“碳排放权交易”的治理效果与减排机制研究

doi:10.19571/j.cnki.1000-2995.2024.10.016

摘要/Abstract

摘要： 面对“碳达峰、碳中和”的战略目标，强化绿色低碳发展的制度保障，是中国经济高质量发展的客观要求。本文基于因素分解框架，纳入能源结构因素，系统性地提出碳排放权交易驱动二氧化碳减排的理论机制。将碳排放权交易试点政策看作一项准自然实验，以2005—2017年30个省级面板数据为样本，运用双重差分方法实证检验了碳交易试点的治理效果与减排机制。研究发现：碳排放权交易的实施显著降低了试点地区的二氧化碳排放，运用工具变量法克服潜在的内生性问题和一系列稳健性检验之后，结论依然成立；机制分析表明，碳排放权交易的治理效果经由产业结构转型、能源结构优化和技术创新三条路径实现，并对二氧化硫、氮氧化物和烟粉尘等污染物产生了协同减排效应；异质性检验显示，碳排放权交易对环境执法严格、创新能力突出、人力资本水平高的地区，以及老工业基地和资源型地区的治理效果更为明显。本文的研究结论不仅为碳排放权交易制度的治理效果和减排机制提供了新的理论支撑及经验证据，而且为全国统一碳市场建立运行之后的制度体系完善与配套政策优化提供有益思路。

关键词: 碳排放权交易, 产业结构, 能源结构, 技术创新

Abstract: In face of the strategic goal of “carbon peak and carbon neutral”, strengthening the institutional guarantee of green and low-carbon development is the objective requirement of China′s high-quality economic development. Based on the factor decomposition framework and the energy structure factor, this paper systematically proposed the theoretical mechanism in which carbon emission trading system drives carbon dioxide emission reduction. Moreover, regarding the carbon emission trading pilot policy as a quasi-natural experiment, this paper empirically tested the governance effect and emission reduction mechanisms by using the difference-in-differences method and taking the panel data of 30 provincial-level regions from 2005 to 2017 as samples. The results showed that the implementation of the carbon emission trading system significantly reduces the carbon dioxide emissions in the pilot areas. The conclusion is still valid after using the instrumental variable method to overcome the potential endogenous problems and a series of robustness tests. The mechanism analysis showed that the governance effect is realized through three paths, namely industrial structure transformation, energy structure optimization, and technological innovation. Besides, it also has a synergistic emission reduction effect on sulfur dioxide, nitrogen oxide, and smoke and dust. The heterogeneity test showed that the impacts of the carbon emission trading system on the regions with strict environmental law enforcement, outstanding innovation ability, high human capital level, old industries-based and resource-based areas are more obvious. The conclusions will not only provide new empirical evidence for the governance effect and emission reduction mechanism of the carbon emission trading system, but also provide useful ideas for the improvement of the institutional system and the optimization of supporting policies after the establishment of the national unified carbon market.

Key words: carbon emission trading, industrial structure, energy structure, technological innovation

董艳, 王昀, 孙款款, 孙晓华. “碳排放权交易”的治理效果与减排机制研究[J]. 科研管理, 2024, 45(10): 160-171.

Dong Yan, Wang Yun, Sun Kuankuan, Sun Xiaohua. Research on the governance effect and emission reduction mechanism of the carbon emission trading system[J]. Science Research Management, 2024, 45(10): 160-171.

参考文献

[1] Shapiro J S, Walker R. Why is pollution from US manufacturing declining? The roles of environmental regulation, productivity, and trade[J]. Am. Econ. Rev., 2018, 108 (12): 3814-3854.
[2] Hille E, Shahbaz M. Sources of emission reductions: market and policy-stringency effects[J]. Energy Econ., 2019, 78(1): 29-43.
[3] 鲁万波, 仇婷婷, 杜磊. 中国不同经济增长阶段碳排放影响因素研究[J]. 经济研究, 2013, 48(04): 106-118.
[4] 徐斌, 陈宇芳, 沈小波. 清洁能源发展、二氧化碳减排与区域经济增长[J]. 经济研究, 2019, 54(07): 188-202.
[5] Modis T. Forecasting energy needs with logistics[J]. Technol. Forecast. Soc. Chang., 2019, 139, 135-143.
[6] Sharifi M, Pool J K, Jalilvand M R, et al. Forecasting of advertising effectiveness for renewable energy technologies: a neural network analysis[J]. Technol. Forecast. Soc. Chang., 2019, 143, 154-161.
[7] 彭水军, 张文城. 中国居民消费的碳排放趋势及其影响因素的经验分析[J]. 世界经济, 2013, 36(03): 124-142.
[8] Chen L, Li K, Chen S, Wang X, Tang L. Industrial activity, energy structure, and environmental pollution in China[J]. Energy Economics, 2021, 104, 105633.
[9] 林伯强, 李江龙. 基于随机动态递归的中国可再生能源政策量化评价[J]. 经济研究, 2014, 49(04): 89-103.
[10] Inglesi-Lotz R. The impact of renewable energy consumption to economic growth: A panel data application[J]. Energy Economics, 2016, 53, 58-63.
[11] Bhattacharya M, Paramati S R, Ozturk I, Bhattacharya S. The effect of renewable energy consumption on economic growth: Evidence from top 38 countries[J]. Applied Energy, 2016, 162, 733-741.
[12] Yang Z H. Study on the dynamic relationship between economic growth, energy consumption and carbon dioxide emission[J]. J. World Econ, 2011, 34 (6), 100-125.
[13] Song M L, Zhao X, Shang Y P. The impact of low-carbon city construction on ecological efficiency: empirical evidence from quasi-natural experiments[J]. Res. Conserv. Recycl, 2020, 157.
[14] 张晓娣, 刘学悦. 征收碳税和发展可再生能源研究——基于OLG-CGE模型的增长及福利效应分析[J]. 中国工业经济, 2015(03): 18-30.
[15] Wu X, Deng H, Li H, Guo Y. Impact of energy structure adjustment and environmental regulation on air pollution in China: Simulation and measurement research by the dynamic general equilibrium model[J]. Technological Forecasting and Social Change, 2021, 172, 121010.
[16] Su B, Ang B W. Multiplicative structural decomposition analysis of aggregate embodied energy and emission intensities[J]. Energy Econ, 2017, 137-147.
[17] Hoekstra R, Jeroen J.C.J.M. van den Bergh. Comparing structural and index decomposition analysis[J]. Energy Econ, 2003, 25 (1), 39-64.
[18] 王锋, 冯根福, 吴丽华. 中国经济增长中碳强度下降的省区贡献分解[J]. 经济研究, 2013, 48(08): 143-155.
[19] Yang L, Li Z. Technology advance and the carbon dioxide emission in China—Empirical research based on the rebound effect[J]. Energy Policy, 2017, 101, 150-161.
[20] Rose A, Casler S. Input-output structural decomposition analysis: a critical appraisal[J]. Econ. Syst. Res., 1996, 8 (1), 33-62.
[21] Kone A, Buke T. A Decomposition Analysis of Energy-Related CO2 Emissions: The Top 10 Emitting Countries[J]. Energy Systems and Management, 2015, 65-77.
[22] Wang Z, Ye X. Re-examining environmental Kuznets curve for China’s city-level carbon dioxide (CO2) emissions[J]. Spatial Stat., 2017, 21, 377-389.
[23] Su B, Ang B W. Structural decomposition analysis applied to energy and emissions: some methodological developments[J]. Energy Economics, 2012, 34(1), 177-188.
[24] Zhan M, Liu X, Wang W, Zhou M. Decomposition analysis of CO2 emissions from electricity generation in China[J]. Energy Policy, 2103, 52, 159-165.
[25] Wang S, Zhu X, Song D, Wen Z, Chen B, Feng K. Drivers of CO2 emissions from power generation in China based on modified structural decomposition analysis[J]. Journal of Cleaner Production, 2019, 220, 1143-1155.
[26] Tan R, Lin B. What factors lead to the decline of energy intensity in China's energy intensive industries[J]. Energy Econ, 2018, 71, 213-221.
[27] Zhang C, Su B, Zhou K, Yang S. Analysis of electricity consumption in China (1990–2016) using index decomposition and decoupling approach[J]. Journal of Cleaner Production, 2019, 209, 224-235.
[28] Levinson A. Technology, international trade, and Pollution from US manufacturing[J]. Am. Econ. Rev., 2009, 99 (5), 2177-2192.
[29] 徐盈之, 徐康宁, 胡永舜. 中国制造业碳排放的驱动因素及脱钩效应[J]. 统计研究, 2011, 28(07): 55-61.
[30] 付华, 李国平, 朱婷. 中国制造业行业碳排放：行业差异与驱动因素分解[J]. 改革, 2021(05): 38-52.
[31] Cherniwchan J, Copeland B R, Taylor M S. Trade and the environment: new methods, measurements, and results[J]. Annu. Rev. Econ., 2017, 9 (1), 59-85.
[32] 宋德勇, 卢忠宝. 中国碳排放影响因素分解及其周期性波动研究[J]. 中国人口·资源与环境, 2009, 19(03): 18-24.
[33] Ang J B. CO2 emissions, research and technology transfer in China[J]. Ecological Economics, 2009, 68(10), 2658-2665.
[34] Qi T, Weng Y, Zhang X, He J. An analysis of the driving factors of energy-related CO2 emission reduction in China from 2005 to 2013[J]. Energy Econ., 2016, 60,15-22.
[35] OECD. Indicators to Measure decoupling of environmental pressure from economic growth[R]. Paris: OECD, 2002.
[36] Kan S, Chen B, Chen G. Worldwide energy use across global supply chains: decoupled from economic growth[J]. Applied energy, 2019, 250, 1235-1245.
[37] Shuai C, Chen X, Wu Y, Zhang Y, Tan Y. A three-step strategy for decoupling economic growth from carbon emission: empirical evidences from 133 countries[J]. Science of the total environment, 2019, 646, 524-543.
[38] Zhang Y, Sun M, Yang R, Li X, Zhang L, Li M. Decoupling water environment pressures from economic growth in the Yangtze River Economic Belt, China[J]. Ecological Indicators, 2021, 122, 107314.
[39] Tapio P. Towards a theory of decoupling: degrees of decoupling in the EU and the case of road traffic in Finland between 1970 and 2001[J]. Transport Policy, 2005, 12(2): 137-151.
[40] Gao C, Ge H, Lu Y, Wang W, Zhang Y. Decoupling of provincial energy-related CO2 emissions from economic growth in China and its convergence from 1995 to 2017[J]. Journal of Cleaner Production, 2021, 297, 126627.
[41] Ang B W. The LMDI approach to decomposition analysis: a practical guide[J]. Energy Policy, 2005, 33 (7), 867-871.
[42] Diakoulaki D, Mandaraka M. Decomposition analysis for assessing the progress in decoupling industrial growth from CO2 emissions in the EU manufacturing sector[J]. Energy Economics, 2007, 29(4), 636-664.
[43] Zhang Y J, Da Y B. The decomposition of energy-related carbon emission and its decoupling with economic growth in China[J]. Renewable and Sustainable Energy Reviews, 2015, 41, 1255-1266.
[44] Shan Y, Guan D, Zheng H, et al. China CO2 emission accounts 1997–2015[J]. Scientific Data, 2018, 5: 170201.
[45] Shan Y, Huang Q, Guan D, et al. China CO2 emission accounts 2016–2017[J]. Scientific Data, 2020, 7(1).
[46] Shan Y, Liu J, Liu Z, et al. New provincial CO2 emission inventories in China based on apparent energy consumption data and updated emission factors[J]. Applied Energy, 2016, 184(12): 742-750.
[47] 李新运, 吴学锰, 马俏俏. 我国行业碳排放量测算及影响因素的结构分解分析[J]. 统计研究, 2014, 31(01): 56-62.