地级市数字经济水平对企业全要素生产率的影响研究——以A股上市企业为例
Research on the Influence of Digital Economy Level of Prefecture-Level Cities on Enterprises’ Total Factor Productivity—Taking A-Share Listed Enterprises as an Example

文章以A股上市公司为样本，综合运用熵权法、LP法、固定效应模型、机制检验模型、工具变量法和双重差分分析模型等，考察数字经济对上市企业全要素生产率的影响。研究表明，数字经济的发展能够显著提高上市企业的生产率。并且通过替换运用主成分分析法的地级市数字经济水平和运用OP、OLS得出的企业全要素生产率水平，研究结果依然成立。同时这种效应在东部城市的企业、国有企业、大型企业中更加明显。数字技术创新和人力资本结构优化是数字经济中提高全要素生产率的重要渠道。大数据试点地区政策可以在提高企业全要素生产率方面发挥政策作用。研究结论为推动数字革命与技术革命深度融合、加快企业数字化转型和产业结构升级提供了重要启示。
Taking A-share listed companies as samples, this paper comprehensively applies entropy weight method, LP method, fixed effect model, mechanism test model, instrumental variable method and double difference analysis model to examine the impact of digital economy on total factor productivity of listed companies. The study shows that the development of digital economy can significantly increase the productivity of listed enterprises. And by replacing the digital economy level of prefecture-level cities using principal component analysis and the total factor productivity level of enterprises derived using OP and OLS, the research results still hold. At the same time this effect is more obvious in enterprises, state-owned enterprises and large enterprises in eastern cities. Digital technology innovation and human capital structure optimization are important channels for increasing total factor productivity in the digital economy. The big data pilot region policy can play a policy role in improving the total factor productivity of enterprises. The findings provide important insights for promoting the deep integration of the digital revolution with the technological revolution, accelerating the digital transformation of enterprises and upgrading the industrial structure.