Natural gas consumption and economic growth: cointegration, causality and forecast error variance decomposition tests for Pakistan

Transcription

1 MPRA Munch Personal RePEc Archve Naural gas consumon and economc growh: conegraon, causaly and forecas error varance decomoson ess for Paksan Shahbaz Muhammad and Chandran V G R and Azeem Pervaz COMSATS Insue of Informaon of Informaon Technology, Lahore, Paksan, Unvers Teknolog Mara, Malaysa, Governmen College Unversy Fasalabad, Paksan 26. November 2 Onlne a hs://mra.ub.un-muenchen.de/353/ MPRA Paer No. 353, osed 3. November 2 2:24 UTC

2 Naural Gas Consumon and Economc Growh: Conegraon, Causaly and Forecas Error Varance Decomoson Tess for Paksan Muhammad Shahbaz Asssan Professor Dearmen of Managemen Scences COMSATS Insue of Informaon Technology Lahore, Paksan Emal: Moble no: V G R Chandran Dearmen of Economcs, Unvers Teknolog Mara, KM 2 Jalan Muar, 859 Segama, Johor, Malaysa Emal: vgrchan@gmal.com Phone: Pervaz Azeem Foregn Faculy Member Dearmen of Economcs, Governmen College Unversy Lahore, Paksan Emal: Dr_azm@homal.com Moble no Absrac: Ths aer examnes he relaonsh beween naural gas consumon and economc growh n Paksan usng a mulvarae model by ncludng caal and labor as he conrol varables for he erods of The resuls of he ARDL bounds esng ndcae he resence of conegraon among he varables. The esmaed long-run mac of gas consumon (.49) on economc growh s greaer han oher facor nus suggesng ha energy s a crcal drver of roducon and growh n Paksan. Furhermore, he resuls of causaly es and varance decomoson analyss sugges a undreconal causaly runnng from naural gas consumon o economc growh. Gas beng he rmary source of energy n Paksan, he mlcaons of hs sudy s ha naural gas conservaon olces could harm growh and, herefore, requres he olcy makers o mrove he energy suly effcency as well as formulae arorae olcy o arac nvesmen and esablsh ublc-rvae arnersh naves. Keywords: Naural Gas Consumon, Growh, Paksan, Conegraon, Causaly.

3 . Inroducon The ssue of energy consumon and growh nexus s examned exensvely by scholars due o s oenal olcy mlcaons (Ozurk e al., 2). Of recen, growng neres emerged on he ssues of he use of naural gas and s relaonsh o economc growh. In order o mee he Kyoo arges and snce naural gas roduce less CO 2 emssons han oher fossl fuels, counres around he world are exlorng he olcy oons o encourage he use of gas as an alernave source (Aergs and Payne, 2). In average, he world naural gas consumon as a ercenage of oal energy s around 2% and 23 % n 99 and 27 resecvely 2. Lkewse, beween 27 and 235, he oal naural gas consumon s execed o grow a.8%, n average (EIA, 2). Smlarly, hgher demand for elecrcy also ncreases he need for naural gas due o he fac ha naural gas s an moran source of elecrcy generaon 3 (EIA, 2). Naural gas becomes aracve oon snce s more fuel effcen, rovdes beer oeraonal flexbly and lower emsson and caal coss. Develong counres ha are no lkely o arac enough nvesmen 4, ncludng foregn drec nvesmens, for oher fuel mx sraeges esecally nuclear energy resolves o use naural gas as an alernave. The growng need for naural gas as well as s mlcaon for growh requres one o undersand he lnk beween hem o beer nform he olcy makers on he avalable olcy oons. Ths s more acue n he case of Paksan for wo man reasons. Frs, here s a lack of sudes examnng he long-run relaonsh as well as he causal lnk beween naural gas consumon and growh o rovde sound olcy lessons for Paksan. Second, naural gas has been If naural gas consumon macs economc growh drecly or accomaned wh comlemen o caal and labor, han energy conservaon olcy could adversely mac he growh. Invesgang boh he long run relaonsh and he causal lnk rovdes lesson for fuure olcy drecon. 2 Auhors calculaon based on he daa obaned from EIA (2) 3 Based on a rojecon, elecrcy generaon from naural gas s execed o ncrease by 2.% over he year 27 o 235 (EIA, 2). 4 Paksan had develomen lans for hydroower bu was dsconnued due o dffcules n acqurng foregn nvesmen (EIA, 2). Paksan s nuclear ower conrbuon o oal energy roducon s small sulyng only 2.34% of he counry s elecrcy (World Nuclear Assocaon, h:// 2

4 a domnan fuel 5 n Paksan accounng for almos 47 ercen of rmary energy demand n 27. Snce 2, naural gas and eroleum were consdered he man sources of energy ha was, n average, 5 ercen and 29 ercen of oal energy consumon n Paksan (Paksan Energy Yearbook, 25). The consumon of eroleum roducs had decreased due o hke n eroleum rces whle he naure of ransoraon s ncreasngly been convered o he use of comressed gas. Ths has resuled n rse n naural gas consumon n he counry. Furhermore, governmen had also made effors o encourage he local comressed gas (CNG) and lquefed eroleum gas (LPG) for he consumon n he ransor, agrculure, and ower secors due o hgh coss of mored ol. Transor and he ower secors accoun for nearly 5% and 4% of he overall gas consumon (GoP 6, 28-9). I also offers he cheaes and relavely cleaner alernave source of energy for he secors. In hs asecs dversfyng fuel mx s no only he rores a counry level bu also a secoral level esecally among ower consumng frms. The above descron rovdes a raonal o nvesgae he mac of naural gas consumon on economc growh and he drecon of causal relaonsh beween naural gas consumon and economc growh. Furhermore, exsng sudes on naural gas consumon and growh s lmed (Aergs and Payne, 2) and consensus on he oenal lnks are sll mxed (Lee and Chang, 25; Zaman, 27; Sar e al., 28). Indeed, Karanfl, (29) argued on he need for conssen resuls for olcy makers o make sense of he fuure olcy drecons for her resecve counres. I was furher recommended ha novel mehods usng he recen economerc ools ha are arorae o examne he energy-growh nexus be mlemened o rovde conssen resuls for olcy makers. In he case of Paksan, o our bes of knowledge, only four sudes (Zahd, 28; Aqeel and Bu, 2; Sddqu, 24; Khan and Ahmed, 29) are avalable and hey gnored nvesgang he 5 In las 2 years, energy consumon has been rled from.6 Bu (quadrllon Brsh hermal uns) n 98 o.9 quadrllon Bu n 2 due o rsng demand whch was he resul of conssen rse n er caa ncome. 6 Governmen of Paksan 3

5 dynamc relaonsh beween gas consumon and economc growh. In addon, mos of hese sudes reled on bvarae models o esablsh he causaly beween gas consumon and economc growh. The nvesgaon s sll lmed by he model secfcaon ssues as well as he use of narorae esmaon echnques. Lükeohl (982) ndcaed ha excluson of oher relevan varables conrbues o basness and nconssen resuls. Incluson of he conrol varables of growh such as caal and labor and esmang a mulvarae model hels rovde more relable evdence abou he causal relaon among he varables (Lozdes and Vamvoukas, 25). Lkewse, mos sudes also uses un roo es such as Augmened Dcky-Fuller (ADF) ha s erceved less relable (Shahbaz e al. 2c). For nsance, Dejong e al, (992) and, Harrs and Solls (23) conended ha due o her oor sze and ower roeres, ADF es s unrelable for small samle daa se. Moreover, ADF es seems o over-rejec he null hyoheses when s rue and acces when s false. In hs aer, we used hree dfferen un-roo ess. In addon, alhough s acknowlegde ha deermng seres as I() and I() s dffcul due o ower defcency nherened n classcal un roo es, he use of ARDL model 7 wll be able o mgae hs roblem as he aroach does no requre re-esng for un roo. Accordng o Rahbek and Moscon (999), alhough Johansen s aroach allows a mxure of I() and I() varables, he rocedure for he conegraon rank can be sensve o he resence of saonary varables. Ths aer nends o overcome he lmaons 8 dscussed above by offerng a more robus secfcaon wh he ncluson of conrol varables usng mulvarae framework as well as a counry secfc evdence. The use of recen esmaon echnque known as Auo Regressve Dsrbued Lag (ARDL) bounds esng as well as vecor error correcon mehod, varance decomoson and mulse resonse funcon allows us o check he robusness of he resuls. The 7 Alhough Johansen s aroach can deal wh he ssue, he conegraon rank can sll be sensve o he resence of saonary seres (Rahbek and Moscon, 999) 8 Deals of lmaon are offered by Jnke e al. (28) and Wolde-Rufael, (2). 4

6 ARDL aroach s known o offer he followng advanages. I yelds conssen long-run esmaes even when he rgh hand sde varables are endogenous (Inder, 993). Usng arorae order of he ARDL model, s ossble o smulaneously correc for () seral correlaon n resduals and () he roblem of endogenous regressors (Pesaran and Shn, 999). Indeed, s a referred conegraon echnque due o s robusness for sudes usng small samle sze 9 and allows he varables o have dfferen omal lags. The aroach s also vald regardless of wheher a seres s I() or I(). Smlarly, Vecor Error Correcon Model (VECM) Granger causaly allows he examnaon of long and shor-run causaly whle nnovave accounng echnque (forecas error varance decomoson and mulse resonse funcon) allows renforcng and confrmng he drecon of causaly of he VECM. In addon, counry secfc evdence of hs sudy allows us o mgae he shorcomngs of cross counry analyss (see Sar and Soyas, 29; Chang e al., 2; Sern, 2). Chandran e al. (2) ndcaes ha counry secfc sudes allow one o ake no accoun he nsuonal, srucural and olcy reform more secfcally. Indeed, offers more room o dscuss he olcy mlcaon for he counry under sudy. The resen aer flls hs ga n energy leraure by examnng naure of drecon of causaly beween naural gas consumon and economc growh n case of Paksan over he erod of by ncludng caal and emloymen. 2. Leraure Revew A number of recen me seres sudes have examned he drecon of causaly beween boh he varables n dfferen counres (boh develoed and develong counres) usng varous conegraon and causaly aroaches. For examle, Yu and Cho (985) for UK, US and Poland, 9 In he energy leraure, a large number of sudes nvolvng relavely small samle sze have ulsed ARDL-bounds esng rocedure. 5

7 Yang (2b) and Lee and Chang (25) for Tawan, Ewng e al. (27), Sar e al. (28) and Hu and Ln (28) for US, Zaman (27) and Amadeh e al. (29) for Iran, Reynolds and Kolodzej (28) for Sove Unon, Adenran (29) and Clemen (2) for Ngera, Faa e al. (24) for New Zealand and Ausrala, and Aergs and Payne (2) for 67 counres. Table summarzes he man fndngs of hese emrcal works. Revew of relevan leraure hghlghs wo moran ssues. Frs, evdence s mxed and s less counry secfc. Lkewse, esmaon echnques are less arorae n some of he sudes ha used small samle sze. Indeed, examnng he lnk usng bvarae models s subjeced o omed varable basness. As Lükeohl (982) ndcaed ha excluson of relevan varables makes he resuls nconssen and more ofen no causal relaonsh can be found beween naural gas consumon and economc growh. Second, he esmaon erods are no curren leadng o lack of knowledge on he lnks beween he wo varables n he resens of new develomens n energy oulooks. Incluson of hs me erods s crucal so ha arorae olcy can be suggesed. For nsance, due o global crss and he recen develomen n clmae change agendas, fuel mx olcy has drascally change and, herefore, whou he ncluson of hs me erods, resuls of he revous sudes mgh be nvald, f no less accurae. 6

8 Table : Summary on he relaonsh beween Gas Consumon and Economc Growh Auhors Counres Samle Perod Mehodology Varables Conegraon Causaon Sngle-Counry Sudes Yang (2b) Tawan GC Real GDP, Naural Gas Consumon No G Y Aqeel and Bu (2) Paksan GC by Hsao Real GDP, Naural Gas Consumon No Y G Sddqu (24) Paksan ADL, GC by Hsao Real GDP, Naural Gas Consumon N.A Y G Lee and Chang (25) Tawan JML, WE, Real GDP er Caa, Naural Gas Yes G Y Consumon Ewng e al. (27) US 2: 25:6 VARGFEVD Indusral Producon, Naural Gas N.A G Y Consumon Zaman (27) Iran JML, VECM Real GDP, Naural Gas Consumon Yes G Y Sar e al. (28) US 2: 25:6 ARDL, VECM Indusral Producon, Naural Gas Yes G Y Consumon Hu and Ln (28) Tawan 982: o 26:4 Hansen and Seo, Real GDP, Naural Gas Consumon Yes G Y VECM Reynolds and Kolodzej (28) Sove Unon , 988 GC Real GNP, Naural Gas Consumon N.A G Y 99, Adenran (29) Ngera GC by Sms Rea GDP, Naural Gas Consumon Yes G Y Amadeh e al (29) Iran ARDL, VECM Real GDP, Naural Gas Consumon Yes G Y Clemen (2) Ngera JML, VECM Real GDP, Naural Gas Consumon Yes G Y Mul-Counry Sudes Yu and Cho (985) UK N.A GC by Sms Real GNP, Naural Gas Consumon N. A G Y US N. A Y G Poland N. A Y G Faa e al. (24) New Zealand ARDL, JML, TY Real GDP, Naural Gas Consumon No Y G Ausrala Yes Y G Zahd (28) Paksan TY Real GDP er Caa, Gas Consumon Yes Y G Bangladesh No G Y Inda No Y G Neal No Y G Sr Lanka No Y G Aergs and Payne (2) 67 Counres Pedron s (999, Real GDP, Naural Gas Consumon, Labor, Yes G Y 2) Real caal Noes: Y and G reresen economc growh and naural gas consumon. Y G ndcaes a undreconal causaly runnng from economc growh o naural gas consumon and G Y s from naural gas consumon o economc growh. G Y ndcaes bdreconal causaly and Y G ndcaes no causal relaonsh. N. A means no aled. GC, VARGFEVD, JML, WE, VECM, ARDL and TY means Granger causaly, Vecor Auoregresson Generalzed Forecas Error Varance Decomoson, Johansen s Maxmum Lkelhood, weak exogeney es, Vecor Error Correcon Mehod, Auoregressve Dsrbued Lag Model o Conegraon and Toda and Yamamoo (995) causaly es. Exraced from Saen and Shahbaz (2) Panel conegraon

9 Search of leraure ndcaes ha large number of sudes n he conex of Paksan examnes he lnk beween oal energy consumon and growh2 wh lmed sudes concenrang on naural gas consumon. Therefore, dese s morance o he economc develomen, he emrcal evdence on he causaly beween naural gas consumon and economc growh n Paksan s less exlored and lmed. Recenly, Khan and Ahmed (29) examned he demand for gas, elecrcy and coal consumon usng Johansen and Juselus (99) conegraon mehodology n a mulvarae framework by ncludng er caal ncome and rce level. The resuls sugges he exsence of a long-run relaonsh beween gas consumon, ncome er caa and rce. In he long-run, ncome and rce exers osve and negave mac on gas consumon n Paksan resecvely. However, he rce level s found o be nsgnfcan. They concluded ha gas consumon s more resonsve o ncome change n he long-run. However, exce for elecrcy and coal consumon, he sudy dd no examne he causaly beween gas consumon, ncome and rce level. Aqeel and Bu (2) also examned causaly beween energy consumon (eroleum, elecrcy and gas), energy rce and economc growh for Paksan. They fal o fnd any causaly beween naural gas consumon and economc growh. Ther emrcal exercse only showed undreconal causaly from economc growh o eroleum consumon and elecrcy consumon o economc growh. Lkewse, Zahd (28) usng he Toda and Yamamoo (995) examned he causal relaonsh beween naural gas consumon and economc growh n Paksan, Inda, Sr Lanka, Bangladesh and Neal over he erod of In he case of Paksan, here s no 2 Mash and Mash (996), Hye and Raz (28) and Saen and Shahbaz (2) reored bdreconal causaly beween energy consumon and economc growh n Paksan, whle Khan and Qayyum (27) and Imran and Sddqu (2) found undreconal causaly runnng from energy consumon o economc growh n SAARC ncludng Paksan. Fnally Noor and Sddqu (2) concluded ha rse n ncome er caa Granger caused energy consumon n Souh Asan counres namely Paksan, Bangladesh, Inda, Neal and Sr Lanka.

10 causal relaon beween naural gas consumon and economc growh. Sddqu (24) also reored he absence of causal relaonsh beween naural gas consumon and economc growh. They concluded ha gas consumon s less moran for boh economc and roducvy growh n Paksan. We can conclude, on he bass of revous sudes regardng Paksan, ha mos of emrcal evdence on he drecon of causaly beween naural gas consumon and economc growh s based on bvarae analyss and he resuls may no be robus enough. In addon, he dynamc relaonsh beween gas consumon and economc growh s gnored. In hs sudy, we nend o revs he lnk beween naural gas consumon and economc growh usng a more recen conegraon mehodology and exlore he dynamcs relaonshs beween he varables. 3. Mehodology 3. Model Secfcaon and Daa Recen emrcal sudes such as Sern, (2); Ghal and El-Sakka, (24); Beaudreau, (25); Sar and Soyas, (27); Lee and Chang, (28); Yuan e al. (28) and Wolde-Rufael, (26) used he roducon funcon framework o examne he causal relaonsh beween energy consumon and economc growh. Followng exsng leraure, convenonal neo-classcal roducon model was used where gas consumon, caal and labor are reaed as searae facor nus as gven below: Y f K, L, G ) ( () Where Y s real GDP, K s real caal sock, L s labor and G s naural gas consumon. Followng Lean and Smyh (2), all varables were dvded by oulaon and exressed n er caa erms. Therefore, L reresens labor force arcaon rae. We used log-lnear secfcaon of Equaon 9

11 . The log-lnear secfcaon rovdes sueror resuls han smle lnear secfcaon. Bowers and Perce (975) have crczed he fndngs of Ehrlch s (975) based on funconal form of emrcal model. Furhermore, Ehrlch (977) and Layson (983) have argued on bass of he heory and emrcal evdence ha log-lnear funconal form rovdes beer resuls as comared o lnear secfcaon 3. In case of Paksan, Shahbaz (2) has roved ha log-lnear secfcaon rovdes sueror resuls han smle lnear secfcaon. Ths sudy covers he erod of 972 o 29. The daa on gas consumon, real GDP, real caal and emloymen were obaned from GoP (29- ) Esmaon Technques 3.2. ARDL Bounds Tesng Aroach o Co negraon and Granger Causaly Ths aer follows he ARDL bounds esng aroach o conegraon develoed by Pesaran e al. (2) o examne he long-run relaonsh beween economc growh, naural gas consumon, real caal and emloymen n he case of Paksan. There are ceran advanages of hs aroach. Frs, he shor and long-run arameers are esmaed smulaneously. Secondly, can be aled rresecve of wheher he varable are negraed of order zero I() or negraed of order one I(). Thrdly, has beer small samle roeres (Smyh and Narayan, 24). ARDL aroach nvolves esmang he followng unresrced error correcon model as follows: 3 See for more deals (Shahbaz, 2) 4 CPI was used o conver he seres no real erm.

12 y y j j y y y y y y y y G L K Y G L K Y T Y (.) k k j j k k k k k k k k G L Y K G L Y K T K (.2) l l j j l l l l l l l l G K Y L G K Y L T L (.3) g g j j g g g g g g g g L K Y G L K Y G T G (.4) Where, s he frs dfference oeraor; j s he consan; s are he long-run coeffcens;,,, reresen shor-run dynamcs and s he random varable whch s assumed o be whe nose. T reresens he me rend. The omal lag srucure under ARDL aroach s deermned by esmang ( ) k regressons for each equaon, where s he maxmum number of lags and k s he number of varables n he equaon. The omal lag srucure s deermned by makng use of Schwarz-Bayesan Crera (SBC) or Akake Informaon Crera (AIC). We used AIC o ensure ha he resduals do no suffer from he roblem of sgnfcan seral correlaon. The asymoc dsrbuons of he es sascs are non-sandard regardless of wheher he varables are I() or I(). Two searae bounds es are avalable o examne he resence of longrun relaonsh among he varables of neres: a Wald or F-es for he jon null hyohess 2 3 4, (referred o as ),, / ( L K G Y F Y for Equaon.) and a -es on he lagged level deenden varable (so ha H : ). Snce he asymoc dsrbuon of Wald or F

13 sascs s non-sandard, one can use he crcal bounds values rovded by Pesaran e al. (2). Pesaran e al. (2) have comued wo asymoc crcal values - one when he varables are assumed o be I() and he oher when he varables are assumed o be I(). These are resecvely known as he lower crcal bound (LCB) and he uer crcal bound (UCB). Followng Pesaran e al. (2), f he es sasc exceeds he corresondng UCB hen here s evdence of a sgnfcan long-run relaonsh. Alernavely, f he es sasc s below he LCB hen he null hyohess canno be rejeced. In addon, f he samle es sasc falls beween hese wo bounds hen he resul s nconclusve. In such case, error correcon mehod s arorae mehod o nvesgae he conegraon (Bannerjee e al. 998). Ths ndcaes ha error correcon erm wll be a useful way of esablshng conegraon. However, crcal values of Pesaran e al. (2) may no be suable for small samle sudes lke ours ha have only 37 observaons. We, herefore, comued crcal values usng surface resonse rocedure roosed by Turner (26). To examne he sably of he ARDL bounds esng aroach o conegraon, sably ess namely CUSUM and CUSUMSQ have been aled (Brown e al. 975). The long-run relaonsh can be esmaed usng he seleced ARDL model. For examle, f varables are conegraed n equaon (.), where Y s used as he deenden varable hen here s a sable long-run level relaonsh among he varables, whch can be descrbed as follows: Y K 2L 3G (.5) /, /, /, / and s he usual error where y y y2 y 2 y3 y 3 y4 y erm. These long-run coeffcens are esmaed by he ARDL aroach o conegraon. The same rocess can be used when oher varables are used as a deenden varable. Gven he exsence of 2

14 long-run relaonsh among varables, an error correcon reresenaon can be develoed as follows: 5 Y a K a ( L) L a G a b b ( L) b b b b b b b b b b b b b b ECT (.6) where ( L) s he dfference oeraor; ECT - s he lagged error-correcon erm derved from he long-run conegrang relaonsh; and, 2, 3 and 4 are serally ndeenden random errors wh mean zero and fne covarance marx. The resence of a sgnfcan relaonsh n frs dfferences of he varables rovdes evdence on he drecon of he shor-run causaon whle a sgnfcan -sasc eranng o he error correcon erm (ECT) suggess he resence sgnfcan long-run causaon. However, should be ke n mnd ha he resuls of he sascal esng can only be nerreed n a redcve raher han n he deermnsc sense. In oher words, he causaly has o be nerreed n he Granger sense. In addon, o unvel he naure of he feedback effecs among he varables, we furher aled he varance decomoson mehod and resonse funcon o check for he robusness of he resuls and o gan more nsghs on he comlexy of he relaonshs. 4. Emrcal Resuls Alhough re-esng for non-saonary of he seres s no necessary for he ARDL bounds es, we sll conduced he es o check ha none of seres s I(2) or hgher n whch case can comlcae he F-es (Ouaara, 24). In dong so, we used hree un roo ess.e. Augmened Dcky-Fuller (ADF), Phll-Perron (PP) and Augmened Dckey-Fuller Generalzed Leas Squares (ADF-GLS). Addonally, also serves as a robusness check on he saonary of he seres. For nsance, DF-GLS un roo es s referred as he resuls end o be more relable and conssen as comared o he ADF and PP un roo ess (Ello e al. 996). The resuls are reored n Table 2. The resuls show ha GDP (Y), naural gas consumon (G), real caal (K) and emloymen (L) 5 If conegraon s no deeced, he causaly es s erformed whou an error correcon erm (ECT). 3

15 are nonsaonary a her levels. The emrcal evdence confrmed ha all he four macroeconomc varables are negraed of order I(). Table 2: The Resuls of Un Roo Tess DF-GLS (wh Varables ADF (wh rend) PP (wh rend) rend) ln.4().5787(4).457() Y lny 4.326()*** 4.467(3)*** 4.42()*** ln G 2.733() 2.625() 2.563() ln G 8.284()*** 8.57(2)*** 8.757()*** ln K.6737().522(3).896() ln K 3.984()** 3.984(2)** 4.42()*** ln L.7263 ().383 ().86 () ln L 8.53 ()*** 8.53 ()*** ()*** Noe: The asersks *** and ** denoe he sgnfcan a % and 5% levels, resecvely. The fgure n he arenhess s he omal lag srucure for ADF and DF-GLS ess, bandwdh for he PP un roo es s deermned by he Schwer (989) formula. The long-run relaonsh beween he varables s nvesgaed hrough he ARDL bound esng aroach o conegraon usng Equaons (..4). The resuls are reored n Table 3. The calculaed F-sascs (6.77) s greaer han UCB a 5% level of sgnfcance when Y serves as he deenden varable. I suggess ha G, K and L are long-run forcng varables n equaon.. Therefore, we can rejec he null hyohess of no conegraon when Y serves as he deenden varable. In conras, he comued F-sasc (6.59) s lower han UCB when naural gas consumon s consdered as he deenden varable. Smlarly, he comued F-sascs (3.59 and 5.32) are less han UCB when K and L are consdered as endogenous varables resecvely. 4

16 Table 3: Resuls of Conegraon Tes Panel I: Bounds Tesng o Conegraon Esmaed Model F Y ( Y / G, K, L) F G ( G / Y, K, L) F K ( K / Y, G, L) F L ( L / Y, G, K) Omal Lag Lengh [2, 2,, 2] [2, 2, 2, 2] [2,, 2, 2] [2, 2, 2, 2] F-Sascs 6.77** 6.59*** Crcal values (T = 37) # Lower bounds I() Uer bounds I() er cen level er cen level Panel II: Dagnosc ess 2 R Adjused- R F-sascs 5.97*** 5.28*** 4.68*** 3.8*** J-B Normaly es.476 (.788).324 (.854).533 (.7774) 4.68 (.282) Breusch-Godfrey LM es.7735 (.26).96 (.776).465 (.3754).496 (.2589) ARCH LM es.963 (.3485) (.4).689 (.7947).8497 (.836) Whe Heeroscedscy es.897 (.56).798 (.253).5668 (.8685).645 (.628) Ramsey RESET.5449 (.47).935 (.3489) (.468) 5.3 (.2) CUSUM Sable Sable Sable Sable CUSUMSQ Sable Sable Sable Sable Noe: The asersks ** and ***denoes he sgnfcan a 5% and % level resecvely. The omal lag srucure s deermned by AIC. The arenhess ( ) s he rob-values of dagnosc ess. # Crcal values were comued by surface resonse rocedure develoed by Turner (26). Snce here s evdence of conegraon when Y serves as he deenden varable, s ossble o esmae he long-run mac of G on Y. The long-run coeffcens derved from he ARDL model are reored n Table 4. The resuls reveal ha G has osve mac on Y and s sgnfcan a ercen sgnfcance level. These fndngs are conssen wh Aergs and Payne (2), n he case of 67 economes ncludng Paksan, bu conradc wh he vews of oher sudes usng Paksan as a case 6. The resuls os ha a ercen ncrease n G ncreases Y by.493 ercen. Smlarly, an ncrease n K s lnked osvely o Y and s sgnfcan a ercen sgnfcance level. Ths emrcal evdence s conssen wh he argumen by Arby and Baool (27) ha K also lays an moran role n economc growh. Therefore, gnorng he nfluence of K and esmang he model 6 I should be noed ha oher sudes use bvarae model o check he mac of naural gas consumon on economc growh. 5

17 n a bvarae framework may lead o basness. A ercen ncrease n K ncreases Y by.46 ercen. However, he resul seems o sugges ha among he nu facors he nfluence of G s greaer han K and L. Ths confrms ha Paksan s an energy-deenden counry and any dsoron o s naural gas suly would defnely mac he economc growh sgnfcanly. Wh he growng demand for gas, whch s execed o ouace s gas roducon, new naves n erms of new exloraon as well as mor oons s needed. More moranly, any aem by he governmen n nroducng conversaon olcy would harm he economc rogress. Unless f here s a subsuon effecs 7 (Smyh e al, 2) beween energy and caal or labor, any shorage n energy suly or rce ncrease would defnely mac he economc growh n Paksan. Table 4: The Long Run Resuls Varable Coeffcen -Sasc Consan * ln G * ln K * ln L * J-B Normaly Tes (.38) Breusch-Godfrey LM Tes.5283 (.5948) ARCH LM Tes.348 (.2548) Whe Heeroskedascy.2772 (.2983) Ramsey RESET.839 (.3688) The dagnosc ess mly ha error erm s normally dsrbued and here s no seral correlaon n he model. There s no sgn of exsence of auoregressve condonal heeroskedascy. The 7 I s ossble ha ceran yes of caal nvesmen may reduce he need for energy use e.g. nvesmen n energy effcen machnery. In he case of Paksan we dd no exend he sudy o examne he subsuon effecs. However, o be ceran ha he ndeenden varables do no exhb any roblems of mulcollneary, we examned he correlaon marces and he varance nflaon facors (VIF). The value of VIF s less han suggesng ha here s no roblem of mulcollneary. Snce our esmaes are a aggregae level and does no use any arcular yes of caal or secoral analyss, s ossble no o deec hgh correlaons beween caal and energy use. Consequenly, he roblem of serous mulcollneary nvolvng gas consumon, caal and labor can be mgaed as ARDL s known o yeld conssen long-run esmaes even when he rgh hand sde varables are endogenous (Inder, 993). Pesaran and Shn (999) roved ha s ossble o correc for seral correlaon n resduals and he roblem of endogenous regressors usng arorae order of he ARDL model. 6

18 Ramsey RESET esmaes show ha funconal form of he model s well secfed. Furhermore, cumulave sum (CUSUM) and cumulave sum of squares (CUSUMSQ) revealed ha our seleced ARDL model s sable (see Fgures and 2). Fgure : Plo of Cumulave Sum of Recursve Resduals CUSUM 5% Sgnfcance The sragh lnes reresen crcal bounds a 5% sgnfcance level. Fgure 2: Plo of Cumulave Sum of Squares of Recursve Resduals CUSUM of Squares 5% Sgnfcance The sragh lnes reresen crcal bounds a 5% sgnfcance level. Alhough K, L and G aear o be he long-run forcng varables based on conegraon es n equaon., he drecon of causaly s less clear. In hs asec, he evdence of conegraon s only a necessary bu no suffcen condon for rejecng Granger non-causaly. The resence of conegrang among he varables leads us o erform he Granger causaly es o rovde more 7

19 nsghs on he drecon of causaly. I s moran o selec he arorae lag lengh n order o avod surous regresson. We emloyed a combnaon of AIC, SBC, and lkehood rao (LR) es n order o selec arorae lag lengh for he VAR. In addon, we checked o see ha he seleced lags ass he usual dagnosc ess o ensure ha he classcal regresson assumons are no volaed. We fnd no serous volaon of he auocorrelaon, normaly and heeroscedascy assumons. Table 5 shows he resuls of he omum lag lengh selecon. Snce he lag lengh orders are dfferen beween AIC and SBC, we reled on LR es o choose he arorae lag lengh (Pesaran and Pesaran, 997). The omum lag lengh chosen s 2 based on he LR es. Table 5: Tes Sascs and Choce Crera for Selecng he Order of he VAR Model Lag Loglkelhood AIC SBC LR es Adjused LR es CHSQ( 6)= [.] CHSQ( 6)= 3.93[.] CHSQ( 32)= [.] CHSQ( 32)= 56.2[.5] The resuls of Granger causaly s reored n Table 6. The causaly can be erformed for he shor-run and long-run. The long-run causaly can be esed by examnng he sgnfcance of coeffcen of he one erod lagged error-correcon erm ( ECT ) usng -es. Smlarly, he shorrun causaly can be deeced by examnng he jon sgnfcance of he lagged exlanaory varables n he equaons. Our emrcal resuls sugges ha he ECT s negave and sascally sgnfcan when Y serves as a deenden varable. The coeffcen of ECT mles ha devaons from shor-run o long-run equlbrum n he curren o fuure erod are correced by abou 38% er year. The resuls ndcaed un-dreconal causal relaonsh runnng from G o Y n he longrun and shor-run. These fndngs are conssen wh Yang (2b) and Lee and Chang (25) for Tawan, Ewng e al. (27) for US, Reynolds and Kolodzej (28) for Former Sove Unon and Clemen (2) for Ngera whle conradc wh he emrcal evdence by Aergs and Payne 8

20 (2) 8, Khan and Ahmed (29), Zahd (28), Sddqu (24) and Aqeel and Bu (2) n he case of Paksan. K also Granger caused Y n boh long-run and shor-run. The undreconal causaly was also found runnng from L o Y n long-run bu no n he shor-run. In conras, Y, K and L dd no Granger cause G n he shor-run. Our major focus was o deec causaly beween G and Y ha s undreconal runnng from G o Y. Ths confrms ha energy (naural gas) conservaon olces may reard he rae of economc growh n he counry. 8 They found bdreconal causal relaonsh beween gas consumon and economc growh whle Khan and Ahmed (29), Zahd (28), Sddqu (24) and Aqeel and Bu (2) reored absence of any causaly beween he sad varables. 9

21 Deenden varable lny ln G Table 6: Resuls of Granger Causaly Tye of Granger causaly Shor-run Long-run Jon (shor and long-run) lny ln G ln K ln L ECT ln G, ECT ln, ECT ln L, ECT F-sascs [-values] (-sascs) F-sascs [-values] 4.992** ** ***.6***.8388***.9457*** [.5] [.47] [.2826] ( 5.722) [.] [.] [.] [.49].935 [.99].475 [.2465] ln K [.345] [.4986] [.5585] ln L [.988] [.425] [.3393] Noe: The asersks ***, and ** denoe he sgnfcan level a he and 5 er cen resecvely. K The Granger causaly ess do no deermne he relave srengh of causaly effecs beyond he seleced me san (Wolde-Rufael, 29). I mles ha causaly ess are narorae because hese ess are unable o ndcae on how much feedback exs from one varable o he oher. For hs reason, we emloyed he generalzed forecas error varance decomoson aroaches roosed by Pesaran and Shn (999). Conrasng he orhogonalzed aroach of Sms (98), hs aroach are no sensve o he order of he varables n he vecor auoregressve and allows for more relable esmaes of he varance of a varable due o shocks of anoher varable n he same sysem of smulaneous equaon. Generalzed forecas error varance decomosons are based on he esmaon of he movng-average reresenaon of he orgnal VAR (Pesaran and Pesaran, 997).

22 The generalzed forecas error varance decomoson ndcaes he nfluence of a shock n one varable ha s exlaned by he shocks of he oher varable. As he sudy s man move s o nvesgae he nerrelaonsh beween naural gas consumon and economc growh, we only decomose he forecas-error varance of economc growh and naural gas consumon. Table 7 reors he resuls of he generalzed forecas error varance decomoson. The resuls confrm ha here s a un-dreconal causaly runnng from naural gas consumon o economc growh. The forecas varance of naural gas consumon exlans more han 34% n horzon and ncreases o around 6-7% n he long-run. Lkewse, economc growh s also redomnanly exlaned by s own varance. However, he nfluence seems o declne over a longer me horzon. In conras, forecas-error varance of naural gas consumon economc growh s manly exlaned by self. The forecas-error varance of economc growh exlans 6% of he forecas-error varance of naural gas consumon. Table 7: Generalzed Forecas Error Varance Decomoson Varance Decomoson of ln Y Varance Decomoson of ln G Horzon ln Y ln K ln L ln G ln Y ln K ln L ln G The row values for he generalzed varance decomoson do no add u o unlke he case of orhogonalzed aroach (Sar and Soyas, 27). 5. Concluson and Polcy Imlcaons Ths sudy has nvesgaed he relaonsh beween naural gas consumon and economc growh by ncludng real caal and emloymen usng he roducon funconal form whn he framework of a mulvarae model over he erod of n he case of Paksan. The ARDL bound esng aroach confrms ha here exss a long-run relaonsh beween real GDP,

23 naural gas consumon, real caal and emloymen. The long-run elascy esmaes ndcae a osve and sgnfcan mac of naural gas consumon, real caal and emloymen on economc growh. In comarson o he long-run elascy (.652) esmaes of Aergs and Payne (2) ulzng almos he same model usng anel daa for 67 counres, our elascy esmae wh resec o naural gas consumon s.493. Ths mgh ndcae he requremen for a counry secfc sudy, lke ours, so ha more accurae magnude of effecs can be esablshed for olcy urose. Furhermore, he resuls of Granger causaly and varance decomoson analyss reveal undreconal causaly runnng from naural gas consumon o economc growh suorng he naural gas consumon-led-economc growh hyohess. Ths suggess ha energy (naural gas consumon) conservaon olces may reard he rae of economc growh n Paksan. Wh gas beng he rmary energy source accounng for 48% of oal energy n 28, ha s almos ndgenously roduced, Paksan need o ensure ha hs source of energy s able o mee he demand. The arorae energy olces regardng naural gas should be alored owards mrovng he energy effcency conssen wh he ace of economc growh n he counry. Paksan beng one of he larges users of CNG should also ncrease he nvesmen n gas roducon nfrasrucure ncludng echnology develomen 9. Alernavely, nensfyng he rvae-ublc arnersh effors would also ensure relable suly of gas, oeraonal effcency, beer dsrbuon as well as allows n achevng mor subsuons arges whch oherwse wll have an adverse effecs on balance of aymens. Commmen o ncrease local gas exloraon and nvesmen ncenves as well as naves o arac nvesmen n he gas roducon would ensure susanable suly of gas o roel he economc. Ths wll also ensures ha local gas rce are kee 9 Alhough Paksan has farly a well develoed gas nfrasrucure, wh he growng demand for gas he effors need be nensfed. 22

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