数字产业集群政策作为中国数字经济发展的重要战略工具,其对城市绿色发展的影响及内在机制尚未得到充分揭示。该研究采用SBM-GML模型测算的绿色全要素生产率作为城市绿色发展水平的衡量指标,将国家数字产业集群政策视为准自然实验,并基于2007—2023年中国284个地级及以上城市的面板数据,运用多期双重差分法系统评估其对城市绿色发展的影响及作用机制。研究发现：①数字产业集群政策显著提升了城市绿色发展水平。基准回归表明,该政策可使城市绿色全要素生产率平均提升0.042个单位。该结论在进行系列稳健性检验后仍然成立。②异质性分析表明,在非资源型城市、非老工业基地城市以及数字经济发展水平较高的城市,数字产业集群政策对城市绿色发展的促进效应尤为突出;而在资源型城市、老工业基地城市及数字经济发展水平较低的城市,该政策效果未达到统计显著性水平。③机制检验表明,数字产业集群政策主要通过绿色技术创新、数字企业和人才集聚、产业结构合理化等方式来促进城市绿色发展。研究结果为数字产业集群政策优化提供了以下启示：首先,坚定数字产业集群政策的战略定位,在总结试点经验基础上逐步扩大政策实施范围,形成国家层面的集群发展新格局;其次,实施差异化扶持策略,针对不同资源禀赋、工业基础和数字经济发展条件的城市制定精准政策,提升资源配置效率;最后,聚焦绿色技术创新、数字要素集聚与产业结构合理化等关键机制,强化政策在推动技术转化、优化人才环境与促进产业协同方面的支持力度。
As a crucial strategic tool for China's digital economy, the impact of the digital industry cluster policy on urban green develop-ment and its underlying mechanisms remains underexplored. This study used green total factor productivity (GTFP) calculated by the SBM-GML model as the indicator for measuring urban green development levels, treated the national digital industry cluster policy as a quasi-natural experiment, and employed a multi-period difference-in-differences (DID) method to systematically evaluate the policy's impact on urban green development and its underlying mechanisms based on panel data from 284 prefecture-level and above cities in China from 2007 to 2023. The findings were as follows: ① The digital industry cluster policy significantly enhanced urban green development. Base-line regression showed that the policy could increase urban GTFP by 0.042 units on average. This result remained valid after conducting a series of robustness tests. ② Heterogeneity analysis showed that the policy's promotional effects were more pronounced in non-resource-based cities, non-old industrial base cities, and cities with higher levels of digital economy development, while they remained statistically insignificant in resource-based cities, old industrial base cities, and cities with lower levels of digital economy development. ③ Mechanism tests indicated that the policy fostered urban green development primarily through green technology innovation, digital enterprise and tal-ent agglomeration, and industrial structure rationalization. This study offers the following insights for policy optimization: First, strengthen the strategic positioning of the digital industry cluster and gradually expand the scope of policy implementation based on pilot experiences to form a new pattern of cluster development at the national level. Second, implement differentiated support strategies and formulate target-ed policies for cities with varying resource endowments, industrial foundations, and digital economy development conditions to enhance re-source allocation efficiency. Finally, focus on key mechanisms such as green technology innovation, digital factor agglomeration, and indus-trial structure rationalization, and strengthen policy support for promoting technology transformation, talent environment optimization, and industrial synergy.
[1] 邓世成,吴玉鸣. 低碳城市试点政策对中国资源型城市绿色转型发展的影响[J]. 中国人口·资源与环境,2024,34(6):65-79.
[2] YAN X L,HE T Y.Wish fulfilment or wishful thinking:assessing the outcomes of China’s pilot carbon emissions trading scheme on green economy efficiency in China’s cities[J]. Energy policy,2024,192: 114261.
[3] YU Z C,XIE W L,GUO J J,et al.Green effect of energy transi-tion policy:a quasi-natural experiment based on new energy demon-stration cities[J]. Finance research letters,2024,66:105669.
[4] 赵亚雄,王修华,刘锦华. 绿色金融改革创新试验区效果评估: 基于绿色经济效率视角[J]. 经济评论,2023(2):122-138.
[5] 董景荣,张文卿,陈宇科. 环境规制工具、政府支持对绿色技术创新的影响研究[J]. 产业经济研究,2021(3):1-16.
[6] GU B B,CHEN F,ZHANG K.The policy effect of green finance in promoting industrial transformation and upgrading efficiency in China:analysis from the perspective of government regulation and public environmental demands[J]. Environmental science and pol-lution research,2021,28:47474-47491.
[7] 魏丽莉,侯宇琦. 数字经济对中国城市绿色发展的影响作用研究[J]. 数量经济技术经济研究,2022,39(8):60-79.
[8] 师磊,阳镇,钱贵明. 数字产业集群政策与关键核心技术突破式创新[J]. 中国工业经济,2025(1):100-117.
[9] 朱东波 .习近平绿色发展理念:思想基础、内涵体系与时代价值[J]. 经济学家,2020(3):5-15.
[10] 徐晓光,樊华,苏应生,等. 中国绿色经济发展水平测度及其影响因素研究[J]. 数量经济技术经济研究,2021,38(7):65-82.
[11] 张杰,范雨婷. 创新型城市绿色发展:效率测算、外部性与提升路径[J]. 中国人口·资源与环境,2023,33(2):102-112.
[12] ZHOU L,FAN J S,HU M Z,et al.Clean air policy and green to-tal factor productivity:evidence from Chinese prefecture-level cit-ies[J]. Energy economics,2024,133:107512.
[13] 谢贤君 .要素市场扭曲如何影响绿色全要素生产率:基于地级市经验数据研究[J]. 财贸研究,2019,30(6):36-46.
[14] FENG Y D,ZOU L H,YUAN H X,et al.The spatial spillover ef-fects and impact paths of financial agglomeration on green develop-ment:evidence from 285 prefecture-level cities in China[J]. Jour-nal of cleaner production,2022,340:130816.
[15] 李慧,佟孟华,张国建,等. 产业转型升级示范区的绿色转型效应:基于“ 数产融合 ”视角[J]. 财经研究,2025,51(1):4-18.
[16] ZHAO X,NAKONIECZNY J,JABEEN F,et al.Does green in-novation induce green total factor productivity:novel findings from Chinese city level data[J]. Technological forecasting and social change,2022,185:122021.
[17] ZHANG R,YING W H,WU K R,et al.The impact of innovative human capital agglomeration on urban green development efficien-cy:based on panel data of 278 cities in China[J]. Sustainable cit-ies and society,2024,111:105566.
[18] WANG G M,SALMAN M,ZHANG K W.Exploring the dynamic spatial spillover and nonlinear threshold effect of urbanization on urban green development efficiency in China[J]. Ecological indi-cators,2025,175:113570.
[19] 彭小辉,王静怡. 高铁建设与绿色全要素生产率:基于要素配置扭曲视角[J]. 中国人口·资源与环境,2019,29(11):11-19.
[20] 朱高立,饶芳萍,张建,等. 数字产业集聚如何驱动绿色全要素生产率提升:基于资源错配视角的实证研究[J]. 经济问题探索,2025(5):63-76.
[21] 段巍,王兵,韩婕. 数字经济重塑产业布局:理论机制与中国实践[J]. 南京社会科学,2025(3):46-57.
[22] 孔令章,李金叶. 城市数字经济发展的“减排”与“增效”效应[J]. 中国人口·资源与环境,2023,33(7):168-179.
[23] YANG S F,CHEN Y M,CHEN H,et al.Digital enterprise distri-bution and green total factor productivity:a spatial agglomeration perspective[J]. Environmental impact assessment review,2025, 112:107832.
[24] 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,2019,35(1):36-60.
[25] 林伯强,谭睿鹏. 中国经济集聚与绿色经济效率[J]. 经济研究,2019,54(2):119-132.
[26] 林小希 .经济集聚对绿色经济效率的影响[J]. 财经科学,2021(5):89-102.
[27] 焦豪,马高雅,张文彬. 数字产业集群:源起、内涵特征与研究框架[J]. 产业经济评论,2024(2):72-91.
[28] GUO D,LI L,PANG G G.Does the integration of digital and real economies promote urban green total factor productivity:evidence from China[J]. Journal of environmental management,2024, 370:122934.
[29] 卢福财,钟诗韵. 数字产业集群发展水平评价及其时空演变[J]. 经济地理,2024,44(6):113-123.
[30] 郭家堂 .公共数据开放与中国绿色全要素生产率:数据要素的视角[J]. 经济研究,2025,60(2):56-72.
[31] MORETTI E.The effect of high-tech clusters on the productivity of top inventors[J]. American economic review,2021,111(10):3328-75.
[32] 徐盈之,张瑞婕,孙文远. 绿色技术创新、要素市场扭曲与产业结构升级[J]. 研究与发展管理,2021,33(6):75-86.
[33] 陈喆,郑江淮. 绿色技术创新能够促进地区经济高质量发展吗:兼论环境政策的选择效应[J]. 当代经济科学,2022,44(4):43-58.
[34] 叶祥松,殷红. 产业结构变迁、产业互动与全要素生产率增长:基于动态结构的视角[J]. 经济学动态,2023(6):44-62.
[35] TAO M M,POLETTI S,WEN L,et al.Modelling the role of indus-trial structure adjustment on China’s energy efficiency:insights from technology innovation[J]. Journal of cleaner production, 2024,441:140861.
[36] 王海,郭冠宇,尹俊雅. 在转型中向“绿”而行:产业结构调整与企业绿色创新[J]. 数量经济技术经济研究,2025,42(1):93-115.
[37] 王兵,刘光天. 节能减排与中国绿色经济增长:基于全要素生产率的视角[J]. 中国工业经济,2015(5):57-69.
[38] 聂长飞,卢建新,冯苑,等. 创新型城市建设对绿色全要素生产率的影响[J]. 中国人口·资源与环境,2021,31(3):117-127.
[39] BAKER A C,LARCKER D F,WANG C C Y. How much should we trust staggered difference-in-differences estimates[J]. Journal of financial economics,2022,144(2):370-395.
[40] GOODMAN-BACON A. Difference-in-differences with variation in treatment timing[J]. Journal of econometrics,2021,225(2):254-277.
[41] SUN L Y,ABRAHAM S.Estimating dynamic treatment effects in event studies with heterogeneous treatment effects[J]. Journal of econometrics,2021,225(2):175-199.
[42] BORUSYAK K,JARAVEL X,SPIESS J.Revisiting event-study designs:robust and efficient estimation[J]. Review of economic studies,2024,91(6):3253-3285.
[43] CENGIZ D,DUBE A,LINDNER A,et al.The effect of mini-mum wages on low-wage jobs[J]. Quarterly journal of economics, 2019,134(3):1405-1454.
[44] 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.
[45] DIAN J,SONG T,LI S L.Facilitating or inhibiting:spatial ef-fects of the digital economy affecting urban green technology inno-vation[J]. Energy economics,2024,129:107223.
[46] 李金城,姚毓春. 数字经济赋能国有企业创新的内在机制与实现路径[J]. 经济学家,2024(6):95-106.
[47] 袁航,朱承亮. 国家高新区推动了中国产业结构转型升级吗[J]. 中国工业经济,2018(8):60-77.
