基于产业转移的高耗能行业碳转移测算、路径与影响因素

摘要/Abstract

摘要： 本文采用多区域投入产出模型（MRIO）测算了2002年、2007年、2012年和2017年中国30个省份高耗能产业转移和碳转移，比较了省际和行业间产业转移和碳转移路径。利用多尺度地理加权回归模型（MGWR）检验了环境规制、产业结构、能源强度和城镇化对碳转移的影响。结果表明，高耗能产业转移与碳转移的路径相似但不完全耦合，产业转移的“北移”趋势逐渐减弱，但碳转移仍然向北。从细分行业来看，也有明显差异，建筑业产业作为转出量最大的行业，主要从上海转出，但是建筑业的碳转出最多的省份是浙江。碳转移的影响因素研究结果表明，环境规制和能源强度对碳转移具有积极影响，城镇化和产业结构对碳转移具有负面影响。

关键词: 高耗能产业转移, 碳转移, 影响因素, 多尺度地理加权回归

Abstract: This study uses a Multi-Regional Input-Output Model (MRIO) to calculate the transfer of high-energy-consuming industries and carbon emissions among 30 provinces in China for the years 2002, 2007, 2012, and 2017. It compares the inter-provincial and inter-industry transfer paths of industries and carbon emissions. Multi-Scale Geographically Weighted Regression Model (MGWR) is applied to examine the impact of environmental regulations, industrial structure, energy intensity, and urbanization on carbon transfers. The results show that the pathways of transfer for high-energy-consuming industries and carbon emissions are similar but not completely linked. The trend of industrial transfer shifting northward is gradually weakening, but carbon transfer continues to move in the same direction. There are significant differences when examining specific industries. The construction industry is the largest transferring industry, primarily transferring out from Shanghai. The province with the most carbon transfer from the construction industry is Zhejiang. The study on factors influencing carbon transfers indicates that environmental regulations and energy intensity have a positive impact on carbon transfers, while urbanization and industrial structure have a negative impact.

Key words: high-energy-consuming industrial transfer, carbon transfer, influencing factors, multiscale geographically weighted regression(MGWR)

李梦, 王雅楠, 李巧, 陈伟, 刘增明, 于倩聿. 基于产业转移的高耗能行业碳转移测算、路径与影响因素[J]. 管理评论, 2025, 37(3): 28-41.

Li Meng, Wang Yanan, Li Qiao, Chen Wei, Liu Zengming, Yu Qianyu. Measurement, Pathway, and Influencing Factors of Carbon Transfer in High-energy Consuming Industries Based on Industrial Transfer[J]. Management Review, 2025, 37(3): 28-41.

参考文献

[1] Yang Y., Qin H. The Uncertainties of the Carbon Peak and the Temporal and Regional Heterogeneity of Its Driving Factors in China[J]. Technological Forecasting and Social Change, 2024,198:122937
[2] 韩梦瑶,刘卫东,杨茗月. 低碳转型下中国高耗能行业的碳风险传导解析:基于隐含碳关联网络视角[J]. 地理研究, 2022,41(1):79-91 Han M. Y., Liu W. D., Yang M. Y. Carbon Risk Transmission of China’s Energy-intensive Industries under Low-carbon Transition: From the Embodied Carbon Network Perspective[J]. Geographical Research, 2022,41(1):79-91
[3] 邵帅,徐俐俐,杨莉莉. 千里“碳缘”一线牵:中国区域碳排放空间关联网络的结构特征与形成机制[J]. 系统工程理论与实践, 2023,43(4):958-983 Shao S., Xu L. L., Yang L. L. Structural Characteristics and Formation Mechanism of Carbon Emission Spatial Association Networks within China[J]. Systems Engineering-Theory & Practice, 2023,43(4):958-983
[4] 陈慧灵,高子恒,王振波. 省级尺度工业碳排放影响因素及碳转移格局[J]. 生态学报, 2023,43(14):5816-5828 Chen H. L., Gao Z. H., Wang Z. B. Analysis on Influencing Factors of Industrial Carbon Emission and Carbon Transfer Pattern at Provincial Level[J]. Acta Ecologica Sinica, 2023,43(14):5816-5828
[5] 刘红光,刘卫东,刘志高. 区域间产业转移定量测度研究-基于区域间投入产出表分析[J]. 中国工业经济, 2011,(6):79-88 Liu H. G., Liu W. D., Liu Z. G. The Quantitative Study on Inter-regional Industry Transfer[J]. China Industrial Economics, 2011,(6):79-88
[6] 高翔,徐然,史依颖,等. 贸易战背景下我国典型制造业转移路径的启示[J]. 系统工程理论与实践, 2020,40(9):2203-2221 Gao X., Xu R., Shi Y. Y., et al. Facing the Trade War, What can Be Enlightened from the Relocation Paths of China’s Typical Manufactures[J]. Systems Engineering-Theory & Practice, 2020,40(9):2203-2221
[7] 魏庆琦,肖伟. 二维假设抽取法及其在工业隐含碳关联分析中的应用[J]. 科技管理研究, 2018,38(14):258-266 Wei Q. Q., Xiao W. Two-dimensional HEM and Its Application in Industrial Embodied Carbon Linkage Measurement[J]. Science and Technology Management Research, 2018,38(14):258-266
[8] 刘红光,张子孟,郭杰. 中国区域间价值链中隐含的碳排放转移研究[J]. 管理评论, 2021,33(9):58-64 Liu H. G., Zhang Z. M., Guo J. Carbon Emissions Embodied in Added-value Chains in China[J]. Management Review, 2021,33(9):58-64
[9] 刘敏,薛伟贤,陈莎. “一带一路”贸易网络能否促进各国全球价值链地位提升[J]. 管理评论, 2022,34(12):49-59 Liu M., Xue W. X., Chen S. Can Trade Network of the Belt and Road Countries Enhance the Status of the Global Value Chains[J]. Management Review, 2022,34(12):49-59
[10] 刘满凤,李昕耀. 产业转移对地方环境规制影响的理论模型和经验验证——基于我国产业转移的实证检验[J]. 管理评论, 2018,30(8):32-42 Liu M. F., Li X. Y. A Theory Model and Empirical Validation in Relation to the Influence that Industrial Transfer may Have on Local Environment Regulation—Based on Empirical Tests of China’s Industrial Transfer[J]. Management Review, 2018,30(8):32-42
[11] 于强. 京津冀协同发展背景下北京制造业的产业转移——基于区位熵视角[J]. 中国流通经济, 2021,35(1):70-78 Yu Q. Research on Industrial Transfer of Beijing’s Manufacturing Industry under the Background of Beijing-Tianjin-Hebei Coordinated Development—The Study from the Perspective of Location Entropy[J]. China Business and Market, 2021,35(1):70-78
[12] Xu J., Zhang M., Zhou M., et al. An Empirical Study on the Dynamic Effect of Regional Industrial Carbon Transfer in China[J]. Ecological Indicators, 2017,73:1-10
[13] 桑瑞聪,岳中刚. 泛长三角区域内产业分工与产业转移——来自四省一市的经验研究[J]. 经济与管理研究, 2011,(9):35-41 Sang R. C., Yue Z. G. Industry Specialization and Migration-empirical Evidences from Four Provinces and One City of Yangtze River Delta[J]. Research on Economics and Management, 2011,(9):35-41
[14] 张公嵬. 我国产业集聚的变迁与产业转移的可行性研究[J]. 经济地理, 2010,30(10):1670-1674 Zhang G. W. The Study of Industrial Agglomeration Change and the Probability of Industry Transfer in China[J]. Economic Geography, 2010,30(10):1670-1674
[15] 尹杰,高翔,杨翠红. 区分内外资企业的国际产业转移测度模型及对中国的实证研究[J]. 系统工程理论与实践, 2024,44(5):1421-1436 Yin J., Gao X., Yang C. H. A Quantitative Model of International Industry Relocation Distinguishing between Domestic and Foreign Enterprises and Its Empirical Study of China[J]. Systems Engineering-Theory & Practice, 2024,44(5):1421-1436
[16] Dong S. C., Xia B., Li F. J., et al. Spatial-Temporal Pattern, Driving Mechanism and Optimization Policies for Embodied Carbon Emissions Transfers in Multi-regional Tourism: Case Study of Provinces in China[J]. Journal of Cleaner Production, 2023,382:135362
[17] 余娟娟,龚同. 全球碳转移网络的解构与影响因素分析[J]. 中国人口·资源与环境, 2020,30(8):21-30 Yu J. J., Gong T. Analyzing the Deconstruction and Influencing Factors of the Global Carbon Transfer Network[J]. China Population Resources and Environment, 2020,30(8):21-30
[18] Zhong Z. Q., Guo Z. F., Zhang J. W. Does the Participation in Global Value Chains Promote Interregional Carbon Emissions Transferring Via Trade? Evidence from 39 Major Economies[J]. Technological Forecasting and Social Change, 2021,169:120806
[19] 潘晨,李善同,何建武,等. 考虑省际贸易结构的中国碳排放变化的驱动因素分析[J]. 管理评论, 2023,35(1):3-15 Pan C., Li S. T., He J. W., et al. Analysis of the Driving Forces of Changes in China’s CO2 Emissions Considering Inter-provincial Trade Structure[J]. Management Review, 2023,35(1):3-15
[20] Lin B. Q., Zhu J. P. Impact of China’s New-type Urbanization on Energy Intensity: A City-level Analysis[J]. Energy Economics, 2021,99:105292
[21] 袁嘉琪,卜伟,唐雨妮. 环境规制、要素配置对工业绿色全要素生产率的影响-产出补偿还是创新补偿[J]. 管理评论, 2023,35(10):45-62 Yuan J. Q., Bu W., Tang Y. N. The Influence of Environmental Regulation and Factor Allocation on Industrial Green Total Factor Productivity: Output Compensation or Innovation Compensation[J]. Management Review, 2023,35(10):45-62
[22] 钱娟,李新春. 有偏技术进步对环境污染的空间溢出效应——基于环境规制的调节作用[J]. 中国人口·资源与环境, 2023,33(12):109-119 Qian J., Li X. C. Spatial Spillover Effects of Biased Technological Progress on Environmental Pollution: Moderating Effects Based on Environmental Regulation[J]. China Population Resources and Environment, 2023,33(12):109-119
[23] 岳利萍,杨欣怡. 双重环境目标约束下的产业转型升级:“减污降碳”何以“协同增效”[J]. 中国人口·资源与环境, 2024,34(1):46-58 Yue L. P., Yang X. Y. Industrial Transformation and Upgrading under the Constraints of Dual Environmental Objectives : How Pollution Control and Carbon Reduction Are Synergistic[J]. China Population Resources and Environment, 2024,34(1):46-58
[24] Zheng C. J., Deng F., Li C. Y., et al. The Impact of China’s Western Development Strategy on Energy Conservation and Emission Reduction[J]. Environmental Impact Assessment Review, 2022,94:106743
[25] Li X., Lai X. D., Zhang F. C. Research on Green Innovation Effect of Industrial Agglomeration from Perspective of Environmental Regulation: Evidence in China[J]. Journal of Cleaner Production, 2021,288:125583
[26] Luo K., Lee C. C., Zhuo C. A Pathway to Coordinated Regional Development: Energy Utilization Efficiency and Green Development-Evidence from China’s Major National Strategic Zones[J]. Energy Economics, 2024,131:107402
[27] Mi Z. F., Meng J., Guan D. B., et al. Chinese CO2 Emission Flows Have Reversed Since the Global Financial Crisis[J]. Nature Communications, 2017,8(1):1712
[28] Song C. Y., Zhang Z. M., Xu W. H., et al. The Spatial Effect of Industrial Transfer on Carbon Emissions under Firm Location Decision: A Carbon Neutrality Perspective[J]. Journal of Environmental Management, 2023,330:117139
[29] Wang Q. C., Lu T., Chen H. S., et al. Tracing Environmental Footprint of Copper Wire Rod Manufacturing in China[J]. Resources, Conservation and Recycling, 2024,204:107503
[30] Zhi Z., Ming Z., Bo Y., et al. Multipath Retrofit Planning Approach for Coal-fired Power Plants in Low-carbon Power System Transitions: Shanxi Province Case in China[J]. Energy, 2023,275:127502
[31] Chen W., Song H. T. National Innovation System: Measurement of Overall Effectiveness and Analysis of Influencing Factors[J]. Technology in Society, 2024,77:102514
[32] 周洋. 增加值视角下中国省际贸易隐含碳测度[J]. 统计与决策, 2022,(5):156-160 Zhou Y. Measuring Implied Carbon in China’s Interprovincial Trade from a Value Added Perspective[J]. Statistics and Decision, 2022,(5):156-160
[33] Pan L. P., Han W. Q., Li Y. Q., et al. Legitimacy or Efficiency? Carbon Emissions Transfers under the Pressure of Environmental Law Enforcement[J]. Journal of Cleaner Production, 2022,365:132766
[34] Bai T. T., Qi Y., Li Z. H., et al. Digital Economy, Industrial Transformation and Upgrading, and Spatial Transfer of Carbon Emissions: The Paths for Low-carbon Transformation of Chinese Cities[J]. Journal of Environmental Management, 2023,344:118528
[35] Zhang X., Wang X., Tang C., et al. China’s Cross-regional Carbon Emission Spillover Effects of Urbanization and Industrial Shifting[J]. Journal of Cleaner Production, 2024,439:140854
[36] Zhao C., Wang B. How does New-type Urbanization Affect Air Pollution? Empirical Evidence Based on Spatial Spillover Effect and Spatial Durbin Model[J]. Environment International, 2022,165:107304
[37] 朱俏俏,靳春丽. 省域碳转移的空间网络结构特征与影响因素研究[J]. 煤炭经济研究, 2023,43(1):37-47 Zhu Q. Q., Jin C. L. Study on the Spatial Network Structure Characteristics and Influencing Factors of Provincial Carbon Transfer[J]. Coal Economic Research, 2023,43(1):37-47
[38] Liu B., Qiu Z. X., Hu L. T., et al. How Digital Transformation Facilitate Synergy for Pollution and Carbon Reduction: Evidence from China[J]. Environmental Research, 2024,251:118639
[39] Chen Z., Song P., Wang B. L. Carbon Emissions Trading Scheme, Energy Efficiency and Rebound Effect-Evidence from China’s Provincial Data[J]. Energy Policy, 2021,157:112507
[40] Dong B. Y., Xu Y. Z., Li Q. N. Carbon Transfer under China’s Inter-provincial Trade: Evaluation and Driving Factors[J]. Sustainable Production and Consumption, 2022,32:378-392