中国各省数字经济对绿色创新效率的非线性影响研究
Research on the Nonlinear Impact of Digital Economy on Green Innovation Efficiency in Chinese Provinces
邓光耀 1张艺迪2
作者信息
- 1. 兰州财经大学 统计与数据科学学院,甘肃 兰州 730020;兰州财经大学 "一带一路"经济研究院,甘肃 兰州 730020
- 2. 兰州财经大学 统计与数据科学学院,甘肃 兰州 730020
- 折叠
摘要
数字经济依托数字信息技术而发展,随着应用深度和覆盖范围的不断拓展,其推动社会各类生产要素转化为数据资源,有效降低了生产成本和生产污染,对中国绿色创新能力的影响日益增加.基于EBM模型的GML指数测算中国各地区绿色创新效率,并使用面板Tobit模型、门槛回归模型和LightGBM模型探究数字经济对绿色创新效率的影响效应.研究发现:数字经济赋能绿色创新效率,中国数字经济与绿色创新效率均在稳定增长.数字经济对绿色创新效率具有非线性效应和单门槛效应.因此,要加强数字经济顶层设计,优化数字产业发展环境,强化数据要素安全,构建合理的数字治理体系.
Abstract
The development of digital economy relies on digital information technology,and with the con-tinuous expansion of its application depth and coverage,it promotes the transformation of various production factors into data resources,effectively reducing production costs and production pollution,and has an in-creasing impact on China's green innovation ability.Based on the GML index of EBM model,this paper cal-culates the green innovation efficiency of various regions in China,and uses panel Tobit model,threshold re-gression model and LightGBM model to explore the impact of digital economy on green innovation effi-ciency.The results show that:the digital economy empowers green innovation efficiency,and both China's digital economy and green innovation efficiency are steadily growing.The digital economy has non-linear ef-fects and single threshold effects on green innovation efficiency.Therefore,it is necessary to strengthen the top-level design of digital economy,optimize the development environment of digital industry,strengthen the security of data elements,and build a reasonable digital governance system.
关键词
数字经济/绿色创新效率/EBM模型/面板Tobit模型/机器学习Key words
digital economy/green innovation efficiency/EBM model/Panel Tobit model/Machine Learn-ing引用本文复制引用
基金项目
国家自然科学基金(2023)(72363021)
甘肃省教育厅双一流科研重点项目(2021)(GSSYLXM-06)
兰州财经大学丝绸之路经济研究院重点科研项目(JYYZ202102)
出版年
2024
NETL
NSTL
万方数据