绿色技术进步及其偏向性对减污降碳协同的影响研究

马越越; 蒋思琪; 郭永帅

PDF(1087 KB)

中国环境科学 ›› 2025, Vol. 45 ›› Issue (12) : 7070-7083.

环境影响评价与管理

绿色技术进步及其偏向性对减污降碳协同的影响研究

马越越, 蒋思琪, 郭永帅

作者信息 +

Research on the impact of green technological progress and its bias on the synergy of pollution reduction and carbon emission reduction

MA Yue-yue, JIANG Si-qi, GUO Yong-shuai

Author information +

文章历史 +

摘要

为探讨绿色技术进步及其偏向性对减污降碳协同的影响,利用2007~2021年全国251个地级市面板数据,使用非期望产出EBM模型和Malmquist-Luenberger指数测度绿色技术进步并分离城市层面的有偏技术进步.结合耦合协同度模型评价碳排放和大气污染物的协同程度,实证分析了绿色技术进步及其偏向性对减污降碳协同的影响方向及作用机制.研究表明:绿色技术进步和资本增强劳动节约型技术进步显著推动减污降碳协同进程,平均影响为0.023和0.005,这一促进作用在经过多种稳健性检验和内生性处置后结论依然成立.绿色技术进步能够通过增加人力资本积累促进减污降碳协同,中介效应占比为8.7%,政府环境规制在人力资本和减污降碳协同间发挥积极的调节作用,有调节的中介指数为0.008;资本增强劳动节约型技术进步改善减污降碳协同的同时不利于城市人力资本水平提高.异质性分析发现绿色技术进步在中小城市以及“胡焕庸”线东侧对减污降碳协同的促进作用显著,特大超大城市和大城市阻碍了减污降碳协同发展,大城市的负向作用更强;资本增强劳动节约型技术进步在特大超大城市和“胡焕庸”线西侧对减污降碳协同的推动作用更为明显.

Abstract

To explore the impact of green technological progress and its bias on the synergy of pollution reduction and carbon emission reduction, this study utilizes panel data of 251prefecture-level cities in China between 2007 and 2021, it employs the EBM model with undesirable outputs and the Malmquist-Luenberger index to measure green technological progress and separate biased technological progress at the city level. Then, after employing the coupling synergy degree model for evaluating the synergy degree of carbon emissions and air pollutants, this paper empirically analyzes the specific influences of green technological progress and its bias on air pollution and carbon emission reduction, as well as the mechanism through which it exerts its influences. According to the research findings: Green technological progress and capital-augmenting labor-saving technological progress can significantly promote the synergy between pollution reduction and carbon reduction, the average effect is 0.023 and 0.005. The promoting effect remains robust after a series of robustness checks and treatments for endogeneity. Green technological progress can promote the synergy between pollution reduction and carbon reduction by increasing the accumulation of human capital, with a mediating effect accounting for 8.7%. Government environmental regulation plays a positive moderating role between human capital and the pollution-carbon reduction synergy, with a moderated mediation index of 0.008. However, capital-augmenting labor-saving technological progress, while improving the synergy, is detrimental to the enhancement of urban human capital. According to the results of the heterogeneity analysis, green technological progress has a stronger promoting effect on the synergy in small and medium-sized cities and in the east of the Hu Line, while in super large cities, very large cities, and large cities, it hampers the synergy between pollution reduction and carbon reduction. Meanwhile, the negative effects are more pronounced in large cities. Capital-augmenting labor-saving technological progress has a stronger promoting effect on the synergy in super large cities, very large cities, and in the west of the Hu Line.

导出引用

马越越, 蒋思琪, 郭永帅. 绿色技术进步及其偏向性对减污降碳协同的影响研究[J]. 中国环境科学. 2025, 45(12): 7070-7083

MA Yue-yue, JIANG Si-qi, GUO Yong-shuai. Research on the impact of green technological progress and its bias on the synergy of pollution reduction and carbon emission reduction[J]. China Environmental Science. 2025, 45(12): 7070-7083

中图分类号： X322 F124.5

参考文献

[1] 生态环境部.2024中国生态环境状况公报 [Z]. 北京:生态环境部, 2025. Ministry of Ecology and Environment of People’s Republic of China. 2024 Report on the state of China ecology and environment [Z]. Beijing: Ministry of Ecology and Environment of People’s Republic of China, 2025.
[2] 中国石化集团经济技术研究院有限公司.中国能源展望2060 (2025年版) [R]. 北京:中国石油化工集团有限公司, 2025. Sinopec Economics and Development Research Institute Company Limited. China energy outlook 2060 (2025 Edition) [R]. Beijing: China Petrochemical Corporation, 2025.
[3] 孙博文,郑世林.环境规制的减污降碳协同效应——来自清洁生产标准实施的准自然实验 [J]. 经济学(季刊), 2024,24(2):624-642. Sun B W, Zheng S L. The synergistic effect of pollution reduction and carbon reduction of environmental regulation——Evidence from the Quasi-Natural experiment of cleaner production standards implementation [J]. China Economic Quarterly, 2024,24(2):624-642.
[4] Antonelli C. Technological congruence and the economic complexity of technological change [J]. Structural Change and Economic Dynamics, 2016,38:15-24.
[5] 何小钢,王自力.能源偏向型技术进步与绿色增长转型——基于中国33个行业的实证考察 [J]. 中国工业经济, 2015,(2):50-62. He X G, Wang Z L. Energy biased technology progress and green growth transformation—An empirical analysis based on 33industries of China [J]. China Industrial Economics, 2015,(2):50-62.
[6] 王林辉,王辉,董直庆.经济增长和环境质量相容性政策条件——环境技术进步方向视角下的政策偏向效应检验 [J]. 管理世界, 2020,(3):39-59. Wang L H, Wang H, Dong Z Q. Policy conditions for compatibility between economic growth and environmental quality: A test of policy bias effects from the perspective of the direction of environmental technological progress [J]. Journal of Management World, 2020,(3): 39-59.
[7] Zhang Y, Peng Y, Ma C, et al. Can environmental innovation facilitate carbon emissions reduction? Evidence from China [J]. Energy Policy, 2017,100:18-28.
[8] Zhang Z Y, Dai X, Ding Y. Government environmental governance and firms’ green innovation: Evidence from listed firms in heavy pollution industries of China [J]. Finance Research Letters, 2023,55: 103848.
[9] Jiakui C, Abbas J, Najam H, et al. Green technological innovation, green finance, and financial development and their role in green total factor productivity: Empirical insights from China [J]. Journal of Cleaner Production, 2023,382:135131.
[10] Qiu Y, Han W W, Zeng D. Impact of biased technological progress on the total factor productivity of China's manufacturing industry: The driver of sustainable economic growth [J]. Journal of Cleaner Production, 2023,409:137269.
[11] 李小克,郑珊珊,张姝晴,等.偏向性技术进步适宜性的测度与结构分解 [J]. 统计研究, 2024,41(7):91-105. Li X K, Zheng S S, Zhang S Q, et al. Measurement and structural decomposition of the appropriateness of biased technological change [J]. Statistical Research, 2024,41(7):91-105.
[12] Färe R, Grifell-Tatjé E, Grosskopf S, et al. Biased technical change and the Malmquist productivity index [J]. Scandinavian Journal of Economics, 1997,99(1):119-127.
[13] Chen P C, Yu M M. Total factor productivity growth and directions of technical change bias: Evidence from 99OECD and non-OECD countries [J]. Annals of Operations Research, 2014,214:143-165.
[14] 刘伟江,杜明泽,白玥.环境规制对绿色全要素生产率的影响——基于技术进步偏向视角的研究 [J]. 中国人口.资源与环境, 2022, 32(3):95-107. Liu W J, Du M Z, Bai Y. Impact of environmental regulations on green total factor productivity: Based on the perspective of technological progress bias [J]. China Population, Resources and Environment, 2022,32(3):95-107.
[15] 谢荣辉.绿色技术进步、正外部性与中国环境污染治理 [J]. 管理评论, 2021,33(6):111-121. Xie R H. Green technology progress, positive externality and environmental pollution control of China [J]. Management Review, 2021,33(6):111-121.
[16] Shen Y, Zhang X. Intelligent manufacturing, green technological innovation and environmental pollution [J]. Journal of Innovation & Knowledge, 2023,8(3):100384.
[17] 胡晓,冯乾彬,宫大庆,等.技术进步偏向性对中国城市碳中和进程的作用机制 [J]. 中国人口.资源与环境, 2022,32(7):91-103. Hu X, Feng Q B, Gong D Q, et al. Influencing mechanisms of directed technical change on the carbon neutrality realization process of Chinese cities [J]. China Population, Resources and Environment, 2022,32(7):91-103.
[18] 刘备,董直庆.技术进步的能源偏向诱发“碳锁定效应”了吗? [J]. 产经评论, 2020,11(4):133-148. Liu B, Dong Z Q. Has the energy bias of technological progress induced carbon lock-in? [J]. Industrial Economic Review, 2020,11(4): 133-148.
[19] 刘自敏,申颢.有偏技术进步与中国城市碳强度下降 [J]. 科学学研究, 2020,38(12):2150-2160. Liu Z M, Shen H. Biased technological progress and carbon intensity reduction in Chinese cities [J]. Studies in Science of Science, 2020, 38(12):2150-2160.
[20] Wang D W, Yu Z N, Liu H Y, et al. Impact of capital and labour based technological progress on carbon productivity [J]. Journal of Cleaner Production, 2024,467:142827.
[21] 宁光杰,林子亮.信息技术应用、企业组织变革与劳动力技能需求变化 [J]. 经济研究, 2014,(8):79-92. Ning G J, Lin Z L. Information technology adoption, workplace organization innovation and labor skill demand change [J]. Economic Research Journal, 2014,(8):79-92.
[22] 阳立高,龚世豪,王铂,等.人力资本、技术进步与制造业升级 [J]. 中国软科学, 2018,(1):138-148. Yang L G, Gong S H, Wang B, et al. Human capital, technology progress and manufacturing upgrading [J]. China Soft Science Magazine, 2018,(1):138-148.
[23] 王金南,张晓婧,薛强,等.生态环境民生理论与新时期发展任务探究 [J]. 中国环境科学, 2024,44(8):4700-4708. Wang J N, Zhang X J, Xue Q, et al. The theory of the people’s livelihood of Eco-environment and the task of development in the new era [J]. China Environmental Science, 2024,44(8):4145-4153.
[24] 吴康,耿一睿,郭涛.城市群绿色技术创新对碳排放的影响——基于人力资本的调节效应 [J]. 自然资源学报, 2024,39(9):2121-2139. Wu K, Geng Y R, Guo T. The impact of green technology innovation on carbon emissions from the perspective of urban agglomeration: The moderating effect of human capitals [J]. Journal of Natural Resources, 2024,39(9):2121-2139.
[25] 赵领娣,张磊,徐乐,等.人力资本、产业结构调整与绿色发展效率的作用机制 [J]. 中国人口.资源与环境, 2016,26(11):106-114. Zhao L D, Zhang L, Xu L, et al. Mechanism of human capital, industrial structure adjustment and green development efficiency [J]. China Population, Resources and Environment, 2016,26(11):106-114.
[26] 黄和平,周桂明.产业数字化对绿色全要素生产率的影响机制研究——兼议环境规制的门槛效应 [J]. 中国环境科学, 2025,45(3): 1713-1730. Huang H P, Zhou G M. Research on the impact mechanism of industrial digitalization on green total factor productivity: The threshold effect of environmental regulation [J]. China Environmental Science, 2025,45(3):1713-1730.
[27] 王洪庆.人力资本视角下环境规制对经济增长的门槛效应研究 [J]. 中国软科学, 2016,(6):52-61. Wang H Q. Study on threshold effects of environmental regulation on economic growth from the perspective of human capital [J]. China Soft Science, 2016,(6):52-61.
[28] Jahanger A, Usman M, Kousar R, et al. Implications for optimal abatement path through the deployment of natural resources, human development, and energy consumption in the era of digitalization [J]. Resources Policy, 2023,86:104165.
[29] Tone K, Tsutsui M. An epsilon-based measure of efficiency in data envelopment analysis [J]. European Journal of Operational Research, 2010,207(3):1554-1563.
[30] 贯君,苏蕾.双重环境规制下政府经济竞争对绿色高质量发展的影响 [J]. 中国环境科学, 2021,41(11):5416-5426. Guan J, Su Lei. Influence of government economic competition on green high-quality development under dual environmental regulations [J]. China Environmental Science, 2021,41(11):5416-5426.
[31] 晏雄,郭菊梅,普蔚.文旅融合对我国绿色全要素生产率的影响研究 [J]. 中国环境科学, 2025,45(2):1162-1175. Yan X, Guo J M, Pu W. A study on the impact of culture and tourism integration on green total factor productivity in China [J]. China Environmental Science, 2025,45(2):1162-1175.
[32] 丁黎黎,杨颖,郑慧,等.中国省际绿色技术进步偏向异质性及影响因素研究——基于一种新的Malmquist-Luenberger多维分解指数 [J]. 中国人口.资源与环境, 2020,30(9):84-92. Ding L L, Yang Y, Zheng H, et al. Heterogeneity and the influencing factors of provincial green-biased technological progress in China: Based on a novel Malmquist-Luenberger multidimensional decomposition index [J]. China Population, Resources and Environment, 2020,30(9):84-92.
[33] Weber W L, Domazlicky B R. Total factor productivity growth in manufacturing: A regional approach using linear programming [J]. Regional Science and Urban Economics, 1999,29(1):105-122.
[34] 杨翔,李小平,钟春平.中国工业偏向性技术进步的演变趋势及影响因素研究 [J]. 数量经济技术经济研究, 2019,(4):101-119. Yang X, Li X P, Zhong C P. Study on the evolution trend and influencing factors of China’s industrial directed technical change [J]. Journal of Quantitative & Technological Economics, 2019,(4):101-119.
[35] 陈晓红,周方毅,胡东滨.数字化对矿产资源与生态环境协调发展的影响 [J]. 中国环境科学, 2025,45(4):2346-2357. Chen X H, Zhou F Y, Hu D B. The impact of digitalization on the coordinated development of mineral resources and the ecological environment [J]. China Environmental Science, 2025,45(4):2346-2357.
[36] 温忠麟,叶宝娟.有调节的中介模型检验方法:竞争还是替补? [J]. 心理学报, 2014,46(5):714-726. Wen Z L, Ye B J. Different methods for testing moderated mediation models: Competitors or backups? [J]. Acta Psychologica Sinica, 2014, 46(5):714-726.
[37] 陈洪波,张骁潇.国家大数据综合试验区如何促进城市绿色转型:基于碳排放量增速和碳生产率增幅的双重视角 [J]. 中国软科学, 2024,(11):172-188. Chen H B, Zhang X X. How can National Comprehensive Big Data Pilot Zone promote green transformation of cities: Based on the dual perspective of the growth rate of carbon emissions and carbon productivity [J]. China Soft Science Magazine, 2024,(11):172-188.
[38] 杨建芳,龚六堂,张庆华.人力资本形成及其对经济增长的影响——一个包含教育和健康投入的内生增长模型及其检验 [J]. 管理世界, 2006,(5):10-18,34,171. Yang J F, Gong L T, Zhang Q H. Human capital formation land its effects on economic growth [J]. Journal of Management World, 2006, (5):10-18, 34,171.
[39] 童健,刘伟,薛景.环境规制、要素投入结构与工业行业转型升级 [J]. 经济研究, 2016,(7):43-57. Tong J, Liu W, Xue J. Environmental regulation, factor input structure and industrial transformation [J]. Economic Research Journal, 2016, (7):43-57.
[40] 董直庆,王辉.环境规制的“本地—邻地”绿色技术进步效应 [J]. 中国工业经济, 2019,(1):100-118. Dong Z Q, Wang H. Local-neighborhood effect of green technology of environmental regulation [J]. China Industrial Economics, 2019, (1):100-118.
[41] 曹婧,毛捷.财政分权与环境污染——基于预算内外双重视角的再检验 [J]. 中国人口.资源与环境, 2022,32(4):80-90. Cao J, Mao J. Fiscal decentralization and environmental pollution [J]. China Population, Resources and Environment, 2022,32(4):80-90.
[42] 杨子晖.政府规模、政府支出增长与经济增长关系的非线性研究 [J]. 数量经济技术经济研究, 2011,28(6):77-92. Yang Z H. An investigation on the nonlinear relationship between government size, expenditure growth and economic growth [J]. Journal of Quantitative & Technological Economics, 2011,28(6):77-92.
[43] 马越越,王维国.环境分权、地方政府竞争对绿色技术创新影响的“本地——邻地”效应 [J]. 中国管理科学, 2021,29(12):68-80. Ma Y Y, Wang W G. The “local-adjacent” effect of environmental decentralization and local government competition on green technology innovation [J]. Chinese Journal of Management Science, 2021,29(12):68-80.
[44] Soto G H. The role of high human capital and green economics in environmental sustainability in the Asia-Pacific region, 1990~2022 [J]. Management of Environmental Quality, 2024,35(8):1929-1952.
[45] 封永刚,蒋雨彤,彭珏.中国经济增长动力分解:有偏技术进步与要素投入增长 [J]. 数量经济技术经济研究, 2017,34(9):39-56. Feng Y G, Jiang Y T, Peng Y. Decomposition of economic growth’s motive force in China: Biased technical progress and factor input growth [J]. Journal of Quantitative & Technological Economics, 2017, 34(9):39-56.
[46] 李强,高楠.城市蔓延的生态环境效应研究——基于34个大中城市面板数据的分析 [J]. 中国人口科学, 2016,(6):58-67. Li Q, Gao N. A study on the effect of urban sprawl on ecological environment: An empirical study based on 34 cities municipal panel data [J]. Chinese Journal of Population Science, 2016,(6):58-67.