JOURNAL OF INTERNATIONAL AND AREA STUDIES Volume 5, Number, 008, pp.-5 Do Seel Consumpion and Producion Cause Economic Growh?: A Case Sudy of Six Souheas Asian Counries Hee-Ryang Ra This sudy aims o deermine he facors of secor gains and labor shifs on povery of Vienam, and examine how far he effecs of hese wo facors on povery reducion have changed over ime. The empirical analysis uilizes daa from he Vienam Household Living Sandards Survey in 998 and 00. As a resul, agriculural secor has been cenral o he srong povery reducion experienced by Vienam over he las decade. Around 60% of he aggregae decline in povery indicaors originaed from improvemen in income of farmers. Lower povery incidence of all he remaining secors joinly accouned for around 30% and 0% of he naional fall in povery indices in 993-998 and 998-00 respecively. In conras, as a resul of quicker movemens from low produciviy secors o higher produciviy ones, labor shifs evolved as a more imporan conribuing facor o povery reducion in he same period. The highes concenraion and severiy of he wo farmer groups, and heir impressive paricipaion in he reducion of aggregae povery as poined ou in his sudy convey a srong message o policy makers, which implies ha policies o reduce povery in Vienam mus coninue o reach farmers if a considerably furher reducion in povery is o be achieved. JEL Codes: C, C3, O53 Keywords: Seel producion, Seel demand, Economic growh, Granger causaliy, Coinegraion, Souheas Asian counries. INTRODUCTION The seel indusry is regarded as a sraegic indusry for he naional economy, playing a crucial role in he economic developmen by providing he basic maerials for consrucion, auomobiles, elecronics, shipbuilding, and so on. However, Souheas Asian counries have been experiencing a lack of domesic seel supply because he capaciy for seel producion is very limied. Figure shows he rend for he oal consumpion and producion of crude seel by six Souheas Asian counries Indonesia, Malaysia, he Philippines, Singapore, Thailand, and Vienam for he period 97-006. Seel consumpion increased o 48. million ons in 006 from.4 million ons in 998. On he oher hand, he oal producion of crude seel by he counries increased by only 9.0 million ons from 8. million ons in 998. The gap beween consumpion and producion has increased from 4.4 million ons in 998 o 33.0 million ons in 006. Also, he six Souheas Asian counries impored a oal Usually, an inpu-oupu analysis is used o examine he impac of he seel indusry on he economy (Kim e al., 998; Choi, 007). Also, Ghosh (006) examined he relaionship beween seel consumpion and economic growh for India. The numbers are calculaed from he IISI (Inernaional Iron and Seel Insiue) Seel saisical yearbook.
HEE-RYANG RA of 33.0 million ons of seel producs, while he oal expor for he year was 9.8 million ons, a difference of 3. million ons in 006. 3 The governmens of hese Souheas Asian counries are planning o increase he capaciy of he seel mills o he level of he demand for seel. The Souheas Asian seel-makers have already launched huge expansion plans for he shor and medium erms. For example, he Indonesian governmen is planning o increase he counry s oal seel producion o 0 million ons by 00, up from 6 million ons in 006, and Malaysia s Ann Joo Resources Bhd is aiming o sar consrucing is 0.5 million onnes mini blas furnace plan. 4 If hese plans are realized, he seel indusry of Souheas Asia could mee he srong domesic demand as well as compee in he inernaional marke o supply o oher regions. Furhermore, he seel secor of hese Souheas Asian counries could enjoy he advanages of he domesic availabiliy of raw maerials and cheap labor, because he inpu coss for seel producion rises rapidly wih a rapid increase in global demand (mainly from China, India, Lain America, and oher Asian counries) as well as he limied availabiliy of iron ore and coking coal. By uilizing hese advanages, expanding he seel producion or/and seel capaciy would lead he region o have a more solid foundaion for economic developmen. The objecive of his sudy is o examine he relaionship beween he seel indusry and he economic growh of hese six Souheas Asian counries by Granger causaliy beween seel consumpion and economic growh, and seel producion and economic growh in a vecor auoregression (VAR) framework. 5 Our empirical resuls could provide meaningful implicaions for policy formulaion regarding he seel indusry. If, for example, here is unidirecional Granger causaliy from seel producion o economic growh, increasing domesic seel producion could lead o a rise in naional income. On he oher hand, no causaliy in eiher direcion would indicae ha seel producion would no affec economic growh and vice versa. In he nex secion, we explain he concep and mehod of he Granger causaliy beween seel consumpion and economic growh, and seel consumpion and economic growh for he six counries. Also we examine daa for he ess. Secion 3 presens he empirical resuls from he esimaions. Finally, secion 4 summarizes he main findings and draws conclusions. 3 SEAISI (Souh Eas Asia Iron and Seel Insiue) Newsleer, July 007. 4 SEAISI (Souh Eas Asia Iron and Seel Insiue) Newsleer, July 007. 5 We acknowledge ha, in heoreical erms, analysis on economic growh heory and seel demand funcion may be needed o examine he relaionship beween seel consumpion (producion) and economic growh. Also, we acknowledge ha an inpu-oupu analysis can be used o examine he impac of he seel indusry on he economy using forward and backward linkage impacs. However, for he large scope of analysis which is beyond his paper and he lack of he indusrial daa for he counries, we leave his analysis for he fuure sudy. Insead, he Granger causaliy may be used as an alernaive way o examine he relaionship beween he seel indusry and economy. The Granger causaliy is a saisical concep of causaliy ha is based on predicion. According o he Granger causaliy, if a variable X Granger-causes (or G-causes ) a variable X, hen pas values of X should conain informaion ha helps predic X above and beyond he informaion conained in pas values of X alone. Is mahemaical formulaion is based on linear regression modeling of sochasic processes (Granger, 969 and 980). See secion for more discussion.
DO STEEL CONSUMPTION AND PRODUCTION CAUSE ECONOMIC GROWTH?: 3 Figure. Seel Consumpion and Producion of Souheas Asia (97-006) 50000 housand meric ones 40000 30000 0000 0000 0 975 980 985 990 995 000 005 Consumpion Producion. METHODOLOGY AND DATA.. Concep and implicaion of he causaliy es Engle and Granger (987) showed ha if he series X and Y are individually I() (i.e., inegraed of order one) and coinegraed, hen here would be a causal relaionship a leas in one direcion. However, he direcion of causaliy can be deeced hrough he vecor error correcion model of long-run coinegraing vecors. Furhermore, Granger s represenaion heorem demonsraes how o model a coinegraed I() series in a VAR forma. VAR can be consruced eiher in erms of he level of he daa or in erms of heir firs differences, i.e., I(0) variables, wih he addiion of an error correcion erm o capure he shor-run dynamics. If he series are I() bu no coinegraed, he causaliy es may give misleading resuls unless he daa are ransformed o induce saionariy. A hree-sage procedure has been employed o es he exisence of causaliy. As he firs sep, we es for he order of inegraion of he naural logarihm of he variables by using augmened Dickey and Fuller (ADF) (98) saisics. Condiional upon he oucome of he ess, he second sage involves invesigaing he coinegraion relaionship among he variables using he VAR approach of Johansen (988, 99) and Johansen and Juselius (990). The hird sage (or second, if a bivariae coinegraion is rejeced) involves consrucing sandard Granger-ype causaliy ess, augmened where appropriae wih a lagged error correcion erm. 6 6 We acknowledge ha he Granger causaliy ess should be used wih care, because i will be ofen be hard o find any clear conclusions unless he daa can be described by a simple -dimensional
4 HEE-RYANG RA Regarding he economic implicaions of he Granger causaliy, he exisence of he Granger causaliy from economic growh o seel consumpion reveals ha a growh in income is responsible for he increasing seel consumpion. This is quie obvious as, wih economic growh, he demands for consumer durables, auomobiles, consrucion, and infrasrucure have been increased where seel is used as one of he basic maerials. The Granger causaliy running from economic growh o seel producion may reflec he increase in seel capaciy or seel producion induced by he economic growh o mee he seel demand. On he oher hand, he exisence of he Granger causaliy running from seel consumpion o economic growh or from seel producion o economic growh may reflec he increase in economic oucome which is realized hrough seel consumpion and producion. For example, he increase in seel consumpion in he auomobile indusry would mean an increase in he producion of auomobiles, leading o a rise in GDP. Also, he increase in seel producion would mean a rise in GDP... Saionariy and coinegraion ess For he Granger causaliy es, we need o perform a uni roo es and deermine wheher he variables are inegraed or no. In his sudy, an ADF es is conduced for he saionary es and Johansen s mehod is adoped for he coinegraion es, following he common way. In he firs sage, he order of inegraion of he variables is invesigaed. We conduc ADF uni roo ess on he naural logarihms of he levels and he firs differences of he variables. On he basis of he ADF saisics, we decide o rejec he null hypohesis of a uni roo. The saionariy es is performed by running a similar es on he firs difference of he variables. Then, in he second sage, he Johansen maximum likelihood procedure is used o deec coinegraion..3. Granger causaliy es Finally, based on he resuls of he coinegraion ess, we perform he Granger causaliy es o idenify he causaliy beween seel consumpion and economic growh, and seel producion and economic growh. 7 If he series, X and Y are individually I() and coinegraed, hen he Granger causaliy ess may use I() daa because of he superconsisency properies of esimaion: Mehod I X m n βi X i + γ iy j + i= j= = α + u () Y = a + q r by i i + c j X j + i= j= v () sysem, and anoher poenially serious problem may be he choice of sampling period, for example, a long sampling period may hide he causaliy (Toda and Phillips, 994). 7 We adop he mehod suggesed by Ghosh (006) for he Granger causaliy es.
DO STEEL CONSUMPTION AND PRODUCTION CAUSE ECONOMIC GROWTH?: 5 where u and v are zero-mean, serially uncorrelaed, random disurbances. Secondly, Granger causaliy ess wih coinegraed variables may uilize he I(0) daa wih an error correcion erm (ECT), i.e., Mehod II ΔX ΔY m n βiδx i + γ iδy j + δect + i= j= = α + u (3) = a + q r bi ΔY i + c jδx j + dect + i= j= v (4) Thirdly, if he daa are I() bu no coinegraed, valid Granger-ype ess require ransformaion o make hem I(0). So, in his case he equaions become: Mehod III ΔX ΔY m n βiδx i + γ iδy j + i= j= = α + u (5) = a + q r biδy i + c jδx j + i= j= v The opimum lag lenghs m, n, q, and r are deermined on he basis of Akaike s (AIC) and/or Schwarz s (SIC) and/or log-likelihood raio (LR) es crierion. For equaions () and (), Y Granger causes (GC) X if H 0 : γ = γ =... = γ n = 0 is rejeced, agains HA : a leas one γ j 0, j =,..., n. X Granger causes Y if H 0 : c = c =... = cn = 0 is rejeced, agains HA : a leas onec j 0, j =,..., r. For equaions (3) and (4), ΔY, Granger causes ΔX if H 0 : γ = γ =... = γ n = 0 is rejeced, agains HA : a leas one c j 0, j =,..., n or δ 0. ΔX Granger causes ΔY if H 0 : c = c =... = cn = 0 is rejeced, agains HA : a leas one r j 0, j =,..., r or d 0. For equaions (5) and (6), ΔY, Granger causes ΔX if H 0 : γ = γ =... = γ n = 0 is rejeced, agains HA : a leas oneγ j 0, j =,..., n. ΔX Granger causes ΔY if H 0 : c c =... = c 0 is rejeced, agains HA : a leas onec j 0, j =,..., r. = n = (6).4. Daa The ess are conduced on he annual daa for he six Souheas Asian counries covering he period 97-006. For he lack of daa in he case of Vienam, we conduced he ess for
6 HEE-RYANG RA he period 985-006. 8 Daa on he gross domesic produc (GDP) a 000 prices, as a proxy o economic growh, have been colleced from Inernaional Financial Saisics (IFS) provided by he Inernaional Moneary Fund (IMF). The annual consumpion and producion of crude seel for he same ime period is aken from he Seel Saisical Yearbook, published by he Inernaional Iron and Seel Insiue (IISI). logseel C, logseel P, and loggdp represen he consumpion of crude seel, he producion of crude seel, and GDP, respecively, afer heir logarihmic ransformaion following he convenional way o measure he seel demand funcion. 3.. Saionariy es 3. EMPIRICAL RESULTS In he firs sage, he order of inegraion of he variables is invesigaed. The resuls of he ADF uni roo ess on he naural logarihms of he levels and he firs differences of he variables are summarized in Tables -. 9 Excep for he loggdp of Indonesia (we may accep he uni roo because i is rejeced a he 0 percen level), he uni roo ess do no rejec he uni roo in level for all cases. However, we rejec he uni roo in he differenced daa a he percen significance level, excep for logseel p and loggdp of Vienam. The uni roo es on he differenced daa of logseel p of Vienam is rejeced a he 0 percen significance level, and he differenced daa of he loggdp of Vienam is rejeced a he 5 percen significance level. For Vienam, he saisics may no be accurae because of he small sample size ( observaions). The series of Vienam may be regarded as being saionary in he differenced daa o perform he Table. The Augmened Dickey-Fuller Uni Roo Tess on he Indonesia Malaysia Philippines Firs Firs Firs Level Level Level difference difference difference log Seel C -.857-4.09 *** -.703-5.94 *** -.686-5.569 *** log Seel P -.943-7.5 *** -.488-5.7 *** -0.9 -.60 * log GDP -.76 * -4.409 *** -.4-5.94 *** -.6-5.655 *** Time period 97-006 97-006 97-006 Noes: Significance levels are 0% *, 5% **, and % ***. We seleced he augmenaion lags for each Dickey-Fuller regression in order o minimize he Schwarz Informaion Crierion (SIC). Each regression conains an inercep bu no ime rend. 8 We acknowledge ha our sample size may no be big enough o esimae he long-run relaionship beween seel consumpion (producion) and economic growh. Also, we acknowledge ha here are oher omied variables o explain seel consumpion, such as seel price, and price of a subsiue or complemen maerial. We leave hese issues of omied variables for he fuure sudy. 9 The Phillip-Perron uni roo es is an alernaive mehod for he Augmened Dickey-Fuller es ha conrols for serial correlaion when esing for a uni roo. The resuls are no repored here, because he resuls are no much differen from hose of he ADF es.
DO STEEL CONSUMPTION AND PRODUCTION CAUSE ECONOMIC GROWTH?: 7 Table. The Augmened Dickey-Fuller Uni Roo Tess on he Singapore Thailand Vienam Level Firs difference Level Firs difference Level Firs difference log Seel C -.36-4.55 *** -.40-5.49 *** -0.976-4.88 *** log Seel P -.39-5.600 *** 0.857-5.054 *** -.4 -.697 * log GDP -.50-3.806 *** -.88-5.396 *** -0.065 -.95 Time period 97-006 97-006 985-006 Noes: Significance levels are 0% *, 5% **, and % ***. We seleced he augmenaion lags for each Dickey-Fuller regression in order o minimize he Schwarz Informaion Crierion (SIC). Each regression conains an inercep bu no ime rend. denoes 5 percen significance level. Granger causaliy es. Thus, we may believe ha all he variables have an I() process, which means he daa are non-saionary in levels. 3.. Coinegraion es Based on he previous ADF uni roo ess, in he second sage, he Johansen maximum likelihood procedure is used o deec coinegraion. This provides a unified framework for esimaion and esing of coinegraing relaions in he conex of a VAR error correcion model. The coinegraion rank, r, of he ime series is esed using wo es saisics. Denoing he number of coinegraing vecors by r 0, he maximum eigenvalue (λ max ) es is calculaed under he null hypohesis ha r 0 = r, agains he alernaive of r 0 > r. The race es is calculaed under he null hypohesis ha r 0 r, agains r 0 > r. Tables 3~8 summarize he saisics of he Johansen coinegraion es for each counry. Regarding he coinegraion beween logseel C and loggdp for Malaysia, he Philippines, and Vienam, he eigenvalue es and he race es reveal ha he null hypohesis r = 0 beween logseel C and loggdp can be rejeced agains he alernaive r a he 5 percen significance level. These imply he exisence of only one coinegraion relaionship beween logseel C and loggdp. Thus, we may use he bivariae sysem logseel C and loggdp, which can be modeled using Mehod I or II. On he basis of SIC and adjused LR es crieria, he opimal lag order of he VAR is chosen as wo. The absence of residual serial correlaion of he individual equaions has also confirmed he correc order of he VAR selecion. For he oher counries Indonesia, Singapore, Thailand he eigenvalue es and he race es reveal ha he null hypohesis r = 0 beween loggdp and logseel C canno be rejeced, meaning he absence of coinegraion beween logseel C and loggdp. Thus, we can use he bivariae sysem ΔlogGDP and ΔlogSeel C, where Δ is he firs difference operaor and hence defines he growh of he respecive variable, which can be modeled as an unresriced VAR (Mehod III). On he basis of SIC and adjused LR es crieria, he opimal lag order of he VAR is chosen as he appropriae order (wo, one, and hree lags, repecively). The absence of residual serial correlaion of he individual equaions has also confirmed he correc order of VAR selecion. Also, regarding he coinegraion beween logseel P and loggdp for Indonesia, Singapore, and Vienam, he eigenvalue es and he race es reveal ha he null hypohesis r = 0 beween logseel P and loggdp can be rejeced agains he alernaive r a he 5
8 HEE-RYANG RA percen significance level. These imply he exisence of only one coinegraion beween logseel P and loggdp. Thus, we can use he bivariae sysem logseel P and loggdp, which can be modeled using Mehods I or II. For he oher counries Malaysia, he Philippines, and Thailand he eigenvalue es and he race es reveal ha he null hypohesis r = 0 beween loggdp and logseel C canno be rejeced, meaning he absence of coinegraion beween logseel P and loggdp. We can use he bivariae sysem ΔlogGDP and ΔlogSeel C in his case (Mehod III). Table 3. The Johansen Tess for Coinegraion (Indonesia) Hypohesized Number of Coinegraing Vecors Eigenvalues Trace Saisics Maximum Eigenvalue Saisic log Seel C & log GDP 0 0.8 9.65 (5.495) 8.0 (4.65) 0.037.54 (3.84).54 (3.84) log Seel P & log GDP 0 0.58 3.649 ** (5.495).60 ** (4.65) 0.033.09 (3.84).09 (3.84) Noes: Significance levels are 5% * and % **. The number in parenheses is a criical value a he 0.05 level. Boh specificaions include wo lags, assuming a rend in he series bu no in he coinegraing relaionships. Table 4. The Johansen Tess for Coinegraion (Malaysia) Hypohesized Number of Coinegraing Vecors Eigenvalues Trace Saisics Maximum Eigenvalue Saisic log Seel C & log GDP 0 0.499.3 ** (5.495) 0.747 ** (4.65) 0.048.467 (3.84).467 (3.84) log Seel P & log GDP 0 0. 0.803 (5.495) 7.595 (4.65) 0.095 3.08 (3.84) 3.08 (3.84) Noes: Significance levels are 5% * and % **. The number in parenheses is a criical value a he 0.05 level. Boh specificaions include wo lags, assuming a rend in he series bu no in he coinegraing relaionships.
DO STEEL CONSUMPTION AND PRODUCTION CAUSE ECONOMIC GROWTH?: 9 Table 5. The Johansen Tess for Coinegraion (Philippines) Hypohesized Number of Coinegraing Vecors Eigenvalues Trace Saisics Maximum Eigenvalue Saisic log Seel C & log GDP 0 0.4 0.05 ** (5.495) 6.448 ** (4.65) 0.048 3.577 (3.84) 3.577 (3.84) log Seel P & log GDP 0 0.367 3.79 (5.495) 0.634 (4.65) 0.6 5.645 ** (3.84) 5.645 ** (3.84) Noes: Significance levels are 5% * and % **. The number in parenheses is a criical value a he 0.05 level. Boh specificaions include wo lags, assuming a rend in he series bu no in he coinegraing relaionships. Table 6. The Johansen Tess for Coinegraion (Singapore) Hypohesized Number of Coinegraing Vecors Eigenvalues Trace Saisics Maximum Eigenvalue Saisic log Seel C & log GDP 0 0.67 4.908 (5.495) 9.636 (4.65) 0.83 6.7 ** (3.84) 6.7 ** (3.84) log Seel P & log GDP 0 0.598 8.67 ** (5.495) 6.44 ** (4.65) 0.073.03 (3.84).03 (3.84) Noes: Significance levels are 5% * and % **. The number in parenheses is a criical value a he 0.05 level. Boh specificaions include wo lags, assuming a rend in he series bu no in he coinegraing relaionships. Table 7. The Johansen Tess for Coinegraion (Thailand) Hypohesized Number of Coinegraing Vecors Eigenvalues Trace Saisics Maximum Eigenvalue Saisic log Seel C & log GDP 0 0.77 5.36 (5.495) 0.399 (4.65) 0.44 4.963 ** (3.84) 4.963 ** (3.84) log Seel P & log GDP 0 0.3 0.807 (5.495) 8.808 (4.65) 0.44.7 (3.84).7 (3.84) Noes: Significance levels are 5% * and % **. The number in parenheses is a criical value a he 0.05 level. Boh specificaions include wo lags, assuming a rend in he series bu no in he coinegraing relaionships.
0 HEE-RYANG RA Table 8. The Johansen Tess for Coinegraion (Vienam) Hypohesized Number of Coinegraing Vecors Eigenvalues Trace Saisics Maximum Eigenvalue Saisic log Seel C & log GDP 0 0.706 7.06 ** (5.495) 5.9 ** (4.65) 0.085.49 (3.84).49 (3.84) log Seel P & log GDP 0 0.839 4.84 ** (5.495) 3.745 ** (4.65) 0.079.069 (3.84) 0.079 (3.84) Noes: Significance levels are 5% * and % **. The number in parenheses is a criical value a he 0.05 level. Boh specificaions include wo lags, assuming a rend in he series bu no in he coinegraing relaionships. 3.3. Granger causaliy es Based on he previous coinegraing es, Table 9 summarizes he exisence or absence of coinegraion beween he variables and he mehod for he Granger causaliy es. Also, he Granger causaliy ess are conduced following he mehods in secion. Tables 0-5 represen he resuls of he Granger causaliy ess for each counry. Firs, regarding he es for causaliy from seel consumpion o economic growh, he null hypohesis of noncausaliy from logseel C o loggdp or from ΔlogSeel C o ΔlogGDP, which is asympoically disribued as a χ variae, can be rejeced in he case of Malaysia (a he percen significance level for Mehod I and a he 0 percen significance level for Mehod II), he Philippines (a he 0 percen significance level for Mehod I and a he 5 percen significance level for Mehod II), and Thailand (a he 5 percen significance level for Mehod III). These imply he presence of unidirecional causaliy running from seel consumpion o economic growh wihou any feedback effec. While esing he causaliy running from economic growh o seel consumpion, he null hypohesis of non-causaliy from loggdp o logseel C or from ΔlogGDP o ΔlogSeel C can be rejeced in he case of Malaysia (a he 0 percen significance level for Mehods I and II), he Philippines (a he percen significance level for Mehod III), Singapore (a he 5 percen significance level for Mehod III), and Vienam (a he percen significance level for Mehod I). These imply he presence of unidirecional causaliy running from economic growh o seel consumpion. Also, regarding he es for causaliy running from seel producion o economic growh, he null hypohesis of non-causaliy from logseel P o loggdp or from ΔlogSeel P o ΔlogGDP can be rejeced in he case of Malaysia (a he 0 percen significance level for Mehod III), he Philippines (a he 5 percen significance level for Mehods III), Singapore (a he 5 percen significance level for Mehods I and II), Thailand (a he 0 percen significance level for Mehod III), and Vienam (a he 0 percen significance level for Mehod I). These imply he presence of unidirecional causaliy running from seel producion o economic growh. Finally, esing he causaliy from economic growh o seel producion, he null hypohesis of non-causaliy from loggdp o logseel P or from loggdp o logseel P can be rejeced in he case of Indonesia, (a he 0 percen significance level for Mehod II) and Singapore (a he 0 percen significance level for Mehod I and a he
DO STEEL CONSUMPTION AND PRODUCTION CAUSE ECONOMIC GROWTH?: percen significance level for Mehod II). These imply he presence of unidirecional causaliy running from economic growh o seel producion. Table 9. Coinegraion and Causaliy Tess Mehod for Causaliy es Coinegraion beween log Seel C & log GDP Coinegraion beween log Seel P & log GDP Mehod for Causaliy es Indonesia No III Yes I, II Malaysia Yes I, II No III Philippines Yes I, II No III Singapore No III Yes I, II Thailand No III No III Vienam Yes I, II Yes I, II Table 0. Granger Causaliy Tess (Indonesia) Null Hypohesis: Non-causaliy Mehod χ P-value Accep Causaliy? Seel C >> log GDP III 3.353 0.87 No log GDP >> Seel C III 0.59 0.77 No log Seel P >> log GDP I.009 0.064 No log GDP >> log Seel P I.933 0.3 No log Seel P >> log GDP II 3.59 0.06 No log GDP >> log Seel P II 5.784 0.056 Yes Table. Granger Causaliy Tess (Malaysia) Null Hypohesis: Non-causaliy Mehod χ P-value Accep Causaliy? log Seel C >> log GDP I 6.95 0.003 Yes log GDP >> log Seel C I 8.75 0.068 Yes log Seel C >> log GDP II 7.780 0.05 Yes log GDP >> log Seel C II 6.50 0.089 Yes log Seel P >> log GDP III 4.09 0.043 Yes log GDP >> log Seel P III 0.007 0.934 No
HEE-RYANG RA Table. Granger Causaliy Tess (Philippines) Null Hypohesis: Non-causaliy Mehod χ P-value Accep Causaliy? log Seel C >> log GDP I 6.79 0.079 Yes log GDP >> log Seel C I 6.47 0.000 Yes log Seel C >> log GDP II 8.05 0.08 Yes log GDP >> log Seel C II 6.60 0.000 Yes log Seel P >> log GDP III 4.907 0.086 Yes log GDP >> log Seel P III 0.33 0.936 No Table 3. Granger Causaliy Tess (Singapore) Null Hypohesis: Non-causaliy Mehod χ P-value Accep Causaliy? log Seel C >> log GDP III 4. 0.50 No log GDP >> log Seel C III 0.89 0.067 Yes log Seel P >> log GDP I 8.48 0.04 Yes log GDP >> log Seel P I 5.303 0.07 Yes log Seel P >> log GDP II 3.65 0.0 Yes log GDP >> log Seel P II 3.896 0.008 Yes Table 4. Granger Causaliy Tess (Thailand) Null Hypohesis: Non-causaliy Mehod χ P-value Accep Causaliy? log Seel C >> log GDP III 4.403 0.036 Yes log GDP >> log Seel C III 0.087 0.769 No log Seel P >> log GDP III 8.4 0.00 Yes log GDP >> log Seel P III.89 0.9 No Table 5. Granger Causaliy Tess (Vienam) Null Hypohesis: Non-causaliy Mehod χ P-value Accep Causaliy? log Seel C >> log GDP I.97 0.754 No log GDP >> log Seel C I.839 0.008 Yes log Seel C >> log GDP II 0.644 0.75 No log GDP >> log Seel C II 3.79 0.50 No log Seel P >> log GDP I 7.36 0.06 Yes log GDP >> log Seel P I 5.40 0.4 No log Seel P >> log GDP II 3.969 0.37 No log GDP >> log Seel P II.566 0.457 No
DO STEEL CONSUMPTION AND PRODUCTION CAUSE ECONOMIC GROWTH?: 3 3.4. Implicaion Based on he previous Granger causaliy es, we idenify he presence of he Granger causaliy beween seel consumpion and economic growh, and seel producion and economic growh. The Granger causaliies boh running from seel consumpion o economic growh and seel producion o economic growh are idenified in four counries: Malaysia, he Philippines, Singapore, and Thailand. Also we can see he Granger causaliies running from economic growh o seel consumpion in Malaysia, he Philippines, and Vienam. For Singapore, he Granger causaliies running from economic growh o seel producion is deeced as well. For Indonesia, only he Granger causaliy running from economic growh o seel producion is deeced. For Vienam, he causaliy is no idenified eiher in he relaionship beween seel consumpion and economic growh, and seel producion and economic growh. As menioned in secion, he seel demand in Souheas Asia is expeced o coninue o grow by around 5 percen, driven by he coninuing economic developmen and he srong demand in seel consuming secors. However, he seel producion in he area canno mee he demand. Our empirical resuls seems o imply ha an increase in seel producion, i.e., an increase in seel capaciy, may resul no only in providing enough seel o he demand secors, bu also in economic growh for Malaysia, he Philippines, Singapore, and Thailand. There is no causaliy in he case of Vienam and only one for Indonesia (from economic growh o seel producion) due o he lack of daa or/and he fac ha he seel indusry is no big enough o influence he economy. In erms of he indusrial srucures, Indonesia and Vienam have been more dependen on he non-manufacuring indusry, i.e., agriculural secor (ADB, 007). For example, for he manufacuring oupu o GDP raio, Vienam recorded jus.3 percen in 006, which is much lower han hose of he oher four counries (9.8 percen for Malaysia,.9 percen for he Philippines, 33.0 percen for Singapore, and 35. percen for Thailand). Furher, in erms of he labor force, he raio of labor force in agriculural secor o oal labor force in Indonesia and Vienam marked 44.5 percen and 5. percen in 006, respecively, which are much higher compared wih hose of he oher four counries (4.6 percen for Malaysia, 35.8 percen for he Philippines, 0.6 percen for Singapore, and 38.6 percen for Thailand). Thus, he difference of he indusrial srucure among he counries may be one reason for he differen resuls from our Granger causaliy es. 4. CONCLUSION This sudy examines he relaionship beween seel consumpion and economic growh, and seel producion and economic growh in six Souheas Asian counries by Granger causaliy es based on he exisence of a long-run equilibrium relaionship. For insance, from he es resuls, we idenify he Granger causaliies boh running from seel consumpion o economic growh and from seel consumpion o economic growh, are idenified in four counries: Malaysia, he Philippines, Singapore, and Thailand. Furher, our empirical resuls may provide policy implicaion ha he increase in seel producion, i.e., increase in seel capaciy, may resul in no only he providing enough seel o demand secors, bu also he economic growh in he case of Malaysia, he Philippines,
4 HEE-RYANG RA Singapore, and Thailand. The expansion of he seel producion capaciy may conribue o he economic growh according o our resuls. As menioned in secion, our Granger causaliy es may have drawbacks because i depends on he righ choice of he condiioning se and righ choice of sampling period. However, we may believe ha our es is sill useful because i is known ha if he daa are reasonably well described by a -dimensional (vecors) sysem, he Granger causaliy concep is mos sraighforward o hink abou and also o es. Briefly, he developmen of he seel indusry of Souheas Asia may conribue no only o meeing he demand bu also o economic growh. However, he developmen of he seel indusry would depend on he governmen s role and capabiliy o accomplish hese prerequisies in he near fuure. In order o make he domesic seel indusry grow, he governmen needs o provide adequae infrasrucure for he seel faciliies. For insance, elecric power, roads, rail road, and pors are essenial prerequisies. Especially, o induce foreign invesmen in he seel indusry, hese prerequisies should be prepared as soon as possible. The oher major deciding facor is he availabiliy of raw maerials. For he inegraed seel plan, iron ore and coking coal are needed o be provided adequaely. Also, he governmen needs o look a boh he mineral policy and he coal policy. I would include he developmen of suiable policies for he exploiaion of new mines, environmenal issues, ariff raes, rading, and he expor or impor of iron ore and coking coals for he developmen of he seel indusry. REFERENCES Asian Developmen Bank, Counry repor for Indonesia, Malaysia, he Philippines, Singapore, Thailand, and Vienam, each year. Choi, D.Y., 007, The economic impac of seel indusry on he Korea economy by inpuoupu analysis, POSRI Business Review, Vol. 7(), pp.9-45. (in Korean) Dickey, D.A. and Fuller, W.A., 98, Likelihood raio saisics for auoregressive ime series wih a uni roo, Economerica, Vol. 49(4), pp.057-07. Engle, R.F. and Granger, C.W.J., 987, Co-inegraion and error-correcion: represenaion, esimaion and esing, Economerica, Vol. 55(), pp.5-76. Ghosh, S., 006, Seel consumpion and economic growh: Evidence from India, Resources Policy, Vol. 3, pp.7-. Granger, C.W.J., 969, Invesigaing causal relaions by economeric models and crossspecral mehods, Economerica, Vol. 37, pp.44-438., 980, Tesing for causaliy: A personal viewpoin, Journal of Economic Dynamics and Conrol, Vol., pp.39-35. Inernaional Iron and Seel Insiue, Seel Saisical Yearbook, each year. Johansen, S. 988, Saisical analysis of coinegraion vecors, Journal of Economic Dynamics and Conrol, Vol., pp.3-54. Johansen, S., 99, Esimaion and hypohesis esing of coinegraing vecors in Gaussian vecor auoregressive models, Economerics, Vol. 59(6), pp.55-580. Johansen, S. and Juselius, K., 990, Maximum likelihood esimaion and inference on coinegraion wih applicaion o money demand, Oxford Bullein of Economics and Saisics, Vol. 5(), pp.69-0. Kim, S.K. e al., 998, The economic impac of POSCO on he Korea economy by inpu-
DO STEEL CONSUMPTION AND PRODUCTION CAUSE ECONOMIC GROWTH?: 5 oupu analysis, Working paper, POSCO Research Insiue. (in Korean) Souh Eas Asia Iron and Seel Insiue, Newleer, Issued in July 007. Toda, H.Y. and Phillips, P.C.B., Vecor auoregression and causaliy: A heoreical overview and simulaion sudy, Economeric Reviews, Vol. 3, pp.59-85. Hee-Ryang Ra, Economis, Cener for Global Area Sudy, POSCO Research Insiue, POSRI Bldg., 47, Samseong-dong, Gangnam-gu, Seoul 35-878, Korea, Tel: (8-) 3457-89. Fax: (8-) 3457-8070. Email: heeryang@posri.re.kr