Energy Consumption- Growth Nexus in Saarc Countries: Using Cointegration and Error Correction Model

Transcription

1 Energy Consumpon- Growh Nexus n Saarc Counres: Usng Conegraon and Error Correcon Model RUDRA PRAKASH PRADHAN Vnod Gupa School of Managemen, Indan Insue of Technology, Kharagpur, Inda E-mal: rudrap@vgsom.kgp.erne.n Absrac The paper explores he nexus beween energy consumpon (ol and elecrcy) and economc growh n he fve SAARC counres over he perod Usng conegraon and Error Correcon Model (ECM), he paper fnds a undreconal shor run and long run causaly from ol consumpon o economc growh n Bangladesh and Nepal, a undreconal shor run and long run causaly from elecrcy consumpon o economc growh n Paksan and Sr Lanka, a undreconal shor run and long run causaly from economc growh o ol consumpon n Inda and Sr Lanka, and a undreconal causaly from economc growh o elecrcy consumpon n Inda and Nepal. I also fnds he bdreconal causaly beween elecrcy consumpon and economc growh n Bangladesh and beween ol consumpon and economc growh n Paksan. The paper a he end suggess ha energy and envronmenal polces should recognze he dfferences n he energy consumpon-growh nexus n order o manan susanable economc growh n he regon. Keywords: Energy Consumpon, Economc Growh, ECM. Inroducon Economc growh of a naon s closely relaed o s energy consumpon. Several sudes on energy economcs have examned hs relaonshp. Mehodologcally, here are wo approaches o race he nexus beween energy consumpon and economc growh. Frs, regresson approach (Pachaur, 977; Tyner, 978), where here s lle aenon o drecon of causaly and second, causaly approach (Odhambo, 2009; Bowden and Payne, 2009; Yuan e al. 2008), where here s hgh sress on he drecon of causaly. The presen paper, however, focuses he causaly approach only. The causal relaonshp beween economc growh and energy consumpon has been he prme focus of economss and polcy analyss snce he semnal work of Kraf and Kraf (978). The cenral ssue of hs causaly approach s wheher economc growh smulaes energy consumpon or s energy consumpon self a smulus for economc growh va ndrec channels of effecve aggregae demand, mproved overall effcency and echnologcal progress (Ghosh and Basu, 2006). There are wo relaed hypoheses on he nexus beween energy consumpon and economc growh: energy - led- growh hypohess and growh- led- energy hypohess. The nvesgaon of hese wo hypoheses s well esablshed n he developmen leraure, ye he oucomes reman nconssen and conroversal (see Table ). Ths may be due o varous srucural frameworks and polces followed by dfferen counres under dfferen condons and me perods. The conroverses are also due o dfferences n mehodology, varous proxes for energy consumpon and growh, presence of omed varables, varyng energy consumpon paerns, ec. (Apergs and Payne, 2009; Bala, 2008; Chou-We e al., 2008; Lee and Chang, 2008; Mahadevan and Asafu- Adjaye, 2007; Lee and Chang, 2007; Haem-J and Irandous, 2005). The conflcs are usually on he drecon of causaly and s long erm verses shor erm mpac on energy polcy. The leraure provdes four possble relaonshps beween energy consumpon and economc growh: undreconal causaly form energy consumpon o economc growh (.e. growh hypohess), undreconal causaly form economc growh o energy consumpon (.e. conservaon hypohess), b-dreconal causaly form energy consumpon o economc growh (.e. feedback hypohess) and no causaly beween energy consumpon and economc growh (.e. neuraly hypohess). The sudy on he drecon of causaly beween energy consumpon and economc growh has many polcy mplcaons. I no only provdes nsghs wh respec o he role of energy consumpon n economc growh bu also provdes a bass for dscusson of energy and envronmenal polces. For nsance, a undreconal causaly runnng from energy consumpon o economc growh mples ha economc growh s dependen on energy consumpon and a decrease n energy consumpon may resran economc growh (Yuan e al., 200; Zhang and Cheng, 2009; Narayan and Sngh, 2007). A number of explanaons may be se forh, f an ncrease n energy consumpon has a negave mpac on economc growh. For nsance, he suaon could be one n whch growng economy requres a decreasng amoun of energy consumpon as producon shfs owards less energy nensve servce secors. Moreover, he negave mpac of energy consumpon on real GDP could be arbued o eher excessve energy consumpon n unproducve secors of he economy, capacy consrans, or an 74

2 Vol. 4, No. 4; Aprl 200 effcen energy supply. A undreconal causaly form economc growh o energy consumpon, on he oher hand, mples ha he counry s no enrely dependen on energy consumpon for s economc growh. Hence, energy conservaon polces can be mplemened wh lle or no adverse effecs on economc growh. Tha means he conservaon hypohess s suppored f an ncrease n economc growh causes an ncrease n energy consumpon. However, s possble ha a growng economy consraned by polcal, nfrasrucural, or msmanagemen of resources could generae neffcences and he reducon n he demand for goods and servces, ncludng energy consumpon (Squall, 2007). In hs case, an ncrease n economc growh would have an adverse mpac on energy consumpon. The bdreconal causaly beween energy consumpon and economc growh mples ha a hgh level of economc growh leads o hgh level of energy demand and vce versa. Tha means hey are nerrelaed and may very well serve as complemens o each oher (Apergs and Payne, 2009). In such a case, an energy polcy orened owards mprovemens n energy consumpon effcency would no adversely affec real GDP. For nsance, energy consumpon polces amed a declnng energy use mus look for some channels o reduce consumer demand n order o mpede unfavorable effecs on economc growh. Such an aemp could be acheved hrough an approprae combnaon of energy axes and subsdes. Polcy makers should also encourage ndusres o adop echnology ha reduces polluon (Haem-J and Irandous, 2005). Fnally, he fndng of no causaly beween energy consumpon and economc growh, so called neuraly hypohess, mples ha energy conservaon polces do no affec economc growh (Asafu-Adjaye, 2000; Paul and Bhaacharya, 2004). In he lgh of above backdrop, presen paper seeks o nvesgae he causaly beween economc growh and energy consumpon n he fve SAARC counres, namely Bangladesh, Inda, Nepal, Paksan and Sr Lanka, durng The resdual of he paper s organzed as follows: Secon II descrbes daa se and economerc modellng. Secon III follows emprcal resuls and s dscusson hereof. The fnal secon offers concluson and polcy mplcaons. 2. Daa Se and Economerc Modellng Daa used n hs analyss are annual me seres on economc growh (GDP) and energy consumpon [.e. per capa elecrcy consumpon (EC) and per capa ol consumpon (OC)] for he fve SAARC counres [Bangladesh, Inda, Nepal, Paksan and Sr Lanka]. The daa are obaned from World Economc Oulook Daabase, Inernaonal Moneary Fund, Washngon. The Table provdes he summary sascs for each of he varables across he fve SAARC counres. I s o be noed ha all hese varables (GDP, EC and PC) are n naural logarhms so ha her frs dfferences approach he growh raes. The es for he energy-led-growh hypohess and growh-led-energy hypohess n he SAARC counres has been underaken by Granger causaly es. Engle and Granger (987) showed ha, f wo varables (say X and Y) are ndvdually negraed of order one [.e. I (I)] and conegraed hen here s possbly of a causal relaonshp n a leas one drecon. Tha means conegraon wh I () varables ndcae he presence and absence of Granger causaly bu does no ndcae he drecon of causaly. The vecor error correcon model s used o deec he drecon of causaly of long-run conegrang vecors. Moreover, Granger Represenaon Theorem ndcaes how o model a conegraed seres n a Vecor Auo Regressve (VAR) forma. VAR can be consruced eher n erms of level daa or n erms of her frs dfferences [I (0)] wh he addon of an error correcon o capure he shor run dynamcs. If he seres are I (I) bu no conegraed, he causaly es may gve some msleadng resuls unless daa are ransformed o nduce saonary. The whole process of causaly beween economc growh and energy consumpon can be performed n hree seps. Sep : Tes for un roo (.e. for order of negraon) n he per capa elecrcy consumpon, per capa ol consumpon and GDP o know he level of saonary. Sep 2: Tes for conegraon o know he exsence of long run equlbrum relaonshp beween energy consumpon and economc growh. Sep 3: Granger causaly es o assess he shor run conegraon and he drecon of causaly beween he wo varables. 2. Tes for Order of Inegraon The Augmened Dckey Fuller (ADF) and Phllps and Peron (PP) un roo es have been appled o know he order of negraon of varables. The esmaon procedure of hese wo ess s descrbed below: 75

3 ΔY p = α 0 + αy + β ΔY + ε... () Where Y s he varable of choce; s he frs- dfference operaor; α (for = 0 & ) and β (for =, 2 p) are consan parameers; and ε s a saonary sochasc process. To deermne he order of negraon of a parcular me seres varable, he equaon has o be modfed by ncludng second dfferences on lagged frs and p lags of second dfferences. Ths s as follows: 2 Δ Y p = η ΔY + μ Δ Y + ξ 2... (2) Where 2 s he second- dfference operaor; η and μ (for =, 2 p) are consan parameers; and ζ s a saonary sochasc process. The p lagged dfference erms are ncluded so ha he error erms (ε and ζ ) n he respecve equaons are serally ndependen. For saonary, he ADF es (Dckey and Fuller, 98) and PP es (Phllps and Perron, 988) are appled o equaons and 2 respecvely. The null hypohess are H 0 : α = 0 agans H 0 : α 0 for equaon and H 0 : η = 0 agans H 0 : η 0 for equaon 2 respecvely. Le d represens he number of mes ha a varable needs o be dfferenced n order o reach he saonary. In hs case, such a varable s sad o be negraed of order d and denoed by I (d). For example, f he varable s saonary a he level daa hen s sad o be negraed of order zero [I (0)]. Smlarly, f he varable s saonary a he frs dfference hen s sad o be negraed of order one [I (I)] and f he varable s saonary a he second dfference hen s sad o be negraed of order wo [I (2)] and so on. 2.2 Tesng for Conegraon The Conegraon echnque s appled o know he exsence of long run equlbrum relaonshp beween he wo varables. For he sascal pon of vew, a long run equlbrum relaonshp means he varables move ogeher over me so ha shor erm dsurbances from he long erm rend wll be correced. A lack of conegraon suggess ha such varable have no long run equlbrum relaonshp and n prncple, hey can wander arbrarly far away from each oher (Dckey e al., 99). Noe ha regresson among negraed seres s meanngful, f and only f hey nvolve conegraed varables. The conegraon es was frs nroduced by Engel and Granger (987) and hen developed and modfed by Johansen (988) and Johansen and Juselus (990). The paper used Johansen maxmum lkelhood (ML) approach o es he exsence of conegraon beween energy consumpon and economc growh. The echnque s used for wo specfc reasons. Frs, he echnque s usually mos relable one and s very useful for small sample properes. Second, several conegraon relaonshps can be esmaed by hs echnque. The conegraon echnque s mean o calculae wo sascs: race (T r ) sascs and he maxmum egenvalue (λ max ) sascs. The esmaon procedures of hese sascs are as follows: Le X be a (n X ) vecor of varables wh a sample of. Assumng X follows I () process, denfyng he number of conegrang vecor nvolves esmaon of he vecor error correcon represenaon: ΔX p p = A0 + X + A ΔX + ε... (3) Where, vecor ΔX and ΔX - are I () represenaon. The long run equlbrum relaonshp among X s deermned by he rank of Π (say r) s zero, hen equaon (3) can be ransferred o a VAR model of ph order and he varables n level do no have any conegrang relaonshp. If 0 < r < n, hen here are n X r marces of α and β such ha Π = α β.. (4) Where, he srengh of conegraon relaonshp s measured by α, β s conegrang vecor and β s I (0), alhough X are I (I). We have o esmae (A 0, A,.., A p-, Π) by maxmum lkelhood mehod, such ha Π can be wren as n (3). The esmaon of hese parameers follows wo-sep procedures. Frs, regress ΔX on ΔX -, ΔX -2,., ΔX -p+ and oban he resduals û. Second, regress X - on ΔX -, ΔX -2,., ΔX -p+ and oban X 76

4 Vol. 4, No. 4; Aprl 200 he resduals ê. Havng obaned he resduals û and ê, we can form he varance-covarance marces. Ths s as follows: uu ee = T T = = T T = uˆ uˆ eˆ eˆ... (5)... (6) T = uˆ eˆ ue... (7) T = The maxmum lkelhood esmaor of β can be obaned by solvng: λ ˆ ˆ INV ( ˆ ) ˆ = 0... (8) ee eu uu Where he egenvalues are ˆ λ ˆ λ... ˆ > 2 > > λn and he normalzed conegrang vecors are ˆ β = ( ˆ β, ˆ β,..., ˆ 2 β n ), such ha ˆ β ˆ ˆ ee β = I. The null hypohess can be esed a r = h (for 0 h < n) agans he alernave hypohess of r = n. Ths s obaned from he followng race sascs: λ rac = L A L 0... (9) Where, L L 0 A Tn = log 2 Tn = log 2 h Tn T T ( 2 ) Log ˆ Log( ˆ ) 2 2 uu 2 ue n Tn T T ( 2 ) Log ˆ Log( ˆ ) 2 2 uu 2 n T and L L = Log( ˆ ) Ths can be furher modfed o ˆ + A 0 2 h+ n ( L L ) = T Log( ˆ ) A 0 r+ λ... (0) λ... () λ... (2) 2 λ... (3) Where, λ r,.. λˆ p are he esmaed egenvalues. The null hypohess o be esed s ha here are a mos r conegrang vecors. Tha s he number of vecors s less han or equal o r, where r = 0,, or 2,.,n. In each case, he null hypohess s esed agans he general alernave hypohess. The maxmum egenvalue (λ max ) sascs can be represened as follows: ( ˆ λ ) λ TLog... (4) max = r+ The null hypohess of r conegrang vecors s esed here agans an alernave hypohess of r + conegrang vecors. Hence he null hypohess r = 0 s esed agans he alernave r =, r = agans he alernave r = 2, and so forh. I s well known ha he conegraon ess are very sensve o choce of lag lengh. The Schwarz Bayesan Creron (SBC) s used o selec he number of lags requred n he conegraon es. 2.3 Granger Causaly Tes There are hree dfferen models ha can be used o deec he drecon of causaly beween energy consumpon and economc growh, dependng upon he order of negraon and he presence/ absence of conegraon. Model : If he wo varables (say X and Y) are ndvdually negraed of order one [.e. I ()] and conegraed, hen Granger causaly es may use I () daa because of super conssency properes of esmaon. The Granger causaly model used n hs conex s as follows: 77

5 Y p q = + αy + j = η β X + ε Where H 0 : β j = 0 for j =,.., q s esed agans H A : β j 0 for a leas one j. X r s = + γ X + j = j j μ λ Y + ξ j j.. (5).. (6) Where H 0 : λ j = 0 for j =,..,s s esed agans H A : λ j 0 for a leas one j. The ε and ξ are random erms, whch are serally uncorrelaed wh zero mean and un varance. And η, μ, α, α 2,.., α p, β, β 2,, β q, γ, γ 2,, γ r, λ, λ 2,, λ s are he parameers o be esmaed. Model 2: If X and Y are I () and conegraed, he Granger causaly es can be appled o I (0) daa wh an error correcon erm. The model used n hs conex s as follows: ΔY p q α ΔY + β jδx j + δec j= = η + + ε.. (7) Where H 0 : β j = 0 for j =,.., q s esed agans H A : β j 0 for a leas one j. ΔX r s γ ΔX + λ jδy j + δec j= = μ + + η.. (8) Where H 0 : λ j = 0 for j =,..,s s esed agans H A : λ j 0 for a leas one j. The EC s error correcon erm, whch combnes long run and shor run dynamcs of conegraed varables owards he long run equlbrum. Model 3: If he daa are I () bu no conegraed, Granger Causaly es requres ransformaon of daa o make hem I (0). The Granger Causaly model n hs case s as follows: p ΔY = η + α ΔY + β ΔX + ε Where H 0 : β j = 0 for j =,.., q s esed agans H A : β j 0 for a leas one j. ΔX r q j = s j = j j j = μ + γ ΔX + λ ΔY + η j.. (9).. (20) Where H 0 : λ j = 0 for j =,..,s s esed agans H A : λ j 0 for a leas one j. 3. Resuls and Dscusson 3. Order of Inegraon Tes The frs and prme sep of he nexus beween energy consumpon and economc growh requres ha boh he varables should be negraed of same order, specfcally (). The ADF and PP ess are deployed for nvesgang he same. The esmaed resuls of hese wo ess are repored n Table 3. The p-values of ADF es and PP es represens ha he seres [economc growh (GDP), per capa ol consumpon (OC) and per capa elecrcy consumpon (EC)] are non-saonary n her levels bu found saonary n he frs dfference. Tha means all hese hree varables ha used n hs sudy are (). Ths s rue for all he fve SAARC counres, namely Bangladesh, Inda, Nepal, Paksan and Sr Lanka, durng Conegraon Tes Ths secon scans he long run equlbrum relaonshp beween [EC, GDP] and [OC, GDP]. Tha s o es wheher wo seres are conegraed. The Johansen conegraon es s deployed for he same. The esmaed resuls are repored n Tables 4 and 5. In boh he cases {[EC, GDP] and [OC, GDP]}, he conegraon es uses an nercep bu no rend. The esmaon procedure of Johansen es s very sensve o he choce of lag lengh. The Schwarz Bayesan Informaon creron (SBC) s used o fx he opmal lag lengh. The esmaed resuls beween per capa elecrcy consumpon and GDP [EC, GDP] ndcae ha he wo seres have one conegrang relaonshp (see Table 4). Ths s because he null hypohess of H 0 : r = 0 agans r s rejeced a % level. Ths s rue for all he fve SAARC counres. The Johansen s conegraon resuls beween per 78

6 Vol. 4, No. 4; Aprl 200 capa ol consumpon and economc growh [OC, GDP] also shown one conegrang relaonshp excep Sr Lanka, where here exss wo conegrang relaonshps (see Table 5). Hence, he superory of Johansen s approach compared o Engle Granger s resdual based approach les n he fac ha Johansen s echnque s capable of deecng mulple conegrang relaonshps among he varables (Asafu-Adjaye, 2000). The above resuls confrm ha here s long run equlbrum relaonshp beween energy consumpon and economc growh n he fve SAARC counres. 3.3 Granger Causaly Tes Havng found ha here s a long run equlbrum relaonshp beween energy consumpon and economc growh, gves an ndcaon ha here exss Granger causaly n a leas one drecon. To es he drecon of causaly, he Error Correcon Model (ECM) s deployed. The sgnfcance of ECM no only provdes an ndcaon of he drecon of causaly bu also enable o dsngush beween shor run and long run Granger causaly. I s o be noed ha he esmaon of ECM s also very lag specfc. The paper uses SBC for choosng he lag lengh n he ECM esmaon. The causaly n hs case s examned hrough he sgnfcance of coeffcen of he lagged error correcon erm and jon sgnfcance of he lagged dfferences of he explanaory varables by usng F-es. The esmaed resuls of ECM are repored n Table 6. The resuls confrmed ha here s undreconal causaly from per capa ol consumpon o economc growh (OC => GDP) n Bangladesh, boh n he shor run and long run. The long run causaly from per capa ol consumpon o economc growh s suppored by he coeffcen of lagged error correcon erm. On he conrary, he shor run causaly from per capa ol consumpon o economc growh s suppored by he F-sascs n he economc growh funcon, whch s also sascally sgnfcan a % level. The reverse causaly from economc growh o per capa ol consumpon s, however, rejeced by he lagged error correcon erm as well as F- sascs n he energy funcon, whch are all sascally nsgnfcan. Moreover, here s also bdreconal causaly beween per capa elecrcy consumpon o economc growh (EC <=> GDP) n he Bangladesh economy, boh n he shor run and long run. Ths s because boh he lagged error correcon erm and F-sascs are sascally sgnfcan n he economc growh funcon and energy funcon respecvely. The resuls for Inda reflec a undreconal causaly from economc growh o per capa ol consumpon (GDP => OC) and from economc growh o per capa elecrcy consumpon (GDP => EC), boh n he shor run and long run. Ths s hghly suppored by he coeffcens of lagged error correcon erm and F-sascs n he energy funcon and economc growh funcon, whch are sascally sgnfcan a 0% level. In he case of Nepal, we found a undreconal causaly from economc growh o per capa elecrcy consumpon (GDP => EC) and from per capa ol consumpon o economc growh (OC => GDP), boh n he shor run and long run. The coeffcens of lagged error correcon and F-sascs are also sascally sgnfcan n he energy funcon and economc growh funcon respecvely. Comng o Paksan economy, he resuls showed he bdreconal causaly beween per capa ol consumpon and economc growh (OC < = > GDP), boh n he shor run and long run. The resuls also showed a undreconal causaly from per capa elecrcy consumpon o economc growh (EC => GDP), boh n he shor run and long run. However, he reverse causaly from economc growh o per capa ol consumpon s rejeced by he lagged error correcon erm and F-sascs n he energy funcon, whch s all sascally nsgnfcan. The resuls of Sr Lanka economy reflec a undreconal causaly from per capa elecrcy consumpon o economc growh (EC => GDP) and from economc growh o per capa ol consumpon (GDP => OC). Ths s hghly suppored by coeffcens of lagged error correcon and F-sascs, whch are sascally sgnfcan n he economc growh funcon and energy funcon respecvely. A summary of he Granger causaly beween [EC, GDP] and [OC, GDP] s presened n Table Concluson Undersandng he nexus beween energy consumpon and economc growh s very val n he effecve desgn and mplemenaon of energy and envronmenal polces. In he case of Souh Asan Assocaon of Regonal Cooperaon (SAARC), he daa receves a grea deal of varaon across he counres, boh a he level of economc developmen (GDP) and energy consumpon [per capa elecrcy consumpon (EC) and per capa ol consumpon (OC)]. The SAARC s bascally domnaed by Inda and Paksan, boh n erms of GDP and energy consumpon. The presen sudy, however, explores he relaonshp beween energy consumpon and economc growh n a bvarae framework {[EC, GDP] and [OC, GDP]} by usng conegraon and Error Correcon Model (ECM). The fve SAARC counres namely Bangladesh, Inda, Nepal, Paksan and Sr Lanka are choosen for hs purpose and ha o avalably of daa durng The emprcal resuls frs 79

7 confrmed he presence of long run equlbrum beween [EC, GDP] and [OC, GDP] n all he fve counres. The esmaed resuls of ECM found he followngs: ) A undreconal causaly runnng from per capa ol consumpon o economc growh (OC => GDP) n Bangladesh and Nepal for boh shor run and long run. 2) A undreconal causaly runnng from per capa elecrcy consumpon o economc growh (EC => GDP) n Paksan and Sr Lanka, boh n he shor run and long run. 3) A undreconal causaly runnng from economc growh o per capa ol consumpon (GDP => OC) Inda and Sr Lanka for boh shor run and long run. 4) A undreconal causaly runnng from economc growh o per capa elecrcy consumpon (GDP => EC) Inda and Nepal for boh shor run and long run. 5) The bdreconal causaly beween per capa ol consumpon and economc growh (GDP <=> OC) n Paksan for boh shor run and long run. 6) The bdreconal causaly beween per capa elecrcy consumpon and economc growh (GDP <=> EC) n Bangladesh, boh n he shor run and long run. Over and above, he paper does no fnd a defne concluson on he ssue of energy consumpon-growh nexus n he fve SAARC counres. Tha means he nexus beween energy consumpon and economc growh s very dvergen across he fve SAARC counres namely Bangladesh, Inda, Nepal, Paksan and Sr Lanka. The emprcal resuls, however, can gve varous polcy mplcaons for he SARRC, parcularly for energy and envronmenal polces. For counres where we found he evdence of a undreconal causaly runnng from energy consumpon o economc growh, reducng energy consumpon could lead o a fall n economc growh. Therefore, when any energy conservaon measures are underaken, consderable care should be aken no o adversely affec he economc growh. In counres, where here was economc growh-led energy consumpon, reducng energy consumpon may be mplemened wh lle or no adverse effec on economc growh. In conras, for counres where here exss a bdreconal causaly beween energy consumpon and economc growh, energy consumpon and economc growh can complemen each oher and energy conservaon measures may negavely affec economc growh (Wolde-Rufael, 2009). To conclude, he nexus beween energy consumpon and economc growh provdes a suable framework n he SAARC o boos her energy and envronmenal polces. Snce energy nfrasrucure s a bg deal o economc growh, a suable energy polcy should be mananed o boos economc growh and manan susanable economc developmen n he regon. A pecemeal approach o such a val ssue s of serous consequences and may affec economc growh n he long run. Therefore, respecve governmen has o look he same a any cos and wh a greaer cauon. References Abosedra, S., & Baghesan, H. (989). New Evdence on he Causal Relaonshp beween Uned Saes Energy Consumpon and Gross Naonal Produc. Journal of Energy Developmen, 4, Akarca, A. T., & Long, T. V. (980). On he Relaonshp beween Energy and GNP: A Reexamnaon. Journal of Energy Developmen, 5, Al-Iran, M. A. (2006). Energy-GDP Relaonshp Revsed: An Example from GCC Counres Usng Panel Causaly. Energy Polcy, 34, Apergs, N., & Payne, J. E. (2009). Energy Consumpon and Economc Growh n Cenral Amerca: Evdence from a Panel Conegraon and Error Correcon Model. Energy Economcs, 3, Aqeel, A., & Bu, M. S. (200). The Relaonshp beween Energy Consumpon and Economc Growh n Paksan. Asa Pacfc Developmen Journal, 8, 0-0. Asafu-Adjaye, J. (2000). The Relaonshp beween Energy Consumpon, Energy Prces and Economc Growh: Tme Seres Evdence from Asan Developng Counres. Energy Economcs, 22, Bala, M. (2008). Energy Consumpon and Economc Growh n Turkey durng he Pas wo Decades. Energy Polcy, 36, Bowden, N., & Payne, J. E. (2009). The Causal Relaonshp beween U. S. Energy Consumpon and Real Oupu: A Dsaggregaed Analyss. Journal of Polcy Modelng, 3,

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10 Vol. 4, No. 4; Aprl 200 Table. Bref Emprcal Work beween Economc growh and Energy Consumpon 83

11 84

12 Vol. 4, No. 4; Aprl 200 Table 2. Summary of Unvarae Sascs Noe: GDP: Gross Domesc Produc ($); EC: Per Capa Elecrcy Consumpon (kwh); OC: Per Capa Ol Consumpon (kg); Max: Maxmum; Mn: Mnmum; SD: Sandard Devaon; Skew: Skewness; Kur: Kuross. 85

13 Table 3. Resuls of Un Roo Tes Counry Varables ADF Tes PP Tes Concluson LD FD LD FD GDP * * U ~ I () Bangladesh EC * * U ~ I () OC * * U ~ I () GDP * * U ~ I () Inda EC * * U ~ I () OC * * U ~ I () GDP * * U ~ I () Nepal EC * * U ~ I () OC * * U ~ I () GDP * * U ~ I () Paksan EC * * U ~ I () OC * * U ~ I () GDP * * U ~ I () Sr Lanka EC * * U ~ I () Crcal Values OC * * U ~ I () Noe: ADF: Augmened Dckey Fuller Tes; PP Tes: Phlps and Perron Tes; LD: Level Daa; FD: Frs Dfference; GDP: Gross Domesc Produc; EC: Per Capa Elecrcy Consumpon; OC: Per Capa Ol Consumpon *: Sascally Sgnfcan; and U ~ I (): Inegraed of Order One. 86

14 Vol. 4, No. 4; Aprl 200 Table 4. Resuls of Johansen s Conegraon Lkelhood Rao Tes (Beween GDP and EC) Noe: r ndcaes he number of conegrang relaonshps; CV: Crcal values, whch are aken from MacKnnon- Haug- Mchels, 999. *: Indcaes level of Sascal Sgnfcance. 87

15 Table 5. Johansen s Conegraon Lkelhood Rao Tes (Beween GDP and PC) Noe: All noaons are defned earler. 88

16 Vol. 4, No. 4; Aprl 200 Table 6. Resuls of ECM Esmaon Counry Models Varables Error Correcon R 2 F Model EC * * Bangladesh GDP 3.72 * * Model 2 OC GDP 3.05 * * Model EC -2.6 * * Inda GDP Model 2 OC -2.5 * GDP Model EC * * Nepal GDP Model 2 OC GDP * * Model EC Paksan GDP 2.62 * * Model 2 OC * GDP 2.6 * * Model EC Sr Lanka GDP 2.62 * * Model 2 OC * GDP * Noe: All noaons are defned earler. 89

17 Table 7. The Drecon of Granger Causaly Tes 90