【摘要】 设计合理的区域间碳排放权分配机制对于中国温室气体达峰目标的实现和减排成本的优化具有重要的理论与现实意义。本文提出了一个考虑技术异质性在内的多因素碳排放权分配理论模型,明确了全国碳减排总量目标、本地区排放总量、本地区碳排放强度以及本地区碳排放效率四个因素对碳排放权分配的影响机制。利用中国企业级低碳专利数据作为低碳技术水平的代理变量,考虑碳市场试点的政策冲击,本文基于消费侧和生产侧碳排放视角,利用随机前沿模型估计了各地区的碳排放效率,并使用估算效率值对碳排放权的地区分配进行了数值模拟。结果显示,当碳排放基于消费侧责任计算时,基于产出或排放量的分配机制将分别比基于多因素的分配机制额外带来1.61%和0.47%的工业总产出损失,而当碳排放基于生产侧责任计算时,仅基于产出或排放量的分配机制将分别比基于多因素的分配机制额外带来0.68%和0.21%的工业总产出损失。与此同时,当分配机制中考虑了碳排放效率时,基于消费侧和生产侧的不同分配会使部分地区产生较大的分配差异,能源生产省份在生产侧核算下需要承担更高碳减排量,以内蒙古为例,其减排量比消费侧核算下高出约65%,而电力调入省份在消费侧核算下需要承担更高碳减排量,以河北为例,其减排量比生产侧核算下高出约83%。更多还原

【Abstract】 Designing a reasonable regional CO₂ emission permit allocation mechanism is important for China to achieve its peak emission goal and to optimize its total emission abatement costs. The Chinese government officially launched the construction of the national emission trading scheme（ETS） at the end of 2017. The national ETS will first cover the electricity generation sector and gradually expand to other industrial sectors. The emission permits will be freely allocated using a benchmark method. There are three key questions for constructing the national ETS. First, how to ensure effectiveness so that the overall emission control target is achieved. Second, how to improve the efficiency of the carbon market to minimize total emission abatement costs. Third, how to balance social equity and the efficiency of environmental policy. To answer these questions, we must study the design of the optimal permit allocation mechanism for China’s national ETS.In this paper, we start by analyzing the marginal abatement cost curve（MACC） which is separated into two parts by carbon emission efficiency. One region’s potential carbon reduction amount is determined by the part that is not related to low-carbon technology. When the social planner allocates emission permits by maximizing the national total output, economic efficiency is achieved. The marginal abatement cost of each region is equalized under the first-order condition of this optimization problem. The corresponding permit allocation mechanism is a multi-criteria mechanism which includes the total emission reduction target, total emission amount, emission intensity, and carbon emission efficiency. In the empirical part, patent data related to environmentally sound technologies are used to measure the low-carbon technology development level in each region. Both consumption-based and production-based carbon emission efficiencies are estimated using stochastic frontier models and used in a numerical simulation. Looking at the carbon emission efficiency trend in different provinces, most regions show a downward drift during the 11 th Five-Year Plan period. During the 12 th Five-Year Plan period, most regions have a turning point in carbon emission efficiency and show a gradual upward trend because of the compulsory carbon emission intensity constraints. For consumption-based efficiency, output-based allocations（OBA） and emissions-based allocations（EBA） lead to 1.61 percent and 0.47 percent larger aggregate output losses than when using the multi-criteria allocation mechanism, respectively. For production-based efficiency, OBA and EBA lead to 0.68 percent and 0.21 percent larger aggregate output losses, respectively. The simulated allocation results differ between consumption-based and production-based allocations. Energy production provinces undertake more emission reduction responsibilities using production-based allocation. For example, Inner Mongolia reduces around 65 percent more emissions using consumption-based efficiency. Comparatively, electricity inflow provinces undertake more emission reduction responsibilities using consumption-based allocations. For example, Hebei reduces around 83 percent more emissions using production-based efficiency.Based on our theoretical analysis and empirical results, we give the following policy suggestions. First, when considering the allocation of carbon emission allowances, China should use multiple criteria such as output, historical emissions, and technological efficiency to avoid "spurring a willing horse". Second, under the optimal multi-criteria allocation framework, firms invest more in low-carbon technology to obtain more emission permits. Thus, endogenous low-carbon technological progress is realized in the long term. Third, permit allocation results are quite different between consumption-based and production-based allocations for some provinces. Therefore, the impacts of different allocation results on regional equity must be fully considered. Fourth, the multi-criteria allocation mechanism proposed in this paper can also be applied to firm-level permit allocations in the future.更多还原