ABSTRACT
ABSTRACT
One of the contentious issues of the ongoing climate negotiations is the huge differences in per-capita CO2 emissions between Annex I and Non-Annex I countries. This paper analyzes the costs of reducing this gap using a global computable general equilibrium (CGE) model. A range of carbon taxes are considered for Annex I countries as policy instruments. Results show that the average per-capita CO2 emissions of Annex I countries would still remain almost twice as high as those of Non-Annex I countries in 2030 even if the CO2 emissions of the former are reduced by 57% from the baseline through a heavy carbon tax of $250/tCO2. The global reduction of CO2 emissions would be only 18% due to an increase in CO2 emissions in the Non-Annex I countries. This reduction would not be sufficient to stabilize atmospheric CO2 concentration at the level implied by UNFCCC to avoid dangerous climate change. The $250/tCO2 carbon tax, on the other hand, would reduce Annex I countries’ gross domestic product by 2.4%, and global trade volume by 2%. This paper concludes that a demand for the convergence of per capita emissions between industrialized and developing countries would not be fruitful in climate change negotiations.
Introduction
One of the contentious issues of the ongoing climate change negotiations is the huge difference in per-capita emissions between developed and developing countries. Developing countries, which mostly fall in the Non-Annex I group, argue that since their per-capita CO2 emissions are very small compared to those of developed countries, it should be legitimate for them to increase their emissions to achieve anticipated economic growth. They further argue that one of the principles of a long-term climate change agreement should be equity in that per-capita emission converges between the countries in the long run. Several existing studies [e.g., Citation1–4] highlight this issue of equity in climate change negotiation. On the other hand, developed countries assert that without meaningful participation of developing countries, especially the emerging developing economies, such as China, India, Brazil and South Africa, achieving the objective of the United Nations Framework Convention on Climate Change (UNFCC) – stabilization of atmospheric concentrations of greenhouse gases (GHGs) at a level that would prevent dangerous anthropogenic interference with the climate system – would not be feasible [Citation5,Citation6]. The merit of this argument rests on the fact that China has already surpassed the United States in CO2 emissions [Citation7] and that non-OECD countries account for 90% of population growth, 70% of the increase in economic output and 90% of energy demand growth over the period from 2010 to 2035 [Citation8]. These arguments could be attributed to the failure of climate change negotiations in the past [Citation9,Citation10] and to causing the world to wait for more than two decades to reach the recent global agreement (i.e., the Paris agreement occurred at the 21st meeting of the Conference of the Parties to the UNFCCC in Paris in December 2015).
A critical question is: Can the stabilization of GHG concentrations in the atmosphere to avoid climate change be achieved while converging the per-capita emissions between industrialized and developing countries? To avoid dangerous consequences in the Earth's atmosphere, the Earth's mean average temperature should not be higher than 2 °C from the pre-industrialization level [Citation11]. The Fourth Assessment of the Intergovernmental Panel on Climate Change (IPCC) reports that concentrations of CO2 (GHG) emissions should be stabilized at 350 ppm (445 PPM CO2-equivalent) to maintain temperature rise at 2 °C [Citation12]. This entails a reduction of CO2 emissions by 85% below the 2000 level.
Historical trends indicate that per-capita CO2 emission has been decreasing for Annex I countries (with an exception in 2010) and increasing for Non-Annex I countries (see Figure 1). In 1990, per-capita CO2 emission of Annex I countries was 11.83 tonnes CO2 (tCO2 hereafter); this decreased by 12% to 10.41 tCO2 in 2010. During the same period (i.e., 1990–2010), Non-Annex I countries’ per-capita emissions increased by 80% from 1.58 to 2.85 tCO2 per capita. The per-capita emission gap between the Annex I countries and Non-Annex I countries decreased by around 26% from 10.25 tCO2 in 1990 to 7.56 tCO2 in 2010.
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20 May 2016Figure 1. Historical per-capita emission gap between the Annex I and Non-Annex I countries (tCO2 per capita).
Figure 1. Historical per-capita emission gap between the Annex I and Non-Annex I countries (tCO2 per capita).
As of the year 2010, the global average per-capita CO2 emission is 4.44 tCO2 [Citation7]. To meet the 2 °C target, global CO2 emissions should drop by 85% in 2050 from 2000 level. This implies that global CO2 emission from fuel combustion, which was 23.5 billion tCO2 in 2000, should be limited at 3.5 billion tCO2 in 2050. According to the UN Population Foundation projection, global population will reach 9.6 billion by 2050 [Citation13], implying 0.367 tCO2 global average per-capita CO2 emission in that year. Thus, to meet the UNFCCC objective (i.e., maintaining Earth’s mean surface temperature at 2 °C above the pre-industrial level), the global average per-capita CO2 emission from fuel combustion must be dropped by 92% in 2050 from the current (2010) level. On average, global per-capita CO2 emission must drop by 6% annually during the 2010–2050 period. Such a high rate of annual reduction of per-capita CO2 emissions indicates the challenge ahead to meet the ultimate objective of the UNFCCC.
The objective of this analysis is to examine the costs to the global economy of moving forward in the direction of converging per-capita emissions between Annex I and Non-Annex I countries. Note that in the very long run (50 to 100 years) it could be technically viable to have global convergence of per-capita CO2 emissions. This could happen when both Annex I and Non-Annex I groups reduce their respective aggregate per-capita emissions from their current levels with Annex I countries many-fold faster than Non-Annex I countries. However, Non-Annex I countries’ argument is for increasing their per-capita emissions in the near term so that they move towards narrowing the per-capita CO2 emission gap. The paper attempts to capture this reality of climate change negotiations and demonstrates that this notion of convergence is counterproductive to meeting the UNFCCC objective. A range of uniform carbon taxes are introduced in Annex I countries as a policy instrument while Non-Annex I countries are exempted from the carbon taxes. The impacts of the policy instruments are simulated using a global, dynamic, multi-sector computable general equilibrium model. A number of studies examine the consequences of meeting the 2 °C target at regional and global levels [see, e.g., Citation14,Citation15]. In so doing, these studies consider global carbon tax. The present study focuses on the impacts of narrowing per-capita emission gaps between Annex I and Non-Annex I groups by imposing carbon tax only on the former, whereas the latter could still increase their per-capita CO2 emissions.
The paper is organized as follows. The second section discusses CO2 emissions and per-capita emissions focusing on the top 30 emitters in 2010. This is followed by brief description of the model in the third section. The fourth section presents impacts on CO2 emissions and per-capita emissions of various countries and regions due to the policy instrument implemented to reduce the per-capita emission gaps. This is followed by a discussion of the impacts of the policy instrument on economic outputs and international trade. Finally, key conclusions are drawn in the sixth section.
Current status of per-capita and total CO2 emissions
In 1990, just two years before the adoption of the UNFCCC, the total CO2 emissions of Non-Annex I countries from fuel consumption were 32% of the global CO2 emissions from fuel consumption; for the remaining 68%, Annex I countries were responsible. After 20 years in 2010, the situation has reversed with Non-Annex I countries accounting for 52% of the global CO2 emissions (see Figure 2). These statistics also imply the need for Non-Annex I countries’ increasing contribution in reducing global CO2 emissions. Moreover, of the global CO2 emissions from fuel consumption in 2010, 90% was contributed by only 33 countries and Taiwan.Footnote1 China and the US alone contributed 43% of the global CO2 emissions from fuel consumption in 2010. If India, Russia, Japan and Germany are added, these six countries contributed more than 60% of the global CO2 emissions from fuel consumption in 2010 (see Figure 3). Of the 33 countries that accounted for 90% of the global CO2 emissions from fuel consumption in 2010, 17 are Non-Annex I countries and the remaining 16 are Annex I countries. Figure 2 implies two important caveats: only 30 plus countries, not necessarily all 186 UNFCCC signatory countries, need to lead to reduce global CO2 emissions; and not only Annex I countries but also Non-Annex I countries, such as China, India, Republic of Korea, Iran, Saudi Arabia, Brazil, Indonesia, Mexico, South Africa, Thailand, Malaysia, Venezuela, Argentina, United Arab Emirates, Egypt, Pakistan and Vietnam would need to contribute to reduce global CO2 emissions. This, however, does not imply that all of these Non-Annex I countries should finance their GHG mitigation efforts by themselves. The debate over who should finance the cost of GHG mitigation is beyond the scope of this study.
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20 May 2016Figure 2. Fuel consumption-related CO2 emissions from Annex I and Non-Annex I countries in 1990 and 2010.
Figure 2. Fuel consumption-related CO2 emissions from Annex I and Non-Annex I countries in 1990 and 2010.
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20 May 2016
Figure 3. Countries that contributed 90% of global CO2 emissions in 2010.
One of the crucial issues that discourages Non-Annex I countries, which fall in the list of top 30 CO2 emitters in 2010 (Figure 2), from having any sort of binding commitment to reduce their GHG emissions, is that their per-capita emissions are much lower compared to those of Annex I countries in the same group of top 30 emitters. For example, India was the third largest CO2 emitter in 2010; however, its per-capita emission was more than 12 times smaller compared to that of the US, the second largest emitter, and Australia, the 16th largest emitter (see ). Similarly, although China was the largest emitter in 2010, its per capita emission is more than 3 times smaller than that of the US. This implies that per-capita emissions in large Non-Annex I emitters such as China, India, Mexico, Indonesia, Brazil, South Africa are expected to rise in the near future.
Table 1. Per-capita emissions in descending order in 2010 (tCO2).
Some Non-Annex I countries such as Korea, Saudi Arabia and the United Arab Emirates, which fall under the group of top 30 emitters accounting for 90% of global emissions, have per-capita emissions higher than those of several Annex I countries. Some Non-Annex I countries under the top 30 emitters’ group, such as Iran, Malaysia, South Africa and Venezuela, have per-capita emissions comparable to those of several Annex I countries.
Methodology and data
A multi-regional, multi-sector, recursive dynamic computable general equilibrium (CGE) model was used for the purpose of this study. Please refer to Timilsina et al. [Citation16] for a detailed description of the model and data. Note that CGE models are the most appropriate and widely applied analytical tools to examine economic and environmental consequences of climate change policies and measures at the national as well as the global level. Please refer to Edenhofer et al. [Citation14] for more details on the application of CGE models for climate policy analysis.
The model has 28 sectors and 25 countries/regions. Each of the 28 sectors is depicted by a set of nested constant elasticity of substitution (CES) production functions (see Figure 4). At the top tier of the production structure, firms in each country/region minimize their production costs by choosing an optimal combination of the aggregate non-energy intermediate input (ND) and the composite of value added and the aggregate energy input (VAE). The non-energy intermediate input in a country/region is formed through a CES combination of that commodity produced in the country/region and that imported from various countries/regions. Similarly, the value added-energy composite is formed through a CES combination of land and non-land factor input, where the latter is the CES composite of labor and the capital-energy composite. This aggregation continues as illustrated in Figure 4.
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Figure 4. Structure of the CGE model developed for the study.
The study gives special attention to energy sector modeling for two reasons. First, since a carbon tax is introduced to fossil fuels, an explicit representation is needed of the fossil fuel sector including various petroleum products. Second, the study aims to assess the competitiveness of biofuels with fossil fuels when carbon tax is introduced into the latter; therefore, an explicit representation of biofuels is also needed. As shown in the “Energy Block” in Figure 4, the total demand for energy is a CES composite of electricity and an aggregate of non-electric energy commodities.Footnote2 One component of the latter is the liquid fuel, which is a CES composite of the ethanol–gasoline and diesel–biodiesel bundles. The model is structured in such a way that it allows direct substitution between gasoline and ethanol, and between diesel and biodiesel.
Land-use changes are incorporated into the model via a constant elasticity of transformation (CET) representation of land supply for each country/region. The “Land Block” in Figure 4 presents the structure of the land-use module incorporated in the CGE model. Total land areas are first divided into 18 agro-ecological zones (AEZ) in every country/region. Under each AEZ in a country or region, total available land area is allocated to forest land, pasture and cropland. On the second level, crops are further divided into four different categories: rice; sugar crops; grains and oilseeds; and fruits, vegetables and other non-grain crops. Finally, the grains and oilseeds category is partitioned into wheat, corn, other coarse grains and oilseeds. Land-use change is induced by changes in relative returns to land as each of the CET nests of the land module agents maximize payoffs by optimally allocating the fixed land area for this nest to the various competing uses.
While modeling the household sector, it was assumed that a representative household maximizes its utility, using a non-homothetic constant difference of elasticities (CDE) function, subject to the budget constraint. The households’ disposable income consists of the factor incomes (net of taxes) minus the direct tax. A household savings rate determines the fraction of disposable income that is saved, and thus available for investments. Hence, total national income accrues to government expenditures, household expenditures and investments.
The government derives revenue from a number of indirect taxes, tariffs and a direct tax on households. Government expenditures are an exogenously determined share of nominal gross domestic product (GDP). Government revenue equals the sum of government expenditures and government savings so that, in the model, the public sector always has a balanced budget. The direct tax on households is adjusted each period to ensure a balanced public budget. International trade is modeled by a system of Armington demands that give rise to flows of goods and services between the regions. On the national/regional level, import demand is driven by CES functions of domestic and imported components of demand for Armington commodities. Export supply is depicted by a two-tier constant elasticity of transformation (CET) function, where, on the first tier, the total output of a sector is designated either to total exports or to domestic supply, and, at the second tier, total exports are partitioned according to their destinations.
The capital stock is composed of old and new capital, where new corresponds to the capital investments at the beginning of the period and old corresponds to the capital installed in previous periods. The ratio of new to old capital is also a measure of the flexibility of the economy, as new capital is assumed to be perfectly mobile across sectors. Furthermore, each period, a fraction of the old capital depreciates. Population and productivity growth are exogenous drivers of the model's dynamics. The former is taken from the projections of the United Nations Population Division, where labor force growth corresponds to growth of the population aged 15–64 years. Productivity growth is modeled as exogenous and factor neutral for agricultural sectors, and labor augmenting for industrial and service sectors.
The model does not fix an exogenous penetration rate for the renewable energy. When carbon tax is introduced to fossil fuels, renewable energy becomes more competitive and its penetration increases. This is determined by the model endogenously. Technology development in the energy supply side has been represented through productivity change. Availability of new resources (e.g., shale gas) could impact on energy prices, which are exogenous to this model. Energy price forecasts from the International Energy Agency were used, which account for new development in energy resources while developing their global energy outlook [Citation8]. Productivity of energy follows an autonomous energy efficiency improvement (AEEI) path so that there is no endogenous technological change in the model. To ensure equilibrium in the model, three sets of market-clearing conditions are met. First, total production of each commodity equals the sum of domestic consumption and export so that the goods and services markets clear. Second, total investment equals total saving, where savings are composed of private (household) savings, public (government) savings and exogenously fixed foreign savings. Third, factor markets clear, which implies full employment.
The basic data needed for the calibration of the model is derived from the GTAP 7.0 database [Citation17].Footnote3 The main reason for using the GTAP database is that no other comprehensive global database, as required by this study, exists. Moreover, most CGE models simulating climate change policies use the GTAP database, and the use of this database in the current study helps compare the present results with those of others. The original GTAP database provides information for 113 countries and 57 commodities and production sectors. For example, biofuels are not a proper sector in the original GTAP 7.0; therefore, the database was modified in a way that allowed the introduction of the biofuels sectors into CGE model. For this purpose, detailed information was collected on production, consumption and trade, a total of seven new biofuel sectors, which were created by splitting existing GTAP sectors. The land data are also based on the GTAP 7.0 database.Footnote4 The model was implemented using GAMS software developed by the GAMS corporation.
Impacts on per-capita and absolute emissions
The study simulates various level of carbon tax ranging from US$10 to US$250 per ton of carbon dioxide. Per ton of carbon, the range corresponds to US$37 to US$917; the upper range is indeed a very high level of carbon tax. Revenue from the carbon tax is recycled, through a lump-sum transfer, to households after maintaining the government revenue neutral. This section presents key results from simulations of the model.
Impacts on per-capita emissions
Figure 5 illustrates that per capita emissions of Annex I and Non-Annex I countries are moving closer as the rate of carbon tax increases. Under the business-as-usual scenario the average per-capita emission of the Annex countries would be 13.2 tCO2 in 2030. This is 3.62 times as high as the average per-capita emission of Non-Annex I countries in the same year. A uniform carbon tax of US$10/tCO2, US$50/tCO2 and US$ 100/tCO2 in the Annex I countries would reduce their per capita emissions by 8%, 24% and 33%, respectively, from the business as usual (BAU) case. If the carbon tax is raised to a very high rate of US$ 250/tCO2, the average per-capita emission of Annex I country would drop by 46%. On the other hand, the 250/tCO2 carbon tax in Annex I countries would cause the per-capita emission of Non-Annex I countries to increase slightly, by 2.8%. Although Annex I countries’ per-capita emission would still be 1.9 times as high as that of Non-Annex I countries at 250/tCO2 carbon tax case, the gap in per-capita emissions between Annex I and Non-Annex I groups would drop by almost 65%.
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20 May 2016Figure 5. Movement of per-capita emission gap between Annex I and Non-Annex I countries along with Annex I countries’ carbon tax rates.
GDP: Gross domestic product.
Figure 5. Movement of per-capita emission gap between Annex I and Non-Annex I countries along with Annex I countries’ carbon tax rates.
GDP: Gross domestic product.
One interesting observation is that at a carbon tax rate greater than 50/tCO2, not only Annex I countries would suffer with economic losses, but Non-Annex countries would also start exhibiting economic losses despite the fact these countries are exempted from any carbon tax. This is due to international trade effect. Although a carbon tax in Annex I countries might cause moving some emission intensive industrial production to Non-Annex countries, this substitution effect would not be able to cause a complete offset of losses in economic outputs that occurred in Annex I countries.
presents change in per-capita emissions in various countries and region. Countries such as Australia, the United Kingdom and the United States would exhibit relatively higher drop of their per-capita emissions, whereas France will see the lowest drop. This is because the energy system, particularly electricity generation, is based on fossil fuels, such as coal in the former countries, whereas more than 80% of electricity is generated from nuclear power plants in France. All developing countries would experience increase in their per-capita emissions as these countries are exempted from carbon tax. This clearly indicates the leakage in emission reduction as the carbon tax in Annex I countries would cause migration of carbon-intensive industrial production to Non-Annex I countries.
Table 2. Change in CO2 emissions per capita from the BAU case in 2030 (%).
The movement toward the convergence of per-capita emissions occurs if a high carbon tax is imposed on developed countries, and developing countries are exempted from any carbon tax. However, meeting the ultimate objective of the UNFCCC – stabilizing atmospheric concentration of GHG emissions at a level that avoids climate change – would not be possible through reductions of GHG emissions from developed countries only. Developing countries also need to significantly reduce their emissions to achieve the ultimate goal of the UNFCCC. But, if developing countries start reducing their emissions, per-capita emissions of developed and developing countries start diverging instead of converging. Some developing countries, such as India and China, have announced their plans to reduce their per-capita emissions, particularly CO2 emissions per unit of GDP. To achieve their plans, these countries are expected to make huge investments in clean energy technologies on both energy supply and demand sides. Furthermore, their per-capita emissions are expected to decrease in spite of significant increase in their income (i.e., GDP per capita) unless the income effect (i.e., the rate of increase in GDP per capita) is greater than intensity effect (i.e., the rate of decrease in emission per capita GDP). The decrease in per-capita emissions in developing countries would lead to further divergence of per-capita emissions between developed and developing countries.
Impacts on CO2 emissions
Figure 6 illustrates the reduction in total CO2 emissions due to the per-capita emissions convergence efforts. A US$10/tCO2 carbon tax on Annex I countries would reduce their aggregate emissions by 11% in 2030. Since, the leakage effect (i.e., increase in emission in Non-Annex I countries due to carbon tax in Annex I countries) of this relatively small level of carbon tax would be negligible, it would reduce the global CO2 emissions by 4% from the baseline. If the carbon tax level is raised to US$250/tCO2, the aggregate emission reduction in Annex I countries would be 57% in 2030. This high-level carbon tax in Annex I countries would produce a significant leakage in Non-Annex I countries, thereby increasing the aggregate Non-Annex I CO2 emissions by 3% in 2030. At the global level the emission reduction would be around 18% from the baseline.
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20 May 2016Figure 6. Impacts on total CO2 emissions (percentage change from the baseline in 2030).
Figure 6. Impacts on total CO2 emissions (percentage change from the baseline in 2030).
presents reductions of CO2 emissions by countries or region. As discussed above, countries with predominant use of fossil fuel in their power generation would experience the relatively higher reductions in their total CO2 emissions. A US$50/tCO2 carbon tax in Annex I countries lead to reduction of their CO2 emissions by 11% to 36% in 2030. On the other hand the US$50//tCO2 carbon tax in Annex I countries causes up to 2.2% increase of CO2 emissions in Non-Annex I countries.
Table 3. Change in total CO2 emissions at various levels of carbon tax in Annex I countries in 2030 from baselines (%).
Note that at the 50% probability of maintaining the global mean temperature rise below 2 °C relative to pre-industrial levels, atmospheric GHG concentrations must stabilize below 450 ppm CO2 equivalent [Citation12]. To achieve this target, global GHG emissions should peak by 2020 at the latest and then be more than halved by 2050 relative to 1990 [Citation11]. The Fifth Assessment Report (AR5) of the IPCC suggests that there would be negative emissions in the long run (e.g., 2100) to stabilize the atmospheric CO2 concentration to avoid dangerous climate change [Citation18]. The current analysis shows that the global CO2 emissions in 2030 would be only 18% lower compared to that in the baseline, whereas more reduction would be needed to remain in the trajectory to maintain 2050 emission level at half of the 1990 level.
Impacts on economic outputs and international trade
Impacts on GDP
Figure 7 presents economic impacts of moving towards convergence of per-capita emissions. A US$50/tCO2 carbon tax on Annex I countries that reduces the per-capita CO2 emission gap between Annex I countries and Non-Annex I countries by 33% from the BAU case would cause 0.5% and 0.3% GDP losses at the Annex I and global levels, respectively, in 2030. If the carbon tax level is raised to US$250/tCO2, it would reduce the per-capita CO2 emission gap by 65% at GDP costs of 2.4% and 1.4% at the Annex I and global levels, respectively, in 2030.
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20 May 2016Figure 7. Impacts on gross domestic product (percentage change from the baseline in 2030).
Figure 7. Impacts on gross domestic product (percentage change from the baseline in 2030).
The impacts on GDP would vary significantly across the Annex I countries (see ). For example, a 33% reduction of CO2 emission intensity gap between Annex I countries and Non-Annex I countries (i.e., US$50/tCO2 carbon tax case) would cause GDP losses from 0.1% (France) to 0.7% (Canada, Australia and New Zealand) in 2030. If the carbon tax level is raised to US$250/tCO2, the economic costs in some countries, such as Canada, would be very high. It is interesting to note that the adverse GDP impacts of oil exporting Non-Annex I countries (e.g., Middle East and North Africa) would even be larger than those of Annex I countries for all carbon tax rates considered here except US$250/tCO2.
Table 4. Change in gross domestic product at various levels of carbon tax in Annex I countries in 2030 from the baseline (%).
Impacts on international trade
The carbon tax introduced in Annex I countries to move forward in the direction of converging per-capita emissions would have large impacts on international trade. Global trade would shrink by 0.5% in 2030 if the per-capita emission gap between the Annex I and Non-Annex I countries is reduced by 33% through a US$50/tCO2 carbon tax introduced in Annex I countries (see Figure 8). The contraction in global trade would reach 2% when the per-capita emission gap is reduced by 65% (i.e., introduction of a US$250/tCO2 carbon tax in the Annex I countries). Since domestic production would be more expensive due to carbon tax, Annex I countries exports would get impacted the most: 1.5% and 5% drops under US$50/tCO2 and US$250/tCO2 carbon tax cases, respectively in 2030. Non-Annex I countries would benefit as their exports increase and imports drop.
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20 May 2016Figure 8. Impacts on international trade (percentage change from the baseline in 2030).
Figure 8. Impacts on international trade (percentage change from the baseline in 2030).
Like in the impacts on GDP, Annex I countries with carbon-intensive economies (e.g., United States, Japan and Australia) would exhibit the highest impacts on their international trade (see ). For example, a US$50/tCO2 carbon tax would cause reduction of exports by 1.5% in Australia and Japan and 2.5% in the United States. Most Non-Annex I countries would gain through increase in their exports.
Table 5. Change in international trade at various levels of carbon tax from the baseline in 2030 (%).
Policy implications
This paper argued that GHG mitigation would be required in both developed and developing countries to achieve the ultimate goal of the UNFCCC. Developing countries have been advocating the convergence of emission intensity. This study suggests, through an empirical analysis, that the emission convergence issue should not be presented as a condition for a global agreement on climate change mitigation. This was what exactly happened in the Paris Agreement [see Citation19]. Instead of splitting into developed and developing country blocks, all parties to the UNFCCC agreed to contribute to the global efforts to combat climate change. They made pledges (also known as “Intended Nationally Determined Contributions” or INDC) on how much each party could reduce GHG emissions over a given time frame. Most parties have already submitted their INDC and the remaining parties are expected to do so soon. Parties also recognized that the current INDC would not be sufficient to achieve the ultimate objective of UNFCCC and they will agree for additional mitigation actions through future negotiations. The Paris Agreement has arranged several funding windows to support climate change mitigation and adaptation activities (e.g., Green Climate Fund, Least Developed Countries Fund, Special Climate Change Fund). These funding windows are expected to be utilized focusing on low-income and most vulnerable countries. The Paris Agreement allows market-based instruments to reduce GHG emissions. For example, it allows international emission trading through a provision called “internationally transferred mitigation outcomes” in its Article 6. It aims to facilitate knowledge and technology transfer through the ‘Technology Mechanism” introduced in Article 10. In a nutshell, the Paris Agreement is leading the global climate change policy initiatives in the direction which is also implied by the findings of this study.
Concluding remarks
Currently, Annex I countries’ per-capita CO2 emission is about 4 times as high as that of Non-Annex I countries. Developing countries are strongly arguing that an agreement on ongoing climate change negotiation should help reduce this disparity, thereby moving forward in the direction of converging on per-capita emissions between the industrialized and developing economies. In the absence of climate change mitigation policies in the industrialized countries, the per-capita emission gap between the Annex I and Non-Annex I countries would still remain almost at the same level as today. Using a global CGE model, a range of potential carbon taxes (S10/tCO2 to $250/tCO2) uniformly introduced in Annex I countries were simulated as a policy instrument to reduce the gaps. The highest carbon tax considered in this study ($250/tCO2) would reduce Annex I countries’ average per-capita emission by 46% from the baseline case in 2030. Since the Non-Annex I countries are exempted from the carbon tax, their average per-capita emission would increase by 3% from the baseline in 2030. The net result is a 65% drop in the gap of per-capita emissions between the Annex I and Non-Annex I countries. This would lead to around 60% of reduction of Annex I countries’ total CO2 emissions reduction from the baseline in 2030. However, this reduction would be mostly offset by increase in CO2 emissions in Non-Annex I countries, thereby leaving a merely 18% reduction at the global level. This reduction may be smaller than needed to remain in the emission trajectory to meet the 2050 level, which should be half of the 1990 level, for stabilization of atmospheric concentration of GHG emissions at the level to avoid dangerous climate change.
The carbon tax, on the other hand, would reduce Annex I countries’ GDP by 2.5% from the baseline in 2030. The economic impacts vary substantially across countries depending upon their fossil fuel intensities of economic outputs. Countries such as Australia, New Zealand, the United Kingdom and the United States are found to suffer higher economic loss compared to other countries. On the other hand, countries like France where nuclear power produces more than 80% of electricity would face the lowest economic loss. The policy instrument to reduce the per-capita emission gaps between the Annex I and Non-Annex I countries would cause the global trade volume to shrink. The $250/tCO2 carbon tax would reduce global trade by 2% from the baseline in 2030. Since domestic production would be more expensive due to carbon tax, Annex I countries’ exports would drop by 5% in 2030.
Since the emerging developing countries, such as India and China, are planning to reduce their CO2 emissions per-capita GDP, they are expected to scale up deployment of clean energy technologies and substitute towards cleaner fuels. This could lead to a decrease in per-capita emission unless the income effect (i.e., the rate of increase in GDP per capita) is greater than the intensity effect (i.e., the rate of decrease in emission per capita GDP). In such case, the gap in per-capita emissions between the developed and developing countries may not converge unless developed countries reduce their emissions at levels much higher than those estimated in this study.
| Countries with emission intensity (EI) > | Countries with EI > | Jordan | 3.1 | Pakistan | 0.8 | |||||
| 20 ton per capita | between 5 and 7 ton | Countries with EI > | Nicaragua | 0.8 | ||||||
| Qatar | 36.9 | per capita | between 2 and 3 ton | Paraguay | 0.7 | |||||
| Kuwait | 31.9 | South Africa | 6.9 | per capita | Zimbabwe | 0.7 | ||||
| Trinidad Tobago | 31.9 | Belarus | 6.9 | Jamaica | 2.9 | Guatemala | 0.7 | |||
| Luxembourg | 21.0 | Iran | 6.9 | Syria | 2.8 | Sri Lanka | 0.6 | |||
| Brunei Dar. | 20.6 | Italy | 6.6 | Algeria | 2.8 | Benin | 0.5 | |||
| UAE | 20.5 | Malaysia | 6.5 | Azerbaijan | 2.7 | Senegal | 0.4 | |||
| Countries with EI > | Slovak Rep. | 6.4 | Cuba | 2.7 | Congo | 0.4 | ||||
| between 10 and 20 ton | Venezuela | 6.3 | North Korea | 2.6 | Tajikistan | 0.4 | ||||
| per capita | Serbia | 6.3 | Panama | 2.4 | Ghana | 0.4 | ||||
| Bahrain | 18.7 | Iceland | 6.0 | Botswana | 2.3 | Bangladesh | 0.4 | |||
| United States | 17.3 | Malta | 6.0 | Egypt | 2.2 | Countries with EI | ||||
| Australia | 17.0 | Spain | 5.8 | Ecuador | 2.1 | Less than 0.4 | ||||
| Saudi Arabia | 16.2 | Ukraine | 5.8 | Tunisia | 2.1 | per capita | ||||
| Canada | 15.7 | Bulgaria | 5.8 | Brazil | 2.0 | Sudan | 0.3 | |||
| Oman | 14.5 | Switzerland | 5.6 | Countries with EI > | Côte d'Ivoire | 0.3 | ||||
| Kazakhstan | 14.2 | France | 5.5 | between 1 and 2 ton | Nigeria | 0.3 | ||||
| Estonia | 13.8 | China | 5.4 | per capita | Kenya | 0.3 | ||||
| Singapore | 12.4 | Bosnia & Herzg. | 5.3 | Uruguay | 1.9 | Cambodia | 0.3 | |||
| Finland | 11.7 | Sweden | 5.1 | Dom. Rep. | 1.9 | Cameroon | 0.3 | |||
| Korea Rep. | 11.5 | Countries with EI > | Gabon | 1.8 | Haiti | 0.2 | ||||
| Netherlands | 11.3 | between 4 and 5 ton | Moldova | 1.7 | Togo | 0.2 | ||||
| Russian Fed. | 11.2 | per capita | Indonesia | 1.7 | Myanmar | 0.2 | ||||
| Czech Rep. | 10.9 | Hungary | 4.9 | Vietnam | 1.5 | Zambia | 0.1 | |||
| Turkmenistan | 10.4 | Portugal | 4.5 | Namibia | 1.5 | Tanzania | 0.1 | |||
| Countries with EI > | Lebanon | 4.4 | Peru | 1.4 | Nepal | 0.1 | ||||
| between 7 and 10 ton | Mongolia | 4.3 | Morocco | 1.4 | Mozambique | 0.1 | ||||
| per capita | Croatia | 4.3 | Bolivia | 1.4 | Eritrea | 0.1 | ||||
| Belgium | 9.8 | Argentina | 4.2 | Costa Rica | 1.4 | Ethiopia | 0.1 | |||
| Germany | 9.3 | Chile | 4.1 | India | 1.4 | DR Congo | 0.05 | |||
| Cyprus | 9.0 | Lithuania | 4.0 | Colombia | 1.3 | |||||
| Japan | 9.0 | Macedonia | 4.0 | Armenia | 1.3 | |||||
| Israel | 8.9 | Countries with EI > | Kyrgyzstan | 1.3 | ||||||
| Ireland | 8.6 | between 3 and 4 ton | Albania | 1.2 | ||||||
| Denmark | 8.5 | per capita | Georgia | 1.1 | ||||||
| Austria | 8.3 | Mexico | 3.8 | Honduras | 1.0 | |||||
| Libya | 8.1 | Turkey | 3.6 | Countries with EI > | ||||||
| Norway | 8.0 | Latvia | 3.6 | between 0.4 and 1 ton | ||||||
| Poland | 8.0 | Thailand | 3.6 | per capita | ||||||
| United Kingdom | 7.8 | Uzbekistan | 3.6 | El Salvador | 0.9 | |||||
| Slovenia | 7.5 | Romania | 3.5 | Yemen | 0.9 | |||||
| Greece | 7.5 | Montenegro | 3.3 | Angola | 0.9 | |||||
| New Zealand | 7.0 | Iraq | 3.2 | Philippines | 0.8 | |||||
| CO2 emission per capita | CO2 emission per GDP | |||||||
|---|---|---|---|---|---|---|---|---|
| Carbon tax rate (US$/tCO2) | ||||||||
| 10 | 50 | 100 | 250 | 10 | 50 | 100 | 250 | |
| Australia and NZ | − 14.9 | − 36.0 | − 46.2 | − 58.7 | − 14.8 | − 35.6 | − 45.5 | − 57.6 |
| Canada | − 9.4 | − 26.7 | − 36.6 | − 50.8 | − 9.3 | − 26.2 | − 35.7 | − 49.2 |
| Germany | − 6.4 | − 21.1 | − 30.5 | − 43.8 | − 6.4 | − 21.0 | − 30.2 | − 43.2 |
| Spain | − 4.2 | − 15.2 | − 23.6 | − 37.5 | − 4.2 | − 15.0 | − 23.2 | − 36.7 |
| France | − 2.9 | − 10.8 | − 17.3 | − 29.4 | − 2.9 | − 10.7 | − 17.1 | − 29.0 |
| UK | − 12.2 | − 35.0 | − 46.2 | − 58.4 | − 12.2 | − 34.9 | − 45.9 | − 58.0 |
| Italy | − 4.2 | − 15.0 | − 23.1 | − 36.6 | − 4.1 | − 14.7 | − 22.7 | − 35.6 |
| Japan | − 8.0 | − 18.2 | − 25.4 | − 37.1 | − 8.0 | − 18.1 | − 25.1 | − 36.4 |
| EFTA and rest of EU | − 8.3 | − 25.6 | − 35.9 | − 50.5 | − 8.2 | − 25.2 | − 35.3 | − 49.4 |
| United States | − 10.8 | − 31.6 | − 43.1 | − 57.8 | − 10.7 | − 31.3 | − 42.5 | − 56.9 |
| Non-Annex I ECA | 0.5 | 1.9 | 3.2 | 4.7 | 0.4 | 1.8 | 2.9 | 4.3 |
| Argentina | 0.1 | 0.3 | 0.6 | 1.2 | 0.1 | 0.4 | 0.7 | 1.4 |
| Brazil | 0.4 | 1.6 | 2.7 | 4.9 | 0.4 | 1.6 | 2.7 | 5.0 |
| Rest of LAC | 0.3 | 1.2 | 2.1 | 4.1 | 0.3 | 1.3 | 2.3 | 4.6 |
| China | 0.2 | 0.8 | 1.3 | 2.5 | 0.2 | 0.6 | 1.0 | 1.9 |
| Indonesia | 0.3 | 1.2 | 2.0 | 3.7 | 0.3 | 1.2 | 2.0 | 3.5 |
| Rest of EAP | 0.5 | 1.8 | 2.9 | 5.0 | 0.4 | 1.6 | 2.6 | 4.4 |
| Malaysia | 0.2 | 0.8 | 1.3 | 2.4 | 0.2 | 0.9 | 1.5 | 2.9 |
| Thailand | 0.3 | 1.2 | 2.1 | 3.7 | 0.3 | 1.0 | 1.8 | 3.3 |
| India | 0.2 | 0.8 | 1.2 | 1.9 | 0.2 | 0.5 | 0.8 | 1.1 |
| Rest of South Asia | 0.2 | 0.8 | 1.4 | 2.7 | 0.2 | 0.7 | 1.2 | 2.3 |
| MENA | 0.0 | 0.2 | 0.4 | 1.0 | 0.2 | 1.1 | 2.0 | 4.0 |
| South Africa | 0.7 | 2.2 | 2.9 | 3.8 | 0.8 | 2.2 | 2.9 | 3.7 |
| Rest of SSA | 0.2 | 0.9 | 1.7 | 3.4 | 0.3 | 1.4 | 2.6 | 5.1 |
| Carbon tax rate (US$/tCO2) | ||||
|---|---|---|---|---|
| Country/region | 10 | 50 | 100 | 250 |
| Australia and New Zealand | − 14.9 | − 36.0 | − 46.2 | − 58.7 |
| Canada | − 9.4 | − 26.7 | − 36.6 | − 50.8 |
| Germany | − 6.4 | − 21.1 | − 30.5 | − 43.8 |
| Spain | − 4.2 | − 15.2 | − 23.6 | − 37.5 |
| France | − 2.9 | − 10.8 | − 17.3 | − 29.4 |
| UK | − 12.2 | − 35.0 | − 46.2 | − 58.4 |
| Italy | − 4.2 | − 15.0 | − 23.1 | − 36.6 |
| Japan | − 8.0 | − 18.2 | − 25.4 | − 37.1 |
| EFTA countries and rest of EU | − 8.3 | − 25.6 | − 35.9 | − 50.5 |
| United States | − 10.8 | − 31.6 | − 43.1 | − 57.8 |
| Non-Annex I ECA | 0.5 | 1.9 | 3.2 | 4.7 |
| Argentina | 0.1 | 0.3 | 0.6 | 1.2 |
| Brazil | 0.4 | 1.6 | 2.7 | 4.9 |
| Rest of Latin America and Caribbean | 0.3 | 1.2 | 2.1 | 4.1 |
| China | 0.2 | 0.8 | 1.3 | 2.5 |
| Indonesia | 0.3 | 1.2 | 2.0 | 3.7 |
| Rest of East Asia and Pacific | 0.5 | 1.8 | 2.9 | 5.0 |
| Malaysia | 0.2 | 0.8 | 1.3 | 2.4 |
| Thailand | 0.3 | 1.2 | 2.1 | 3.7 |
| India | 0.2 | 0.8 | 1.2 | 1.9 |
| Rest of South Asia | 0.2 | 0.8 | 1.4 | 2.7 |
| Middle East and North Africa | 0.0 | 0.2 | 0.4 | 1.0 |
| South Africa | 0.7 | 2.2 | 2.9 | 3.8 |
| Rest of sub-Saharan Africa | 0.2 | 0.9 | 1.7 | 3.4 |
| Carbon tax rate (US$/tCO2) | ||||
|---|---|---|---|---|
| Country/region | 10 | 50 | 100 | 250 |
| Australia and New Zealand | − 0.2 | − 0.7 | − 1.2 | − 2.6 |
| Canada | − 0.1 | − 0.7 | − 1.3 | − 3.1 |
| Germany | 0.0 | − 0.2 | − 0.4 | − 1.1 |
| Spain | 0.0 | − 0.3 | − 0.6 | − 1.4 |
| France | 0.0 | − 0.1 | − 0.2 | − 0.6 |
| UK | 0.0 | − 0.2 | − 0.4 | − 1.0 |
| Italy | − 0.1 | − 0.3 | − 0.6 | − 1.4 |
| Japan | 0.0 | − 0.2 | − 0.5 | − 1.1 |
| EFTA countries and rest of EU | − 0.1 | − 0.4 | − 0.9 | − 2.1 |
| United States | − 0.1 | − 0.5 | − 1.0 | − 2.1 |
| Non-Annex I Europe and Central Asia | 0.0 | 0.2 | 0.3 | 0.4 |
| Argentina | 0.0 | − 0.1 | − 0.1 | − 0.2 |
| Brazil | 0.0 | 0.0 | 0.0 | − 0.1 |
| Rest of Latin America and Caribbean | 0.0 | − 0.1 | − 0.2 | − 0.5 |
| China | 0.0 | 0.2 | 0.3 | 0.6 |
| Indonesia | 0.0 | 0.0 | 0.1 | 0.2 |
| Rest of East Asia and Pacific | 0.0 | 0.2 | 0.3 | 0.5 |
| Malaysia | 0.0 | − 0.1 | − 0.2 | − 0.5 |
| Thailand | 0.0 | 0.2 | 0.3 | 0.4 |
| India | 0.1 | 0.3 | 0.4 | 0.8 |
| Rest of South Asia | 0.0 | 0.1 | 0.2 | 0.4 |
| Middle East and North Africa | − 0.2 | − 0.9 | − 1.6 | − 2.9 |
| South Africa | 0.0 | 0.0 | 0.0 | 0.0 |
| Rest of sub-Saharan Africa | − 0.1 | − 0.5 | − 0.8 | − 1.6 |
| Exports | Imports | |||||||
|---|---|---|---|---|---|---|---|---|
| Carbon tax rate (US$/tCO2) | ||||||||
| Country/region | 10 | 50 | 100 | 250 | 10 | 50 | 100 | 250 |
| Australia and New Zealand | − 0.4 | − 1.5 | − 2.6 | − 5.1 | − 0.1 | − 0.5 | − 0.9 | − 1.7 |
| Canada | − 0.2 | − 1.1 | − 2.0 | − 4.1 | − 0.2 | − 1.1 | − 2.0 | − 4.4 |
| Germany | − 0.2 | − 0.7 | − 1.2 | − 2.5 | − 0.1 | − 0.2 | − 0.5 | − 1.1 |
| Spain | − 0.3 | − 1.4 | − 2.4 | − 4.8 | 0.0 | − 0.2 | − 0.5 | − 1.3 |
| France | − 0.1 | − 0.7 | − 1.3 | − 2.6 | 0.0 | − 0.1 | − 0.3 | − 0.7 |
| UK | − 0.1 | − 0.5 | − 0.9 | − 2.0 | − 0.1 | − 0.3 | − 0.6 | − 1.3 |
| Italy | − 0.2 | − 1.1 | − 1.9 | − 4.0 | − 0.1 | − 0.4 | − 0.7 | − 1.8 |
| Japan | − 0.4 | − 1.5 | − 2.7 | − 5.3 | 0.0 | − 0.2 | − 0.4 | − 1.1 |
| EFTA countries and rest of European Union | − 0.2 | − 1.0 | − 1.9 | − 4.1 | − 0.1 | − 0.6 | − 1.1 | − 2.6 |
| United States | − 0.6 | − 2.5 | − 4.3 | − 8.0 | 0.0 | − 0.1 | − 0.2 | − 0.6 |
| Non-Annex I Europe and Central Asia | 0.0 | 0.0 | 0.0 | − 0.5 | − 0.1 | − 0.3 | − 0.5 | − 1.3 |
| Argentina | 0.2 | 0.9 | 1.6 | 2.8 | − 0.2 | − 0.8 | − 1.3 | − 2.5 |
| Brazil | 0.1 | 0.3 | 0.4 | 0.6 | − 0.2 | − 0.7 | − 1.3 | − 2.7 |
| Rest of Latin America and Caribbean | 0.2 | 1.0 | 1.6 | 2.9 | − 0.2 | − 1.0 | − 1.8 | − 3.3 |
| China | 0.0 | 0.1 | 0.2 | 0.2 | 0.0 | 0.0 | − 0.1 | − 0.4 |
| Indonesia | 0.1 | 0.6 | 0.9 | 1.6 | 0.0 | 0.1 | 0.1 | 0.0 |
| Rest of East Asia and Pacific | 0.0 | 0.1 | 0.2 | 0.0 | 0.0 | 0.1 | 0.1 | 0.0 |
| Malaysia | 0.1 | 0.2 | 0.3 | 0.4 | 0.0 | − 0.2 | − 0.4 | − 0.9 |
| Thailand | 0.0 | 0.1 | 0.2 | 0.1 | 0.1 | 0.1 | 0.2 | − 0.1 |
| India | 0.0 | 0.0 | − 0.1 | − 0.4 | 0.0 | 0.1 | 0.1 | − 0.2 |
| Rest of South Asia | 0.1 | 0.3 | 0.4 | 0.7 | 0.1 | 0.2 | 0.2 | 0.2 |
| Middle East and North Africa | 0.5 | 2.3 | 4.0 | 7.7 | − 0.7 | − 3.0 | − 5.1 | − 9.2 |
| South Africa | 0.0 | − 0.2 | − 0.4 | − 0.8 | − 0.1 | − 0.3 | − 0.4 | − 0.8 |
| Rest of sub-Saharan Africa | 0.2 | 0.9 | 1.5 | 2.6 | − 0.3 | − 1.1 | − 2.0 | − 3.8 |
Acknowledgments
Y.-H. Henry Chen provided research assistance. The author would like to thank two anonymous referees, Florian Landis and David G. Victor for insightful comments. The Knowledge for Change Trust Fund of the World Bank is acknowledged for financial support. The views and findings presented here are those of the author and should not be attributed to the World Bank.
Disclosure statement
No potential conflict of interest was reported by the author.
Notes
1. Since Taiwan is not a UN member, it is not included in the list of “countries” in this paper. It ranks as the 20th largest economy in terms of CO2 emissions in 2010.
2. An in-depth breakdown of the power sector at a technology level would be ideal. Studies such as Chen et al. [Citation21] and Timilsina and Shrestha [Citation22] have done so for single-country CGE models. However, the model used here is a global model using GTAP data [Citation17]. Lack of information prevents us breaking down the electricity sector at the technology level.
3. Note that only data from GTAP have been used here. The CGE model presented here is not a GTAP CGE model. It is a revised/upgraded version of the model presented in Timilsina et al. [Citation16].
4. The authors acknowledge that a more recent version of GTAP data (GTAP 8.0) is available now [Citation17]. The new database presents data for year 2007; the version of the GTAP database used in this analysis uses data for year 2004. Since there would not be much change in the structure of an economy in 3 years; using the new version of data is not expected to alter the results significantly.