提高碳全要素生产率是有力推进“碳达峰”“碳中和”工作的重要抓手,是城市低碳化发展的重要途径。基于2003—2019年中国城市数据,研究制造业集聚对城市碳排放全要素生产率的影响及其作用机制。基准回归结果表明,制造业集聚显著抑制了城市碳全要素生产率的提高。异质性分析表明,制造业集聚的抑制作用在数字经济发展水平较高地区变得不再显著。宏观机制研究表明,制造业集聚抑制城市碳全要素生产率的原因主要在于其对碳技术效率和碳技术进步的抑制,在匹配城市土地出让数据的基础上,制造业集聚扩大了土地供给面积、提高了土地成交价格,导致集聚拥挤效应凸显,阻碍知识溢出,不利于提高城市碳全要素生产率。微观机制分析表明,在匹配企业微观数据后,制造业集聚显著抑制了企业绿色发明专利数量的增加,损害了碳全要素生产率增长的微观基础。
Improving the total factor productivity of carbon is an important starting point to vigorously promote the work of “carbon peaking, carbon neutrality”, and an important way for urban low carbon development. This article is based on urban data in China from 2003 to 2019 to study the impact and mechanism of manufacturing agglomeration on total factor productivity of urban carbon emissions. The benchmark regression results indicate that manufacturing agglomeration significantly suppresses the improvement of total factor productivity of urban carbon emissions. The heterogeneity analysis shows that the inhibitory effect of manufacturing agglomeration is no longer significant in regions with high levels of digital economy development. Macroscopic mechanism research shows that the main reason why manufacturing agglomeration inhibits urban carbon total factor productivity is due to the inhibition of carbon technology efficiency and progress. By matching urban land transfer data, it can be found that manufacturing agglomeration has expanded the land supply area and increased land transaction prices, leading to a prominent agglomeration crowding effect, hindering knowledge spillover, and not conducive to improving urban carbon total factor productivity. Micro mechanism analysis shows that after matching micro data of enterprises, it can be found that manufacturing agglomeration significantly suppresses the increase in the number of green invention patents of enterprises, thereby damaging the micro foundation of carbon total factor productivity growth.
[1] Wang X, Wang S, Zhang X. Heterogeneity and influence factors of carbon productivity: Evidence from Chinese manufacturing enterprises[J]. Journal of Cleaner Production, 2023:136938
[2] 张平淡,屠西伟. 制造业集聚对绿色经济效率的双边影响[J]. 经济理论与经济管理, 2021(11):35-53
[3] 邵帅,张可,豆建民. 经济集聚的节能减排效应:理论与中国经验[J]. 管理世界, 2019(1):36-60
[4] Xu H, Liu W, Zhang D. Exploring the role of co-agglomeration of manufacturing and producer services on carbon productivity: An empirical study of 282 cities in China[J]. Journal of Cleaner Production, 2023:136674
[5] Liu X, Zhang X. Industrial agglomeration, technological innovation and carbon productivity: Evidence from China[J]. Resources, Conservation and Recycling, 2021:105330
[6] Li W, Wang W, Wang Y, et al. Historical growth in total factor carbon productivity of the Chinese industry – A comprehensive analysis[J]. Journal of Cleaner Production, 2018:471-485
[7] 张宁. 碳全要素生产率、低碳技术创新和节能减排效率追赶——来自中国火力发电企业的证据[J]. 经济研究, 2022(2):158-174
[8] 李强,冯波. 中国省际碳全要素生产率增长及收敛性[J]. 北京理工大学学报(社会科学版), 2014(3):14-21
[9] 王慧,孙慧,肖涵月,等. 环境政策不确定性、双向FDI与低碳全要素生产率的关系[J]. 中国人口·资源与环境, 2020(11):75-86
[10] 陈阳,唐晓华. 制造业集聚对城市绿色全要素生产率的溢出效应研究——基于城市等级视角[J]. 财贸研究, 2018(1):1-15
[11] 张平淡,屠西伟. 制造业集聚、技术进步与企业全要素能源效率[J]. 中国工业经济, 2022(7):103-121
[12] 张平淡,屠西伟. 制造业集聚与企业减污:大气污染和水体污染的差异[J]. 财贸经济, 2023(2):122-136
[13] Wang L, Wang H, Cao Z, et al. Can industrial intellectualization reduce carbon emissions? — Empirical evidence from the perspective of carbon total factor productivity in China[J]. Technological Forecasting and Social Change, 2022:121969
[14] 毛小明,钟诚. 产业集聚对于中国省域碳排放的影响及空间效应分析[J]. 南昌大学学报(人文社会科学版), 2022(2):56-65
[15] 谢波,徐琪. 产业集聚、外商直接投资与碳减排——基于中介效应与面板门槛模型分析[J]. 技术经济, 2019(12):120-125
[16] 及添正,邓宏兵,张天铃. 生产性服务业集聚对碳排放效率的影响——基于长江经济带108个城市企业数据的分析[J]. 资源科学, 2023(1):31-47
[17] 赵凡,罗良文. 长江经济带产业集聚对城市碳排放的影响:异质性与作用机制[J]. 改革, 2022(1):68-84
[18] Marshall A. Principle of Economics[M]. London: Macmillan, 1890
[19] Williamson J G. Regional inequality and the process of national development: A description of the patterns [J]. Economic Development and Cultural Change, 1965(4):3-45
[20] Brakman S, Garretsen H, Gigengack R, et al. Negative feedbacks in the economy and industrial location[J]. Journal of Regional Science, 1996(4):631-651
[21] 朱希伟. 理性的空间:集聚,分割与协调[M]. 杭州:浙江大学出版社, 2012
[22] 汪彩君,徐维祥,唐根年. 过度集聚、要素拥挤与产业转移研究[M]. 北京:中国社会科学出版社, 2013
[23] 林毅夫,任若恩. 东亚经济增长模式相关争论的再探讨[J]. 经济研究, 2007(8):4-12
[24] 赵志耘,吕冰洋,郭庆旺,等. 资本积累与技术进步的动态融合:中国经济增长的一个典型事实[J]. 经济研究, 2007(11):18-31
[25] 戴天仕,徐现祥. 中国的技术进步方向[J]. 世界经济, 2010(11):54-70
[26] 李治国,王杰. 经济集聚背景下数字经济发展如何影响空间碳排放?[J]. 西安交通大学学报(社会科学版), 2022(5):87-97
[27] 李贲,吴利华. 开发区设立与企业成长:异质性与机制研究[J]. 中国工业经济, 2018(4):79-97
[28] 陈家祥. 关于开发区协调发展的问题——以南京市为例[J]. 城市问题, 2010(2):2-7
[29] Du K, Li J. Towards a green world: How do green technology innovations affect total-factor carbon productivity[J]. Energy Policy, 2019:240-250
[30] 王林辉,董直庆. 资本体现式技术进步、技术合意结构和我国生产率增长来源[J]. 数量经济技术经济研究, 2012(5):3-18
[31] Zhou P, Ang B W, Han J Y. Total factor carbon emission performance: A Malmquist index analysis[J]. Energy Economics, 2010(1):194-201
[32] Lin B, Du K. Modeling the dynamics of carbon emission performance in China: A parametric Malmquist index approach[J]. Energy Economics, 2015:550-557
[33] Chen J, Gao M, Cheng S, et al. Global 1km×1km gridded revised real gross domestic product and electricity consumption during 1992-2019 based on calibrated nighttime light data[J]. Scientific Data, 2022(1):202-223
[34] 林伯强,谭睿鹏. 中国经济集聚与绿色经济效率[J]. 经济研究, 2019(2):119-132
[35] Fingleton B, Longhi S. The effects of agglomeration on wages: Evidence from the micro-level[J]. Journal of Regional Science, 2013(3):443-463
[36] 吴晓怡,邵军. 经济集聚与制造业工资不平等:基于历史工具变量的研究[J]. 世界经济, 2016(4):120-144
[37] Ciccone A, Hall R E. Productivity and the density of economic activity[J]. American Economic Review, 1996(1):54-70
[38] 封志明,张丹,杨艳昭. 中国分县地形起伏度及其与人口分布和经济发展的相关性[J]. 吉林大学社会科学学报, 2011(1):146-151
[39] 赵涛,张智,梁上坤. 数字经济、创业活跃度与高质量发展——来自中国城市的经验证据[J]. 管理世界, 2020(10):65-76
[40] 何文举,张华峰,陈雄超,等. 中国省域人口密度、产业集聚与碳排放的实证研究——基于集聚经济、拥挤效应及空间效应的视角[J]. 南开经济研究, 2019(2):207-225
[41] 寇宗来,刘学悦. 中国企业的专利行为:特征事实以及来自创新政策的影响[J]. 经济研究, 2020(3):83-99
[42] Xie R, Teo T S H. Green technology innovation, environmental externality, and the cleaner upgrading of industrial structure in China — Considering the moderating effect of environmental regulation[J]. Technological Forecasting and Social Change, 2022:122020
[43] Yi M, Liu Y, Sheng M S, et al. Effects of digital economy on carbon emission reduction: New evidence from China[J]. Energy Policy, 2022:113271
