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2026 , Vol. 36 >Issue 3: 43 - 56

DOI: https://doi.org/10.12062/cpre.20251002

应对气候变化与“双碳”目标

数据要素市场化与城市能源系统韧性——基于数据交易平台设立的准自然实验

  • 汪克亮 ,
  • 彭佳辉 ,
  • 许如玉
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  • 中国海洋大学经济学院,山东 青岛 266100
汪克亮,博士,教授,博导,主要研究方向为资源与环境经济学。E-mail：klwang@163.com。
许如玉,博士研究生,主要研究方向为数字经济与可持续发展。E-mail：ruyuxl@163.com。

收稿日期: 2025-06-15

  修回日期: 2025-08-19

  网络出版日期: 2026-06-05

基金资助

国家自然科学基金面上项目“复合系统视阈下制造业绿色转型的演化机理、绩效评价及调控策略研究”（批准号：72373138）

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Data factor marketization and urban energy system resilience: a quasi-natural experi-ment based on the establishment of data trading platforms

  • WANG Keliang ,
  • PENG Jiahui ,
  • XU Ruyu
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  • School of Economics, Ocean University of China, Qingdao Shandong 266100, China

Received date: 2025-06-15

  Revised date: 2025-08-19

  Online published: 2026-06-05

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摘要

数字时代下,数据要素成为推动经济社会系统性变革的战略资源与关键要素,深化数据要素市场化配置改革是激活数据要素价值、构建更具韧性的现代能源体系的重要举措。该研究基于2010—2023年中国278个地级及以上城市的面板数据,将“数据交易平台设立”视为准自然实验,运用双重机器学习模型实证检验数据要素市场化对城市能源系统韧性的影响及作用机制。研究发现：①数据要素市场化有助于提升城市能源系统韧性,且该结论经一系列稳健性检验和内生性处理后依旧成立。②机制检验表明,在内部治理维度,数据要素市场化可通过优化资源配置和促进绿色创新来提升城市能源系统韧性;在外部环境维度,政府数字治理认知与市场信息通达度具有正向调节作用,能够强化数据要素市场化对城市能源系统韧性的积极影响。③数据要素市场化提升城市能源系统韧性的作用效果在不同禀赋结构、基础设施和制度环境的城市中表现出显著异质性。具体来说,在非老工业基地、非资源型城市和数字基础设施水平较高、传统基础设施水平较高、市场发育程度较高、财政透明度较高的城市组别中,数据要素市场化对城市能源系统韧性的提升作用更明显。根据上述结论,该研究提出以下政策建议：以数据交易平台为引领,充分激活能源数据应用价值;聚力探索“内部治理优化-外部环境赋能”双维驱动路径;制定差异化发展举措,提高政策供给的靶向性。

关键词： 数据要素市场化; 能源系统韧性; 内部治理优化; 外部环境赋能

本文引用格式

汪克亮 , 彭佳辉 , 许如玉 . 数据要素市场化与城市能源系统韧性——基于数据交易平台设立的准自然实验[J]. 中国人口·资源与环境, 2026 , 36(3) : 43 -56 . DOI: 10.12062/cpre.20251002

Abstract

In the digital era, data elements have become the strategic resources and key elements driving systemic economic and social changes. Deepening the reform of data factor marketization is an important measure to unlock the value of data factors and build a more resilient modern energy system. Based on panel data of 278 prefecture-level and above cities in China from 2010 to 2023, this study treated the establishment of data trading platforms as a quasi-natural experiment and used a double machine learning model to empiri-cally examine the impact of data factor marketization on urban energy system resilience and its underlying mechanisms. The results showed that: ① Data factor marketization contributed to promoting urban energy system resilience, and this conclusion remained valid after a series of robustness tests and endogeneity treatments. ② Mechanism tests indicated that, in terms of internal governance, data factor marketization could enhance urban energy system resilience by optimizing resource allocation and promoting green innovation. In terms of the external environment, the government's digital governance awareness and market information accessibility exerted a posi-tive moderating effect, strengthening the positive impact of data factor marketization on urban energy system resilience. ③ The impact of data factor marketization on urban energy system resilience exhibited significant heterogeneity among cities with different endowment structures, infrastructure levels, and institutional environments. Specifically, the positive impact was more pronounced in city groups that were not old industrial bases, were non-resource-based, and had higher levels of digital infrastructure, traditional infrastructure, market development, and fiscal transparency. Based on the above conclusions, this study puts forward the following policy recommenda-tions: leverage data trading platforms to fully activate the application value of energy data; pursue a dual-dimensional pathway of “inter-nal governance optimization-external environmental empowerment;” and formulate differentiated development measures to enhance the targeting of policy supply.

Key words： data factor marketization; energy system resilience; internal governance optimization; external environmental empower-ment

参考文献

[1] 宋跃刚,高雯. 创新驱动政策能否提升可再生能源企业韧性:来自国家创新型城市试点政策的微观证据[J]. 中国人口·资源与环境,2025,35(1):144-158.
[2] 韩君,赵星宇 .“数据要素×”的碳排放效应:理论分析与实证检验[J]. 东方论坛-青岛大学学报(社会科学版),2025(3):75-93.
[3] SHEN N,ZHOU J,ZHANG G,et al.How does data factor mar-ketization influence urban carbon emission efficiency:a new meth-od based on double machine learning[J]. Sustainable cities and so-ciety,2025,119:106106.
[4] 赵放,徐熠,朱梦婷,等. 数据要素市场化配置如何影响国有企业 ESG 责任履行:基于准自然实验的考察[J]. 中国软科学,2024(10):212-224.
[5] 王守文,郭蕊,王树斌. 中国能源韧性与科技创新的协调演化及影响因素研究[J]. 中国软科学,2025(1):208-224.
[6] BAO M,DING Y,SANG M,et al.Modeling and evaluating nodal resilience of multi-energy systems under windstorms[J]. Applied energy,2020,270:115136.
[7] 黄建,冯升波,肖彬彬,等. 安全降碳背景下能源韧性的测度指标及其宏观分析框架研究[J]. 宏观经济研究,2022(12):115-125.
[8] YANG J,ZHOU K,HU R.City-level resilience assessment of inte-grated energy systems in China[J]. Energy policy,2024,193: 114294.
[9] DONG K,DONG X,JIANG Q,et al.Assessing energy resilience and its greenhouse effect:a global perspective[J]. Energy econom-ics,2021,104:105659.
[10] 赵政楠,茹少峰,薛飞. 黄河流域生态韧性的时空格局与分布动态演进:基于能值生态足迹模型的分析[J]. 中国人口·资源与环境,2024,34(8):136-147.
[11] GAO Z,ZHAO Y,LI L,et al.How does supply chain digitaliza-tion enhance energy resilience:empirical evidence from listed companies in China[J]. Energy economics,2025,145:108447.
[12] WANG Z,HAO Y.Can smart cities improve energy resilience: evidence from 229 cities in China[J]. Sustainable cities and soci-ety,2024,117:105971.
[13] YANG B,CUI Y.Can the energy consumption rights trading system enhance energy resilience:a synergistic perspective of green fi-nance and financial technology[J]. Energy,2025,322:135605.
[14] JIANG M,YU X.Enhancing the resilience of urban energy sys-tems:the role of artificial intelligence[J]. Energy economics, 2025,144:108313.
[15] NEPAL R,ZHAO X,LIU Y,et al.Can green finance strengthen energy resilience:the case of China[J]. Technological forecast-ing and social Change,2024,202:123302.
[16] XUE Y,YE H,WU H.The role of green credit in energy resil-ience:a quasi-natural experiment from China[J]. Journal of envi-ronmental management,2025,391:126490.
[17] MO S,LIU X.Strengthening the resilience of urban energy sys-tems amid renewable energy transition:a new method based on double machine learning[J]. Energy policy,2025,206:114776.
[18] DU X,FANG S.Does the lack of energy resilience a serious prob-lem at the forefront of policy analysts:role of supply chain digitali-zation and environmental law in OECD countries[J]. Energy eco-nomics,2025,141:108150.
[19] JIANG G,CHEN F,GU M.Supply chain digitization and energy resilience:evidence from China[J]. Energy economics,2025, 144:108420.
[20] ZHAO X,ZHAO J,TAGHIZADEH-HESARY F. Is energy sys-tem resilience improved in the energy transition:evidence from China[J]. Energy economics,2025,146:108485.
[21] ALDIERI L,GATTO A,VINCI C.Is there any room for renewable energy innovation in developing and transition economies:data en-velopment analysis of energy behaviour and resilience data[J]. Re-sources,conservation and recycling,2022,186:106587.
[22] NEPAL R,ZHAO X,DONG K,et al.Can artificial intelligence technology innovation boost energy resilience:the role of green fi-nance[J]. Energy economics,2025,142:108159.
[23] ZHANG Y,HU W,TAO Y,et al.How does smart artificial intel-ligence influence energy system resilience:evidence from energy vulnerability assessments in G20 countries[J]. Energy,2025, 314:134290.
[24] FAN W,LV W,WANG Z.How to measure and enhance the resil-ience of energy systems[J]. Sustainable production and consump-tion,2023,39:191-202.
[25] 孙伟增,司璐,吕越. 数字经济发展、资本跨区域非对称流动与异地分类投资[J]. 经济研究,2025,60(3):69-86.
[26] 史恩惠,李红昌. 数据要素市场化与战略性新兴企业突破式创新[J]. 山西财经大学学报,2025,47(7):102-114.
[27] 杨亚平,杨鑫,陈凯. 数据要素市场化对企业数字化创新的影响[J]. 经济管理,2025,47(3):5-25.
[28] 陈寒钰,赵紫凤,刘超. 数据要素市场建设促进了产业数字化发展吗:基于数据交易平台的准自然实验[J]. 宏观经济研究, 2024(1):61-74.
[29] 王晓丹,石玉堂,刘达. 数据要素市场化配置对数实融合的影响研究:基于数据交易平台设立的准自然实验[J]. 广东财经大学学报,2024,39(2):44-58.
[30] 郑国强,张馨元,赵新宇. 数据要素市场化如何驱动企业数字化转型[J]. 产业经济研究,2023(2):56-68.
[31] 谢地,王荣基,贺城. 数据要素市场化配置赋能企业新质生产力发展[J]. 经济学动态,2025(5):19-37.
[32] 黄桂琴,胡赵顺. 数据要素市场化与企业供应链韧性:基于双重机器学习的因果推断[J]. 商业研究,2025(3):142-152.
[33] 戴魁早,王思曼,黄姿. 数据交易平台建设如何影响企业全要素生产率[J]. 经济学动态,2023(12):58-75.
[34] 汪芳,张赞,赵玉林. 数据要素市场化与制造企业市场势力:来自国家大数据综合试验区的证据[J]. 经济学动态,2025(4):87-105.
[35] 张正平,冯朝秀. 数据要素市场建设与数字普惠金融发展:基于大数据交易平台设立的准自然实验[J]. 中国流通经济, 2025,39(4):86-98.
[36] 张贵,钱钰. 数据要素市场化配置与城市间创新合作:基于数据交易平台设立的准自然试验[J]. 现代经济探讨,2025(6):1-15.
[37] 杨艳,王理,廖祖君. 数据要素市场化配置与区域经济发展:基于数据交易平台的视角[J]. 社会科学研究,2021(6):38-52.
[38] 曹长帅 .数据要素市场化配置与城市韧性提升:来自数据交易平台设立的证据[J]. 山西财经大学学报,2025,47(8):1-14.
[39] 郑威,陈辉. 数据要素市场化配置对城市经济韧性的影响:促进还是抑制?[J]. 现代财经(天津财经大学学报),2023,43(12):78-92.
[40] 胡斌红,赵嘉仪. 数据要素市场化配置能促进就业吗:基于数据交易平台设立的准自然实验[J]. 商业研究,2025(2):63-71.
[41] 贺建风,周玉兰. 数据要素市场化、新质生产力与城乡共同富裕:基于数据交易平台设立的准自然实验[J]. 经济问题探索, 2025(5):91-109.
[42] 曹增栋,涂勤,夏文浩. 数据要素市场化驱动城市减污降碳的双边效应研究[J]. 城市问题,2025(4):57-67.
[43] 杜传忠,曹效喜,刘书彤. 数据要素市场化与地区绿色低碳发展:来自数据交易平台建设的准自然实验[J]. 经济与管理研究,2025,46(4):25-44.
[44] DONG L,ZHU X,YANG L,et al.Unleashing the power of data element markets:driving urban green growth through marketiza-tion,innovation,and digital finance[J]. International review of economics & finance,2025,99:104070.
[45] 郑国强,张馨元,赵新宇. 数据要素市场化能否促进企业绿色创新:基于城市数据交易平台设立的准自然实验[J]. 上海财经大学学报,2024,26(3):33-48.
[46] 周雪峰,王大英. 数据要素市场化、数字化转型与企业绿色创新[J]. 商业研究,2024(3):32-40.
[47] YAN H,ZHAO Z,ZHENG Y,et al.Evaluating the energy-sav-ing and efficiency-enhancing potential of data factor marketiza-tion:empirical evidence from 270 cities in China[J]. Journal of environmental management,2025,378:124686.
[48] YANG B.Data element marketization and energy efficiency of heavy polluting enterprises:a technology innovation perspective[J]. Jour-nal of environmental management,2025,391:126318.
[49] 洪永淼,林滔,史九领. 数据要素的基本属性、价值形成与市场构建[J]. 中国经济问题,2025(3):1-16.
[50] SCHUMPETER J A.Capitalism,socialism,and democracy[J]. American economic review,1942,3:594-602.
[51] JIA W,ZHANG Z,SU B,et al.Impact of local government envi-ronmental attention on corporate total factor productivity:evidence from 288 Chinese cities[J]. Journal of environmental manage-ment,2025,374:124052.
[52] 蔡运坤,周京奎,袁旺平. 数据要素共享与城市创业活力:来自公共数据开放的经验证据[J]. 数量经济技术经济研究,2024, 41(8):5-25.
[53] 李雪琴,郑酌基,韩先锋. 乘“数”而上:政府数据治理赋能企业数字创新[J]. 数量经济技术经济研究,2024,41(12):68-88.
[54] 王鹏,岑聪. 市场一体化、信息可达性与产出效率的空间优化[J]. 财贸经济,2022,43(4):147-164.
[55] 林孝文,刘翰程. 制度型开放如何提升企业产能利用率:兼论地方官员特征和市场信息可得性的调节效应[J]. 现代财经(天津财经大学学报),2025,45(4):22-39.
[56] 倪婷婷,王跃堂. 区域行政整合、要素市场化与企业资源配置效率[J]. 数量经济技术经济研究,2022,39(11):136-156.
[57] CHERNOZHUKOV V,CHETVERIKOV D,DEMIRER M,et al.Double/debiased machine learning for treatment and structural pa-rameters[J]. Econometrics journal,2018,21(1):C1-C68.
[58] ZHANG Z,ZHAO M,CHEN Y,et al.The nexus between energy leg-islation,energy transition,and energy resilience:evidence from 55 countries worldwide[J]. Energy,2025,324:135906.
[59] 王振霞,闫冰倩,王蕾. 能源价格与房地产市场波动:来自中国地级市层面的经验证据[J]. 金融研究,2023(2):1-20.
[60] 熊凌云,黄林菲,杨李娟. 全国统一大市场建设与城市创业活力:来自工程建设项目审批制度改革的证据[J]. 中国工业经济,2025(5):81-99.
[61] 石玉堂,王晓丹,秦芳,等. 数据要素市场化配置对全国统一大市场建设的效用研究[J]. 科研管理. 2024,45(12):1-10.
[62] 赵彦庆,范世铖,牛蕊. 数据要素市场化建设对城市全要素生产率的影响研究[J]. 现代财经(天津财经大学学报),2025,45(8):23-40.
[63] 郭家琛,王凤,刘珊,等. 人工智能政策赋能城市能源效率提升[J]. 中国人口·资源与环境,2025,35(4):24-37.
[64] 江艇 .因果推断经验研究中的中介效应与调节效应[J]. 中国工业经济,2022(5):100-120.
[65] 王贤彬,杨超群. 节能目标政策与地区能源效率[J]. 数量经济技术经济研究,2024,41(5):49-70.
[66] 钞小静,廉园梅,元茹静,等. 数字基础设施建设与产业链韧性:基于产业链恢复能力数据的实证分析[J]. 数量经济技术经济研究,2024,41(11):112-131.
[67] 杨玉玲,贾锐宁,马原. 交通基础设施对服务业全要素生产率的影响研究:基于单区制及两区制空间杜宾模型的检验[J]. 统计研究,2025,42(3):117-130.
[68] 贺光烨,吴晓刚. 市场化、经济发展与中国城市中的性别收入不平等[J]. 社会学研究,2015,30(1):140-165.
[69] 田高良,刘晓丰,司毅. 财政透明度与企业避税行为[J]. 管理工程学报,2024,38(3):58-75.
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