数字经济对工业碳排放绩效的影响——基于异质型环境规制的门槛效应

摘要
图/表
参考文献
相关文章 (8)

全文: PDF (544 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要基于2011~2020年30个省的面板数据,以行政命令型、市场激励型及公众参与型环境规制为门槛变量,构建双向固定效应模型与面板门槛回归模型,分析数字经济对工业碳排放绩效的影响效应..研究发现:数字经济对工业碳排放绩效提升具有促进作用,但其作用大小受到异质型环境规制的约束,不同类型和强度的环境规制作用下,数字经济的影响效果存在差异;区域异质性分析表明,东部地区的数字经济影响效应在市场激励型环境规制的门槛约束下发挥最大值,且在门槛前后,数字经济对工业碳排放绩效的影响由抑制作用转变为促进作用;中部地区的数字经济影响效应在公众参与型环境规制的门槛约束下发挥最大值,且在门槛前后,数字经济对工业碳排放绩效的影响由促进作用转变为抑制作用;西部地区的数字经济影响效应在行政命令型环境规制的门槛约束下发挥最大值,且影响效应在门槛内最强.因此,政府应制定多元化环境监管政策组合,并根据地区特点充分发挥数字经济发展对工业碳排放绩效的促进作用.

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	李柏桐
	李健
	唐燕
	夏美君

关键词 ：异质型环境规制, 数字经济, 工业碳排放绩效, 门槛效应

Abstract：Given the backdrop of heterogeneous environmental regulations, investigating the influence of the digital economy on industrial carbon emission performance assumes paramount significance. Leveraging panel data spanning 2011 to 2020 from 30 provinces, and employing administrative order, market incentive, and public participation environmental regulations as threshold variables, we construct a bi-directional fixed-effect model and a panel threshold regression model to scrutinize this relationship. Our findings reveal that while the digital economy can enhance industrial carbon emission performance, its efficacy is contingent upon the regulatory landscape. Across different types and intensities of environmental regulations, the impact of the digital economy varies. Regional analysis underscores this variability: in the eastern region, the digital economy’s impact peaks under the threshold of market-incentive environmental regulation, transitioning from inhibitory to promotional effects pre- and post-threshold. Conversely, in the central region, the digital economy’s impact peaks under the threshold of public participatory environmental regulation, transitioning from promotional to inhibitory effects pre- and post-threshold. In western China, the digital economy’s impact peaks under the threshold of administrative order environmental regulation, exhibiting its strongest effect within the threshold. Consequently, policymakers are urged to craft a diverse environmental regulatory framework and leverage digital economy development to enhance industrial carbon emission performance, tailored to regional characteristics.

Key words： heterogeneous environmental regulations digital empowerment industrial carbon emission performance threshold effect

收稿日期: 2024-02-22

PACS:

X703.5

基金资助:贵州省2023年度哲学社会科学规划课题(23GZZB17)

通讯作者: 李健,教授,lijian631219@163.com E-mail: lijian631219@163.com

作者简介: 李柏桐(1993-),女,辽宁营口人,天津理工大学博士研究生,研究方向为循环经济与生态工业工程.发表论文20篇.libaitong1204@163.com.

引用本文:

李柏桐, 李健, 唐燕, 夏美君. 数字经济对工业碳排放绩效的影响——基于异质型环境规制的门槛效应[J]. 中国环境科学, 2024, 44(9): 5263-5274. LI Bai-tong, LI Jian, TANG Yan, XIA Mei-jun. The impact of digital economy on industrial carbon emission performance: Threshold effect analysis of heterogeneous environmental regulations. CHINA ENVIRONMENTAL SCIENCECE, 2024, 44(9): 5263-5274.

链接本文:

http://www.zghjkx.com.cn/CN/ 或 http://www.zghjkx.com.cn/CN/Y2024/V44/I9/5263

[1] 杨冕,徐江川,杨福霞.能源价格、资本能效与中国工业部门碳达峰路径[J]. 经济研究, 2022,57(12):69-86. Yang M, Xu J C, Yang F X.Energy price,energy efficiency of capital and the path of carbon peak in China’s Industrial Sector [J]. Economic Research Journal, 2022,57(12):69-86.
[2] 尹上岗,杨山,龚海波.长三角工业经济规模与污染排放异速关系及互动机制[J]. 地理学报, 2022,77(9):2202-2218. Yi S H, Yang S, Gong H B.The allometric relationship and interactive mechanism between the size of industrial economies and the emissions of industrial pollution in the Yangtze River Delta [J]. Journal of Geographical Sciences, 2022,77(9):2202-2218.
[3] Liu S, Xiao Q. An empirical analysis on spatial correlation investigation of industrial carbon emissions using SNA-ICE model [J]. Energy, 2021,224:120183.
[4] 陈诗一.能源消耗、二氧化碳排放与中国工业的可持续发展[J]. 经济研究, 2009,44(4):41-55. Chen S Y. Energy consumption CO₂ emission and sustainable development in Chinese industry [J]. Economic Research Journal, 2009,44(4):41-55.
[5] 史丹,李鹏.“双碳”目标下工业碳排放结构模拟与政策冲击[J]. 改革, 2021,(12):30-44. Shi D, Li P. Industrial carbon emission structure simulation and policy impact under the target of “Double Carbon” [J]. Reform, 2021,(12): 30-44.
[6] 陈斌,何思思.数字经济时代的虚拟集聚与制造业技术创新——来自我国城市群的经验证据[J]. 南方经济, 2023,(8):72-92. Chen B, He S S. Virtual agglomeration and manufacturing technology innovation in the digital economy era: Empirical evidence from urban agglomerations in China [J]. South China Journal of Economics, 2023,42(8):72-92.
[7] 宋洋.数字经济、技术创新与经济高质量发展:基于省级面板数据[J]. 贵州社会科学, 2020,(12):105-112. Song Y. Digital economy, technological innovation, and high quality economic development: Based on provincial panel data [J]. Guizhou Social Sciences, 2020,(12):105-112.
[8] 刘鑫鑫,惠宁.数字经济对中国制造业高质量发展的影响研究[J]. 经济体制改革, 2021,(5):7. Liu X X, Hui N. Research on the influence of digital economy on the high quality development of China’s manufacturing industry [J]. Reform of Economic System, 2021,(5):7.
[9] 阳镇.数字经济如何驱动企业高质量发展？——核心机制、模式选择与推进路径[J]. 上海财经大学学报, 2023,25(3):92-107. Yang Z. How does the digital economy drive the high-quality development of enterprises? Core mechanism, mode selection, and promotion path [J]. J Shanghai Univ Fin Econ, 2023,25(3):92-107.
[10] Fang G, Gao Z, Tian L, et al. What drives urban carbon emission efficiency? Spatial analysis based on nighttime light data [J]. Applied Energy, 2022,312:118772.
[11] 卢福财,刘林英,徐远彬.互联网发展对工业绿色全要素生产率的影响研究[J]. 江西社会科学, 2021,(1):14-24. Lu F C, Liu L Y, Xu Y B. Research on the impact of internet development level on industrial green total factor productivity—Based on panel data of 285 cities in China [J]. Jiangxi Social Sciences, 2021,(1):14-24.
[12] 孔芳霞,刘新智.数字经济发展对工业绿色转型的影响研究——基于中国城市的经验证据[J]. 软科学, 2023,37(4):27-35. Kong F X, Liu X Z. Research on the impact of digital economy development on industrial green transformation [J]. Soft Science, 2023,37(4):27-35.
[13] 孙振清,成晓斐,谷文姗.异质性环境规制对工业绿色发展绩效的影响[J]. 华东经济管理, 2021,35(8):10-21. Sun Z Q, Cheng X F, Gu W S. Influence of heterogeneous environmental regulation on industrial green development performance [J]. East China Economic Management, 2021,35(8):10-21.
[14] 吕桁宇,马春爱,汤桐,等.环境规制、技术创新与工业企业能源强度[J]. 统计与决策, 2023,39(10):59-64. Lv H Y, Ma C A, Tang T, et al. Environmental regulation, technological innovation, and energy intensity of industrial enterprises [J]. Statistics & Decision, 2023,39(10):59-64.
[15] 高红贵,肖甜.异质性环境规制能否倒逼产业结构优化——基于工业企业绿色技术创新效率的中介与门槛效应[J]. 江汉论坛, 2022,(3):13-21. Gao H G, Xiao T. Can heterogeneous environmental regulations drive industrial structure optimization: Mediation and threshold effects based on the efficiency of green technology innovation in industrial enterprises [J]. Jianghan Tribune, 2022,(3):13-21.
[16] Liu H, Shi H, Chu J, et al. Threshold effects in the relationship between internet development and express delivery industry environmental efficiency [J]. Journal of Cleaner Production, 2022,340: 130815.
[17] 王晓岭,陈语,王玲.高质量发展目标下的环境规制与技术效率优化——以钢铁产业为例[J]. 财经问题研究, 2021,(12):39-48. Wang X L, Chen Y, Gao L, et al. Environmental regulation and technological efficiency optimization under the goal of high-quality development: A case study of the steel industry [J]. Research on Financial and Economic Issues, 2021,(12):39-48.
[18] 顾露露,庞晶,徐子芥.碳减排、环境规制与高污染行业企业价值[J]. 管理科学, 2022,35(6):40-55.
[19] 余畅,马路遥,曾贤刚,等.工业企业数字化转型的节能减排效应研究[J]. 中国环境科学, 2023,43(7):3755-3765. Yu C, Ma L Y, Zeng X G, et al. Research on energy saving and emission reduction effect of industrial enterprises’ digital transformation [J]. China Environmental Science, 2023,43(7):3755-3765.
[20] Zhang W, Li H, Wang S, et al. Impact of digital infrastructure inputs on industrial carbon emission intensity: evidence from China’s manufacturing panel data [J]. Environmental Science and Pollution Research. 2023,30(24):65296-313.
[21] 李少林,冯亚飞.区块链如何推动制造业绿色发展？——基于环保重点城市的准自然实验[J]. 中国环境科学, 2021,41(3):1455-1466. Li S L, Feng Y F. How does blockchain promote the high-quality development of manufacturing? A quasi-natural experiment based on key environmental protection cities. [J]. China Environmental Science, 2021,41(3):1455-1466.
[22] 钟文,杨俊,郑明贵,等.中国城市数字经济对物流业碳排放的影响效应及传导机制[J]. 中国环境科学, 2024,44(1):427-437. Zhong W, Yang J, Zheng M G, et al. The impact and transmission mechanism of China’s urban digital economy on carbon emissions in the logistics industry [J]. China Environmental Science, 2024,44(1): 427-437.
[23] Arsiwala A, Elghaish F, Zoher M. Digital twin with Machine learning for predictive monitoring of CO₂ equivalent from existing buildings [J]. Energy and Buildings. 2023,284:112851.
[24] 郑玉雯,李婧婧,薛伟贤.数字经济培育西部零碳工业园区的路径研究[J]. 科技管理研究, 2023,43(19):227-240. Zheng Y W, Li J J. Research on the path of digital economy cultivating zero-carbon industrial parks in Western China [J]. Science and Technology Management Research, 2023,43(19):227-240.
[25] 荆树伟,冯月,阎俊爱,等.从制造到智造:产权性质异质下传统制造型企业如何推行精益数字化[J]. 中国科技论坛, 2022,(8):77-88. Jing S W, Feng Y, Yan J A, et al. From manufacturing to intelligent manufacturing: how traditional manufacturing enterprises promote lean digitization under heterogeneous property rights [J]. Forum on Science and Technology in China, 2022,(8):77-88.
[26] 王娇,王凡林,于瑶.客户数字化转型与企业全要素生产率——基于技术进步与要素重置视角的分析[J]. 经济经纬, 2023,40(6): 83-96. Wang J, Wang F L, Yu Y, et al. Customer digital transformation and total factor productivity of enterprises: An analysis from the perspective of technological progress and factor reset [J]. Economic Survey, 2023,40(6):83-96.
[27] 康红普,任世华,王保强,等.煤炭工业数字化发展战略研究[J]. 中国工程科学, 2023,25(6):170-178. Kang H P, Ren S H, Wang B Q, et al. Digital development strategy of coal industry [J]. Strategic Study of CAE, 2023,25(6):170-178.
[28] Feng Y, Wang X, Du W, et al. Effects of environmental regulation and FDI on urban innovation in China: A spatial Durbin econometric analysis [J]. Journal of Cleaner Production, 2019,235:210-224.
[29] Li Z, Lu X, Wang S, et al. The threshold effect of environmental regulation in the nexus between green finance and total factor carbon productivity: evidence from a dynamic panel threshold model [J]. Environmental Science and Pollution Research, 2023,30(14):42223-42245.
[30] 宋美喆,柒江艺.数字经济背景下环境规制对绿色全要素生产率的影响——基于城市面板数据的分析[J]. 中国流通经济, 2023, 37(6):14-26. Song M Z, Qi J Y. The impact of environmental regulation on green total factor productivity in the context of the digital economy [J]. China Business and Market, 2023,37(6):14-26.
[31] Liang L, Wu J, Cook W D, et al. The DEA game cross-efficiency model and its Nash equilibrium [J]. Operations Research, 2008,56(5): 1278-1288.
[32] Cheng Z, Li L, Liu J, et al. Total-factor carbon emission efficiency of China’s provincial industrial sector and its dynamic evolution [J]. Renewable and Sustainable Energy Reviews, 2018,94:330-339.
[33] 苏振,郑应宏,郭峦.数字经济对旅游业碳排放效率的影响及门槛效应[J]. 中国人口·资源与环境, 2023,33(8):69-79. Zheng Y H, Guo L. Impact of the digital economy on the carbon efficiency of the tourism industry and its threshold effect [J]. China Population, Resources and Environment, 2023,33(8):69-79.
[34] 钟文,杨俊,郑明贵,等.中国城市数字经济对物流业碳排放的影响效应及传导机制[J]. 中国环境科学, 2024,44(1):427-437. Zhong W, Yang J, Zheng M G, et al. The impact and transmission mechanism of China’s urban digital economy on carbon emissions in the logistics industry [J]. China Environmental Science, 2024,44(1): 427-437.
[35] 肖仁桥,陈小婷,钱丽.异质环境规制、政府支持与企业绿色创新效率——基于两阶段价值链视角[J]. 财贸研究, 2022,33(9):79-93. Xiao R Q, Chen X T, Qian L. Heterogeneous environmental regulation, government support and Enterprises’ Green innovation efficiency: From the perspective of two—stage value chain [J]. Financ Trad Res, 2022,33(9):79-93.
[36] 胡迪,袁梦怡.市场型环境规制能促进碳中和目标实现吗[J]. 科技进步与对策, 2023,40(14):103-113. Hu D, Yuan M Y. Can market-based environmental regulation promote China to achieve th egoal of carbon neutrality [J]. Science & Technology Progress and Policy, 2023,40(14):103-113.
[37] Wu W, Wang W, Zhang M. Does internet public participation slow down environmental pollution? [J]. Environmental Science & Policy, 2022,137:22-31.
[38] Guo R, Yuan Y. Different types of environmental regulations and heterogeneous influence on energy efficiency in the industrial sector: Evidence from Chinese provincial data [J]. Energy Policy, 2020,145: 111747.
[39] Zhang M, Sun R, Wang W. Study on the effect of public participation on air pollution control based on China’s Provincial level data [J]. Environment, Development and Sustainability, 2021,(9):1-14.
[40] 何维达,温家隆,张满银.数字经济发展对中国绿色生态效率的影响研究——基于双向固定效应模型[J]. 经济问题, 2022,(1):9-29. He W D, Wen J L, Zhang M Y. Research on the impact of digital economy development on China’s Green ecological efficiency: Based on two-way fixed effects model [J]. On Economic Problems, 2022,(1): 9-29.
[41] 尹礼汇,吴传清.环境规制与长江经济带污染密集型产业生态效率[J]. 中国软科学, 2021,(8):181-192. Yin L H, Wu A Q. Environmental regulation and ecological efficiency of pollution intensive industries in the Yangtze River Economic Belt [J]. Chin Soft Sci, 2021,(8):181-192.
[42] 相瑞兵,田成诗,张焰朝.环境规制与企业研发投入:挤出抑或诱发——来自二氧化硫排污费征收的经验证据[J]. 中国环境科学, 2023,43(12):6803-6816. Xiang R B, Tian C S, Zhang Y C, et al. Environmental regulation and firm R&D investment: crowding out or inducing--Empirical evidence from the collection of sulfur dioxide pollution fees [J]. China Environmental Science, 2023,43(12):6803-6816.
[43] 刘颖,王诗.考虑环境非期望产出的工业行业绿色全要素生产率异质性与提升选择偏好[J]. 中国环境科学, 2023,43(11):6183-6193. Liu Y, Wang S. Green total factor productivity heterogeneity and promotion choice preference in industrial categories considering environmental undesirable-outputs [J]. China Environmental Science, 2023,43(11):6183-6193.
[44] 邝嫦娥,李文意.环境规制对绿色经济效率的空间影响——以长江中游城市群为例[J]. 地域研究与开发, 2023,42(3):53-59. Kuang G E, Li W Y. Spatial impact of environmental regulation on green economic efficiency: Taking the middle reaches of Yangtze River City Cluster as an example [J]. Areal Research and Development, 2023,42(3):53-59