Keskustelualoitteita #66 Joensuun yliopisto, Taloustieteet

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1 Keskuselualoea #66 Joensuun ylopso, Talouseee uel npu subsuon under radable carbon perms sysem: evdence from nnsh energy plans Mkael Lnden ISBN ISSN no 66

2 UEL INPUT SUBSTITUTION UNDER TRADABLE CARBON PERMITS SYSTEM: EVIDENCE ROM INNISH ENERGY PLANTS Mkael Lnden*,a, Ma Mäkelä** & Juss Uusvuor** SEPTEMBER 2009 *Deparmen of Busness and Economcs, Unversy of Joensuu ** The nnsh ores Reserch Insue (Mela), nland Absrac. ollowng he Kyoo proocol and he European Unon clmae polces larger han 20 MW energy plans are par of he EU s emssons-radng scheme (ETS). Ths greenhouse gas emsson mgaon sraegy, radable carbon quoa sysem, sared n The scheme s no mandaory for he frms wh sze less han 20MW. Also he frms usng renewable fuels wll no pay for allowances. Advanced energy producon echnologes enable power and heang plans o use boh nonrenewable fossl fuels and renewable wood fuels n energy producon. Wood fuel demand may consue a subsue for fossl fuel demand f he prce of radable carbon allowances s relavely hgh. In hs conex plan level panel daa from years n nland s analyzed wh panel and mxed models. Economerc demand equaons are specfed for he rao of wood and fossl fuel. The resuls show ha hgh allowance prces n he years 2005 and 2006 compared o he years 2003 and 2004 decreased he use of fossl fuels and he demand for wood fuels ncreased. Ths ncrease was he larger he smaller proporonal user of wood-fuel a plan was. However he downurn of allowance prces n year 2007 ended hs process. The heerogeney of energy plans n sze, ndusry and locaon deermnes he nensy and exenson of fuel use bu her role s lmed n he fuel subsuon. a) Correspondng auhor: mka.lnden@joensuu.f

3 1. Inroducon The European Unon emssons radng scheme (EU ETS) sared n The frs phase ended n 2007 and he second one began n 2008 and wll las unl The scheme encompasses he whole EU regon and s desgned o be he man nsrumen o reduce CO 2 emssons requesed by he Kyoo Proocol. Energy plans wh larger hermal npu capacy han 20 MW are ncluded whn he scheme, as well as ron, seel, mneral, pulp and paper ndusres and ol refneres. In oal, he frs phase of he sysem covered approxmaely 12,000 nsallaons, whch correspond abou 45% of EU s aggregaed CO 2 emssons. These nsallaons are ssued CO 2 emsson perms. The emsson allowances are each equvalen o a on of CO 2 and hey are provded from he nal allocaon or purchased whn he EU area. Power secor s he bgges and mos acve acor n EU's emsson radng. (Pon Carbon 2008; EC 2008.) In a cap and rade sysem such as EU-ETS a arge amoun of CO 2 emsson reducons se by polcymakers can be reached n a cos effcen way (Menaneau e al. 2003). In parcular, he sysem does no defne a mehod or a place how he emsson reducons should be made. To reach reducons n emssons, energy plans can () reduce her producon, () mprove her energy effcency by nvesmens, () nves n he carbon capure and sorage (CCS) echnology, or (v) subsue lowcarbon fuels, such as renewable fuels, for hgh-carbon fuels. Because of he naure of energy plans, (hey serve muncpales or ndusres), he frs opon s no commonly avalable. As o he opon of nvesmens, Baley and Dy (2008) noced ha UK emssons radng scheme had only a mnor mpac on nvesmen decsons of energy plans, whch could be he case n EU ETS n shor run. Also Kara e al. (2008) confrm he same fndng n her sudy lookng a he condons of he Nordc elecrcy markes. Noe ha on he general level emsson quoas and allowance markes se he frms n a complex and dynamc conex wheren shor and long run behavour may be n conflc (e.g. see Harsad and Eskeland 2007, Boucekkne e al 2008, Zhang 2007 and references heren). The fourh choce o reduce CO 2 emssons, subsung low-carbon fuels for hghcarbon fuels, can be carred ou whou subsanal rsks or expenses n many 1

4 crcumsances. In hs sudy we focus on hs opon, by nvesgang he subsuon of wood fuels for fossl ones usng nnsh frm-level daa. Because renewable fuels such as wood fuels are consdered as carbon neural n he EU ETS, fuel npu subsuon beween bo-fuels and fossl fuels may be favourable for energy producers. Even hough emssons radng enhance he compeve advanage of renewable fuels n energy producon n heory, emprcal sudes o confrm hs are rare. Parcularly, frm-level daa on he fuel-mxes of energy plans ha could be used n economerc analyses, are no commonly avalable. Tauchmann (2006) suded possble consequences of emssons radng by esmang he fuel prce sensvy of energy plans wh German daa. The analyss was based on a panel daa se of major German elecrcy producers from 1968 unl He concluded ha German energy ules have a low prce sensvy, whch ndcaes ha prces of CO 2 emsson allowances may have only mnor mpac on he fuel mxes of energy plans. However some resuls (e.g. Armura 2002) ndcae ha uncerany concernng he radng rules and prces under allowance markes dsor he frms fuel npu decsons. Even hough he fuel prce sensvy of energy plans may be low n German, s no necessarly so n he Nordc counres, whch s ndcaed by Brännlund and Lundgren (2004). They suded he fuel npu subsuon of Swedsh heang plans under wo dfferen polcy changes by usng a cos share lnear Log model. In her smulaons, he boh polcy nsrumens, a CO 2 axaon and a subsdy for wood fuel producon, ncreased he demand for wood fuels subsanally. The heerogeney of energy plans affecs he demand for wood fuels also whn froners. Brännlund and Krsröm (2001) found ou ha prce elasses for dfferen fuels vary wh plan sze, whle hey suded he mpacs of changes n Swedsh energy axaon. German and nnsh producon srucures n energy producon dffer from each oher by her fuel-mx and also by her combuson echnology. As noed n Tauchmann (2006) hard coal and lgne are domnan fuels n German, whle bo-fuels, coal, naural gas and pea are he mos sgnfcan fuels n nland. In erms of combuson echnology, pulverzed fuel and fludzed bed combuson are he wo man echnologes for sold fuel ulzaon. The former s essenally a coal burnng 2

5 echnology, whle fludzed bed combuson s more suable for mul-fuel ulzaon (Kangas e al. 2009). I s hs laer combuson echnology whch s domnan n nland, hus makng he crcumsances for fuel npu subsuon under he EU-ETS perhaps beer n nland as compared o Germany. urhermore, pea s a relavely mporan fuel n energy producon n nland. uel properes of pea and wood are relavely smlar, whereupon pea can be ofen subsued for wood also n unsophscaed bolers. nland s commed o ncrease s share of renewable energy source (RES) from 28,5% o 38% by 2020, whch has led o he neres o promoe wood fuel ulsaon n he counry. Currenly, n he nnsh energy polcy, he EU-ETS s he mos mporan energy polcy nsrumen o promoe RES n he emssons radng secor, even hough many oher EU counres apply also eher feed-n arff sysems or radable green cerfcae sysems o suppor RES. Thus, s worhwhle o sudy how hs EU wde clmae polcy ool affecs he subsuon beween wood and he fossl fuels n nland. Ths sudy focuses on wood fuel ulzaon excludng black lquor. Bomass s he mos mporan RES n nland, wh he share of over 80%. The am of he paper s o sudy he mpacs of he EU-ETS on he fuel subsuon by usng an economerc approach. We do hs by akng no accoun he heerogeney of energy plans wh respec o her sze, ndusry ype and locaon. or example, he supply of wood fuels resrcs he demand for wood fuels dfferenly n dfferen regons of he counry. urhermore, large energy plans are no ofen able o purchase exensve amoun of wood fuels because of ransporaon coss combned wh relavely low energy conen of wood. Also, he ype of energy plan s a deermnng facor n erms of he fuel subsuon: an energy plan relang o he fores ndusry use naurally more wood fuels han e.g. a muncpal energy plan. Addonally, he mechansm of emssons radng causes varaon n wood fuel ulsaon among dfferen sze caegores of energy plans. The res of hs paper s srucured as follows. We frs derve fuel npu demand properes from a smple sac model o movae he economerc approach used n he emprcal par of he sudy. In he followng secon he plan-level energy npu and emsson radng prce daa are presened. Afer hs, he economerc 3

6 specfcaons and esmaon sraeges are descrbed ogeher wh he resuls. We end wh conclusons and dscusson. 2. Dervng fuel npu demands wh allowance perms Consder a frm ha s forced o nernalze s greenhouse gas emsson as a byproduc of he producon process. Ths happens wh governmen ssung a lmed number of polluon perms or allowances o he frms. rms whose margnal abaemen coss are larger han he allowance prce can oban exra allowances from less pollung frms. Typcally he frm buys hese allowances from radable permsson markes. An alernave way o conrol emssons s o use a less pollung echnology or use low emng npus n he producon process. Decreasng supply of he oal number of pollung perms ncreases he allowance prce makng hese alernave emsson reducon mehods more feasble. Over all, effcenly workng emsson perm marke s seen as he leas cos sysem o reduce greenhouse gases (Teenberg 2006). Assume ha he frm has wo fuel npus: one wh hgh emsson rae (H), and one wh low emsson rae (L) eh > el. Only he former s conrolled wh radable permssons. Le eh H = m be he number of allowances ha he frm obans from he sae n he frs place. The emssons e from he npu usage s ehl (, ) = eh H+ el L. The governmen ssues he fxed number of allowances for he frms,.e. M N = m. Thus M s he oal number of permssons for he frms ha can be = 1 redsrbued whn he permsson rade. rm can buy a number of perms o ncrease s emssons, PX[ eh eh] = PX[ m m ] >0 wh radable marke prce. P X Now he frm s prof maxmzaon problem s followng MAX{ pf( H, L) c( H, L) P [ e H e H], HL, X H H 4

7 where p s he fxed prce of oupu and chl) (, s he convex cos funcon of fuel npus. The frs order condons wh a lnear producon funcon f H + f L 1) are H L pf = c + P e pf H H X H L = c L. The margnal producs of npus equal her margnal coss ncludng he margnal coss of allowance rghs. As Pe X H s posve he frm uses less H npu compared o a frm ha s no forced o nernalze s emssons. Noe also ha f f H > f and L c H < c he reducon n H s no necessarly large f he allowance radng prce P X s L low. Some relevan comparave sacs resuls are obaned by oal dfferenang he frs order condons wh respec o H, L, and P X : chh chl dh eh dpx = clh c LL dl 0. Solvng wh Cramer s rule for dl / dp and dh / dp X X gves e c dh / dpx = < 0 cl L > 0, c c c H LL 2 HH LL HL e c dl / dpx = > 0 cl H < 0. c c c H LH 2 HH LL HL The ncrease of allowance prce usage ( dh < 0) ( dp X > 0) leads o decrease n hgh emsson fuel H. However he demand for low emsson npu L ncrease n response o an ncrease n he allowance prce dl / dp X > 0 subsues o each oher n energy producon,.e. f he raw maeral npus are clh = c HL < 0. 1 ) f and f sand for paral dervaes of f(h,l) wh respec o H and L. These margnal producs H L are measured as he consan un effcences of he fuel npus n power and hea producon. 5

8 3. Daa The economerc analyss n hs sudy reles on a regonal frm-level daa colleced by nnsh ores Research Insue (METLA). The daa-se used comples sascs on he sold wood fuel ulzaon beween The annual daa conss of approxmaely 800 energy ules wh her nomnal effcences, plan characerscs lke regonal locaon and ndusry ype, and amouns of ulzed wood fuels n energy conen. Snce he frm-level daa abou fossl fuel consumpon was no avalable, was esmaed hrough a represenave energy plans approach. Energy plans were classfed no four dfferen groups, as he yearly ulzaon raes of dfferen ypes of plans dffer sgnfcanly. These four ndusry groups are: small communy plans, large communy plans, energy plans relaed o sawmlls and energy plans relaed o pulp or paper ndusres. The annual observaons of fuel-mxes were based on observaons from 4 o 30 represenave energy plans, dependng on he ndusry group. The fossl fuel consumpons were esmaed hrough a compled sascs on ulsed wood-based fuels and nomnal effcences assumng ha he annual ulzaon raes of energy plans are equal among dfferen groups. Allowance prce level was esmaed o be 5-20 per onne n mos predcons before he begnnng of he EU-ETS (POMAR 2007). However, he volaly of allowance prce was hgh durng he frs phase. In he begnnng of he phase, he prce level rose from 8 o over 30 per onne by summer Durng auumn 2005 o sprng 2006 he prce seled on he level of The nformaon abou realzed CO 2 emssons n 2005 led o he collapse of allowance prces n lae sprng 2006 and decreased he prce level from almos 30 o below 10. The prce recovered slowly o he level of 15-20, before sared o snk agan owards he end of The prce deprecaed seadly and wen below 1 n sprng 2007 and sood close o zero unl he end of he frs phase. Noe ha we don have daa on fuel npu prces a frm level. However we know ha aggregae prce rao of wood and fossl fuel npus have been sable durng he perod analyzed. Thus he role of prce rao varable n he model s of second order mporance. 6

9 4. Economerc Models and Resuls In he followng we specfy hree models o sudy he subsuon beween wood and fossl fuels. We esmae he response of rao beween wood and fossl based raw maeral npus o changes n he CO 2 allowance prces. The models are augmened wh energy producon scale, ndusry, and regonal specfc effecs. Random and xed Effec Models Consder he followng Random Effec (RE) panel daa model ha esmaes he response of rao beween wood and fossl based raw maeral npus (ln( E / E )) o W changes n he CO 2 emsson radng prces (ln EMISP ) ln( E / E ) = α + β lntrend + β D20MW + β ln EMISP W β D20MW ln EMISP05 + β D20MW ln EMISP β D20 ln EMISP07 + c DSAWMILL + c DINDUSTRY j 1 j j α + = + c DINDUSTRY 2 + d ln CAPACITY + g REGION + ( ε) Tradng s oblgaory for plans larger han 20MW usng fossl based fuels n energy producon. (Kara e al. (2008) esmaed ha 62% of nnsh nsallaons ha are producng CO 2 emssons are ncluded no he scheme.) As all plans n he sample use wood-fossl fuel npu mx n energy producon, he rao s a naural fuel npu adjusmen measure when he emsson rade prces vary. The radng sysem sared n he year The annual dfferences of prce responses for plans represenng dfferen ndusry ypes are modeled wh he followng varables E W / E 7

10 0, year , year 2004 ln EMISP = emsson radng prce: ln(28 Euro / on), year 2005 ln(23 Euro / on), year 2006 ln(9.5 Euro / on), year 2007 D20 MW = 0, plan s smaller or equal o 20MW 1, plan s larger han 20MW D20MW ln EMISP05 = emmson radng prce for plans > 20MW n year 2005 D20MW ln EMISP06 = emmson radng prce for plans > 20MW n year 2006 D20MW ln EMISP07 = emmson radng prce for plans > 20MW n year 2007 The frs varable measures he general emsson prce effec on fuel usage. The small plans may adjus oward greener fuel mx albe hey are no forced o pay emssons. The dummy varable D20MW gves he sze caegory effec on he fuel rao. The las hree varables gve he year specfc emsson prce effecs for large plans,.e. he plans whch have o pay for CO 2 emssons f hey use fossl based fuels. The sample ncludes small plans ha are conneced closely o wood-processng ndusry. The dummy varable DSAWMILL receves he value 1, f he plan s par of a sawmll, oherwse receves he value 0. The dummy varable DINDUSTRY1 caegorzes he plans beween process ndusry and non-process ndusry classes. Smlarly, he varable DINDUSTRY 2 caegorzes he plans beween communy energy ules and oher ndusry classes. The scale of energy producon deermnes he exenson of fuel use. We use n hs conex ln CAPACITY as he sze varable. I measures he average level (n %) of used nomnal oupu capacy of he plan per year. Noe ha boh E w and E are measured also n MWh. Thus he rao EW / E s whou uns. However as we use he logarhmc ransformaon, ln( E / E ) = ln E ln E, we can argue ha s W w 8

11 response o a change n some explanaory varable sll has he MWh nerpreaon besdes he ypcal elascy nerpreaon conneced o logarhmc varables. nally lntrend = 0,1, 2,3, 4 measures he general busness condon n he energy secor durng he years The las foureen dummy varables,, REGION j j = 1, 2,...,14 selec for each plan he regon (measured as fores dsrcs) where he plan s locaed. We argue ha he dfferen regons have dfferen fuel supply profles, especally concernng he wood based fuels. The reference regon s he REGI ON 0, he Åland archpelago n Souh-Wes nland, where small wood based plans are common. α 0 s he general nercep of he model, α ' s are he random frm-specfc effecs, and ε s he normally dsrbued error erm. Noe ha he RE-specfcaon requres ha α ' s are uncorrelaed wh ε s and wh he explanaory varables (for more deals, see Balag 2008). The Hausman es repored n Table 1 rejeced hs uncorrelaon. The fxed effecs (E) panel daa model can be esmaed whou hs requremen bu hs alernave s no feasble n hs conex snce he specfed model ncludes several me-nvaran varables. Insead we propose a 2-sep or herarchcal E 2 -model: we frs esmae he fxed effecs wh a panel model ha excludes any oher me-nvaran varables han he cross-seconal dummes,.e. dosyncrac consans for he plans. The LSDVesmaes for hese are regressed hen n second sep on all oher me-nvaran varables. Table 1 repors he resuls from RE and E 2. gure 1 gves he esmaed fxed frm-level effecs. The negave sgn for he varable D20MW ndcaes ha large plans use relavely more fossls fuels compared o small plans. On he average he effec s E / E = exp( 8.34) n he RE esmaon and E / E = exp( 17.17) n he E 2 W esmaon. The coeffcen esmaes of he emsson prce varables ndcae ha he use of wood based fuels has ncreased. The prce effec s he larges n 2005 on he large fossl fuel usng plans. In oal he emsson radng durng has ncreased he demand for wood fuel (on average, measured n MWh) wh effec of W 9

12 Table 1. RE and E 2 esmaon resuls. T = 5, N = 722, Toal panel (unbalanced) = Dependen varable ln ( EW / E) RE MODEL 2-level E MODEL Coeffcen HCSE -value Coeffcen HCSE value C * lntrend * lnemisp * 2.30 D20MW D20MWxlnP * 4.18 D20MWxlnP * 3.59 D20MWxlnP * 0.01 DSAWMILL DINIDUSTRY DINDUSTRY lncapacity * REGION REGION REGION REGION REGION REGION REGION REGION REGION REGION REGION REGION REGION REGION R */0.404 DW */1.51 JB-Normaly */4.23 Hausman RE/E-es es for fxed effecs 14.36* *) refers o he 1s sep of E 2 esmaon E / E = exp( ) =2.43 and E / E = exp( ) = W W The negave sgn of DSAWMILL s unexpeced. 10

13 gure 1. The frm specfc effecs of ln(e W /E ).076 fxed effecs for frms Densy AI Kernel densy esmae for AI The resuls for ndusry dummes are oppose n he RE and E 2 esmaons. Noe ha he resuls are no comparable snce he E 2 esmaon ncludes only a subse of he varables of RE-esmaon n he frs sage, and he second sage esmaon (OLS on esmaed frm specfc fxed effecs) also dffers from he RE-esmaon. The resuls from RE-esmaon are as expeced as he mos of process ndusry and communy energy plans are large uns usng relavely more fossl based fuels compared o small plans. Also he regon dummes are negave. The plans are larger on he manland regons compared o he Åland plans. nally ln CAPACITY varable has a posve coeffcen n boh esmaons ndcang ha he hgher s he level of capacy he more wood fuel s used. Noe ha ypcally he large uns have hgher capacy level han he small ones. As our esmaons nclude he varable D20MW o capure he plan sze effec we argue ha he posve capacy effec on he fuel rao sems from plans close o, bu below, he sze of 20MW. 11

14 The model fs are n sascal erms adequae. The resduals are normal n RE eamaon, he model explans close o 36% of he varaon n ln( E / E ), he random plan componens explan 38% of he error varance, and he DW-value ndcaes ha no resdual auocorrelaon s presen. However he Hausman es rejecs he RE-specfcaon makng he esmaes nconssen. Ths means ha we have o emphasze he E 2 resuls or use some oher, a more general esmaon approach, whch would allow for conrollng he evden random heerogeney n observaons. W ln( EW / E ) Whle he E 2 resuls above are adequae, he 2-sep E-model can be consdered o be a farly resrcve and awkward approach o model and esmae boh he planwhn and plan-beween varably n he plans fuel rao ( E / E ) W. Therefore we nex nroduce a model alernave, he Random Coeffcen, or mxed 2-level model, whch ncorporaes no one sngle model boh aspecs of he ndvdual plan varably. Ths mxed model alernave s a general model approach ha enables one o effcenly conrol and esmae he observed and unobserved heerogeney among he plans. In addon we oban some neresng esmaes descrbng he evoluon of he sochasc srucure of he daa and model coeffcens ha are no obaned from he RE- and E-models. Random Coeffcen Model In hs model we used he followng specfcaons n he wo sages: 1-level ln( E / E ) = α + β lntrend + d lncapacity + ε W 1 2-level α = α + α D20MW + α ln EMISP + α DSAWMILL + α DINDUSTRY α DINDUSTRY 2 + α REGION + ζ 5 j= 6 j j α, 19 β = β + β D20MW + β ln EMISP + β DSAWMILL + β DINDUSTRY β DINDUSTRY 2 + β REGION + ζβ 5 j= 6 j j, 19 12

15 ε ξ 0 σ σ N 2 2 α, α αβ (0, σε ) and N,. 2 ξ β, 0 σβα σ β The mxed model assumes ha some of he frs sage model parameers are random n he cross-seconal dmenson. The α parameer measures he plan-beween varably of l n( EW / E) and β measures how hs varably changes n me. However he plan-whn varably s also modeled because we explan he frs sage (random) coeffcens wh plan specfc me-nvaran conrols. nally we allow also for dosyncrac randomness or unobserved heerogeney for plan responses α and β,.e. each oher. ζ α, and ζ β,. Noe also ha α and β can correlae wh The compose form of he above model s called he condonal model ha ncely shows he versaly of he mxed model approach ha ncludes all he 2-way neracon erms wh he l ntrend varable ln( E / E ) = α + α D20MW + α ln EMISP + α DSAWMILL + α DINDUSTRY1 W α DINDUSTRY j= 6 j j 19 α REGION + ( β + β D20MW + β ln EMISP + β DSAWMILL + β DINDUSTRY β DINDUSTRY 2 + β REGION ) lntrend 5 j= 6 j j + d ln CAPACITY + ( ζ + ζ ln TREND + ε ). 1 α, β, The model consss of 48 fxed effecs parameers and of 4 random (covarance) parameers ( σ, σ, σ, σ a ε α β β ) ha all can be esmaed conssenly wh Maxmum Lkelhood (ML) or RESTRICTED Maxmum Lkelhood (REML) mehods. Noe ha we canno use D20MW ln EMISP05 -ype year specfc varables n he model as hey lack he needed cross-seconal varably n hs conex. However, 13

16 augmenng he model wh a more general neracon varable D20MW ln EMISP we receve all relevan nformaon from he model concernng he emsson prce effecs on l n( EW / E). Table 2 presens relevan resuls afer some prelmnary esmaons and model reducons. Table 2. Mxed model esmaon Varable Coeffcen esmae -value Inercep lntrend D20MW lnemisp lntrend * D20MW lntrend * lnemisp D20MW * lnemisp DSAWMILL DINDUSTRY DINDUSTRY lntrend * DSAWMILL lntrend * INDUSTRY lntrend * INDUSTRY lncapacity REGION REGION REGION REGION REGION REGION REGION REGION REGION REGION REGION REGION REGION REGION The resuls are neresng and close o he ones receved earler. Mos neresngly lntrend ln EMISP varable s now sascally sgnfcan wh posve value of 0.78 and has many mes larger value han earler (0.62 compared o 0.16 and n Table 1). Boh are posve ndcang ha n he sample here has been a srong shf owards usng more wood based fuels durng he years Noe ha he 14

17 neracon varables lntrend D20MW and lntrend ln EMISP are negave. The former has a naural nerpreaon: he large plans use relavely more fossl fuels compared o small plans durng he sudy perod. We argue ha he rend effecs domnae n he laer neracon varable snce we conrol separaely for emsson prces wh varables l n EMISP and ln EMISP D20MW. Snce hese boh are posve he emsson prces have reduced he use of fossl fuels especally for large plans. Table 3 shows ha he random par of he model s sascally sgnfcan. There exss random varably among he plans fuel rao boh n he cross secon and n me dmenson. The varance n he growh of change of he nal sae EW / E s much smaller han he varance n he nal sae EW / E self. The me dependen growh varaon (he slope varaon) beween plans s more han fve mes less han he sae (or nercep) level varaon (1.814 and 8.622). Naurally frm sze and echnology condons resrc s growh possbles. Noe also ha he perod beween he years 2003 and 2007 n nland was a perod of seady economc growh. In spe of hs he covarance beween he nercep and me slope E W / E coeffcens s negave and her correlaon ρ ab, σ αβ = s Ths means σ σ 2 2 α β ha here exss a convergence among he random plan specfc componens ζ α, n me,.e. he smaller he plan level E W / E nally was he faser grew n me. Ths offers addonal suppor o he resul ha subsuon from fossl fuels o wood fuels has aken place among he sample plans durng he perod of Table 3. Esmaes of Covarance Parameers Parameer Esmae Sd. Error Wald Z P-value 2 Resdual σ ε Inercep 2 σ α lntrend 2 σ β σ αβ

18 A relaed and more precse nformaon concernng he frm specfc l n( EW / E) evoluon s obaned from he me dependen varance of he compose error,.e. he me dependen cross-seconal varance σ = VAR[ ζ + ζ ln TREND + ε ] 2 α, β,, = σ + σ lntrend + σ + 2σ ln TREND ( = 1, 2,..., T ) α β ε aβ Noe ha σ 2 s quadrac n me and has a mnmum value f σ < 0..e. MIN 2 = exp( σ / σ ). The esmae for hs me pon s e. he TREND αβ β convergence sops afer md year The resul s obvous as he emsson radng sared n year 2005 and he plans have o adjus her fuel mx under he new polcy. In fac he cross-secon error varance evolves n years wh he followng values ( ). Clearly he mnmum s n year Thus he plo of he cross secon varances s hump-shaped ndcang ha he plans have responded o nroducon of emsson radng homogenously. However afer he year 2005 hs endency of unobserved heerogeney among he frms has changed. αβ 5. Conclusons and Dscusson Economerc sudes on he mpacs of he EU radable CO2 perm sysem on he fuel demand have remaned scarce. In hs sudy we provded new resuls concernng he mpacs of he EU-ETS cap and rade sysem on he fuel mx of energy plans. We used daa from nland, where he ndusral and polcy conexs sugges ha he radable CO2 perm sysem mgh have had larger mpacs han perhaps n oher European counres. The resuls ndcae ha he EU-ETS sysem has ncreased he wood energy consumpon of he plans, and ha wood fuels have been subsued for fossl fuels. However, over he perod of hese mpacs seemed o have declne. There are a lo of energy-nensve ndusres. e.g. he fores and seel ndusres n nland, whch have drven he nnsh energy secor owards cenralzed uns. Also 16

19 he cold clmae has affeced ha local dsrc heang sysems have peneraed consderably n he counry (Ercsson e al 2004). The large uns mply ha he EU- ETS covers an exceponally large share of he oal CO 2 emssons n nland, whch ncreases he mporance of he sysem n he nnsh condons, and whch may have conrbued o he resuls receved n hs sudy. Emsson radng and possble hgh prce level of he emsson allowance n he fuure do no auomacally guaranee an ncreased use of wood fuels n nland. or n oher counres wh smlar condons. Because he energy conens of unprocessed wood fuels, e.g. fores chps, are relavely low, long ransporaon dsances are no profable. Ths means ha wood-fuel markes reman regonal. Anoher ssue relaes o he markeng poson of energy producers. A dsrc hea producer has usually a monopoly poson on regonal markes, whch enables ransferrng he cos of purchasng CO 2 perms o he hea prces (Brännlund e al. 2004). Ths may reduce he subsuon mpac of emssons radng. Leraure Armura, T. H An Emprcal Sudy of he SO 2 Allowance Marke: Effecs of PUC Regulaons. Journal of Envronmenal Economcs and Managemen. 44: Balag, B.H Economerc Analyss of Panel Daa, 4 h ed. Wley, NY. Boucekkne, R., Hronenko, N. & Y. Yasenko Opmal rm Behavour under Envronmenal Consrans, CORE DP Baley. I. & Dy. C Energy markes. capal nera and economc nsrumen mpacs. Clmae Polcy. 9: Brännlund, R and Krsröm, B Too ho o handle? Benefs and coss of smulang he use of bofuels n he Swedsh heang secor. Resource and Energy Economcs. 23: Brännlund, R. and Lundgren, T A dynamc analyss of nerfuel subsuon for Swedsh heang plans. Energy Economcs. 26: Brännlund, R., Marklund, P-O. and Sjösröm, M Evaluang Marke Effcency whou Prce Daa: The Swedsh Marke for Wood uel. Appled Economcs. 36:

20 Ercsson, K., Huunen, S., Nlsson, L. J. and Svennngsson, P Boenergy polcy and marke developmen n nland and Sweden. Energy Polcy. 32: Harssad, B. & Eskeland, G.S Tradng for he uure. Sgnalng n Perm Markes. CICERO WP Kangas. H-L., Lnunen. J. & Uusvuor. J The Cofrng Problem of a Power Plan under Polcy Regulaons. Energy Polcy (n press). Kara. M., Syr. S., Lehlä. A., Helynen. S., Kekkonen. V., Ruska. M., & orssöm. J The mpacs of EU CO 2 emsson radng on elecrcy markes and elecrcy consumers n nland. Energy Economcs. 30: Menaneu, P., non, D. & Lamy, M Prces versus quanes: choosng polces for promong he developmen of renewable energy. Energy Polcy. 31: Pon Carbon hp:// Refereed POMAR Marke analyss and rsk managemen of EU emsson radng. Projec Repor. Unversy of Helsnk. Tauchmann. H rng he furnace? An economerc analyss of ule` fuel choce. Energy Polcy. 34: Teenberg, T. H Emsson Tradng: Prncples and Pracce. 2nd edon. R. Washngon. 233 p. Zhang, Does Uncerany Maer? A Sochasc Dynamc Analyss of Bankable Emsson Perm Tradng for Global Clmae Change Polcy. World Bank Polcy Research WP