首页|期刊导航|西安石油大学学报(社会科学版)|国家新一代人工智能创新发展试验区政策能否提升碳生产率?

国家新一代人工智能创新发展试验区政策能否提升碳生产率?OACHSSCD

Can the Policy of the National New-Generation Artificial Intelligence Innovation and Development Pilot Zone Enhance Carbon Productivity?

中文摘要英文摘要

人工智能是驱动能源效率提升和碳排放精准管理,实现"碳达峰、碳中和"目标实现的重要力量.基于2013-2023 年中国31 个省份面板数据,将国家新一代人工智能创新发展试验区作为准自然实验,构建双重差分模型探究人工智能对碳生产率的影响效应以及作用机制.研究发现:(1)人工智能试点政策显著提升了碳生产率,且这一结论经过一系列稳健性检验依旧成立.(2)从机制路径来看,人工智能通过促进创新能力来提升碳生产率;环境规制强度的提高会正向调节人工智能对碳生产率的促进作用.(3)由异质性分析可知,人工智能对碳生产率的促进效果在胡焕庸线东南侧以及高数字化地区更为明显.(4)门槛检验发现,产业结构对碳生产率有单一门槛效应,门槛值为 1.425,当产业结构超过门槛值时,人工智能对碳生产率的影响显著为正.

Artificial intelligence is an important force driving the improvement of energy efficiency and the precise management of carbon emissions,and achieving the goals of"carbon peak and carbon neutrality".Based on panel data from 31 provinces of China from 2013 to 2023,the national new generation artificial intel-ligence innovation and development pilot zones were used as quasi-natural experiments to construct a differ-ence-in-differences model so as to explore the impact effect and mechanism of artificial intelligence on carbon productivity.The study found:(1)The pilot artificial intelligence policy significantly has improved carbon pro-ductivity,and this conclusion remaines valid after a series of robustness tests.(2)From the perspective of the mechanism,artificial intelligence has enhanced carbon productivity by promoting innovation capabilities;an in-crease in the intensity of environmental regulations can positively moderate the promoting effect of artificial in-telligence on carbon productivity.(3)From the heterogeneity analysis,it can be known that the promoting effect of artificial intelligence on carbon productivity is more obvious on the southeast side of the Hu Huanyong Line and in highly digitalized areas.(4)The threshold test reveals that the industrial structure has a single threshold effect on carbon productivity.The threshold value is 1.425.When the industrial structure exceeds this threshold,the impact of artificial intelligence on carbon productivity is significantly positive.

张优智;张宇

西安石油大学 经济管理学院,陕西 西安 710065西安石油大学 经济管理学院,陕西 西安 710065

管理科学

人工智能碳生产率双重差分模型门槛效应

artificial intelligencecarbon productivitydifference-in-differences modelthreshold effect

《西安石油大学学报(社会科学版)》 2026 (4)

71-81,11

陕西省社会科学基金项目"数字经济驱动陕西传统制造业转型升级的机制、效应与政策研究"(2023D044)西安石油大学教育教学改革研究项目"基于'思政引领+AI赋能'的人力资源管理专业人才培养模式创新与实践研究"(JGYB202518)西安石油大学研究生创新与实践能力培养计划资助项目"数实融合对西安先进制造业高质量发展的影响研究"(YCX2523020).

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