Understanding the Interactions between Emissions Trading Systems and Renewable Energy Standards Using a Multi-Regional CGE Model of China

Transcription

1 Policy Reseach Woking Pape 8159 WPS8159 Undestanding the Inteactions between Emissions Tading Systems and Renewable Enegy Standads Using a Multi-Regional CGE Model of China Ying Fan Jie Wu Govinda Timilsina Yan Xia Public Disclosue Authoized Public Disclosue Authoized Public Disclosue Authoized Public Disclosue Authoized Development Reseach Goup Envionment and Enegy Team August 2017

2 Policy Reseach Woking Pape 8159 Abstact Many counties have intoduced policy measues, such as cabon picing, geenhouse gas offsetting mechanisms, enewable enegy standads, and enegy efficiency impovements, to achieve thei climate change mitigation tagets. Howeve, in many instances, these measues ovelap in ways that may dilute each policy s geenhouse gas eduction potential. This study examines how a enewable enegy standad in the powe secto would inteact with a national emission tading scheme that is intoduced to achieve a geenhouse gas mitigation taget. Using a static, multiegional computable geneal equilibium model of China to simulate policy measues, the study finds that the addition of a sepaate enewable enegy standad policy would incease the economic cost fo achieving a taget level of geenhouse gas mitigation. The study concludes that although enewable enegy standad policies pomote the use of enewable enegies, they ae an economic buden fom the pespective of educing geenhouse gas emissions if a cabon picing mechanism is in place. This pape is a poduct of the Envionment and Enegy Team, Development Reseach Goup. It is pat of a lage effot by the Wold Bank to povide open access to its eseach and make a contibution to development policy discussions aound the wold. Policy Reseach Woking Papes ae also posted on the Web at The authos may be contacted at gtimilsina@woldbank.og. The Policy Reseach Woking Pape Seies disseminates the findings of wok in pogess to encouage the exchange of ideas about development issues. An objective of the seies is to get the findings out quickly, even if the pesentations ae less than fully polished. The papes cay the names of the authos and should be cited accodingly. The findings, intepetations, and conclusions expessed in this pape ae entiely those of the authos. They do not necessaily epesent the views of the Intenational Bank fo Reconstuction and Development/Wold Bank and its affiliated oganizations, o those of the Executive Diectos of the Wold Bank o the govenments they epesent. Poduced by the Reseach Suppot Team

3 Undestanding the Inteactions between Emissions Tading Systems and Renewable Enegy Standads Using a Multi-Regional CGE Model of China 1 Ying Fan, Jie Wu, Govinda Timilsina, Yan Xia 2 Keywods: emissions tading scheme, enewable enegy standads, CGE model; climate change mitigation, China JEL Classifications: D58, Q54 1 The authos would like to thank Cuihong Yang, Jing Cao, Bekele Debele, Gao Batmanian, Todd M. Johnson, Dafei Huang and Mike Toman fo thei valuable comments and suggestions. The views and intepetations ae of authos and should not be attibuted to the Wold Bank Goup and the oganizations they ae affiliated with. We acknowledge Wold Bank s Knowledge fo Change (KCP) Tust Fund. 2 Ying Fan is a Pofesso at Beihang Univesity, Beijing; Jie Wu is an Assistant Pofesso at Shanghai Univesity of Finance and Economics; Govinda Timilsina is a Senio Economist at the Reseach Depatment of the Wold Bank, Washington, DC and Yan Xia is eseache at Chinese Academy of Sciences, Beijing.

4 1. Intoduction Diffeent policy instuments ae being intoduced in both developed and developing counties fo geenhouse gas (GHG) mitigation. Initially, GHG mitigation options such as enegy technology mandates (e.g., enewable enegy utilization equiements) and enegy efficiency standads wee the focus unde climate change mitigation initiatives. While vaious policy options including fiscal incentives and egulatoy mandates now ae common in both developed and developing counties to pomote lowe-cabon enegy use and efficient consumption of enegy, maket based mechanisms fo climate change mitigation, such as the clean development mechanism (CDM) and othe GHG offset mechanisms, also played a cucial ole in the deployment of these measues. Moe ecently, paticulaly afte the Pais Ageement, cabon picing has emeged as a key policy instument in seveal counties, including developing counties, to achieve thei nationally detemined commitment (NDC) ageed in the Pais Ageement. One issue often aised by policy makes is how to addess the economic buden to tax payes that could aise due to potential ovelapping of vaious policy options. This issue aises when multiple policies (e.g., cabon picing, enewable enegy mandates and enegy efficiency standads) ae implemented at the same time. This study aims to addess that question in the context of enegy and GHG mitigation policies in China. Like othe counties, China has poposed vaious policy options to meet its NDC, including a national emission tading system (ETS) and a mandate fo use of non-fossil 2

5 fuels to meet a given faction (20%) of the total pimay enegy supply. 3 While the national ETS is expected to be intoduced in 2017, enewable enegy standads (RES) policies ae aleady in place since The ETS has been aleady tested though seven pilot schemes at the povincial and city levels since A ich liteatue exists on the design issues of both ETS and RES sepaately (see e.g., Lesse and Su, 2008; Langniß et al., 2009; Coutue and Gagnon, 2010; Schallenbeg-Rodiguez and Haas, 2012; Hüble et al., 2014; Ouyang and Lin, 2014; He et al., 2015). Undestanding of inteactions between these measues also is citical fo the successful implementation of each policy. Applying a theoetical model to undestand the inteactions between emissions tading and othe policy instuments, Fankhause et al. (2010) ague that enewable enegy obligations within a capped aea might have undemined the cabon pice and inceased the mitigation costs. Using a patial equilibium model to exploe the inteactions between emission tading and thee enewable electicity suppot schemes, Böhinge and Behens (2015) suggest that policy makes should addess the implications of the ovelap between emission caps and diffeent RES policy instuments. Using a CGE model to analyze the inteactions between a enewable potfolio standad and a cap-and-tade policy in the United States, Mois (2009) finds that the enewable enegy potfolio inceased the welfae costs of cap-and-tade policy. Some studies blamed the enewable enegy mandate in the EU fo causing the plummeting of CO2 pemits pices unde the EU ETS between 2008 and 2013, because 3 China has set a taget of educing its emission intensities 60% to 65% below its 2005 level by 2030; it has also planned to supply 20% of total enegy consumption in 2030 fom non-fossil fuel souces. 3

6 the mandate cutailed the demand fo CO2 pemits (Van den Begh et al., 2013; Weigt et al., 2013). Examining the elationship between the EU-ETS pemit pice dop and enewable policies in the EU, Koch et al. (2014) finds that the gowth of wind and sola powe geneation unde the EU mandate obustly explains the EU-ETS pemit pice dynamics. Some liteatue (Nodhaus,2011; Böhinge et al., 2009; Tsao et al., 2011; Mois, 2009) also suggests that a sepaate enewable enegy mandate might advesely affect low cabon economic development that could be encouaged by boade cabon picing policies. This is because favoing a paticula technology (hee enewable enegy) would depess the cabon pice and associated investments on othe lowe cabon technologies. Fo example, Nodhaus (2011) agues that depessed cabon pices caused by the additional RES policy ae not likely to povide sufficient incentives fo investments in low-cabon technologies. Newell (2015) stesses technology policies, such as enewable potfolio standads, could aise athe than lowe the societal costs of climate mitigation; on the othe hand, cabon picing policies, such as a cabon tax with pat of the tax evenue ecycled to eseach and development of clean technologies, would be the most cost efficient option fo climate change mitigation. One could ague that adoption of clean and enewable enegy would not only help educe GHG emissions, they would have othe benefits, such eduction of local ai pollution. If the benefits fom local ai pollution ae quantified and accounted fo in the analysis, it might be possible that a policy that consides both emission tading and enewable potfolio standads simultaneously is moe economic as compaed to an 4

7 emission tading scheme alone. Howeve, quantification of ai pollution benefits is complex and accounting fo these intangible benefits in a social accounting matix, the main database fo a CGE model is futhe complicated. Against this backgound, ou pape uses a static, multi-egional CGE model to analyze the inteactions between ETS and RES policies in China by compaing thei economywide impacts both at national and povincial levels. We simulated thee cases: (i) a base case in the absence of the ETS and RES policies; (ii) an ETS case which consides a national emission tading scheme to educe national CO2 emissions by 10% fom the base case; and (iii) an ETS-cum-RES case whee a sepaate RES policy is intoduced on top of the ETS to achieve the same level of emission eduction taget. Ou simulation esults show that an additional RES policy would futhe educe GDP and incease the welfae loss associated with the ETS. The pape is oganized as follows. Section 2 descibes the CGE model used, and how ETS and RES policies ae implemented in this model. Section 3 pesents the data and policy scenaios. Section 4 pesents the economy-wide implications effects of ETS alone and in combination with RES. Finally, key conclusions ae dawn in Section Methodology This eseach is implemented in the CEEP Multi-Regional Enegy-Envionment- Economy Modelling System (CE 3 MS), which is based on a multi-egional static CGE model fo China (Wu et al., 2016). The CE 3 MS includes 30 egions in accodance with the administative stuctue of mainland China (excluding Tibet due to a lack of data). 5

8 Each egion has independent institutions as poduction sectos, ual and uban households, a epesentative entepise, and a local govenment; and, meanwhile, has elevant economic activities such as poduction, consumption, savings, and investment. Each egion has 17 epesentative poduction sectos: one agicultual, five enegy, seven non-enegy industial, and fou sevice sectos (Table 1). The CE 3 MS database deives fom the China 2007 egional social accounting matices (SAMs). Secto codes Agi Coal Coil Mine Fpap Peto Chem Nmm Metal Omf Ele Gas Cons Tans Wsale Esta Ots Table 1. Secto declaations and desciptions. Desciption Agicultue, foesty, animal husbandy and fishey Coal Cude oil and natual gas Mining Manufactue of foods, beveage, tobacco, textile, weaing, appael, leathe, wood, pape and publishing Coking, gas and pocessing of petoleum Chemical industy Manufactue of nonmetallic mineal poducts Manufactue and pocessing of metals and metal Poducts Othe manufactue Poduction and supply of electic, heat powe Poduction and supply of gas, wate Constuction Tanspot, stoage, post, infomation tansmission, compute sevices and softwae Wholesale and etail tades, hotels and cateing sevices Real estate, leasing, business sevices and financial intemediation Othe sevices Expot and impot povides the linkages between each egion and the est of the wold. Most impotantly, a multi-egional model diffes fom a national model in its inteegional linkages among all egions, including commodity tading, and the mobility of labo and capital. Unlike developed counties, the cental govenment plays a quite impotant ole in development decisions in China; theefoe, a cental govenment is descibed at the national level in this model. The basic modules of CE 3 MS ae poduction module, emissions tading module, commodity tading module, 6

9 institution module, labo mobility module, and maco closue, of which the key featues ae outlined below. 2.1 Poduction module The model assumes that all sectos ae chaacteized by constant etuns to scale and ae taded in pefectly competitive makets. Constant elasticity of substitution (CES) functions and nesting stuctues ae used to chaacteize the poduction technologies fo all sectos. In the poduction of non-electicity sectos, enegy is teated as a special esouce athe than an intemediate input and is combined with value-added. Thus, enegy can be substituted by othe enegy o intemediate input. 1 j, j, j, j, j, j, j, 1 j, j, QA QVAE QINTA PVAE PINTA QINTA 1 QVAE j, j, j, j, j, j, 1 j, (1) (2) PA QA PVAE QVAE PINTA QINTA (3) whee PA and QA ae the poduce pice and output of secto j in egion, PINTA and QINTA ae the pice and quantity of intemediate input, PVAE, j and QVAE ae the pice and quantity of value added and enegy input. and, j ae the efficiency paamete and shae paamete of the CES function, and is the substitution elasticity paamete. The combination of intemediate input is pesented by Leontief functions as Equation 4 and Equation 5: QINT ica QINTA (4) i, j, i, j, j, PINTA ica PQ (5) j, i, j, i, i whee QINT i, is the quantity of commodity i as intemediate input of secto j in egion, PQ i, is the pice of commodity i in egion, ica i, is the coefficient of 7

10 intemediate input. The combination of value added and enegy input is descibed in Equations vae, vae, vae vae vae j vae j j j, j, j, j, 1 j, j,, QVAE QVA QVE PVA PVE QVE vae j, j, j, vae j, 1 j, QVAj, vae 1 j, (6) (7) PVAE QVAE PVA QVA PVE QVE (8) 1 va, va, va va va j va j j j, j, j, j, 1 j, j,, QVA QLD QKD WL, (1 ) va j tval j, QKD j, va WK j, (1 tvak) 1 j, QLD j, va 1 j, (9) (10) PVA QVA (1 tval) WL QLD (1 tvak) WK QKD (11) whee PVA and QVA ae the pice and quantity of value added, PVE and QVE ae the pice and quantity of total enegy input, WL and QLD ae the pice and quantity of labo, WK and QKD ae the pice and quantity of capital input. tval and tvak ae value added tax ates of labo and capital. Equations pesent the stuctue of enegy input of secto j in egion. 1 ve, ve, ve ve ve j ve j j j, j, j, j, 1 j, j,, QVE QVEE QNELE PVEE PNELE QNELE ve j, j, j, ve j, 1 j, QVEE j, ve 1 j, (12) (13) PVE QVE PVEE QVEE PNELE QNELE (14) 1 nele, nele, nele nele nele j nele j j j, j, j, j, 1 j, j,, QNELE QVEC QVENC PVEC PVENC QVENC nele j, j, j, nele j, 1 j, QVEC j, nele 1 j, (15) (16) 8

11 PNELE QNELE PVEC QVEC PVENC QVENC (17) whee PVEE and QVEE ae the pice and quantity of electicity input, PNELE and QNELE ae the pice and quantity of non-electicity input. QVEC, PVEC, QVENC, PVENC ae the coal input and non-coal input and the coesponding pices, espectively. To implement the RES policy in CE 3 MS, electic powe geneation is epesented by eight geneation technologies: coal (Coa), natual gas (Ngs), petoleum (Pet), nuclea (Nuc), hydopowe (Hyd), wind (Win), sola (Sol), and othe enewable technologies (Oth). The stuctue of electicity poduction is given in Figue 1. In paticula, coal, natual gas, and petoleum ae aw mateial inputs of coal-, natual gas-, and petoleum-poweed geneation and thus ae consideed as intemediate inputs athe than value-added o enegy inputs fo coal-, natual gas-, and petoleum-poweed geneation. Electicity CES Natual gaspoweed Coalpoweed Petoleumpoweed Nuclea powe Hydo powe Wind powe Sola Othe CES CES Intemediate input Leontief Value-added enegy CES Intemediate input Leontief Value-added enegy CES Non-enegy input Petoleum Enegy CES Value added CES Non-enegy input Enegy CES Value added CES Electicity Gas Capital Labou Electicity Gas Capital Labou Figue 1. Stuctue of electicity poduction The total electicity output aggegation shows impefect substitution of electicity fom diffeent geneation technologies, which eflects the eality that vaious powe 9

12 geneation technologies coexist while having diffeing geneation costs. The substitution elasticity of diffeent geneation technologies is set to 2 in this study, with efeence to the MIT-EPPA model (Paltsev et al., 2005; Sue Wing, 2006). The RES policy is implemented by a poduction subsidy, and the subsidy cost is passed to final consumes via a tax on electicity consumption et 1 ' 1 ' 1 1 k, k, k, k, k, k QA PA PA Qele (18) Pele Qele PA QA (19) et k, k, k et whee k denotes diffeent powe geneation technologies, PA k, and QA k, ae the on-gid pice and output of electicity by technology k, Pele and Qele ae the composite pice and total output of electicity in egion. is the paamete of substitution elasticity of diffeent geneation technologies. The RES policy is implemented though a poduction subsidy fo enewable electic powe geneation in this model, which is descibed in Equation 22. With a subsidy, the on-gid pice of enewable powe will be lowe and leads to a substitution of enewable powe fo fossil-deived powe. In this analysis, we assume that the subsidy cost is passed though to consumes by an electicity consumption tax. 4 1 et et et k, k, et et et et et et k, k, k, k, k, (1 k, ) k, QA QINTA QVAE (20) 4 This tax is simila to a situation in which all of the additional cost of the enewable electicity is passed fowad to all electicity uses like in the case of a feed-in taiff. Diffeent appoaches would be possible to geneate govenment evenue to finance a enewable enegy subsidy. Landis and Timilsina (2015) incease VAT to subsidize wind powe in Bazil. Timilsina and Landis (2014) incease tax on fossil fuels to subsidize enewable enegy in Moocco. The geneal equilibium esults would be slightly diffeent acoss these appoaches. Since the electicity secto in China is a lage secto, a small tax on electicity to subsidize enewable enegy is not expected to distot the secto much. 10

13 PP QA PINTA QINTA PVAE QVAE (21) et et et et et k, k, k, k, k, k, PP PA k Win Sol Oth k, k,,,, 1 sub (22) k, (23) PA QA Pele Qele, k Win, Sol, Oth sub k, k, tax k, et PP is the poduce pice of electicity by technology k in egion, PINTA k, and QINTA et k, ae the pice and quantity of intemediate input by technology k. sub is the subsidy ate and tax is the added electicity consumption tax ate. 2.2 Emissions tading module We assume thee is a single, national ETS in which emittes fom diffeent egions all paticipate. We employed a gandfatheing appoach whee initial quotas ae distibuted fo fee. 5 Unde tading scheme, each tading secto detemines its actual emission eductions and tading volume unde the objective of minimizing the total cost by compaing its maginal abatement cost and cabon pice. This is descibed in Equations below: Min TC C ( COE COEE ) CP ( COEE COQ ) (24) t t t t 1 t t (25) s t COEE COQ.. t t t t whee TC t is the total cost which includes the abatement cost and tading cost of secto tj in egion. COEE t is the actual emissions unde the ETS policy, while COE t is the emissions in the benchmak. t COQ is the initial emission quota allocated to secto tj in egion, and CP 1 is the CO2 pice unde ETS. 5 Note that a povince s total emission quota is equal to the sum of sectoal quotas of that povince; we have not applied any othe ule to allocate the national quota to povincial quotas. 11

14 The decision of emissions eduction in tading sectos will diectly affect thei poduction as the total poduction costs in these sectos change. Theefoe, the equation of poduction costs in tading sectos will change fom Equation 3 to Equation 26 as below:,, =,, +,, +, (26) Figue 2. Famewok fo combination of ETS and RES policies in CE 3 MS Figue 2 shows the famewok fo combination of ETS and RES policies in CE 3 MS. Accoding to the existing empiical expeience fom seven pilot ETSs, eight industies (five enegy sectos and thee enegy-intensive sectos) ae consideed as emissions tading sectos in the nationwide cabon maket in China. Unde the ETS policy, each tading secto will decide on emissions eductions by compaing its maginal abatement costs with the cabon pice. Please see Figue 3 fo these maginal abatement cost cuves acoss the egion and sectos. 12

15 2.3 Commodity tading module Commodity tading in the model includes impot, expot, and tansfeing among egions. The output of poduction sectos in each egion not only supplies the local maket, but also othe egions in China and the est of wold, which ae pesented in Equations cet cet cet cet cet j, cet, cet j, j, j, j, j, j, j, j j, QA QDS 1 QE, 1 PDS PE QE cet j, j, j, cet j, 1 j, QDS j, cet 1 j, (27) (28) PA QA PDS QDS PE QE (29) PE j, pwe j, (1 te j) EXR (30) Equations descibe the allocation of commodity j between domestic maket QDS ) and expot ( QE ), which is decided by the commodity pice ( PDS ) in ( domestic maket and the expot pice ( PE ). pwe is the fee on boad pice of commodity j and te j is its expot tax ate. EXR is the exchange ate. Equations descibe how the supply of commodity j in egion in the domestic maket will be allocated among egion and othe egions in China. 1 ds ds ds ds ds j, ds j, j, ds j, j, j, j, 1 j, ) j,, j, QDS QRRE ( QRD 1 PRRE PRD QRD ds j, j, j, ds j, 1 j, QRRE j, ds 1 j, (31) (32) PDS QDS PRRE QRRE PRD QRD (33) QRR ie QRRE (34) s, js,, j, PRRE ie PQ (35) j, js,, j, S 13

16 QRD and QRRE ae the supply of commodity j in egion and the total supply to othe egions, espectively. PRD and PRRE ae coesponding pices. QRR s, is the supply of commodity j in egion to egion s, and s, ie is the Leontief coefficient. Composite commodities will be ultimately used fo intemediate input, govenmental and esidential final consumption, fixed assets investment and inventoy investment. Both of the total supply and demand of commodities ae epesented by nested CES function and the supply function follows constant elasticity of tansfomation (CET) function while the demand function follows the Amington assumption. 2.4 Household and institution module The households income is composed of labo payment, pat of capital compensation and tansfe payments fom local govenment. The utility function of households is assumed as a Cobb-Douglas function in this model, which can deive the households consumption fo diffeent commodities as the following equations: YH shifl WLR QLSR shifkh WKR QKSR tansfgtoh (36) h, h, h, h, PQ QH shh mpc (1 ti ) YH (37) h, h, h, h h, whee YH h, is the total income of household h in egion, QLSR and QKSR ae the supply of labo and capital in egion, WLR and WKR ae the aveage wage and capital etun in egion, QH h, is the households consumption of commodity j. h, tansfgtoh is the egional govenment tansfe payment in egion. shifl h,, shifkh h,, h, shh ae shae paametes, and mpc h, is the households popensity to 14

17 consumption. tih is the income tax ate. The egional entepise income includes capital compensation and local govenment tansfe payments. And the income excluding the entepise income tax will totally tansfom to savings. The egional govenment income consists of popotional 6 local tax evenues and the cental govenment tansfe payments. The expenditue includes tansfe to local households and commodity consumption which is also detemined by the Cobb- Douglas utility function. 3. Scenaios The following scenaios ae adopted to assess the impact of combining RES policy with an ETS policy (Table 2). A benchmak scenaio, S0, epesents a situation in the absence of ETS and RES policies to educe GHG emissions. An ETS scenaio efes to a nationwide tading of cabon emission pemits whee emittes with suplus pemits sell to those who needs them to meet thei emission eduction tagets. The total CO2 emissions allowed on the pat of the coveed sectos is 10% below the benchmak, a puely hypothetical taget fo scenaio compaison. 7 In the ETS-cum-RES scenaio, a sepaate RES mandate is intoduced on top of the ETS and both the ETS and RES policies togethe ae set to achieve the 10% emission eduction taget. 8 The RES policy 6 The popotions of tax allocation between egional govenments and the cental govenment ae fom the tax law. 7 Please note that any hypothetical taget would be fine hee to compae these two policies. We selected 10% because an ealie study (Cao et al. 2016) found that meeting China s INDC entails eduction of aveage emission fo the peiod by 9.8% fom the baseline, whee the baseline includes all existing policies (e.g., policies included in 13th 5 Yea Plan). 8 Note that we ae not compaing hee ETS and RES policy instuments to achieve the same emission eduction taget. Instead, we aim to compae the ETS system with and without the pesence of a sepaate RES policy. Unde both cases, the emission eduction taget is the same. 15

18 unde the ETS-cum-RES scenaio is implemented though a RES poduction subsidy ate of 50% 9, and the emissions tading taget is loweed such that the RES subsidy and the emissions pice achieve the desied 10% emissions eduction elative to benchmak. Consideing that hydopowe has the lowest geneation cost and high competitiveness compaed with othe enewable enegy technologies in China, it is not included in the RES policy in this study. The technologies included ae sola, biomass, and wind. Table 2. Scenaios unde diffeent policies. Scenaio RES subsidy ate CO 2 intensity decease S0: Benchmak scenaio without any policies 0 0 Scenaio ETS: ETS policy only 0 10% Scenaio ETS-cum-RES: ETS policy and RES policy 50% 10% Fo simplicity of pesenting the esults, the 30 egions ae classified into thee aeas (easten, cental, and westen) based on the egional divisions used by the National Bueau of Statistics of China. Table 3 shows the classification of egions. Categoy Easten egions Cental egions Westen egions Table 3. Classification of egions. Regions Beijing (BJ), Tianjin (TJ), Hebei (HB), Liaoning (LN), Shanghai (SH), Jiangsu (JS), Zhejiang (ZJ), Fujian (FJ), Shandong (SD), Guangdong (GD), Hainan (HN) Shanxi (SX), Jilin (JL), Heilongjiang (HL), Anhui (AH), Jiangxi (JX), Henan (HeN), Hubei (HuB), Hunan (HuN) Inne Mongolia (IM), Guangxi (GX), Chongqing (CQ), Sichuan (SC), Guizhou (GZ), Yunnan (YN), Shaanxi (SaX), Gansu (GS), Qinghai (QH), Ningxia (NX), Xinjiang (XJ) 4. Results Because this is a static long-tem analysis, the esults shown in this section do not 9 The subsidy ate is detemined based on data on levelized costs fo powe geneation fom vaious souces and cuent electicity geneation mix. A 50% pice subsidy means eduction of the long-un maginal cost of the enewable enegy aggegate (excluding hydo), which is the pice of electicity fom those souces in the model, by 50%. 16

19 explicitly petain to any specific yea. We can think of them implicitly as eflecting an equilibium situation afte fully deploying the policy instuments being studied. Note that the esults measue changes in key vaiables (GDP, sectoal outputs, intenational tade) due to ETS and ETS cum RES as compaed to the situation in the absence of ETS and RES. They do not epesent any paticula yea although we used SAM of Maginal abatement costs by sectos and egions The stating point fo any emission tading study is to undestand the maginal costs of CO2 abatement of vaious sectos in vaious egions. This is the basis of tade between the sectos and also among the egions. A secto with maginal abatement cost highe than maket cleaing CO2 pemit pice buys CO2 pemits wheeas a secto with maginal abatement cost lowe than maket cleaing CO2 pemit pice sells CO2 pemits. Figue 3 shows the maginal abatement cost (MAC) cuves of enegy and enegy-intensive sectos in the base case (i.e., befoe the emission tading). Fo a given secto, the maginal abatement cost ae significantly diffeent acoss the egions epesenting how expensive it would be to educe CO2 emissions fom that secto in a egion. In most egions, the electicity secto has lowe maginal abatement cost as compaed to othe sectos due to moe flexibility to poduce electicity fom diffeent souces. Fo example, due to its utilization of an abundant endowment of fossil enegy esouces, Inne Mongolia offes the highest CO2 emission mitigation potential fom electicity geneation, and coal and oil mining, fo a given abatement cost. Moe geneally, westen esouce abundant egions, such as Shanxi, Inne Mongolia, and 17

20 Ningxia, offe lowe abatement cost compaed to easten industialized egions. Coal Coil Abatement cost (Yuan/Ton CO 2 ) Abatement cost (Yuan/Ton CO 2 ) % 10% 20% 30% 40% 50% 60% 70% Emissions eduction atio 0 0% 10% 20% 30% 40% 50% Emissions eduction atio 400 Peto 400 Chem Abatement cost (Yuan/Ton CO 2 ) Abatement cost (Yuan/Ton CO 2 ) % 10% 20% 30% 40% 50% Emissions eduction atio 0 0% 10% 20% 30% 40% 50% Emissions eduction atio Nmm Metal Abatement cost (Yuan/Ton CO 2 ) Abatement cost (Yuan/Ton CO 2 ) % 5% 10% 15% 20% 25% 30% 35% 40% Emissions eduction atio 0 0% 10% 20% 30% 40% 50% Emissions eduction atio 18

21 Ele Gas Abatement cost (Yuan/Ton CO 2 ) Abatement cost (Yuan/Ton CO 2 ) % 10% 20% 30% 40% 50% 60% 70% Emissions eduction atio 0 0% 10% 20% 30% 40% 50% 60% 70% 80% Emissions eduction atio Beijing Tianjin Hebei Shanxi InneMongolia Liaoning Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan Hubei Hunan Guangdong Guangxi Hainan Chongqing Sichuan Guizhou Yunnan Shaanxi Gansu Qinghai Ningxia Xinjiang Figue 3. Maginal abatement cost cuves of enegy and enegy-intensive sectos in the absence of ETS 4.2 Cabon maket unde the policy scenaios Figue 4 pesents tade of CO2 mitigation between the sectos and acoss the egions unde the ETS (S1) and ETS-cum-RES (S2) scenaios. Unde the ETS scenaio, the total tading volume of CO2 mitigation was million tons to achieve a taget of educing 10% CO2 emissions fom the base case (i.e., in the absence of these policies). The equilibium maket pice of CO2 pice yuan/ton (o US$7.1 with exchange ate of 0.15 US$ fo one yuan). If the sepaate enewable enegy mandate fo electicity geneation is imposed on top of the ETS fo the same taget of CO2 mitigation (i.e., 10% below the base case), with 50% subsidies fo sola, wind, and biomass, the volume of emission tade slightly deceases, by 1.5%, to million tons. As a esult, the equilibium CO2 pice also deceases, by 3.5%, to yuan/ton. The eduction in tade volume and CO2 pice is caused by the eduction in electicity sectos demands fo emission allowances due to 19

22 the enewable enegy mandate. Figue 4. Inte-egional emissions tading unde ETS and ETS-cum-RES cases Although the impacts of enewable enegy mandate on CO2 emissions tade is small at the national level, it is significant to some povinces. Fo example, the inteegional tansfe of funds fom cental egion to westen egion unde the ETS deceases by 29% fom 123 million yuan to 87 million yuan as the enewable enegy mandate causes the size of ETS maket to shink. This is a clea disadvantage to the Westen 20

23 pooe egion of adding a sepaate enewable policy on top of the ETS. The inteegional tansfe of funds fom easten egion to cental egion, howeve does not change much; it gets educed by less than 1% fom 1,333 million yuan to 1,322 million yuan. Although the electicity sectos in most egions choose to sell fewe allowances unde the ETS-cum-RES case, the electicity sectos in Hebei, Jilin, Heilongjiang, Jiangxi, Hubei, and Guizhou will get highe income by selling moe allowances compaed to the ETS case. This is because eduction of CO2 in these egions is moe economic despite the shinkage of the oveall cabon maket due to highe flexibility of CO2 eduction fom thei powe sectos. In othe wods, although the RES policy lowes the CO2 pice and total tading volume, the maginal abatement costs of electicity sectos in these egions ae still less than the CO2 pice. 4.3 Economic impacts Table 4 pesents the impacts on key economic vaiables of the ETS and ETS-cum- RES policies. Model simulations eveal that ETS would cause less than 0.1% (20 billion Yuan) eduction in Chinese GDP. Howeve, due to the vey lage size of Chinese national GDP, the pecentage eduction in GDP appeas to be vey small. Due to the expansion of clean infastuctue caused by the ETS policy, thee would be a net incease in total investment by 5 billion Yuan. 21

24 Table 4. Economic impacts (changes fom the base case) ETS ETS-cum-RES GDP (million yuan) (-0.073%) (-0.101%) Welfae (million yuan) Investment (million yuan) 5037 (0.042%) 4221 (0.035%) -Easten egions (million yuan) -183 (-0.003%) -334 (-0.005%) -Cental egions (million yuan) 4301 (0.145%) 3833 (0.129%) -Westen egions (million yuan) 918 (0.038%) 723 (0.030%) 3% ETS ETS-cum-RES 2% GDP change 1% 0% -1% -2% -3% BJ TJ HB SX IM LN JL HLJ SH JS ZJ AH FJ JX SD HN HB HN GD GX HAN CQ SC GZ YN SAX GS QH NX XJ Figue 5a. GDP change in egions unde ETS and ETS-cum-RES cases ETS ETS-cum-RES Welfae change (Million Yuan) BJ TJ HB SX IM LN JL HLJ SH JS ZJ AH FJ JX SD HN HB HN GD GX HAN CQ SC GZ YN SAX GS QH NX XJ Figue 5b. Welfae change in egions unde ETS and ETS-cum-RES cases In compaing the economic impacts between the ETS and ETS-cum-RES policy, we find as expected that the enewable enegy mandate plus ETS policy would lead to 22

25 a lage GDP loss than the ETS alone (though by only about 8 billion, a vey small pecentage diffeence in GDP loss). This is because the RES mandate would have diveted some of the cheape eduction that can be achieved though the emission tading to elatively expensive eduction mandated by the RES policy. Note that enewable enegy souces ae suppoted though subsidy. Necessay budget to finance the enewable electicity subsidy unde the ETS-cum-RES policy is collected though an additional tax on electicity consumption. The inceased electicity pice would educe the eal income of households and thus diectly contibute to educed household welfae. It also would incease pices of sectoal outputs, especially of electicity intensive industies and theeby causing eductions in domestic consumption as well as expots of those goods and ultimately causing the GDP to decease. Fo example, household electicity consumption deceases by 0.58% fom the base case due to the additional RES policy on top of the ETS scheme to meet 10% CO2 emission eduction taget in China. 4.4 Impacts on economic stuctue Industial stuctue Tables 5 show the changes in sectoal outputs fom the base case unde ETS and ETS-cum-RES scenaios. Fo example, the output of coal industy, the main souce of CO2 emission in China, would dop by 9% unde ETS scenaio fom the base case. Similaly, sectoal outputs of coal fied electicity geneation industy would decease by 3%. When the RES policy is added in the pesence of the ETS policy, the enegy and enegy-intensive industies would expeience futhe output losses. This is because the 23

26 RES imposes a substitution of fossil fuel based electicity geneation with enewable electicity and would cause eduction of fossil fuel demand fo powe geneation and theeby fossil fuel supply. Moeove, it also inceases electicity pices and causes outputs of electicity intensive industies to decease futhe. Table 5 Sectoal output change in egions unde ETS and ETS-cum-RES cases (%). Agi Coal Coil Mine Fpap Peto S1 S2 S1 S2 S1 S2 S1 S2 S1 S2 S1 S2 Total BJ TJ HB SX IM LN JL HLJ SH JS ZJ AH FJ JX SD HN HB HN GD GX HAN CQ SC GZ YN SAX GS QH NX XJ

27 Table 5 (continue). Sectoal output change in egions unde ETS and ETS-cum-RES cases (%). Chem Nmm Metal Omf Ele Gas S1 S2 S1 S2 S1 S2 S1 S2 S1 S2 S1 S2 Total BJ TJ HB SX IM LN JL HLJ SH JS ZJ AH FJ JX SD HN HB HN GD GX HAN CQ SC GZ YN SAX GS QH NX XJ

28 Table 5 (continue). Sectoal output change in egions unde ETS and ETS-cum-RES cases (%). Cons Tans Wsale Esta Ots S1 S2 S1 S2 S1 S2 S1 S2 S1 S2 Total BJ TJ HB SX IM LN JL HLJ SH JS ZJ AH FJ JX SD HN HB HN GD GX HAN CQ SC GZ YN SAX GS QH NX XJ Note: 1. S1 and S2 denote ETS and ETS-cum-RES cases, espectively. 2. The value 0 in the table indicates zeo output of that secto in the base case. The esults show that the outputs in tanspot, wholesale, eal estate, and othe sevices sectos unde ETS-cum-RES case ae moe than the ETS case. This is because the RES policy would ceate moe demand fo goods and sevices to be poduced fom 26

29 these sectos to suppot expansion of enewable enegy industies in China Powe geneation mix Table 6 pesents the powe geneation mix unde the vaious scenaios and pecentage change in outputs of each powe geneation technology. Note that the dops in electicity outputs of fom fossil fuel based technologies ae highe unde the ETScum-RES scenaio ae highe as compaed to that in ETS scenaio. This is because the RES policy causes substitution of fossil fuel based powe geneation with the enewable enegy based electicity. Table 6. Geneation mix (%) unde diffeent scenaios along with pecentage change in electicity outputs of diffeent geneation technologies S0 ETS ETS-cum-RES Popotion Change Popotion Change Popotion Coa Ngs Pet Nuc Hyd Win Sol Oth Inteestingly, electicity geneation fom enewable as well as fossil souces is deceasing unde the ETS scenaio. The eason is that the nesting stuctue used to model electicity geneation technologies (Figue 1) does not allow diffeent substitution possibility between the aggegate electicity geneation fom fossil fuels and aggegate electicity geneation fom enewable enegy souces. Since the shae of non-fossil shae of total electicity geneation is elatively small (< 10%) in China, this 27

30 igid nesting stuctue adopted in the model used fo this study would not impact the esult much fo a small cabon pice. Howeve, the model stuctue must be changed to allow the substitution effect to wok if cabon picing level is high Impacts on esidential consumption of goods and sevices Table 7 pesents the impacts of ETS and ETS-cum-RES scenaios on household consumption of goods and sevices. Fom the table, thee obsevations can be made. Fist, unde the both schemes, household consumption of fossil fuels and enegy intensive poducts (non-metallic mineals, metals, chemicals) would dop by highe popotions than othe goods and sevices. Second, the dops in household consumption of goods and sevices would be highe unde ETS-cum-RES scenaio than that of ETS scenaio. The diffeence in dops of electicity consumption between the ETS and ETScum-RES scenaio is noticeable as the adoption of RES policy inceases the pice fo electicity consumption, and thus leads to significant decease of electicity consumption, compaing with the ETS case. Thid, the dops of household consumption of good and sevices ae much highe in some povinces (e.g., Hebei, Liaoning, Heilongjiang, Guizhou, Hainan, Xinjiang) than in othe povinces. This is because households in these povinces consume popotionally highe amounts of enegy and enegy intensive goods and sevices. 28

31 Table 7. Change in household consumption fom the base case (%). Agicultue Coal Cude oil Mining Food, pape Petoleum S1 S2 S1 S2 S1 S2 S1 S2 S1 S2 S1 S2 Total BJ TJ HB SX IM LN JL HLJ SH JS ZJ AH FJ JX SD HN HB HN GD GX HAN CQ SC GZ YN SAX GS QH NX XJ Note: 1. S1 and S2 denote ETS and ETS-cum-RES cases, espectively. 2. The value 0 in the table indicates thee is no household consumption of commodities in the base case. 29

32 Table 7b. Household consumption change in egions unde ETS and ETS-cum-RES cases (%). Chemicals Non metals Metal Othe MF Electicity Gas S1 S2 S1 S2 S1 S2 S1 S2 S1 S2 S1 S2 Total BJ TJ HB SX IM LN JL HLJ SH JS ZJ AH FJ JX SD HN HB HN GD GX HAN CQ SC GZ YN SAX GS QH NX XJ

33 Table 7c. Household consumption change in egions unde ETS and ETS-cum-RES cases (%). Constuction Tanspot Wholesale Real Estate Othes S1 S2 S1 S2 S1 S2 S1 S2 S1 S2 Total BJ TJ HB SX IM LN JL HLJ SH JS ZJ AH FJ JX SD HN HB HN GD GX HAN CQ SC GZ YN SAX GS QH NX XJ Expot and impot Figue 6 pesents the impacts on expot and impot of total goods and sevices unde ETS and ETS-cum-RES scenaios. Both ETS and ETS-cum-RES scenaios would cause expots of fossil fuels and enegy intensive goods to decease and expots 31