The Relationship Between Commercial Energy Consumption and Gross Domestic Income in Kenya

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1 The Relaionship Beween Commercial Energy Consumpion and Gross Domesic Income in Kenya Susan M. Onuonga The Journal of Developing Areas, Volume 46, Number 1, Spring 2012, pp (Aricle) Published by Tennessee Sae Universiy College of Business DOI: /jda For addiional informaion abou his aricle hp://muse.jhu.edu/journals/jda/summary/v046/46.1.onuonga.hml Access provided by Kenyaa Universiy. Library (19 Apr :49 GMT)

2 T h e J o u r n a l o f D e v e l o p i n g A r e a s Volume 46 No. 1 Spring 2012 THE RELATIONSHIP BETWEEN COMMERCIAL ENERGY CONSUMPTION AND GROSS DOMESTIC INCOME IN KENYA ABSTRACT Susan M. Onuonga Kenyaa Universiy, Kenya The causal relaionship beween economic growh and energy consumpion represens a widely sudied opic in energy economics lieraure. Alhough i is well known ha here is a srong correlaion beween energy consumpion and economic growh, he issue of causaliy is sill conroversial. The paper invesigaed he causal relaionship beween energy consumpion and economic growh in Kenya using published daa. By using he Ganger-causaliy Error Correcion Model, he resuls sugges ha economic growh causes energy consumpion in Kenya. The implicaion of he sudy is ha energy conservaion measures would no lead o negaive effecs on he counry s economic growh. JEL Classificaions: C32, C33, Q41 and Q43 Keywords: Commercial energy consumpion, Gross Domesic Produc, Granger- Causaliy Error Correcion model Corresponding Auhor s smo602000@yahoo.com INTRODUCTION Energy plays a key role in he economy from boh he demand side and supply side. On he demand side, energy is one of he basic iems ha a consumer buys o maximize her uiliy. On he supply side energy is a key facor of producion jus as capial, labor, land and maerials, a fac ha is hardly included in he macroeconomic growh heories. As from he oil crisis of 1970s, and is effecs on he economies has brough o he righ he imporance of energy as a facor of producion beside labor and capial. Energy deermines he economic growh of a counry and is sandards of living. There is hus a causal relaionship running from energy o economic growh or vice versa. Alhough i is well known ha here is a srong correlaion beween energy and economic growh, he issue of causaliy is sill conroversial (Masih and masih, 1996; Sern, 1993; Ebohon, 1996; Cheng and Lai,1997; Ghali and El-Sakka, 2004). This raises such imporan quesions as: wheher energy is a simulus o growh, or wheher economic growh is a simulus o energy consumpion. The answers o hese quesions have imporan implicaions for policy makers on energy. If causaliy runs from energy o Gross Domesic Produc (GDP) hen, he economy is energy dependen. According o Jumbe (2004), economic growh is deermined by energy consumpion. If his is he case, a shorage of energy supply may negaively affec economic growh leading o poor economic performance and increased unemploymen. On he oher hand, if causaliy runs from GDP o energy, i means ha he counry is no energy dependen. Tha is, energy conservaion policies may be implemened wihou adversely affecing economic growh and employmen. In he even

3 306 ha here is no causaliy in eiher direcion, (referred o us as neuraliy hypohesis), hen energy and GDP are no correlaed. The counry can implemen energy conservaion policies wihou affecing economic performance of he counry. I is herefore imporan o empirically deermine he relaionship beween energy consumpion and economic growh. This will add informaion on he curren debae on global warming where counries are supposed o reduce emissions of Greenhouse Gases ha pollue he environmen. There will be added informaion on he effec of conservaion of energy on economic growh. If causaliy is from energy o GDP, hen conservaion of energy will have a negaive effec on economic growh. The resuls are beneficial o energy invesors and planners. Kenya has developed Vision 2030, which conains a long-erm sraegy for ransforming he counry ino a middle-income economy in he nex wo decades. In he firs medium plan ( ) of vision 2030, hree projecs dealing wih energy are idenified, namely: a rapid rural elecrificaion, an increase of energy access; and a leas cos power developmen programme o generae addiional 505MW of elecriciy (Republic of Kenya, 2007a). These projecs are mean o enable he counry achieve he Vision. In his Vision, i is no clearly known wheher energy drives he economy or vice versa. Causaliy analysis of energy and economic growh is essenial in he achievemen of his Vision. LITERATURE REVIEW Given he imporance of energy- income causaliy analysis, many sudies have been carried ou in boh developed and developing counies. There is no consensus on he resuls obained. Kraf and Kraf (1978), in heir sudy on USA economy, suppored unidirecional causaliy hypohesis for he period Erol and Yu (1987) invesigaed he relaionship beween energy consumpion and GDP for England, Ialy, Germany, France, Japan and Canada using he daa. The resuls showed bidirecional causaliy for Japan, unidirecional causaliy running from energy consumpion o GDP for Canada, and unidirecional causaliy running from GDP o energy consumpion for Ialy and Germany. The sudy did no find any causaliy for France and England. Sern (1993) examined he relaionship beween energy consumpion and GDP for USA using mulivariae coinegraion model. The resuls showed no relaionship beween he wo variables. This conradics Kraf and Kraf (1978) `s findings. Ebohon (1996) invesigaed he causaliy beween energy consumpion and economic growh for Tanzania and Nigeria. The sudy found a bilaeral causaliy beween energy consumpion and economic growh for boh counries. Masih and Masih (1996), in heir sudy for he Philippines, found no causaliy beween energy consumpion and economic growh. In anoher sudy, Masih and Masih (1997) found bidirecional causaliy for Korea and Taiwan. In he sudy done by Chenge and Lai (1997) for Taiwan province of China, found causaliy running from economic growh o energy consumpion, and from energy consumpion o employmen wihou feedback. Shyamal (2004) examined he causal relaionship beween energy consumpion and economic growh in India for he period Applying Engle-Granger coinegraion and he sandard Granger

4 307 causaliy mehods, he sudy found bi-direcional causaliy beween energy consumpion and economic growh. Some sudies sudy he relaionship beween energy and economic growh by separaing energy ino is componens. Jumbe (2004), examined he relaionship beween elecriciy consumpion and GDP for Malawi for he period The sudy found bidirecional causaliy beween elecriciy consumpion and GDP. However, when he sudy examined he relaionship beween elecriciy consumpion and non-agriculural GDP, he sudy found a unidirecional causaliy relaionship beween he wo variables. Ghosh (2002) examined he relaionship beween economic growh and elecriciy consumpion of India beween 1950 and The sudy found a unidirecional causaliy relaionship from economic growh o elecriciy consumpion. From he lieraure review, i is observed ha he resuls are mixed; including bilaeral, unidirecional and no relaionships beween energy consumpion and economic growh. I is herefore imporan o examine he case in Kenya, especially now ha he counry has se up Vision This paper addresses he issue of energy-income causaliy by using he Granger causaliy error Correcion model (ECM) approach. The following secion discusses energy profile in Kenya. KENYA'S ENERGY PROFILE In Kenya, sources of energy comprise boh commercial and non-commercial alernaives. Commercial sources of energy include peroleum producs and elecriciy, while noncommercial ones, comprise biomass and o a lesser exen oher alernaive renewable energy such as solar energy, wind power and biogas. Crude oil is he leading source of he world modern energy supply. In Kenya, peroleum fuel is a major source of modern energy accouning for abou 20 per cen of he oal energy consumpion. This form of energy is mainly used in he ranspor, indusrial and commercial secors. Consumpion of peroleum was housand onnes in 2007, up from housand onnes in he previous year. The overall demand is projeced o rise by 2% per annum on average o reach 2.93 million ones by financial year 2009/10 (Republic of Kenya, 2004). Peroleum exploraions are sill going on in Kenya, and harvesing of his form of energy has no sared. Therefore, he counry relies on impored peroleum for is local consumpion. Elecric power is anoher imporan source of energy in Kenya. I conribues abou 10 per cen of he oal energy consumed. This ype of energy is mainly derived from hydro, hermal oil and geohermal sources. The insalled capaciy by 2007 were 677.3, and 128 Megawas for hydro, hermal oil and geohermal, respecively. In he pas, he Kenya Power and Lighing Company (KPLC) carried ou disribuion and sale of elecriciy. Reforms ha were inroduced in he power sub-secor beween 1994 and 2000 led o he separaion of power generaion and markeing. Kenya Elecriciy Generaing Company Ld (KENGEN) is now he major producer of elecriciy in Kenya. KENGEN does no saisfy he demand for elecriciy in Kenya. Because of his, privae producers have been commissioned by KENGEN o supplemen he power generaed especially in imes of drough. These privae producers are in wo caegories, namely: he Independen Power Producers (IPPs) and he Emergency Power Producers (EPPs).

5 308 Mos of he elecriciy in Kenya is hydro-based. The conribuion of hydroelecriciy o oal elecriciy supply was 55, 51, and 57 per cen in he years 2005, 2006 and 2007, respecively (Republic of Kenya, 2007b). The conribuions of hermal oil for he same periods were approximaely 26, 30 and 27 percen, respecively. The conribuion of geo-hermal for he same years was 18, 18 and 17 percen of he oal elecriciy supplied, respecively. In addiion o he above supplies of elecriciy, Kenya has an agreemen wih he Uganda Elecriciy Board (UEB) o supply he counry wih 30 MW annually. Elecric power, is consumed by all secors, bu mainly in he large and medium commercial and indusrial, domesic and small commercial and rural elecrificaion. The consumpion of elecriciy has grown over he years and i is expeced o coninue growing as he economy grows. and more especially, if he vision 2030 is o be achieved. Consumpion of elecriciy by ype of user in he year 2007 is illusraed in he following pie char. FIGURE 1. ELECTRICITY CONSUMPTION DSC LM(C&I) R E Source of original daa: Republic of Kenya, 2007, pp 186. Noes: DSC, represens domesic and small commercial LM represens large and medium (Commercial and Indusrial), while RE sand for Rural elecrificaion. Biomass is anoher source of energy in Kenya. Biomass resources are derived from fores formaions such as closed foress, woodlands, bush lands, grasslands, farmlands, planaions and agriculural and indusrial residues. These resources include wood fuels and agriculural residues. This ype of energy leads in erms of oal supply of energy in he counry, supplying abou 70 per cen of Kenya s oal energy needs. Abou 80 per cen of he Kenyan populaion depends on wood fuel for domesic energy needs, providing 93 per cen and 80 per cen of he rural household and urban area energy requiremens respecively (Republic of Kenya, 2000a). These forms of energy are mainly uilized in he manufacuring commercial, ranspor and he residenial sub-secors. For Kenya o mee is growing energy needs, he counry faces boh supply and demand side managemen consrains. The governmen has come up wih energy policy o address hese issues (Republic of Kenya, 2004). However, for such a policy here is need o undersand he causal relaionship beween energy consumpion and GDP. The purpose of his paper is o deermine such a relaionship. Because of lack of appropriae

6 309 official ime series daa on biomass energy, only elecriciy and oil are considered in his sudy. METHODOLOGY, DATA AND MODEL In order o invesigae he relaionship beween energy and Gross Domesic Produc (GDP) in Kenya, a wo-sep procedure was adoped. Firs, ime series properies of he daa were invesigaed by use of uni roo es and long- run relaionship invesigaed by use of coinegraion analysis. To carry ou saionariy analysis, uni roo es was used. Dickey and Fuller (1981) approach was applied by use of he following model: The idea of using many lagged difference erms is o minimize he auocorrelaion in he error erm. In each case he Ho: δ=0 (here is a uni roo). The es saisic on he Y a a Y i i i1 p Y U parameer was hus compued and compared o he criical values of in Dickey and Fuller (1981). Failing o rejec he null hypohesis implies ha he series conain uni roo hence is non-saionary a levels. In his sudy he ADF es was performed on log(gdp) and log(energy) series. In boh equaions, he consan and he linear rend were included since his represens he mos general specificaion. Tesing for co-inegraion was done using he Engle-Granger wo-sep procedure (Granger, 1986; and Engle and Granger, 1987). The procedure involved esing wheher he regression residuals of he following long-run regressions were saionary: log(percapia income) = a 0 +a 1 log(percapia energy)+ u 1 (2) log(percapia Energy) =b 0 +b 1 log(percapia income)+u 2 (3) where u 1 and u 2 are error erms assumed o be uncorrelaed, wih zero mean and consan variance. The wo equaions were esimaed using Ordinary Leas Squares mehod ( OLS). In he second sep, he causal relaion beween energy and GDP of Kenya was invesigaed. If he variables were non- saionary a levels and he linear combinaion of hem was non- saionary, he sandard Granger causaliy es was used. If he series were non- saionary a levels and here was a long- run relaionship among he variables, hen he ECM approach was used (Yang, 2000). The sandard Granger causaliy analysis was however, done before he ECM. Following Granger (1969), he saemen ha log(energy) Granger causes log(gdp), means how much of he curren log(gdp) can be explained by pas values of log(gdp) and wheher adding lagged values of log(energy) can improve he explanaion. The same applies o he saemen ha log (GDP) Granger causes log (Energy). Granger causaliy, however, does no mean ha if one says log (Energy) Granger causes log(gdp), ha log(gdp) is he resul of log(energy). The sandard Granger causaliy was invesigaed by use of he following wo regressions: (1)

7 310 n log( GDP) ai log( GDP) i j log( Energy) j u1 i1 n j1 (4) m log( Energy) bi log( Energy) i j log( GDP) j u2 i1 m j1 (5) where u 1 and u 2 are error erms assumed o have zero means and uncorrelaed, n and m are lag lenghs and should were se o be he longes period over which one series prediced he oher. The null hypoheses was ha log(energy) does no Granger cause log(gdp) in regression 4 and ha log(gdp) does no Granger cause log(energy) in regression 5. This was esed by F es for he join significance of he parameers β j and α j. When using he ECM approach causaliy was esed by esimaing he following regressions: Δlog(GDP) a 0 n n Δlog(GDP) i θ Δlog(Energy) j π u1 1 i 1 i j 1 j e 1 (6) m log( Energy) a 1 b log( Energy) i 1 i i m y log( GDP) j 1 j j u 21 e 2 (7) Where Δ, is he firs difference operaor, while u^1-1 and u^2-1 are esimaed residuals from equaions 2 and 3, respecively. In his approach log (Energy) Grangercauses log(gdp) if eiher he coefficiens on lagged log(energy) are saisically significan or he coefficien on lagged error erm (π) is saisically significan. Similarly, in regression 7, log(gdp) Granger-causes log(energy) if eiher he coefficiens on lagged log(gdp) are saisically significan or he coefficien on lagged error erm (ρ) is saisically significan. Four lags were used in boh equaions. The choice of lag lengh was deermined by esing he significance of he parameers θ,, b and y. This lag lengh was a reasonable period on which he independen variable can influence he dependen variable. The daa used in his sudy were available from Kenya s Economic Surveys and Saisical Absracs. From hese documens, daa on energy consumpion per-capia and Gross Domesic per-capia were exraced. Because of lack of daa on oher forms of energy, only commercial energy (peroleum and elecriciy) were considered in his paper. Energy consumpion per-capia was calculaed by dividing oal energy consumed each year by oal populaion of he same year, while GDP per-capia was calculaed by dividing he oal GDP of he counry in each year by he corresponding year s populaion. All he daa were convered ino naural logs before causaliy analysis.

8 311 EMPIRICAL RESULTS The empirical resuls are presened in hree sages. Firs here is he saionariy es,followed by coinegraion resuls and lasly causaliy resuls are presened. Saionariy Tes As discussed before i was necessary o es for saionariy of he series. The resuls are presened in Table 1. TABLE 1. ADF UNIT-ROOT TESTS FOR STATIONARITY Variable Level Firs- Difference log(gdp) -2.7(0.08) (0.000) log(e) -3.19(0.03) -3.43(0.003) Noes: In brackes are Mackinnon p-values The Mackinnon esimaed values for rejecion of he null hypohesis a 1%, 5%, and 10% are -4.25, -3.54, and Therefore, he null hypohesis of non-saionariy of he wo series a levels was no rejeced. The log of GDP per-capia and of energy consumpion per-capia were saionary a heir firs differences. Income and energy series are herefore, inegraed of order one. The lag lengh ha removed serial correlaion for firs difference of boh series was uni, and hese were deermined by use of Akaike Informaion Crierion (AIC) (Akaike, 1969). Coinegraion Tes The resuls for coinegraion analysis are presened in Table 2. TABLE 2. COINTEGRATION TEST Regression ADF log(gdp)on log(energy) -3.7(0.11) log(energy) on log (GDP) -3.7(0.09) Noes: In brackes are Mackinnon p-values The lag lenghs as deermined by AIC were 5 and 7 respecively for firs and second equaions. The resuls for boh equaions showed ha he residuals of boh esimaed equaions were saionary providing evidence ha GDP and energy were coinegraed. Therefore, he ECM approach was found o be appropriae in esing for causaliy beween energy consumpion and GDP. Table 3, presens resuls for he sandard Granger causaliy es beween energy consumpion and GDP.

9 312 Causaliy Tes TABLE 3. GRANGER CAUSALITY TEST Regression F-value log(gdp) on log(energy) 0.71 log(energy) on log(gdp) As shown from able 3, only regression log(energy) on log(gdp) is saisically significan a 10% level suggesing ha here is unidirecional causaliy running from economic growh o energy consumpion. Wha his means is ha including pas values of log(gdp) in log(energy) equaion provides a beer explanaion of he curren values of log(energy). In oher words, economic growh causes energy consumpion. TABLE4. RESULTS OF ENGLE-GRANGER CAUSALITY ERROR CORRECTION MODEL log(gdp) on log(energy) 0.35(0.95) 0.013(0.7) 0.37 log(energy) on log(gdp) 4.4 (0.002) -0.82(0.0016) The resuls in able 4 showed ha here was unidirecional causaliy running from GDP o energy consumpion in Kenya over he sample period. This mean ha adding pas values of Δlog(GDP) in he Δlog(energy) equaion provided a beer explanaion of changes in energy consumpion. This agreed wih he resuls obained earlier under he sandard Granger causaliy es. Economic growh in Kenya leads o increase in demand for energy. CONCLUSIONS This paper aimed a invesigaing causaliy linkage beween energy consumpion and GDP in Kenya using secondary daa over he period According o Engle- Granger coinegraion procedure, here is long-run relaionship beween energy consumpion and GDP in Kenya. The sudy used he ECM approach bu compared he resuls wih hose of he sandard Granger causaliy approach. Resuls found, suggesed ha economic growh causes oal energy consumpion in Kenya. The resuls were similar in boh approaches. This resul agreed wih oher previous sudies (Kraf and Kraf, 1978, Jumbe, 2004, Anjum, 2001) bu disagreed wih ohers ha found ha energy drives he economy or a bidirecional causaliy or neuraliy hypohesis. One reason for his resul is ha Kenya s economy is dominaed by agriculure as he major source of income, hus i is no ye an indusrialized economy where energy drives he economy. I is less dependen on energy as an inpu in is GDP producion as compared o advanced counries. The resul obained in his sudy has imporan policy implicaions on Kenya` energy and economic growh policy. Kenya uses a lo of foreign exchange o finance fossil energy impors bill. The counry s impor bill on crude peroleum and peroleum producs amouned o 29,014; 31,354; 40,788; 63,680; and 57,217 Kenya Shilling millions in he years 1997, 1998, 1999, 2000 and 2001, respecively. Therefore, using

10 313 energy more efficienly and subsiuing oil for locally produced renewable energy wherever possible could be a good policy. Energy conservaion policy especially on impored fossil energy canno lead o any adverse side effecs on economic growh in Kenya. A lo of foreign exchange can be saved ha can be uilized in oher producive areas leading o greaer economic growh and oher benefis such as increased employmen. The oher policy implicaion is ha increased economic growh in Kenya, will lead o increased demand for commercial energy holding oher facors consan. Therefore, here is need for he counry o inves more on renewable energy ha has more advanages compared o fossil energy as far as environmenal conservaion is concerned. In addiion, given ha here are some indicaions of peroleum poenial wihin he counry, i will save a lo of money spen on imporaion of peroleum if he governmen can provide conducive environmen ha can accelerae is exploiaion. REFERENCES Akaike, H., Fiing auoregressive models for predicion..annals of he Insiue of Saisical Mahemaics,1969, 21, PP Anjum, A. and Mohammad, S. B., The relaionship beween energy consumpion and economic growh in Pakisan. Asia-Pacific Developmen Journal, 2001,Vol 8. PP Chenga, B.S and Lai, W.L., An invesigaion of coinegraion and causaliy beween energy consumpion and economic aciviy in Taiwan Energy Economics,1997,vol.19. pp Dickey and W.Fuller., Likelihood raio saisics for auo-regressive ime series wih uni roos. Economerica,1981, vol.49,pp Ebohon, O.J., Energy, economic growh and causaliy in developing couries: A case sudy of Tanzania and Nigeria. Energy policy, 1996, vol.24, pp Engle,R., and R.W.Granger., Co-inegraion and Error Correcion: represenaion, esimaion, and esing. Economerica,1987,vol. 55, pp Erol, U. and E.S.H. Yu., On he relaionship beween energy and income for indusrialized counries. Journal of energy and Employmen, 1987,vol.13, pp Ghali, K.H., and Eli-Sakka, M.I.T., Energy use and oupu growh: A mulivariae coinegraion analysis.energy Economics 2004, vol.26,pp Ghosh,S., Elecriciy consumpion and economic growh in Taiwan, Energy Policy. 2002, vol.28, pp Glasure Y U and A.R Lee., Coinegraion, Error Correcion and he Relaionship beween GDP and Energy: The case of Souh Korea and Singapore, Resource and Energy Economics,1997,vol. 20, pp Granger, C. W. J., Developmens in he sudy of co-inegraed economic variables, Oxford Bullein of Economics and Saisics, 1986, vol. 48, no.3, pp Granger, C. W. J., Invesigaing causal relaions by economeric models and crossspecral mehods, Economerica, 1969,vol. 37,no. 3, pp Gujarai, D.N., Basic Economerics.1995, Tokyo: McGraw-Hill. Gor, S., Consumpion of Commercial Energy in he Residenial Secor of Kenya , Unpublished Maser`s Thesis,1994, Kenyaa Universiy, Nairobi. Jumbe, C.B.L., Coinegraion and causaliy beween elecriciy consumpion and GDP: Empirical evidence from Malawi. Energy Economics 2004,vol. 26, pp

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