Applied Energy 112 (2013) Contents lists available at SciVerse ScienceDirect. Applied Energy

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1 Appled Energy 112 (213) Contents lsts avalable at ScVerse Scencerect Appled Energy journal homepage: Measures to mprove the performance of Chna s thermal power ndustry n vew of cost effcency Y-Shu Wang a, Ba-Chen Xe a,b,, L-Feng Shang a, Wen-Hua L a a College of Management and Economcs, Tanjn Unversty, Tanjn 372, Chna b Center for Energy and Envronmental Polcy, Insttute of Polcy and Management, Chnese Academy of Scence, Bejng 119, Chna hghlghts " Not only techncal effcency, but also cost nformaton s consdered n effcency evaluaton. " Take the undesrable output-carbon emssons nto model desgnng. " Prevous power polcy reforms do not have obvous effect on effcency mprovement. " Coal prce change s not the man factor that leads to cost effcency fluctuatons. artcle nfo abstract Artcle hstory: Receved 25 September 212 Receved n revsed form 11 January 213 Accepted 12 January 213 Avalable onlne 2 February 213 Keywords: Coal prce Cost effcency Malmqust ndex Sustanable development Thermal power ndustry The heavy losses of Chna s thermal power ndustry have attracted lots of attenton. Besdes the adjustment of power prce, how to mprove ts poor performance becomes an mportant ssue. Combnng the cost Malmqust wth the Luenberger ndex, ths paper ntroduces a new method to measure the cost effcences of Chna s 3 provnces thermal power ndustres wth carbon emssons consdered. Furthermore, we quantfy the nfluence of nput prce changes on the prce effect (PE) usng panel data regresson. The emprcal results ndcate that: (1) combnng dynamc effcency wth statc effcency, the results wll be more objectve; (2) compared wth prevous emphass on adjustng external factors, the future polcy reforms should ncentvze corporatons to mprove ther management; and (3) external fuel prce change s not the drect reason for cost effcency fluctuaton, and the thermal power ndustry should make more efforts to mprove ther techncal effcency. Ó 213 Elsever Ltd. All rghts reserved. 1. Introducton Thermal power s the predomnant generaton form n Chna; t has accounted for more than 8% of the total power generated over the past 5 years [1]. However, the thermal power ndustry has ncurred heavy losses n recent years. Snce the polces of separate power plants from the grd (SPFG) and yardstck power prce (YPP) were mplemented by the government [2], power prces have not been able to keep up wth the acceleratng rses n market-orented coal prces. Together wth the losses n the thermal power ndustry, natonwde power shortage has emerged, so t s extremely urgent to reverse ths poor operatonal trend. There are many ways to mprove the economc benefts of Chna s thermal power ndustry, two of whch are often used. One s to drectly ncrease sales revenue through rasng the Correspondng author at: College of Management and Economcs, Tanjn Unversty, Tanjn 372, Chna. Tel.: ; fax: E-mal addresses: xebachen@tju.edu.cn, xebachen@126.com (B.-C. Xe). power prce under a certan amount of power demand, the other s to decrease producton cost and reduce management, fnancal expenses by mprovng the cost effcency ndrectly. Wth regard to the former opton, the government has mplemented the polcy of coal-electrcty prce lnkage (CEPL) several tmes snce 25, but ths had no sgnfcant effect and power shortages occurred frequently. By contrast, through the mprovements of nternal cost effcency such as technology progress and resources allocaton optmzaton, power plants can counteract the negatve effect resultng from fuel prce changes to some extent. Thus we should pay more attenton to the later opton. Most of the tradtonal effcency evaluatons consder nformaton about usage quanttes but fal to take prce factors nto account. Furthermore, accordng to Internatonal Energy Agency (IEA) reports, 49.28% of Chna s carbon emssons came from thermal power producton n 21 [3]. It s deemed that the power ndustry should be gven pror attenton n mplementng polces of carbon emsson reducton [4,5]. Therefore, t s mportant to take both economc benefts and envronmental effects nto consderaton n evaluatng the ndustry s effcency /$ - see front matter Ó 213 Elsever Ltd. All rghts reserved.

2 Y.-S. Wang et al. / Appled Energy 112 (213) Abbrevaton SPFG YPP CEPL CRS VRS CE STE APE IM ML The polcy of separate power plants from the grd The polcy of yardstck power prce The polcy of coal-electrcty prce lnkage Constant Returns to Scale Varable Returns to Scale Cost Effcency Statc Techncal Effcency nput Allocaton and Prce Effcency Input based Malmqust productvty ndex of MU Malmqust Luenberger productvty ndex CM AEC PE CML OLS IPCC Shanx Shan-X Cost Malmqust productvty ndex Allocatve Effcency Change prce effect Cost Malmqust Luenberger productvty ndex Ordnary Least Squares Intergovernmental Panel on Clmate Change Located n North Chna regon Located n Northwest regon The nfluences of coal prce rses on the thermal power ndustres vary greatly among regons. Some can operate qute well whereas others suffer heavy losses. Ths ndcates that effcency dfferences exst wthn regons. Have recent polces had postve effects on mprovng the ndustry s effcency? How can changes n the external envronment nfluence effcency? These questons are closely related to natonal electrc power system reform. Therefore, t s mportant to study the statc and dynamc effcences of the thermal power ndustres n dfferent provnces and perods. 2. Lterature revew Among the numerous methods of effcency evaluaton, the non-parametrc EA method frst ntroduced by Charnes et al. [6] has been wdely used, relyng on ts characterstc of havng no need to consder dmenson and specfed functonal form between the nputs and outputs. The thermal power system s one of ts most mportant felds of applcaton, where there have been many achevements usng ths tool. The followng research extends pure statc effcency to dynamc productvty by combnng cross-secton effcency wth vertcal development. The majorty of scholars fnd that besdes nternal factors, external factors, such as polcy changes and economc development, also nfluence the effcency of the thermal power ndustry. The followng research lterature s partcularly relevant to the above three perspectves. Assumng CRS and VRS, Färe et al. [7] adopted the EA model based on a radal dstance functon to evaluate the pure techncal and scale effcency and nput congeston of 22 Illnos electrc utltes. Smlar research ncludes a cost effcency analyss for coalfred electrc generaton facltes n the US [8] and a techncal effcency analyss of Chna s thermal power generaton [9]. To verfy the stablty of the EA model, Lu et al. [1] conducted a stablty test n studyng the operatonal effcency of Tawan thermal power plants. To comply wth the current focus on sustanable development, the latest research takes envronmental effects nto consderaton. Sueyosh et al. [11] ncorporated both desrable and undesrable outputs nto the unfed analytcal structure to examne the performance of coal-fred power plants under the US Energy Polcy Act. Sözen et al. [12] defned two effcency ndexes whch dffer accordng to whether envronmental effects were consdered, and then nvestgated the relatonshp between effcency scores and ther nput/output factors. Assaf et al. [13] analyzed the cost effcency of Japanese steam power generaton companes usng the fxed and random Bayesan fronter models. Xe et al. [14] used a two-stage envronmental network EA model to study the effcency performance of Chna s power system. To measure the effcency change dynamcally, Färe et al. [15] developed an nput-based Malmqust productvty ndex accordng to Shephard s nput dstance functons and decomposed the ndex nto changes n techncal effcency as well as changes n the fronter technology. An emprcal study of 19 coal-fred steam electrc generatng plants n Illnos durng found that rates of productvty growth were relatvely stable, but sgnfcant productvty slowdown occurred n Yunos and Hawdon [16] compared the performance of Malaysa s Natonal Electrcty Board wth those of other countres at a smlar stage of development. Abbott [17] analyzed the changes n the Australan electrcty supply ndustry durng the perod from 1969 to 1999 and evaluated the nfluence of related reform on effcency. The Malmqust Luenberger productvty ndex, frst ntroduced by Chung et al. [18], was used to analyze the envronmentally senstve productvty growth of the thermal power ndustry [19,2]. Arocena and Waddams Prce [21] and Chang and Hu [22] employed the concept of total-factor productvty to study the dynamc effcency of electrcty generaton plants and regonal energy utlzaton. Jaratė measured the envronmental effcency and productvty of publc power generaton across the EU over the perod [23]. Consderng the uncontrolled external envronment of MUs, some scholars focused on ther effect on effcency. Charnes et al. [24] and Grosskopf and Valdmans [25] stratfed ther research samples n terms of categorcal varables that capture the characterstcs of the operatng envronment. Banker and Morey [26] drectly ncluded uncontrollable varables n ther lnear functons, along wth tradtonal nputs and outputs. Nowadays, the most common method ams to nclude uncontrollable varables by combnng a EA model wth regresson. Chlngeran [27] and Lam and Shu [9] employed Tobt analyss n the second stage to regress the tradtonal effcency scores obtaned n the frst stage aganst a set of selected uncontrollable varables. Yu et al. [28] dscussed the weather effects on performance of UK electrcty utltes. Sarks and Cordero [29] analyzed to what extent utlty ownershp, fuel structure and some polluton-preventon measures nfluence US power plant ecologcal effcency. Cost effcency provdes a perspectve for takng prce factors nto consderaton. Accordng to Manadaks and Thanassouls [3], t reflects the dstance between the mnmum cost of producng a gven output and actual cost. Thus, we conclude that cost effcency can provde a better reflecton of ndustry performance. As the potental handlng costs of carbon emssons are uncertan, a drectonal dstance functon s employed n whch emssons are regarded as undesrable outputs. Therefore, we employ a developed cost Malmqust Luenberger ndex (CML) n the followng analyss n whch the detaled potental handlng costs of carbon emssons need not be known. A regresson analyss usng the panel data s performed to determne whether coal prce changes wll greatly nfluence cost effcency [31]. The remander of the paper s organzed as follows: Secton 3 ntroduces the modfed cost Malmqust Luenberger ndex (CML) n detal; Secton 4 conducts an emprcal analyss of the performance of the thermal power ndustry over the perod from 2 to 21, usng 3 provnces

3 18 Y.-S. Wang et al. / Appled Energy 112 (213) as MUs, and measures the effect of nput prce changes on effcency; the conclusons are stated n Secton 5, together wth suggestons for mprovng the performance of the thermal power ndustry n Chna. 3. Methodology 3.1. Malmqust Luenberger productvty ndex Färe et al. [32] developed a non-parametrc approach to the calculaton of an nput-based Malmqust productvty ndex (IM) that has been appled to many felds [32]. However, f there are undesrable outputs, IM may not be computable. To overcome the shortcomngs of the tradtonal Malmqust ndex, Chung et al. substtuted drectonal dstance functons for Shephard s dstance functons and renamed t the Malmqust Luenberger productvty ndex. Suppose there are t =1,..., T tme perods, k =1,..., K MUs, n perod t each MU has nput vector x t ¼ x t 1 ;...; xt n, desrable output vector y t ¼ y t 1 ;...; yt m, and undesrable output vector u t ¼ u t 1 ;...; ut I. Suppose also that the output set meets the followng condtons: PðxÞ ¼fðy; uþ : x can produce ðy; uþg ðy; uþ 2PðxÞ and 6 h 6 1 mply ðhy; huþ 2PðxÞ ðy; uþ 2PðxÞ and y 6 y mply ðy ; uþ 2PðxÞ f ðy; uþ 2PðxÞ and u ¼ then y ¼ whch shows that the outputs (y,u) are weakly dsposable and y by tself s strongly dsposable. Moreover, the good output y s nulljont wth u. Choosng the drecton to be g =(y,u), the drectonal output dstance functons may be calculated as follows [33,34]:! t ðxt;k ;y t;k ;u t;k ;y t;k ;u t;k Þ ¼max b s:t: XK k¼1 X K k¼1 X K k¼1 z k y t km P ð1þbþyt k m ; m ¼ 1;...;M z k u t k ¼ð1bÞut k ; ¼ 1;...;I z k x t kn 6 xt k n ; n ¼ 1;...;N z k P ; k ¼ 1;...;K Furthermore, we defne Statc Techncal Effcency (STE) of each MU as follows 1 : ƒ! STE ¼ 1=ð1 þ Þ ð3þ! tþ1 ðx t ; y t ; u t Þ s the nput dstance functon for an nput output vector (x t,y t,u t ) at perod t relatve to the nput requrement set L t+1. Accordngly,! t ðxtþ1 ; y tþ1 ; u tþ1 Þ means the dstance for (x t+1,- y t+1,u t+1 ) relatve to L t. Calculaton of! t ðx tþ1 ; y tþ1 ; b tþ1 ; y tþ1 ; b tþ1 Þ needs to transform the rght-sde of the above constrant from perod t to t +1. Thus, between perod t and t + 1, ML s the geometrc mean of two Malmqust productvty ndexes: 2 1þ! t ðx t ;y t ;u t ;y t ;u t Þ 1þ! 3 tþ1 ðx t ;y t ;u t ;y t ;u t 1=2 Þ ML ¼ 4 1þ! t ðx tþ1 ;y tþ1 ;u tþ1 ;y tþ1 ;u tþ1 Þ 1þ! 5 tþ1 ðx tþ1 ;y tþ1 ;u tþ1 ;y tþ1 ;u tþ1 Þ 1 CRS can provde a hgher degree of dstncton, so EA model n ths paper s based on constant returns to scale assumpton. ð1þ ð2þ ð4þ ML ndcates productvty mprovements f ts value s greater than 1. In order to measure change n effcency and techncal change, or equvalent change n the fronter technology, ML s decomposed nto two components: ML ¼ TE TC 1 þ! t ¼ ðy t ; x t ; u t Þ 1 þ! tþ1 ðy tþ1 ; x tþ1 ; u tþ1 Þ " 1 þ! tþ1 ðy tþ1 ; x tþ1 ; u tþ1 Þ 1 þ! # 1=2 tþ1 1 þ! ðy t ; x t ; u t Þ t ðy tþ1 ; x tþ1 ; u tþ1 Þ 1 þ! ð5þ t ðy t ; x t ; u t Þ where the quotent outsde the bracket (TE) measures the change n techncal effcency, and the ratos nsde the bracket (TC) measure the shft n the producton fronter between perods t and t + 1[35] Cost Malmqust Luenberger productvty ndex The tradtonal Malmqust productvty ndex only consdered quanttes; t faled to take producton costs nto account. Manadaks and Thanassouls [3] used non-parameter mathematcal programmng to compute productvty and decompostons of ts change n terms of nput cost. Addng condton that w t s the nput prce under the assumpton n Secton 3.1, C t (y t,u t,w t ) defnes the mnmum cost of producng a gven output vector (y t,u t ) gven the nput prce w t and the technology of perod t. For unt k, C t (y t,- u t,w t ) can be calculated as follows: C t ðy t ; u t ; w t Þ¼mn x;z s:t: w t kn x n X J j¼1 X J j¼1 X J j¼1 z j y t jm P yt km z j x t jn 6 x n z j u t j 6 ut k z j P ; P The cost rato w t x t /C t (y t,u t,w t ) measures the extent to whch the aggregate producton cost n perod t can be reduced by securng the output vector (y t,u t ) under the nput prce vector w t. The relatonshp between Cost Effcency (CE) and STE can be defned as formula (7). CE ¼ C t ðy t ; u t ; w t Þ=w t x t ƒ! ƒ! ¼½1=ð1 þ ÞŠ ½ð1 þ ÞC t ðy t ; u t ; w t Þ=w t x t Š ¼ STE APE where nput Allocaton and Prce Effcency (APE) reflects the cost effcency whch s nfluenced by the prce of nput and ts allocaton ablty. Combned the merts of ML and CM, the cost Malmqust Luenberger productvty ndex of perod t, t + 1 s defned as follows: " # 1=2 CML ¼ Ct ðy tþ1 ; u tþ1 w t Þ=w t x tþ1 Ctþ1 ðy tþ1 ; u tþ1 ; w tþ1 Þ=w tþ1 x tþ1 C t ðy t ; u t ; w t Þ=w t x t C tþ1 ðy t ; u t ; w tþ1 Þ=w tþ1 x t where w t x t ¼ P N n¼1 wt n xt n, CML reflects the change of cost effcency, a value above 1 ndcates progress. Smlarly to ML, CML can also be decomposed nto components that gve nsghts nto the root causes of productvty change. Frst, CML can be decomposed as follows: ð6þ ð7þ ð8þ

4 Y.-S. Wang et al. / Appled Energy 112 (213) CML ¼ OECCTC ¼ Ctþ1 ðy tþ1 ;u tþ1 w tþ1 Þ=w tþ1 x tþ1 C t ðy t ;u t ;w t Þ=w t x t " # C t ðy tþ1 ;u tþ1 ;w t Þ=w t x tþ1 C tþ1 ðy tþ1 ;u tþ1 ;w tþ1 Þ=w tþ1 x C t 1=2 ðy t ;u t ;w t Þ=w t x t ð9þ tþ1 C tþ1 ðy t ;u t ;w tþ1 Þ=w tþ1 x t The component outsde the square bracket captures nput overall effcency change (OEC) between perod t and t + 1, whch examnes whether the producton unt catches up to the cost boundary durng the perod. The term nsde the square bracket s referred to as cost-techncal change (CTC), whch measures the shft of the cost boundary. For further nformaton, such as the effect of nput prce changes, the terms obtaned n the frst stage decomposton of CML can be decomposed further: OEC ¼ TEC AEC 1 þ t ¼ ðyt ; x t ; u t Þ 1 þ tþ1 ðy tþ1 ; x tþ1 ; u tþ1 Þ Ctþ1 ðy tþ1 ; u tþ1 ; w tþ1 Þ= w tþ1 x tþ1 1 þ t ðyt ; x t ; u t Þ h ð1þ C t ðy t ; u t ; w t Þ= w t x t 1 þ tþ1 ðy tþ1 ; x tþ1 ; u tþ1 Þ CTC ¼ TCH PE " # ¼ 1 þ 1=2 tþ1 ðy tþ1 ; x tþ1 ; u tþ1 Þ 1 þ tþ1 ðy t ; x t ; u t Þ 1 þ t ðytþ1 ; x tþ1 ; u tþ1 Þ 1 þ t ðyt ; x t ; u t Þ 2 h C t ðy tþ1 ; u tþ1 ; w t Þ= w t x tþ1 ð1 þ tþ1 ðy tþ1 ; x tþ1 ; u tþ1 ÞÞ 4 C tþ1 ðy tþ1 ; u tþ1 ; w tþ1 Þ= w tþ1 x tþ1 1 þ t ðytþ1 ; x tþ1 ; u tþ1 Þ h 3 C t ðy t ; u t ; w t Þ= w t x t 1 þ tþ1 ðy t ; x t ; u t 1=2 Þ 5 C tþ1 ðy t ; u t ; w tþ1 Þ= w tþ1 x t 1 þ t ðyt ; x t ; u t Þ ð11þ TEC n formula (1) and TCH n formula (11) correspond to TE and TC n formula (5) respectvely. AEC n formula (1) ndcates the extent to whch the unt catches-up wth the optmum nput mx n lght of the nput prces n each perod. The prce effect (PE) captures the shfts n the cost boundary, whch may be caused by relatve nput prce shfts. The relatonshp between CML and ML s: CML ¼ OEC CTC ¼ TEC AEC TCH PE ¼ ML AEC PE 4. Emprcal study 4.1. ata acquston ð12þ Takng 3 provncal admnstratve regons n Chna as MUs, 2 CML was used to study the dynamc cost effcency of the thermal power ndustry durng the perod from 2 to 21. In addton to raw materals, equpment, and labor nputs, the producton process consumes electrcty named auxlary power. Thus, the nputs are labor, nstalled capacty, energy consumpton and auxlary power. Snce there s wde electrcty dspatchng between provnces, takng the support of electrcty on the local economy nto account, ths study proposes GP supported by power, as well as power generated, to be desrable outputs. Carbon emssons are ncluded as undesrable output. As ntroduced n Secton 3, CML can be 2 Tbet s not ncluded because of ncomplete data. decomposed nto three parts: ML, AEC and PE; the last one reflects the drect mpact of external prce factors on cost effcency changes. Thus, the regresson analyss that followed used PE as the dependent varable and the nput prce ratos as the ndependent varables. etaled nformaton s shown n Table 1 [36 39] Analyss of statc effcences between provnces Based on formula (2) and formula (7), cost effcency of each provnce s thermal power ndustry can be calculated. The annual average CEs and ther decompostons of all provnces are shown n Table 2. In vew of statc cost effcency, few provnces le on the fronter, and only Bejng has been effcent over the entre perod. On the whole, for the regons wth developed economes, or where thermal power generaton plays a domnant role, t s easer to acheve hgh effcency. In provnces such as Hube, Guangx and Schuan, where clean energy s well developed, ther average effcences are.767,.754 and.77 respectvely, below the natonal average value. Accordng to STE and APE, we fnd that the techncal effcences of Zhejang, Hanan, Tanjn, etc. are hgher, but nput allocaton or external prce s not n favor of savng cost. Shanx, Shandong, Henan, etc. have hgher APEs where coal resources s rch and almost all power generated s thermal power, whle there exsts tremendous space for STE mprovement. For the provnces lke Schuan and Guangx where both STE and APE are lower, besdes technology restrcton brought by relatvely poor economc condtons, the development of clean energy wll nevtably reduce the equpment utlzaton of thermal power, thereby affectng the overall effcency of thermal power generaton Analyss of dynamc effcences between provnces Accordng to formula (8) (11), we calculated the annual average CMLs and ther decompostons as Table 3 showed. Majorty of CMLs are larger than 1, whch means the overall effcency of thermal power ndustry s ncreasng. The greatest dfference between dynamc effcency and statc effcency s that some provnces wth hgher proporton of clean energy, such as Qngha, Schuan, Hube and others, show hgher dynamc effcency. Especally, Schuan whose statc effcency s the lowest has the thrd hghest CML value of Ther hgh AEC values ndcate that thermal power ndustres n these regons have made efforts to optmze nput allocaton durng ths perod. Except for these provnces wth abundant clean energy, the dynamc effcency of Bejng s also hgh, as the same as ts statc analyss, whch ndcates that the thermal power ndustry of Bejng has pushed the cost fronter upwards. In lght of the detaled nformaton of decompostons, PEs n Shangha and Jangsu are only.99 and.978, from whch we conclude the man factor that restrcts ther cost effcency s the nput prce. However, for the provnces such as Jln and Nngxa, the technology and resources allocaton should be mproved urgently. The above analyss lacks detaled nformaton of effcency change for specfc provnces. We choose eght key provnces wth most thermal power producton to vew ther CMLs durng every perod, and then analyze the nfluence of external economc stuaton and polcy adjustments on ther dynamc effcences. etaled nformaton can be seen n Fg. 1. CMLs of power mportng provnces, such as Zhejang and Guangdong, have changed frequently durng the perod, whereas CMLs of equlbrum and exportng provnces fluctuate slghtly around 1. Ths means that the economc benefts of power mportng provnces are more vulnerable to the supply stuaton and polcy changes. In partcular, we fnd that Shanx, Hebe and others show lower dynamc cost effcences n 24, 25 and 28.

5 182 Y.-S. Wang et al. / Appled Energy 112 (213) Table 1 ata sources and processng. Indcator Varable type Unt ata sources ata processng Labor Input Person Chna labor statstcal yearbook The number of the electrcty, heat producton and supply ndustry s used nstead (21 211) Total energy Input Mllon tons Chna energy statstcs yearbook Converted by the coal, ol and gas physcal quantty consumpton (standard coal) (21 211) Installed capacty Input Mllon kw Chna power yearbook (21 211) Auxlary power Input Hundred Chna power yearbook (21 Avalable power generaton/(1auxlary power rate) auxlary power rate consumpton mllon kw h 211) Power esrable Hundred Chna power yearbook (21 Exclude auxlary power consumpton generated output mllon kw h 211) GP supported esrable Trllon yuan Chna power yearbook, Chna Real GP (25 constant prce) power generated/power consumed by power output (25 PPP) statstcal yearbook (21 211) Carbon emsson Undesrable Mt Chna energy statstcs yearbook Calculated by IPCC method based on energy consumpton. output (21 211) Standard coal prce Independent varable /ton Qnhuangdao coal tradng data Accordng to combuston values, standard coal prce = atong qualty mx prce 7/6, and data before 23 are estmated by the prce ndex [39] Average earnng Independent Chna labor statstcal yearbook Correspondng to the electrcty and heat producton and supply ndustry varable (21 211) Generator cost Independent /kw State electrcty regulatory Approxmate value s employed varable commsson report Electrcty prce Independent varable /kw h Chna prce yearbook (21 211) The annual average ndustral electrcty prce s calculated by the weghted average method Table 2 The average statc cost effcences and ther decompostons from 2 to 21. CE STE APE CE STE APE Anhu Jangx Bejng Laonng Fujan Inner Mongola Gansu Nngxa Guangdong Qngha Guangx Shandong Guzhou Shanx Hanan Shan-X Hebe Shangha Henan Schuan Helongjang Tanjn Hube Xnjang Hunan Yunnan Jln Zhejang Jangsu Chongqng Table 3 The average dynamc effcences and ther decompostons from 21 to 21. AEC PE ML CML AEC PE ML CML Anhu Jangx Bejng Laonng Fujan Inner Mongola Gansu Nngxa Guangdong Qngha Guangx Shandong Guzhou Shanx Hanan Shan-X Hebe Shangha Henan Schuan Helongjang Tanjn Hube Xnjang Hunan Yunnan Jln Zhejang Jangsu Chongqng One common characterstc of these regons s that almost all ther fossl fuel s coal, so the nfluence of ncreased coal prces s relatvely large. As well as coal, Guangdong uses ol and gas as fuel to generate power, thus ts unfed fuel structure led to less effcency reducton n the year when coal prces ncreased. To research further nformaton, accordng to fuel structures we

6 Y.-S. Wang et al. / Appled Energy 112 (213) / 2/1 3/2 4/3 5/4 6/5 7/6 8/7 9/8 1/9 Hebe Henan Guangdong Jangsu Inner Mongola Shandong Shanx Zhejang Fg. 1. CMLs of major power producng provnces Category I(coal&ol&gas) 1.95 Category II(coal).9 1/ 2/1 3/2 4/3 5/4 6/5 7/6 8/7 9/8 1/9 Fg. 2. Comparson of CMLs between dfferent categores. classfy representatve provnces nto two categores. 3 The average dynamc effcences of two types are shown n Fg. 2. The effcences of the two categores share smlar trends. Except for 26 the effcences of Category I prove to be hgher than those of Category II. Provnces belong to Category I mantan stable growth of effcency more easly, whch to a certan extent benefts from the buffer role of mxed structure aganst energy supply shortages by sudden rse n coal prce. Furthermore, coal-fred provnces dscharge more emsson of other ar pollutons such as NO X and SO 2, whch s not consdered n ths research, thus those provnces would get lower effcency [4] Analyss on effect of economc condton and polcy Fg. 3 shows the change n the average CML and ts decompostons durng the studed perod. In general, AEC fluctuates slghtly around 1, whereas PE changes more greatly. urng the frst three years, almost all these effcency ndexes remaned larger than 1. However, snce 23, the next year when Chna adopted the polces of SPFG, the dynamc effcency showed a downtrend, and CML decreased more than ML. Amed at brngng competton nto the thermal power ndustry, SPFG and YPP dd restran the development of some poorly performng thermal power plants, but they dsrupted prevous order of ndustry s operaton as well. Majorty of plants could not adapt to ths structural reform n a short tme, thereby delays the growth n effcency. Fortunately, the overall dynamc effcency remans more than 1; that s, the whole ndustry s cost effcency has stll ncreased. After 24, the coal prce changed more frequently than t dd prevously, and these ndexes have 3 Category I: Provnces wth a mxed structure of thermal power generaton, such as Shangha, Schuan, and Guangdong. Category II: Provnces that are domnated by coal-fred power, such as Shanx, Hebe, and Guzhou. fluctuated around 1. In general, the effcences would decrease obvously n years when the coal prce rose sharply. It seems that coal prce rse has a negatve effect on effcency. Furthermore, the low effcency n 26 s related to no effectve utlzaton of newly ncreased generator sets. The effcences ncrease slghtly n 27 and 29, but are stll around 1. Thus, we conclude the polcy of CEPL dd not have a substantal postve effect on effcency, even f t dd, postve effect would lag by about 1 year Analyss of panel regresson From the analyss above, we fnd that CML and ts decompostons changed obvously durng the studed perod, and the nput prce seems to be one factor. For further nformaton, a regresson aganst the nput prce was carred out. As noted above, PE reflects the shfts n the cost boundary caused by relatve nput prce shfts, and t shares the smlar trend as CML n Fg. 3. Thus, we select PE as the dependent varable. Before regresson analyss, we shall ntroduce the changes of nput prce over the perod. The labor cost changes vared greatly among dfferent provnces, but the coal prce changed consstently wth each other, as s the case for generator set and power prce. Fg. 4 descrbes the prce changes of generator set, standard coal and power. We can see that the coal prce rose faster than that of power. Comparatvely, the generator costs fluctuated durng the perod, they dropped before 24 and then fluctuated around 4 kw 1. It should be noted that although the plants need not pay for auxlary power, more auxlary power means less power for sale, thus we assume the cost of auxlary power s the ndrect reducton of sales revenue. Hoff [41] demonstrated that OLS was effectve n regressng effcency results aganst external factors. Accordng to the results of the unt root test, the data for ndependent and dependent

7 184 Y.-S. Wang et al. / Appled Energy 112 (213) AEC PE ML CML.95 1/ 2/1 3/2 4/3 5/4 6/5 7/6 8/7 9/8 1/9 Fg. 3. Comparson for CML and ts decompostons. 6 prce of generator set (thousand yuan/kw) prce of standard coal (thousand yuan/ton) prce of power (yuan/kwh) Fg. 4. Changes of nputs prces durng the perod.

8 Y.-S. Wang et al. / Appled Energy 112 (213) Table 4 Results of panel regresson. ependent aarable: PE Method: Pooled EGLS (Cross-secton weghts) Varable Coeffcent Std. Error t-statstc Prob. Constant Labor Fuel Generator set Power Weghted statstcs R-squared.994 Mean dependent var Adjusted R-squared.994 S.. dependent var.454 S.E. of regresson.36 Sum squared resd.381 urbn Watson stat Unweghted statstcs R-squared.39 Mean dependent var 1.4 Sum squared resd.392 urbn Watson stat varables prove to be stable. Through the F test, we select the mxed model as the optmal model, rejectng the varable ntercept and varable coeffcent models. As the objects of our research are populaton, not samples, we drectly choose fxed effects models. The results of regresson by Evews are shown n Table 4. From the results, we can see that the heterogenety n the panel data regresson makes the weghted least squares method superor to ordnary least squares. The labor earnng change has no sgnfcant effect on PE, but the prces of coal, generator sets, and power have a sgnfcantly negatve nfluence on PE, respectvely.66,.418,.261. The bggest negatve coeffcent of generator sets may explan why PE and CML stay at such a low level n 26, not only neffcent utlzaton of equpments but also the rse of generator sets prce cause the decrease of effcency. Compared wth generator sets and power, the coeffcent of fuel prce s the lowest, whch ndcates that general fuel prce change would not brng great change n PE. Whle Fg. 3 showed that fluctuaton of CML dd have a relatonshp wth the sgnfcant coal prce changes, we suppose one reason may be that sharp change of coal prce affects ML ndrectly. That s, fast ncreases of coal prce do not encourage techncal mprovements; n contrast, they brng lots of dsorder such as dle staff and equpment, whch leads to a decrease n techncal effcency. 5. Conclusons Choosng Chna s 3 provnces as MUs, we nvestgated the dynamc cost effcency of the thermal power ndustry from 2 to 21 usng a new ndex combnng CM and ML. The research takes both nput prce changes and the mplct cost of carbon emssons nto account. The decomposed ndex PE was then regressed aganst the nput prce rato ndexes. We obtaned the followng conclusons: (1) Results combnng dynamc effcency wth statc effcency prove to be more comprehensve, whch should be used n later performance evaluaton of thermal power ndustry. For the provnces wth hgh proporton of clean energy, we fnd that although effcences of ther thermal power ndustres have ncreased as a whole, there stll exsts substantal room for mprovement. For the thermal power domnated provnces, the ones wth mxed fuel structures usually acheve hgher dynamc effcency, so we should encourage a mxed fuel structure for better allocaton of resources and less carbon emssons. (2) The focus of future polcy reforms should shft from adjustng external envronment to encouragng corporatons to mprove ther management. The polcy of SPFG and YPP dd not ntroduce perfect competton; n contrast, the cost effcency of thermal power plants was restraned. Although t seems that CEPL helped to mprove the effcency, the nfluence of power prce changes s ndrect and post-acton. It s dffcult to ensure that the plants wll not suffer such a bg negatve effect n case of coal prce rse. Therefore, future polcy reform should arouse the plants enthusasm for producton and encourage themselves to ncrease utlzaton effcency of avalable resources. (3) Thermal power ndustry executves should pay more attenton to ther own techncal effcency rather than smply complanng about coal prce rse. Through the analyss above, we fnd that, although the fuel prce change has a slghtly negatve effect on PE, t has more nfluences on ML ndrectly. Nevertheless, almost each sharp rse of fuel prce s followed by a CML decrease, whch ndcates that how to ensure stable cost effcency s the prmary topc the authorty should consder. There are several effectve ways, ncludng encouragng a mxed fuel structure, mprovng the operatonal effcency of coal-fred generators, and elmnatng backward generator sets. However, our research has defcences that could be addressed. Frst, due to the lack of statstcal data, dfferent provnces share the same prces for coal, generator sets, and electrcty, whch may mask some useful nformaton. Second, consderng the characterstcs of EA model, we converted the ol and gas to standard coal unts and adopted ts estmated prce of t n the regresson analyss. To some extent, t wll affect the evaluaton results, especally for the provnces that consume more ol and gas. These ssues wll be mproved n future research. 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