数字低碳之路：工业机器人与城市工业碳排放

数字低碳之路：工业机器人与城市工业碳排放

Digital Low-carbon Road: Industrial Robots and Urban Industrial Carbon Emissions

《财经研究》2023年49卷第10期 页码：34 - 48 online：2023年10月3日

作者

中：黄赜琳 , 蒋鹏程

英：Huang Zelin, Jiang Pengcheng

作者单位：上海财经大学 财经研究所, 上海 200433

摘要及关键词

摘要：随着人工智能技术与经济社会的深度融合发展，工业机器人已经成为推动经济低碳转型发展的重要驱动力。已有研究主要从劳动力市场视角讨论了工业机器人的经济效应，而文章主要考察了工业机器人对城市工业碳排放的影响。首先，文章构建包含工业机器人和能源投入的理论模型。理论研究表明，工业机器人能够赋能城市工业碳减排。其次，利用中国城市面板数据的实证研究发现工业机器人有效降低城市工业碳排放，推动城市经济向低碳方向发展，且具有长期影响。异质性分析发现，工业机器人能够抑制非资源型城市、数字化水平较高城市、东部以及南方城市的工业碳排放，但对资源型城市、数字化水平较低城市、中西部以及北方城市的影响不显著。机制检验结果表明，在工业机器人发挥城市工业碳减排效应的过程中，绿色技术创新和人机匹配度是重要的作用机制。进一步采用门槛模型发现，随着互联网普及率、人力资本水平和政府科技投入的提升，工业机器人减排效应呈边际效应递增态势，这意味着完善宽带基础设施建设、提高人力资本水平、加大财政科技投入是促进工业机器人减排效应的实现路径。文章的研究为利用人工智能技术实现“双碳”目标，促进经济低碳转型提供了经验证据和政策启示。

关键词：工业机器人；工业碳排放；绿色技术创新；人机匹配度

Summary: China is gradually transforming from a manufacturing power to an industrial power, but it has also caused environmental problems such as high energy consumption and high emissions. The industrial sector has become the main source of carbon emissions. Reducing industrial carbon emissions is a key link in achieving the goals of “carbon peaking” and “carbon neutrality”. With the deep integration and development of artificial intelligence technology and economic society, industrial robots have become an important driving force to promote low-carbon economic transformation and development. The existing research mainly discusses the economic effect of industrial robots from the perspective of labor market, while this paper mainly examines the impact of industrial robots on urban industrial carbon emissions, the mechanism of action, and the boundary conditions for realization. Firstly, this paper constructs a theoretical model including robots, energy factor input, and environmental factors. Theoretical research shows that industrial robots can reduce urban industrial carbon emissions. Secondly, based on China’s urban panel data, this paper uses a variety of econometric models to find that industrial robots can effectively reduce urban industrial carbon emissions, promote low-carbon economic transformation, and have a long-term impact. Heterogeneity analysis finds that industrial robots can inhibit industrial carbon emissions in non-resource-based cities, cities with a higher digitization level, and eastern and southern cities, but have no significant impact on resource-based cities, cities with a lower digitization level, and cities in central, western and northern regions. The mechanism test shows that green technology innovation and human-machine matching are the mechanism of industrial robots to reduce industrial carbon emissions. Further using the threshold model, it is found that with the increase of the Internet penetration rate, human capital level, and government investment in science and technology, the emission reduction effect of industrial robots shows an increasing trend of “marginal effect”. This means that improving broadband infrastructure construction, improving human capital level, and increasing financial investment in science and technology are the realization paths to promote the emission reduction effect of industrial robots. This paper provides empirical evidence and policy implications for using artificial intelligence technology to promote the goal of low-carbon transformation.

Key words:industrial robots; industrial carbon emissions; green technology innovation; human-machine matching

其他信息

DOI：10.16538/j.cnki.jfe.20230714.402

收稿日期：2023-04-20

基金项目：国家哲学社会科学基金面上项目（23BJL031）；上海社科基金一般项目（2021BJL004）

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