大数据战略对电力消费碳排放的影响——基于国家级大数据综合试验区的准自然实验

常皓亮¹　金碚^2,3　薛飞¹

（1. 中国社会科学院大学应用经济学院；2. 中国社会科学院；3. 郑州大学商学院）

　　内容提要：全面实施国家大数据战略是助推高质量发展的重要引擎。本文以国家级大数据综合试验区作为切入点，聚焦研究大数据综合试验区建设的减排效果。基于中国2011—2019年161个地级市的面板数据，以国家级大数据综合试验区作为一项准自然实验，采用双重差分法，考察大数据战略对城市电力消费碳排放的影响及其潜在机制。研究结果表明，国家级大数据综合试验区建设能够有效降低电力消费碳排放水平，该结论在进行一系列稳健性检验后仍然成立；机制检验表明，大数据综合试验区建设主要通过促进技术创新和数字普惠金融发展降低电力消费碳排放水平；异质性分析结果表明，试验区对于资源型城市电力消费碳排放具有更强的影响效应，并且除内蒙古、广东、沈阳外，其余试验区均对电力消费碳排放的降低产生了积极作用。本文的研究结果对于进一步推动大数据战略，促进数字经济高质量发展具有政策参考价值。

　　

　　关键词：大数据；电力消费碳排放；技术创新；数字普惠金融；国家级大数据综合试验区

　　

　　作者简介：常皓亮，中国社会科学院大学应用经济学院博士研究生，北京，102488；金碚，中国社会科学院学部委员，北京，100044；郑州大学商学院院长，郑州，450001；薛飞，中国社会科学院大学应用经济学院博士研究生。

　　

　　基金项目：国家社会科学基金重大研究专项“加快构建中国特色哲学社会科学学科体系、学术体系、话语体系” 之“新时代中国特色经济学基本理论问题研究”（18VXK002）；中国社会科学院学部委员创新工程项目“经济学范式变革与中国经济的创新道路”（2022-2023）

　　

　　引用格式：常皓亮,金碚,薛飞.大数据战略对电力消费碳排放的影响——基于国家级大数据综合试验区的准自然实验[J].经济与管理研究,2023,44(5):93-109.DOI:10.13502/j.cnki.issn1000-7636.2023.05.006.

　　

Impact of Big Data Strategy on Carbon Emissions from Electricity Consumption

—A Quasi-natural Experiment from National Big Data Comprehensive Pilot Area

CHANG Haoliang¹, JIN Bei^2,3, XUE Fei¹

(1. University of Chinese Academy of Social Sciences, Beijing 102488;

2. Chinese Academy of Social Sciences, Beijing 100044;

3. Zhengzhou University, Zhengzhou 450001)

　　

　　Abstract: Entering a new stage of data-driven economic development, China is promoting the construction of national big data comprehensive pilot areas. With the development and application of big data in resources, ecological environment and other fields, its role in the goal of carbon peaking and carbon neutrality is also gradually attracting attention. Previous studies show that the continued integration of data, technology and scenarios in the real economy will promote the transformation of production, living and regulation, thereby demonstrating the potential for energy conservation and emission reduction. However, behind the vigorous development of the experimental zone, the carbon emission caused by the increase in its own electricity demand cannot be ignored. Therefore, this paper considers the construction of national big data comprehensive experimental areas as a quasi-natural experiment, and analyzes the relationship between the construction and the carbon emission of electricity consumption from both theoretical and empirical perspectives.

　　First, this paper examines the impact of the construction of national big data comprehensive pilot areas on carbon emissions from electricity consumption with the difference-in-differences method using the panel data of 161 prefecture-level cities in China from 2011 to 2019, and conducts various methods to test the robustness. Second, it analyzes the transmission path of big data strategy on carbon emissions from electricity consumption, further expanding the research on the impact of the digital economy on carbon emissions. Third, based on the perspectives of resource endowment, innovation factors, and pilot areas, this paper investigates the heterogeneity of big data strategies on carbon emissions from electricity consumption, to gain a deeper understanding of the impact mechanism.

　　The research results show that: (1) The construction of national big data comprehensive pilot areas can significantly reduce the carbon emissions from electricity consumption. This finding is still valid after a series of robustness tests, such as the parallel trend test, the placebo test, and the PSM-DID method. (2) The construction has a negative impact on carbon emissions from electricity consumption by promoting technological innovation and enhancing the development of digital inclusive finance. (3) Most pilot areas have a positive reduction effect. Specifically, compared with non-resource-based cities, the marginal utility of the construction in resource-based cities is greater in reducing carbon emissions from electricity consumption.

　　These findings have important implications for better leveraging the demonstration and leading role of pilot areas and for China’s green and low-carbon development in the new era.

　　Keywords: big data; carbon emission from electricity consumption; technological innovation; digital inclusive finance; national big data comprehensive pilot area