How does data factor marketization influence urban carbon emission efficiency? A new method based on double machine learning

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society Pub Date : 2025-02-01 DOI:10.1016/j.scs.2024.106106

Neng Shen, Jingwen Zhou, Guoping Zhang, Lianjun Wu, Lin Zhang

{"title":"How does data factor marketization influence urban carbon emission efficiency? A new method based on double machine learning","authors":"Neng Shen, Jingwen Zhou, Guoping Zhang, Lianjun Wu, Lin Zhang","doi":"10.1016/j.scs.2024.106106","DOIUrl":null,"url":null,"abstract":"<div><div>Data factor marketization (DFM) can fully leverage the multiplier effect of data and provide impetus for China 's carbon emission efficiency (CEE) improvement. Drawing from the panel data across 282 Chinese cities from 2011 to 2021, this research takes the establishment of data trading platforms as the quasi-natural experiment, and innovatively uses the double machine learning (DML) model to study the impact of DFM on CEE and its mechanisms. The findings indicate that: (1) DFM has a strong favorable impact on CEE. Furthermore, this conclusion remains valid following a series of robustness tests such as adjusting samples and changing models. (2) DFM can influence CEE by accelerating digital finance development, improving technological innovation level and promoting industrial structure towards the direction of advanced development (3) The effect of DFM has obvious regional heterogeneity. It is more significant for non-resource-based, high administrative level, low-intensity environmental regulation and economically developed cities. This study quantifies the promotion effect of the DFM on CEE, and provides important experience and enlightenment for comprehensively deepening the construction of data resource system and achieving sustainable development.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"119 ","pages":"Article 106106"},"PeriodicalIF":10.5000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Cities and Society","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210670724009284","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Data factor marketization (DFM) can fully leverage the multiplier effect of data and provide impetus for China 's carbon emission efficiency (CEE) improvement. Drawing from the panel data across 282 Chinese cities from 2011 to 2021, this research takes the establishment of data trading platforms as the quasi-natural experiment, and innovatively uses the double machine learning (DML) model to study the impact of DFM on CEE and its mechanisms. The findings indicate that: (1) DFM has a strong favorable impact on CEE. Furthermore, this conclusion remains valid following a series of robustness tests such as adjusting samples and changing models. (2) DFM can influence CEE by accelerating digital finance development, improving technological innovation level and promoting industrial structure towards the direction of advanced development (3) The effect of DFM has obvious regional heterogeneity. It is more significant for non-resource-based, high administrative level, low-intensity environmental regulation and economically developed cities. This study quantifies the promotion effect of the DFM on CEE, and provides important experience and enlightenment for comprehensively deepening the construction of data resource system and achieving sustainable development.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Sustainable Cities and Society Social Sciences-Geography, Planning and Development

CiteScore

22.00

自引率

13.70%

发文量

810

审稿时长

27 days

期刊介绍： Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including: 1. Smart cities and resilient environments; 2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management; 3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management); 4. Energy efficient, low/zero carbon, and green buildings/communities; 5. Climate change mitigation and adaptation in urban environments; 6. Green infrastructure and BMPs; 7. Environmental Footprint accounting and management; 8. Urban agriculture and forestry; 9. ICT, smart grid and intelligent infrastructure; 10. Urban design/planning, regulations, legislation, certification, economics, and policy; 11. Social aspects, impacts and resiliency of cities; 12. Behavior monitoring, analysis and change within urban communities; 13. Health monitoring and improvement; 14. Nexus issues related to sustainable cities and societies; 15. Smart city governance; 16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society; 17. Big data, machine learning, and artificial intelligence applications and case studies; 18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems. 19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management; 20. Waste reduction and recycling; 21. Wastewater collection, treatment and recycling; 22. Smart, clean and healthy transportation systems and infrastructure;