A Co-Integration Analysis Between Electricity Consumption and Economic Development in Hebei Province

Transcription

1 Internatonal Journal of Energy and Power Engneerng 25; 4(4-): -6 Publshed onlne July 4, 25 ( do:.648/j.jepe.s ISSN: X (Prnt); ISSN: X (Onlne) A Co-Integraton Analyss Between Electrcty Consumpton and Economc Development n Hebe Provnce Huru Zhao, Yaowen Fan, Nana L, Fuqang L 2, Yuou Hu 2 School of Economcs and Management, North Chna Electrc Power Unversty, Bejng, Chna 2 North Chna Grd Company Lmted, Bejng, Chna Emal address: nancyl7@63.com (Nana L) To cte ths artcle: Huru Zhao, Yaowen Fan, Nana L, Fuqang L, Yuou Hu. A Co-Integraton Analyss Between Electrcty Consumpton and Economc Development n Hebe Provnce. Internatonal Journal of Energy and Power Engneerng. Specal Issue: Current Energy Issues n Chna. Vol. 4, No. 4-, 25, pp. -6. do:.648/j.jepe.s Abstract: Electrcty s a convenent and clean energy whch can provde strong support for the development of all walks of lfe. The power development should mantan coordnaton wth the regonal economc development, n whch power development may advance sometmes. Hebe provnce s a typcal resource-based area n Chna, and ts power consumpton s closely related to economc development, whch makes t mportant to study the relatonshp between electrcty and economc development n Hebe. In order to select the economc factors affectng electrcty demand, the gray correlaton analyss s used to analyse the correlaton among dfferent factors. And then, a long-term equlbrum model between electrcty consumpton and economc factors s proposed through co-ntegraton analyss. The analyss result showed that the electrcty consumpton, GDP, the level of resdental consumpton, effcency levels and economc structures have a long-run equlbrum relatonshp n Hebe Provnce, n whch the economc structure has the strongest mpact on the electrcty consumpton, followed by GDP, energy consumpton ntensty and the resdental consumpton level. Currently, the mpact of the economc restructurng on electrcty demand n Hebe cannot be overlooked. Furthermore, ths model can be used to gve a reference to Hebe Electrc Power Plannng. Keywords: Electrcty Consumpton, Economc Development, Co-Integraton Theory. Introducton In recent years, Hebe has made consderable progress n economy through takng advantage of the unque natural resources, geographcal locaton and other aspects. The GDP of Hebe has reached 2.83 trllon yuan n 23 and the average annual growth rate from 978 to 23 s.78%.meanwhle, Hebe s economc development s nseparable from the rapd growng electrcty consumpton. In 22, Hebe s total electrcty consumpton has reached bllon kwh, accountng for 6.2 percent of Chna's power consumpton and ts per capta electrcty consumpton s kwh. In recent years, as the non-statonary of the tme seres of electrcty and economy, the co-ntegraton theory related wth non-statonary tme seres has become the man method for the relatonshp analyss between power and economy. Engel-Granger method s mpled to estmate the relatonshp between the US energy and economy n []. Ths method has also been appled to the Group of Seven and 6 newly ndustralzed countres except Chna[2]. Analyss of the relatonshp between the Greek GDP and energy consumpton n has been made usng vector error correcton model[3]. In the related researches for Chna, Johansen Method has been used for Tawan n and [4-5], ths method has also been used to analyse the relatonshp between electrcty consumpton and economc development between and 97-2n Chna[6-7]. Hebe s located n north central Chna, and t s a typcal resource-based provnce whose electrcty consumpton condton s qute dfferent wth whole Chna obvously. Thus ths paper uses gray relatonal analyss model to select economc factors whch affect the electrcty demand most n Hebe. Then co-ntegraton analyss model has been proposed to llustrate the relatonshp between electrc demand and economc growth whch could be helpful for future electrcty plannng.

2 2 Huru Zhao et al.: A Co-Integraton Analyss Between Electrcty Consumpton and Economc Development n Hebe Provnce 2. Theory and Methodology 2.. Grey Correlaton Analyss The basc dea of gray correlaton analyss s to determne the degree of assocaton between factors based on the smlarty between the curve. Grey correlaton analyss usually compares the data seres whch reflects changes n each factor. The correlaton level between factors s judged by the degree of assocaton whch s obtaned by comparng the assocaton between factor curves. There are sx steps n the gray correlaton analyss: ()Determne the reference sequence and comparatve sequence X [ X(), X(2), X( n)] s the reference sequence and X [ X (), X (2), X ( n)](,2,, l) s the comparatve sequence. (2)Calculate sequencex and gray absolute correlaton φ of sequence X. Gray absolute correlaton s only assocated wth geometrc shape of sequence X and X, whch has nothng to do wth ther relatve locaton. The specfc formula s shown as follows: S S φ () S S S S Where, k, 2, n. S X ( k) X ( n) n k 2 2 (2) S X ( k) X ( n) n k 2 2 (3) X ( k) X( k) X() X ( k) X( k) X() (3) Calculate the gray relatve correlaton π between X and X. Gray relatve correlaton denotes the relatonshp between the changng rate of sequence wth respect to the startng pont. Namely, the closer the changng rate of X and X, the greater the gray relatve correlaton s. π ' ' S S ' ' ' ' S S S S Where, k, 2, n. (4) (5) S X ( k) X ( n) n ' ' ' k 2 2 (6) S X ( k) X ( n) n ' ' ' k 2 2 (7) ' X( k) X ( k) X() ' X( k) X ( k) X() (4) Calculate the grey synthetc correlaton degree ρ between X andx. ρ θφ ( θ) π Where, θ [,], n general, θ can be.5. (5) Select the key factors accordng to the calculaton results. Determne the threshold value for ρ and select the key factors. If synthetc correlaton degree ρ s bgger than ρ, X should be the key ndcator Co-Integraton Analyss Co-ntegraton was frstly put forward by Granger n 98and Engle and Granger proposed the theorem and ts concrete operatonal framework [8-9].In general, yt~i(d) shows that yt becomes statonary after d tmes dfferencng. If varables are all I(), ther lnear combnaton o usually satsfes I(). Further, statonary lnear combnaton seres can be called co-ntegrated whch mples the exstence of a long-term equlbrum relatonshp between the varables. When examne the statonary of each hstory seres, Augmented Dckey and Fuller(ADF) approach s usually used[]. ADF test s an mproved form of DF (Dckey and Fuller) unt root test n whch the statstcal test functon s presented as: t t t p (8) (9) X α βt δx θ X ε () Where t ε s the random error. It s an ndependent dentcally dstrbuted (..d.) whte nose process. For a gven level of sgnfcance, the tme seres s stable f the ADF test value s less than the crtcal value. The next step after the unt root test s JJ (Johansen and Juselus) co-ntegraton test. If two or more varables are I(d), ther lnear combnaton s co-ntegraton, whch can be defned as sad long-run equlbrum relatonshp[]. There are two ways to test the co-ntegraton: TRACE and MAX are commonly two output results n ths test.

3 Internatonal Journal of Energy and Power Engneerng 25; 4(4-): Quanttatve Analyss of the Relatonshp Between Power and Economy n Hebe Studes have shown that there s a certan relatonshp between the electrcty demand and economy development, whch has been demonstrated by scholars [6-7]. But the economc factors mpactng the electrcty demand have not gotten consstent conclusons. Economc growth, ndustral structure, populaton, urbanzaton rate, export and technologcal advance may affect the electrcty demand. Therefore, the gray correlaton model has been used to select the economc factors whch affect the electrcty demand most. The varables are pcked and defned as follows. Electrcty Consumpton (Q).The total electrcty consumpton of Hebe Provnce n 22 has reached bllon kwh, accountng for 6.2 percent of Chna's power consumpton, and accountng for.2% of world electrcty consumpton. Meanwhle, per capta electrcty consumpton of Hebe has reached kwh. Hebe Electrc Power Consumpton data s shown as Fgure. Resdental consumpton level (RCL). RCL reflects the lvng standards of local resdents. When n economc expanson, RCL s consderably hgh. From 978 to 22, the level of consumpton n Hebe provnce ncrease wth the growth of GDP, and reached,749 yuan (nomnal value) n 22. The data s shown as Fgure 3. Fgure 3. The resdental consumpton level n Hebe. Effcency level (EF). EF refers to energy consumpton ntensty. In 98-2, the energy consumpton ntensty of Hebe s reduced from 5. tons of standard coal to.66 tons of standard coal. The data s shown as Fgure 4. Fgure. The electrcty consumpton n Hebe. Gross domestc product (GDP).GDP refers to the gross domestc product n Hebe, whch reflects the level of economc development. The GDP of Hebe s trllon yuan n 22, accountng for 5.2 percent of Chna's GDP. The data of GDP s shown as Fgure2. Fgure 4. The energy consumpton ntensty n Hebe. Fgure 2. The GDP n Hebe. Economc structure (STRU).STRU refers to the tertary ndustry proporton of GDP. The proporton of the frst ndustry s relatvely small whle the proporton of the secondary ndustry s relatvely stable wth the hghest proporton. Compared wth 978, the proporton of prmary ndustry dropped from 28.52% to 2.37% n 22, the proporton of secondary ndustry has remaned at about 5% level, the proporton of tertary ndustry ncreased to 2.2% from 35.47% n 22. The data s shown as Fgure 5.

4 4 Huru Zhao et al.: A Co-Integraton Analyss Between Electrcty Consumpton and Economc Development n Hebe Provnce part of the data are processed logarthmc Results of Unt-Root Tests To check the statonary of varables used n the model, ADF test s adopted n ths paper, results are shown n Table 2. Table 2. Unt roott test of varables Fgure 5. The proporton of the tertary ndustry. 4. Model and Results 4.. The Gray Correlaton Analyss Seres lngdp Trends and nterceptt ADF value (C,C,3) lngdp (C,C,5) lnq lnq lnrcl (C,C,) (C,C,) (C,C,) lnrcl (C,C,) lnstru (C,C,) ln STRU (C,C,5) lnef (C,C,2) lnef (C,C,) P-Value *** ** ** ** *** To fully characterze the level of economc development, the GDP, resdental consumpton level, exports level, ndustry structure (tertary proporton) and techncal progress (energy ntensty) are chosen to select the key factors based on the gray correlaton analyss. Data nterval s and the results are shown n Table. Indcators Table. Gray correlaton analyss result Correlaton GDP RCL EXP STRU EF Rank When the ndcators ncrease, the co-ntegratorequres more data. Also, spreadsheet shows that total exports model n multvarate model has lttle effect on electrcty consumpton, so the followng varables are selected to buld the co-ntegraton model: GDP, the levell of consumpton, ndustral structure, and energy ntensty. In order to elmnate fluctuatons and heteroscedastcty, Table 3. The lag ntervals ndcates the frst dfference of a tme seres.***,** and *ndcate results are statstcally sgnfcant at %,5% and % levels, respectvely. As shown n Table 2, the nulll hypothess of a unt root could not be rejected. Results ndcate that the null hypothess of a unt root was sgnfcantly rejected n the second dfference. Therefore we conclude thatt all fve varables are at frst-dfference statonary, whch fulflls the requrements of the co-ntegraton test Select the Lag Intervals for VAR model We need to construct an unrestrcted vector autoregressve (VAR) that s composed of lnq, lngdp, STRU, lnrcl, and EF to analyze the co-ntegraton relatonshp among the varables. Therefore, we need to select the optmal lag order. In ths paper, we choose a lag of 2 by usng the Schwarz nformaton crteron (SC), sequental modfed LR test (LR), Fnal predcton error (FPE), Akake nformaton crteron (AIC) and Hannan-Qunn nformaton crteron (HQ).As shown n table 3, lag nterval of 2 s conformably chosen by the crtera of LR, AIC and HQ. Lag LogL LR NA * FPE AIC SC HQ 3.7e e * -2.6.e-6* * * *ndcates lag order selected by the crteron Johansen Co-Integraton Test We use trace statstc and the maxmum egenvalue statstc to estmate the number of co-ntegraton relatonshps and the normalzed co-ntegratng coeffcent. The results are shown as table 4.

5 Internatonal Journal of Energy and Power Engneerng 25; 4(4-): -6 5 Table 4. Co-ntegraton test results Hypotheszed No. of CE(s) Egenvalue Trace Statstc.5Crtcal Value Prob.** None At most At most At most At most Hypotheszed No. of CE(s) Hypotheszed No. of CE(s) Egenvalue Trace Statstc.5Crtcal Value None At most At most At most At most Trace method and the max egenvalue method show the presence of a co-ntegraton relatonshp between the varables, ndcatng that GDP, consumer level (RCL), ndustry structure (STRU),energy ntensty(ef)hold a long-term stable relatonshp wth electrcty consumpton. Table 5. Co-ntegraton coeffcents Co-ntegratng Equaton(s): Log lkelhood Normalzed co-ntegratng coeffcents (standard error n parentheses) 4.5. The Long-Term Equlbrum Model of Economy and Electrcty Demand The Co-ntegraton coeffcents n tme nterval s shown as table 5. lnq lngdp lnstru lnrcl lnef (.9965) (.29864) (.97) (.84) lnq.84lngdp.5lnrcl.6lnstru.67lnef () The results show that % of GDP growth can cause.84% growth n electrcty demand, pont change n tertary ndustry proporton accounted for.6% reducton n power consumpton, energy consumpton ntensty ncreases percent, electrcty consumpton ncrease.67%. The mpact of changes n the GDP s maxmum among all key factors affectng the demand for electrcty. 5. Concluson and Polcy Implcatons Through qualtatve analyss and gray correlaton analyss, GDP, the resdental consumpton level, ndustral structure, technologcal advancement have an mpact on electrcty demand n Hebe Provnce. The co-ntegraton analyss shows that long term equlbrum relatonshp among GDP, the resdental consumpton level, ndustral structure, energy ntensty (EF) s exst. % of GDP growth can cause.84% growth n electrcty demand, pont change n tertary ndustry proporton accounted for.6% reducton n power consumpton, energy consumpton ntensty ncreases percent, electrcty consumpton ncrease.67%. The mpact of changes n GDP s maxmum n all the factors affectng the demand for electrcty. The model also shows when future electrcty demand forecastng s beng made, economc growth, economc structure, lvng standards and techncal progress factors should all be take nto consderaton comprehensvely and the mpact of structural changes needs extra attenton. Acknowledgments Ths study s supported by the Humanty and Socal Scence project of the Mnstry of Educaton of Chna (Project number: YJA7927), the Natonal Natural Scence Foundaton of Chna (Project number: ), and Scence and Technology Project of State Grd Corporaton of Chna (Contract number: SGHBDKJS46). References [] Stern D I. Energy and Growth n the USA:multvarate approach[j]. Energy Economcs, 5(2), pp.37-5,993. [2] Soytas U, Sar R. Energy consumpton and GDP: causalty relatonshp n G7 countres and emergng markets[j]. Energy Economcs, 5(), pp.33-37, 23. [3] Hondroyanns G, Lolos S, Papapetrou E. Energy consumpton and economc growth:assessng the evdence from Greece[J]. Energy Economcs, 24(4), pp , 22. [4] Cheng B L, La T W. An nvestgaton of co-ntegraton and causalty between energy consumpton and economc actvty n Tawan [J]. Energy Economcs, 9(4), pp , 997. [5] Yang H Y. A Note on the causal relatonshp between energy consumpton and GDP n Tawan [J]. Energy Economcs.22(4), pp.39-37, 2. [6] Ln Boqang. Structural change, effcency mprovement and electrcty demand forecastng[j]. Economc Research, 38(5), pp , 23.

6 6 Huru Zhao et al.: A Co-Integraton Analyss Between Electrcty Consumpton and Economc Development n Hebe Provnce [7] Shu A, Lam P L. Electrcty consumpton and economy growth n Chna [J]. Energy Polcy, 32(), pp , 24. [8] Granger C.W.J. Some propertes of tme seres data and ther use n econometrc model specfcaton [J]. Journal of econometrcs, 6(), pp. 2-3, 98. [9] Engle R F, Granger C W J. Co-ntegraton and error correcton: representaton, estmaton, and testng [J]. Econometrca: journal of the Econometrc Socety, pp , 987. [] Dckey D A, Fuller W A. Lkelhood rato statstcs for autoregressve tme seres wth a unt root [J]. Econometrca: Journal of the Econometrc Socety, pp.57-72, 98. [] Johansen S, Juselus K. Maxmum lkelhood estmaton and nference on co-ntegraton wth applcatons to the demand for money [J]. Oxford Bulletn of Economcs and statstcs, 52(2), pp. 69-2, 99.