تجزیه و تحلیل اقتصادی از یک مسیر کربن پایین تا سال 2050: یک مورد از چین، هند و ژاپن

This article studies the economic implications that different global GHG emission mitigation policies may have in the major Asian economies, namely, China, India, and Japan. The analysis covers the period 2010–2050 and is performed by means of a recursive dynamic computable general equilibrium model (GEM-E3). Four scenarios are investigated: the three standard AME scenarios, and a fourth scenario with a GHG emission reduction path compatible with the 2 °C target, reducing global GHG emissions in 2050 by 50%, relative to 2005. The scenarios are compared with the already adopted and announced policies of the respective countries, in the context of the Copenhagen pledges for 2020 and their long-term objectives in 2050. We further discuss the role of energy efficiency measures and zero-carbon power technologies in order to reach the long-term 2 °C target. We find that postponing significant emission reductions may not accrue an economic benefit over time whereas it may increase some risks by possibly overstretching the reliance on zero-carbon technologies.

The UNFCCC 2009 Copenhagen Accord (UNFCCC, 2009) on climate policy states that deep cuts in global greenhouse gas (GHG) emissions are needed “so as to hold the increase in global temperature below 2 degrees Celsius”. Meeting this 2 °C target will require reducing world GHG emissions by 50% globally in 2050,1 with major transformations in global energy and economic systems. Countries such as the EU, US and Japan have announced or are debating domestic reductions in the range of 80–95% compared to 1990. The EU has recently put forward a roadmap detailing the transition scenario that the EU could follow from now to 2050 in order to reduce its GHG emissions by 80% (European Commission, 2011a and European Commission, 2011b). Achieving a 50% reduction of global GHG emissions by 2050 will require substantial reductions in the major Asian economies as well. This article explores the economic implications of such global transition scenarios for the three largest Asian GHG-emitters' countries2 (China, India and Japan), which are among the top world six largest emitters,3 and which are projected to account for 35% of world GHG emissions in 2050. The assessment has been made in the context of a broader modeling exercise within the Asian Modelling Forum (AME) of the Energy Modelling Forum (EMF) (see Calvin et al., 2011). This article considers four global climate policy scenarios until 2050, with two scenarios compatible with the 2 °C target. All four scenarios assume a single carbon price for the world. The first three scenarios are the ‘standard’ scenarios of the AME: a low, middle and a high carbon price path until 2050, called respectively, the CO2 Price $10 scenario, CO2 Price $30 scenario, and CO2 Price $50 scenario (Calvin et al., 2011). The CO2 Price $50 scenario can reach the 2 °C target. The fourth scenario, called hereafter E1*, is also compatible with the 2 °C target, and is derived from the E1 scenario in the ENSEMBLES project.4 The E1* scenario assumes a 50% reduction of global GHG emissions by 2050 (vs. 2005). This article has two main objectives. Firstly, we compare the emission pathways of the four scenarios with the Copenhagen pledges in 2020 and to which extent the pathway is compatible with a 50% chance of staying below 2 °C warming (IPCC, 2007). Further, we focus on the macroeconomic consequences of the scenarios in 2020 and 2050, assessing the effects on GDP, carbon value and economic sectors, and on the role played by energy efficiency and zero-carbon technologies. The analysis uses the computable general equilibrium (CGE) GEM-E3 global model (Capros et al., in press), which for the purpose of this study includes an energy efficiency module, a bottom-up module for the power generation sector, and the electrification of the transport sector.5 These extensions allow us to better represent the structural shift of the energy sector towards 2050 both in the reference as in the low carbon scenarios. Improvements in energy efficiency may play a key role in attaining ambitious GHG emission reduction targets, representing potentially up to half of the overall reduction in emissions (e.g. Russ et al., 2009). Yet in a CGE model such energy efficiency improvements usually are captured by price-induced factor substitutions and by energy efficiency improvements that are incorporated in the reference, which do not change when a policy is implemented. This version of the GEM-E3 model allows for additional energy efficiency improvements in a policy context with more ambitious climate targets. In particular agents are able to use part of their budget to obtain higher energy productivity, however the decision on the amount of money spent for energy productivity is specified exogenously. As these additional energy efficiency improvements incur a cost, they are not windfall gains. The second extension consists of the integration of a bottom up representation of the power generation sector into the CGE model. The power generation sector has a key role in the overall adjustment towards a less carbon intensive economy. Identifying in a discrete way the different power generation technologies is crucial for a consistent evaluation of the overall energy cost. The deployment of power technologies in GEM-E3 has been calibrated to the results of the PRIMES model and the POLES global energy model for similar scenarios (Dowling and Russ, 2012). Finally, the electrification of the transport sector is expected to play a key role for long-term GHG emissions abatement. Given the current high dependence of transport on oil and the required large reductions in fossil fuel consumption, a major process of electrification of the transport system is necessary. This is modeled in GEM-E3 with an increasing demand of electricity from the transport sector, leading to higher electricity prices, and therefore having economy-wide effects. The article has four main sections, in addition to this introduction. In the next section the main features of the GEM-E3 global model are presented. 3 and 4 detail the assumptions for the reference and the climate scenarios, respectively. Section 5 deals with the main results and their interpretation. Section 6 concludes.

This article explores the economic implications of four GHG emission reduction scenarios to 2050 in the three largest GHG emitters in Asia: China, India and Japan. Those countries will play a determinant role in substantial global GHG reductions by the middle of the century. The world version of GEM-E3, a CGE model, is used to quantify the effects of the following four scenarios: the three standard AME scenarios (with the “high” CO2 Price $50 scenario reaching the 2 °C target) and the E1* scenario that is also compatible with the 2 °C target. The global economy adjusts to GHG emission constraints through the following three mechanisms. The first, model-internal mechanism relates to sectoral and trade effects induced by the introduction of a carbon value. The second mechanism is the deployment of zero-carbon power according to the scenarios derived with the POLES/PRIMES model. Through the introduction of a detailed power sector in GEM-E3, the changes in demand for capital and material resulting from this deployment of zero-carbon technologies are now represented within GEM-E3. The final mechanism is the fixing of increased investment into energy efficiency that would be stimulated in a world with stringent climate policies. The last two mechanisms play a key role when the economy needs to meet very ambitious GHG reductions. They indeed reinforce the consistency of the CGE analysis as demanding carbon mitigation policies have explicit costs on the economy (electricity prices rise and firms need to spend money in order to improve energy efficiency), which are explicitly accounted for in the CGE model. We find that the GHG emission intensities of China and India in our reference are comparable to or lower than their Copenhagen pledges. This suggests that their pledges may not incur any additional effort compared to what would happen anyway, as simulated in the reference scenario. Regarding the climate scenarios, annual world GDP growth for the period between 2005 and 2050 would be between 2.25% under the CO2 Price $50 scenario and 2.32% in the CO2 Price $10 scenario, instead of 2.34% in the reference. China and India would have also a slightly lower growth rate. For instance, China would grow at 4.21% in the E1* scenario, instead of at 4.36% in the reference, while India would grow at 4.39%, instead of 4.59%. The carbon values reach a maximum of 256$/tCO2 for the E1* scenario, while the carbon value is 43 in the CO2 Price $10 scenario. The E1* scenario shows higher emissions than CO2 Price $50 scenario in 2020, which is compensated by a steeper emission decrease in the 2020–2050 period. This steep decrease is not only mirrored by a higher carbon value but also by higher levels of exogenously determined deployment of zero-carbon power technologies and energy efficiency improvements. The carbon budget as well as the GDP growth is comparable over time (until 2050) for the CO2 Price $50 scenario and the E1* scenario. This shows that postponing significant emission reductions may not accrue an economic benefit over time, whereas possibly excessively relying on the deployment of zero-carbon technologies. This may increase the risk that the 2 °C target is not met. Indeed, missing the (possibly cheap) emission reductions in an early stage not only exacerbates the reduction ambitions as such in later periods, but also increases the dependence on other drivers such as zero-carbon technologies in order to reach the needed reductions. However, if emission reductions beyond the Copenhagen pledges start already in an early stage (such as in CO2 Price $50 scenario), then such a high deployment of zero-carbon technologies may not be required, while the GDP levels in 2050 are comparable to those of the E1* scenario. There are several extensions which could improve this analysis. For instance, a vintage specification in the power generation sector and inertia are not considered. Other possible extensions could be a bottom-up approach to transport and electricity and gas networks, which might allow a better modeling of the transport and energy sectors to meet ambitious mitigation policies.