采用双重差分和定性比较分析方法探究低碳城市试点政策提升碳排放效率的多维路径。首先,采用数据包络分析法测量碳排放效率。基于2009—2021年我国279个城市的面板数据,运用双重差分法实证分析低碳城市试点政策提升碳排放效率的政策净效应。其次,从政策工具视角构建分析模型,运用模糊集定性比较分析法探究低碳城市试点政策提升碳排放效率的多维路径。研究结果表明,实施低碳城市试点政策显著提升了试点地区的碳排放效率,试点地区人均碳排放效率的提升效果优于整体碳排放效率的提升效果。从政策的动态效应看,低碳城市试点政策对碳排放效率的提升效应具有长效性,政策执行效果持续增强,但也表现出一定的波动性,试点政策对试点地区碳排放效率的影响呈现倒“U”型趋势。不同类型政策工具的作用效果存在差异,产业结构调整是低碳试点政策提升碳排放效率的基础性工具,碳权市场交易机制对低碳试点政策提升碳排放效率产生叠加效应。多种类型政策工具的联合效应是低碳城市试点政策提升碳排放效率的主要作用机制,在提升路径上存在权威规制、公众规制和多元协同规制三种模式。
The improvement of carbon emission efficiency is an inevitable choice for China to address global climate change and achieve the dual goals of environmental protection and economic development. This study adopts a mixed research method of difference-in-differences and qualitative comparative analysis. Firstly, using panel data from 279 cities from 2009 to 2021, The net policy effect of low-carbon city pilot policies on carbon emission efficiency is analyzed empirically using difference-in-differences. An analytical model is constructed from the perspective of policy tools, and qualitative comparative analysis is employed to explore the multidimensional pathways of these policies in improving carbon emission efficiency. The findings show that low-carbon city pilot policies have significantly improved the carbon emission efficiency of the pilot cities,with per capita carbon emission efficiency having a greater effect than overall carbon emission efficiency. In terms of the dynamic effects of policies, the improvement of carbon emission efficiency by low-carbon city pilot policies is long-lasting, with continuously enhanced policy implementation effects. However, at the same time, there is also a certain degree of volatility, and the impact of pilot policies on carbon emission efficiency exhibits an inverted U-shaped trend. In the process of improving carbon emission efficiency, low-carbon city pilot policies adopt diversified policy tools, including command-control, economic incentives, and publicity and guidance. Different types of policy tools have different effects: industrial restructuring is the fundamental tool for improving carbon emission efficiency under low-carbon pilot policies; the carbon rights market trading mechanism has a cumulative effect on improving carbon emission efficiency under low-carbon pilot policies; the combined effects of various types of policy tools are the main mechanism for improving carbon emission efficiency under low-carbon city pilot policies, and there are three modes of regulation on the path of improvement: authoritative regulation, public regulation, and multi-stakeholder collaborative regulation.
[1] 张钰,韩新阳,王林钰.不一样的能源塑造不一样的城市[N].中国能源报,2017-07-24 (4)
[2] 程叶青,王哲野,张守志,等.中国能源消费碳排放强度及其影响因素的空间计量[J].地理学报,2013(10):1418-1431
[3] 绿色低碳发展智库伙伴.中国城市低碳发展规划峰值和案例研究[M].北京:科学出版社,2016:8-21
[4] 庄贵阳.低碳城市的理论、方法与实践[M].北京:中国社会科学出版社,2021:5-12
[5] 陈楠,庄贵阳.中国低碳试点城市成效评估[J].城市发展研究,2018(10):88-95,156
[6] 李超骕,田莉.基于PSR模型的低碳城市评估指标体系研究[J].城市建筑,2018 (2):13-17
[7] 丁丁,蔡蒙,付琳,等.基于指标体系的低碳试点城市评价[J].中国人口·资源与环境,2015(10):1-10
[8] 史修艺,徐盈之.低碳城市试点政策的公平性碳减排效果评估——基于工业碳排放视角[J].公共管理学报,2023(1):84-96,173
[9] 王连芬,赵园,王良健.低碳试点城市的减碳效果及机制研究[J].地理研究,2022(7):1898-1912
[10] 范贤贤,郭平.低碳城市试点政策对城市经济高质量发展的影响[J].经济经纬,2023(4):3-14
[11] 邓思远,杨湘浩,叶旭.低碳城市试点政策对企业技术创新的影响研究——基于断点回归设计的实证分析[J].产业经济评论,2022(6):71-85
[12] 韦东明,顾乃华.城市低碳治理与绿色经济增长——基于低碳城市试点政策的准自然实验[J].当代经济科学,2021(4):90-103
[13] 张永年.中国城市碳排放效率动态演进、区域差异及空间收敛性[J].城市问题,2023(7):33-42,83
[14] 徐英启,程钰,王晶晶.中国资源型城市碳排放效率时空演变与绿色技术创新影响[J].地理研究,2023(3):878-894
[15] 孙兴,刘熙.中国城市碳排放效率的时空演变及影响因素——基于异质性空间随机前沿模型[J].地理研究,2023(12):3182-3201
[16] 彭文斌,曹笑天,苏昌贵,等.长江中游城市群碳效率时空演化特征——基于三阶段SBM-DEA模型[J].生态学报,2023(9):3532-3545
[17] 江三良,鹿才保.环境规制影响碳排放效率的外部性及异质性——基于生产性服务业集聚协同的分析[J].华东经济管理,2022(10):56-69
[18] 徐维祥,周建平,刘程军. 数字经济发展对城市碳排放影响的空间效应[J]. 地理研究, 2022(1): 111-129
[19] 郭艺,曹贤忠,魏文栋,等. 长三角区域一体化对城市碳排放的影响研究[J]. 地理研究, 2022(1): 181-192
[20] Sun L X, Li W. Has the opening of high-speed rail reduced urban carbon emissions? Empirical analysis based on panel data of cities in China[J]. Journal of Cleaner Production, 2021(321): 128958
[21] 马海良,董书丽.不同类型环境规制对碳排放效率的影响[J].北京理工大学学报(社会科学版),2020(4):1-10
[22] 曹建飞,韩延玲,刘慧龙.数字经济发展如何影响城市碳排放？——来自中国283个地级市的经验数据[J].生态经济,2024(2):39-51
[23] Sun L X, Li W. Has the opening of high-speed rail reduced urban carbon emissions? Empirical analysis based on panel data of cities in China[J]. Journal of Cleaner Production, 2021(321): 128958
[24] 陈宇,孙枭坤.政策模糊视阈下试点政策执行机制研究——基于低碳城市试点政策的案例分析[J].求实,2020(2):46-64,110-111
[25] 约翰·W·克雷斯维尔,薇姬·L·查克著,游宇等译.混合方法研究:设计与实施[M].重庆:重庆大学出版社,2017
[26] 陈林,伍海军.国内双重差分法的研究现状与潜在问题[J].数量经济技术经济研究,2015(7):133-148
[27] Christopher C H.The Tools of Government[M].London:Macmillan Press,1983
[28] 吕志奎.公共政策工具的选择——政策执行研究的新视角[J].太平洋学报,2006(5):7-16
[29] 马士国.环境规制工具的选择与实施:一个述评[J].世界经济文汇,2008(3):76-90
[30] 盛科荣,李晓瑞,孙威,等.中国城市网络地位对碳排放效率的影响[J].地理学报,2023(11):2864-2882
[31] Dietz T, Rosa E A.Rethinking the environmental impacts of population[J]. Affluence and technology,1994(1):277-300
[32] Wang S,Wang Z,Fang C.Evolutionary characteristics and driving factors of carbon emission performance at the city level in China[J].Science China(Earth Sciences),2022(7):1292-1307
[33] 徐英启,程钰,王晶晶,等.中国低碳试点城市碳排放效率时空演变与影响因素[J].自然资源学报,2022(5):1261-1276
[34] James J H, Joseph H. Choosing among alternative nonexperimental methods for estimating the impact of social programs: The case of manpower training[J]. Journal of the American Statistical Association,1989(84):862-874
[35] 徐盈之,杨英超,郭进.环境规制对碳减排的作用路径及效应——基于中国省级数据的实证分析[J].科学学与科学技术管理,2015(10):135-146
[36] 王敏,黄滢.中国的环境污染与经济增长[J].经济学(季刊),2015(2):557-578
[37] 赵涛,于晨霞,潘辉.我国低碳城市发展影响机制研究——基于35个副省级以上城市样本的实证分析[J].经济问题,2017(8):111-116
[38] 刘传明,孙喆,张瑾.中国碳排放权交易试点的碳减排政策效应研究[J].中国人口·资源与环境,2019(11):49-58
[39] 崔和瑞,王欢歌.产学研低碳技术协同创新演化博弈研究[J].科技管理研究,2019(2):224-232
