe = LFDI = β0 + β1 LFDI 1 + βu + β3u 1 + β4u Adj. R = JBnormal = 15.1*** Far = Farch = *** Fhe = *** Noe: 1. Far is he F-saisic of Breusch-Godfrey Serial Correlaion LM Tes Farch is he F-saisic of ARCH Tes JBnormal is he Jarque-Bera Saisic of Normaliy Tes Fhe is he F-saisic of Whie Heeroskedasiciy Tes. Null hypohesis of BDS es is he residuals are i.i.d. 3. *** significan a 1% level ** significan a 5% level. * significan a 10% level. BDS es on residuals of ARMA model BDS Z- saisics in all dimension unil 5 are significan BDS Z- saisics in all dimension unil 6 are significan The resuls of ARMA model for boh series, GDP and FDI, clearly show ha he models suffer normaliy failure in heir residuals. In paricular, ARMA model of FDI has low goodness of fi (adjused R ) and is residuals also face problems of ARCH effec and heeroskedasiciy. Mos imporanly, he BDS es saisics on boh ARMA residuals fail o accep he null hypohesis of independen and idenically disribued (i.i.d.). The deparures from i.i.d. series idenified in he ARMA models may well be aribuable o he presen of auoregressive condiional heeroskedasiciy in series innovaions which probably due o he volailiy of series wihin he period of sudy (e.g. during he Asian financial crisis and he conrols of capial ouflows)

11 Malaysian Foreign Direc Invesmen and Growh 93 For his reason, GARCH model is developed o capure he volailiy of he series. The seleced GARCH model is displayed on Table 4. The resuls of BDS es on residuals of GARCH model indicae ha he residuals are now i.i.d. which suggesed ha he seleced GARCH model is fi o he daa series. Table : 4 GARCH models for FDI and GDP Series ARMA model Diagnosic es GDP GARCH (1,1): h = u h LFDI (1.37) (-1.5) (1.35) (-45.79)*** FDI GARCH(,1): h = u u h LGDP (.35)** (1.) (-0.71) (.00)** (-.35)** Noe: 1. Farch is he F-saisic of ARCH Tes JBnormal is he Jarque-Bera Saisic of Normaliy Tes. Null hypohesis of BDS es is he residuals are i.i.d. 3. Z-saisics in parenheses 4. *** significan a 1% level ** significan a 5% level. * significan a 10% level. JBnormal = 11.7*** Farch =.76* JBnormal = 0.6 Farch = 3.04* BDS es on residuals of ARMA model BDS Z- saisics in mos dimensions are insignifican BDS Z- saisics in all dimensions are insignifican In he seleced GARCH model of GDP, LFDI is included as addiional regressor in order o observe he impac of FDI flow o volailiy of GDP (see Table 4).In similar manner, in GARCH model of FDI, LGDP is added o as a regressor o observe he impac of growh on volailiy of FDI. In boh equaions, coefficiens of hese addiional variables (i.e. LFDI and LGDP) are significan wih negaive signs. This indicaes ha flow of FDI does conribue o sabiliy (less volailiy) of GDP and growh hrough GDP also conribues o sabiliy (less volailiy) of FDI ino he counry. No doub he resuls reflec wha has happened in he counry.

12 94 Journal of Economic Cooperaion In fac, Malaysia s impressive economic growh since he 1960 s and is sabiliy especially before he Asian financial crisis was largely due o policies promoing foreign invesmen. I sared wih he inroducion of he Invesmen Incenives Ac 1968 and followed by esablishmen of he Free Trade Zones during he second Malaysia Plan ( ). Since hen, Malaysia has araced a large porion of invesmen which flowed ino Asia. Malaysia recorded as a second larges FDI recipien among Asian economies in 1995 a abou US$5.8 billion (UNCTAD, 1996). I is clear ha FDI is one of he imporan facors conribues o sabiliy of Malaysian economic growh as FDI is usually expor-oriened and ofen helps ransfer echnology and managemen experise o he hos counry. However,in 1997, he figure was lower due o he lack of confidence as a resul of he Asian financial crisis. Even hough by 1998, in figures, he invesor confidence had improved, i was found ha he number of invesmen projec a he negoiaion sage in 1998 was much higher han in year 1997 (MIDA, various issues). This indicaes ha uncerainy of economic performance has led o delayabiliy aspec of foreign invesmen or insabiliy of he FDI. The crisis affeced Malaysia badly, causing economic growh o fall o -6.8% which was he lowes ever in Malaysia s modern economic hisory. Delayabiliy of foreign invesmen was eviden in Malaysia during 1997/98 period when he saus of implemenaion of approved manufacuring projecs is considered. If in 1994, he proporion of projecs approved a he advanced sage of implemenaion was 41.1 per cen, in 1998 he projecs approved, a similar saus of implemenaion, was only 6.4 per cen. The proporion of projecs a he negoiaion sage was very high in 1998 wih 68.5 per cen due o he uncerainy of he counry s economic growh. Obviously, he performance of he counry refleced by is economic growh is very imporan o mainain sabiliy of foreign invesmen ino he counry for long-run. 4. Conclusion This paper has used a mehodology by Toda-Yamamoo o es he direcion of causaliy beween FDI and growh for Malaysia over he period of 1990 o 00 using quarerly daa. Our empirical findings based on he Toda-Yamamoo causaliy es seem o sugges ha here is no evidence of causaliy beween GDP and FDI. Based on hese resuls,

13 Malaysian Foreign Direc Invesmen and Growh 95 he assumpion ha FDI causes growh, vice versa, raised some doubs. Having said his, he sudy, however, finds ha he causaliy beween FDI and GDP is no maer. Mos imporanly, he performance of one variable does conribue o sabiliy of anoher variable. The policy implicaion could be drawn a his poin is he improvemen of GDP and FDI should be emphasized by he auhoriy o ensure sabiliy of FDI inflow ino he counry and sabiliy of he counry s income. Growh should come wih he qualiy of human capial, infrasrucures, insiuions, good governance, informaion and communicaion echnology and also legal framework. All hese are he compulsory elemens needed o enable he counry o be compeiive in aracing FDI and o mainain he sabiliy of FDI paricularly for fuure developmen. A dynamic package inernally will definiely arac FDI ino he counry. In reurn, he flood of FDI ino he counry may simulae he economic growh of a counry and mos imporanly i is able o reduce he upswing and downswing of he economic growh for long-erm planning. Thus, policy on aracing FDI is equally imporan for sabiliy of economic growh in he counry.

14 96 Journal of Economic Cooperaion REFERENCES Ahukorala, P. and J. Menon (1995) Developing counries wih foreign invesmen: Malaysia Ausralian Economic Review 1, 9-. Anonymous (1996) Invesing in Malaysia:Curren Rules, Incenives, Requiremen, Eas Asian Execuive Repors, Vol. 18, No. 7, Blomsrom, M. (1986) Foreign Invesmen and produciviy Efficiency: The Case of Mexico, Journal of Indusrial Economics, 15, Chen, E. (1983) Mulinaional Corporaions, Technology and Employmen. London: Macmillan. Chowdhury, A. & Mavroas, G. (005) FDI and Growh: A Causal Relaionship, Research Paper No. 005/5, WIDER, Unied Naion Universiy. Cohen, B. (1975) Mulinaional Firms and Asian Expors. New Haven, CT: Yale Universiy. Fry, M. (1996) How Foreign Direc Invesmen in Pacific Asia Improves he Curren Accoun, Journal of Asian Economies, 7, Gujarai, D.N Basic Economerics. Fourh ediion, New York: McGraw-Hill/Irwin. Jansen, K. (1995) The macroeconomic effecs of direc foreign invesmen: The case of Thailand World Developmen 3, Johansen, S. (1988) Saisical Analysis of Coinegraion Vecors Journal of Economic Dynamics and Conrol 1,

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