A Generalized Equilibrium Approach to Balance the Residual Abatements Resulting from COP-21 Agreement 1 Frédéric Babonneau, Alain Haurie and Marc Vielle IAEE - Bergen June 19-22, 2016 1 Supported by the QNRF under Grant Agreement no 6-1035-5–126 1 / 21
Contents Context and Objectives 1 A Dynamic meta-game model for climate negotiations 2 INDCs evaluation 3 Fair agreements for additional efforts 4 Conclusion 5 2 / 21
Context and Objectives Context and Objectives 1 A Dynamic meta-game model for climate negotiations 2 INDCs evaluation 3 Fair agreements for additional efforts 4 Conclusion 5 3 / 21
Context and Objectives Adressed questions What do INDCs mean? And what might be the economic impacts of INDC 1 implementation? How an international carbon market might affect climate agreements? 2 How to share additional efforts on 2015-2050 to reach the 2 o C target in 2100? 3 How to design a fair agreement among groups of countries? How each country will use its allocations on the horizon 2015-2050? What will 4 be the associated costs for each country? 4 / 21
A Dynamic meta-game model for climate negotiations Context and Objectives 1 A Dynamic meta-game model for climate negotiations 2 INDCs evaluation 3 Fair agreements for additional efforts 4 Conclusion 5 5 / 21
A Dynamic meta-game model for climate negotiations Meta-games for climate negotiations Global emissions Budget Coopera8ve US EU China Non Coopera8ve Interna8onal emissions trading scheme 6 / 21
A Dynamic meta-game model for climate negotiations Meta-games for climate negotiations Global emissions Budget The payoff (welfare loss) of player j at equilibrium satisfies : Coopera8ve T − 1 US EU China j (Ω t )) − p t (Ω t )( ω t j (Ω t ))) β t j ( π t j ( e t j − e t � min , ω j Non Coopera8ve t = 0 subject to actions chosen by the other players and under the budget Interna8onal emissions trading scheme sharing constraint T − 1 ω t � j ≤ θ j Bud . t = 0 6 / 21
A Dynamic meta-game model for climate negotiations Meta-games for climate negotiations The payoff (welfare loss) of player j at equilibrium satisfies : T − 1 β t j ( π t j ( e t j (Ω t )) − p t (Ω t )( ω t j − e t j (Ω t ))) � min , ω j t = 0 Global emissions Budget subject to actions chosen by the other players and under the budget sharing constraint Coopera8ve T − 1 ω t � j ≤ θ j Bud . US EU China t = 0 Non Coopera8ve Applying standard Kuhn-Tucker multiplier method, with multipliers ν j , we obtain the following first order necessary conditions for a Nash Interna8onal emissions trading scheme equilibrium: j ( p t (Ω t ) + p t ′ (Ω t )( ω t j (Ω t ))) ν j = β t j − e t ∀ t ∀ j T − 1 ω t � 0 = ν j ( θ j Bud − j ) t = 0 T − 1 ω t � 0 ≤ θ j Bud − j t = 0 6 / 21
A Dynamic meta-game model for climate negotiations Meta-games for climate negotiations The payoff (welfare loss) of player j at equilibrium satisfies : T − 1 j (Ω t )) − p t (Ω t )( ω t j (Ω t ))) β t j ( π t j ( e t j − e t � min , ω j t = 0 Global emissions Budget subject to actions chosen by the other players and under the budget sharing constraint Coopera8ve T − 1 ω t � j ≤ θ j Bud . US EU China t = 0 Non Coopera8ve Applying standard Kuhn-Tucker multiplier method, with multipliers ν j , we obtain the following first order necessary conditions for a Nash Interna8onal emissions trading scheme equilibrium: j ( p t (Ω t ) + p t ′ (Ω t )( ω t j (Ω t ))) ν j = β t j − e t ∀ t ∀ j T − 1 � ω t 0 = ν j ( θ j Bud − j ) t = 0 T − 1 ω t � 0 ≤ θ j Bud − j t = 0 Abatement cost functions π are estimated through statistical emulation on a large set of GEMINI-E3 simulations 6 / 21
A Dynamic meta-game model for climate negotiations A noncooperative meta-game approach Input Global budget Bud and allocations among countries (i.e., θ j ) Model Minimize the economic impacts for each country by deciding: How to use the budget on the horizon 1 Permit sales and buyings on the trading market 2 Output Emissions, Permit exchanges, Permit prices, Percentage of welfare losses, ... ⇒ By testing different allocations, one can find a fair burden sharing. For example if we adopt a Rawlsian approach to distributive justice, the optimal game design problem consists in finding the θ j ’s in such a way that one minimizes the largest welfare loss among the countries. 7 / 21
A Dynamic meta-game model for climate negotiations Estimation of the abatement cost functions We use the CGE model GEMINI-E3 as a the provider of data for the estimation of the abatement cost functions for each group of countries Estimations are based on statistical emulations of a sample of 200 GEMINI-E3 numerical simulations (4 periods × 11 = nb estimations) The abatement costs are polynomial functions of degree 4 in the country abatement level 2 q j ( t ) 2 + α j 3 ( t ) q j ( t ) 3 + α j AC j ( t ) = α j 1 ( t ) q j ( t ) + α j 4 ( t ) q j ( t ) 4 . (1) 2000 USA 1800 EU UMB CHI 1600 IND RUS OPE 1400 ROW ASI 1200 LAT LDC MAC 1000 800 600 400 200 0 0 5 10 15 20 25 30 35 40 45 50 55 Abatement (%) 8 / 21
INDCs evaluation Context and Objectives 1 A Dynamic meta-game model for climate negotiations 2 INDCs evaluation 3 Fair agreements for additional efforts 4 Conclusion 5 9 / 21
INDCs evaluation INDC analysis and consolidation Difficulties to convert INDCs in consistent emissions abatements in 2030: Objectives are related to different reference emissions (Historical emissions, BAU emissions, Intensity target, etc) Conditional and unconditional targets Objective year: from 2025 to 2035 Missing information and unsubmitted INDCs ⇒ We use conventional target related to GEMINI-E3 BAU scenario. 10 / 21
INDCs evaluation INDC targets in Mt CO2-eq in 2030 Unconditional Conditional Reduction compared to GEMINI-E3 BAU USA 4’045 3’796 -47% EUR 3’230 3’230 -25% UMB 2’510 2’499 -14% CHI 17’748 15’860 0% IND 6’681 6’482 0% RUS 2’649 2’473 -1% OPE 3’834 3’456 -2% ROW 3’688 3’465 -13% ASI 5’491 4’975 0% LAT 4’245 4’059 0% LDC 4’713 4’423 0% World 58’833 54’718 11 / 21
INDCs evaluation INDCs impacts on welfare losses on [2015, 2030] Without International carbon market With International carbon market Welfare loss CO 2 prices in $ /t Welfare loss CO 2 prices in $ /t in % of disc. HC 2020 2030 in % of disc. HC 2020 2030 USA 0.37 53 71 0.08 3.6 5 EUR 0.02 27 36 -0.01 3.6 5 UMB 0.03 7 10 0.03 3.6 5 CHI -0.09 - - -0.11 3.6 5 IND 0.01 - - -0.02 3.6 5 RUS -0.03 - - -0.07 3.6 5 OPE 0.10 - - 0.06 3.6 5 ROW 0.03 2 3 0.03 3.6 5 ASI -0.02 - - -0.03 3.6 5 LAT -0.01 - - -0.02 3.6 5 LDC -0.08 - - -0.11 3.6 5 World 0.08 0.04 International carbon market has a positive impact on global and all individual costs. Low welfare losses clearly reflect a lack of ambition of INDCs. 12 / 21
INDCs evaluation Decomposition of welfare losses LDC LDC Abatement Costs Abatement Costs LAT LAT Quotas buying GTT ASI ASI GTT ROW ROW OPE OPE RUS RUS IND IND CHI CHI UMB UMB EUR EUR USA USA -0.2 -0.1 0 0.1 0.2 0.3 0.4 -0.2 -0.1 0 0.1 0.2 0.3 0.4 13 / 21
Fair agreements for additional efforts Context and Objectives 1 A Dynamic meta-game model for climate negotiations 2 INDCs evaluation 3 Fair agreements for additional efforts 4 Conclusion 5 14 / 21
Fair agreements for additional efforts Emissions budget on 2015-2050 15 / 21
Fair agreements for additional efforts Global welfare loss on 2015-2050 16 / 21
Fair agreements for additional efforts Different coalitions agreements (2 o C target) 6.0% Global welfare loss CoaliFon welfare loss 5.0% 4.0% 3.0% 2.0% 1.0% 0.0% G20-USA G20-IND G20 G20+LAT G20+OPE G20+ASI G20+ROW ALL-OPE ALL 17 / 21
Fair agreements for additional efforts Examples of fair agreement (2 o C target) on [2015, 2050] Equalized-WL agreement Adjusted-WL agreement Region Emissions budget in Welfare loss Emissions budget in Welfare loss Mt CO 2 -eq % of BAU emi. in % of DHC Mt CO 2 -eq % of BAU emi. in % of DHC USA 166852 64 0.8 153046 59 0.9 EUR 80240 52 0.8 69620 45 0.9 UMB 63602 63 0.8 56640 56 0.9 CHI 264910 52 0.8 273760 54 0.5 IND 73986 55 0.8 76346 57 0.5 RUS 57230 67 0.8 58882 69 0.5 OPE 100890 76 0.8 103250 78 0.5 ROW 101480 65 0.8 105020 67 0.5 ASI 105020 65 0.8 109150 67 0.5 LAT 86730 72 0.8 90270 74 0.5 LDC 79060 79 0.8 84016 84 0.0 World 1,180,000 62 0.8 1,180,000 62 0.8 18 / 21
Fair agreements for additional efforts WL decomposition for Equalized-WL and Adjusted-WL agreements Abatement Costs Abatement Costs LDC LDC LAT Quotas buying LAT Quotas buying ASI ASI GTT GTT ROW ROW OPE OPE RUS RUS IND IND CHI CHI UMB UMB EUR EUR USA USA -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 3 19 / 21
Conclusion Context and Objectives 1 A Dynamic meta-game model for climate negotiations 2 INDCs evaluation 3 Fair agreements for additional efforts 4 Conclusion 5 20 / 21
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