1. Introduction The Kyoto protocol, in which the ratified Annex B countries abate CO 2 emissions, ends in Accordingly, negotiations for the inte

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1 Post-Kyoto Climate Regimes: Per Capita Cumulative CO 2 Emissions versus Contraction and Convergence of CO 2 Emissions Preliminary Draft Version Hanae Tamechika * February 2012 Abstract The Copenhagen Accord sets the target for the post-kyoto international climate framework as limiting the global temperature increase to less than 2 degrees Celsius above the pre-industrial levels. In this paper, we construct a dynamic computable general equilibrium model and analyze the economic effects of two methods for allocating emission quotas across all countries under the post-kyoto international climate framework. Two types of CO 2 emission quotas are considered: historical responsibility (HR), which allocates emission quotas such that the per capita cumulative CO 2 emissions for the period are equalized across all countries and contraction and convergence of CO 2 emissions (C&C), which allocates emission quotas such that the per capita CO 2 emissions in 2050 are equalized across all countries. Meinshausen et al (2009) states that limiting the cumulative CO 2 emissions over the period to 1,440 Gt CO 2 yields a 50% probability of warming exceeding 2 degrees Celsius, relative to the pre-industrial levels. This paper assumes that the global cumulative CO 2 emissions from 2000 to 2050 are 1,440 Gt CO 2. It is shown that the rates of decrease in the GDP of developing countries under the HR scenario are smaller than those under the C&C scenario. In addition, the rates of decrease in the GDP of industrialized countries under the C&C scenario are smaller than those under the HR scenario. China becomes the importer of emission rights in the long run, even under the HR scenario, whose allocation method is based on cumulative CO 2 emissions. Moreover, GDP loss in China increases over time (GDP losses in China worsen off over time). Keywords: computable general equilibrium modelling; permit allocation; climate policy * Graduate School of Economics, Osaka University, 1-7, Machikaneyama, Toyonaka, Osaka, , Japan. Phone: ; Fax: tamechika@econ.osaka-u.ac.jp

2 1. Introduction The Kyoto protocol, in which the ratified Annex B countries abate CO 2 emissions, ends in Accordingly, negotiations for the international climate change policy that will come into effect after 2012, the so-called post-kyoto protocol, have begun. In these negotiations, emission targets and the allocation of emission quotas for multiple countries are being discussed. There are also some studies that focus on the CO 2 emission quotas allocation under the post-kyoto protocol (e.g. Böhringer and Welsch 2004).Under the Kyoto protocol framework, which a group of counties or regions abate CO 2 emissions, carbon leakage occurs. The issue of carbon leakage is defined as follows: the impact of CO 2 emission reduction on the world CO 2 emissions are small when only a group of countries reduce their CO 2 emissions, and this small impact could be further diminished by the increase in CO 2 emissions in non-abatement countries. Therefore, the desirable post-kyoto protocol is one in which CO 2 emission abatement is implemented in all countries including developing countries, which tend to rapidly increase their CO 2 emissions. The 15th Conference of the Parties (COP 15), held at Copenhagen in 2009, set the emission target as limiting the temperature increases to less than 2 degrees Celsius above preindustrial levels in order to prevent dangerous climate change. This requires stabilization of atmospheric CO 2 emissions at 450 ppm CO 2 eq. In this paper, we focus on this 450 ppm scenario. To achieve this target, the methods for allocating emission quotas across countries, such as the contraction and convergence of CO 2 emissions, must be considered. In this method, emission quotas are allocated all countries such that the per capita CO 2 emissions in the terminal point are equalized across them. Developing countries argue that emission quotas must be allocated according to historical responsibility, and mention that emission targets must be set according to the amount of cumulative CO 2 emissions. In this paper, we simulate emission reduction under the post-kyoto protocol. In accordance with the Copenhagen Accord, we set the 450 ppm target. In this paper, the two allocation methods of CO 2 emission quotas for the period: per capita cumulative CO 2 emissions and contraction and convergence of CO 2 emissions. Under the per capita cumulative CO 2 emissions scenario, which allocates emission quotas so as to equalize per capita cumulative CO 2 emissions across all countries, industrialized countries face negative emission quotas. That is, they are not allowed to emit CO 2 emissions under this scenario. Therefore, it is necessary to note that implementation of international emission trading is required under the per capita cumulative CO 2 emissions scenario. The rest of this paper is organized as follows. Section 2 discusses CO 2 emissions by regions and Section 3 provides an overview of the model and the data. Section 4 describes our policy scenarios. Simulation results are discussed in Section 5. Section 6 concludes. 2

3 2. CO 2 emissions In this section, we survey CO 2 emissions. Table 1 summarizes CO 2 emissions for the periods. As shown in the table, the largest emitter of cumulative CO 2 emissions is United States, followed by China, Russian Federation, Germany, United Kingdom and Japan. Since CO 2 emissions correlate with populations, we take account of population, when considering historical responsibility on climate change. Therefore, we define the per capita cumulative CO 2 emissions as the indicator of the historical responsibility on climate change. Table 1: CO 2 emissions from 1950 to 2005, mt of CO 2 Region / Country WRI data United States China Russian Federation Germany United Kingdom Japan France India Canada Ukraine Poland Italy South Africa Australia Mexico Regions in our model North America (US and Canada) pacific oecd (aus, nz and korea, canada) JAPAN China ( including Hong Kong) India OECD Europe Eastern Europe Rest of the world (Other Asia, Middle East, Africa Latin America, Mexico) total

4 Table 2 provides the projected CO 2 emissions for the periods. We calculate future CO 2 emissions by the following procedure. First CO 2 emissions from 2005 to 2035 are given by EIA (2010). Next, CO 2 emissions from 2035 to 2050 are derived by extending at the growth rate of CO 2 emissions from 2030 to 2035, as projected by EIA (2010). Table 2: CO 2 emissions projection, mt of CO 2 JPN pao EEU oeu nam CHN IND row Model 3.1 Model We construct a multi-regional and multi-sector dynamic computable general equilibrium model based on Rutherford and Paltsev (2000). The model has 8 regions and 6 sectors. In each region, there are three types of agents; representative household, government and firms. A household determines consumption and investment (savings) so as to maximize his utility subject to a budget constraint. A household supplies capital, labour, land and natural resources and then allocates his factor income to purchase of goods and investment (savings). Its investment is determined by the Ramsey infinite horizon optimizing model. We assume that labour, land and natural resources are mobile within a region, and that land and natural resources are sector-specific factors. We also assume that capital is mobile between regions. Next, the government collects tax revenue from output taxes, intermediate demand taxes, factor taxes, final demand taxes, import tariffs and export subsidies, and then, allocates his tax revenue to purchase of goods. We assume that tax rates are constant. Finally firms produce goods with constant returns to scale technology to maximize profits using primary factors and intermediate inputs. To explain bilateral cross-hauling in goods trade, we use the so-called Armington assumption: goods produced in different regions are qualitatively distinct (Armington, 1969). We assume two types of production function which is based on the GTAP-EG model 4

5 (Rutherford and Paltsev, 2000); the fossil-fuel production function and the non-fossil fuel production function. Fossil fuel production activities include extraction of coal, crude oil, and natural gas. Production has the structure shown in Figure 1. Fossil fuel output is produced as a constant elasticity of substitution (CES) aggregate of natural resources and non natural resources input composite. The non natural resources input for the production is a Leontief composite of capital, labour, land, intermediate inputs. Non fossil fuel production (including electricity) has the structure shown in Figure 2.Output is produced with Leontief aggregation of non-energy goods and an energy- primary factor composite. The energy-primary factor composite is a CES function of energy composite and primary factor composite. The primary factor composite is a CES aggregation of primary factors. The energy composite is a CES aggregation of electricity and non-electric energy input composite. The non-electric energy is a CES aggregation of coal and liquid energy composites and the liquid energy composite is a CES aggregation of petroleum and coal products and natural gas. The fossil fuel composite is a Leontief aggregate of fossil fuel goods and CO2 emissions. The utility function for the representative household is a nested CES function, as shown in Figure 3. Aggregate consumption is a CES aggregation of a non-energy composite and energy composite. The non-energy composite is a Cobb-Douglas aggregate of non-energy goods, and the energy composite is a Cobb-Douglas aggregate of electricity, petroleum and coal products, natural gas, and coal. Moreover, the fossil fuel composite is a Leontief aggregate of fossil fuel goods and CO2 emissions. In our model, representative households are assumed to have an infinite horizon. Therefore, we need set the terminal condition so as to solve the dynamic model. We assume that t in the terminal period, the growth rate of investment is equal to that of output. The amount of CO 2 emissions is assumed to be proportional to the volume of fossil fuels and refined oil and coal products, which are used by firms as intermediate inputs or consumed by households. Within our model, the price per unit to CO 2 emission is determined such that the amount of the actual CO 2 emissions equals CO 2 emission quotas, when the amount of CO 2 in the business-as-usual (BAU) scenario exceeds emission quotas. Then, we define the unit price to emit CO 2 as permit price. The permit price differs by regions when regions apply domestic CO 2 taxes. On the other hand, the permit price is equalized among countries when international emission trading is allowed. Furthermore, a household owns CO 2 emission quotas and collects permit revenue. Table 3 provides the regions and sectors incorporated in our model. The world is aggregated into 8 regions: North America (NAM), Pacific OECD, Japan (JPN), China (CHN), India (IND), OECD Europe (OEU), Eastern Europe, and the rest of the world (ROW). Sectors are aggregated into 6 sectors: coal, crude oil, natural gas, refined oil and coal products, electricity and heat, and 5

6 non-energy macro good aggregate. Figure 1: Production function of fossil fuel sectors Figure 2: Production function of non fossil fuel sectors 6

7 Table 3: Regions and sectors Regions Figure 3: Final demand Sectors NAM North America (USA and Canada) Energy PAO Pacific OECD (Australia, New Zealand, Korea) COL Coal JPN Japan GAS Natural gas CHN China P_C Refined oil and coal products IND India OIL Crude oil OEU OECD Europe ELY Electricity and heat EEU Eastern Europe Non-energy ROW Rest of the world ROI Non-energy macro good aggregate 3.2 Data We employ the GTAP 7 database as the benchmark data. The GTAP 7 database provides production, imports and exports, other activities, energy data, and CO 2 emissions. Our baseline projection is calibrated by incorporating EIA projections on CO 2 emissions and the growth rates of GDP (EIA, 2010). 7

8 4. Scenario design In this paper, we simulate the scenario to stabilize the atmospheric CO 2 concentration at 450 parts per million (ppm) CO 2 eq. The 450 ppm scenario limits global warming at 2 degrees Celsius or lower, relative to pre-industrial levels. We assume that global CO 2 emission budgets for the periods are set at 1,314, million tons of CO 2. These global budgets of cumulative CO 2 emissions are derived by calculating the cumulative CO 2 emissions for the period in the contraction and convergence case under the assumption that global CO 2 emissions are to be reduced by 25% in 2050, relative to 1990 emission levels (a detailed discussion of the procedure for calculating the global CO 2 emission budgets is presented in Section 4.2). Meinshausen et al (2009) states that limiting cumulative CO 2 emissions for the period to 1,440 Gt CO 2 yields a 50% probability of warming exceeding 2 degrees Celsius, relative to preindustrial levels. Cumulative CO 2 emissions from 2000 to 2004 are 124, million tons of CO 2 (IEA, 2009). Therefore, we can maintain the increase in global temperature below 2 degrees Celsius in 2050,relative to pre-industrial levels,with the probability of 50%, if the cumulative CO 2 emissions from 2005 to 2050 are 131,549 million tons of CO 2. Therefore, our global CO 2 emission budgets from 2005 to 2050 fall within 50% probability of warming exceeding the 2 degrees Celsius estimated by Meinshausen et al (2009). In this paper, all countries (regions) are assumed to reduce CO 2 emissions over the period. We introduce two methods for allocating CO 2 emission quotas for this period: the historical responsibility scenario and the contraction and convergence of CO 2 emissions scenario. The historical responsibility scenario allocates emission quotas among countries such that the per capita cumulative CO 2 emissions over the period are equalized across all countries. The contraction and convergence of CO 2 emissions scenario, on the other hand, allocates emissions quotas among countries such that the per capita CO 2 emissions in 2050 are equalized across all countries. 4.1 Emission quotas allocation formula: Historical Responsibility The historical responsibility scenario allocates our global budgets of cumulative CO 2 emissions, which is 1,314, million tons of CO 2, across all countries according to their historical responsibility for climate change. Historical responsibility is often measured by the cumulative CO 2 emissions since CO 2 emission data from 1900 to 1949 for many countries is, however, non-existent. Because of this data limitation, we consider cumulative CO 2 emissions from 1950 to Hence, the historical responsibility scenario allocates emissions quotas from 2005 to 2050 among countries such that the per capita cumulative CO 2 emissions from 1950 to 2050 are equalized across all countries. For setting emissions quotas, CO 2 emission data from 1950 to 2004 and population data from 1950 to 8

9 2050 are required. We employ the CO 2 emission data from the World Resources Institute (2010), and use data from the IDB (2010) for the population from 1950 to The procedure for calculating emission quotas per year for each country (region) is as follows: first, cumulative world CO 2 emissions from 1950 to 2050 are calculated by adding the world cumulative CO 2 emissions from 1950 to 2004 to our global budgets of 1,314, million tons of CO 2 ; next, we calculate the world cumulative population from 1950 to 2050 by using the IDB population data (2010). Then, the per capita cumulative CO 2 emissions are derived by dividing the world cumulative carbon emissions from 1950 to 2050 by the world cumulative population from 1950 to The formula for per capita cumulative CO 2 emissions is z = 2004 t=1950 CO2 world(t) + global emission budgets 2050 t=1950 POP world (t) where z represents the level of per capita cumulative CO 2 emissions, t denotes the year, CO2 world (t) is CO 2 emissions in year t, and POP world (t) denotes world population in year t. Then, the annual emission quotas for each country are calculated by multiplying per capita cumulative (1) CO 2 emissions by the annual population for each country. The formula for the annual emission quotas allocation is Z i (t) = z pop i (t) (2) where Z i (t) represents the annual emission quotas, i denotes the country, and pop i (t) denotes the national population in year t. 4.2 Emission quotas allocation formula: Contraction and Convergence of CO 2 emissions (C&C) Under the contraction and convergence of CO 2 emissions (C&C) scenario, we set the CO 2 emission reduction target, such as reducing the world carbon emissions in 2050, to a level of 25% below 1990 levels. We assume that all countries reduce their CO 2 emissions from 2005 to 2050 and that per capita CO 2 emissions in 2050 are equalized across all countries. The formula for per capita annual CO 2 emissions is z i (t) = 46 (t 2004) z 46 i (2004) + (t 2004) z c (3) 46 where z i (t) represents the level of per capita CO 2 emissions in t in country i, t denotes the year, z c is the level of per capita CO 2 emissions in 2050 CO 2 emissions. That is, the annual per capita CO 2 emissions are calculated by the weighted average of per capita CO 2 emissions in 2004 and The formula for the annual emission quotas allocation, therefore, is Z i (t) = z c pop i (t) (2) 9

10 where Z i (t) represents the annual emission quotas, i denotes the country, and pop i (t) denotes the national population in year t in country i. Our global budgets of CO 2 emissions from 2005 to 2050 are obtained from the emission quotas under this C&C scenario. 4.3 Emission trading Table 4 summarizes the emission targets in the historical responsibility and C&C scenarios. Under the historical responsibility scenario, industrialized countries or regions such as NAM, OEU, EEU, PAO, and JPN have negative emission quotas, as shown in Table 3. These countries are not allowed emit any CO 2 emissions. Thus, international emission trading is required in the historical responsibility scenario in order to implement the historical responsibility scenario. In this paper, therefore, we assume that international emission trading is adopted under the historical responsibility scenario 1. 1 IEA (2008) shows that the 450 ppm scenario will not be achieved without reductions in emissions by the non-oecd countries, even if the OECD countries were to reduce their emissions to zero. 10

11 Table 4: Emission quotas, mt of CO 2 HR scenario JPN pao EEU oeu nam CHN IND row world C&C_NTR and C&C_TRD scenarios JPN pao EEU oeu nam CHN IND row world Policy scenarios In this paper, we simulate the following four scenarios: BaU: Business as usual. All countries or regions do not reduce CO 2 emissions. HR: All countries or regions face the emission quotas such that the per capita cumulative CO 2 C&C_TRD: emissions from 1950 to 2050 are equalized, and international emission trading is adopted. All countries or regions face the emission quotas such that the per capita CO 2 emissions in 2050 are equalized and gradually reduce CO 2 emissions from 2005 to 2050 using international emission trading. C&C_NTR: All countries or regions face the emission quotas such that the per capita CO 2 emissions in 2050 are equalized and gradually reduce CO 2 emissions from 2005 to 2050, and international emission trading is not adopted. We compare the differences between the equilibrium solutions for each of the above three scenarios, 11

12 in which CO 2 emission abatement is implemented, and the equilibrium solution for BaU scenario. 5. Simulation results In this section, we present the simulation results and examine them. 5.1 Emission target Table 5 summarizes the rate of reduction of CO 2 emissions. The rate of reduction varies from region to region. India (IND) and the rest of the world (ROW) receive sufficient emission quotas in all three scenarios, HR, C&C_TRD, and C&C_NTR. In all scenarios, emission quotas in India (IND) and the rest of the world (ROW) are above their BaU CO 2 emissions. India (IND) and the rest of the world (ROW) own the so-called hot air in the scenarios HR, C&C_TRD, and C&C_NTR. Furthermore, India (IND) and the rest of the world (ROW) receive much higher emission quotas in the HR scenario than in the C&C_TRD and C&C_NTR scenarios. Under HR, the reduction rates in the industrial countries other than Pacific OECD (PAO) exceed 100%, meaning that the industrialized countries other than Pacific OECD (PAO) are not allowed to emit CO 2 emissions. China (CHN) increases its CO 2 emissions at a rapid rate. China (CHN) faces emission targets in the HR scenarios, unlike India (IND) and the rest of the world (ROW). China receives higher emission quotas under HR than under C&C_TRD and C&C_NTR. Under HR, China (CHN) s emission target in the beginning is lower, however becomes high over time. 5.2 Permit price In this section, we examine the permit prices under HR and C&C_TRD. Table 6 shows permit prices. Under HR, the permit price in 2005 is $2/t CO 2. The permit price in the HR scenario rises over time, resulting in the permit price in 2050 being $7/t CO 2. Under C&C_TRD, on the other hand, the permit price in 2005 is $21.75/tCO 2. The permit price in the C&C scenario declines over time, resulting in the permit price being around $5/tCO 2 after In this way, the difference between permit price in HR and C&C_TRD scenarios is caused by reduction rates. In 2005, the global reduction rate under HR is 17% and under C&C_TRD is 2%, as shown in Table 4. In the beginning, the high reduction rate is imposed under the HR scenario and the low reduction rate under the C&C_TRD scenario. In addition, under the HR scenario, countries or regions need to devote 12

13 much effort to abate emissions in the beginning because they must reduce emissions substantially at that time, before they can abate emissions with ease during the latter half of the periods. Therefore, the permit price declines. Under the C&C_TRD scenario, the reduction rate of CO 2 emissions increases over time, resulting in the rise of the permit price. 5.3 Volumes of exports and imports of emission permits Table 7 shows the volume of exports and imports of emission permits under the HR and C&C_TRD scenarios. In the C&C_TRD scenario, India (IND) and the rest of the world (ROW) are exporters of emission permits. On the other hand, the largest importer of emission permits is North America (NAM). North America (NAM) will import 1, million tons of emission permits in 2030 and 3, million tons in The second largest importer of emission permits is China (CHN). China (CHN) will import 2, million tons of emission permits in 2030 and 3, million tons in In the HR scenario, India (IND) and the rest of the world (ROW) are exporters of emission permits from 2005 to In the HR scenario, North America (NAM) is the largest importer of emission permits as well. North America (NAM) will import 8, million tons of emission permits in 2030 and 9, million tons in The second largest importer of emission permits under the HR scenario is OECD Europe (OEU). OECD Europe (OEU) will import 3, million tons of emission permits in 2030 and 3, million tons in In the HR scenario, China (CHN), who increases its future CO 2 emissions at a rapid rate, becomes the importer of emission permits in the long run. The China s volume of imports of emission permits in the HR scenario is smaller than that in the C&C_TRD scenario. Compared with the C&C_TRD scenario, India (IND) and the rest of the world (ROW) under the HR scenario, which export emission permits, increase the volume of exports of emissions permits from 2005 to All industrial countries under the HR scenario increase their volume of imports of emission permits compared to the C&C_TRD scenario. This is because the reduction rates of CO 2 emissions for industrial countries in the HR scenario are higher than those in the C&C_TRD scenario. 5.4 GDP GNI Table 8 provides the percentage changes in GDP from BaU. The rate of decrease in the GDP of Japan (JPN) in the HR scenario is smaller than that in the C&C_TRD scenario. In terms of GDP, the HR scenario is desirable for JPN. In the beginning of the period, the rates of decrease in the GDP of countries or regions other than Japan (JPN) in the C&C_TRD scenario are smaller than those in the HR scenario. Then, in the latter half on this period, the rates of decrease in the GDP of countries or regions 13

14 other than Japan (JPN) in the C&C_TRD scenario are larger than those in the HR scenario. Table 9 shows the percentage changes in gross national income (GNI) from BaU. GNI is derived by adding permit revenue to GDP. The rates of decrease in the GDP of emission permit exporters such as India (IND) and the rest of the world (ROW) in the HR scenario are smaller than those in the C&C_TRD scenario from 2005 to In terms of GNI, the HR scenario is desirable for India (IND) and the rest of the world (ROW). In the beginning of the period, the rates of decrease in the GNI of countries or regions other than India(IND) and the rest of the world (ROW) in the C&C_TRD scenario are smaller than those in the HR scenario. Then, in the latter half of this period, the rates of decrease in the GNI of countries or regions other than India(IND) and the rest of the world (ROW) in the C&C_TRD scenario are larger than those in the HR scenario. 5.5 C&C_NTR case Table 10 shows the simulation results of the C&C_NTR scenario. In this section, we examines that results. The marginal abatement costs vary by region and range from $0/tCO 2 to $208/tCO 2. The marginal abatement costs in India (IND) are $0/tCO 2 from 2005 to The marginal abatement costs in the rest of the world (ROW) are $0/tCO 2 from 2010 to This is because BaU CO 2 emissions in India (IND) are below the emission quotas during the period and because BaU CO 2 emissions in the rest of the world (ROW) are below the emission quotas during the period. Regions other than India (IND) and the rest of the world (ROW) increase their marginal abatement costs over time. These results are due to the increase in the reduction rate over time. The rates of decrease in the GDP of regions other than India (IND) and the rest of the world (ROW) in the C&C_NTR scenario are smaller than those in the C&C_TRD scenario. This is because international emission trading lowers the burdens of emission reduction in these regions. 6. Conclusions In this paper, we analyzed the post-kyoto scenario using a dynamic general equilibrium model. To achieve the 450 ppm target, we establish two types of methods to allocate emission quotas. We simulate the HR and C&C scenarios. Developing countries argue that the rate of emission reduction for a country must be set according to the cumulative CO 2 emissions in that country. This paper shows that the HR scenario, which allocates emission quotas across all countries on the basis of cumulative CO 2 emissions, is preferable for developing countries compared to the C&C scenario. Even under the HR scenario, China, 14

15 however, becomes the importer of emission rights in the long run, and the reduction rate of CO 2 emissions in China increases over time. Reference Armington, P. S. (1969). A theory of demand for products distinguished by place of production. IMF Staff Papers, 16, Böhringer, C. and Welsch, H., (2004). Contraction and convergence of carbon emissions: an intertemporal multi-region CGE analysis. Journal of Policy Modeling, 26, EIA (2010), International Energy Outlook 2010, Energy Information Agency (EIA). GTAP (2005), Global Trade Analysis Project, GTAP 7 Data Package, University of Purdue. IEA (2008), World Energy Outlook (2008 edition), International Energy Agency, OECD/IEA, Paris, France. IEA (2009), CO2 Emission from Fuel Combustion (2009 edition), International Energy Agency, OECD/IEA, Paris, France. Meinshausen, M, Meinshausen, N, Hare, W, Raper, S C B,Frieler, K, Knutti, R, Frame, D J and Allen, M R (2009). Greenhouse gas emission targets for limiting global warming to 2 C. Nature, 458, Rutherford, T. F. and S. V. Paltsev (2000). GTAP in GAMS and GTAP-EG: Global Datasets for Economic Research and Illustrative Models, Department of Economics, University of Colorado, Working Paper. United States Census Bureau (2010). International Data Base (IDB), United States Census Bureau. WRI (2010). Earth Trends Searchable Database: Climate and Atmosphere -- CO2 Emissions: Total 15

16 CO2 emissions. World Resources Institute (WRI). 16

17 Table 5: Emission reduction in percentage of BaU emissions HR scenario JPN pao EEU oeu nam CHN IND row world C&C_NTR and C&C_TRD scenarios JPN pao EEU oeu nam CHN IND row world

18 Table 6: Permit price in $US per ton CO 2 HR scenario JPN pao EEU oeu nam CHN IND row C&C_TRD scenario JPN pao EEU oeu nam CHN IND row

19 Table 7: Permit exports and imports, mt of CO 2 positive: exports, negative: imports HR scenario JPN pao EEU oeu nam CHN IND row C&C_TRD scenario JPN pao EEU oeu nam CHN IND row

20 Table 8: GDP (% change from BaU) HR scenario JPN pao EEU oeu nam CHN IND row C&C_TRD scenario JPN pao EEU oeu nam CHN IND row

21 Table 9: GNI (% change from BaU) HR scenario JPN pao EEU oeu nam CHN IND row C&C_TRD scenario JPN pao EEU oeu nam CHN IND row

22 Table 10: Simulation results under the C&C_NTR scenario Marginal abatement cost in $US per ton CO 2 JPN pao EEU oeu nam CHN ind row GDP (GNI) (% change from BaU) JPN pao EEU oeu nam CHN IND row