In the next 40 years, China will need to achieve high-quality development under carbon emission constraints. Among the critical challenges China needs to face is the potential for increased imbalances in regional development. This chapter seeks to answer three questions. First, will carbon emission constraints aggravate the imbalance in China’s regional development? Since the 11th Five-Year Plan period (2006–2010), the government has promoted energy conservation and emission reduction through control of energy consumption and intensity. Under energy conservation and emission reduction policies, the gap in GDP per capita between high-carbon, more-developed and low-carbon, less-developed regions has widened to a certain extent. In the future, will the imbalance in regional development intensify as carbon constraints grow? We conducted multi-scenario analysis using a computable general equilibrium (CGE) model, and the findings show that if carbon neutrality is promoted by prioritizing efficiency of emissions reduction, then regional development imbalances may be the exacerbated, creating significant challenges to high-quality development. Second, why do carbon emission constraints exacerbate imbalances in regional development? Answering this question requires an understanding of who bears the major cost of emissions reduction. High-energy-consuming industries in the midstream of the industry chain may bear the highest abatement costs due to their limited bargaining power over the upstream energy sector and downstream consumption sector. High-energy-consuming industries bear more abatement costs at this stage due to their own transformation and upgrading demand and lower marginal abatement costs compared to other industries. As economic development in less-developed regions is more dependent on these industries, the uniform imposition of carbon emission constraints will exacerbate imbalances in regional development. Third, how can imbalances in regional development be eliminated? On one hand, through “dual control” of carbon emission, a carbon market and carbon tax policies, the costs of emission reduction can be more reasonably shared and more equity issues can be considered while pursuing efficiency. On the other hand, a compensation mechanism could smooth the transition and support less-developed, high-carbon regions through transfer payments and transition finance tools. We compared various policy scenarios using the CGE model, and conclude that in the process of achieving carbon neutrality, dual control of carbon emission, will play a major role in sharing the responsibilities of emission reduction more equitably; that transfer payments are the most effective means to eliminate regional disparities; and dynamically determining the inflow of transfer funds according to the progress of the transition will reduce the decline of national GDP and eliminate imbalances in regional development. Transition finance can also promote equity in regional development at the cost of a potential decline in GDP.
Hinweise
Authors: Ji Chen, Wei Nie, Kuan Zhen, Lin Wang, Shuai Wang, Shurui Jiang, Lei Xu.
Common prosperity and carbon neutrality are major national strategies that will affect China’s development. This chapter asks the following questions: Does carbon neutrality further widen the regional development gap and why? How might China build an effective policy system to eliminate imbalances in regional development given the carbon emission constraints?
Our answers to these questions are four-fold. First, through analysis of the current situation, we argue that the cost of emissions reduction varies greatly among China’s province-level regions, and the pursuit of efficient emission reduction alone will bring inequality, and that achieving carbon neutrality may lead to a wider regional development gap. The second section explores the issue of cost allocation for carbon reduction from the perspective of industry cost transmission, and digs into the deeper reasons why carbon emission constraints exacerbate regional imbalance. The third section proposes that in order to prevent carbon emission constraints from exacerbating regional imbalances, it is necessary to establish a policy system for reasonable emission reduction cost sharing and fair compensation transformation. Finally, the CGE model is used to construct different emission reduction scenarios and pathways, and we discuss the policy roles of each stage in emission reduction.
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4.1 High-Quality Development Under Carbon Emission Constraints: Focusing on the Imbalance in Regional Development
4.1.1 Abatement Costs Vary Greatly Among Chinese Province-Level Regions; Pursuit of Efficiency Alone Will Bring Challenges to Fairness
The greenhouse effect generated by carbon emission affects every country on the planet. Although the abatement cost of carbon emission subjects varies among regions, industries, and periods, the unit abatement effect is the same. This means that the most efficient solution for emissions reduction is to let emitters with low abatement costs take on more responsibility for abatement and as far as possible until regions with high abatement costs reach their targets. The total cost is minimized when the marginal abatement costs of each subject is equal.1
The cost of emission reduction is closely related to the level of economic development. Using panel data for 165 countries worldwide for 2000–2014, Liu and Feng found that the marginal cost of emissions reduction is generally highest in developed countries.2 The Intergovernmental Panel on Climate Change (IPCC) and OECD studies conclude that the cost of emission reduction in less developed regions is usually lower than in developed regions.3 There are four main reasons. Firstly, that energy use in less developed regions is often lower and economic cost is higher in developed regions because the technology is more advanced and there is less room to reduce carbon emission or reduce production activities. Less developed regions tend to have less advanced technology and are less efficient energy users. They can achieve synergy between efficiency and increased production, while developed regions have higher technology levels and less room to further reduce carbon emission, or they even need to reduce production activities, which is more economically costly.4 Secondly, there is a scale effect in reducing carbon emission; the higher the level or intensity of carbon emission, the more room for emission reduction and the smaller the marginal cost of emission reduction.5 Thirdly, less developed regions tend to have a higher share of fossil energy consumption, and the cost of emission reduction through energy substitution is low. Developed regions have a higher share of clean energy consumption, and further emission reduction may require an adjustment to output.6 Finally, less developed regions have a higher share of secondary production, while developed regions have a higher share of tertiary production, and the former has a relatively lower cost of emission reduction.7
There are differences in economic development, industrial systems, and energy structures between China’s province-level regions, and carbon emission vary among the regions. In 2019, the difference between the Ningxia Hui Autonomous Region, the region with the highest carbon emission intensity in China, and the Tibet Autonomous Region, the lowest, was 120 times. Ningxia’s carbon emission is about 20 times that of developed low-carbon regions such as the municipalities of Beijing and Shanghai.8 Differences in economic development cause greater differences in abatement costs between regions, with research suggesting that marginal abatement costs are low and are rising relatively slowly in regions with low levels of economic development such as Ningxia, Xinjiang, Liaoning, Inner Mongolia, and Shanxi, while marginal abatement costs are higher and rising faster in Beijing, Tianjin, Guangdong, and Henan. In the efficiency of emission reduction-first scenario, regions with low marginal abatement costs will be first to act, and their marginal abatement costs will rise with the amount of abatement until they reach the level of regions with high abatement costs. Before abatement costs are caught up, regions with high marginal abatement costs are less constrained by carbon abatement and may increase their emissions and production at early stages of abatement due to higher output per unit of carbon emission. The uneven responsibility for emission reduction will exacerbate the regional development gap, to a certain extent.
In fact, from the very beginning of its energy conservation and emission reduction policy, China has incorporated considerations relating to regional equity. Since 2006, the government has updated its provincial energy consumption intensity reduction or carbon emission intensity reduction targets every five years. The targets are set by considering the “development stage, resource endowment, strategic positioning, ecological and environmental protection” of each province-level region, and the energy consumption intensity and carbon intensity reduction targets of 31 administrative regions are graded. Comparing regional emissions reduction targets for the 13th Five-Year Plan (FYP) period with the marginal emission reduction costs of each region,9 it is clear that the responsibility sharing scheme does not make efficiency the primary consideration, which influences regions with lower emissions reduction costs to further reduce emission. Currently, the policy allows regions with higher emission reduction costs but stronger economic capacity to take on more emission reduction responsibilities, reflecting a degree of equity (Fig. 4.1).
A bar graph compares the carbon intensity reduction targets and the marginal cost of carbon reduction in 31 provinces in China. The carbon intensity reduction target is the highest in 8 provinces including Beijing, Tianjin, Hebei, Shanghai, Jiangsu, Zhejiang, Shandong, and Guangdong.
Fig. 4.1
A comparison of carbon intensity reduction targets and emission reduction costs by region in the 13th Five-Year Plan.
Source State Council, 13th Five-Year Plan for Controlling Greenhouse Gas Emissions. Zhao Qiaozhi and Yan Qingyou, Spatial evolution trajectory of marginal CO2 abatement costs in Chinese provinces Statistics and Decision Making, Vol. 14, 2019. CICC Global Institute
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However, the equity considerations of the current policy have not reversed the trend of greater negative impacts on high-carbon, less developed regions. Our comparative analysis of GDP per capita in high-carbon and low-carbon less developed regions finds that since the implementation of energy and carbon emission control policies, the gap between GDP per capita in high-carbon less developed regions and less developed regions has started to widen, which shows that energy constraints and carbon emission constraints still exacerbate the uneven development between regions (Fig. 4.2).
A declining line graph highlights the following points. In 2006, it highlights that the eleventh F Y P identifies the energy intensity reduction targets. In 2011, it highlights that the twelfth F Y P identifies the carbon intensity reduction.
Fig. 4.2
Gap in GDP per capita between high-carbon, less developed regions and less developed regions in China (1998–2020). Note Based on 2004 carbon emission intensity and GDP per capita, province-level regions are divided into developed, high-carbon less developed and less developed regions. High-carbon less developed regions include Shanxi, Anhui, Henan, Sichuan, Guizhou, Shaanxi, Gansu, Qinghai, Ningxia, and Xinjiang, while less developed regions include Jiangxi, Hunan, Guangxi, Hainan, Chongqing, Yunnan, and Tibet; GDP at constant 1998 prices.
Source China Statistical Yearbook, Carbon Emission Accounts & Datasets (CEADs), CICC Global Institute
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4.1.2 The Carbon Constraint Will Become Tight Under the Carbon Neutral Strategy, and the Problem of Unbalanced Regional Economic Development May Intensify
Looking ahead, will imbalances in regional development continue to intensify as China’s carbon emission constraints strengthen? We conducted multi-scenario analysis using a CGE model. The results show that if carbon neutrality is promoted by prioritizing efficiency of emission reduction, it may bring serious regional development imbalances to China and pose a great challenge to high-quality development.
In our baseline scenario, we assume higher future growth rates in regions with lower GDP per capita and a gradual reduction in the gap between less developed and developed regions. The Gini coefficient of the province-level regions’ GDP per capita gradually decreases from 0.19 in 2020 to 0.08 in 2060. However, due to the absence of carbon emission controls, carbon emission will not reach the peak of 13.3bn tonnes until around 2040, after which they slowly decrease to 12.5bn tonnes in 2060, which is higher than the current level. Compared with our baseline scenario, our optimal efficiency scenario leads to uneven development across regions, and the degree of unevenness is more pronounced after the rapid reduction phase in 2030.
Specifically, the Gini coefficient of GDP per capita under our optimal efficiency scenario is consistently higher than that of our baseline scenario, implying more inequitable regional economic development and more pronounced inequality in development in terms of per-capita income and per-capita consumption. In addition, we expect carbon emission constraints to reduce China’s GDP by 1% in 2030 and 10% in 2060 under our optimal efficiency scenario compared to our baseline scenario (Fig. 4.3).
2 line graphs. Left. It plots the declining Gini coefficients for B A U and C T N from 2020 to 2060. Right. It plots the increasing aggregate G D P for B A U and C T N from 2020 to 2060.
Fig. 4.3
Simulation of Gini coefficient of GDP per capita and total GDP under our baseline scenario and the optimal efficiency scenario of emission reduction. Note BAU (business as usual) indicates the no carbon reduction development scenario and CTN (carbon trading national) is the carbon reduction efficiency first scenario.
Source CICC Global Institute
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By region, the decline in GDP per capita is greater in less developed province-level regions than in developed province-level regions under our optimal efficiency scenario, implying that the pursuit of efficiency in emission reduction alone will result in more severe negative impacts on development in less developed regions. Specifically, compared to our baseline scenario, less developed regions such as Tibet, Yunnan, Henan, and Jiangxi have larger declines in GDP per capita in 2060 in our optimal efficiency scenario, generally exceeding 15%, while more developed regions such as Shanghai, Guangdong, and Zhejiang have smaller declines in GDP per capita that do not exceed 1% (Fig. 4.4).
A negative bar graph plots the changes in per capita G D P in 31 provinces in China. The decline in G D P is the highest in Tibet and the lowest in Guangdong and Zhejiang.
Fig. 4.4
Simulated difference of decline in GDP per capita between the baseline and optimal efficiency scenarios.
Source CICC Global Institute
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4.2 Carbon Emission Constraints Exacerbate Regional Imbalances: Who Is Bearing the Cost of Abatement?
From the above analysis, it is clear that China’s less developed regions, with their heavy industrial structure, high carbon intensity, and low marginal abatement costs, may need to bear more responsibility for emission reduction. However, it is important to note that most of the energy-intensive industrial products produced in these less developed regions are not for local consumption but are sold to more developed regions or exported abroad. Can the costs of reducing the emission of the production process be passed onto the end-consumer? We explore which industries and regions will carry more of the costs of emission reduction from the perspective of industry chain cost transmission.
4.2.1 China’s High-Energy-Consuming Industries Have Weak Cost Pass-through Capabilities, and They May Bear Most of the Cost of Emission Reduction
Generally speaking, the cost of carbon emission reduction is first shared by the production side and then passed to the downstream consumption side. Some supply chains have insufficient pass-through capacity, which may result in uneven cost sharing. Therefore, the initial sharing of emission reduction responsibilities and the cost pass-through capacity of the industry chain will affect the final distribution of carbon reduction costs.
The ability of an industry to pass on costs mainly depends on factors such as market supply and demand, industry concentration, and government price controls. When industry concentration is high and supply is tight, the bargaining power to the downstream is higher. Focusing on high-carbon industries, energy sectors such as coal, oil, and electricity are in the upstream of the industrial chain, while energy-intensive industrial sectors such as chemicals, iron and steel, non-ferrous metals, and building materials are mostly in the midstream. We measured the cost transmission capacity index of each industry during 2016–2019 with reference to the analysis framework of Wu et al. [14],10 and find that the cost pass-through capacity of coal and oil mining industries in the upstream is substantially higher than that of the midstream energy-intensive industrial sectors (Fig. 4.5).
A bar graph compares the cost conductivity index in 42 industries. The index is the highest for oil and gas extraction and the lowest for transportation and postal services.
Fig. 4.5
Cost conductivity index by industry for the period 2016–2019. Note Cost pass-through capacity is the downward transmission capacity of costs, measured by the price increase/cost increase in a certain period of time.
Source 2018 Annual China Input–Output Tables, National Bureau of Statistics, CICC Global Institute
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The upstream energy sector has a relatively smooth cost pass-through to the midstream industrial sector. Looking at the power industry as an example, in terms of supply and demand, power has been in “tight balance” in recent years. This is because, on one hand, the vast majority of renewable energy in the clean transition needs to be used by the end-user as electricity, instead of electricity generated from fossil fuels, and these alternative scenarios continue to push up power demand. On the other hand, data centers, 5G-base stations, and other new areas of high-power consumption have emerged, meaning that the power consumption elasticity coefficient has rebounded in recent years, reflecting increased reliance on electricity for economic growth. In terms of industry concentration, China’s two major power grid companies cover most of the country’s electricity supply, making the industry highly concentrated. In terms of price diversion, as market-oriented reforms in the energy sector such as for electricity and oil and gas are advanced, the pass-through of energy prices to the middle and lower reaches will be smoother, which will facilitate the pass-through of more carbon emission reduction costs in the energy sector to the middle and lower reaches.
The midstream industrial sector has weak cost pass-through capability and will face carbon reduction costs. Considering China’s current industrial structure and economic development, it is difficult for midstream energy-consuming industries to pass on costs to the downstream consumption side. In the steel and cement industries, as the peak of urbanization and industrialization has passed, the demand for crude steel, cement, and other building materials is low, and the capacity utilization rate of cement went much less in recent years, reflecting obvious excess capacity. At the same time, cement, steel, and other products face competition in import and export trade, and with excess capacity, the capacity to transfer cost to the downstream is even lower, facing the dilemma of squeezed profits. In other words, although the carbon cost is initially imposed on the production side, theoretically, it can be transferred to the consumption side through the industrial chain. However, under the current industrial structure and supply and demand environment, a large amount of carbon cost will be silted up in the midstream of energy-consuming supply chains.
4.2.2 High-Carbon Industries Should Bear More Abatement Costs, but the Distribution Is Unequal
Freely passing on carbon cost will accelerate the transformation and upgrading of high-energy-consuming industries, which are seeing sluggish growth. It is foreseeable that under the dual control of energy consumption (through a trading market and carbon tax), higher electricity costs, the approaching launch of a carbon market, and other emission reduction pressures, high-energy-consuming industries will accelerate the elimination of excess capacity and inefficient technologies, and will enhance industrial concentration.
Leading enterprises compete for internal advantages in their industries by reducing energy consumption and technology upgrades, which leads to higher profit margins. Middle-tier enterprises will face a more serious squeeze from both upstream and downstream, and carbon emission constraints may be implemented to cut down outputs, reduce emissions, and purchase carbon quotas, among other measures, resulting in reduced profit margins. Enterprises at the tail-end of industry because of the outdated capacity will be forced out. This is in line with the dual logic of industrial optimization and upgrading and promoting carbon emission reduction.
Differences in the supply and demand environment and the pattern of competition of each industry cause uneven carbon cost pass-through from the upstream to downstream of the industrial chain, while differences in industrial structure of different regions will cause uneven sharing of carbon reduction costs among regions. In terms of absolute amounts, regions with high added value from high energy-consuming manufacturing industries, such as Shandong, Jiangsu, and Guangdong, will bear higher carbon reduction costs. Meanwhile, in terms of capacity to bear costs, Hebei, Ningxia, Jiangxi, Henan, and Shandong have high added value from high energy-consuming manufacturing industries as a proportion of regional GDP and are less able to cover any cost (Fig. 4.6). Therefore, it is necessary to consider the absolute amount of costs borne and affordability, among other factors.
A bar and line graph compares the value added by high energy-intensive manufacturing industries in 31 provinces in China and their respective energy-intensive manufacturing share of G D P. The value added is the highest for Shangdong and the share of G D P is the highest for Hebei.
Fig. 4.6
Value added by high energy-consuming manufacturing industries by region and share of regional GDP.
Source China Carbon Accounting Database, CICC Global Institute
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4.3 Building an Effective Policy System: Reasonable Sharing of Costs and Fair Compensation for Green Transformation
Under the carbon constraints, high-energy-consuming industries bear most of the abatement costs, resulting in regions with more concentrated high-carbon industries bearing greater abatement costs, thus further aggravating the imbalance in regional development. However, from the perspective of efficiency, greater emission reductions in high-carbon industries are conducive to solving the problem of overcapacity and promoting technological innovation in existing capacity. From the dimension of marginal abatement costs, high energy-consuming industries that take on more emission reduction tasks can reduce overall abatement costs nationwide. Can a policy system effectively balance equity in inter-regional development and efficiency?
We believe that an effective policy system should include two aspects. First, reasonable distribution of costs. Considering that no policy can be considered completely reasonable, our analysis focuses on how to consider equity in the implementation of cost sharing policies. The second aspect is compensation for just transition, compared to reflecting equity through cost sharing policy tools. The policy tools of equitable compensation can play a greater role in mitigating or even avoiding the widening of regional disparities under the carbon emission constraints.
4.3.1 Reasonable Cost-Sharing Policy Tools
4.3.1.1 Dual Control Over Carbon Emission
The current dual control policy on carbon emissions benefits low-income and high-emission areas, to a certain extent, when allocating the responsibility for emission reduction to regions. In the future, the allocation of carbon emission reduction might be further optimized, and the carbon emission constraints on high-emission industries should be maintained. Moreover, more sectors should be allowed to bear a larger share of the cost of emission reduction. For example, the EU allocates carbon credits11 to three sectors—power generation, energy-intensive industries, and others, mainly residential and transportation—and the sectors allocate carbon credits of their respective sectors among member states. The essential difference between China’s and the EU’s allocation of carbon emission rights is that China allocates carbon emission rights to the regions first, then the regions allocate the credit to the industry sectors (by giving them to large enterprises). The EU directly allocates carbon emission rights to the sectors, and the rights are then allocated within the sectors and finally, to localities.
In China, after being assigned targets to reduce management difficulties, the regions often further decompose the targets to large-scale enterprises with heavy energy consumption or carbon emission. For example, in 2011, the National Development and Reform Commission (NDRC) launched the Implementation Plan for the Energy Saving and Low Carbon Action of Ten Thousand Enterprises, which requires the participation of enterprises with an annual energy consumption of more than 10,000 tonnes of standard coal. These enterprises tend to be concentrated in a few high-energy-consuming industries. In China, the marginal cost of emission reduction in these industries is relatively low and the cost of supervision and management is also relatively low because the industries are large enterprises. Therefore, China’s dual energy consumption control system, in practice, tends to allow large enterprises in high-energy-consuming industries to undertake emission reduction tasks.
4.3.1.2 Emissions Trading Market
The responsibility for carbon emission reduction is achieved through the initial allocation of carbon quotas. China launched a national carbon market in July 2021, starting with the power industry, with subsequent plans to include more high-carbon emission industries such as steel, construction materials, petrochemicals, non-ferrous metals, paper, and aviation. As more industries are included, the market will face the problem of rational allocation of carbon quotas among multiple industries. There are complex production relationships among different industries, and there are large differences in technology levels, emission reduction potential, and energy consumption intensity, among others. The distribution of emission reduction responsibilities among industries will have an impact on the balanced development, transformation, and upgrading of related industries. With reference to the operational experience of foreign carbon markets and the research of domestic and foreign academics, factors to be considered in sharing emission reduction responsibilities among industries mainly include efficiency, responsibility, capacity, and potential of emission reduction, as well as the impact on national or regional industrial structure and economic development.
Efficiency in emission reduction: If the “green premium”, i.e., the premium in choosing zero carbon substitution over traditional technologies, is used as an indicator to characterize the cost of emission reduction in different industries, the cost of emissions reduction varies greatly. If efficiency is pursued, i.e., the total emission reduction cost of each industry is minimized, the non-ferrous and petrochemical industries, which have a lower green premium, need to take more responsibility for emission reduction. However, if quota allocation is based on this strategy, there is a risk of “whipping the lead cow,” which punishes the best-performing sector and is not conducive to technological progress in other industries where emission reduction is more complex.
Responsibility for and capacity of emission reduction: Generally, the current level of carbon emission (or the cumulative amount of carbon emissions in a certain historical period) is used to characterize the level of responsibility for emission reduction of an industry, and the value added of the industry is used to measure its emission reduction capacity. In terms of responsibility, the EU’s principle of free allocation of allowances takes into account cumulative emissions within a historical period, and industries with high historical emissions assume greater responsibility for reduction. In terms of capacity, if based on the principle of vertical equity, industries with higher output value, i.e., higher capacity, assume more responsibility for emission reductions and pay more economic costs. When apportioning responsibility, the responsibility and capacity of the industry can be taken into account, and the responsibility and capacity of industries with high emissions and high value added will be matched and will moderately increase the pressure from emission reduction.
Emission reduction potential: There are large differences in the potential for carbon intensity reductions in different industries. Some industries are close to the global, advanced level of energy intensity and face a technological ceiling, with little room for further reduction. Some industries see a large gap between domestic and global levels of energy intensity and, and have large potential for emission reduction. For industries with greater potential for emission reduction, quotas can be reduced accordingly to stimulate the adoption of existing advanced technologies for emission reductions and upgrading.
Industry synergy: In addition to factors such as efficiency in, responsibility for, and capacity for emission reduction, the impact of allocation of carbon allowance on the coordinated development of industry is an essential consideration. Looking at the EU experience as an example, policymakers believed that the power sector was more efficient in reducing emissions and had a higher capacity to transfer carbon costs to end-users, and hence favored the industrial sector in the allocation of free allowances, which eventually led to an overburdened power sector and weaker incentive for the industrial sector to reduce emissions. Later, a “cross-industry correction factor” was added to dynamically adjust the allowance allocation mechanism based on changes in efficiency, responsibility, capacity, and trade in each industry.
4.3.1.3 Carbon Tax
Carbon taxes mainly adopt price interventions to guide the tax subject to optimize production and operation methods to reduce carbon emissions.12 If the tax rate is too high, it will lead to an excessive cost burden on enterprises, which would in turn have a negative impact on their competitiveness and regional economic and social development. If the tax rate is too low, it may lead to an inability to complete the task of carbon emission reductions and a loss of efficiency. Considering the reality that the marginal cost of carbon emission reduction varies greatly across China, a question concerning the balance between equity and efficiency is, if China levies a carbon tax in the future, should the tax rate be set uniformly across the country or vary across regions?
A flat tax rate theoretically gives a uniform carbon price across the country, and regions with large total carbon emissions will bear more of the abatement costs. Compared with a differentiated tax rate, a uniform tax rate achieves a larger scale of emission reduction, i.e., greater efficiency of emission reduction. A differentiated tax rate can account for factors such as carbon emission, abatement costs, and tax capacity of different regions and industries, which is more feasible and focuses more on equity. At present, China’s relatively mature environment-based tax system mainly reflects the idea of differentiated tax rate design. Environmental protection tax was formally introduced by the central government in January 2018 to delineate a uniform tax band and implement differentiated tax rates in each region (Table 4.1). The environmental protection tax fully reflects the characteristics of differentiated taxation, especially the large difference in tax between developed and less developed regions, which can effectively alleviate the problem of equitable development between regions due to taxation.
Table 4.1
Current status of environmental protection tax in China
Rates for air pollution are Rmb1.80–6.00 per equivalent value
Rates for water pollution are Rmb2.10–3.50 per equivalent value
High tax rate
Beijing, Tianjin, Hebei, Shanghai, Jiangsu, Henan
Rates for air pollution are Rmb4.80–12.00 per equivalent value
Rates for water pollution are Rmb4.80–14.00 per equivalent value
Source: Tang and Ming et al., Ministry of Ecology and Environment, CICC Global Institute
4.3.2 Policy Tools for Equitable Compensation for Green Transformation
4.3.2.1 Transfer of Payments
High-carbon industries subject to carbon13 emission constraints will force the regions where they are located to face the substantial challenge of economic transformation. For regions that are highly dependent on high-carbon industries, this challenge will be reflected more notably in local fiscal revenues (Fig. 4.7). Looking at resource tax as an example, the share of resource tax revenue in local public finance was substantially higher in resource-dependent regions in 2020. Within some heavily resource-dependent regions, the ratio is more than 20%. In Shanxi province, which has the highest proportion of resource tax collection in China, the coal and coke industry’s proportion of total tax revenue in 2020 peaked at 44.6%.14 However, in the process of economic transformation, local public finance needs to play an important supporting role due to large initial investments, long return cycle, and low initial return rate in the development of new industries. In addition, the high levels of unemployment in the transition process create a need for fiscal support in providing basic security and necessary expenditures such as retraining. In short, areas in transition and under carbon emission constraints will face a double challenge of declining tax revenue and increasing expenditures. Transfer payments from the central government are the most effective way to help the local green transformation, which also reflects fair compensation for high-carbon regions.
A bar and line graph compares the local government revenue from resource taxes in 31 provinces in China and their respective share of the total local government revenue. Both are the highest in Shanxi and the lowest in Jiangsu and Shanghai.
Fig. 4.7
Resource tax and its proportion in local fiscal revenue in 2020.
Source National Bureau of Statistics, CICC Global Institute
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Transfer payments for achieving carbon neutrality should promote the just transition of regions: These can help the introduction and development of new industries, and reduce the negative social and economic impacts of the transformation of traditional industries. China currently focuses on general transfers and special transfers. General transfers do not specify how funds should be used, adding flexibility and autonomy to local financing. Special transfers are used for specific projects and are earmarked for specific purposes, effectively avoiding local governments’ preference for economic performance and providing more financial efficiency in environmental protection and social habitat. Although China’s transfer payment system is relatively comprehensive, the transfer payment mechanism directly related to carbon neutrality has not yet been put into practice. The area of energy conservation and environmental protection is dominated by special transfer payments, but these payments do not take carbon neutrality into consideration. The special transfer payments for ecological and environmental protection have three aspects—subsidies for energy-saving and emission reduction, special funds for clean energy development, and transfer funds for ecological and environmental protection—which aim to address ecological and environmental governance and sustainable energy use in a targeted manner and have a limited role in alleviating regional inequalities caused by carbon emission constraints.
4.3.2.2 Transition Finance
Another way to fairly compensate high-carbon industries is to vigorously implement transition finance. Just as green finance focuses on providing financial support to green projects, transition finance focuses specifically on providing preferential financial services for the economic and social impacts of the transition. In recent years, the concept of transition finance has gained international attention and has focused primarily on giving previously high-carbon companies in low-carbon transition the financial support necessary to help them better access the necessary resources and avoid the formation of excessive stranded and non-performing assets. Research has shown that too rapid a curtailment of normal funding for traditional energy-intensive and high-carbon industries can lead to difficulties in accessing the resources necessary for technological innovation and transformation and upgrading.15 The EU, the Climate Bonds Initiative (CBI), and the International Capital Markets Association (ICMA) have published reports, recommendations, and framework principles on transition finance. Domestically, Bank of China and China Construction Bank have developed and shared their perceptions on and approaches to classifying transformation bonds.16
As mentioned, the cost of carbon abatement in China is mainly borne by high energy-consuming industries, and the main task of transition finance is to support these industries, which bear most of the abatement costs, to provide a fair transition opportunity. Financial support specifically includes bonds and preferential monetary policies, e.g., targeted RRR cuts and targeted refinancing, in the form of low-cost capital for local financial institutions, thereby reducing the cost of financing for local economic development and meeting capital needs.
Compared with fiscal transfers, the advantage of using the support policies of transition finance is the allocation of funds in a market-oriented manner, allowing financial institutions rather than the government to select projects and provide support. Meanwhile, enterprises and individuals that are willing and able can apply for credit from financial institutions. As a result, the market can spontaneously match the supply and demand and reduce intervention in the market. It is worth noting that in the process of implementing transition finance, a balance should be kept between supporting transformation and preventing “greenwashing”. Efforts should be made to avoid situations in which financial support is a mere formality. To this end, it is necessary to further standardize the entry criteria and information disclosure system for transition finance support projects, and to establish a green project supervision system that combines regular self-inspection by commercial banking institutions as well as verification and random inspection by regulators.
4.4 Policy Actors in Different Stages of Emission Reduction
If a policy system that balances emissions reduction and development equity is established, will China achieve high-quality development under the carbon emission constraints? What is the cost of economic development in this process? What are the roles of the various policy instruments? To answer these questions, we use the CGE model17 to analyze eight policy scenarios, including a baseline scenario without carbon reduction that achieves high-quality development without carbon emission constraints; a carbon reduction efficiency priority scenario that pursues carbon reduction efficiency without equity; a carbon market scenario, in which power and high energy-consuming industries are included in the carbon market; a carbon market and carbon tax scenario, in which high power- and energy-consuming industries are included in the carbon market and other industries are subject to a uniform carbon tax; a carbon emissions double control scenario; a carbon transfer scenario, which gives transfer payments to high-carbon and low-income regions; a dynamic transfer scenario, which is based on the carbon transfer scenario; and a transition finance scenario, which provides financial support for the transformation of high-carbon and low-income regions.
Achieving carbon neutrality involves three stages.
Carbon peak stage (before 2030): Before achieving carbon neutrality, the main goal of carbon emission policy is to achieve peak carbon emissions. Total carbon emission before the peak will grow, but the growth rate decreases as the peak approaches, so the carbon emission constraints on economic development will go through a weak and gradually strengthening process.
Rapid emissions reduction stage (2030–2045): The greatest constraint on economic development is imposed in this phase, and the strength of the constraint is accelerated because decarbonization technology needs to be deployed on a large scale and the related investment needs to be strengthened continuously. Industries related to traditional energy sources also need to accelerate the transformation, and the contribution to economic development is gradually weakened.
Deep decarbonization stage (2045–2060): Innovative decarbonization technology and its related industries have matured, and large-scale deployment is complete or nearly complete, the degree of decoupling between economic development and carbon emission everywhere is accelerated and completed, and the carbon constraint gradually weakens.
We have estimated the Gini coefficient and lost GDP in eight scenarios of the three stages: Peak carbon, rapid emission reduction, and deep decarbonization (Figs. 4.8 and 4.9). Based on our results, we explore the role of each policy instrument at different stages in emissions reduction. The dual control of carbon emission plays an important role in the reasonable sharing of responsibility for emission reduction. In the dual carbon emission control scenario, we keep the inter-provincial decomposition of carbon emission intensity reduction targets implemented since the 13th FYP period to 2060 and divide China’s regions into five types. The rate of reduction of carbon emission intensity for each grouping will be increased in phases over 2015–2034, 2035–2044, and 2045–2060.18 Overall, this upholds equity in sharing emission reduction among regions, allowing regions with lower emission intensity but better economic conditions to take on more intensity reduction targets. In terms of the per-capita GDP Gini coefficient between regions, the decline seen in the dual control carbon emission scenario is similar to that of the other scenarios during the carbon peaking phase, and all scenarios show a faster decline, which indicates that the difference in the effect of regional emission reduction efficiency and development equity among policies cannot be clearly reflected due to the relatively low pressure of carbon emission reduction. This indicates that the difference in the effect of regional efficiency in emission reduction and development equity among policies is not obvious due to the relatively low pressure of carbon reduction. The Gini coefficient curve is notably lower than that of the other scenarios. In the deep decarbonization stage, the inter-provincial development gap of the dual control scenario gradually approaches that of the other scenarios, which reflects that the decoupling of economic development and carbon emission in each province-level region is strengthened, and the effect of the “double carbon” policy intervention is gradually weakened.
A multiline graph plots the carbon emissions and the Gini coefficients per capita G D P for B A U, C T N, C T N Market, C T N Tax, P C I, P C I Finance, P C I Transfer, and P C I Transfer Dynamics. All the curves plot a declining trend.
Fig. 4.8
Carbon neutral emissions pathways and development equity. Note In this chart, the BAU indicates the no emission reduction development scenario, CTN indicates the carbon reduction efficiency first scenario, CTN-market indicates the carbon market scenario, CTN-tax indicates the carbon tax scenario, PCI indicates dual control scenario of carbon emission and intensity, PCI-transfer indicates the direct transfer payments scenario, and finally PCI-transfer-dynamics indicates the dynamic transfer payments scenario.
Source CICC Global Institute
A bar and line graph compares the G D P and the G D P losses for B A U, C T N, C T N Market, C T N Tax, P C I, P C I Finance, P C I Transfer, and P C I Transfer Dynamics from 2020 to 2060. The G D P for all the scenarios increase over the years whereas the G D P losses are different for different scenarios.
Fig. 4.9
Comparison of economic development and lost GDP by scenario.19
Source CICC Global Institute
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The role of carbon markets in curbing development imbalances between regions will be gradually strengthened in the middle and late stages of carbon neutrality. In the peak carbon stage, due to the less emission reduction constraint and strength, the gap between the dual control policy, which emphasizes equity, and the carbon pricing policy, which emphasizes efficiency, on development equity is barely visible. In the rapid emission reduction stage, the gap between the carbon pricing policy and the dual control policy on equity gradually widens. In the deep emission reduction stage, China has largely achieved transformation of its industrial structure, and the goals of carbon emission and development tend to be decoupled, so the impact of the two emission reduction tools on development equity between regions converges. At this stage, as the total amount of carbon emission around the country would already be small, finding lower-cost emission reduction technologies will become a major task. Meanwhile, the carbon market, a softer and more precise market-based instrument, should play a greater role than the cruder administrative instrument of dual control of carbon emission.
Differentiated carbon tax policies have the potential to curb the increase in regional imbalances under the carbon emission constraints. In the carbon tax scenario, we assume that the carbon tax policy will start to be implemented and will play an abatement role when the carbon market has reached a more mature stage of operation after 2030. Looking at countries that have imposed carbon taxes, rates range from about Rmb80–800/tonne of carbon, with a common practice of initially setting a lower rate and gradually increasing it. We suggest the following rates: US$100/tonne for 2030–2034, US$300/tonne for 2035–2044, and US$500/tonne for 2045–2060. From the model’s output, none of the inter-region GDP per capita Gini coefficients decrease at a rate as pronounced as the other scenarios. The uniform carbon tax does not demonstrate fairness. It can be seen that if a one-size-fits-all non-differential tax rate is applied, the same pressure to reduce emission is applied to all non-electricity and energy-intensive industries such as construction, transportation, and other services. Therefore, a superimposed non-discriminatory carbon tax would further widen the regional development gap, making it difficult to play a role in balancing emission reduction and equity. China’s carbon tax policy has yet to be introduced, and the design criteria of environmental tax can be referred to set regional differentiated tax rates in the future.
The equitable compensation effect of transition finance gradually emerges in the middle and late stages of the carbon neutrality process, as the model shows. We test the effect of targeted transition finance policy support through a CGE model based on differentiated provincial carbon intensity targets and reduced financing rates for less developed regions.20 The results show that by providing low-cost financing for the transition of less developed regions which rely on traditional fossil fuel energy, the Gini coefficient of per capita GDP decreases more substantially between regions in the “transition finance scenario” after 2040, indicating more equitable regional economic development outcomes. It is worth noting that although the effect of targeted financial support only becomes visible after 2040, the financial policies should still be implemented upfront. There are two reasons for this. First, to alleviate the local initial resistance to green transformation and to allow the low-carbon transformation to start as soon as possible. Second, the goal of targeted financial support is to enable local governments to invest in technological transformation and upgrading as well as infrastructure renovation at low cost, among others, and to accumulate fixed capital, which takes time to accumulate, e.g., construction cycle and patent audit. Usually, the process has a time lag in its effect on economic growth. In addition, according to the model, the GDP drag in the financial policy scenario is smaller than that in the carbon emission reduction dual control scenario, where the latter GDP is 0.02% higher than the former in 2020 and the gap widens to 4.15% in 2060. Therefore, giving more financial support to some of the less developed regions that are traditionally resource-dependent can have a substantial effect on alleviating social inequality during the green transition, without compromising the efficiency of economic development.
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The actual determination of carbon reduction targets varies in the specifics determined in different segments. For example, the power industry determines the growth rate of power generation. To facilitate readers’ understanding, we unify the simplified expression as carbon emission rights.
We use the CGE model of Prof. Can Wang and Dr. Shihui Zhang’s team in the School of Environment, Tsinghua University, to construct all scenario analyses in this chapter. The model is a quantitative simulation system based on general equilibrium theory, macroeconomic structural relationships, and national accounting data to describe the operation of economic systems, and it has become a standard modeling tool for global macroeconomic and environmental policy analysis. Specifically, the model used in this paper chooses 2017 as the base year and includes 31 administrative regions (excluding Hong Kong SAR, Macao SAR, and the Taiwan region of China, due to data limitations) and 11 sectors (agriculture, coal, crude oil, mining, natural gas, electricity, high energy-consuming manufacturing, other manufacturing, construction, transportation, and services). The main data sources include: (1) Social accounting matrix, constructed based on the 2017 Chinese multi-regional input–output tables in the CEADs database; (2) exogenously given elasticities of substitution, including elasticities of substitution in the production function and in the utility function, from existing studies; and (3) energy consumption and carbon emissions data, using the 2017 energy consumption and carbon by industry by province-level region in the CEADs database emissions data from CEADs database as a benchmark. Detailed information of this CGE model can be found at http://cheer.nsccwx.cn.
Group I (Beijing, Tianjin, Hebei, Shanghai, Jiangsu, Zhejiang, Shandong) had an annual decrease in carbon emissions intensity of 4.5, 5.5, and 8.2%; Group II (Fujian, Jiangxi, Henan, Hubei, Chongqing, Sichuan) had an annual decrease in carbon emissions intensity of 4, 6.2, and 7.8%; Group III (Shanxi, Liaoning, Jilin, Anhui, Hunan, Guizhou, Yunnan, Shaanxi) had an annual decrease in carbon emissions intensity of 3.8, 4.6, and 7.1%. The annual decrease rate of carbon emission intensity of the fourth group (Inner Mongolia, Heilongjiang, Guangxi, Gansu, Ningxia) is 3.5, 4.4, and 6.5%, and the annual decrease rate of carbon emission intensity of the fifth group (Hainan, Tibet, Qinghai, Xinjiang) is 3, 3.7, and 5.1%.
The initial interest rate in China is estimated to be about 4.5% in 2022 and the natural rate is about 1.6% in 2060. Assuming that China finances less developed regions with green transformation at the refinancing rate for supporting agriculture and small-scale loans (about 2%, which is about 2.5 ppt lower than the market rate), and considering the gradual successful transformation of the less developed regions, the gap between the interest rate in less developed regions and the normal market rate will gradually converge, we set preferential financing rates for less developed regions in the model in three time intervals: 2022–2030 rates for less developed regions are 2% lower than other regions, 1.5% lower over 2031–2040, and 1% lower over 2041–2060. The rationale for these settings is twofold. First, the current one-year refinancing rate for China’s agricultural and small-scale loans is about 2%, which is about 2.5 percentage points lower than the normal market rate. Assuming that China’s green transition to less developed regions is financed at the rate of support for agriculture and small-scale refinancing, then 2% lower than normal is a reasonable initial setting. Second, considering the gradual successful transition of less developed regions, the gap between interest rates in less developed regions and normal market rates should converge. The level of the normal market interest rate is gradually declining and may fall to 1.6% in 2060. To avoid a negative interest rate, it is reasonable to set the gap between the two at 1% before 2060. For the sake of simplicity, we set a three-step gap of 2, 1.5, and 1%, which declines over time.
