Is Renewable Energy Consumption Effective to Promote Economic Growth in Pakistan: Evidence from Bounds Testing and Rolling Window Approach

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1 MPRA Munch Personal RePEc Archve Is Renewable Energy Consumpon Effecve o Promoe Economc Growh n Paksan: Evdence from Bounds Tesng and Rollng Wndow Approach Shahbaz Muhammad and Muhammad Adnan Hye Qaz and Zeshan Muhammad COMSATS Insude of Informaon Technology, Lahore, Paksan, Insue of Busness Managemen (IOBM), arach, Paksan., Quad--Azam Unversy, Islamabad 20. Sepember 202 Onlne a hps://mpra.ub.un-muenchen.de/4608/ MPRA Paper No. 4608, posed. Ocober 202 3:22 UTC

2 Is Renewable Energy Consumpon Effecve o Promoe Economc Growh n Paksan: Evdence from Bounds Tesng and Rollng Wndow Approach Muhammad Shahbaz Deparmen of Managemen Scences, COMSATS Insue of Informaon Technology, Lahore, Paksan. Emal: shahbazmohd@lve.com UAN: , Fax: , Moble: Qaz Muhammad Adnan Hye Insue of Busness Managemen (IOBM), arach, Paksan. E-mal: qaz.adnan@obm.edu.pk Mohammad Zeshan School of Economcs, Quad--Azam Unversy, Islamabad, Paksan, Emal: zeshanqau.sb@gmal.com Absrac: The am of presen sudy s o re-nvesgae he mpac of renewable energy consumpon on economc growh by ncorporang capal and labor as poenal deermnans of producon funcon n case of Paksan. We have used he ARDL bounds esng and rollng wndow approach (RWA) for conegraon. The causaly analyss s conduced by applyng VECM Granger causaly and nnovave accounng approaches. The resuls showed ha all he varables are conegraed for long run relaonshp. Renewable energy consumpon, capal and labor boos economc growh. The causaly analyss ndcaed bdreconal causaly beween economc growh, renewable energy consumpon and capal over he perod of 972Q-20Q4. The sudy opens up new drecons for polcy makers o explore new sources of energy susan economc growh. eywords: Renewable Energy, Economc Growh, Rollng Wndow Approach

3 Inroducon Over he pas en years, ndusralzed counres have aaned sable energy consumpon paern. On he oher hand n developng counres, on average, are makng 5% annual growh n energy consumpon. The surprsng very s ha abou 8% of energy consumpon s grafed by fossl fuels. Lke oher developng counres n Paksan, prmary energy consumpon has rased 80% n precedng wo decades. I was 34 mllon oe n and reached o 6 mllon oe o us n Aborgnal naural gas, mpored ol, hydel power generaon, coal consumpon, and fnally nuclear power consue 45%, 35%, 2%, 6%, and 2% respecvely n energy. Convenonal energy s consumed mosly o saae he energy requremens n Paksan. Shekh [34] argues ha conrbues up o 99% n he oal energy consumpon. As he marke for he convenonal energy s much broad and exensve as compared o renewable energy, ha s why nvesors are lesser neresed n hs source of energy. I resuls n lesser share of renewable energy consumpon n oal energy blend and s a hrea o he fuure level of producon. Noneheless; Paksan Alernave Energy Board s dong a grea og n hs regard, ams ha produce 5% of oal energy hrough renewable energy n he nex 20 years (hall e al. [5]). Paksan has abundan poenal for renewable energy. Solar energy s a cheaper source of energy as compared o fossl fuels and Paksan has comparave advanage of producng energy wh. I doesn necessae any refnng nor does nvolve any ransporaon whch sors a cheaper and srkng subsue for fossl fuels. Noneheless, s ulzed n a very lmed way n Paksan e.g. hghways elephone exchanges, emergency 2

4 elephones, hospal ules ec. So far, a solar energy program for 00 home has been naed n Baluchsan whch can enlghen houses here. In addon o hs, he coaslne zones n Paksan are very rch for producon of wnd energy. I s proeced ha has lkely o produce energy of 50,000 MW. The landscapes of Norhern areas make a suable canddae for wnd energy also. I s esmaed ha 5000 vllage can be elecrfed f hs energy s made operaonal n Paksan. I s more approprae for mcro hydro plans whch can yeld energy of 300 MW. Canal sysem n Paksan arranges for a grea prospec for renewable energy. Jus Punab has he poenal o yeld energy of 350 MW. Along wh, here are also he prospec for he mcro plans whch can provde energy of 3 MW o small households and busness uns. As Paksan s an agraran economy, would be able o make avalable cheaper energy o s rural secor f makes proper use of bogas. I can yeld 7.25 mllon cubc meers energy n he form of bogas daly whch s suffcen o mee he cookng oblgaon of ffy mllon folks. Hence, s no he defcency of resources bu msmanagemen and laxy whch s makng our lves dffcul. Energy (renewable energy consumpon) plays a val role by expandng domesc producon. Ths mples ha energy consumpon s also an mporan deermnan of economc growh lke oher facors of producon such as labour and capal. Exsng energy leraure provdes four compeng hypoheses beween energy consumpon (renewable) and economc growh n case of Paksan. These compeng hypoheses are very mporan for polcy pon of vew. For nsance, reducons n energy would no We ook he help of varous repors, avalable on he offcal webse of Alernave Energy Developmen Board Governmen of Paksan, for hs sudy. 3

5 have adverse mpac on economc growh f economc growh Granger causes energy consumpon/ neural hypohess s found beween boh he varables. If bdreconal causaly s found boh he varables / energy consumpon Granger causes economc growh hen new sources of energy should be explored. Energy s an mporan smulus of producon process and energy mus Granger cause economc growh. An expanson n producon s lnked wh energy demand and economc growh mgh Granger cause energy consumpon. The man obecve of presen sudy s o nvesgae he relaonshp beween renewable energy consumpon capal, labour and economc growh n case of Paksan of usng Cobb-Douglas producon funcon over he perod of 972Q-20Q4. In case of Paksan, hs sudy conrbued o energy leraure by fve folds applyng: () he ARDL bound esng approach o conegraon for long run relaonshp; () he rollng wndow approach (RWA) o examne robusness of he ARDL resuls; () OLS and ECM for long run and shor run mpacs of renewable energy consumpon on economc growh; (d) he VECM Granger causaly approach s o examne causal relaonshp beween he varables and (v) nnovave accounng approach o (IAA) es he robusness of he VECM Granger causaly resuls. Our fndngs reveal ha conegraon beween renewable energy consumpon economc growh, capal and labor exss n case of Paksan. Furher, our emprcal evdence repors ha renewable energy consumpon has posve mpac on economc growh. Capal and labour also adds n economc growh. Furhermore, esmaed resuls ndcaed bdreconal causaly relaonshp beween renewable energy consumpon and economc growh. 4

6 II. Leraure Revew: Conemporaneous research on energy consumpon provdes a sream of nformaon regardng he drecon of causaly beween renewable energy consumpon and economc growh. All he counres have dfferen effecs of renewable energy consumpon; some counres repor renewable energy consumpon feches handsome conrbuon n economc growh whle for some counres hs source of energy s no suffcen. For example, Ewng e al. [2] assered ha renewable energy consumpon has lle mpac on economc growh n case of Uned Saes. In conras, Payne ([23], Uned Saes) and Twar ([35], Inda) affrmed ha renewable energy conrbues much n economc growh and sugges ha he share of renewable energy n oal energy blend mus rse over me. In he same spr bu wh panel daa 2, Twar [35] fnds posve response of GDP n response o renewable energy consumpon nnovave shock. In addon, Magnan and Vaona [9] also share he same vews for Ialy and advsed o dscourage renewable energy conservaon polces. Arfn and Syahruddn [6] repored ha adopon of energy conservaon polces would affec economc growh n Indonesa because causaly s runnng from renewable energy consumpon o economc growh. Table-: The summary of sudes on renewable energy consumpon-growh nexus No. Feedback hypohess Conservaon hypohess Growh hypohess Neuraly hypohess. Ewng e al. [2] Sar e al. [28] Payne [23] Payne [24] 2. Twar [34] Sadorsky [28] Bowden [8] Menegak [2] 3. Apergs and Payne [] Magnan and Vaona [9] Mahmood and Mahmood [20] 4. Apergs and Payne [2] Arfn and Syahruddn [6] 2 Ausra, Belgum & Luxembourg, Bulgara, Fnland, France, Germany, Greece, Republc of Ireland, Ialy, Norway, Porugal, Span, Sweden, Swzerland, Turkey and Uned ngdom 5

7 5. Apergs and Payne [3] 6. Apergs and Payne [4] 7. Twar [35] 8. Apergs and Payne [5] Noe: Growh hypohess represens un-dreconal causaly runnng from renewable energy consumpon o economc growh; Conservaon hypohess represens un-dreconal causaly runnng from economc growh o renewable energy consumpon; Feedback hypohess represens b-dreconal causaly; Neuraly hypohess represens no causaly. Oher han growh hypohess, emprcal sudes also exrac conservaon hypohess. For nsance, Sar e al. [29] share hs vew for Uned Saes whle Sadorsky [28] for a panel of counres 3, boh of he sudes fnd conservaon polces are more suable. On oher hand, Apergs and Payne [] worked wh a panel of OECD counres 4 and found he bdreconal causaly beween renewable energy consumpon and economc growh. These fndng are conssen wh Apergs and Payne [2]; who worked wh a panel of 3 Eurasan counres 5, Apergs and Payne []; for 6 Cenral Amercan counres 6, Apergs and Payne [4]; for a panel of 80 counres 7. Recenly, Apergs and Payne [5] nvesgaed 3 Argenna, Brazl, Chle, Chna, Colomba, Czech Republc, Hungary, Inda, Indonesa, orea, Mexco, Peru, Phlppnes, Poland, Porugal, Russa, Thaland, Turkey. 4 Ausrala, Ausra, Belgum, Canada, Denmark, France, Germany, Iceland, Ialy, Japan, Luxembourg, Neherlands, New Zealand, Norway, Porugal, Span, Sweden, Swzerland, Uned ngdom, Uned Saes. 5 Armena, Azerbaan, Belarus, Esona, Georga, azakhsan, yrgyzsan, Lava, Moldova, Russa, Taksan, Ukrane, Uzbeksan. 6 Cosa Rca, El Salvador, Guaemala, Honduras, Ncaragua, Panama. 7 Algera, Argenna, Ausrala, Ausra, Bangladesh, Belgum, Bolva, Brazl, Bulgara, Canada, Cameron, Chle, Chna, Comoros, Cosa Rca, Denmark, Domncan Republc, Ecuador, Egyp, El Salvador, Ehopa, Fnland, France, Gabon, Germany, Ghana, Greece, Guaemala, Gunea, Honduras, Hungary, Iceland, Inda, Indonesa, Iran, Ireland, Ialy, Japan, Jordan, enya, orea, Luxembourg, Madagascar, Malaw, Malaysa, Mal, Maurus, Mexco, Morocco, Mozambque, Neherlands, New Zealand, Ncaragua, Norway, Paksan, Panama, Paraguay, Peru, Phlppnes, Poland, Porugal, Romana, Senegal, Souh Afrca, Span, 6

8 he causaly beween renewable elecrcy consumpon and economc growh n case of Cenral Amercan counres namely Cosa Rca, El Salvador, Guaemala, Honduras, Ncaragua, Panama. They appled panel conegraon developed by Larsson e al. [6] and panel VECM Granger causaly approach. Ther resuls ndcaed he conegraon beween he varables. Renewable elecrcy consumpon adds n economc growh and feedback hypohess exss beween renewable elecrcy consumpon and economc growh n long run and renewable elecrcy consumpon Granger causes economc growh n shor run. In conras, some sudes fnd no causal relaonshp beween renewable energy consumpon and economc growh. Payne [24] repors no causal relaonshp beween renewable energy consumpon and economc growh for Uned Saes. A same nference s drawn by Menegak [2] for a panel of 27 European counres 8. Table- represens he summary of emprcal sudes regardng relaonshp beween renewable energy consumpon and economc growh. Mahmood and Mahmood [20] esed he drecon of causal relaon beween renewable energy consumpon and economc growh n 7 Asan developng economes 9. Ther fndngs valdaed he feedback hypohess for Bangladesh, conservaon hypohess for Inda, Iran, Paksan, and Syran Arab Republc and neural hypohess beween boh varables s confrmed for Sr Lanka. Sr Lanka, Sudan, Swazland, Sweden, Swzerland, Syra, Thaland, Tunsa, Turkey, Uganda, Uned ngdom, Uned Saes, Uruguay, Venezuela, Zamba. 8 Belgum, Bulgara, Czech Rep., Denmark, Germany, Esona, Ireland, Greece, Span, France, Ialy, Cyprus, Lava, Lhuana, Luxemburg, Hungary, Neherland, Ausra, Poland, Porugal, Romana, Slovena, Slovaka, Fnland, Sweden, U, Norway. 9 Inda, Iran, Paksan, Syran Arab Republc, Bangladesh, Jordan and Sr Lanka 7

9 III. Modelng Framework and Daa Collecon The purpose of curren nvesgaon s o lnk he relaonshp among renewable energy consumpon and economc growh n case of Paksan usng quarerly daa over he perod of Ths sudy employ Cobb-Douglus producon funcon o analyss he correlaon beween renewable energy consumpon and economc growh ncludng capal and labour as addonal facors of producon. Commonly, he equaon of producon funcon s as follows: 3 2 u AR L e () where s domesc oupu n real erms; R, and L ndcae renewable energy consumpon, real capal and labor respecvely. A shows level of echnology o be ulzed n he counry and e s he error erm supposed o be dencally, ndependenly and normally dsrbued. The reurns o scale s assocaed wh renewable energy consumpon, capal and labour s shown by, and 2 3 respecvely. We have convered all he seres no logarhms n order o lnearze he form of nonlnear Cobb- Douglus producon. The man reason s ha lnear specfcaon does no seem o provde conssen resuls and no helpful for polcy makng purpose (Shahbaz e al. [33]; Shahbaz and Ferdun [30]). To cover hs problem, we use log-lnear specfcaon o nvesgae relaonshp beween renewable energy consumpon and economc growh n case of Paksan. Ehrlch [0, ], Cameron [9] and Layson [7] recommended peran log-lnear 8

10 modelng n aanng beer, conssen and effcen emprcal resuls 0. The log-lnear funconal form of Cobb-Douglus producon funcon s modeled as follows: log log A logr 2 log 3 logl u (2) The emprcal equaon o nvesgae he relaonshp beween renewable energy consumpon and economc growh s modeled keepng echnology consan. The loglnear specfcaon o assess he relaonshp beween renewable energy consumpon and economc growh s as follows: 0 R 3 4 L u (3) Where, R, and L s he logarhm of per capa real GDP, renewable energy consumpon (kg of ol equvalen per capa) per capa, capal use per capa and labor per capa respecvely. The long run assocaon among renewable energy consumpon and economc growh n case of Paksan s nvesgaed by applyng he ARDL bounds esng approach presens by Pesaran e al. [27]. The emprcal leraure ndcaes he varous conegraon approaches n order o es conegraon. Bu, he ARDL bounds esng approach s preferable due o s advanages over oher conegraon echnques. For nsance, order of negraon of he seres does no maer for applyng he ARDL bounds esng f no varable s found o be saonary a I(2). Ths approach s more approprae as compared o convenonal conegraon echnques for 0 See Shahbaz e al. [32] for more deals 9

11 0 small sample (Haug, [4]). Whn he general-o-specfc framework, unresrced verson of he ARDL chooses proper lag order o capure he daa generang procedure (see Shahbaz and Lean, [3] for more deals). Approprae specfcaon of he ARDL model s suffcen o smulaneously correc for resdual seral correlaon and endogeney problems (Pesaran and Shn, [26]). The equaon of unresrced error correcon model (UECM) o nvesgae he long-and-shor runs relaons beween he seres s followng: m m m s l l l q p L R T L R L R T (4) m m m s l l l q p L R T L R L R T R (5) m m m r k k k q p L R T L R L R T (6) m m m r k k k q p L R T R L L R T L (7)

12 Where Δ s he dfferenced operaor and s resdual erm n perod. The akake nformaon creron (AIC) s appled o decde suable lag lengh of he frs dfferenced varables followng Lükepohl [8]. The proper calculaed F-sasc depends upon he approprae lag order selecon of he seres o be ncluded n he model. The overall sgnfcance of he coeffcens of lagged varables s nvesgaed by applyng an F-es advanced by Pesaran e al. [27]. The null hypohess of no long run relaonshp beween he varables n equaon (3) s H : 0 agans he alernae hypohess of 0 R L long run relaonshp.e. H : 0. Two asympoc crcal values have been 0 R L generaed by Pesaran e al. [27]. These bounds are upper crcal bound (UCB) and lower crcal bound (LCB) are used o decde wheher varables are conegraed for long run relaonshp or no. If all he varables are saonary a I(0) hen we use LCB o es conegraon beween he seres. We use UCB o examne long run relaonshp beween he seres f he varables are negraed a I() or I(0) or I()/I(0). We compue he value of F-es applyng followng models such as F ( / R,, L), F R ( R/,, L), ( /, R, L) and ( L /, R, ) for equaons (4) o (7) respecvely. The decson of conegraon s F L aken wh he help of followng rules: f upper crcal bound (UCB) s less han our compued F-sasc hen we conclude conegraon. If compued F-sasc does no exceed lower crcal bound hen no conegraon among he varables. The decson abou conegraon beween he seres s quesonable f compued F-sasc s found beween LCB and UCB 2. Our decson regardng conegraon s nconclusve f calculaed F-sasc falls beween LCB and UCB. In such an envronmen, error F For deals see Shahbaz e al. [32] 2 If he varables are negraed a I(0) hen F-sasc should be greaer han lower crcal bound for he exsence of conegraon beween he seres

13 2 correcon mehod s an easy and suable way o nvesgae conegraon beween he varables. Afer he confrmaon of long run relaonshp among he varables hen n nex sep we nvesgae he causal relaon beween he seres. Granger, [3] saed ha once he varables are negraed a I() hen vecor error correcon mehod (VECM) s suable approach o es he drecon of causal lnk among he varables. Relavely, he VECM s resrced form of unresrced VAR (vecor auoregressve) and resrcon s leved on he presence of long run relaonshp beween he seres. All he seres are endogenously used n he sysem of error correcon model (ECM). Ths shows ha n such suaon, response varable s explaned boh by s own lags and lags of ndependen varables as well as he error correcon erm and by resdual erm. The VECM n fve varables case can be wren as follows: s p s r o r m l ECT L R (8) s p s r o r m l ECT R R (9) s p s n k k m l ECT L R (0) s p s n k k m l ECT R L L ()

14 Where ndcaes dfferenced operaor and u are resdual erms and assumed o be dencally, ndependenly and normally dsrbued. The sascal sgnfcance of lagged error erm.e. ECT furher valdaes he esablshed long run relaonshp beween he varables. The esmaes of ECT also shows he speed of convergence from shor run owards long run equlbrum pah n all models. The VECM s superor o es he causal relaon once seres are conegraed and causaly mus be found a leas from one drecon. Furher, he VECM helps o dsngush beween shor-and-long runs causal relaonshps. The sascal sgnfcance of esmae of lagged error erm.e. ECT wh negave sgn confrms he exsence of long run causal relaon usng he -sasc. Shor run causaly s ndcaed by he on 2 sascal sgnfcance of he esmaes of frs dfference lagged ndependen varables. For example, he sgnfcance of 0 mples ha 22, renewable energy consumpon Granger-causes economc growh and causaly runs from economc growh o renewable energy consumpon can be ndcaed by he sgnfcance of 22, 0. The same nference can be drawn for res of causaly hypoheses. Fnally, we use Wald or F-es o es he on sgnfcance of esmaes of lagged erms of ndependen varables and error correcon erm. Ths furher confrms he exsence of shor-and-long run causaly relaons (Shahbaz e al. [32]) and known as measure of srong Granger-causaly (Oh and Lee, [22]). 3

15 The daa span of presen sudy s 972Q-20Q4. The daa on renewable energy consumpon s colleced from SBP (200-). We have used world developmen ndcaors (CD-ROM, 20) o collec on daa on real GDP, real capal and labour respecvely. IV. Emprcal Resuls and Dscussons Ths sudy apples Ng-Perron un roo es n order o es he order of negraon. Ths es s superor and more powerful as compared o radonal un roo ess such ADF, DF-GLS, PPS ec. Baum, [7] saed ha s necessary condon o es he negrang order of he varables before applyng he ARDL bounds esng approach o conegraon relaonshp beween he seres. The assumpon of he ARDL bounds esng s ha he varables should be negraed a I(0) or I() or I(0)/I() and no seres s saonary a I(2). If any varable s negraed a I(2) hen he compuaon of he ARDL F-sasc becomes nvald. The resuls of Ng-Perron un roo es are shown n Table-2. The emprcal resuls ndcae ha all he seres are non-saonary a level and saonary a s dfference. So, all he varables are ndcaed order one.e. I(). Table-: Resuls of Ng-Perron Un Roo Tes Level Varables MZa MZ MSB MPT R

16 L s Dfference * R * * L Noe: * ndcaes he sgnfcance a he % level. The ARDL approach o conegraon checks he presence of long run lnk among varables. The lag selecon s very mporan n case of he ARDL approach o conegraon. Hence hs sudy uses akake nformaon creron (AIC) o choose suable lag lengh ha helps us n capurng he dynamc relaonshp o selec he bes ARDL model o esmae. The resuls of lag lengh are repored n Table-3 whch ndcaes ha lag 5 s approprae. The resuls of he ARDL bounds esng esng approach are repored n Table-4. The emprcal evdence ndcaes ha our compued F-sascs for F ( / R,, L), F R ( R/,, L) and F L ( L /, R, ) are 8.776, 4.06 and for economc growh, renewable energy consumpon and labour equaons respecvely. These F- sascs are greaer ha upper crcal bounds developed by Pesaran e al. [27] a per cen, 0 per cen and 5 per cen levels of sgnfcance. 5

17 Table-3: Lag Selecon Crera VAR Lag Order Selecon Crera Lag LogL LR FPE AIC SC HQ NA 2.24e e e e e *.24e-4* * * * e e e * ndcaes lag order seleced by he creron LR: sequenal modfed LR es sasc (each es a 5% level) FPE: Fnal predcon error AIC: Akake nformaon creron SC: Schwarz nformaon creron HQ: Hannan-Qunn nformaon creron 6

18 Table-4: Resuls of ARDL Conegraon Tes Varable R L F-sascs 8.776* 4.06*** *** Crcal values per cen level 5 per cen level 0 percen level Lower bounds Upper bounds Dagnosc ess Durbn-Wason Noe: *, ** and *** show he sgnfcance a 5% and 0% level respecvely. Table-4: Resuls of Johansen Conegraon Tes Hypohess Trace Sasc Maxmum Egen Value R = * * R * * R R Noe: * ndcaes sgnfcance a % level. Ths confrms he presence of conegraon beween economc growh, renewable energy consumpon, capal and labour n case of Paksan. Ths mples ha here s a long run relaonshp beween he varables over he perod of 972Q-20Q4. The robusness of he ARDL bounds esng approach s examned by applyng Johansen conegraon mulvarae conegraon approach. The resuls are repored n Table-5. We can nfer 7

19 ha here are wo conegrang vecors whch valdae he presence of long run relaonshp beween he varables. Ths enals ha he ARDL conegraon analyss s relable and robus. The nvesgaon of long run relaonshp beween he varables leads us o examne he margnal mpacs of renewable energy consumpon, capal and labor on economc growh n long run as well as n shor run. Table-5 deals wh long run margnal mpac of deermnans of economc growh. The resuls shown n Table-5 reveal ha posve relaonshp found from renewable energy consumpon o economc growh and sascally sgnfcance level s per cen. All else s consan, per cen rse n renewable energy consumpon spurs economc growh by per cen. The mpac of capal on economc growh s posve and s sascally sgnfcan a 5 per cen level of sgnfcan. eepng he oher hngs consan, per cen ncrease n capal use enhances domesc producon and hence economc growh by per cen. The relaonshp beween labour and economc growh s posve and s sascally sgnfcan a per cen level of sgnfcance. A per cen of economc growh s smulaed by per cen ncrease n labour, all else s same. Table-5: Long-and-Shor Run Analyss Dependen Varable = Long Run Resuls Varable Coeffcen Sd. Error Prob. value Consan *

20 R 0.603* ** L 0.400* Shor Run Resuls Consan * R * R 0.002** *** L * ECM * Dagnosc Tess Tes F-sasc Prob. value 2 SERIAL ARCH WHITE REMSA Noe: * and ** denoe he sgnfcan a % and 5% level respecvely. The lower segmen of Table-5 repors he resuls of shor dynamcs of renewable energy consumpon, capa and labour on economc growh. In shor span of me, renewable energy consumpon, lagged of renewable energy consumpon, capal and labour 9

21 conrbue economc growh sgnfcanly. The negave and sascally sgnfcan esmae of ECM corroboraes he esablshed long run relaonshp beween renewable energy consumpon, capal, labour and economc growh n case of Paksan. The resuls ndcae ha esmae of ECM I s sascally sgnfcan a per cen level of sgnfcance. Ths mples ha 3.4 per cen changes n economc growh are correced by devaons n shor run owards long run equlbrum pah n each quarer. In hs model, shor run devaons n economc growh ake 29 years and 6 monh o converge o long run equlbrum pah. The shor run dagnosc ess show ha no seral correlaon s found and same nerpreaon can be drawn for ARCH es. Our emprcal exercse ndcaes ha here s no problem of heerogeney and error erm has homogenous varance. The Ramsey rese es shows ha funconal for model s well specfed. Resuls of Rollng Regresson The rollng regresson model s used o evaluae he sably of he coeffcen of he ARDL model n he sample sze. Oher esmaon mehods assume ha he coeffcens of he varables reman consan over he sample sze. Bu n realy he economc condon canno remans consan and as resuls he economc ndcaor are flucuaed over me, and her coeffcens canno remans same (Pesaran and Tmmermann, [25]). Wh he help of rollng regresson approach, we can esmae he coeffcen of each observaon of he sample by seng he rollng wndow sze. If he economc ndcaors are changed overme so hs approach capures hs nsably. 20

22 Fg- Coeffcen of INPT and s wo*s.e. bands based on rollng OLS Q4 979Q2 98Q4 984Q2 986Q4 989Q2 99Q4 994Q2 996Q4 999Q2 200Q4 2004Q2 2006Q4 2009Q2 20Q4 Wndow sze 20 The fgure- o fgure-4 shows he rollng wndow resuls. The black ck lne represens he coeffcens and lgh black upper and lower band represens he coeffcens sascal level of sgnfcance (a 5%) The fg- shows he graph of nercep ha shows remans posve over he sample sze..5 F-g-2 Coeffcen of Ln R and s wo*s.e. bands based on rollng OLS Q4 979Q2 98Q4 984Q2 986Q4 989Q2 99Q4 994Q2 996Q4 999Q2 200Q4 2004Q2 2006Q4 2009Q2 20Q4 Wndow sze 20 The fgure-2 shows he graph of R coeffcens. I shows negave n 978Q 4 and 999Q 3 o 2006Q 2. In he remanng sample has posvely relaed o economc growh. 2

23 Fg-3 Coeffcen of Ln and s wo*s.e. bands based on rollng OLS Q4 979Q2 98Q4 984Q2 986Q4 989Q2 99Q4 994Q2 996Q4 999Q2 200Q4 2004Q2 2006Q4 2009Q2 20Q4 Wndow sze 20 Fg-3 represens he capal coeffcens. I shows ha capal s negavely relaed o economc growh. In he sample of 976Q 4 o 977Q 4, 997Q4 o 998Q 4, and 2005Q o 2006Q 4. 0 Fg-4 Coeffcen of Ln L and s wo*s.e. bands based on rollng OLS Q4 979Q2 98Q4 984Q2 986Q4 989Q2 99Q4 994Q2 996Q4 999Q2 200Q4 2004Q2 2006Q4 2009Q2 20Q4 Wndow sze 20 Fg-4 represens he labor force coeffcens. I shows ha capal s negavely relaed o economc growh, n he sample of 982Q 2-984Q 2, 989Q 3-990Q 2, and 99Q 2-993Q. In he remanng sample remans posve. 22

24 The VECM Granger Causaly Analyss Afer fndng long-and-shor runs affec of renewable energy consumpon, capal and labour on economc growh n case of Paksan over he perod of 972Q-20Q4. The drecon of causal relaonshp beween hese varables s nvesgaed by applyng he VECM Granger causaly approach. The approprae envronmenal and energy polcy o susan economc growh s dependen upon he naure of causal relaon beween he seres. In dong so, we appled he VECM Granger causaly approach o deec he causaly beween renewable energy consumpon, capal, labour and economc growh whch would help polcy makers n formulang comprehensve energy polcy o accelerae economc growh for long run. The Table-6 presens he emprcal evdence of long run and shor run causaly relaonshps. The resuls sugges ha feedback hypohess beween renewable energy consumpon and economc growh, renewable energy consumpon and labor, labor and economc growh, n case of Paksan for long run. The resuls ndcae ha causaly runnng from renewable energy consumpon o economc growh s sronger compared o causal relaonshp from economc growh o renewable energy consumpon. Ths shows ha governmen mus pay her aenon o launch comprehensve energy polcy n explorng new sources of renewable energy o susan economc growh. The R & D acves should be encouraged n energy secor. To overcome energy crss n he counry, governmen mus gve ncenve o foregn nvesors o nvesmen n energy secor of Paksan. The undreconal causaly exss from capal o renewable energy 23

25 consumpon, economc growh and labor. The feedback hypohess s also found beween economc growh and labor and, labor and renewable energy consumpon. In shor run, bdreconal causal relaonshp s found beween renewable energy consumpon and economc growh. The feedback hypohess also exss beween capal and economc growh. Economc growh and labor Granger cause each oher. The undreconal causaly s found runnng from labour o renewable energy consumpon. The sascally sgnfcance of on long-and-shor run causaly corroboraes our long run and shor run causal relaonshps beween he seres over he sudy perod of 972Q-20Q4. 24

26 Table-6: VECM Granger Causaly Analyss Dependen Varables Drecon of Causaly Shor Run Long Run Jon Long-and-Shor Run Causaly R L ECT, ECT R, ECT, ECT L, ECT * 4.369* ** * * * ** [0.0003] [0.0075] [0.0400] [-4.305] [0.0000] [0.0000] [0.0500] R 8.349* ** -0.64* 7.373* * 3.984** [0.0000] [0.364] [0.0320] [ ] [0.0000] [0.0059] [0.0043] 3.868* [0.007] [0.3949] [0.8058] L 3.994* * 2.440** 4.572* * * [0.0078] [0.442] [0.5950] [-3.832] [0.0484] [0.008] [0.002] [0.0073] Noe: * and ** show sgnfcan a % and 5% percen respecvely. 25

27 Exsng energy leraure reveals ha he Granger causaly approaches such he VECM Granger causaly es has some lmaons. The causaly es canno capure he relave srengh of causal relaon beween he varable beyond he seleced me perod. Ths weakens he relably of causaly resuls by he VECM Granger approach. To overcome hs problem, we appled nnovave accounng approach (IAA). The IAA s combnaon of varance decomposon mehod (VDM) and mpulse response funcon (IRF). The varance decomposon approach (VDM) deermnes he response of he dependen acor o shocks semmng from ndependen acors. The IRF s an alernae of VDM. The Table-7 shows he resuls of VDM 3. The varance decomposon approach ndcaes he magnude of he predced error varance for a seres accouned for by nnovaons from each of he ndependen varable over dfferen me-horzons beyond he seleced me perod. Table-7 repors ha economc growh s explaned 40.6 per cen by nnovave shocks of renewable energy consumpon. The conrbuon of capal and labor conrbue o economc growh s mnmal.e per cen and 4.90 per cen respecvely. A per cen of economc growh s conrbued by facors ousde he model such as echnologcal advancemens. Renewable energy consumpon s conrbued per cen by s own shocks and 8.94 per cen by nnovaons semmng n economc growh. Capal and labour explan renewable energy consumpon by 9.48 per cen and 0.59 per cen her nnovave shocks. The conrbuon of renewable energy consumpon s greaer han economc growh o capal. A 6.67 per cen capal s conrbued by s own nnovaons. 3 The resuls of mpulse response funcon are avalable from auhors upon reques 26

28 Table-7: Varance Decomposon Mehod Perod Varance Decomposon of Varance Decomposon of R Varance Decomposon of Varance Decomposon of L R L R L R L R L

29

30 The share of labour s neglgble. Fnally, economc growh, renewable energy consumpon and capal do no seem o conre much o labour hrough her nnovave shocks. Almos, 80 per cen of labour s explaned by s own nnovaons. Overall, resuls ndcae bdreconal causaly beween economc growh and renewable energy consumpon. The causal relaonshp s sronger from renewable energy consumpon o economc growh. These fndngs are conssen wh he VECM Granger causaly analyss. Ths enals ha causaly resuls are robus and relable for polcy makng purpose. V. Concluson and Fuure Research The presen sudy nvesgaed he relaonshp beween renewable energy consumpon and economc growh usng Cobb-Douglus producon funcon n case of Paksan. The auoregressve dsrbued lag model or he ARDL bounds esng approach o conegraon appled o es he exsence of long run relaonshp beween renewable energy consumpon, capal, labour and economc growh. The VECM Granger causaly approach s used o examne he drecon of causal relaonshp beween hese seres and nnovave accounng approach s used o es he robusness of he causaly resuls. Our emprcal exercse confrmed ha he varables are conegraed for long run relaonshp over he sudy perod of 97Q-20Q4. The resuls ndcaed ha renewable energy consumpon rases economc growh. Capal and labor are also mporan facors of economc growh conrbung o domesc producon n he counry. The rollng wndow resuls explan ha renewable energy consumpon, capal and labor 29

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