Impact of Emission Trading Market Linkage on Carbon Price: Findings of the GTAP-E Model Mengfei Jiang, Xi Liang University of Edinburgh Business School 19 June 2017, the 40 th IAEE Singapore Conference
Carbon Pricing 1998 - Kyoto Protocol International Emissions Trading (IET) The European Union ETS Clean Development Mechanism (CDM) Joint Implementation (JI) 2009 Copenhagen Summit Negotiating position of the European Union European Union revised its carbon allowances system for the post-kyoto period 2015 - Paris Agreement Internationally Transferred Mitigation Outcomes (ITMOs) Nationally Determined Contributions (NDCs) Potential global carbon market 2
Existing and Emerging ETS Source: the World Bank, 2014 Timeline of ETS developing in China Pilot ETS in 7 regions National ETS Link with other ETS 2011 2017 Near future (Anger N., 2008; Flachsland et al, 2011; Guoyi et al., 2012; Qi et al., 2013; Gavard et al., 2013; Kachi et al., 2015; Wang et al., 2015; Tao et al., 2015;) 3
Efficiency Gain from Linkage $/t PlinkA PautA MAC B Reduction Target A Qaut X Y Qlink Reduction Target B MAC A $/t PautB PlinkB The efficiency gain from linkage in a compliance period is equal to the total difference between the sum of the mitigation costs of the two ETS before and after linkage, which is the total area of (X + Y). Figure: Simplified Illustration of Distribution of Efficiency Gains when Linking Two ETSs (assuming carbon prices of two system converge after linkage) 4
GTAP-E multi-sector, multi-regional CGE model Taxes Goods and Services Taxes Goods and Services 5
GTAP-E: fundamental features Representative Agents Behaviors Household behaviour: maximize utilities max ci U(c 1,, c n ), subject to m = N i=1 p i (c i + s i ) Industry behaviour: maximize profits N max xij,v π ij j = p j y j i=1 Equilibrium Conditions Market clearance Zero profit Income balance Elasticity of Substitution Trade-offs F pi x ij f=1 w f v fj, Subject to y j = j (X 1j,,, X Nj ; v 1j,, v Fj ) C N F N i = j=1 βij p j y j +α i f=1 w f V f j=1 pj s j + p i s i p i y i f F = j π = pj Aj m = N j=1 F f=1 p j y j γ fj V f w N f i=1 w f V f m (p i /β ij ) β ij F f=1 (w f /γ fj ) γ fj Variables c m p s v w x y U π A α β γ Denotation Consumption of commodity Households income Commodity price Households saving Households primary factors Households wages for factors Intermediate inputs Outputs of industry Households utility Enterprises profit Constraints of production technology Scaling parameter Share of each good in expenditure on consumption Share of each intermediate inputs in the cost of production Share of each factor inputs in the cost of production 6
Model Calibration Benchmark database (GTAP 8 Database Year 2007); Define sets, parameters, variables and equations; Assign values to elasticity parameters and initial values to variables from the database Solve model Re-solve model Simulation Shock by changing exogenous variables or parameters: Substitution coefficients, etc. Find new values for the endogenous variables: Emission price Emission reduction GDP, etc. Results 7
Aggregated Regions & Sectors REGIONS USA EU27 EEFSU JPN ROA1 EEX CHN IND ROW DESCRIPTION United States European Union Eastern Europe and Former Soviet Union Japan Other Annex 1 Countries Net Energy Exporters China India Rest of the World TYPE SECTORS DESCRIPTION NON- ENERGY Agriculture Aggregation of all agriculture products, plus managed forest land and logging activities; Transportation Energy-Intensive Industry Pipeline transport, and water, air and land transport; Iron and steel, non-metallic minerals products, non-ferrous metals products, chemical rubber products and fabricated metal products; Other Industries All other industries not included elsewhere, e.g. food, tobacco, construction, mining, equipment and others; Other Services All other services not included elsewhere, e.g. communication, finance, public services, dwellings and others; ENERGY Oil Extraction of petroleum; Coal Mining and agglomeration of hard coal, lignite and peat; Nature Gas Extraction of natural gas; Petroleum Refined oil and petro chemistry products; Electricity Electricity and heat generation, transmission and distribution. Electric generation technologies include: Coal, Gas, Refined Oil, Hydro, Nuclear, Wind, Solar, Biomass 8
Scenarios: policy constraints ETS in the model Scenario 1 2 3 CHN EU27 JPN RoA1 USA EEFSU EEx IND RoW Multilateral Trading Description ETS adopted separately in these countries Chinese ETS is NOT covered in global carbon market Chinese ETS is covered in global carbon market 9
Results: emission price (USD/ton CO 2 ) Scenario 1 Scenario 2 Scenario 3 CHN 29.97 0 40.08 EU27 40.37 27.62 40.08 JPN 121.91 27.62 40.08 RoA1 126.19 27.62 40.08 USA 24.1 27.62 40.08 EEFSU 0 0 0 EEx 0 0 0 IND 0 0 0 ROW 0 0 0 10
Results: emission reduction (%) Scenario 1 Scenario 2 Scenario 3 CHN -40* 0.32-40* EU27-17* -17* -17* JPN -30* -30* -30* RoA1-40* -40* -40* USA -17* -17* -17* EEFSU 1.91 0-28.79 EEx 1.47 0.96 1.36 IND -0.15-0.13-0.16 RoW 1.63 1.07 1.5 * Fixed emission reduction targets 11
Results: GDP changes (%) 0.2 0-0.2-0.4 CHN EU27 JPN RoA1 USA EEFSU EEx IND RoW 0.11 0.11 0.08 0.03 0.02 0.03-0.03 Scenario -0.06 1 Scenario -0.04 2 Scenario -0.04-0.06 3-0.14-0.14-0.15-0.17-0.22-0.22-0.21-0.22-0.26-0.32-0.46-0.6-0.8-1 -1.2-0.88-0.87-1.1-0.8 12
Findings highlight A strong and robust carbon price could give investors a right price signal on the value of carbon emission, thus incentive the carbon market activity and improve the liquidity; Allowing multilateral trading of emission among shifts the burden of the reduction away from the relatively carbon-efficient economies (EU, Japan and the rest of Annex 1 countries) towards coal in the USA; Additional emissions will be emitted in those countries with no binding constraint relative to the emission reduction in countries with binding constraints A linkage between Chinese carbon market and the international carbon market leads to a significant lower decrease in the GDP in China, resulting as 0.04%. 13
Contributions Contribute to methodology Assessing applicability and limitation of CGE model and their use in economy-wide climate change policy analysis. (Wing, 2004; Biabiker et al., 2004; Qi et al., 2013) Contribute to policy-making Understanding the impacts of carbon market linkage will benefit the development and improvement of climate change policy, maximise efficiency of carbon trading market, and effectively promote carbon abatement with clear carbon price signal. Contribute to theory With a modified and extended CGE model, this research will verify and replenish the multiple policy interaction and carbon market linkage analysis. This work also fill the literature gap of climate change policy analysis in China. (Cheng and Zhang, 2011; Zhang, etal., 2014; Duan et al., 2014; Liu and Wang, 2014; Fan and Wang, 2014; Wu et al., 2014; Zhou, et al., 2013; Qi, et al., 2014) 14
Thank you very much! 15