Energy Consumption and Economic Growth in South Asian Countries: A Co-integrated Panel Analysis

Transcription

1 World Academy of Scence, Engneerng and Technology Inernaonal Journal of Energy and Power Engneerng Energy Consumpon and Economc Growh n Souh Asan Counres: A Co-negraed Panel Analyss S. Noor and M. W. Sddq Dgal Open Scence Index, Energy and Power Engneerng wase.org/publcaon/7879 Absrac Ths sudy examnes causal beween energy use and economc growh for fve Souh Asan counres over perod Panel conegraon, M and FMOLS are appled for shor and long run esmaes. In shor run undreconal causaly from per capa GDP o per capa energy consumpon s found, bu no vce versa. In long run one percen ncrease n per capa energy consumpon end o decrease 0.3 percen per capa GDP..e. Energy use dscourage economc growh. Ths shor and long run relaonshp ndcae energy shorage crss n Souh Asa due o ncreased energy use coupled wh nsuffcen energy supply. Besde hs long run esmaed coeffcen of error erm sugges ha shor erm adjusmen o equlbrum are drven by adjusmen bac o long run equlbrum. Moreover, per capa energy consumpon s responsve o adjusmen bac o equlbrum and aes 59 years approxmaely. I specfes long run feedbac beween boh varables. Keywords Energy consumpon, Income, Panel co-negraon, Causaly. I. INTRODUCTION NERGY s he engne of economc growh, as many E producon and consumpon acves nvolve energy as basc npu. On producon sde, convenonally, economss snce Adam Smh have aled abou land, labor, and capal as major npus for economc acvy. These npus were sgnfcan ngredens of agraran economes of 7h and 8 h cenures. However, n 9 h cenury, he growh of ndusral naons has observed a fourh major npu ha s energy. On consumpon sde, n he Keynesan framewor where consumpon and ncome are sgnfcanly correlaed, smlarly energy consumpon n all forms drves economc producvy. I leads o economc growh and prospery whch ensures expanson of he economy n erms of hgher GDP and GDP per capa. The preemnen case of he prmary role of energy ha plays an mporan role n he economy was found n 970s energy crss. In s ol crss OAP resraned ol consgnmen o US and oher counres as hey suppored Israel n conflc. Resrced supply go much hgher prces S. Noor s wh he Economcs Deparmen, GC Unversy Lahore, Pasan as research Scholar (phone: ; e-mal: saeedanoor@gmal.com). M. W. Sddq s wh Economcs Deparmen, GC Unversy Lahore, Pasan as Assocae Professor (Ph No ; e-mal: mwsddq@gmal.com). whn few monhs. I nversely affeced he US economy by nfluencng pressng demand of energy by hgh cos and scarcy of ol. In US alone, n 974 GDP sharply urned down afer wo decades of seady growh. Moreover, a macro level economes have faced boh nflaonary and deflaonary mpacs on domesc economes []. Smlarly, n 2 nd ol crss proess severely dsruped he Iranan ol secor and producon beng grealy curaled and expors suspended. Laer, ol expors were agan sared under he new regme. These were nconssen and a a lower volume, whch pushed up prces. I resuled n very hgh prces han expeced under normal crcumsances [2]. Therefore, he 970s energy crss araced he analyss o nvesgae he relaonshp beween energy consumpon and economc growh, as was argued ha energy consumpon drecly causes GDP growh. Snce he end of 970s, many sudes [3], [4], [5] have been conduced o suppor he argumens whch sugges ha energy use s hghly posvely correlaed wh GDP growh. Bu emprcal evdence s varyng and conflcng abou drecon of causaly, wheher economc growh leads o energy consumpon or energy use booss up he GDP growh. From polcy perspecve, based on he drecon of causaly here are mporan polcy mplcaons. Because, he energy conservaon polcy may or may no be aen, depends on he drecon of causaly [6]. Undreconal causaly runnng from GDP o mples ha ncome s he nal recepor of exogenous shocs and equlbrum s resored hrough adjusmen n energy consumpon. These are less energy dependen economes and energy conservaon polces may be mplemened whou adverse effecs on economc growh and employmen [7]. On he oher hand, f causaly runs from energy consumpon o GDP hen mples ha he economy s energy dependen and energy consumpon measures may smulae economc growh [8]. Bdreconal causaly ndcaes ha boh energy consumpon and hgh level of economc acvy muually persuade each oher. Fnally, Nocausaly beween energy consumpon and economc growh referred as neuraly hypohess [9] mples ha energy conservaon measure may pursued whou affecng he economy. Souh Asa s mporan o world energy mares as experencng rapd energy demand growh. The prmary Inernaonal Scholarly and Scenfc Research & Innovaon 4(7)

2 World Academy of Scence, Engneerng and Technology Inernaonal Journal of Energy and Power Engneerng Dgal Open Scence Index, Energy and Power Engneerng wase.org/publcaon/7879 energy consumpon has ncrease nearly 64 percen beween 992 and 2002 n souh Asa. In 2002 souh Asa, accouned for approxmaely 4. percen of world commercal energy consumpon up from 2.8 percen n 992 [0]. Therefore, Souh Asan naons are facng rapdly ncreasng demand for energy coupled wh nsuffcen energy supply. They are energy-defc counres and fghng wh energy shorfalls n he form of recurren, cosly, and wdespread elecrcy ouages. Because of he economc and polcal effecs arsng from such shorfalls, mprovng he supply of energy, parcularly he supply of elecrcy, s an mporan prory of regonal governmens. To avod energy crss and effcen ulzaon of energy recourses, USAID Souh Asa Regonal Inave for Energy (SARI/Energy) program has been n operaon snce Afghansan and Pasan joned he SARI/Energy program n The USAID s an egh counry program ha promoes regonal energy secury hrough hree acves areas: () cross border energy rade, (2) energy mare formaon, and (3) regonal clean energy developmen. Through hese acves, SARI/Energy faclaes more effcen regonal energy resource ulzaon, mproves he envronmenal mpacs of energy producon, and ncreases regonal access o energy, wors oward ransparen and profable energy pracces. SARI/Energy counres nclude: Afghansan, Bangladesh, Bhuan, Inda, Maldves, Nepal, Pasan, and Sr Lana []. The followng secons of he paper se ou leraure revew, model, daa, emprcal resuls and concluson, polcy mplcaons. II. LITERATURE REVIEW The poneer sudy by Kraf and Kraf [3] found evdence of undreconal causaly from GNP growh o energy consumpon n case of he US for perod Yu and Cho [9], Yu and Hwang [2] and Erol and Yu[3] found no for US economy when hey used Granger mehod. However, Yu and Hwang [2] deeced ha energy consumpon negavely affeced employmen by usng Sm s echnques. Yu and Cho [9] also deduced causaly from GDP o energy n Republc of Korea, reversed n he case of he Phlppnes. Mash and Mash [7] found bdreconal causaly n Pasan. Aqeel and Bu [4] and Zahd [5] suppored exsence of undreconal causaly from GDP o energy consumpon whle nverse causaly evdence s found by Khan and Qayyum [6]. Zahd [5] also found undreconal causaly from GDP o energy consumpon for Bangladesh and SrLana. In Case of Inda Asafu-Ajaye [7] and Khan and Qayyum [6] found undreconal causaly from energy consumpon o ncome whle Neuraly hypohess s suppored by Zahd [5] Smlarly, Undreconal casualy from economc growh o energy consumpon s also found by Asafu-Adjaye [7] n Phlppne and Thaland, Wolde-Rafael [6] n Egyp, Gabon and Morocco, Yoo [8] and Tang [9] n Malaysa and Apergs and Payne [20] n sx Cenral Amercan Counres. There are mxed resuls from one sudy o anoher for ndvdual counres and regons. Thus, hs sudy s amed o nvesgae he core relaonshp beween per capa energy consumpon and per capa GDP for fve seleced Souh Asan counres. III. DATA AND VARIABLES The sudy uses panel daa consss of 5 Souh Asan counres (N=...5) for he perod 97 o 2006 (T=...3). The seleced counres are Bangladesh (BGD), Inda (IND), Nepal (NPL), Pasan (PAK) and SrLana (LKA). The varables used n he model are Gross domesc produc per capa (curren US $), per capa energy use (loon of ol equvalen), gross fxed capal formaon (curren US $) and oal labor force. The daa was sourced from World Developmen Indcaors (2008) [2]. IV. MODEL SPIFICATION The followng mulfacor neoclasscal producon funcon framewor proposed by Ghal and El-Saa [22] s used o fnd ou he relaon beween dfferen facors of producon (ncludng energy) and oupu: GDP = f { (, K, L ) } () The double Ln model s used o represen he growh model, so ha all varables can be explaned n growh erms. The panel verson of equaon () can be wren as follows: GDP = α + β β β (2) 0 + K + L + ε where, s Cross-Secons. denoes me perod. ε s he error erm wh he usual sascal properes whle α and β are coeffcens. I s dffcul o oban sgnfcan -rao or F-sascs for regressons whle esmang samples wh very few observaons. I s common problem of me-seres when annual daa s used for esmaons, snce here are very few annual seres whch exended more han ffy years. To overcome hs problem an effcen soluon s o pool daa no a panel of me seres from dfferen cross-seconal uns. Hence, use of panel daa has advanage ha can explo boh he cross seconal and me seres dmensons of daa and provde more effcen esmaons of parameers by consderng broader sources of varaon [23]. V. METHODOLOGY To esmae (2) sudy uses panel conegraon framewor. The conegraon analyss of panel daa consss of four seps: A. Panel Un Roo Tess The purpose of un roo ess s o chec he saonary of daa. Four dfferen sascs proposed by Phllps-Perron [24], Maddala and Wu [25], Levn e al. [26] and Im e al. [27] are adoped each clamng more power agans he null of un roo n a varable. Inernaonal Scholarly and Scenfc Research & Innovaon 4(7)

3 World Academy of Scence, Engneerng and Technology Inernaonal Journal of Energy and Power Engneerng Dgal Open Scence Index, Energy and Power Engneerng wase.org/publcaon/7879 B. Conegraon Tess Conegraon es s prmarly used o nvesgae he problem of spurous regresson, whch exss only n he presence of non-saonary. Therefore afer applcaon of un roo ess, f each of he varables s saonary hen ssue arses wheher here exss a long-run equlbrum relaonshp beween he varables. For hs heerogeneous panel conegraon es developed by Pedron [28] s employed. I allows he conegraon vecor o vary across dfferen secons of he panel, and also for heerogeney n errors across cross-seconal uns. The Kao [29] es s also used o chec conegraon of daa. C. Panel Fully Modfed OLS esmaes The sudy esmaes he long run relaonshp by usng fully modfed ordnary leas square (FMOLS) echnque developed by Pedron [30] for heerogeneous conegraed panels. D. Granger Causaly Tes Fnally, once he panel conegraon s mplemened, a panel error correcon model (M) s esablshed o sudy shor-run and long-run causales beween GDP per capa and per capa. The wo-sep procedure of Engle-Granger [3] s performed as: frsly, esmaon of he long-run model for (2) n order o oban he esmaed resduals ε. Secondly, o esmae he Granger causaly model wh a dynamc error correcon: GDP K L θ λ ε θ GDP θ = j K 4 L + μ = θ + 2 λ 2 ε + θ Δ j 2 GDP + θ 22 + θ 23 K + θ Δ 24 L + μ 2 = θ 3 j+ λ 3ε 3 GDP K 34 L + μ 3 = θ 4 j+ λ 4ε 4 GDP K 44 L + μ 4 where, Δ denoes frs dfferencng. λ s he lag lengh and s chosen opmally for each counry usng a sep-down procedure up o a maxmum of wo lags. The sources of causaon beween GDP per capa and per capa are denfed by esng for he sgnfcance of he coeffcens of dependen varables n (3) and (4). For shorrun causaly, sudy es H 0 : θ 2, = 0 for all and n (3) or H 0 : θ 2, = 0 for all and n (4). Whle, he long-run causaly s esed by loong a he sgnfcance of speed of adjusmen λ, whch s he coeffcen of he error correcon erm, ε,-. The sgnfcance of λ ndcaes he long-run relaonshp of he conegraed process, and so movemens along hs pah can be consdered permanen. For long-run causaly, es H 0 : λ =0 for all n (3) or H 0 : λ 2 =0 for all n (3) (4) (5) (6) (4) s used. Smlarly, sources of causaon beween GDP per capa and oher wo varables (capal and labour) are denfed hrough (5) and (6). The raonal o adop hese ess s; he panel un roo and panel conegraon approach avods he problem of spurous regresson hrough nvesgang he order of negraon of he varables. If he varables are non-saonary, esng wheher he varables are conegraed. If he varables are conegraed, follows ha a ear combnaon of he nonsaonary varables wll be saonary. The panel conegraon framewor also has he advanage ha because ess wheher here s a long-run relaonshp beween he varables or no. I allows dsngushng beween shor-run and long-run mpacs, whch s no possble wh convenonal panel daa analyss. VI. EMPIRICAL RESULTS A. Panel Un Roo Resuls Resuls of he panel roo ess are repored n able I. Is show ha all ess do no rejec he null hypohess of nonsaonary n he level form for all varables by consderng boh ndvdual effec and ndvdual ear rend effec. All ess rejec null-hypohess of non-saonary when varables are used a frs dfference. Ths mples ha seres of varables GDP per capa, per capa, K and L are negraed of order one, and I () process. These resuls are conssence wh noaon ha mos of macroeconomcs varables are nonsaonary a level, bu become saonary afer frs dfferencng [32]. Consequenly, as pooled daa s saonary a frs dfference, he seres follow sochasc rends and herefore can be conegraed as well. TABLE I PANEL UNIT ROOT TESTS RESULTS Tes Sascs LLC IPS MW(ADF) PP(Fsher) A: Level Model Specfcaon: Indvdual Effecs Ln GDP 3.45 (0.99) 7.02 (.00) 0.53(.00) 0.46 (.00) Ln 0.30 (0.99) 7.09 (.00) 0.43(.00) 0.44(.00) Ln K 0.09 (0.46) 2.2 (0.98).97(0.99).8(0.99) Ln L.53 (0.32) 4.8 (0.50).43 (0.29) 6.(0.49) Model Specfcaon: Indvdual Effecs and Indvdual Lnear Trends Ln GDP 0.66 (0.70) 2.3 (0.98) 4.74(0.90) 4.58 (0.9) Ln 0.07 (0.52).47 (0.98) 4.74(0.90) 4.58 (0.9) Ln K 2.05 (0.52).85 (0.3) 2.(0.02) 6.24 (0.79) Ln L 3.45 (0.99) 0.75 (0.22) 6.3(0.9) 5.96 (0.8) B: Frs Dfferences Model Specfcaon: Indvdual Effecs ΔLnGDP 6.55 (0.00) 7.76 (0.00) 74.(0.00) 08.(0.0) ΔLn 2.5 (0.00).3 (0.00) 07.(0.00) 09.9(0.0) ΔLn K 8.5 (0.00) 8.4(0.00) 78.2 (0.00) 84.6 (0.00) ΔLn L 5.46 (0.00) 5.03 (0.00) 53.5(0.00) 06.4(0.0) Model Specfcaon: Indvdual Effecs and Indvdual Lnear Trends ΔLn GDP 0.3(0.00).3 (0.00) 08.8 (0.00) 57.2(0.0) ΔLn 2.(0.00).5(0.00) 2.(0.00) 334.(0.0) ΔLn K 7.80(0.00) 7.50(0.00) -6.33(0.00) 67.4(0.00) ΔLn L 4.79(0.00) 9.28(0.00) 5. (0.00) 52.(0.0) Noes: LLC, IPS, MW and PP ndcaed he Levn e al. (2002), Im e al. (2003), Maddala and Wu (999) and Phllps-Perron (992) panel un roo and saonary ess. All ess examne he null hypohess of non-saonary Inernaonal Scholarly and Scenfc Research & Innovaon 4(7)

4 World Academy of Scence, Engneerng and Technology Inernaonal Journal of Energy and Power Engneerng Dgal Open Scence Index, Energy and Power Engneerng wase.org/publcaon/7879 (un roo). The four varables were grouped no one panel wh sample N= 5, T=35. The parenheszed values are he probably of rejecon. Probables for he MW (ADF Fsher Ch-square) and PP (Fsher ch-square) ess are compued usng an asympoc χ2 dsrbuon, whle he oher ess follow he asympoc normal dsrbuon. B. Conegraon Pedron seven ess based on resduals from (2) are repored n able II. Resuls show exsence of conegraon beween varables a 0 percen sgnfcan level as for all hree models hese rejec he null of no conegraon. Therefore, s concluded ha he varables are conegraed and a long run relaonshp exs for group as a whole and he members of he panel. Tes Sascs TABLE II HETEROGENEOUS PANEL COINTEGRATION RESULTS No Deermnsc Deermnsc Inercep and Trend Trend No Deermnsc Inercep and Trend Panel Conegraon Sascs ( Whn-Dmenson ) Panel v-sascs (0.099) (0.052) (0.084) Panel pp ype ρ- sascs (0.054) (0.056) (0.065) Panel pp ype - sascs (0.09) (0.07) (0.02) Panel ADF ype -sascs (0.098) (0.035) (0.073) Group Mean Panel Conegraon Sascs (Beween-Dmenson) Group pp ype ρ-sascs (0.023) 0.49 (0.075) (0.073) Group pp ype - sascs (0.022) (0.035) (0.094) Group ADF ype -sascs (0.097) (0.067) 0.45 (0.090) Noe: Ths able repors Pedron (2004) resdual conegraon ess. The number of lag runcaons used n he calculaon of sascs s fxed a. The null hypohess s no conegraon. Probably values are n parenhess. From he Kao resdual conegraon resul repored n able III, srong evdence s found o rejec he null hypohess of no conegraon a one percen level of sgnfcance. Therefore, s concluded ha here exs a srong evdence of long-run conegraon relaonshp beween he varables for he mulcounry panel. These resuls are conssen wh Lee [33], sadorsy [34] and Apergs and Payne [2]. TABLE III KAO RESIDUAL COINTEGRATION TEST RESULT Model Specfcaon : No Deermnsc Trend ADF -sascs -.64 (0.00) Noes: Ths able repors Kao (999) resdual conegraon es. The number of lag runcaons used n he calculaon of sascs s fxed a. The null hypohess s no conegraon. Probably values are n parenhess and compued usng asympoc Ch-square dsrbuon. C. FMOLS Esmaes The long run esmaes based on Pedron s group mean FMOLS esmaors for ndvdual and panel are repored n able IV. On per counry bass, he resuls are mx for all fve counres. Magnude of coeffcens denoes long-run elasces of oupu wh respec o energy consumpon, capal and labor. In long run, elascy of energy consumpon ranges from (SrLana) o 2.44(Inda). However for hree counres (Bangladesh, Inda and Nepal), coeffcen of per capa s sgnfcanly posve, ha s an ncrease n energy consumpon ends o promoe GDP per capa, whle remanng wo (Pasan and SrLana) have negave elascy whch mean an ncrease n per capa end o decrease GDP per capa n long-run. From he elasces can also be nferred ha due o ncrease n per capa growh goes down more n Pasan raher han n Sr Lana (.247 > 0.477). Moreover for ndvdual counres s noed ha magnude of per capa s larger han magnude of K and L, mples ha energy s an mporan ngreden for economc growh and srong energy polces are requred o aan susaned economc growh and ha may vary for ndvdual counres. TABLE IV FULLY MODIFIED OLS ESTIMATES (DEPENDENT VARIABLE IS LN GDP) Independen Varables Counres Inercep Ln Ln K Ln L BNG (2.29) (9.930)* (-.009) (-.929)*** IND (2.25) (0.97)* (.20) (-.929)* NPL (-7.979)* (.483)*** (0.009) (5.9)* PAK (0.280) (-9.502)* (4.793)* (-.867)*** LKA (-4.47)* (-8.807)* (5.79)* (0.09)* Panel Group (8.50)* (-2.9)** 0.60 (4.43)* (-3.)* Noes: The number of lag runcaons used n calculaon s 2. The values n parenheses denoe he -sascs followng a sandard normal dsrbuon. Asers *, ** and *** ndcae sascal sgnfcance a %, 5% and 0% levels, respecvely. The coeffcen of capal s posve and sgnfcan for 2 counres ou of 5. Only for Pasan and SrLana posvely affecs GDP per capa whle for remanng counres no long-run relaonshp s found. The sgn of labor s negave for Bangladesh, Inda and Pasan whle posve for Nepal and SrLana only. For panel resuls of regresson equaon wh GDP per capa as dependen varable show ha coeffcens of per capa and L are negave and sascally sgnfcan and coeffcen of K s posve and sgnfcan. These resuls sugges ha one percen ncrease n energy consumpon per capa ends o decrease 0.3 percen GDP per capa; mples ha per capa dscourage GDP per capa n he long-run. I may be because he Souh Asan naons are poor n energy secor. Ther energy producon capacy s unable o mee rsng demand of energy. Increase n GDP enlarges economy wh he expanson of dfferen secors (Agrculure, ndusres, household ec.). Energy consumpon also goes up n dfferen forms n growng secors where s used as basc npu. Therefore ncrease n energy consumpon coupled wh nsuffcen energy supply lead o shorage, energy crss and evenually power-cu off. Tha energy crss negavely effecs Inernaonal Scholarly and Scenfc Research & Innovaon 4(7)

5 World Academy of Scence, Engneerng and Technology Inernaonal Journal of Energy and Power Engneerng Dgal Open Scence Index, Energy and Power Engneerng wase.org/publcaon/7879 economc growh and hence, an ncrease n energy consumpon end o decrease economc growh. The coeffcen of labor for whole regon s also negave ha ndcae a negave effec of labor on GDP per capa. I may be due o bran-dran, uneducaed, unslled and low producvy of labor force. Moreover resuls show ha labor ends o decrease GDP per capa more han per capa. Alhough hs may be due o he fac ha n developng counres, labor ends o be abundan and relavely cheaper. These resuls are smlar wh he fndngs of Sar and Soyas [35]. Capal plays a sgnfcan and posve role n GDP per capa ha one percen ncrease n capal rse GDP per capa by 0.6 percen. I s conssen wh heory ha more capal accumulaon ensures he economc growh. D. Granger Causaly Tes Resuls The shor-run and long-run panel Granger causaly resuls from esmang panel based error correcon model se ou n (3), (4), (5) and (6) are repored n Table: V. The opmal lag lengh s obaned (2) by usng Schwarz Informaon Crera (SIC). Dependen Varable ΔLn GDP --- ΔLn ΔLn K ΔLn L TABLE V PANEL GRANGER CAUSALITY RESULTS Source of Causaon (Independen Varables) Shor- run Long-run ΔIn GDP ΔLn ΔIn K ΔLn L M - Χ 2 -sascs (p-value) Coeffcen (-rao) (0.952) (0.255) (0.57) (-4.502*) (0.028)** (0.83) (0.402) (-2.24*) (0.623) (0.497) (0.023)** (2.933*) (0.293) (0.236) (0.732) (.540) Noes: Wald Ch-square ess repored wh respec o shor-run changes whle error erm coeffcen as long-run changes. Parenheses values are he probably of rejecon of Granger non-causaly. Aserss * and ** ndcae sascally sgnfcan a % and 5% level respecvely. Resuls sugges ha GDP per capa s causng per capa hrough error correcon erm bu no he vce versa. Ths mples ha here s sgnfcan undreconal causaon from GDP per capa o per capa n he shor-run. Moreover, here s exsence of undreconal causaly from labor o capal, whle among oher varables no sascally sgnfcan causal relaonshp s found. In long-run, for GDP per capa equaon, he esmaed coeffcen on error correcon erm s negave and sascally sgnfcan. I shows ha shor-erm adjusmens o equlbrum are drven by adjusmen bac o long-run equlbrum hrough error correcon erm. I aes 59 years (calculaed as he nverse of he absolue value of coeffcen on he error correcon erm). For per capa equaon, he esmaed coeffcen on error correcon erm s negave and sascally sgnfcan ndcang ha per capa energy consumpon s responsve o adjusmens bac o equlbrum. I specfes long-run feedbac beween GDP per capa and per capa. VII. SUMMARY AND POLICY IMPLICATIONS The objecve of sudy s o nvesgae causal relaonshp beween energy consumpon and economc growh by applyng a mulvarae model n fve Souh Asan counres over perod Recenly developed panel conegraon echnque s appled whle long run relaonshp s esmaed usng fully-modfed ordnary leas square. The fndngs of he sudy have mporan polcy mplcaons. A undreconal causaly s found from GDP per capa o per capa n shor-run. Whle, negave relaon exss beween he wo n he long-run. Thus, accordng o he resuls, Souh Asan counres are benefed o adop energy conservaon polcy o avod he shorage of energy. Oherwse energy crss may serously endanger he developmen of economes n he long-run. Thus, s que mporan ha along wh he hgh energy consumpon, he energy producon rases o ha exan o ensure susaned economc growh. To say away from he energy crss here should be some shor-erm and long-erm plannng, modfed polces and enormous nvesmen needed. Avod he mpor of crude ol a a massve cos of foregn reserve. Souh Asan counres are rch n hydro resource of energy. Therefore, here s need o buld new dams, nsallaon of wnd power plan and dal energy projecs o explore he energy producon. Moreover, polcy orenaon needs a drasc modfcaon o ulze endogenous resources. There mus be shor-erm and longerm decsons regardng he sae of naural resources of he economy. REFERENCES []. Ienberry, G.J. (986). The rony of sae srengh: Comparave responses o he ol shocs n he 970s. Inernaonal Organzaon, 40 (), [2]. Tme Magazne, hp:// [3]. Kraf, j., and Kraf, A. (978). On he relaonshp beween energy and GNP. Journal of Energy and Developmen, 3, [4]. Aarca, A.T., and Long, T.V. (979). Energy and employmen: a me seres analyss of he causal relaonshp. Resources and Energy, 5, [5]. Aarca, A.T., and Long, T.V. (980). On he relaonshp beween energy and GNP: a re-examnaon. Journal of Energy and Developmen, 5, [6]. Wolde-Rufael, Y. (2006). Elecrcy consumpon and economc growh; a me seres experence for 7 Afrcan counres. Energy Polcy, 34, [7]. Mash, A. M. M., and Mash, R. (996). Elecrcy consumpon, real ncome and emporal causaly: resuls from a mul-counry sudy based on conegraon and error correcon modeg echnques. Energy Economcs, 8, [8]. Jumbe, C. B. L. (2004). Conegraon and causaly beween elecrcy consumpon and GDP: emprcal evdence from Malaw. Energy Economcs, 26, [9]. Yu, S.H., and Cho, J.Y. (985). The causal relaonshp beween energy and GNP: an nernaonal comparson. Journal of Energy and Developmen, 0, [0]. Energy Informaon Admnsraon (EIA), hp:// Inernaonal Scholarly and Scenfc Research & Innovaon 4(7)

6 World Academy of Scence, Engneerng and Technology Inernaonal Journal of Energy and Power Engneerng Dgal Open Scence Index, Energy and Power Engneerng wase.org/publcaon/7879 []. Souh Asan Regonal Inave for Energy (SARI/ENERGY), hp:// [2]. Yu, E.S.H., and Hwang, B-K. (984). The relaonsho beween energy and GNP: furher resuls. Energy economcs, 6(3), [3]. Erol, U., and Yu, E.S.H. (987). Tme seres analyss of he causal relaonshp relaonshp beween US energy and employmen. Resources of Energy, 9, [4]. Aqeel, A., and Bu, M. (200). The relaonshp beween energy consumpon and economc growh n Pasan. Asa-Pacfc Developmen Journal, 8(2), 0-0. [5]. Zahd, K. (2008). Energy-GDP relaonshp: a casual analyss for he fve counres of Souh Asa. Appled Economercs and Inernaonal Developmen, 8(), [6]. Khan, M, A., and Qayyum, A. (2006). Dynamc modeg of energy and growh n Souh Asa, Worng paper. Pasan Insue of Developmen Economcs. [7]. Asafu-Adjaye, J. (2000). The relaonshp beween energy consumpon, energy prces and economc growh: me seres evdence from Asan developng counres. Energy Economcs, 22, [8]. Yoo, S.H. (2006). The causal relaonshp beween elecrcy consumpon and economc growh n he ASEAN counres. Energy Polcy, 34 (8), [9]. Tang, C.F. (2008). A re-examnaon of he relaonshp beween elecrcy consumpon and economc growh n Malaysa. Energy polcy, 36, [20]. Apergs, N., and Payne, J.E. (2009). CO 2 emssons, energy usage and oupu n ceneral Amerca. Energy Polcy, 37, [2]. World Ban. (2008). World Developmen Indcaors [CD Rom 2009]. World Ban, Washngon, D.C. [22]. Ghal, K. H., and El-saa, M.I.T. (2004). Energy use and oupu growh n Canada: a mulvarae conegraon analyss. Energy Economcs, 26, [23]. Aserou, D. (2006). Panel daa economercs. In, Appled economercs: a modern approach usng Evews and Mcrof (s ed, pp ). Palgrave Macmllan, New Yor. [24]. Phllps, P. (992). Hyper-conssen esmaon of a un roo n me seres regresson. Cowles Foundaon Dscusson Papers, No [25]. Maddala, G.S., and Wu. S. (999). A comparave sudy of un roo ess wh panel daa and a new smple es. Oxford Bullen of Economcs and Sascs, 6, [26]. Levn, A., Ln, C.F., and Chu, C.S. (2002). Un roo ess n panel daa: asympoc and fne-sample properes. Journal of Economercs, 08, 24. [27]. Im, K. S., Pesaran, M. H., and Shn, Y. (2003). Tesng for un roos n heerogeneous panels. Journal of Economercs, 5, [28]. Pedron, P. (2004). Panel conegraon: asympoc and fne sample properes of pooled me seres ess wh an applcaon o PPP hypohess: new resuls. Economerc Theory, 20(3), [29]. Kao, C. (999). Spurous regresson and resdual based ess for conegraon n panel daa. Journal of Economercs, 90 (), 44. [30]. Pedron, P. (2000). Fully modfed OLS for heerogeneous conegraed panels, nonsaonary panels, panel conegraon and dynamc panels. Advances n Economercs, 5, [3]. Engle, R.F., and Granger, C.W.J. (987). Conegraon and error correcon: represenaon, esmaon, and esng. Economerca, 55, [32]. Nelson, C.R., and Plosser, C.I. (982). Trends and random wals n macroeconomc me seres: some evdence and mplcaons. Journal of Moneary Economcs, 0(2), [33]. Lee, C.C. (2005). Energy consumpon and GDP n developng counres: a conegraed panel analyss. Energy Economcs, 27, [34]. Sadorsy, p. (2009). Renewable energy consumpon and ncome n emergng economes. Energy Polcy, 37(0), [35]. Sar, R., and Soyas, U. (2007). The growh of ncome and energy consumpon n sx developng counres. Energy Polcy, 35, Inernaonal Scholarly and Scenfc Research & Innovaon 4(7)